Application of the Ecological Flows Tool to complement water planning efforts in the Delta & Sacramento River: multi-species effects analysis and ecological flow criteria

Abstract

Beginning with the launch of the current phase of this project in October 2008 and extending through to its conclusion in 2014, the Ecological Flows Tool (EFT) project has had the goal of improving water planning in the Sacramento River and the San Joaquin-Sacramento Delta. The waters which flow through these two ecoregions are among the most highly regulated anywhere in the world, serving over 20 million people, supporting a $40 billion agriculture industry, and sustaining diverse, although highly altered, ecosystems. Because of a chronic inability to find "balance" in the trade-offs among competing objectives and resource demands, the Delta is universally regarded to be in crisis. A central challenge in managing the Sacramento River and Delta is evaluating how alternative river management scenarios are likely to impact different components of the ecosystem. Our project directly addresses this challenge. Aided by over 70 scientists and managers since the project’s 2004 inception, we have developed an integrated bio-physical tool that characterizes how a suite of focal species are expected to respond to alternative flow, river bank, and gravel management scenarios. EFT interfaces with existing water management tools, and is intended to be used to support the recovery of the Delta and Sacramento River ecosystems that are currently managed primarily to meet human water delivery needs.

<Paragraph 1 of 4 page Executive Summary>

Full text

DRAFT Final Report
Application of EFT to Complement Water Planning for Multiple Species
i | Page
Final Report
Application of the Ecological Flows Tool to
Complement Water Planning Efforts in the
Delta & Sacramento River
Multi-Species Effects Analysis & Ecological Flow Criteria
Prepared for The Sacramento River Program of The Nature Conservancy
Ecosystem Restoration Program
Agreement E0720044

Application of the Ecological Flows Tool
to Complement Water Planning Efforts in
the Delta & Sacramento River
Prepared for:
The Sacramento River
Program of The Nature
Conservancy
Multi-Species Effects Analysis & Ecological Flow
Criteria
Lead Authors:
Clint Alexander, Donald Robinson and Frank Poulsen
Funded by:
California Department
of Fish and Wildlife
Ecosystem Restoration
Program
Agreement No. ERP-07D-P06 - DFG# E0720044
For inquiries on this report, contact:
Ryan Luster
The Nature Conservancy
rluster@tnc.org
1.530.897.6370 (ext. 213)
Suggested Citation:
Alexander, C.A.D., D.C.E. Robinson, F. Poulsen. 2014. Application of
the Ecological Flows Tool to Complement Water Planning Efforts in
the Delta & Sacramento River: Multi-Species effects analysis &
Ecological Flow Criteria. Final Report toThe Nature Conservancy.
Chico, California. 228 p + appendices.
Cover Photo:
Shasta Dam (iStock photo)
© 2014 The Nature Conservancy
No part of this report may be reproduced, stored in a retrieval
system, or transmitted, in any form or by any means,
electronic, mechanical, photocopying, recording, or otherwise,
without prior written permission from The Nature
Conservancy.
ESSA Technologies Ltd.
Vancouver, BC Canada V6H 3H4
www.essa.com

Final Report
Application of EFT to Complement Water Planning for Multiple Species
i | Page
Organization of Report
To facilitate your ability to identify background and findings that are of most interest, this
report is organized as follows:
Chapter 1. Overview – This Chapter describes the vision, history and goals of the project;
its tasks and deliverable products to date. It describes categories of ecological flow needs
assessment and how these needs are tackled by the Ecological Flows Tool.
Chapter 2. Ecological Flow Needs Considered and Methods – This Chapter
summarizes the kinds of management actions that can be evaluated using EFT. It also
describes the species and ecological needs which are considered by EFT, and includes
high level narrative descriptions of the 25 indicators that form Sacramento River and Delta
EFT. The Chapter also provides high level descriptions of each indicator along with where
and when the indicator effects take place. This Chapter also provides a concise explanation
of how each indicator’s results are combined (rolled up) in different ways, to provide outputs
that range from the detailed to high level summaries. In addition to describing various
categories of outputs available from EFT, we provide an explanation of the different
approaches to synthesizing outcomes and comparing results using a weight-of-evidence
approach to develop higher level net effect conclusions. Descriptions of the external models
that EFT leverages (e.g., CALSIM) which provide input to EFT are also provided in this
Chapter (including how these models can be substituted for others as they become
available). The Chapter also describes the methodology involved with using EFT to develop
rule-sets and eco-friendly flow regimes for incorporation into other physical planning
models.
Chapter 3. Recent EFT Applications – This Chapter provides a description of recent
applications of EFT to water operation planning, with particular emphasis on multi-level
results. This includes the first full application of EFT (SacEFT and DeltaEFT) to selected
Bay Delta Conservation Plan alternatives. We include net effect summaries, summaries of
physical change as well as detailed species and indicator results for several water operation
and future climate scenarios. These effects analyses are structured according to defined
comparisons intended to isolate water operation and conveyance effects, as well as
anticipated effects associated with future climate change and human demand. A second
major focus of this Chapter is to unveil results for a pilot study showing how EFT can be
used to develop rule-sets and recommended flow regimes for incorporation into physical
planning models (e.g., in this example, CALSIM). As an initial test of the approach, we
illustrate results of the method as applied to winter Chinook and Delta smelt. A summary of
a previous application of SacEFT to a North-of-the-Delta Offstream Storage investigation is
also provided.

ii | Page
Chapter 4. Where to From Here? – Isolates the biggest lessons learned over more than
10 years of work, and plots a course for the next phase of coupled, multi-species, ecological
flow decision support for the Sacramento River and Delta.
Appendix A – Provides the original backgrounder report that was provided prior to the first
Sacramento River Ecological Flows Tool design workshop. While it is superseded by the
SacEFT Record of Design in Appendix B, this companion document illustrates the
structured workshop and peer review approach taken in the development of SacEFT.
Appendix B – Provides the Record of Design for the Sacramento River Ecological Flows
Tool. A standalone report, this document provides additional detail about the development
and technical implementation of each SacEFT indicator too voluminous for inclusion in the
main body of this report.
Appendix C – Provides the original backgrounder report that was provided prior to the first
Delta Ecological Flows Tool design workshop. While it is superseded by the DeltaEFT
Record of Design in Appendix D, this companion document illustrates the structured
workshop and peer review approach taken in the development of DeltaEFT.
Appendix D – Provides the Record of Design for the Delta Ecological Flows Tool. A
standalone report, this document provides additional detail about the development and
technical implementation of each DeltaEFT indicator too voluminous for inclusion in the
main body of this report.
Appendix E – Provides the software user guide for the Ecological Flows Tool Reader
software.
Appendix F – Isolates and provides the systematic indicator screening & selection criteria
used to guide decisions about what species and habitat indicators to include in EFT.
Appendix G – This Appendix provides details on the default relative suitability thresholds
used to establish EFT's roll-up ratings of good, fair and poor annual performance by
indicator. These suitability thresholds help characterize outputs, are fully configurable, but
are only one type of information provided by EFT.
Appendix H – A comprehensive listing of all EFT input and output locations mapped to
each species and performance indicator.
Appendix I – This Appendix provides a complete list of EFT derived rule-sets and
recommended flow/water temperature regimes for all species and indicators.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
iii | Page
Table of Contents
List of Figures ............................................................................................................................................ iv
List of Tables ............................................................................................................................................ viii
List of Abbreviations, Measurement Units and Fundamental Terms .................................................. xii
Executive Summary ................................................................................................................................. xvi
1 Overview ................................................................................................................................................ 1
1.1 Project History and Goals ............................................................................................................. 3
1.2 Vision - Multiple Ecological Flow Needs ....................................................................................... 5
1.3 Ecological Flow Needs: ‘What’ are they? ..................................................................................... 7
1.4 Summary of Project Tasks & Deliverables ................................................................................... 9
2 Core Methods & Ecological Flow Needs Considered ..................................................................... 17
2.1 Management Actions That Can Be Evaluated Using EFT ......................................................... 19
2.2 Sacramento River Ecoregion Ecological Objectives & Performance Indicators ........................ 21
2.3 Key Attributes of SacEFT Performance Indicators ..................................................................... 34
2.4 San Joaquin-Sacramento Delta Ecoregion Ecological Objectives & Performance
Indicators .................................................................................................................................... 36
2.5 Key Attributes of DeltaEFT Performance Indicators ................................................................... 43
2.6 Coupled Modeling – Hydrologic & Physical Foundations ........................................................... 46
2.7 Categories of Available Outputs ................................................................................................. 54
2.8 Structured Comparisons & EFT Analysis Steps ......................................................................... 69
2.9 Integrating EFT with Systems Operations Models ..................................................................... 75
3 Recent EFT Applications ................................................................................................................... 82
3.1 Overview ..................................................................................................................................... 82
3.2 Effects Analysis Application of SacEFT to North-of-the-Delta Offstream Storage
Investigation ................................................................................................................................ 84
3.3 Effects Analysis Application of EFT to Selected Bay Delta Conservation Plan Scenarios ........ 93
3.4 Pilot Investigation: Incorporating EFT Derived Ecological Flow Criteria to CALSIM ................ 178
4 Where to From Here? ....................................................................................................................... 208
4.1 A New Paradigm: Flexible Ecosystem Priorities ....................................................................... 208
4.2 Other Promising Avenues ......................................................................................................... 214
5 References and Further Reading .................................................................................................... 219
Appendix A: Sacramento River Ecological Flows Tool Backgrounder Report ................................ A-1
Appendix B: Sacramento River Ecological Flows Tool (SacEFT v.2) Record of Design ................ B-1
Appendix C: Delta Ecological Flows Tool Backgrounder Report ...................................................... C-1
Appendix D: The Delta Ecological Flows Tool (DeltaEFT v.1.1) Record of Design.......................... D-1
Appendix E: EFT Reader Software – User’s Guide ..............................................................................E-1
Appendix F: Indicator Screening & Selection Criteria ......................................................................... F-1
Appendix G: Default Relative Suitability Thresholds .......................................................................... G-1
Appendix H: Master Register of EFT Input and Output Locations .................................................... H-1
Appendix I: EFT Derived Flow Needs ..................................................................................................... I-1

iv | Page
List of Figures
Figure 2.1: The two ecoregions of EFT: Sacramento River (SacEFT) and DeltaEFT (DeltaEFT). ......... 18
Figure 2.2: “Four box” conceptual framework for characterizing flow management actions that
can be evaluated using EFT. ................................................................................................. 20
Figure 2.3: Different climate forcing, operational standards, or conveyance features of the
Sacramento River and/or San Joaquin-Sacramento Delta translate into alternate
flow regimes (different colored lines). .................................................................................... 20
Figure 2.4: SacEFT includes the six species groups shown. ................................................................... 21
Figure 2.5: Example SacEFT output report for Fremont cottonwood at a specific cross section. ........... 24
Figure 2.6: Example spawning WUA relationships for winter-run Chinook, fall-run Chinook and
steelhead for three river segments used by SacEFT. ............................................................ 27
Figure 2.7: DeltaEFT includes the seven species and habitat groups shown. ........................................ 37
Figure 2.8: Current EFT hydrologic foundation. ....................................................................................... 47
Figure 2.9. Meander Migration and Bank Erosion Model – example of centerlines for 56 years
for one scenario. ..................................................................................................................... 51
Figure 2.10. Meander Migration and Bank Erosion Model – variable erosion example. ............................ 51
Figure 2.11: Example SacEFT output showing annual results for the Fremont cottonwood
initiation indicator (FC1) across six scenarios.. ...................................................................... 56
Figure 2.12: Annual sorted results and relative suitability thresholds for the SacEFT Fremont
cottonwood initiation (FC1) performance indicator run using historic observed flows
(WY1938-2003). ..................................................................................................................... 58
Figure 2.13: An example of the RS method applied to annual roll-up ratings for four scenario
groups and five indicators. ..................................................................................................... 62
Figure 2.14: An example of the RS method applied to multi-year roll-up ratings for four scenario
groups and five indicators. ..................................................................................................... 62
Figure 2.15: Boxplot of temperature stress for fall-run Chinook (CS10) showing median value by
location for alternative scenarios, including 25th and 75th percentiles (edge of
boxes) as well as tails of extreme values (lines). ................................................................... 65
Figure 2.16: Steelhead rearing habitat (CS2) results for a year rated as favorable. .................................. 66
Figure 2.17: DeltaEFT invasive species deterrence result for a year rated as favorable. ......................... 67
Figure 2.18: An example screen capture from the Annual Spatial report for DS4: Index of risk of
entrainment for Delta smelt, showing the performance at each location. .............................. 68
Figure 2.19: Example flow traces underpinning EFT Ecological Flows criteria and rule-sets.
Individual water year traces are colored based on the indicator’s relative
performance suitability in EFT. ............................................................................................... 75
Figure 2.20: The pilot monthly ecological flow criterion was integrated into CALSIM using
CALSIM’s native WRESL language and integrated with the over 700 existing
WRESL files containing existing CALSIM rules. .................................................................... 79
Figure 2.21: CALSIM operation rules written as WRESL-language statements for minimum flows. ......... 79
Figure 2.22: CALSIM rules as WRESL-statements for maximum flows. ................................................... 80

Final Report
Application of EFT to Complement Water Planning for Multiple Species
v | Page
Figure 2.23: Scenarios were screened based on their ability to meet the ecological flow criteria
(upper left panel), their impact on storage (upper right panel) and exports (lower
panel). .................................................................................................................................... 81
Figure 3.1: Artist’s rendition of the Sites Reservoir location relative to the Sacramento River. ............... 87
Figure 3.2: General map showing proposed (August 2013) North Delta point of diversion and
new conveyance tunnels to State and Federal pumping plants in the South Delta ............... 95
Figure 3.3: Fall-run Chinook spawning habitat (CS1) area under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario. .................................................................. 126
Figure 3.4: Late fall-fun Chinook spawning habitat (CS1) area under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario. .................................................................. 127
Figure 3.5: Spring-run Chinook spawning habitat (CS1) area under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario. .................................................................. 127
Figure 3.6: Fremont cottonwood initiation success (FC1) under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario. .................................................................. 128
Figure 3.7: Median large woody debris input (LWD1) to the river under three BDCP scenarios,
in comparison to the NAA-ELT baseline scenario (upper left panel) and under one
BDCP scenario in comparison to the NAA-LLT baseline scenario (lower left panel). ......... 130
Figure 3.8: Late fall-run Chinook suitable spawning habitat (CS1) area under the NAA-ELT and
NAA-LLT scenarios, compared to the NAA-Current reference case. .................................. 133
Figure 3.9: Spring-run Chinook suitable spawning habitat area (CS1, upper left panel), thermal
egg-to-fry survival (CS3, upper right panel), and juvenile rearing habitat (CS2, lower
left panel) under the NAA-ELT and NAA-LLT scenarios, compared to the NAA-
Current reference case......................................................................................................... 134
Figure 3.10: Green sturgeon egg survival (GS1) under the NAA-ELT and NAA-LLT scenarios
compared to the NAA-Current reference case. .................................................................... 135
Figure 3.11: Median green sturgeon egg survival (GS1) by Water Year type. ........................................ 138
Figure 3.12: Median Fremont cottonwood initiation (FC1) by Water Year type. ...................................... 139
Figure 3.13: Median suitable potential habitat (BASW1) for bank swallows by Water Year type,
showing suitable potential habitat (left panel) and nest inundation/sloughing risk
(right panel). ......................................................................................................................... 140
Figure 3.14: Median large woody debris input (LWD1) to the Sacramento River by Water Year
type. ...................................................................................................................................... 141
Figure 3.15: Late fall-run Chinook smolt weight gain (CS7, upper left panel), smolt predation risk
(CS9, upper right panel), and smolt temperature stress (CS10, lower left panel)
under three BDCP scenarios compared to the NAA-ELT reference case. .......................... 146
Figure 3.16: Composite view of a detailed Excel report created by EFT software, showing details
of smolt weight gain in Yolo Bypass (CS7) under the NAA-ELT scenario in WY1986.
In this year the performance of late fall-run Chinook is driven by the high proportion
of the cohort travelling via the main-stem. ........................................................................... 147
Figure 3.17: Detailed visualization report show locations of smolt weight gain in Yolo Bypass
(CS7) under the NAA-ELT scenario in WY1986. ................................................................. 148
Figure 3.18: Winter-run Chinook smolt weight gain (CS7) under the ESO-LLT scenario compared
to the NAA-ELT reference case (upper left panel). .............................................................. 149

vi | Page
Figure 3.19: Steelhead smolt temperature stress (CS10) effects under three BDCP scenarios
compared to the NAA-ELT reference case (left panel); and for the ESO-LLT
scenario compared to the NAA-LLT reference case (right panel). ...................................... 150
Figure 3.20: Composite view of a detailed Excel report created by EFT software, showing details
of smolt temperature stress (CS10) under the NAA-ELT scenario in WY1980. .................. 151
Figure 3.21: Detailed visualization report show locations of smolt temperature stress (CS10)
under the NAA-ELT scenario in WY1980............................................................................. 152
Figure 3.22: Median proportion of maximum spawning habitat for splittail (SS1) under three
BDCP scenarios (left panel) compared to the NAA-ELT reference case, and showing
annual differences relative to the NAA-ELT baseline scenario (right panel). ...................... 153
Figure 3.23: Median Delta smelt habitat suitability index (DS2) under three BDCP scenarios
relative to NAA-ELT baseline (upper left panel), and the ESO-LLT scenario relative
to the NAA-LLT baseline (lower left panel).. ........................................................................ 154
Figure 3.24: Median longfin smelt abundance index (LS1) under three BDCP scenarios relative to
the NAA-ELT baseline (upper left panel), and ESO-LLT relative to the NAA-LLT
baseline (lower left panel). ................................................................................................. 155
Figure 3.25: Median overbite clam larval suppression (ID2) under three BDCP scenarios relative
to the NAA-ELT baseline (left panel), and showing individual year differences
relative to the ELT baseline (right panel). ............................................................................ 156
Figure 3.26: Median brackish (TW1) and freshwater (TW2) wetland area in the Late Long Term
for ESO-LLT relative to NAA-LLT (upper left and lower left panels, respectively), and
showing individual year differences relative to the LLT base case (upper and lower
right panels). ......................................................................................................................... 157
Figure 3.27: Smolt temperature stress (CS10) in the Early Long Term (ELT, 2030) and Late Long
Term (LLT, 2060) period compared to the NAA-Current reference case for fall-run
Chinook (upper left panel), late fall-run Chinook (upper right panel), winter-run
Chinook (lower left panel), and steelhead (lower right panel). ............................................. 160
Figure 3.28: Median Delta smelt habitat suitability index (DS2) under future climate and demand
relative to the NAA-Current baseline (left panel), showing individual year differences
relative to the baseline scenario (right panel). ..................................................................... 161
Figure 3.29: Median longfin smelt abundance index (LS1) under future climate and demand
relative to the NAA-Current baseline (left panel), showing individual year differences
relative to the baseline (right panel). .................................................................................... 162
Figure 3.30: Median overbite clam larval suppression (ID2) under future climate and demand
relative to the NAA-Current baseline (left pane), showing individual year differences
relative to the baseline (right panel). .................................................................................... 163
Figure 3.31: Median brackish (TW1) and freshwater (TW2) wetland area under future climate and
demand scenarios relative to the NAA-Current baseline (upper left and lower left
panels, respectively), showing individual year differences relative to the baseline
(upper and lower right panels ). ........................................................................................... 164
Figure 3.32: Median proportion of maximum spawning habitat for splittail (SS1) by Water Year
type. ...................................................................................................................................... 166
Figure 3.33: Median habitat suitability index for Delta smelt (DS2, left panel) and entrainment risk
for Delta smelt (DS4, right panel) by Water Year type. ........................................................ 167
Figure 3.34: Median abundance index for longfin smelt (LS1) by Water Year type. ................................ 168

Final Report
Application of EFT to Complement Water Planning for Multiple Species
v i i | Page
Figure 3.35: Median Brazilian waterweed suppression (ID1, upper left panel), overbite clam larval
suppression (ID2, upper right panel), and Asiatic clam larval suppression (ID3, lower
left panel) by Water Year type. ............................................................................................. 169
Figure 3.36: Fall-run Chinook spawning habitat (CS1) area for historical and preferred scenarios
relative to the DRR 2011 reference case scenario. ............................................................. 193
Figure 3.37: Late fall-run Chinook suitable spawning habitat (CS1, left panel) and suitable rearing
habitat (CS2, right panel) for both DRR simulations relative to the historical scenario. ...... 194
Figure 3.38: Spring-run Chinook spawning habitat (CS1, left panel) and juvenile rearing habitat
(CS2, right panel) for both DRR simulations relative to the historical scenario. .................. 195
Figure 3.39: Suitable spawning habitat for steelhead (CS1) for both DRR simulations relative to
the historical scenario........................................................................................................... 196
Figure 3.40: Median nest inundation/sloughing risk (BASW2) for bank swallow under the pilot
EFT rule-set relative to reference case and historical scenarios (left panel), showing
individual year differences relative to base case scenario (right panel). ............................. 197
Figure 3.41: Median Fremont cottonwood initiation success (FC1) for the pilot EFT rule-set
relative to the reference case and the historical (1943-2004) scenario. .............................. 198
Figure 3.42: Median historical habitat suitability index (DS2) relative to reference and preferred
scenarios. ............................................................................................................................. 201
Figure 3.43: Median Delta smelt entrainment risk (DS4) relative to the DRR 2011 reference case
scenario (left panel), showing individual year difference relative to baseline scenario
(right panel). ......................................................................................................................... 204
Figure 3.44: Example DS4 results for the same sample year before/after EFT rule-set.. ....................... 205
Figure 4.1: Hypothetical example of state-dependent priorities. ............................................................ 211
Figure 4.2: Hypothetical trade-off example for two different species objectives. ................................... 212
Figure 4.3: Recommended multiple objective, state-dependent ecological flow optimization
system (lower panel) vs. approach used in pilot study (upper panel). ................................. 213
Figure F.1: Focal habitat, species filtering and screening criteria (vetting process) for EFT. ................. F-2

v i i i | Page
List of Tables
Table 1.1: Common methodologies for determining environmental flows (Alexander et al. 2013,
and references therein). ........................................................................................................... 8
Table 1.2: Project tasks and associated deliverables. ............................................................................ 10
Table 2.1: Summary of SacEFT ecological objectives for each focal species and their
associated performance indicators. ....................................................................................... 22
Table 2.2: Relative importance of each EFT salmon performance indicator by run type. Details
on Delta performance indicators are provided below. ............................................................ 33
Table 2.3: SacEFT performance indicators (SacEFT Ecoregion) – units, overall calculation,
weighting and roll-up attributes. ............................................................................................. 34
Table 2.4: Summary of timing information relevant to the SacEFT focal species. ................................. 36
Table 2.5: Summary of DeltaEFT ecological objectives for each focal species and their
associated performance indicators. ....................................................................................... 38
Table 2.6: DeltaEFT performance indicators (Delta Ecoregion) – units, overall calculation,
weighting and roll-up attributes. ............................................................................................. 44
Table 2.7: Summary of timing information relevant to the DeltaEFT focal species. ............................... 46
Table 2.8: Location of TUGS simulation segments and amount of supplementary gravel added
in the case of the “Gravel Injection” scenario (not used in this report). ................................. 53
Table 2.9: Overview of all EFT outputs. .................................................................................................. 55
Table 2.10: Summary of the default relative suitability (RS) thresholds and associated reference
time periods used to rate EFT indicators as favorable, fair, or poor. ..................................... 57
Table 2.11: EFT effects analysis – high-level roll-up using the relative suitability (RS) method. ............. 61
Table 2.12: EFT effects analysis – multi-year analysis using the Effect Size (ES) synthesis
method. .................................................................................................................................. 64
Table 2.13: An example showing the result of the Net Effect Score (NES) analysis applied to one
of a suite of BDCP case studies. ............................................................................................ 74
Table 2.14: Initial EFT Ecological Flow rules for winter-run Chinook. ....................................................... 76
Table 2.15: Initial EFT Ecological Flow rules for Delta smelt entrainment risk. ........................................ 77
Table 2.16: Summary of ecological flow criteria for protection of Sacramento River bank swallow
habitat potential. WYT = Water Year Type. ........................................................................... 78
Table 2.17: CALSIM screening models. Five CALSIM models of increasing complexity were
used to screen different implementations of the monthly ecological flow criteria. ................. 81
Table 3.1: Interim Plan Formulation Alternatives – NODOS Investigation. ............................................ 86
Table 3.2: Operation and conveyance effects are shown for different NODOS scenarios in the
Sacramento River ecoregion using the change in the percentage of favorable years
relative to existing conditions (RS method). ........................................................................... 89
Table 3.3: Operation and conveyance effects are shown for different NODOS scenarios in the
Sacramento River ecoregion using the change in the percentage of favorable years
relative to the No Action Alternative (RS method). ................................................................ 90
Table 3.4: Rank order performance of interim NODOS alternatives by SacEFT focal species or
group. ..................................................................................................................................... 92

Final Report
Application of EFT to Complement Water Planning for Multiple Species
ix | Page
Table 3.5: Summary of BDCP physical restoration actions. ................................................................... 96
Table 3.6: Summary of reference case (NAA: No Action Alternative) scenario and three BDCP
action alternatives (ESO: Expected Starting Operations; LOS: Low Output Spring;
HOS: High Output Spring). ..................................................................................................... 98
Table 3.7: Flow values at Keswick and Hamilton City are shown for selected BDCP scenarios
at the Early Long Term (ELT) future climate period. ............................................................ 101
Table 3.8: Flow values at Keswick and Hamilton City are shown for selected BDCP scenarios
at the Late Long Term (LLT) future climate period. ............................................................. 102
Table 3.9: Flow values at Keswick and Hamilton City are shown for three future climate and
demand scenarios. ............................................................................................................... 103
Table 3.10: Excess Cumulative Streampower at Hamilton City (Cumulative Excess Streampower
is defined as the sum of flows above a threshold of 425 cms). ........................................... 104
Table 3.11: Water temperature values (degrees C) at Keswick and Hamilton City are shown for
three future climate and demand scenarios. ........................................................................ 105
Table 3.12: Flow values at Mallard Island and Old and Middle River are shown for selected
BDCP scenarios at the Early Long Term (ELT) future climate period. ................................ 106
Table 3.13: Flow values at Mallard Island and Old and Middle River are shown for selected
BDCP scenarios at the Late Long Term (LLT) future climate period. .................................. 107
Table 3.14: Flow values at Mallard Island and Old and Middle River are shown for three future
climate and demand scenarios. ........................................................................................... 108
Table 3.15: Water temperature values (degrees C) at Port Chicago and Terminous are shown
for three future Climate and Demand scenarios. ................................................................. 109
Table 3.16: EC (a proxy for salinity) values at Collinsville and Port Chicago are shown for
selected BDCP scenarios at the Early Long Term (ELT) future climate period. .................. 111
Table 3.17: EC (a proxy for salinity) values at Collinsville and Port Chicago are shown for
selected BDCP scenarios at the Late Long Term (LLT) future climate period. ................... 112
Table 3.18: EC (a proxy for salinity) values at Collinsville and Port Chicago are shown for three
future Climate and Demand scenarios. ................................................................................ 113
Table 3.19: Operation and conveyance effects are shown for selected BDCP scenarios in the
Sacramento River ecoregion at the Early Long Term (ELT) future climate period
using the change in the percentage of favorable years reported for each indicator
(RS method). ........................................................................................................................ 114
Table 3.20: Operation and conveyance effects are shown for selected BDCP scenarios in the
Sacramento River ecoregion at the Late Long Term (LLT) future climate period
using the change in the percentage of favorable years reported for each indicator
(RS method). ........................................................................................................................ 115
Table 3.21: Climate and demand effects are shown for selected No Action Alternative (NAA)
scenario at two future climate periods in the Sacramento River ecoregion using the
change in the percentage of favorable years reported for each indicator (RS
method). ............................................................................................................................... 117
Table 3.22: Operation and conveyance effects are shown for selected BDCP scenarios in the
Delta ecoregion at the Early Long Term (ELT) future climate period using the
change in the percentage of favorable years reported for each indicator (RS
method). ............................................................................................................................... 118

x | Page
Table 3.23: Operation and conveyance effects are shown for selected BDCP scenarios in the
Delta ecoregion at the Late Long Term (LLT) future climate period using the change
in the percentage of favorable years reported for each indicator (RS method). .................. 119
Table 3.24: Climate and demand effects are shown for selected No Action Alternative (NAA)
scenario at two future climate periods in the Delta ecoregion using the change in the
percentage of favorable years reported for each indicator (RS method). ............................ 120
Table 3.25: Operation and conveyance effect sizes are shown for selected BDCP scenarios at
the Early Long Term (ELT) future climate period using the median difference Effect
Size (ES) method (preserving the native units of each indicator). ....................................... 122
Table 3.26: Operation and conveyance effect sizes are shown for selected BDCP scenarios at
the Late Long Term (LLT) future climate period using the median difference Effect
Size (ES) method (preserving the native units of each indicator). ....................................... 124
Table 3.27: Climate and demand effect sizes are shown for the No Action Alternative (NAA)
scenario at three future climate periods using the median difference Effect Size (ES)
method (preserving the native units of each indicator). ....................................................... 131
Table 3.28: Summary of Water Year patterns observed for salmonid indicators from the
Sacramento River ecoregion. ............................................................................................... 136
Table 3.29: Operation and conveyance sizes are shown for selected BDCP scenarios at the
Early Long Term (ELT) future climate period using the median difference Effect Size
(ES) method (preserving the native units of each indicator). ............................................... 142
Table 3.30: Operation and conveyance sizes are shown for selected BDCP scenarios at the
Late Long Term (LLT) future climate period using the median difference Effect Size
(ES) method (preserving the native units of each indicator). ............................................... 144
Table 3.31: Climate and demand effect sizes are shown for the No Action Alternative (NAA)
scenario at three future climate periods using the median difference Effect Size (ES)
method, preserving the native units of each indicator. ......................................................... 158
Table 3.32: Summary of Water Year patterns observed for salmonid indicators from the San
Joaquin-Delta ecoregion. ..................................................................................................... 165
Table 3.33: Summary of Project vs Climate/Demand effects for Sacramento River and Delta
ecoregion, as measured by the RS difference. .................................................................... 172
Table 3.34: Summary of Project vs Climate/Demand effects for Sacramento River and Delta
ecoregion, as measured by the ES method. ........................................................................ 173
Table 3.35: Overall weight of evidence and assessment of net effects by species, Sacramento
River Ecoregion and Delta Ecoregion. ................................................................................. 174
Table 3.36: Overall summary of "winners and losers" for the selected BDCP alternatives. ................... 176
Table 3.37: Summary of conditions used for the reference case ecological flow scenario and the
modified version including pilot study rule-sets for winter-run Chinook and Delta
smelt. .................................................................................................................................... 181
Table 3.38: Flow at Keswick and Hamilton City is shown for the reference case, pilot study and
historical scenarios with percentage differences shown next to absolute flows. ................. 184
Table 3.39: Temperature (degrees C) at Keswick is shown for the reference case, pilot study
and historical scenarios with percentage differences shown next to absolute
temperatures. ....................................................................................................................... 185

Final Report
Application of EFT to Complement Water Planning for Multiple Species
xi | Page
Table 3.40: Flow values at Mallard Island and Old and Middle River are shown for the reference
case and pilot EFT rule-set with percentage differences shown next to absolute
flows. .................................................................................................................................... 186
Table 3.41: Salinity (measured as EC) values at Collinsville and Port Pittsburg are shown for the
reference case, pilot study and historical scenarios with percentage differences
shown below the absolute EC. ............................................................................................. 187
Table 3.42: Ecological flow effects are shown for selected pilot study and historical scenarios in
the Sacramento River ecoregion, using the change in the percentage of favorable
years reported for each indicator (RS method). ................................................................... 188
Table 3.43: Ecological flow effects are shown for selected pilot study and historical scenarios in
the Delta ecoregion, using the change in the percentage of favorable years reported
for each indicator (RS method). ........................................................................................... 189
Table 3.44: Pilot study, historical and reference case flow effect sizes are shown for using the
median difference Effect Size (ES) method (preserving the native units of each
indicator). .............................................................................................................................. 191
Table 3.45: Pilot study and historical flow effect sizes are shown for the median difference Effect
Size (ES) method (preserving the native units of each indicator). ....................................... 199
Table 3.46: Summary of pilot study and historical effects for Sacramento River and Delta
ecoregion, as measured by the RS (left) and ES (right) methods. ...................................... 203
Table 3.47: Overall weight of evidence and assessment of net effects by species, Sacramento
River Ecoregion and Delta Ecoregion. Refer to legend below the table. ............................. 206
Table F.1: Classification concepts employed for the evaluation of EFT performance indicators. ......... F-8

Final Report
Application of EFT to Complement Water Planning for Multiple Species
x i i | Page
List of Abbreviations, Measurement Units and
Fundamental Terms
Abbreviations
BA
Biological Assessment
BASW
Bank Swallow
BDCP
Bay Delta Conservation Plan
BO
Biological Opinion
CALSIM
California's monthly hydrosystem planning tool
CDEC
California Data Exchange Center
CEQA
California Environmental Quality Act
CRSS
Colorado River Simulation System
CS
Chinook salmon
CVP
Central Valley Project (California)
Delta
San Joaquin-Sacramento Delta
DeltaEFT
Delta Ecological Flows Tool
DEM
Digital Elevation Model
DFG
California Department of Fish and Game
DRERIP
Delta Regional Ecosystem Restoration Implementation Plan
DRR
Delivery Reliability Report
DS
Delta smelt
DSM2
(San Francisco) Delta Simulation Model version 2 (California)
DWR
California Department of Water Resources
EBC
Existing Biological Condition
EC
Electroconductivity
EFT
Ecological Flows Tool (includes SacEFT for the Sacramento River, and
DeltaEFT for the Delta)
EHW
Extreme High Water
EIS/R
Environmental Impact Study/Report
ELT
Early Long Term (2025)
ERP
Ecosystem Restoration Program
ESO
Expected Starting Operations
FC
Fremont Cottonwood
GCID
Glenn-Colusa Irrigation District
GIS
Geographic Information System
GS
Green sturgeon
HEC-5Q
Flood control and conservation systems simulation model
HEC-RAS
Hydrologic Engineering Center River Analysis System
HOS
High Output Scenario
ICIF
ICF International
ID
Invasive deterrence
IFIM
Instream Flow Incremental Methodology
IHA
Index of Hydrologic Alteration

Final Report
Application of EFT to Complement Water Planning for Multiple Species
x i i i | Page
IMF
Instream Minimum Flow
LLT
Late Long Term (2060)
LOS
Low Output Scenario
LS
Longfin smelt
LWD
Large Woody Debris
MTL
Mean Tide Level
NAA
No Action Alternative
NEPA
National Environmental Policy Act
NMFS
National Marine Fisheries Service
NMFS BO
National Marine Fisheries Service Biological Opinion
NOAA
National Oceanic and Atmospheric Administration
NODOS
North-of-the-Delta Offstream Storage
OCAP
Operations Criteria and Plan
PHABSIM
Physical Habitat Simulation
PI
Performance Indicator
PPIC
Public Policy Institute of California
PTM
Particle Tracking Model
RKI
River Kilometer Index
RM
River mile
ROA
Restoration Opportunity Area
RPA
Reasonable and Prudent Alternative
SacEFT
Sacramento River Ecological Flows Tool
SAIC
Science Applications International Corporation
SLWRI
Shasta Lake Water Resources Investigation
SRWQM
Sacramento River Water Quality Model
SS
Splittail
SWP
State Water Project (California)
SWRCB
State Water Resources Control Board
TNC
The Nature Conservancy
TUGS
The Unified Gravel-Sand sediment transport model
TW
Tidal wetlands
TXFR
Transfer
USBR
United States Bureau of Reclamation
USFWS
United States Fish and Wildlife Service
USFWS BO
United States Fish and Wildlife Service Biological Opinion
USGS
United States Geological Survey
USRDOM
United States Bureau of Reclamation Daily Operations Model (Sacramento
River, California)
VEC
Valued Ecosystem Component
WRESL
Water Resources Simulation Language (used in CALSIM)
WUA
Weighted Usable Area
WY
Water Year
WYT
Water Year Type
X2
Distance (km) from the Golden Gate Bridge to the location of the low salinity
zone, defined as 2‰ bottom salinity

x i v | Page
Measurement Units
%
Percent (a fraction of one hundred)
‰
Permille (a fraction of one thousand)
cfs
cubic feet per second
cm
centimeter
ft
feet (ft2 = square feet)
ha
hectare
kcfs
thousand cubic feet per second
km
kilometer
m
meter
MAF
million acre-feet
mm
millimeter
Fundamental Terms and Concepts
Indicator
Throughout this report, the word "indicator" is used in a general sense as
it commonly is in applied science, without specific reference to how
different authors occasionally decide to customize meanings of this
(plastic) word. In this report, an "indicator" is analogous to a
"performance indicator", or "metric", or "valued ecosystem component"
(VEC). For our purposes, these words refer synonymously to any
element of the environment that has ecological, economic, social or
cultural significance. Subtleties and nuances as to whether an indicator
"suggests, gets close to, approximates" but does not provide an
objective "measure" are easily resolved by reviewing the actual definition
for the indicator (or performance indicator, etc.). All of these terms are
used to answer the question, 'how do I know' whether an action, or some
fundamental natural driving conditions in the environment are causing
things (that have value) to get better, worse or stay the same. The lack of
a distinction between an indicator, or a metric is actually useful as it
opens up more options as to what is an acceptable way to assess 'how
do I know'. Decision makers, stakeholders, and members of the general
public can make judgments and decisions with "indicators" just as well as
"metrics" so long as the terms are clearly defined and logically linked to
something of value.
Performance
indicator
Metric
Valued Ecosystem
Component (VEC)
Performance
measure
EFT baseline
simulation
An EFT baseline simulation was used for some indicators to inform
decisions about relative suitability thresholds (see Section 2.7.2 for
details). EFT baseline simulations are selected to maximize the range of
water year types and year to year variation in flow conditions based on
available data. Because of the requirement for long-term, high-resolution
datasets (both temporal and spatially), this typically necessitated
selection of the available long-term historical record. Historical data
includes modified, regulated, artificial flows following construction of
major dams, diversions and pumping plants. For some indicators (when
the historic record was short), the EFT baseline combined the available
historic data with simulated no action or reference case data. See
Section 2.7.2.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
xv | Page
Historical flows
The measured empirical flows that occurred during the selected period of
record (for our purposes, typically some continuous sequence of years
within 1939-2002). These flows often include a shifting mixture of
modified, regulated, artificial (potentially "degraded") flows following
construction and operation of dams, diversions, conveyance structures
and pumping plants. Shifting climate change effects on precipitation and
other hydrologic processes are also embedded. When the time series is
long enough, they will also include a range of water year types and
related flow variations that even though regulated, still manage to "show
through" in the historic dataset.
Historical flows  natural / pristine / unregulated / unmodified /
unimpaired flows.
Natural flows
Natural flows represent the pristine, unmodified, unregulated, unaltered
flows that would occur in the absence of any human presence,
infrastructure, modifications, hydrosystem operations, water withdrawals
and related land-use changes (e.g., forestry, agriculture). In this report,
this is merely a theoretical concept. We do not use natural flows in our
simulations (because they are not available).
Unimpaired flows
Reverse engineered flows found by attempting to remove the effects of
reservoirs and diversions on existing hydrology time-series. These flows
are thought of as a proxy for natural flows. Challenges with these
estimates are manifold, and include absence of the effects of levees,
channelization 'improvements', wetland storage and related evaporation
processes, forest practices, groundwater interactions, etc. Unimpaired
flow estimates are typically not performed for a wide range of locations,
are often monthly in temporal resolution, and typically rely on volume
correlations, precipitation correlations, subbasin to subbasin
extrapolations and other techniques that produce unquantifiable errors.
Reference case
scenario
Represents a chosen point of comparison, or baseline, that embeds any
number of assumptions about the level of human development, climate
change, and baseline system operations.
Study scenario
Represents an action scenario that contains alternative assumptions
about any one or more of the level of human development, climate, and
system operations. Depending on the chosen reference case scenario,
the chosen study scenario can be used to isolate a specific effect, such
as a system operation and conveyance change or a change in expected
future climate (or both).

x v i | Page
Executive Summary
The Need
Beginning with the launch of the current phase of this project in October 2008 and
extending through to its conclusion in 2014, the Ecological Flows Tool (EFT) project has
had the goal of improving water planning in the Sacramento River and the San Joaquin-
Sacramento Delta. The waters which flow through these two ecoregions are among the
most highly regulated anywhere in the world, serving over 20 million people, supporting a
$40 billion agriculture industry, and sustaining diverse, although highly altered, ecosystems.
Because of a chronic inability to find "balance" in the trade-offs among competing objectives
and resource demands, the Delta is universally regarded to be in crisis. A central challenge
in managing the Sacramento River and Delta is evaluating how alternative river
management scenarios are likely to impact different components of the ecosystem. Our
project directly addresses this challenge. Aided by over 70 scientists and managers since
the project’s 2004 inception, we have developed an integrated bio-physical tool that
characterizes how a suite of focal species are expected to respond to alternative flow, river
bank, and gravel management scenarios. EFT interfaces with existing water management
tools, and is intended to be used to support the recovery of the Delta and Sacramento River
ecosystems that are currently managed primarily to meet human water delivery needs.
An important challenge that has faced water managers has been the gap in scientifically
credible, representative, flow-based ecological models which can be linked to appropriate
physical hydrological models at a daily (or finer) resolution and at biologically relevant
locations. EFT has helped to fill this gap through the development of submodel algorithms
which simulate the physical needs of 13 representative focal species (and habitats) across
the Sacramento River and Delta ecoregions. The peer-reviewed species submodels are
made up of 25 key life-history indicators, each of which is driven by relevant measures of
flow, water temperature, channel migration, salinity and/or stage at a daily timescale. In
addition to coupling multiple ecological indicators to the physical inputs simulated by a
standard suite of hydrological tools for evaluating operations and conveyance alternatives
(CALSIM, SRWQM, DSM2 and their numerous components), EFT is linked to models of
channel migration, soil erosion and sediment transport. This enables evaluations of the
potential benefits not only of flow modifcation, but also of riprap removal and gravel
augmentation.
By design, the development of each EFT indicator is based on a logical progression of
steps that begins with the development of cause-effect conceptual models which link the
physical regime to representative life-history stages of the focal species. Based on the
implementation of these models, it is possible in a second step to identify flow management
regimes that best meet critical needs of specific life-history stages. Prior to the creation of
the EFT model and software, much of the knowledge related to focal species and their
needs was isolated in reports, papers and disconnected models and tools that were difficult
to access. EFT provides an integrated framework that can synthesize a very wide range of
ecological information to allow far more comprehensive consideration of environmental

Final Report
Application of EFT to Complement Water Planning for Multiple Species
x v i i | Page
needs than was previously possible. This level of synthesis and integration makes it
possible to identify and address trade-offs among multiple focal species.
The outputs created by EFT are varied to meet the needs of different users. For research
biologists familiar with the physical needs and temporal patterns of each focal species’ life-
history, daily and location specific graphs can be produced for any flow scenario and year,
showing how each indicator and its driving physical processes vary by location and date.
This allows users with specialized knowledge to evaluate model behavior and predictions at
the finest scale. Other animated data visualizations are included for Delta species and
performance indicators. For system managers and operators, a synthesis of detailed results
is provided through a simple suitability rating system (Good/Fair/Poor “traffic light”
assessments). These can be visualized by year or can be combined ("rolled up") even
further by pooling years, for a very broad comparison of relative performance of alternative
scenarios.
EFT Applications
The demand for and value of the Ecological Flows Tool is reflected in its use in several
major investigations in the last few years. These investigations began with the use of the
Sacramento River (SacEFT) branch of the decision analysis tool in 2011, to evaluate
relative ecological effects of several alternative North-of-the-Delta Offstream Storage
(NODOS) scenarios. The results of that analysis were considered in the interim joint
environmental impact study/report (EIS/R) and revealed mixed impacts, depending on
species and indicators. Most recently, we applied the full EFT model to selected Bay Delta
Conservation Plan (BDCP) alternatives (a focus of Chapter 3). The analysis of BDCP
scenarios included scenarios for expected starting operations (ESO), low output (LOS), and
high output (HOS), as well as for climate change. Prior to the full EFT analysis of BDCP
alternatives, a subset of focal species models (Sacramento River salmonids and green
sturgeon) were used as part of the set of tools brought to bear on the BDCP EIS/R effects
anlaysis. In addition to these three analyses, a prototype version of SacEFT (previous
project phase) was used to study some of the early alternatives being considered as part of
the Shasta Lake Resource Investigation. In all, EFT has demonstrated its ability to
incorporate physical inputs simulated by a widely-used suite of planning tools and to provide
defensible ecological outputs which have been used as part of the decision-making process
for each investigation.
EFT analyses of the BDCP alternatives show that overall, the LOS BDCP alternative is
preferable for species completing life-history stages in the Sacramento River (especially fall-
run Chinook, late fall-run Chinook and spring-run Chinook) while the HOS BDCP alternative
is preferable for San Joaquin-Delta species (especially longfin smelt and, to a lesser
degree, Delta smelt). Fall-run Chinook, late fall-run Chinook and splittail do better under all
BDCP alternatives considered ("winners"), while green sturgeon, deterence of invasives,
and brackish wetland habitats are expected to experience deteriorating conditions. Spring-
run Chinook are expected to do the most poorly under ESO and HOS alternatives in terms
of spawning habitat, egg-to-fry survival, and redd dewatering. In general, juvenile stranding
losses increase, particularly for winter-run Chinook. Delta temperature stress on winter-run
Chinook also increases over all Early Long Term (ELT) alternatives. Likewise, Delta

x v i i i | Page
temperature stress is also elevated over all ELT alternatives for steelhead. While LOS
ecosystem benefits are superior for species in the Sacramento River, results from HOS are
generally very similar. The various trade-offs noted, the HOS alternative is likely the most
preferable in terms of delivering ecological benefits. EFT results suggest the HOS is more
likely to benefit Delta smelt and the LOS is predicted to be detrimental to longin smelt.
With a few exceptions, the climate change signal and effects in the BDCP study generally
dwarfed the operational alternatives considered, especially in the Late Long Term period
(LLT) (2065). Even though compensation was not the general outcome, the BDCP
alternatives do have the potential to provide some offsetting benefits to help cope with
climate change effects. In particular, spawning habitat is improved by the conveyance and
operations in BDCP alternatives for fall-run Chinook and spring-run Chinook (LOS
alternative only). Delta rearing conditions are improved by notching of the Fremont Weir
associated with the ESO, LOS and HOS BDCP alternatives, offsetting losses that are
otherwise expected for late fall-run, winter-run and, to a lesser degree, spring-run Chinook.
Spring-run Chinook also receive compensatory offsets of otherwise detrimental climate
change effects from the LOS scenario, in terms of reductions to redd dewatering losses and
improved Sacramento River rearing conditions. A caveat with these improvements lies in
the relative benefit of the flow mediated improvements versus the detrimental effects of
warming spawning, rearing and Delta water temperatures.
Analyses of the EFT BDCP scenarios – all of which include changes in future climate and
sea level – highlight the need for greater focus on efforts to mitigate for climate change
itself. The magnitude of climate effects in the BDCP analyses shows the inadequacy of
simply comparing whether certain operations are better or worse relative to a progressively
deteriorating baseline, meanwhile ignoring the downward trend of the baseline itself.
Studies which ignore such changes to the baseline divert attention from the cumulative total
change in ecological conditions and can mask what can often be striking differences
between historic operations and those proposed. Use of a historical reference case was
recommended by the Delta Science Panel in its review of BDCP, even though the approach
is unwelcome by some who feel that use of a historical record is a flawed reference with
numerous shifts in operational standards and climate. The counterpoint to this critque is that
the use of a historical reference case enables the study of the level of cumulative change,
regardless of whether it is produced by climate change, changes in operations and
conveyance, or increasing human water demand.
During the initial development of EFT’s conceptual models and algorithms, communication
between the physical driving models and EFT was completely unidirectional. The hydrologic
models (CALSIM, DSM2 and related tools) provided input to EFT, which in turn was run to
create multi-species ecological effects output. As we gained familiarity with the hydrologic
models, it became apparent that the ability of EFT to simulate positive ecological outcomes
could be harnessed to improve the rule-sets used in the physical models themselves. To
test this ability, we conducted an initial pilot study using only a few of the 25 EFT indicators
(for winter-run Chinook and Delta smelt) where analysis of EFT flow traces and conceptual
models were used to create new rules for CALSIM that attempted to improve outcomes for
these two focal species.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
x i x | Page
The initial pilot investigation demonstrated that the operation of the California water system
can be changed to make timing of releases from Shasta Dam more beneficial to selected
species without adverse consequences on storage and water exports. However, it also
highlighted the inherent trade-offs between species and life-stages and how applying the
same rule-set for a given water year type every year actually constrains options and
contributes to the inability to adequately balance trade-offs.
Where To From Here?
There is a pressing need to develop greater awareness of the value of flexibility to manage
ecosystem trade-offs over time within and among objectives. The detailed applications of
EFT in Chapter 3 crystalize the fact that it is impossible to achieve all ecosystem objectives
– let alone the co-equal goals of meeting human, agricultural and environmental needs –
each and every year. There are plain, irreconcilable and ceaseless trade-offs that must be
tracked and confronted, with winners and losers in different years depending on hydrologic
conditions and priorities. These trade-offs do not occur because of a failure to create clever
enough models that magically find the optimal solution; rather, an optimal solution does not
exist. In Chapter 4 we describe a paradigm shift involving seeing balance as a condition
which does not involve the same species or objectives losing (or winning) unnecessarily
often. A key element is state-dependent priorities instead of one-size-fits-all water year
rules. Under state-dependent priorities, flows are optimized for different species according
to the recurrence interval necessary to support healthy population conditions along with
ongoing tracking of the recent history of conditions and related ecosystem outcomes.
The further improvement of interaction between EFT and the hydrologic models is the
current “leading edge” of inquiry for the EFT model. Implementing the new paradigm will
require extending the modeling system by adding the capability to perform dynamic, state-
dependent, multi-objective optimization with highly parallel simulations. This will enable the
exploration of a much broader solution-space for multiple ecological criteria. An important
aspect of this ongoing research is the application of ecosystem and water management
rules which vary ("on", "off") according to the recent history of hydrologic conditions and the
“most needy” ecological indicators.
Human communities, agricultural users and the ecosystems of the Sacramento River and
San Joaquin-Delta are all facing very pressing challenges. EFT represents a large
investment in the synthesis and integration of a vast body of knowledge and tools to
respond to these challenges. It is a successful and rare example of a coupled, interacting
model of operations, hydrodynamics, and multi-species ecosystem and geomorphic
responses between the linked Sacramento River and Delta ecoregions; the kind of
approach envisioned by the CALFED Science Advisory Panel in 2008, and subsequently by
the Delta Science Council and a variety of other cross-disciplinary researchers (e.g., PPIC,
UC Davis).
More than ever, there is great value and potential in the development and application of
integrative modeling tools. EFT provides a robust framework for the joint collaborative work
of experts and resource managers to come together to explore, develop, test and improve
solutions to California's water management problems. Scientific uncertainties, coupled with

xx | Page
the time required for iterative learning, will mean that the development of ecological flow
recommendations will take many years and undergo periods of surprise and change. With
its emphasis on specific cause-effect linkages based on functional flow, EFT provides a
solid framework that remains open to testing, enhancement and adaptation over time.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 | Page
1 Overview
This report presents results from the multi-year Ecological Flows Tool project (Project)
whose goal was to provide a more complete understanding of multi-species’ flow regime
needs and how water management operations across the San Joaquin-Sacramento Delta
and the Sacramento River can better meet these needs.
With the aid of over 70 scientists and managers since the Project’s inception in 2004, the
Ecological Flows Tool (EFT) team was amongst the first to quantify how specific
components of the Sacramento River and San Joaquin-Sacramento Delta flow regimes can
be "specialized" to promote key ecosystem functions in support of smarter, more eco-
friendly flow management (TNC et al. 2008). Ecological flow management is widely
recognized as one important tool toward promoting the resilience and recovery of native
species. Many river-dependent plants and animals are strongly influenced by and have
adapted to a river’s natural variation in flow, and many fish and riparian species possess
traits that allow them to tolerate or exploit certain flow conditions. While not the only
stressor, the alteration of river flow regimes and related habitat losses associated with dam,
diversion, and other water supply operations is one of the leading causes of declines in
imperiled aquatic ecosystems (Arthington et al. 1991, 2006; Richter et al. 1996, 1997;
Stanford et al. 1996; Poff et al. 1997; IFC 2002; Postel and Richter 2003; Tharme 2003;
Petts 2009; Fleenor et al. 2010; Carlisle et al. 2010; Poff and Zimmerman 2010; Poff et al.
2010; National Research Council 2012; Hanak et al. 2013).
Quantifying the critical features of an ecologically beneficial flow regime for multiple aquatic
and riparian species that are compatible with water supply delivery for human needs is
fraught with both system uncertainty and trade-offs over conflicting values. Our approach to
these challenges involves greater awareness of the need for flexibility to balance trade-offs
over time, rather than seeking an elusive, singular and static point of balance.
The Project attacks one of the central problems faced by environmental water managers:
lack of representative, credible, integrated functional flow criteria that are explicitly linked
with physical models over large spatial scales. Unlike approaches which focus on a small
number of simplified and static ecosystem needs, EFT describes 25 site specific, functional
flow algorithms (based on conceptual models) for 13 representative species and key
habitats across the Sacramento River and Delta ecoregions. We include life-history stage
indicators for both listed and non-listed species and habitats. EFT's life-history stage
conceptual models are then linked with multiple physical models of flow, water temperature,
salinity, stage, channel migration and sediment transport to enable ecological effects
analyses. Additionally, we have used the tool to both develop and test flexible, dynamic
(state-dependent) flow criteria for incorporation into other models.

Chapter 1: Overview
2 | Page
It is important to stress that restoring functional elements of a flow regime is not the same
as restoring a "natural" or pre-regulated or unimpaired flow regime. In our nearly 10 years of
work developing and applying EFT, and guided by the advice of many exceptional scientists
and managers, we have been concerned with defining representative critical functions and
quantifying a pattern of variation that can over time balance needs amongst multiple
species. Within this context, three overarching challenges confront assessment and
prescription of ecological (or environmental) flows. The first challenge is how to credibly
characterize and define cause-effect conceptual models to describe how representative
components of linked ecosystems respond to flow regime alterations. The second challenge
is using these models to quantify acceptable target flow criteria and departures from natural
flow regimes that will maintain specific critical features of the ecosystem (especially those
that support endangered species recovery). The third and most vexing problem is deciding
how to reconcile trade-offs amongst alternative ecosystem values and water supply needs
for human use through time. The extensive body of work accomplished in this Project and
summarized in this report offers an important contribution to how all three of these
challenges might be navigated.
Prior to EFT, much of the important information on focal species existed in hard-to-access
isolated reports and unconnected models and tools. EFT has integrated and synthesized a
wide array of disparate information, linking ecological submodels to existing physical
planning models, and providing a major advance in the water community's capabilities for
more rapidly assessing multiple ecological trade-offs. Developing and peer reviewing these
flow-habitat-biota hypotheses has been aided by a sustained collaboration with over 70
aquatic biologists, hydrologists, geomorphologists and hydrosystem engineers during the
selection of EFT's focal species, indicators, and the subsequent algorithm development
since 2004 (ESSA 2011, 2013).
All models are conceptualizations of reality and are often thought of as aggregate
hypotheses that describe how different variables of interest are linked and influenced by
interacting physical, habitat and biological processes. Modeling ecosystem relationships is
often used to assess ecosystem health or, in the case of flow regime assessments, to
determine trade-offs between human water uses and ecological needs (Rapport et al.
1998). Because of the high uncertainty and lack of understanding surrounding the complex
interactions of communities of species with their physical environments (e.g., lagged
compensatory density-dependent survival mechanisms), many modeling approaches
emphasize physical limiting factors and other habitat variables. The implicit assumption is
that more functional habitat will – all else being equal – support higher abundances. A step
beyond physical habitat modeling (alone) is to model a specific set of species and life-
stages by defining explicit linkages with changes in important habitats. In other words, many
habitat (and life-stage specific focal species) models simulate the potential for lower/higher
adult abundance. However, due to compensatory dynamics that often drive population level
responses outside of a given life-stage time period, more high-quality habitat at a particular
(usually juvenile) life-stage does not always translate to a higher abundance of adults.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
3 | Page
In response to these limitations, some researchers attempt to develop full life-cycle
population representations that predict space-time abundance of a particular species or
even the individual behavior and movement of a species as they are born, grow, develop
into adults and reproduce. This significant additional detail, and the aim of predicting
changes over time in adult abundance or population viability (or recovery potential), comes
with a price; single-species models are typically “data hungry” and require intensive
calibration procedures to tune life-cycle responses to the available historic datasets. The
Delta Science Panel review of BDCP concluded: "There are no life-cycle models that
integrate the factors that BDCP will influence" (DSP 2014, pg. 13).
Because we used a functional flow approach that emphasizes specific cause-effect
linkages, the formulation of EFT's indicators1 is open to testing and adaptation through time
as new data and understanding emerge. Indeed, the uncertainties surrounding how multiple
stressors and flow management interact (e.g., nonlinear responses, invasive species, water
quality changes, etc.) can make a flow regime target that seems adequate today of less
value in the future (Hanak et al. 2011). EFT provides a framework that allows new indicators
to be added, and others dropped through time as knowledge evolves. Our approach to
identifying the desired flow regime is therefore more aptly described as "functional" than
"natural". By carefully choosing a representative range of species and ecosystem functions
over a broad geographic scale, variation and consequences of different flow regimes can be
quantified and trade-offs brought into clearer focus.
1.1 Project History and Goals
“The panel believes it is essential that a sense of urgency be developed for initiating
a dedicated project to build a simplified ecosystem model that is tailored to assess
responses to changes in conveyance facilities. This project could build upon existing
modeling capabilities…but will require that a full-time multidisciplinary team be
devoted to the project for at least several years.”
CALFED Science Advisory Panel, June 24, 2008
This Final Report synthesizes the outcomes of the Ecological Flows Tool project (Project),
launched in October 2008 and completed in April 2014 entitled: "Complementing Water
Planning Efforts for the Delta and Sacramento River: Application of the Ecological Flows
Tool for The San Joaquin-Sacramento Delta and Sacramento River". Chapter 2
summarizes EFT focal species, performance indicators (PIs), and analysis methods. In
addition to describing categories of outputs, we provide an explanation of the different
approaches to synthesizing outcomes and generating higher level net effect conclusions.
1 Refer to the List of Abbreviations, Measurement Units and Fundamental Terms for a definition of "indicator" and other core
concepts used throughout this report.

Chapter 1: Overview
4 | Page
Chapter 2 also describes external models currently used by EFT as well as the
methodology involved with using EFT to develop rule-sets for eco-friendly flow regimes. In
particular, Chapter 3 focuses on findings and lessons from three major applications of EFT.
In Chapter 3 we present results from an application of EFT to selected North-of-the-Delta
Offstream Storage (NODOS), Delta Conservation Plan (BDCP) alternatives2 as well as
describe an initial pilot test using EFT to derive ecological flow criteria for inclusion in
CALSIM. We then perform a subsequent "full circle" effects analysis using EFT to measure
the ecosystem benefits and trade-offs of these initial (and incomplete) eco-friendly criteria
we added to CALSIM. Chapter 4 concludes with logical next steps and promising new
avenues for future research. The Project was designed and managed by The Nature
Conservancy (TNC) and ESSA Technologies Ltd. (the Project Team).
The origins of this Project are in part an outgrowth of nearly three decades of conservation
work by The Nature Conservancy (TNC) and its partners in the Middle Sacramento River.
TNC received CALFED Ecosystem Restoration Program (ERP) funding in 2004 (grant
ERP−02D−P61) to expand the ecological considerations and scientific foundation of water
management decisions in the Upper and Middle Sacramento River, from Keswick Reservoir
to Colusa. Referred to as the Sacramento River Ecological Flows Study (the Flows Study),
work on a variety of tasks was completed between 2004 and 2008 (TNC et al. 2008). One
of these tasks was the design and development, by TNC and ESSA Technologies Ltd., of a
prototype decision analysis tool – the Sacramento River Ecological Flows Tool (SacEFT),
which incorporated biophysical habitat models for six Sacramento River species, linked to
physical models of flow, water temperature, channel migration and sediment transport. That
effort was completed in 2008 and culminated in completing the first phase of EFT.
On the strength of the foundational work under the Flows Study (TNC et al. 2008), TNC was
awarded an additional grant by the Ecosystem Restoration Program (ERP-07D-P06 / DFG#
E0720044) in 2008 to refine and expand the capability of SacEFT for application to the San
Joaquin-Sacramento Delta.
Extending the SacEFT decision analysis tool to incorporate Delta targets and management
actions has: 1) allowed the first phase ERP funds to be leveraged; 2) achieved economies
of scale through efficient application of a proven approach to link and integrate biophysical
models; 3) provided a focal point for further assembling and quantifying important,
representative functional cause-effect linkages in the Delta ecoregion; and, most
significantly 4) created new capability to integrate species’ trade-off evaluations between
the Sacramento and Delta ecoregions. This approach unites the ability to evaluate
ecological effects in both of these highly linked ERP ecoregions and draws additional
attention to trade-offs associated with management actions between Sacramento River
2 Note: This effects analysis application is performed, written and interpreted by our team, and applies both SacEFT and
DeltaEFT. Previously, portions of SacEFT version 2 were considered by external BDCP Consultants as part of the vast BDCP
effects analysis.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
5 | Page
Basin dam operations and changes proposed in the Delta. Using EFT, it is possible to
simultaneously assess whether actions contemplated in one ecoregion jeopardize the
considerable conservation progress and investment in the other. To our knowledge, no
other trade-off evaluation tool exists that integrates how ecoregions and multiple species
performance indicators relate to one another and the general magnitude of these trade-off
interactions.
1.1.1 Project Goals
The goals and findings of the Flows Study (and associated initial work on SacEFT) are
documented in TNC et al. (2008). The Ecological Flows Tool Project (ERP-07D-P06 / DFG#
E0720044), the subject of this Final Report, had four goals:
1. Complete expert peer review and refine SacEFT, to further increase the robustness
of analyses and technical credibility for application to relevant water management
planning and effects analysis efforts evaluating Sacramento River targets.
2. Facilitate the incorporation of the most robust and defensible findings from various
Delta planning efforts and on-going studies3, and incorporate them into a DeltaEFT
branch of the existing decision analysis tool, thereby integrating the strongly linked
Sacramento River and San Joaquin-Sacramento Delta ecoregions.
3. Apply both SacEFT and DeltaEFT (collectively referred to as EFT) to relevant water
management planning efforts to highlight the ecological trade-offs in both
ecoregions. Work with relevant water management agencies to identify and evaluate
notable water operation scenarios that have been proposed (e.g., North-of-the-Delta
Offstream Storage (NODOS), Bay Delta Conservation Plan (BDCP), Shasta Lake
Resource Investigation, Bureau of Reclamation’s Operating Criteria and Plan
(OCAP) Review/Remand, DWR’s System Re-Operation Program).
4. Effectively communicate the knowledge gained to agency managers and
stakeholders, as well as to the public.
1.2 Vision - Multiple Ecological Flow Needs
The vision for EFT is to link physical hydrogeomorphic models (flow, water temperature,
sediment transport, meander migration) to a representative set of ecosystem performance
indicators in a decision analysis tool for evaluating multiple ecosystem trade-offs both in the
Sacramento River and Delta. Our inclusion of a broad suite of ecological considerations in
water-planning exercises catalyzes clearer communication of new, dynamic, flexible
ecological flow targets and guidelines, and makes it more efficient to take these targets into
account during water operation and conveyance investigations. From the beginning, a high
priority of the EFT team has been to select representative species and ecological indicators
3 Primarily studies available between 2008 and 2012.

Chapter 1: Overview
6 | Page
that capture the essence of existing scientific understanding. We have aimed for a multi-
species, multi-indicator approach while being careful to avoid paralysis caused by too broad
a sphere of concern. We believe we have approximated a “Goldilocks” level of detail for
components in EFT. While some EFT indicators can be quite sophisticated and others
relatively simplistic, we have worked hard to achieve an overall balance of credibility and
level of detail. We made a conscious design decision to avoid detailed data-hungry single-
species models that, while comprehensive in their attempt to represent all life-history
processes for that species, may suffer from a statistical challenge just as problematic as
model over-simplification –– equifinality4 (multiple combinations of parameters that
reproduce historic observations yet may yield different future predictions). Details on the
formal focal habitat/species filtering and screening criteria (vetting process) used for
DeltaEFT are provided in Appendix F.
EFT works by integrating 25 site specific, functional flow algorithms (conceptual models) for
13 representative species and key habitats across the Sacramento River and Delta
ecoregions, with widely used hydrogeomorphic models. EFT's life-history stage conceptual
model algorithms are then linked with multiple physical hydrogeomorphic models of flow,
water temperature, salinity, channel migration and sediment transport (e.g., CALSIM,
USRDOM, SRWQM, DSM2) to enable ecological effects analyses, as well as development
and testing of flexible, dynamic (state-dependent) flow criteria. In this way, EFT
transparently relates multiple attributes of the flow regime to multiple species’ life-history
needs, providing a more comprehensive understanding of the effects of water operations on
representative focal species and their habitats. The functional relationships that relate to
EFT’s performance indicators are based on the best available science, and represent the
collective knowledge of more than 70 scientists from state and federal agencies, consulting
firms, and research institutions who have participated in our workshops since 2005 or who
wrote primary papers on which the functional relationships are based.
We show in this report how EFT contributes to a more comprehensive understanding of
how proposed changes to water operations infrastructure and management (and future
climate conditions) affect species and their habitats. EFT does not solve social value
decisions about whether a particular action or alternative is "good" or "bad." Rather, EFT is
designed to provide information about the positive, neutral, and/or negative effects of a
particular alternative, across a suite of representative focal species and their habitats.
Importantly, this includes trade-offs that exist among multiple species’ needs. EFT’s intuitive
outputs make it clear how actions implemented for the benefit of one geographic area or
focal species may affect (positively and/or negatively) another area or focal species. For
example, EFT can demonstrate how altering Sacramento River flows to meet export
4 It is endemic to mechanistic modeling of complex open environmental systems that there are many different model structures and
many different parameter sets within a chosen model structure that may be acceptable in reproducing historically observed behavior
of that system. This is called 'equifinality'. This is more than an academic concern if mechanistic models fit to historic data are relied
upon to predict future trajectories of a variable of interest in detail. This is a significant concern when different (equally plausible in
terms of fit to historical data) parameter sets produce different future trajectories.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
7 | Page
pumping schedules in the Delta affects focal species’ performance indicators both in the
Sacramento River and the Delta. This ecoregional trade-off capability is unique to EFT.
As demonstrated in Chapter 3, EFT is also useful for developing functional flow guidelines.
Because of the multi-species approach, EFT helps communicate how to prioritize trade-offs
among ecological objectives and adjust these priorities based on emerging conditions (e.g.,
water year types) and the ability to realize different objectives over time. These guidelines
and criteria, based on EFT analyses, can be simplified for use in physical hydrosystem
models such as new WRESL and other policy/rule statements in models like CALSIM and
CalLite. Over time and with appropriate testing and optimization, this will improve the
ecological flow guidelines contained in these tools.
1.3 Ecological Flow Needs: ‘What’ are they?
Ecological (or environmental) flows are concerned with access to and distribution of water
to sustain the biodiversity and natural services provided by aquatic and riparian
ecosystems. They refer to the quality, quantity, timing, and shape of flow regimes that
support ecosystem functions, processes and resilience. The natural flow paradigm treats
flow as the "master variable" needed to drive natural variation of hydrologic regimes to
protect native biodiversity and the evolutionary potential of aquatic and riparian ecosystems
(Arthington et al. 1991, 2006; Richter et al. 1996, 1997; Stanford et al. 1996; Poff et al.
1997; IFC 2002; Postel and Richter 2003; Tharme 2003; Petts 2009; Fleenor et al. 2010;
Carlisle et al. 2010; Poff and Zimmerman 2010; Poff et al. 2010; Hanak et al. 2013).
Ecological flow assessments are concerned with determining the flow regime required (or
the acceptable departure from the original flow regime) to maintain specified, valued
features of the ecosystem. Consideration of a single, minimum threshold flow, to the
exclusion of other ecologically relevant flows (Tennant 1976), has been considered for
some time to be an unacceptable approach to instream flow management. Because of the
important functions of extreme flows and flow variation through time, maintaining a
consistent base flow year after year is a management strategy that has also fallen from
favor.
Methods for assessing ecological flow needs have emerged, ranging from screening the
degrees of change and risks over large spatial areas with readily available data (e.g.,
Richter et al. 1996; Olden and Poff 2003; Poff et al. 2010; Sanderson et al. 2011) to site-
specific, bottom-up, causally-reasoned functional flow methods applied to specific locations
and species (e.g., Bovee et al. 1998; Parasiewicz 2001; Jowett and Davey 2007; Conallin et
al. 2010). As different methods focus on different questions, they are all valuable for
advancing understanding of ecological flow needs. Top-down approaches are generally
concerned with agile risk identification and prioritization over broad spatial scales (using
readily available data) while bottom-up methods emphasize identification of causally-
reasoned functional flows for specific species and habitats, in specific river segments.
Depending on how their eco-hydrologic performance indicators were developed, it may be

Chapter 1: Overview
8 | Page
possible to convert the outcomes from top-down methods into ecological flow
criteria/guidelines that can be used in other decision support systems. Bottom-up methods
are sometimes (but not always) more expensive to undertake, due to their more demanding
site and species specific data requirements and the need for more detailed cause-effect
conceptual models that link physical data to specific habitat or species life-history survival
outcomes.
The four different general methods for producing ecological flow need recommendations are
summarized in Table 1.1.
Table 1.1: Common methodologies for determining environmental flows (Alexander et al.
2013, and references therein).
eFlow
Methodology
Description
1. Expert opinion
and rules of thumb
Ecological flow needs generated by a group of domain specialists in aquatic
biology/ecology or fluvial geomorphology (or related discipline). Normally, said experts
will have many person-decades of experience. An example of an expert opinion
assessment is recommending the 10th percentile of mean annual discharge and asserting
that these maintain river health (e.g., Tennant Method, Q90). The best expert
assessments involve individuals from a range of relevant disciplines (biology,
geomorphology, ecology, hydrology), agencies, institutions or firms to ensure views are
representative and impartial. These “desktop” methods have the benefit of being quick
and inexpensive to develop with low data needs, but have been criticized as being
simplistic and failing to encompass a full understanding of river processes.
Ecological flows generated using this approach are more heuristic, qualitative, opinion-
based and more difficult to "test" (prove/disprove). While their ultimate verisimilitude
may be as strong as the other flow need recommendations from other methods,
“acceptance” of expert opinion guidelines tends to be more open to debate, and there
are usually more defined “camps” of supporters (believers) and non-supporters (non-
believers).
2. Generalized
hydrologic indices
Use changes in simple hydraulic variables (statistical metrics) as a surrogate for habitat
factors of target biota. These methods are relatively easy to implement, requiring only
minimal data. Includes the Index of Hydrologic Alteration (IHA) and other metrics of the
degree of pre- and post-regulation/depletion change to flow regime, or other measures
comparing unimpaired flows/historic flows with current flows. This approach does not
use explicit characterization of target species life-history needs and consequences, does
not on its own quantify available habitat, nor make other specific inferences on
ecological responses. Often, recommendations from these methods are considered
subjective.
On their own, these methods do not help resolve specific ecological effect size changes
inherent in the different degrees of flow regime departure / alteration. When the degree
of response of a specific Valued Ecosystem Component (VEC) is linked with levels of
hydrologic alteration, these indicators may be characterized as statistical/empirical

Final Report
Application of EFT to Complement Water Planning for Multiple Species
9 | Page
eFlow
Methodology
Description
relationships, or as functional flows (depending on details of how degree of alteration
was linked with the VEC).
3. Empirical/
statistical
relationships
The relationship is indicated between flow or other driving explanatory variable and
native species abundance or desired habitat area (or other desired ecological attribute),
but a step-by-step cause-effect prediction from physical variable to habitat change to
biological response is not made (the mechanism is not clearly articulated, but is instead,
"within" the data). These approaches may use models of the quantity and suitability of
physical habitats to support target species under different flow regimes (e.g., IFIM,
PHABSIM). Habitat simulation methodologies that develop empirical relationships can
provide high resolution habitat-flow relationships but tend to focus on single species, not
whole ecosystems. IFIM/PHABSIM and related method outputs are restricted to flow-
hydraulic habitat relationships and often show poor linkages with biological responses.
Other empirical/statistical approaches develop relationships that can be combined with
a hydrologic index or with causally-reasoned functional flows.
4. Causally-
reasoned
functional flows
Are developed for specific species and habitats, in specific river reaches, and are
generally based on cause-effect box-arrow conceptual models linking flow and other
variables (e.g., water temperature, channel migration, sediment transport) with changes
in important physical habitats through in some cases, to life-history survival mechanisms
of the species of interest. Ecological flows derived in this manner (process modeling)
require additional site and species specific data, and other physical habitat
measurements and/or modeling, and are the most amenable to direct hypothesis
testing/validation. Fleenor et al. (2010) describe this and other hydrologic and statistical
methods that are commonly applied. When multiple functional flows are developed for a
representative suite of species and habitats, these methods are the most holistic
methods. Developing flow need criteria from these more rigorous methods also tends to
generate higher resource and data requirements.
The four categories of ecological flow methods described above in Table 1.1 are ordered in
terms of the level of scientific rigor applied to creating their underlying rationale and body of
evidence. Functional flows provide the highest degree of explicit cause-effect reasoning
between flows, important habitat attributes, and survival and productivity measures for
target species. Different ecological and recreational flow need recommendations may be
based on one, two or more of these methods. The majority of EFT's performance indicators
are developed using method 4 and secondarily 3.
1.4 Summary of Project Tasks & Deliverables
To meet the Project goals, our work was organized into three tasks:
 Task 1: SacEFT Model Refinements and Application.
 Task 2: DeltaEFT Model Development to Evaluate Flow Needs for Delta Species.
 Task 3: Project Management, Draft and Final Report.

Chapter 1: Overview
10 | Page
The Project work plan involved over 20 subtasks (Table 1.2) that were completed over a
period of five years. The bulk of our work was designing, building and peer reviewing
SacEFT (version 2.0) and DeltaEFT (version 1.1). EFT indicator development involved a
number of important interrelated tasks: 1) expert design and review workshops (moving
from conceptual model to cause-effect rules, algorithms); 2) database development; 3) data
loading/configuration (and related data hunting); 4) programming; 5) output visualization
development; 6) user interface programming; 7) developing relative suitability thresholds for
EFT indicators; and 8) testing/bug fixing (iterative). Chapter 2 summarizes EFT's species
and performance indicators with links to detailed Records of Design for both SacEFT and
DeltaEFT.
This Draft Final Report integrates the capabilities of SacEFT and DeltaEFT to assess
effects of selected BDCP alternatives and shows how other data were used to develop and
assess the effectiveness of EFT-derived ecological flows criteria in CALSIM (Chapter 3).
Table 1.2: Project tasks and associated deliverables.
Task
Deliverables
Task 1: SacEFT Model
Refinements and
Application
 Task 1.1 - Facilitate SacEFT Model Refinement Workshop
 Task 1.2a - Draft SacEFT Model Refinements Workshop Technical Memo
 Task 1.2b - Final SacEFT Model Refinements Workshop Technical Memo
 Task 1.4 - Updated SacEFT v2.0 Design Document [Appendix B]
 Task 1.3 - SacEFT Application to Relevant Water Management Scenarios
[Chapter 3, this document]
 Task 1.5 - Refined SacEFT v2.0 Software and Install Pack
 Task 1.3b - SacEFT Application to NODOS Admin EIS/R
 Task 1.3c - Finalize and test alternative ecological flow requirements for
Sacramento River-dependent targets [Chapter 3, Appendix I, this
document]
 Task 1.7 - Task 1 Quarterly Reports (multiple)
Task 2: DeltaEFT Model
Development to
Evaluate Flow Needs
for Delta Species
 Task 2.2a - Draft DeltaEFT Backgrounder Report
 Task 2.2b - Final DeltaEFT Backgrounder Report [Appendix C]
 Task 2.3 - Facilitate DeltaEFT Model Design Workshop
 Task 2.9a - Initial DeltaEFT Outreach Presentations
 Task 2.4a - Draft DeltaEFT Design Guidelines
 Task 2.4b - Final DeltaEFT Design Guidelines [Appendix D]
 Task 2.5a - DeltaEFT alpha version
 Task 2.5b - DeltaEFT beta version
 Task 2.5c - DeltaEFT Database and Software, v1.0
 Task 2.7 - Simple DeltaEFT User’s Guide [Appendix E]
 Task 2.5d - Final DeltaEFT Database and Software (v.1.1), including new
intuitive spatial visualizations
 Task 2.6 - DeltaEFT Install Pack and Webpage
 Task 2.9d - Develop and test alternative ecological flow requirements for
Delta-dependent targets [Chapter 3, Appendix I, this document]
 TNC Task 1: Incorporate longfin smelt abundance index to DeltaEFT
 Task 2.10 - Task 2 Quarterly Reports (multiple)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
11 | Page
Task
Deliverables
Task 3: Project
Management, Draft
and Final Report
 Task 3.2: Support Work Scope, Contract Documentation
 TNC Task 2.1: Support for analysis and incorporation of Draft Final BDCP
alternatives into Draft Final Report [this document]
 Task 3.3: Draft Final Report [this document, especially Chapter 3]
 TNC Task 2.2: Support for analysis and incorporation of Final BDCP alternatives
into Final Report [in progress]
 Task 3.4: Final Report [in progress]
 Task 3.1: Quarterly Reports
Given the volume of products, the Ecosystem Restoration Program has established a
dedicated web site (www.wildlife.ca.gov/erp/erp_proj_delta_eft.aspx) to make the following
available:
 Original SacEFT Backgrounder Report (from previous Flows Study, ESSA 2005)
[Appendix A]
 Flows Study Final Report (from previous Flows Study, TNC et al. 2008)
 Updated SacEFT v2.0 Record of Design (Task 1.4) [Appendix B]
 SacEFT Application to NODOS Admin EIS/R (Task 1.3b)
 Final DeltaEFT Backgrounder Report (Task 2.2b) [Appendix C]
 Final DeltaEFT v.1.1 Record of Design (Task 2.4b) [Appendix D]
 Simple EFT User’s Guide (Task 2.7) [Appendix E]
 Final EFT Reader Software and Installation Webpage [i.e., delivers both refined
SacEFT v2.0 Software and Install Pack (Task 1.5) & DeltaEFT Install Pack (Task
2.6)]
Following is a summary of the primary deliverables produced under the ERP grant to TNC:
1999-2007 (prior to Agreement No. E0720044)
In 1999, TNC initiated a pilot study on mechanisms affecting riparian vegetation
recruitment along the Sacramento River. These studies suggested that a variety of
altered riverine processes were limiting natural recruitment of riparian vegetation. The
Sacramento River Ecological Flows Study was initiated to address such processes
and to complement existing revegetation efforts. It also expanded the scope of
investigations to address the needs of both terrestrial and aquatic species. The Flows
Study effort began in 2001, with the submittal of a proposal by the Ecological Flows
team to the CALFED Ecosystem Restoration Program (ERP). After extensive reviews
by CALFED, independent technical reviewers, and individual stakeholders, the Study
was funded in 2004 under CALFED Grant No. ERP-02D-P61 to The Nature
Conservancy. The goals, tasks and deliverables of this first major phase are described
in TNC et al. (2008). One of the Flows Study tasks included design and development
of version 1.0 of the Sacramento River Ecological Flows Tool (SacEFT).

Chapter 1: Overview
12 | Page
2008
The Project Team delivered the SacEFT v.1 Model Review Workshop October 7 & 8,
2008 in Chico California with over 30 participants (Task 1.1). ESSA completed a draft
SacEFT Model Refinements Workshop Technical Memo (November 5, 2008), and
distributed it to workshop participants for comments (Task 1.2a). ESSA incorporated
TNC suggestions and workshop participant peer review comments to complete a final
SacEFT Model Refinements Workshop Technical Memo (December 17, 2008). The
document defined understanding of enhancement options arising from peer review of
SacEFT v.1, and prioritized them according to effort, feasibility and importance (Task
1.2b). In parallel, our team completed the DeltaEFT Backgrounder document
December 23, 2008, a key input in advance of the DeltaEFT design workshop
(planned for January 2013).
2009
The Project Team planned a 2-day DeltaEFT Model Design Workshop January 27 &
28, 2009 in Rancho Cordova to elicit the essential information needed to: 1) design
the DeltaEFT Model; 2) determine priority candidate focal species, habitats and
functional relationships; and 3) define the candidate management scenarios to apply
in DeltaEFT. The Model Design Workshop was attended by 29 experts in the areas of
Delta ecology and biology, physical modelers, and water managers with in-depth
knowledge of existing data sets, fish population biology, and environmental water
gaming.
On November 16, 2009, ESSA delivered an on-line training seminar for the SacEFT
v.1 Reader software.
2010
On February 22 to 24, 2010 we also presented materials (poster and brochure) at the
California Water Environmental Modeling Forum, and co-presented DeltaEFT to
experts attending this conference in Monterrey California. We also prepared and co-
delivered a presentation on DeltaEFT to
the State Water Resource Control Board
in Sacramento on February 25, 2010.
Task 1.5 – Refined SacEFT v.2 software
and install pack (database, indicator
algorithm changes, Graphical User
Interface enhancements, related software
programming and Excel reporting
changes) – was completed in the spring of
2010. ESSA software developers also
completed revisions to the install pack

Final Report
Application of EFT to Complement Water Planning for Multiple Species
13 | Page
software program, to link to the appropriate EFT Reader database. This included a
new deployment web site (October 2010) for users to register to receive the EFT
Reader download.
In June 2010, we completed DeltaEFT
Design Guidelines (Task 2.4b). The
document is based on an extensive
literature review associated with the
development of the DeltaEFT
Backgrounder, input from experts
attending the DeltaEFT Model Design
Workshop (January 2009),
subsequent literature reviews
following the lifting of the grant freeze
in October 2009, and select one-on-
one follow-up with modeling experts.
SacEFT v.2 was immediately put into service to conduct an effects analysis for six
BDCP alternatives, delivered June 23, 2010 to Science Applications International
Corporation (SAIC). Results included: 1) a high-level summary of SacEFT focal
species performance indicator trends; 2) a summary of ecological performance of the
BDCP alternatives for SacEFT v.2’s steelhead (Oncorhynchus mykiss), green
sturgeon (Acipenser medirostris), and Chinook salmon (O. tshawytscha) performance
indicators (this analysis compared the percentage of years that had favorable
conditions during the six simulations, including the change between the no action
alternative and the proposed project in each of three time periods); and 3) an example
of specific target water temperatures for green sturgeon egg incubation relative to the
expected water temperatures that occur under the BDCP PP-LLT scenario. Our team
completed the first prototype (or alpha version) of DeltaEFT subsequently in July 2010
(using temporary placeholder datasets).
On October 18, 2010, we were granted access to key data requested by our team on
March 4, 2010; these data were needed to develop and test the prototype version of
DeltaEFT. This period was punctuated by multiple rounds of non-disclosure
agreement negotiations between TNC and California’s Department of Water
Resources (DWR) (related to BDCP confidentiality). Once we received the requested
matching CALSIM, SRWQM and DSM2 data, our team focused on reviewing and
beginning to sequentially load datasets into the DeltaEFT database, and address
numerous unrelated data gaps/issues thereafter.
2011
In February 2011, we delivered SacEFT presentations at California Water
Environmental Modeling Forum (Pacific Grove/Monterey), and in March 2011 we
CH7
CH7
CH7
CH7
ST7

Chapter 1: Overview
14 | Page
responded to a request by DWR (and subsequently TNC) to apply SacEFT v.2 to the
North-of-the-Delta Off-stream Storage Administrative Draft Environmental Impact
Study (NODOS Admin EIS/R). (The decision to focus on NODOS EIS/R temporarily
slowed progress on development of DeltaEFT, which was previously slowed by
numerous challenges acquiring required historical and modeled physical input
datasets, and navigating non-disclosure / confidentiality issues.)
On March 3, 2011 we presented SacEFT with a focus on the bank swallow (Riparia
riparia) habitat potential model to the Bank Swallow Technical Advisory Committee at
the University of California, Davis. This expert review identified several important
refinements to finalize the model’s sophisticated spatial calculations. These
refinements were not identified during the SacEFT v.1 review workshop.
In September 2011 we completed Task 1.3b – SacEFT Application to NODOS Admin
EIS/R (TNC and ESSA 2012). Here we performed Sacramento River Chinook,
steelhead, green sturgeon, Fremont cottonwood (Populus fremontii) and bank swallow
effects analysis associated with five NODOS alternatives. This included use of
SacEFT v.2 to capture changes in the percentage of years in the simulation period
that report favorable indicator ratings. The structure of this analysis mirrored the
results package delivered as part of the SacEFT v.2 BDCP effects analysis for
Chinook, steelhead and green sturgeon (under Subtask 1.3).
In August 2011, and the following December 2011, our team completed the alpha and
beta versions of DeltaEFT (Tasks 2.5a and 2.5b respectively). Testing, refinement and
development continued in sprints during and after this period until May 2012 when
ESSA completed version 1.0 of DeltaEFT (Task 2.5c). The timing of the opportunity to
contribute to the San Joaquin-Sacramento Delta Conservation Plan’s ecological
effects analysis using SacEFT delayed progress on completing the first full version of
DeltaEFT.
2012
In July 2012, the ESSA team completed DeltaEFT version 1.1 (Subtask 2.5d). This
version of the software more clearly and effectively communicates Delta Ecological
Flows Tool (DeltaEFT) outputs and trade-offs by providing intuitive spatial
visualizations (output reports) in the EFT graphical user interface.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
15 | Page
Indicator performance indicators for the Sacramento River were accessible through
the EFT Reader software tool as traffic light roll-ups and as graphic and tabular
reports in Excel. However, some of DeltaEFT's indicators required spatially-explicit
reports. The new spatial visualization features added to DeltaEFT output now make it
clear “where” things are and reveal patterns of spatial variation in DeltaEFT indicator
performance. The re-release of DeltaEFT as version 1.1 also triggered creation of a
new installation program and associated web page (Task 2.6), available here:
http://essa.com/tools/eft/download/.
On August 3, 2012 we completed updating the User Guide for the EFT system. This
included a description of functionality for the updated Graphical User Interface for
DeltaEFT. This User Guide is integrated into the Help menu of the EFT Reader
software, and directs users to the following web site: http://eft-userguide.essa.com/.
Delivery of the EFT User Guide5 on-line simplifies maintenance and updates. The
User Guide includes:
 A summary of application requirements.
 A Quick Start Tutorial, including how to install the EFT Reader (with associated
screen images).
 Step-by-step instructions for all major User Interface components.
On September 19, 2012 we completed the first DeltaEFT analysis, applying the tool to
four preliminary San Joaquin-Sacramento Delta Conservation Plan alternatives
(including two baseline/reference cases and climate change alternatives). These
preliminary results were presented to the State Water Resource Control Board staff in
5 This is not a "Design Document", but a simple introduction to operation of the EFT Reader software (both SacEFT and DeltaEFT).

Chapter 1: Overview
16 | Page
Sacramento on October 3, 2012. A second presentation on DeltaEFT was delivered
as part of a panel presentation to the State Water Resource Control Board's formal
workshop hearings on November 13, 20126. These important efforts went towards
fulfilling obligations under Subtask 2.9c of the grant ("DeltaEFT Presentations to
Individual Agencies").
In December 2012, efforts focused on preparations for the DeltaEFT peer review
workshop, scheduled for January 30, 2013 in Sacramento. This included agenda
preparation, logistical input, meeting invitation support, and beginning to prepare
presentation materials. While not a formal Project deliverable, we also documented
review feedback from the January 2013 workshop.
2013-2014
In January 2013, the DeltaEFT as-built Design Document was revised (longfin smelt,
Spirinchus thaleichthys, added). Work developing and testing alternative ecological
flow requirements for Sacramento River and Delta-dependent targets was conducted
from the summer of 2013 through to December 2013, and is the subject of Chapter 3.
In November 2013, we added longfin smelt to DeltaEFT v.1.1, updated the Design
Document, and then initiated the final EFT effects analysis on selected BDCP
scenarios (Chapter 3, this report). That effects analysis modeling was completed in
late January 2014.
6 See: www.waterboards.ca.gov/waterrights/water_issues/programs/bay_delta/docs/wrkshp3/leowinternitz.pdf

Final Report
Application of EFT to Complement Water Planning for Multiple Species
17 | Page
2 Core Methods & Ecological Flow Needs Considered
This Chapter summarizes EFT's key concepts, approaches and methods, specifically:
 the kinds of management alternatives that can be evaluated using EFT (Section 2.1);
 the objectives and functional ecological flow needs considered in EFT and their key
attributes (Sections 2.2 - 2.5);
 a description of our coupled modeling approach (Section 2.6);
 a review of the different categories of available EFT outputs (Section 2.7);
 a summary of how different effects are distinguished based on the structure of the
trade-off comparison (Section 2.8); and finally,
 how EFT rule-sets can be integrated within systems operation models (Section 2.9).
EFT's multi-species, multi-indicator paradigm provides a “portfolio” approach for assessing
how different flow and habitat restoration combinations suit the different life stages of target
species. In so doing, EFT transparently relates attributes of the flow regime to multiple
species’ life-history needs in an overall effort at careful organization of representative
functional flow needs. This provides a robust scientific framework for evaluating and
prescribing ecological flow guidelines contributing to the understanding of water operation
effects on focal species and their habitats.
EFT’s focal species and performance indicators (PIs) are frequently split into two
geographic regions: the Sacramento River ecoregion, where SacEFT is applied between
Keswick (RM 301) and Colusa (RM 143); and the Delta ecoregion defined from a location
just above Fremont Weir (RKI 182) and extending downstream into the Delta west and east
of the mainstem river (Figure 2.1), where DeltaEFT is applied.

Chapter 2: Ecological Flow Needs Considered
18 | Page
Figure 2.1: The two ecoregions of EFT: Sacramento River (SacEFT) and DeltaEFT
(DeltaEFT).
Every decision support modeling exercise must include assumptions about what is included
and excluded in order to keep the effort tractable. Details on the formal focal species and
indicator screening and selection process used for EFT are provided in Appendix F.
Vetting of candidate species and indicators was further achieved through expert design and
review workshops (two for SacEFT and two for DeltaEFT). These workshops were used to
further review candidate conceptual model algorithms for the indicators that would be built
into EFT. Workshop participants met in plenary to review the project background, learn

Final Report
Application of EFT to Complement Water Planning for Multiple Species
19 | Page
about the intended scope and use of the model, and consider candidate conceptual models
and our approach to evaluating trade-offs. Participants then worked through issues of model
scope, bounds and integration of the candidate submodels. Subgroups then focused on
refining the details and high priority pathways of each conceptual submodel. The intention
was to identify a small subset of priority performance indicators per focal species to
integrate into EFT. Subsequent peer review workshops were held to review test applications
of initial versions of these models in both SacEFT and DeltaEFT.
An overview of the species and habitat indicators in EFT are provided in the sections that
follow.
For economy, this Chapter does not attempt to reiterate algorithm details and assumptions
of EFT's life-history stage conceptual models. Appendix A and Appendix D provide detailed
as-built Records of Design for both the SacEFT and DeltaEFT branches of the tool.
2.1 Management Actions That Can Be Evaluated Using EFT
This section describes the range of management actions that can be evaluated using EFT.
The specific alternatives evaluated in Chapter 3 are presented in Sections 3.3.2 and 3.4.2.
2.1.1 Reservoir Operations and Conveyance
The primary emphasis of EFT is to provide ecological trade-off information and recommend
ecological flow criteria for water storage, conveyance and operation alternatives. Flow
related management actions that can be evaluated using EFT include: 1) external climate
forcing (historical or future) and human population demands; 2) Sacramento River Dam and
diversion operations; 3) Delta conveyance and pumping operations; and 4) the coordinated
operational criteria that are nested within Sacramento River and Delta (e.g., D-1641
with/without Biological Opinions). These represent a "four box" conceptual framework for
communicating scenario elements (Figure 2.2). Each of these "boxes" represents multiple
“levers” that can be changed, any of which can impact conditions in the Sacramento River
and Delta. Different rules in these "boxes" ultimately translate into different flow regimes
(Figure 2.3).
2.1.2 Bank Protection and Gravel Augmentation Evaluation
In addition to analyzing effects of alternative flow and water temperature regimes, SacEFT
enables comparisons of rock removal and gravel augmentation actions. However, the
alternatives studied in this report do not include gravel augmentation or bank protection
modifications. Additional information on the coupled models used to support SacEFT effects
analyses of these management actions are described in Section 2.6.

Chapter 2: Ecological Flow Needs Considered
20 | Page
Figure 2.2: “Four box” conceptual framework for characterizing flow management actions
that can be evaluated using EFT.
Figure 2.3: Different climate forcing, operational standards, or conveyance features of the
Sacramento River and/or San Joaquin-Sacramento Delta translate into alternate
flow regimes (different colored lines). The specifics of what each of these flow
traces represents will depend on the details. The different flow traces provided
here are for illustration purposes only.
Jan Jul Jan Jul Jan
1966 1967 1968 1969
Flow (cfs)
0
20000
40000
60000
80000
100000
120000
140000
VINA BASE SACE FTFLOW B ASE CFS FLOW VINA NODOS SACE FTFLOW NODOS CFS FLOW VINA SHAST A SA CEFTFLOW SHAS TA CFS FLOW

Final Report
Application of EFT to Complement Water Planning for Multiple Species
21 | Page
2.2 Sacramento River Ecoregion Ecological Objectives &
Performance Indicators
A total of six species groups and 12 distinct performance indicators are represented within
the SacEFT ecoregion (Figure 2.4). In the case of salmonids, steelhead trout and four
Chinook run-types share a common PI framework.
Figure 2.4: SacEFT includes the six species groups shown.
The PIs are listed along with a narrative summary in Table 2.1. More details about the PI
calculation and default relative suitability thresholds are presented in Section 2.7.2 and
Appendix G. Functional details are available in Appendix A (ESSA 2011). Key attributes of
each performance indicator (e.g., units, key index locations) are provided in Section 1.1.

Chapter 2: Ecological Flow Needs Considered
22 | Page
Table 2.1: Summary of SacEFT ecological objectives for each focal species and their
associated performance indicators.
Sacramento River
Focal Species
& Habitats
Ecological Objectives
Performance indicators
Fremont
cottonwood
Maximize areas available for
riparian initiation, and rates
of initiation success at
individual index sites.
FC1
FC2
Cottonwood seedling initiation index
Risk of scour after successful initiation
Bank swallow
Maximize availability of
suitable nesting habitat
BASW1
BASW2
Suitable habitat potential (bank length, m)
Risk of inundation and bank sloughing
during nesting
Western pond turtle
habitat, mainstem
Sacramento River
Maximize availability of
habitat for foraging,
basking, and predator
avoidance
LWD1
Index of old vegetation recruited to
Sacramento River (ha)
Green sturgeon
Maximize quality of habitat
for egg incubation
GS1
Egg-to-larvae survival (proportion)
Chinook salmon
Steelhead trout
Maximize quality of habitat
for adult spawning
Maximize quality of habitat
for egg incubation
Maximize availability and
quality of habitat for
juvenile rearing
CS1
CS3
CS5
CS6
CS2
CS4
Area suitable spawning habitat (000s ft2)
Thermal egg-to-fry survival (proportion)
Redd scour (scour days)
Redd dewatering (proportion)
Area suitable rearing habitat (000s ft2)
Juvenile stranding (index)
As shown, while we include multiple subcomponent effects at a variety of life-stages (in the
case of salmonids), we intentionally avoid attempting to measure effects at the population
level. Attempting to build detailed ecological models that make accurate predictions of
ecosystem behavior is challenging and usually not possible in complex, open natural
systems (Oreskes et al. 1994). Non-stationarity and equifinality7 become particularly
important challenges in parameter/calibration rich models often necessitating a leap of faith
when applying them to future conditions. These models are often sensitive to assumed
initial starting conditions. Additionally, most population-level life-cycle models do not
themselves integrate all of the factors that are influenced by a particular action. So while the
target level of detail and end output metric may be more palatable with life-cycle models,
7 It is endemic to mechanistic modeling of complex open environmental systems that there are many different model structures and
many different parameter sets within a chosen model structure that may be acceptable in reproducing historically observed behavior
of that system. This is called 'equifinality'. This is more than an academic concern if mechanistic models fit to historic data are relied
upon to predict future trajectories of a variable of interest in detail. This is a significant concern when different (equally plausible in
terms of fit to historical data) parameter sets produce different future trajectories.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
23 | Page
the number of assumptions and sensitivity of the tools to these assumptions is generally
very high, and in some cases may obscure the "true" accuracy of predictions.
While life-cycle modeling can aid in the determination of net effects for a species when sub-
stage effects are inversely correlated, it is still possible to draw overall conclusions about
the effect of alternative scenarios in their absence. As described in Section 2.6 and in
Chapter 3 we gauge overall effects of flow management and climate change using weight of
evidence net effect scoring. Where feasible, our indicators also weight life-stage outcomes
by the proportion of the population in that life-stage that is affected. An excessive pre-
occupation on life-cycle models as "the solution" to effects analysis does not serve the
cause of realistic expectation management. For example, Roni et al. (2011) in a
comprehensive evaluation of salmon habitat restoration in Puget Sound, concluded:
“Given the large variability in fish response (changes in density or abundance) to
restoration, 100% of the habitat would need to be restored to be 95% certain of
achieving a 25% increase in smolt production for either species. Our study
demonstrates that considerable restoration is needed to produce measurable
changes in fish abundance at a watershed scale.”
Ultimately, ongoing adaptive management and long-term monitoring programs are required
to continually test and improve conceptual models of all forms. Conceptual models and
performance indicator algorithms used in EFT can in the interim help determine whether
different actions are more likely than not to increase resilience and help species cope with
ever changing conditions.
2.2.1 Fremont Cottonwood Initiation (FC1)
The concepts behind the Fremont cottonwood response variable trace from Mahoney and
Rood’s (1998) recruitment box model, bolstered by site-specific field studies performed by
Roberts et al. (2002, 2003). Seeds of Fremont cottonwood disperse between mid-April and
mid-June (Apr-15 to Jun-21 is default in SacEFT), and seeds that land on non-inundated
ground begin to develop roots which grow down toward the water table. The SacEFT model
assumes that the water table elevation is identical with the river stage, and then adds a
further 30 cm above the water table to account for a capillary fringe zone. As water
elevation drops with declining river stage, seedlings will survive as long as their roots are
able to maintain contact with the water table inside a period of drought tolerance prescribed
by the model (five days). Hence for successful initiation, the water table cannot decline at a
rate that exceeds the taproot growth rate, defined as 22 mm d–1 (with five day "grace
period" to allow for up/down fluctuations in river stage that may temporarily desiccate the
initiating seedling). Should a seedling develop a taproot of 50 cm, it is assumed to reach a
source of permanent groundwater sufficient to keep it alive through the remainder of its first
year. Further details can be found in ESSA (2011).

Chapter 2: Ecological Flow Needs Considered
24 | Page
The calculation of Fremont cottonwood seedling survival is made at a sequence of ”nodes”
along 11 index cross sections along the Sacramento River. Two field studies (Roberts et al.
2002 and Roberts 2003) provide the data necessary to apply this model to three intensively
studied locations (RM 172, 183, and 192) while nine other index cross sections and
matching stage-discharge curves were obtained from HEC-RAS. These cross sections are
located at RM 159, 164, 165, 172, 183, 185.5, 192, 195.75, 199.75, 206 and 208.25.
SacEFT’s riparian initiation model calculates whether a single seedling in the center of each
of these “nodes” along 11 cross sections would or would not survive given a particular flow
regime during the critical life-history period. The node count of surviving seedlings (Figure
2.5) is then used as an index of seedling initiation success (more being better).
Furthermore, SacEFT only makes this calculation for cross sectional nodes that are in the
target elevation zone for initiation, which is defined as anything above 8,500 cfs elevation +
3 ft. Calculations for locations and river stages below and above this height are ignored.
Figure 2.5: Example SacEFT output report for Fremont cottonwood at a specific cross
section.
At present, with the existing 11 cross sections, the value 53 surviving nodes within the
target elevation range (summed over all cross sections) was found by visual inspection to
Water year:
Location of interest:
1983
Fremont - HR172
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
3000
3500
4000
4500
5000
5500
6000
Elevation (m)
Distance along cross section (m)
SacEFT - Riparian Initiation Report
Ground Elevation (m)
Surviving seedling
locations
Root elevation (m)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
25 | Page
represent “good” initiation success, from historical flow data sorted descending (best to
worst counts for each year) over the 66 year historical record. The lower threshold bound of
performance (i.e., "poor") on successfully initiating nodes over these 11 cross sections was
assigned to a node count ≤36.
Details on all default relative suitability thresholds used to "roll-up" EFT results are
discussed in more detail in Section 2.7.2 and Appendix G.
2.2.2 Fremont Cottonwood Scour (FC2)
Newly initiated (but not yet “established”) Fremont cottonwood seedlings are susceptible to
high flow events that inundate the seedlings and mobilize the gravel and sand containing
their root systems. In EFT, scour risk is quantified by determining whether flow thresholds of
80,000 cfs and 90,000 cfs are exceeded in the first year following fair or good initiation
(FC1) years. Additional background is provided in ESSA (2011).
2.2.3 Bank Swallow Habitat Potential (BASW1)
Bank swallows nest and rear their young in burrows along the river banks, and prefer soils
with particular characteristics, burrowing depth, and burrow age. Burrows remain habitable
for about three years and are abandoned after that due to ectoparasites and other factors
which degrade the quality of burrows over time. The meandering of the (unrocked) river
channel occurs naturally during high flow events, creating new bank swallow
burrowing/nesting areas. Coupled to a river Meander Migration model (ESSA 2011), EFT
simulates and reports the length of suitable bank habitat areas produced annually from
approximately Butte City (RM 170) to Woodson Bridge (RM 222). Performance indicator
details and science foundation references are provided in ESSA (2011).
2.2.4 Bank Swallow Nest Inundation (BASW2)
During their spring and early summer nesting period, bank swallows and their young are
susceptible to extremely high flows that can inundate nesting burrows, drowning the
nestlings. EFT tracks high flow events known to be associated with dangerously high river
stage elevations, at four representative locations. During the nesting period these flows and
water levels, while potentially creating future nesting sites, will induce high mortality for the
current year’s cohort of nesting bank swallows. Performance indicator details and science
foundation references are provided in ESSA (2011).
2.2.5 Large Woody Debris Recruitment (LWD1)
Recruitment of old, mature vegetation is an important habitat requirement for western pond
turtles (Actinemys marmorata) and is used as a proxy measurement for potential habitat
quality in the main channel of the Sacramento River. While western pond turtles utilize
oxbow habitats and sloughs, they are also capable of utilizing the main channel under

Chapter 2: Ecological Flow Needs Considered
26 | Page
appropriate conditions. To calculate the amount of large woody debris recruited to the main
channel, EFT incorporates results from its spatially explicit bank erosion model combined
with GIS mapping of mature forest vegetation, to calculate the amount of taller vegetation
added to the river each year. As with the BASW1 performance indicator, bank erosion
calculations are driven by the Meander Migration model. Performance indicator details and
science foundation references are provided in ESSA (2011).
2.2.6 Green Sturgeon Egg Survival (GS1)
Green sturgeon eggs are susceptible to overheating during the April to July spawning and
14-day larval development period of each day-cohort. Warm water temperatures during egg
incubation increase the number of embryos that develop abnormally and reduce hatching
success. Specifically, water temperatures above 17°C reduce egg survival and are lethal
above 20°C. SacEFT uses modeled daily water temperature at two equally-weighted
spawning index locations to simulate the proportion of survival for the larval young-of-year.
Annual summaries are the average of the two locations. Performance indicator details and
science foundation references are provided in ESSA (2011).
2.2.7 Chinook & Steelhead Spawning Habitat (CS1)
Salmonids (four seasonal run-types of Chinook plus steelhead trout) prefer to spawn in
streams with a specific combination of water depth, velocity and gravel composition. EFT
incorporates these preferences based on the River2D model and combines them with daily
flow during the spawning period to calculate and report the weighted available habitat area
for spawning (WUA) at up to five index reaches of the Upper Sacramento River8. Each run-
type follows a calendar which divides the run-type into daily cohorts over the spawning
period. The performance indicator for each reach is calculated by weighting the WUA on
each spawning day by the proportion of adult spawners present during the run-specific
spawning period. Annual summaries are calculated by taking the average of all the reaches
(see Figure 2.6). Because substrate is one of the components of WUA, changes to
substrate composition can affect the overall value of the spawning beds. EFT can
incorporate substrate changes through linkage to The Unified Gravel-Sand model (TUGS;
see Section 2.6.4), which simulates the addition and transport of gravel.
8 Readers interested in why a particular index site was chosen, details of the weighting rules, etc. are referred to Appendix A.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
27 | Page
Figure 2.6: Example spawning WUA relationships for winter-run Chinook, fall-run Chinook
and steelhead for three river segments used by SacEFT. Source/Adapted from:
USFWS (2003).
Performance indicator details and science foundation references are provided in ESSA
(2011).
There is a common misperception that habitat potential is equivalent to spawning
abundance in the EFT model. This is not the case: none of the Chinook or steelhead
performance indicators include explicit treatment of adult spawning populations. They are
measures of habitat potential only, and not of how many actual spawners, eggs or
juveniles make use of the potential habitat. This means that a simulation may result in high
spawning WUA (good habitat potential) but in the real world there could be situations
where very few spawners are present to take advantage of the good habitat (e.g., due to
poor ocean conditions, overfishing, straying or differential use of alternative tributary
habitats, etc.).

Chapter 2: Ecological Flow Needs Considered
28 | Page
2.2.8 Chinook & Steelhead Egg-to-Fry Survival (CS3)
The developing eggs of each of the four seasonal run-types of Chinook and steelhead trout
have specific water temperature requirements to successfully mature. EFT uses
relationships borrowed from the SALMOD model (Bartholow and Heasley 2006), along with
daily water temperature at up to five index reaches to simulate the maturation and
proportional survival of developing eggs. Each run-type follows a calendar which divides the
run-type into daily cohorts over the spawning period. The PI is measured at the reach by
weighting survival using the relative density of each spawning day-cohort. Annual
summaries are calculated by taking the average of all the reaches. Performance indicator
details and science foundation references are provided in ESSA (2011).
2.2.9 Chinook & Steelhead Redd Scour (CS5)
Spawning redds contain the developing eggs of each of the four seasonal run-types of
Chinook and steelhead trout, and are susceptible to extremely high flow events that
mobilize the redd gravel, killing a proportion of the developing eggs/embryos. EFT
combines these high flow events with the species and run-type specific spawning and egg
development calendar to calculate and report the frequency of two levels of extreme flow
events at up to five index reaches, when the developing eggs are sensitive to scour.
Performance indicator details and science foundation references are provided in ESSA
(2011).
2.2.10 Chinook & Steelhead Redd Dewatering (CS6)
Spawning redds contain the developing eggs of each of the four seasonal run-types of
Chinook and steelhead trout, and are susceptible to declining flows that expose and
desiccate the spawning redds. EFT incorporates empirical relationships developed from
GIS bathymetric models to calculate the proportion of spawning WUA habitat exposed
during periods of declining flows which occur between the spawning day and the
emergence of each juvenile day-cohort at up to five index reaches. Each run-type follows a
calendar which divides the run-type in each reach into daily cohorts over the spawning
period, followed by a temperature-based egg development period. The PI is measured at
the reach by weighting the index of dewatering exposure using the relative density of each
spawning day-cohort. Annual summaries are calculated by taking the average of all the
reaches. Performance indicator details and science foundation references are provided in
ESSA (2011).
2.2.11 Chinook & Steelhead Juvenile Rearing Habitat (CS2)
Juveniles of each of the four seasonal run-types of Chinook and steelhead trout prefer to
rear in streams with a specific combination of water depth and velocity. EFT incorporates
these preferences from the River2D model and combines them with daily flow during the
rearing period to calculate and report the weighted available habitat area for rearing (WUA)
at up to five index sections of the Upper Sacramento River. Each run-type follows a

Final Report
Application of EFT to Complement Water Planning for Multiple Species
29 | Page
calendar which divides the run-type into daily cohorts over the rearing period which comes
after the end of egg-maturation. The performance indicator at the reach is then weighted by
the relative density of rearing juveniles present throughout the species and run-specific
rearing period. Annual summaries are calculated by taking the average of all the reaches.
Performance indicator details and science foundation references are provided in ESSA
(2011).
2.2.12 Chinook & Steelhead Juvenile Stranding (CS4)
Free swimming juveniles of each of the four seasonal run-types of Chinook and steelhead
trout typically reside in their natal stream for three to 12 months after emerging from the
gravel. During this period they are susceptible to declining flows that may strand them in
side channels, exposing them to high water temperatures, desiccation and other factors that
heighten rates of mortality. EFT incorporates empirical relationships developed from GIS
bathymetric models to calculate these effects at up to five index reaches of the Sacramento
River. Because juveniles are able to avoid stranding (unlike eggs), it is not possible to
calculate a proportion of juveniles stranded. Instead, stranding is calculated using the same
methodology as redd dewatering (CS6), to provide an index for each reach, of the
proportion of juveniles exposed to stranding during periods of declining flow. The
performance indicator is weighted by the relative density of juveniles present during the
species and run-specific rearing period. Annual summaries are calculated by taking the
average of all the reaches. Performance indicator details and science foundation references
are provided in Appendix A (ESSA 2011).
2.2.13 Chinook & Steelhead – What life-history Attributes are 'Most' Limiting?
Recognizing the commentary above, reviewers of the EFT salmon models and related
performance indicators often request definitive statements about the overall net species
effect when EFT indicator results are mixed. For example, "the models do not clearly tell us
whether improvements in spawning habitat and smolt growth will or will not compensate for
other factors, such as temperature stress". Another classic example in SacEFT is that
rearing WUA and juvenile stranding results are often inversely correlated9. A helpful
approach to this conundrum is to consider some of the fundamental life-history properties of
each run of Chinook and steelhead (including the timing of these events). We discuss some
of the fundamental characteristics of each Chinook run-type below and how these
observations can assist in shaping general interpretation of the importance of various EFT
salmon indicators (i.e., those that tend, all else equal, to be more/less limiting).
The biological significance of a reduction in available spawning habitat varies at the
population level in response to a number of factors, including adult escapement. By far, fall-
run Chinook are presently the most numerous (primarily as a result of considerable
9 This is because potential rearing habitat in SacEFT is used as an input to weight the impact of juvenile stranding, making it
inevitable that as more rearing habitat is created it exposes proportionally more juveniles to stage-flow recession events.

Chapter 2: Ecological Flow Needs Considered
30 | Page
hatchery supplementation) and widely distributed salmon in the Central Valley, and not
reliant on the upper Sacramento River mainstem. They return from the ocean during June
through November and spawn from early October through late December. Fall-run juveniles
enter the ocean at comparably smaller sizes due to the fact that they emigrate relatively
soon after emergence, relying more on early ocean growth than the other run types (Vogel
and Marine 1991; NMFS 1997, 2009; Moyle et al. 2008).
A daily average water temperature of 60°F (15.6°C) is considered the upper temperature
limit for growth and rearing of outmigrating Chinook juveniles (NMFS 1997). Currently, a
56°F (13.3°C) compliance point is used at Bend Bridge near the town of Red Bluff. Water
temperatures below this point warm rapidly. Summer water temperatures in many California
rivers already exceed 71.6°F (22°C) (Katz et al. 2012). Thus, small thermal increases in
summer water temperatures can result in suboptimal or lethal conditions and consequent
reductions in salmonid distribution and abundance.
The migration of juvenile Chinook salmon from their riverine origin to the food-rich ocean is
considered one of the most vulnerable periods of the life-cycle. Mark recapture studies with
fall-run Chinook salmon have suggested that salmon smolts entering the central Delta via
the Delta Cross Channel and Georgiana Slough have a much lower survival index than
those remaining in the mainstem Sacramento River (NMFS 1997). An important refuge and
stronghold for foraging and growth, access to productive floodplain rearing habitat is
expected to be a major benefit to all run types of Chinook, especially given historical habitat
loss and simplification.
Late fall-run Chinook spawn December through January, when water temperatures are the
least difficult to manage. They migrate and spawn at times when the rivers are high, cold,
and turbid, hence, spawning flows are generally not the primary limiting factor (NMFS 1997,
2009). Late fall-run Chinook are found mostly in the Sacramento River between the Red
Bluff Diversion Dam and Keswick Dam. Small numbers also spawn in Battle Creek,
Cottonwood Creek, Clear Creek, Mill Creek, as well as in the Yuba and Feather Rivers. Like
fall-run Chinook, this population is also largely sustained by hatchery production. Late fall-
run Chinook normally benefit from conservation actions taken for winter-run Chinook (Moyle
et al. 2008; NMFS 2009).
Spring-run Chinook make use of the mainstem Sacramento River and several tributaries.
As a consequence, spawning habitat in the mainstem Sacramento River is a concern but
not the primary stressor/limiting factor (NMFS 1997, 2009). Only three extant independent
populations exist, and they are especially vulnerable to disease or catastrophic events
because they are in close proximity. Water temperatures during adult migration, holding,
and spawning are one of the most significant stressors for this run type. Adult spring-run
Chinook salmon require freshwater streams with cold temperatures over the summer and
suitable gravel for reproduction. Spring-run Chinook salmon are immature when upstream
migration begins and need to hold in suitable habitat for several months prior to spawning.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
31 | Page
While immature, the maximum suitable water temperature for holding is 59°F (15°C) to 60°F
(15.6°C) (NMFS 1997). Suitable water temperatures for adult spring-run Chinook salmon
migrating upstream to spawning grounds range from 57°F (13.9°C) to 67°F (19.4°C) (NMFS
1997). Emergence typically occurs from January through as late as May (NMFS 2009). For
maximum embryo survival, water temperatures during incubation should be between 41ºF
(5°C) and 55.4ºF (13°C) and oxygen levels must be close to saturation (Moyle 2002, as
cited in NMFS 2009). Fortunately, in many streams these temperatures are frequently
possible during the November to January incubation period. The Central Valley spring-run
Chinook salmon population is spatially confined to relatively few remaining streams,
continues to display broad fluctuations in abundance, and a large proportion of the
population (i.e., in Butte Creek) faces the risk of high mortality rates due to elevated water
temperatures during the adult holding period (NMFS 2009). Additionally, Delta conditions
are considered more of a limiting factor for spring-run (and winter-run) relative to the fall
runs (NMFS 2009).
Spawning escapements of winter-run Chinook salmon in the Sacramento River have
declined from near 100,000 in the late 1960s to less than 200 in the early 1990s (Good et
al. 2005, as cited in NMFS 2009). The construction and operation of Shasta Dam
immediately reduced the winter-run Chinook salmon range from four independent
populations to just one (NMFS 2009). As a result, winter-run Chinook spawn almost entirely
in the Sacramento River and a few tributaries upstream of Red Bluff. NMFS winter-run
Chinook recovery plans list Sacramento River spawning flows and embryo incubation flow
fluctuations amongst the highest stressor categories/limiting factors (NMFS 2009). The
remaining available spawning habitat, including the mainstem Sacramento River, is
currently maintained with cool water releases from Shasta and Keswick dams. Adults arrive
as early as December, with spawning occurring from March through August. Water
temperatures are the second most highly weighted stressor category in National Oceanic
and Atmospheric Administration (NOAA) Fisheries winter-run Chinook recovery planning
documents (NMFS 2009). The embryo incubation life stage (includes the June to August
period) of winter-run Chinook salmon is very sensitive to elevated water temperatures
(NMFS 2009). Preferred water temperatures for Chinook salmon egg incubation and
embryo development range from 46°F (7.8°C) to 56°F (13.3°C) (NMFS 1997). A significant
reduction in egg viability occurs at water temperatures above 57.5°F (14.2°C) and total
mortality may occur at 62°F (16.7°C) (NMFS 1997). Additionally, dropping incubation flows
from 13,000 cfs to 5,500 cfs would result in dewatering 21% of winter-run redds (USFWS
2006).
Winter-run Chinook spend much longer in freshwater and typically enter the ocean at
comparably larger sizes. As a consequence, Delta conditions represent a relatively greater
limiting factor for winter-run (and spring-run) than for the fall runs. Water temperatures in the
Delta are generally suitable throughout the winter-run Chinook salmon adult immigration
and holding life stage period except for during June and July. Water temperatures in the

Chapter 2: Ecological Flow Needs Considered
32 | Page
Delta likely do not adversely affect winter-run Chinook salmon juveniles until the late spring
(NMFS 1997).
Steelhead use tributaries extensively, and are not restricted/reliant on the Sacramento River
mainstem. In the Central Valley, steelhead are also produced in large quantities by
hatcheries, not by wild spawning fish. Steelhead use seasonal habitats of intermittent
streams for spawning and rearing. As a consequence, water temperatures are one of the
most important stressors for this species (NMFS 2009).
The overall importance of each stressor, the relative degree each is thought to be limiting
for EFT salmon performance indicators, is shown in Table 2.2.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
33 | Page
Table 2.2: Relative importance of each EFT salmon performance indicator by run type. Details on Delta performance indicators
are provided below.
Relative importance of stressor and degree of limitation
Performance indicator
Fall
Late Fall
Spring
Winter
Steelhead
Sacramento
ecoregion
Suitable spawning habitat (CS1)
[Sacramento mainstem]
Thermal egg-to-fry survival (CS3)
Redd dewatering (CS6)
Redd scour risk (CS5)
Juvenile stranding (CS4)
Suitable rearing habitat (CS2)
Delta ecoregion
Smolt weight gain (CS7)
Smolt predation risk (CS9)
Smolt temperature stress (CS10)

Chapter 2: Ecological Flow Needs Considered
34 | Page
2.3 Key Attributes of SacEFT Performance Indicators
Most of EFT’s performance indicators are calculated on a daily (or finer) time-step at
multiple index locations. Naturally, these daily calculations come in many different units
appropriate to the performance indicator (e.g., square feet of suitable habitat, survival rates,
counts of surviving cottonwood seedlings, etc.). Further, the daily calculations for most
aquatic performance indicators (see above) are weighted by the appropriate life-history
distributions as well as by differences in habitat quantity/quality among the modeled index
sites. For example, if a sudden dramatic low flow event occurs at the very beginning or very
end of the egg incubation period for a particular Chinook run-type, the weighted effect on
the overall cumulative redd dewatering performance indicator (CS6) will be negligible.
Table 2.3 summarizes the units, overall nature of the calculations and general location
weighting and roll-up methods for SacEFT performance indicators (details are available in
ESSA 2011). Related background on driving physical data and fundamental concepts
behind EFT are provided in Section 2.6. The default relative suitability threshold
assumptions used to "roll-up" annual water year performance are given in Section 2.7.2 and
Appendix G.
Table 2.3: SacEFT performance indicators (SacEFT Ecoregion) – units, overall calculation,
weighting and roll-up attributes.
Indicator Name
Native units
PI Calculation
Location weights/roll-up
FC1
Cottonwood
initiation
Index
Daily stage recession at selected
cross sections is coupled to potential
root growth during seed dispersal
period
Annual sum of counts of
successful initiation at 10 locations
between RM 159–208
FC2
Cottonwood
scour risk
Index
Very high scouring flow during good
FC1 years reduces survival
Sum over all cross sections and
cross section nodes (no weighting)
BASW1
Bank swallow
habitat potential
Bank length
(m)
Annual new river bank exposed due
to channel migration
River bends from RM 170-222 are
added
BASW2
Bank swallow
inundation risk
Index
High scouring flow during nest period
reduces survival
Four locations with equal weight
are averaged
LWD1
Large woody debris
recruitment
Area
(ha)
GIS-based areas of old-growth
vegetation are coupled to channel
migration
Total channel migration on old
growth river bends are added from
RM 170-222
GS1
Green sturgeon
egg-to-larvae
survival
Survival
Proportion
(0–1)
Daily temperature above
physiological limit reduces survival
Two locations with equal weight
are averaged

Final Report
Application of EFT to Complement Water Planning for Multiple Species
35 | Page
Indicator Name
Native units
PI Calculation
Location weights/roll-up
CS1
Chinook &
steelhead spawning
habitat
WUA
(000s ft2)
Sum of daily WUA multiplied by daily
calendar weight during the spawning
period
Up to five locations are weighted
equally to allow for summing WUA
across all locations
CS3
Chinook &
steelhead
egg-to-fry survival
Survival
Proportion
(0–1)
Cumulative egg-to-fry survival during
egg-development period, weighted
by daily spawning distribution
Up to five locations are weighted
equally to allow for averaging
across all locations
CS5
Chinook &
steelhead
redd scour
Peak flow
(scour days)
Number of days exceeding scouring
flow criteria
Up to five locations are weighted
equally for averaging across all
locations
CS6
Chinook &
steelhead
Redd
dewatering
Proportion
(0–1)
Cumulative exposure from weighted
daily spawning distribution and daily
decline in flow during the egg
development period
Up to five locations are weighted
equally to allow for averaging
across all locations
CS2
Chinook &
steelhead
rearing
habitat
WUA
(000s ft2)
Weighted average rearing area based
on spawning emergence distribution
and residency period
Up to five locations are weighted
equally to allow for summing WUA
across all locations
CS4
Chinook &
steelhead juvenile
stranding
Stranded
juveniles
(index)
Index of cumulative juvenile
stranding based on weighted
spawning-emergence distribution
and residency period
Up to five locations are weighted
equally to allow for averaging
across all locations
2.3.1 Ecologically Important Index Locations
The study area of SacEFT extends from Keswick Dam to Colusa. Each performance
indicator in SacEFT is referenced to at least one, usually multiple locations, either at a point
location or along a reach. SacEFT currently uses either USRDOM or USRWQM daily
modeled flows. Daily water temperatures for SacEFT are also provided by USRWQM.
Appendix H summarizes the spatial location and resolution for all performance indicators in
SacEFT, and provides the mapping of how CALSIM, USRDOM and USRWQM modeled
output locations map to location in EFT.
2.3.2 Ecologically Important Life-history Timing
Almost all of SacEFT indicators have a sub-annual temporal component which is important
to the simulation of life histories. Details on key life-history timing windows for SacEFT
indicators are summarized in Table 2.4 and described in ESSA (2011).

Chapter 2: Ecological Flow Needs Considered
36 | Page
Table 2.4: Summary of timing information relevant to the SacEFT focal species. Lightly
shaded regions denote the 25% “tails” for some indicators. Source: salmonids:
SALMOD (Bartholow and Heasley 2006, ultimately Vogel and Marine 1991); all
other indicators: ESSA 2011.
Performance Indicator
J
F
M
A
M
J
J
A
S
O
N
D
Fremont Cottonwood Initiation (FC1)
Fremont Cottonwood Scour (FC2)
Bank Swallow N (BASW1)
Bank Swallow Sloughing (BASW2)
Green Sturgeon Egg (GS1)
Large Woody Debris (LWD1)
Spring Spawning (CS 1)
Spring Egg (CS 3,5,6)
Spring Juvenile (CS 2,4)
Fall Spawning (CS 1)
Fall Egg (CS 3,5,6)
Fall Juvenile (CS 2,4)
Late Fall Spawning (CS 1)
Late Fall Egg (CS 3,5,6)
Late Fall Juvenile (CS 2,4)
Winter Spawning (CS 1)
Winter Egg (CS 3,5,6)
Winter Juvenile (CS 2,4)
Steelhead Spawning (CS 1)
Steelhead Egg (CS 3,5,6)
Steelhead Juvenile (CS 2,4)
2.4 San Joaquin-Sacramento Delta Ecoregion Ecological Objectives
& Performance Indicators
A total of seven focal species and habitats and their 13 distinct PIs are represented within
the DeltaEFT ecoregion (Figure 2.7). In the case of salmonids, steelhead trout and four
Chinook run-types share a common PI framework.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
37 | Page
Figure 2.7: DeltaEFT includes the seven species and habitat groups shown.
The PIs are listed along with a narrative summary in Table 2.5. More details about the PI
calculation and default relative suitability thresholds are presented in Section 2.7.2 and
Appendix G. Functional details are available in Appendix D (ESSA 2013). Key attributes of
each performance indicator (e.g., units, key index locations) are provided in Section 2.5.

Chapter 2: Ecological Flow Needs Considered
38 | Page
Table 2.5: Summary of DeltaEFT ecological objectives for each focal species and their
associated performance indicators.
Delta Ecoregion
Focal Species
& Habitats
Ecological Objectives
Performance Indicators
Chinook salmon
Steelhead trout
Promote smolt weight gain
by providing enhanced
rearing in Yolo Bypass
Reduce non-entrainment
mortality through flow
management in Bay-Delta
Provide preferred
temperature range for
resident smolts
CS7
CS9
CS10
Juvenile development in Yolo Bypass
(% weight gain)
Juvenile mortality risk (passage time) (d)
Juvenile temperature stress (°C-d)
Delta smelt
Provide cold water
spawning habitat
Provide appropriate adult
abiotic environment
Reduce entrainment risk
through effect of flow on X2
location
DS1
DS2
DS4
Spawning success (index)
Habitat suitability (index)
Entrainment risk (index)
Longfin smelt
Provide appropriate abiotic
environment
LS1
Abundance (index)
Splittail
Provide extensive period
for spawning
SS1
Potential spawning habitat (proportion)
Tidal wetlands
Provide productive habitat
for ecosystem
Provide appropriate abiotic
environment
TW1
TW2
Brackish wetland area (ha)
Freshwater wetland area (ha)
Invasive deterrence
Suppress invasive aquatic
vegetation
Suppress invasive clams
ID1
ID2
ID3
Suppression of Brazilian waterweed Egeria
(index)
Suppression of overbite clam Corbula
(index)
Suppression of Asiatic clam Corbicula
(index)
As shown, while we include multiple subcomponent effects at a variety of life stages (in the
case of salmonids), we intentionally avoid attempting to measure effects at the population

Final Report
Application of EFT to Complement Water Planning for Multiple Species
39 | Page
level. Attempting to build detailed ecological models that make accurate predictions of
ecosystem behavior is challenging and usually not possible in complex, open natural
systems (Oreskes et al. 1994). As described in Section 2.6 and in Chapter 3 we instead
gauge overall effects of flow management and climate change using weight of evidence net
effect scoring. Where feasible, our indicators also weight life-stage outcomes by the
proportion of the population in that life stage that is affected. While life-cycle modeling
can aid in the determination of net effects for a species when sub-stage effects are
inversely correlated, it is still possible to draw overall conclusions about the effect of
alternative scenarios in the absence of such detailed modeling. Ultimately, ongoing
adaptive management and long-term monitoring programs are required to continually test
and improve conceptual models of all forms.
2.4.1 Chinook & Steelhead Juvenile Development in Yolo Bypass (CS7)
When it is inundated during sustained periods of high flow, Yolo Bypass provides a high
quality off-channel environment for enhanced growth of the four seasonal run-types of
migrating Chinook and steelhead. During their downstream passage from Knights Landing
to Mallard Island, juveniles follow migration calendars that are unique to the run-type. Day-
cohorts travel along multiple routes based on a go-with-the-flow rule, potentially migrating
over Fremont Weir, Sacramento Weir or through the main channel of the Sacramento River.
While travelling along up to three routes, migration distance varies with daily flow at
locations along the route, and growth rate depends on the temperature and productivity of
the route. The annual PI for the entire year-cohort is measured as the proportional
contribution to total biomass gain for the subset of the entire population travelling along
each route. Performance indicator details and science foundation references are provided in
ESSA (2013).
2.4.2 Chinook & Steelhead Predation Risk (CS9)
During their downstream migration, juveniles of the four seasonal run-types of Chinook and
steelhead are exposed to predators. Routes or scenarios which offer shorter migration
times will have lower mortality. During their downstream migration from Hood to Mallard
Island, juveniles follow calendars that are unique to the run-type. Predation risk is currently
defined for the main channel of the Sacramento River only. Daily migration distance varies
with flow, measuring the passage time from the upstream location at Hood, to the
downstream location at Rio Vista. Performance indicator details and science foundation
references are provided in ESSA (2013).
2.4.3 Chinook & Steelhead Thermal Stress (CS10)
During their downstream migration, juveniles of the four seasonal run-types of Chinook and
steelhead are exposed to different thermal environments. Day-cohorts of each run-type
follow calendars that are unique to the run-type, migrating from Hood to Mallard Island
based on a go-with-the-flow rule, through six alternative routes in the western and eastern
Delta. Along each route, daily migration distance varies with flow, and growth rate depends

Chapter 2: Ecological Flow Needs Considered
40 | Page
on the temperature along the route. Routes and days which are cooler or warmer than the
physiological optimum will result in lower growth over the course of their passage, providing
a measure of thermal stress in units of absolute value degree-days. The annual PI for the
entire year-cohort is measured as the proportional contribution to degree-days for the
subset of the entire population travelling along each route. Performance indicator details
and science foundation references are provided in ESSA (2013).
2.4.4 Delta Smelt Spawning Success (DS1)
Spawning success of Delta smelt (Hypomesus transpacificus) is based on evidence which
suggests that spring water temperatures affect the spawning success of the population. The
DS1 index is modeled as the longest duration of continuous days with optimal spawning
conditions. Those conditions are defined as days with an average temperature between 12
and 16°C (the range associated with peak occurrence of ripe females), which also coincides
with salinities <6‰, an empirical upper threshold, below which over 90% of Delta smelt are
observed. DS1 is simulated at 22 locations selected to be representative of the entire Delta.
Since spawning locations are unknown, all locations are weighted equally. Performance
indicator details and science foundation references are provided in ESSA (2013).
2.4.5 Delta Smelt Habitat Suitability (DS2)
The DS2 habitat suitability performance indicator is based on the widely-used X2-Habitat
Index relationship that was incorporated into the Reasonable and Prudent Alternative (RPA)
for the 2008 Delta Smelt Biological Opinion. The relationship is based on a model that
estimates the probability of occurrence of Delta smelt as a function of water temperature,
Secchi depth (a surrogate for turbidity), and specific conductance (a proxy for salinity). The
daily X2 location is estimated based on historical and modeled data from five salinity
stations in the Sacramento River between river kilometer 54 and 92. The salinity gradient
between stations is assumed to be linear, and the location of the 2‰ concentration which
defines the X2 position is found by interpolating between stations. The relative suitability
threshold breakpoints are equivalent to the X2 targets of 74 and 81 km described in the
2008 Delta Smelt Biological Opinion. Performance indicator details and science foundation
references are provided in ESSA (2013).
2.4.6 Delta Smelt Entrainment Risk (DS4)
The index of risk of entrainment for Delta smelt is based on a Particle Tracking Model
(PTM) which simulates the fate of particles released at 20 sites in the Delta under a range
of inflows and exports. Entrainment is simulated as the proportion of particles which
ultimately end up at the Central Valley Project (CVP) or State Water Project (SWP) water
export facilities. In order to utilize the results from the PTM, which simulates passive,
neutrally buoyant particles, it is applied only to the larval and juvenile life-stages, which
have a limited capacity for active swimming. Using the entrainment simulations, the model
is based on a logistic regression relating the Export:Import ratio to entrainment, using daily
combined Old River and Middle River flow, weighted by a calendar-based spawning

Final Report
Application of EFT to Complement Water Planning for Multiple Species
41 | Page
probability relationship. Finally multiple locations in the Delta are combined based on
weights derived from empirical sampling studies. Performance indicator details and science
foundation references are provided in ESSA (2013).
2.4.7 Longfin Smelt Abundance Index (LS1)
The longfin smelt abundance index is based on a statistical relationship developed by
Mount et al. (2013). The study developed a linear regression model relating the average X2
value from January to June to a Log10 transformation of the annual index of longfin smelt
abundance from the fall midwater trawl survey. The relationship was developed for three
time periods and we applied the regression coefficients based on 2003 to 2012 data, i.e.,
after the pelagic organisms decline. The daily X2 location is estimated based on historical
and modeled data from five salinity stations in the Sacramento River between river
kilometer 54 and 92. The salinity gradient between stations is assumed to be linear and the
location of the 2‰ concentration is found by interpolating between stations. Performance
indicator details and references are provided in ESSA (2013).
2.4.8 Splittail Potential Spawning Habitat (SS1)
Sacramento splittail (Pogonichthys macrolepidotus) spawn in shallow flowing waters
characterized by dense vegetation, low temperature and high clarity. Although they may
spawn opportunistically at any time, most spawning in Yolo Bypass occurs between
February and April. Eggs are deposited in waters of <2 m in depth and undergo a shallow-
water development period of 15 days before they can tolerate greater depths. Potential
spawning habitat in Yolo Bypass is simulated over the spawning calendar using an
empirical relationship between flow and depth, so that each day’s flow can be converted to
the area <2 m depth. Using the flow-area relationship, each day-cohort is simulated over its
development period, and the minimum area during that period is used to assign a spawning
potential score for the day-cohort. The score for each day-cohort is then scaled by the
maximum possible habitat area (about 32 acres), to derive a weighted proportional area
which can then be summed over the spawning calendar to provide the correctly weighted
proportional spawning area for the year. Performance indicator details and science
foundation references are provided in ESSA (2013).
2.4.9 Brackish Wetland Area (TW1)
The brackish wetland performance indicator is used to estimate the wetland area under
different EFT scenarios. Three index locations within Suisun Bay are used to represent
brackish conditions near sites identified as BDCP Restoration Opportunity Areas (ROAs),
and include a range of tidal influences and salinity concentrations. The ROAs themselves
are excluded, as they are mostly located in managed wetlands or farmed lands that have
subsided, whose elevation will have to be raised in order to recreate a functional tidal
wetland. Brackish wetland is calculated as the area at the index locations between annual
Mean Tide Level (MTL) and Extreme High Water (EHW), based on simulations of hourly
stage (water elevation). These two thresholds are combined with a LiDAR-based Digital

Chapter 2: Ecological Flow Needs Considered
42 | Page
Elevation Model (DEM) to compute the area within the two elevations. Performance
indicator details and science foundation references are provided in ESSA (2013).
2.4.10 Freshwater Wetland Area (TW2)
The freshwater wetland performance indicator is used to estimate the wetland area under
different EFT scenarios. Two index locations (Shin Kee Tract, Big Break) are used to
represent freshwater conditions near sites identified as BDCP ROAs. The ROAs
themselves are excluded, as they are mostly located in managed wetlands or farmed lands
that have subsided, whose elevation will have to be raised in order to recreate a functional
tidal wetland. Freshwater wetland is calculated as the area at the index locations between
Mean Tide Level (MTL) and Extreme High Water (EHW), based on simulations of hourly
stage (water elevation). These two thresholds are combined with a LiDAR-based Digital
Elevation Model (DEM) to compute the area within the two elevations. Performance
indicator details and science foundation references are provided in ESSA (2013).
2.4.11 Brazilian Waterweed Suppression (ID1)
The ID1 performance indicator is a categorical indicator which models the likelihood of
suppression of Brazilian waterweed (Egeria densa), using simple rules based on expert
assessment of the role of variations in net Delta outflow and salinity in two regions (eastern
Suisun Bay and the western part of the interior Delta), using a total of eight measurement
locations to calculate the average salinity for a region. Brazilian waterweed prefers a nearly
freshwater environment of <5‰, and according to this model there is a high likelihood of
suppression if salinity exceeds 10‰ for three months between May and October in at least
40% of all years. This condition is expected to be met predominantly during low flow years.
Combined with consistent higher salinity, the categorical response model is further
influenced by the rate of salinity change, so that rapid “shocks” of increased salinity improve
the likelihood of suppression. Performance indicator details and science foundation
references are provided in ESSA (2013).
2.4.12 Overbite Clam Suppression (ID2)
The ID2 performance indicator is a categorical indicator which models the likelihood of
suppression of the overbite clam (Corbula amurensis)10, using simple rules based on expert
assessment of variations in net Delta outflow and salinity in three regions within the eastern
Suisun Bay and the western part of the interior Delta, using a total of 15 measurement
locations to calculate the average salinity for a region. The overbite clam prefers a brackish
environment of 5‰ - 10‰, and according to this model there is a high likelihood of
suppression if salinity lies below 3‰ or above 30‰ between December and April, in at least
half of all years. The non-brackish condition is expected to be met predominantly during
very high flow years. Combined with these constraints, the categorical response model is
10 The species is also known as Potamocorbuila amurensis

Final Report
Application of EFT to Complement Water Planning for Multiple Species
43 | Page
also affected by the rate of salinity change, so that rapid “shocks” of decreased salinity
improve the likelihood of suppression. Performance indicator details and science foundation
references are provided in ESSA (2013).
2.4.13 Asiatic Clam Suppression (ID3)
The ID3 performance indicator is a categorical indicator which models the likelihood of
suppression of Asiatic clam (Corbicula fluminea) larvae and young recruits, using simple
rules based on expert assessment of variations in net Delta outflow and salinity in two
regions (eastern Suisun Bay and the western part of the interior Delta) using a total of eight
measurement locations to calculate the average salinity for a region. The Asiatic clam
prefers a nearly freshwater environment of <10‰, and according to this model there is a
high likelihood of suppression if salinity exceeds 12‰ for three months between May and
October in at least 40% of all years. This condition is expected to be met predominantly
during low flow years. Combined with consistent higher salinity, the categorical response
model is further influenced by the rate of salinity change, so that rapid “shocks” of increased
salinity improve the likelihood of suppression. Performance indicator details and science
foundation references are provided in ESSA (2013).
Details on all default relative suitability thresholds used to summarize and "roll-up" EFT
results are discussed in more detail in Section 2.7.2 and Appendix G.
2.5 Key Attributes of DeltaEFT Performance Indicators
Table 2.6 summarizes the units, overall nature of the calculations, and general location
weighting and roll-up methods for DeltaEFT performance indicators (details are available in
ESSA 2013). Related background on driving physical data and fundamental concepts
behind EFT are provided in Section 2.6. The relative suitability threshold assumptions used
to "roll-up" annual water year performance are given in Section 2.7.2 and Appendix G.

Chapter 2: Ecological Flow Needs Considered
44 | Page
Table 2.6: DeltaEFT performance indicators (Delta Ecoregion) – units, overall calculation,
weighting and roll-up attributes.
Indicator Name
Native units
PI Calculation
Location weights/roll-up
CS7
Chinook &
steelhead
juvenile
development
in Yolo
Weight
gain
(%)
% weight gain for each day-cohort on
each route; high flow routes have
more fish
Up to three routes through delta
network, weighted to allow
addition of routes
CS9
Chinook &
steelhead
juvenile
mortality
risk
Passage
Time
(days)
Passage days for each day-cohort on
each route; high flow routes have
more fish
One route through delta network
CS10
Chinook &
steelhead
juvenile
temperature
preference
Thermal
stress
(°C-days)
Degree-days departure from
optimum temperature for each day-
cohort on each route; high flow
routes have more fish
Six routes through delta network,
weighted to allow addition of
routes
DS1
Delta smelt
spawning
success
Index
(days)
Daily temperature and salinity at
numerous locations are compared to
observed preferences during spring
spawning period
All 24 locations are equally
weighted with the daily spawning
calendar to average optimum
days across all locations
DS2
Delta smelt
habitat suitability
Index
Based on fitted relationship between
X2 location and abiotic needs in Sep-
Dec period
Annual average of index value
over period
DS4
Delta smelt
entrainment risk
Entrainment
Proportion
(0–1)
Daily entrainment risk at numerous
sites based on spawning calendar
coupled to Particle Tracking Model
results and Old & Middle River flow
Annual sum of entrainment based
on daily weights
LS1
Longfin smelt
abundance
Index
Based on fitted relationship between
X2 location and longfin smelt
abundance in Jan-Jun period
Only one location
SS1
Splittail
spawning
habitat
Proportion
maximum
(0–1)
Daily proportion of total possible
habitat area during peak spawning
period
Annual sum of daily-weighted
percentage in Yolo Bypass
TW1
Brackish tidal
wetland
Area
(ha)
Area in upper tidal zone, based on
GIS/DEM maps
Annual sum in 3 brackish water
index locations
TW2
Freshwater tidal
Area
(ha)
Area in upper tidal zone, based on
GIS/DEM maps
Annual sum of 2 freshwater index
locations

Final Report
Application of EFT to Complement Water Planning for Multiple Species
45 | Page
Indicator Name
Native units
PI Calculation
Location weights/roll-up
wetland
ID1
Egeria
suppression
Index
High mid-year salinity, consistently
over years, including “shocks” of
rapid change
Annual average index over 8
locations in 2 regions
ID2
Corbula
suppression
Index
High or low winter-spring salinity,
consistently over years, including
“shocks” of rapid change
Annual average index over 15
locations in 3 regions
ID3
Corbicula
suppression
Index
High mid-year salinity, consistently
over years, including “shocks” of
rapid change
Annual average index over 8
locations in two regions
2.5.1 Ecologically Important Index Locations
Each performance indicator in DeltaEFT is referenced to at least one location (usually
multiple locations) either at a point location or at a polygon or series of alternative routes.
Depending on the performance indicator, DeltaEFT currently uses one or more of four
physical outputs simulated by DSM2: flow, electroconductivity, water temperature, and/or
stage. Location names assigned by DSM2 and the California Data Exchange Center
(CDEC) are not fully standardized. Appendix H summarizes the spatial location and
resolution for all performance indicators in DeltaEFT, which also provides the mapping of
how DSM2 modeled output locations map to location in EFT.
2.5.2 Ecologically Important Life-history Timing
Almost all of DeltaEFT indicators have a sub-annual temporal component that is important
to the simulation of its life-history. Details on key life-history timing windows for DeltaEFT
indicators are summarized in Table 2.7, and described in ESSA (2013).

Chapter 2: Ecological Flow Needs Considered
46 | Page
Table 2.7: Summary of timing information relevant to the DeltaEFT focal species. Lightly
shaded regions denote the 25% “tails” for some indicators.
Performance Indicator
J
F
M
A
M
J
J
A
S
O
N
D
Spring smolt migration (CS 7,9,10)
Fall smolt migration (CS 7,9,10)
Late Fall smolt migration (CS 7,9,10)
Winter smolt migration (CS 7,9,10)
Steelhead smolt migration (CS 7,9,10)
Delta smelt spawning success (DS1)
Delta smelt habitat suitability (DS2)
Delta smelt entrainment risk (DS4)
Longfin smelt abundance (LS1)
Splittail spawning habitat (SS1)
Brackish tidal wetland (TW1)
Freshwater tidal wetland (TW2)
Egeria suppression (ID1)
Corbula suppression (ID2)
Corbicula suppression (ID3)
2.6 Coupled Modeling – Hydrologic & Physical Foundations
In our experience, and reiterated by many workshop participants during the history of this
project, it is exceedingly rare for "one" decision support platform to satisfy all objectives.
Model coupling offers a practical and feasible way forward to overcome a number of gaps
and limitations. Coupled modeling –– the approach used by EFT –– involves sequentially
running independent models, and matching model outputs from the preceding tool with the
input requirements of the next model in the chain. EFT uses a coupled hydrologic and
physical modeling foundation based on existing physical models that are commonly used
for water planning in California's Central Valley. Rather than reinventing models, EFT
currently utilizes output data sets from the daily disaggregation of CALSIM II, USRWQM,
DSM2, and other models that are used to investigate water delivery and other standards set
for the CVP and SWP in California (Figure 2.8). EFT utilizes these data and adds ecological
calculations to evaluate effects on multiple ecosystem targets. This is accomplished by
loosely coupling groups of models and running them serially, rather than attempting to
"build in" EFT algorithms directly into the external physical models11 (or vice versa). EFT
focal species submodels are integrated and centered on a single relational database. The
EFT software’s graphical user interface, model controller and analysis engine, and output
reporting tools, connect to and interact with this central database over the internet.
Figure 2.8 shows the external physical modeling system on top of which EFT provides an
ecological effects “plug-in”. Some of these models generate results for the Sacramento
11 Though Chapter 4 describes a pilot investigation that demonstrates how EFT flow criteria can be extracted and transplanted into
CALSIM.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
47 | Page
River ecoregion, others for the Delta ecoregion (or both). A brief summary and links to
further references on these foundational hydrologic modeling tools are provided below.
In addition to these models, select gauging records are used for river discharge, stage,
salinity, and water temperatures. Using data from models and stream gauges permits mixed
prospective and retrospective analyses.
Figure 2.8: Current EFT hydrologic foundation. EFT is designed to swap in any model which
provides data at the locations shown in Appendix H.
2.6.1 CALSIM II
The California Department of Water Resources (DWR)/U.S. Bureau of Reclamation
(Reclamation) CALSIM II planning model is used to simulate the operation of the CVP and
SWP over a range of hydrologic conditions. CALSIM II is a generalized reservoir-river basin
simulation model that allows for specification and achievement of user-specified allocation
targets, or goals (Draper et al. 2004). CALSIM II represents the most commonly used
planning model for the SWP and CVP system operations and has been used in many
previous system-wide evaluations of SWP and CVP operations as well as BDCP. CALSIM II
produces monthly outputs for river flows and diversions, reservoir storage, Delta flows and
exports, Delta inflow and outflow, deliveries to project and non-project users, and controls
on project operations.
Inputs to CALSIM II include water diversion requirements (water demands), stream
accretions and depletions, rim basin inflows, irrigation efficiencies, return flows, non-
Sacramento
River
Delta
CALSIM-II
Monthly flows
USRDOM
Daily flow disagregation
Northern boundary =
Keswick
Southern boundary =
Knights Landing
SRWQM
Daily flow
disagregation
Daily water
temperatures
Same boundaries as
USRDOM
The Unified
Gravel-Sand
(TUGS) sediment
transport model
Meander Migration
(MM) model
DSM2 (HYDRO-QUAL-PTM)
Flow, stage, salinity, water temperature, particle
fate, turbidity (if avail.)
Tides, hydrodynamics
Boundary conditions = stage at Martinez, monthly
water diversions into Delta
Own node-link representation
EFT
Database Hydro-
ecological
response
algorithms
“Plug-in”

Chapter 2: Ecological Flow Needs Considered
48 | Page
recoverable losses, and groundwater operations. Sacramento Valley and tributary rim basin
hydrologies are developed using a process designed to adjust the historical sequence of
monthly stream flows over an 82-year period (1922 to 2003) to represent a sequence of
flows at a future level of development.
The CALSIM II simulation model uses single time-step optimization techniques to route
water through a network of storage nodes and flow arcs based on a series of user-specified
relative priorities for water allocation and storage. Physical capacities and specific
regulatory and contractual requirements are input as linear constraints to the system
operation using the water resources simulation language (WRESL). The process of routing
water through the channels and storing water in reservoirs is performed by a mixed integer
linear programming solver. For each timestep, the solver maximizes the objective
function to determine a solution that delivers or stores water according to the specified
priorities and satisfies all system constraints. The sequence of solved linear programming
problems represents the simulation of the system over the period of analysis.
Adjustments to historic water supplies are determined by imposing future level land use on
historical meteorological and hydrologic conditions. The resulting hydrology represents the
water supply available from Central Valley streams to the CVP and SWP at a future level of
development. CALSIM II uses rule-based algorithms for determining deliveries to North-of-
the-Delta and South-of-the-Delta CVP and SWP contractors. This delivery logic uses runoff
forecast information, which incorporates uncertainty and standardized rule curves. The rule
curves relate storage levels and forecasted water supplies to project delivery capability for
the upcoming year. The delivery capability is then translated into SWP and CVP contractor
allocations which are satisfied through coordinated reservoir-export operations.
Reclamation’s 2008 Operations Criteria and Plan (OCAP) Biological Assessment (BA)
Appendix D provides more information about CALSIM II (USBR 2008a).
CALSIM II results are also used to estimate water quality, hydrodynamics, and particle
tracking in the DSM2 model. The outputs feed into temperature models including the Upper
Sacramento River Water Quality Model (USRWQM) and the Reclamation Temperature
Model, and have been used to inform other habitat and biological assessments.
2.6.2 USRDOM / USRWQM
USRDOM
The Upper Sacramento River Daily Operations Model (USRDOM) is designed to model the
flows and related operations in the upper Sacramento River from Keswick to Knights
Landing on a daily timescale. The model is designed to simulate both low flow (water
supply) and high flow (flood) operations in order to improve the weak performance of the
Upper Sacramento River Water Quality Model (USRWQM) at flows above 15,000 cfs. A
critical element is the local runoff between Keswick Reservoir and Bend Bridge where

Final Report
Application of EFT to Complement Water Planning for Multiple Species
49 | Page
cumulative flows from unregulated tributaries can exceed 100,000 cfs during large rainfall or
flooding events. Daily outputs such as inflows, outflows, diversions and end-of-the day
storage conditions are used as inputs to USRWQM instead of using the results from a
CALSIM II daily disaggregation routine. The full 82-year period of monthly CALSIM II
operations data is translated to a daily timestep by a utility called CAL2DOM. It uses inputs
and outputs from CALSIM II, USRDOM hydrology, and other datasets to compute inflows,
diversions, and evaporation rates for USRDOM. Because the spatial resolution between
USRDOM and CALSIM II is inconsistent, the CAL2DOM utility also disaggregates and
consolidates flow data. USRDOM was developed using the HEC-5 software, the same
software used by the USRWQM. The model has previously been used to evaluate the
potential benefits and impacts of the North-of-the-Delta Off-stream Storage (NODOS)
program. A more detailed description of USRDOM and the temporal downscaling process is
included in a CH2M Hill development and calibration report (CH2M Hill 2011).
USRWQM
The Upper Sacramento River Water Quality Model (USRWQM)12 was developed using the
HEC-5Q framework to simulate mean daily (using 6-hour meteorology) reservoir and river
temperatures at key locations on the Sacramento River. The timestep of the model is daily
and provides water temperature each day for the 82 year hydrologic period used in CALSIM
II. The model has been used in the previous CVP and SWP system operational
performance evaluations as well as BDCP. Monthly flows from CALSIM II for an 82-year
period (water years 1922 to 2003) are used as input into the USRWQM after being
temporally downsized to daily average flows. Temporal downscaling is performed on the
CALSIM II monthly average tributary flows to convert them to daily average flows for HEC-
5Q input. Monthly average flows are then converted to daily tributary inflows based on 1921
through 1994 daily historical record (one of three historical records for three aggregate
inflow areas). The HEC-5 component of USRWQM simulates daily flow operations in the
upper Sacramento River.
A more detailed description of USRWQM and the temporal downscaling process is included
in an RMA calibration report (RMA 2003). For more information on the USRWQM, see
Appendix H of Reclamation’s 2008 OCAP BA (USBR 2008b).
2.6.3 Meander Migration and Bank Erosion Model
To enable the modeling of bank swallow habitat (BASW1) and recruitment of large woody
debris (LWD1), SacEFT has been explicitly coupled with a Meander Migration Model,
developed by University of California, Davis researchers (Larsen 1995; Larsen and Greco
2002; Larsen et al. 2006b) that calculates channel migration using a simplified form of
equations for fluid flow and sediment transport developed by Johannesson and Parker
(1989). The model considers the effects of a variable hydrograph on meander migration
12 This model is also referred to synonymously as USRWQM and SRWQM HEC-5Q depending on the analyst and author.

Chapter 2: Ecological Flow Needs Considered
50 | Page
rates. The underlying hypothesis is that the bank migration rate, when thresholds are
exceeded, is linearly related to the sum of the cumulative excess stream power in the same
time interval (Larsen et al. 2006a).
The Meander Migration Model requires the following six input values, which reflect the
hydrology of the watershed and the hydraulic characteristics of the channel: initial channel
planform location, “characteristic discharge”, reach-average median particle size of the bed
material, reach-average width, depth, and slope. The crux of the model is the calculation of
the velocity field. The analytic solution for the velocity results from the simultaneous solution
of six partial differential equations representing fluid flow and bedload transport. An initial
calibration also plays a critical role. To calibrate the model, researchers use the channel
planform centerline from two years for which centerlines can be accurately delineated using
digitized aerial photos. The calibration process consists of adjusting the erosion and
hydraulic parameters in the Meander Migration Model until the simulated migration closely
matches the observed migration. The erosion potential map is initially determined from GIS
coverages and delineates areas of higher and lower erosion potential due to differences in
land cover, soil, and geology. The erosion potential map is then adjusted in the near-
channel-bank areas by calibrating the channel centerlines between the two time periods.
See Larsen and Greco (2002) for details.
As applied and configured for SacEFT, the Meander Migration Model focuses on three river
segments located between RM 170-185, 185-201, and 201-218. The model has also been
previously applied in various locations between Red Bluff (RM 243) and Colusa (RM 143).
The finest unit of resolution of interest is a bend. We apply a fixed zonal concept based on
segments, using the locally well-known concept of river miles to reference these bends.
While we recognize that channel alignment has changed significantly since the U.S. Army
Corps of Engineers 1964 centerline survey, the critical consideration is that these locations
be “well-known” and consistent across SacEFT’s submodels. This in no way inhibits the
spatial accuracy of meander migration calculations; it just simplifies the manner in which
specific bends are identified. As described earlier, for purposes of determining the suitability
of bank swallow nesting habitat, the exact locations of individual bends of interest are still in
approximately the same zones whether at RM 191 or RM 208. Knowing exactly where it is
does not help us answer questions related to bank swallow nesting habitat.
ESSA has developed a GIS-based erosion model that allows users to combine the
predictions from the Meander Migration Model with other spatial information, such as soil
and vegetation information. Each year, the model simulates the location of the river
channel, the area of eroded banks and the location of the banks at the end of the year. The
location of the river channel is calculated from the centerline based on the assumption that
the distance from the local channel to the bank remains constant during the simulation. The
eroded area for each year is defined as the channel area overlapping the previous year’s
banks. The river banks at the end of the year are calculated by subtracting the eroded area

Final Report
Application of EFT to Complement Water Planning for Multiple Species
51 | Page
from the banks at the start of the year. Figure 2.9 shows an example of change of
centerlines simulated by the Meander Migration Model over a period of 56 years.
Figure 2.9. Meander Migration and Bank Erosion Model – example of centerlines for 56
years for one scenario.
The bank erosion is simulated by finding the distance between this and last year’s
centerlines and eroding the bank by the same distance. The distance between centerlines is
found in 0.25 m intervals by gradually increasing the width of a buffer from last year’s
centerline and determining the segments of this year’s centerline that are within this area of
interest. The centerline segments are then used to erode the bank by locating the nearest
bank in the direction the centerline is migrating and remove the bank to the same depth as
the distance between centerlines. This approach yields bank variable width erosion with
high precision (Figure 2.10). The new bank locations are then used to calculate next year’s
erosion.
Figure 2.10. Meander Migration and Bank Erosion Model – variable erosion example.

Chapter 2: Ecological Flow Needs Considered
52 | Page
2.6.4 The Unified Gravel-Sand Model (TUGS)
Stillwater Sciences has developed The Unified Gravel-Sand (TUGS) model to simulate how
bed mobilization and scour affect grain size distribution, including the fraction of sand in
both the surface and subsurface layers (Cui 2007). TUGS simulates changes in grain size
by accounting for how sediment flux interacts with sediment in both the surface and
subsurface of the channel bed. TUGS is capable of providing a variety of grain size-specific
transport estimates for gravel and sand, and of tracking these two classes of sediment by
their proportions in surface and subsurface layers. The model can be used to assess the
effects of different management scenarios (e.g., gravel augmentation, flow releases to
increase the frequency of bed mobilization and scour, reduction in fine sediment supply) on
salmonid spawning habitat.
Though most existing bedload transport models can predict sediment transport rates and
bed surface/subsurface textures as a function of sediment supply and routing, they
generally have ignored the presence of sand. Including fractions of sand in surface and
subsurface grain size distributions is of interest for evaluating the extent and quality of
salmonid spawning habitat. Surface grain size distributions can support estimates of
available spawning habitat in terms of the availability of spawning-sized gravel, and
subsurface grain size distributions, especially the fraction of sand, and can support
estimates of spawning gravel quality. The TUGS model is designed to fulfill this need by
simulating how bed mobilization and scour affect grain size distribution, including the
fraction of sand, in both the surface and subsurface.
As described in Cui (2007), The Unified Gravel-Sand (TUGS) Model employs:
a) the surface-based bedload equation of Wilcock and Crowe (2003);
b) a combination of the backwater equation and the quasi-normal flow assumption for
flow;
c) Exner equations for sediment continuity on a fractional basis, including both gravel
and sand, and the process of gravel abrasion;
d) the bedload, surface layer, and subsurface gravel transfer function of Hoey and
Ferguson (1994) and Toro-Escobar et al. (1996); and
e) a hypothetical surface-subsurface sand transfer function.
The model also uses existing cross sections developed by the Army Corps of Engineers
and DWR as part of the Sacramento and San Joaquin River Basins Comprehensive Study.
The TUGS model can be applied to any reach of the Sacramento River for which channel
cross sections and surface and subsurface grain size data are available, and has been
calibrated for the Sacramento River using existing bulk sampling data collected by DWR in
1980, 1984, and 1994. Stillwater Sciences has added to the dataset by collecting new bulk

Final Report
Application of EFT to Complement Water Planning for Multiple Species
53 | Page
samples in the upper and middle Sacramento River in 2005, at locations sampled
previously by DWR.
Two default scenarios were incorporated into SacEFT. The first is a “No Gravel” scenario
that assumes no gravel injection to the rivers, although small amounts of natural sand and
gravel are present. The second scenario, “Gravel Injection”, contains a single gravel
injection in Water Year (WY) 1940, with no subsequent additions (Table 2.8). As part of the
TUGS calibration process, a third “zero gravel” scenario was also developed using historical
flow at Keswick and historical gravel additions from 1981 to 2006.
Table 2.8: Location of TUGS simulation segments and amount of supplementary gravel
added in the case of the “Gravel Injection” scenario (not used in this report).
Upper RM
Lower RM
Gravel Injection (m3)
(injection scenario only)
301.956
299.800
299.800
297.000
179,423 (234,677 yd3)
297.000
295.600
295.600
292.400
188,662 (246,760 yd3)
292.400
289.375
 These are bulk amounts, assuming a gravel porosity of 0.4.
SacEFT requires annual estimates of the gravel grain size-distribution at each of five river
segments in order to calculate the Weighted Useable Area available for spawning
(ST1/CH1). This habitat estimate is then used as one of the inputs to calculate subsequent
performance indicators for egg maturation, survival, and juvenile rearing. In the absence of
gravel data, no calculations are possible for these linked components. For the current
SacEFT effects analyses in this report, we used the “No Gravel” addition dataset developed
using historical flow data at Keswick (RM 301) to define how substrate composition changes
in the simulations. This scenario involves modest historical gravel injections and
assumptions about the initial sediment storage (Stillwater Sciences 2007).
Note: The SacEFT results included in this report use the default "No Gravel" addition
dataset.
2.6.5 DSM2
DSM2 is a one-dimensional hydrodynamic and water quality simulation model used to
simulate hydrodynamics, water quality, and particle tracking in the Sacramento-San Joaquin
Delta (USBR 2008c). It is the most commonly used planning model for Delta tidal hydraulic
and salinity modeling and is capable of describing the existing conditions in the Delta, as

Chapter 2: Ecological Flow Needs Considered
54 | Page
well as performing simulations for the assessment of incremental environmental impacts
caused by future facilities and operations.
The DSM2 model has three separate components: HYDRO, QUAL, and PTM. HYDRO
simulates velocities and water surface elevations and provides the flow input for QUAL and
PTM. EFT uses these standard DSM2-HYDRO outputs to predict changes in flow rates and
depths, and their effects on covered species, as a result of the BDCP and climate change.
The QUAL module simulates the fate and transport of conservative and non-conservative
water quality constituents, including salts, given the flow field simulated by HYDRO. EFT
uses these standard outputs to estimate changes in salinity, and their effects on covered
species, as a result of the BDCP and climate change. Reclamation’s 2008 OCAP BA
Appendix F provides more information about DSM2 (USBR 2008c).
DSM2-PTM simulates pseudo 3-D transport of neutrally buoyant particles based on the flow
field simulated by HYDRO. It simulates the transport and fate of individual particles traveling
throughout the Delta. The model uses velocity, flow, and stage output from the HYDRO
module to monitor the location of each individual particle using assumed vertical and lateral
velocity profiles and specified random movement to simulate mixing. PTM has multiple
applications ranging from visualization of flow patterns to simulation of discrete organisms
such as fish eggs and larvae. Additional information on DSM2 can be found on the DWR
Modeling Support Branch website at http://modeling.water.ca.gov/.
2.7 Categories of Available Outputs
2.7.1 Overview
Practical synthesis and integration of results for multiple scenarios, multiple species life-
history stages, eco-regions and index locations is challenging. Various management
scenarios and impacts on ecological indicators operate over a wide range of spatial and
temporal scales and can be analyzed at differing levels of detail depending on the interests
of the audience (e.g., high-level managers as well as technical staff and researchers). To
overcome this challenge, the EFT software provides output that spans the range from
location- and daily-detail through to high level (“rolled up”) overviews of multiple indicators
and scenarios.
While the software output interface makes use of a simple “traffic light” paradigm for
expressing relative suitability (RS), this is only one type of output created by EFT. EFT's
outputs can equally be used to provide effect size (ES) comparisons based on the natural
units specific to each indicator, as well as map-based visualizations and animations. An
overview of all EFT outputs can be found in Table 2.9. The remaining sections in this
Chapter provide a summary of EFT's main categories of outputs. Readers will encounter
these important output concepts throughout Chapter 3. We conclude with a description of

Final Report
Application of EFT to Complement Water Planning for Multiple Species
55 | Page
how EFT outputs are used to generate target eco-flow rule-sets for each focal species and
indicator (Section 2.7.8).
Table 2.9: Overview of all EFT outputs. The main categories of outputs are summarized in
the remaining sections in this Chapter.
EFT Output
Description
RS summary
Compares the proportion of Good years for a performance indicator,
across scenarios based on the tail of the distribution
NES summary
Compares changes to the performance indicator raw units median across
scenarios
Multi-year rollup R/Y/G
Reports the % in each category to allow comparison of scenarios
Annual year rollup R/Y/G
Reports each year’s R/Y/G to allow comparison of scenarios and identify
patterns of performance
Physical changes summary
Compares changes in median monthly values in a table for physical
attributes (flow, water temperature, salinity)
XL Reports
Allows detailed examination of indicator at each location, along with
physical driving variables
Effect size boxplots
Compares performance indicator changes between scenarios in a boxplot
format showing median, quartiles, range and outliers
Water year characterization
boxplots
Compares performance indicator changes between water year types in a
boxplot format showing median, quartiles, range and outliers
Spatial visualizations
Reports the location-based performance of an indicator on a map
X2 animations
Map-based animated daily time-series of the location of X2
Meander migration
animation
Map-based animated annual time-series of the centerline of the
Sacramento River
2.7.2 EFT Relative Suitability (RS) Thresholds
Context
Multiple scenarios, species, indicators, and year simulations create a very complex solution
space. In the face of this complexity, EFT aims to integrate and clearly communicate the
multiple ecological trade-offs associated with different water operation alternatives. This
capability arises through a standardized approach for synthesizing results to reveal trade-
offs across species and their indicators.
Most of EFT’s 25 performance indicators are calculated on a daily (or finer) time-step at
multiple index locations. Naturally, these daily calculations come in many different units
appropriate to the performance indicator (e.g., square feet of suitable habitat, survival rates,
counts of surviving cottonwood seedlings, etc.). Furthermore, the daily calculations for most
aquatic performance indicators are also weighted by temporal life-history distributions as
well as by differences in habitat quantity and quality across the modeled index sites. For
example, if a sudden dramatic low flow event occurs at the very beginning or very end of

Chapter 2: Ecological Flow Needs Considered
56 | Page
the egg incubation period for a particular Chinook run-type, the overall effect on the redd
dewatering performance indicator (CS6) will be negligible due to the low biological
weighting associated with the “tail” of the temporal distribution.
The challenge of identifying “acceptable” and “unacceptable” changes in habitat conditions
or focal species indicator results confronts all biological effects analysis methods. When
screening results, the EFT output interface makes use of a simplified “traffic light” paradigm
to provide an intuitive and high-level overview of whether a performance indicator is
experiencing good/favorable conditions (Green), performing only fairly (Yellow), or is
experiencing unfavorable/poor conditions (Red) on an annual time scale. This requires
identification of two suitability thresholds for all performance indicators (a good/fair and a
fair/poor threshold). Figure 2.11 shows a simple example of how the EFT software
represents scenarios and years for one indicator.
Figure 2.11: Example SacEFT output showing annual results for the Fremont cottonwood
initiation indicator (FC1) across six scenarios. Cottonwood initiation is not a
process that is expected to occur every year, so the infrequency of favorable
(Green) years in some scenarios is not necessarily an indicator of an
unacceptable change.
Establishing Relative Suitability (RS) Thresholds
During the course of this work, despite several expert surveys, we were unable to elicit a
single unequivocal standard for assigning a favorable, fair, or poor suitability rating to all
EFT indicators. For example, there is no established absolute amount of Weighted Useable
Area (WUA) or salmonid rearing habitat that is considered "favorable". To accommodate a
variety of situations, EFT relative suitability thresholds are based on one of three general
methods:
 Absolute: If available, we use absolute thresholds supported in the literature or
recommended by expert opinion i.e., at design workshops, subsequent reviews of
design materials (e.g., 95% survival, 80,000 cfs). If that fails, then
 Discontinuity: Use apparent discontinuities (curve-breaks) in the empirical historic
(or proxy-historical) cumulative distribution of the natural units of the indicator. If that
fails, then

Final Report
Application of EFT to Complement Water Planning for Multiple Species
57 | Page
 Tercile: Use the 1/3 and 2/3 breakpoints of the cumulative distribution if no clear
curve-break discontinuities are apparent.
Using one of these three approaches (detailed in Table 2.10), suitability thresholds (dividing
breakpoints for good/fair and fair/poor) were set for each indicator.13 In the second and third
approaches described above, suitability threshold identification requires an evaluation of the
distribution of annual indicator value outputs to identify natural or tercile breaks. Details on
assumptions that underpin default RS thresholds are provided in Table 2.10 and Appendix
G.
Table 2.10: Summary of the default relative suitability (RS) thresholds and associated
reference time periods used to rate EFT indicators as favorable, fair, or poor.
Refer to Appendix G for additional details. Dates for some major infrastructure
works are also indicated. 
Indicator Name
Good 
Threshold Setting Method
A
D
T
Years for D,T
Sacramento River Ecoregion
Shasta Dam: construction began 1937, complete 1945
Keswick Dam: construction began 1941, complete 1950
FC1 Cottonwood initiation


1943 – 2004 (H); n = 62
FC2 Cottonwood scour risk


–
BASW1 Bank swallow habitat potential


1940 – 1994 (H); n=55
BASW2 Bank swallow inundation risk


–
LWD1 Large woody debris recruitment


1940 – 1994 (H); n=55
GS1 Green sturgeon egg-to-larvae survival


–
CS1 Salmonid spawning habitat


1939 – 2002 (H); n=64
CS3 Salmonid egg-to-fry survival


–
CS5 Salmonid redd scour


–
CS6 Salmonid redd dewatering


1971 – 2002 (H); n=32
CS2 Salmonid rearing habitat


1939 – 2002 (H); n=64
CS4 Salmonid juvenile stranding


1971 – 2002 (H); n=32
Delta Ecoregion
Banks pumping plant: complete 1963
Tracy pumping plant: construction began 1963, complete 1967
CS7 Salmonid juvenile development in Yolo


2002 – 2007 (H); 1976 – 1991 (S); n=22
CS9 Salmonid juvenile mortality risk


2002 – 2007 (H); 1976 – 1991 (S); n=22
CS10 Salmonid juvenile temperature
preference


2002 – 2007 (H); 1976 – 1991 (S); n=22
DS1 Delta smelt spawning success


2002 – 2010 (H); n=9
13 Although fully configurable through the EFT database, relative suitability threshold changes are not made lightly, since every RS
method result is founded on a preceding threshold setting exercise.

Chapter 2: Ecological Flow Needs Considered
58 | Page
Indicator Name
Good 
Threshold Setting Method
A
D
T
Years for D,T
DS2 Delta smelt habitat suitability


–
DS4 Delta smelt entrainment risk


1989 – 2000 (H); 1975 – 1991 (S); n=29
LS1 Longfin smelt abundance


2002 – 2008 (H); 1975 – 1991 (S); n=24
SS1 Splittail spawning habitat


1989 – 2010 (H); n=22
TW1 Brackish tidal wetland


2002 – 2006 (H); 1975 – 1991 (S); n=22
TW2 Freshwater tidal wetland


1997 – 2010 (H); 1975 – 1991 (S); n=31
ID1 Egeria suppression


–
ID2 Corbula suppression


–
ID3 Corbicula suppression


–
 Key to Good:  = More of the indicator is better;  = Less of the indicator is better. Key to Threshold Setting Method: A =
Absolute; D = Discontinuity; T = Tercile. Key to Years: H = Historical observations; S = Simulated/proxy data intended to
portray a typical condition.
Figure 2.12 shows an example of this sorted (“cumulative”) distribution with selected
threshold breakpoints. As might be expected, the native units of each plot vary with the
performance indicator (see ESSA 2011, 2013).
Figure 2.12: Annual sorted results and relative suitability thresholds for the SacEFT Fremont
cottonwood initiation (FC1) performance indicator run using historic observed
flows (WY1938-2003). Breakpoints are indicated by horizontal lines. This
definition of threshold suitability also takes into consideration comparisons with
aerial photographs of historically strong cottonwood recruitment at study sites vs.
model results (abstracted from ESSA (2011), Figure 3.2 [Appendix B]).
SacEFT - Riparian Initiation (FC1) Calibration
7
99
53
36
0
20
40
60
80
100
1983
1958
1941
1969
2003
1998
1956
1982
2004
1963
1973
1999
1980
1965
1989
1993
1976
1957
1970
1988
1946
1979
1961
1960
1986
1985
1964
1949
1962
1948
1945
1950
1944
Water Year (Historical Flows)
# nodes w
surviving
cottonwood
seedlings
over all
cross
sections

Final Report
Application of EFT to Complement Water Planning for Multiple Species
59 | Page
EFT baseline simulation
Distributional outputs like Figure 2.12 are the result of an EFT baseline simulation (a model
run typically based on a continuous historical time series sometime between 1939 and
2002; details depend on species and PI, refer to Appendix G). Each EFT baseline
simulation was selected to maximize the range of water year types and year to year
variation in flow conditions based on available high-resolution data. Because of the
requirement for long-term, high-resolution datasets (both temporal and spatially), this
typically required selection of data available from the long-term historical record. Historical
data include modified, regulated, artificial flows following construction and operation of
major dams, diversions and pumping plants. Historical flow (and water temperature)
datasets also include different stanzas and changes in driving climate.
Note: In this report, historic flows  natural / pristine / unregulated / unmodified / unimpaired
flows. Historical flows are just that –– the measured empirical flows which occurred during
the selected period of record. Hence, these flows can and will include a shifting mixture of
modified, regulated, artificial (potentially "degraded") flows following construction and
operation of dams, diversions, conveyance structures and pumping plants. However, when
the time series is long enough, they will also include a range of water year types and related
flow variations that even though regulated, still manage to "show through" in the historic
dataset.
For some DeltaEFT indicators, when the historic record was too short, the EFT baseline
combined the available historic data with a simulated no action proxy historical flow
simulation. Details are described below and in Appendix G.
Hence, it is important to recognize that EFT's baseline simulations do not use (nor claim to
use) natural, unregulated, pristine flows. Pristine unregulated flows do not exist at the
temporal (daily), and spatial resolution (Appendix H), over the range of water years (multiple
decades) required by EFT to establish baseline conditions.
While there have been various efforts to remove the effects of reservoirs and diversions on
existing hydrological time-series (so called unimpaired flows), these estimates do not
include removal of the effects of levees, channelization “improvements”, wetland storage
and related evaporation processes, forest practices, groundwater-surface water
interactions, etc. Moreover, unimpaired flow estimates (with all of these various embedded
limitations) are calculated at a limited number of locations (usually below rim dams and at
the end of major rivers entering the San Joaquin-San Francisco Delta), not the wide range
of sites (Appendix H) required to calculate EFT's functional performance indicators, and
often only at a monthly resolution. Further, volume correlations, precipitation correlations,
subbasin to subbasin extrapolations, and other (murky) techniques are embedded in the

Chapter 2: Ecological Flow Needs Considered
60 | Page
unimpaired flow datasets used in the Central Valley14. This represents a series of limitations
(or at least unquantified errors) that make these unimpaired datasets
unsuitable/inappropriate for use in EFT.
EFT emphasizes multiple functional flows. Functional flows are a distinct concept from
natural flows. The functional flow needs represented in EFT's indicators are not dependent
on the existence of "natural" (or unregulated or pristine, etc.) flows. Rather, the life-history
needs of various species identified during conceptual model and related algorithm
development –– while they would no doubt show more frequent and better levels of
response under natural, pristine, unregulated flows –– still do generate positive, neutral and
negative levels of response when confronted with variation shown in long-term historic flow
records (even though regulated, artificial, modified). In this way, functional flows help to
identify achievement of attenuated (or mimicked) natural processes in the presence of
regulated/managed changes. While it would be ideal to have a long-term, high-resolution
natural (or pristine or unregulated, etc.) flow record, EFT's functional flow indicators do not
rely upon the existence of these (currently unavailable) flows.
Interpretation of EFT RS thresholds
While some indicators shown in Table 2.10 are based on an “absolute” scale (via expert
opinion or from a Biological Opinion), most RS thresholds are based on records of historic
flow, some of which extend for many decades with the resulting empirically-driven indicator
results broken into low, medium and high categories to define the default suitability
thresholds (e.g., Figure 2.12). When new reference case and study scenarios are run, their
RS outputs are computed using these same default thresholds (via tercile/discontinuity
curve-break analyses).
Conventionally, the RS comparisons are expressed as the arithmetic difference in the
percentage of good/favorable years between scenarios. For example, if 22% of years are
good in the reference case scenario and 37% of years are good in a study scenario, the RS
comparison will be +15%, as shown in Table 2.11. This can be thought of as measuring the
change in the proportion of years in the upper (good) tail of the distribution of years.
A helpful complement to establishing RS thresholds is to identify historical years when a
performance indicator was known to have experienced favorable or poor performance. In
some cases, our suitability threshold decisions were informed by these types of
comparisons (e.g., for Fremont cottonwood), where records of favorable and poor years
were measured and documented in such a way that enabled the units of the EFT
performance indicator to be related to these observations. Despite best efforts however,
repeated surveys of experts during our follow-up on input during EFT design workshops did
not yield high response rates on "absolute" suitability thresholds for many EFT performance
14 Methods at Rim Dams are more reliable, but not useful at the locations required by EFT's functional performance indicators.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
61 | Page
indicators. This is in part due to the derived nature of EFT performance indicators (e.g.,
"Weighted Useable Area" vs. "Adult Spawning Abundance").
While the RS method provides a methodology that is fully internally consistent for
comparing scenario results (i.e., a comparison of multiple scenarios using the same
performance indicator will always provide an accurate picture of which water management
scenarios are “better” than others), it does not necessarily provide a concrete inference
about the ecological significance of a particular effect. For example, it is possible for a year
that ranks as “good” with this method to be biologically suboptimal. Similarly, a year that
ranks as “poor” may not be biologically meaningful and therefore, the need to carefully
interpret results is always present.
Table 2.11: EFT effects analysis – high-level roll-up using the relative suitability (RS) method.
The method reports the percentage change in the years with good/favorable
conditions compared to a reference case. This standardizes the comparison units
in terms of a relative suitability rating and is internally consistent and able to
accurately identify alternatives that are better or worse. The RS method does not
provide an assessment of absolute suitability.
Focal species
Performance indicator
(incomplete listing)
Effect Alternative
vs. Reference case
Alt. 1
Alt. 2
Alt. 3
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1)
15
16
15
Late Fall Chinook
Suitable spawning habitat (CS1)
-3
-5
-2
Winter Chinook
Juvenile stranding (CS4)
-14
-18
-17
Suitable rearing habitat (CS2)
10
26
4
2.7.3 Annual RS Roll-up
An example of the annual RS output created directly by the EFT software is shown in Figure
2.13. These annual roll-up summaries group performance indicator results for selected
scenarios together, and within each scenario show the annual ranking of selected
indicators. They can help to identify water years that exert a strong signal across all
scenarios. This information can be shown "optically" as in Figure 2.13 or in tabular form per
the example in Table 2.11.

Chapter 2: Ecological Flow Needs Considered
62 | Page
Figure 2.13: An example of the RS method applied to annual roll-up ratings for four scenario
groups and five indicators.
2.7.4 Multi-year RS Roll-up
The highest level of RS synthesis provided by EFT is the multi-year roll-up. Once again
grouped by scenario, Figure 2.14 shows the percentage of years in the simulation having
favorable, fair, and poor conditions, utilizing the same results as the annual roll-up.
Figure 2.14: An example of the RS method applied to multi-year roll-up ratings for four
scenario groups and five indicators.
The RS method does not provide a quantitative assessment of absolute suitability by
conveying the absolute size of the effect. Changes like +15% gain in favorable years are a
convenient way to compare scenarios but carry no statistical inference (like α=0.05).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
63 | Page
RS-based differences between alternatives may be more sensitive to changes at the tails of
the annual distribution, compared to the methods based on Effect Size (described below).
Using this method, boundary effects can mean that a small percent change may cause a
year to switch ranks. A few indicators may also have a narrow range.15
In summary, the RS synthesis method tends to emphasize changes in the favorable and
poor ends of indicator performance distributions rather than the central tendency. While the
method provides a useful framework for screening results, it can suffer from boundary
effects and hyper-sensitivity if the relative suitability thresholds are set too narrow. The key
benefit of the RS method is that it removes units and standardizes comparisons in terms of
a common suitability rating relative to a chosen reference case. The best use of the RS
method is therefore to serve as a screening tool to compare scenario results in association
with additional synthesis methods. The annual and multi-year RS roll-ups are internally
consistent and will correctly identify alternatives that are better or worse for a given
indicator.
2.7.5 EFT Syntheses Based on Effect Size (ES)
Context
A companion synthesis we use involves comparing multi-year median values for each
indicator for each alternative so that the modeled Effect Size (ES) can be considered in
terms of the raw units. As with the RS synthesis method, this approach also makes use of a
reference case to provide comparative percentage changes but in this case, the change is
expressed in terms of the raw units. Like RS methods, the sign of the difference depends on
whether the indicator improves (more is better) or declines (more is worse) relative to the
reference case (see Table 2.10). Depending on preferences, visual color shading like that
shown in Table 2.12 can be applied to help the reader decode the direction and magnitude
of positive and negative changes. In this report we highlight positive changes from the
baseline case with green shading and negative changes with red shading; using stronger
shades to indicate greater departure from the baseline. The threshold used to set these
visual cues is itself a judgment decision. We chose a ±10% change in median values as a
convention. This does not provide an absolute basis for judging whether an indicator
difference is suitable or acceptable; rather, this threshold change provides a convenient way
to compare ES changes amongst alternatives, but carries no statistical inference (like
α=0.05) on its own. Because ES differences are based on changes to the multi-year median
values, the ES approach is expected to be more muted relative to the tail-oriented RS
method, which is subject to greater changes.
15 Relative suitability thresholds for all performance indicators are fully configurable in the EFT database (Appendix G).

Chapter 2: Ecological Flow Needs Considered
64 | Page
As with the RS method described in Section 2.7.2, the ES synthesis method is best used as
a screening tool to compare results based on changes in the median of the distribution of
indicator results.
Table 2.12: EFT effects analysis – multi-year analysis using the Effect Size (ES) synthesis
method. This view presents the multi-year median values for each alternative with
percentage differences, and preserves the native units of each performance
indicator. The sign of the difference depends on whether the indicator improves
(more is better) or declines (more is worse) relative to the reference case.
Arbitrary green and red shadings are used to help decode patterns by
categorizing levels of positive and negative changes: 5-10%, 10-20% and >20%.
While the native units of each performance indicator are provided, these changes
too do not provide an assessment of absolute suitability.
Focal species
Performance indicator
(incomplete listing)
Reference
case
Alt. 1
Alt. 2
Alt. n
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
3,738
4,081
(9.2%)
4,069
(8.9%)
3,998
(6.9%)
Late Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,272
1,195
(-6.0%)
1,187
(-6.7%)
1,232
(-3.1%)
Winter Chinook
Juvenile stranding index (CS4)
0.085
0.106
(-2.1%)
0.094
(-0.9%)
0.101
(-1.6%)
Suitable rearing habitat (CS2; 000s ft2)
37,153
37,602
(1.2%)
37,804
(1.8%)
37,101
(-0.1%)
Effect Size Boxplots
In order to explore potentially meaningful changes flagged by the RS and ES methods, we
can dig deeper into selected potential effects by plotting median effects across all years by
location, and preserve the level of variation using boxplots (e.g., Figure 2.15). This can be
used to show both the level of variation overall amongst alternative- as well as location-
specific effects. Grouping results by water year type is a further elaboration of this kind of
analysis.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
65 | Page
Figure 2.15: Boxplot of temperature stress for fall-run Chinook (CS10) showing median value
by location for alternative scenarios, including 25th and 75th percentiles (edge of
boxes) as well as tails of extreme values (lines). These ES summary plots are
available by alternative over all locations, as shown above with results for
individual locations, and can also be stratified by water year type.
2.7.6 Within Year Daily Results
In selected cases we also review detailed daily results and make use of the spatial
visualization (mapping and animation) features of EFT. These detailed outputs are
important when interpreting effects that have been screened as being potentially meaningful

Chapter 2: Ecological Flow Needs Considered
66 | Page
(e.g., Figure 2.16; Figure 2.17). These outputs are automated through the EFT software
(and are distinct / independent of the RS and ES methods).
Figure 2.16: Steelhead rearing habitat (CS2) results for a year rated as favorable.
Water year:
Location of interest:
River Miles
Species
Units Sq Feet
Steelhead
1986
CS Reach 5
280.2 - 298.5
0
20000
40000
60000
80000
100000
120000
140000
0
100
200
300
400
500
16-Jun
23-Jun
30-Jun
07-Jul
14-Jul
21-Jul
28-Jul
04-Aug
11-Aug
18-Aug
25-Aug
01-Sep
08-Sep
15-Sep
22-Sep
29-Sep
06-Oct
13-Oct
20-Oct
27-Oct
03-Nov
10-Nov
17-Nov
24-Nov
01-Dec
08-Dec
15-Dec
22-Dec
29-Dec
05-Jan
12-Jan
19-Jan
26-Jan
02-Feb
09-Feb
16-Feb
23-Feb
02-Mar
09-Mar
16-Mar
23-Mar
30-Mar
06-Apr
13-Apr
20-Apr
27-Apr
04-May
11-May
18-May
25-May
01-Jun
08-Jun
Cumulative Annual WUA
(1,000 sq ft)
Daily WUA (1,000 sq ft)
Period of Interest
SacEFT - Chinook & Steelhead Rearing WUA Report
Distribution
WUA
Good
Fair
Poor
Cumulative
0
2
4
6
8
10
12
14
16-Jun
23-Jun
30-Jun
07-Jul
14-Jul
21-Jul
28-Jul
04-Aug
11-Aug
18-Aug
25-Aug
01-Sep
08-Sep
15-Sep
22-Sep
29-Sep
06-Oct
13-Oct
20-Oct
27-Oct
03-Nov
10-Nov
17-Nov
24-Nov
01-Dec
08-Dec
15-Dec
22-Dec
29-Dec
05-Jan
12-Jan
19-Jan
26-Jan
02-Feb
09-Feb
16-Feb
23-Feb
02-Mar
09-Mar
16-Mar
23-Mar
30-Mar
06-Apr
13-Apr
20-Apr
27-Apr
04-May
11-May
18-May
25-May
01-Jun
08-Jun
Flow (kCFS)
Period of Interest

Final Report
Application of EFT to Complement Water Planning for Multiple Species
67 | Page
Figure 2.17: DeltaEFT invasive species deterrence result for a year rated as favorable.
All daily site-specific data are recorded in EFT's database, which can be used for further
custom analyses.
2.7.7 Spatial Visualizations and Animations (DeltaEFT only)
In the Delta, unique spatial dynamics can exert control over the consequences of different
flow regimes. To help users understand these patterns, DeltaEFT includes spatial
visualizations and animations for various performance indicators. This provides another
important method for interpreting and communicating results. Figure 2.18 shows an
example of a screen capture from the Annual Spatial report for DS4: Index of risk of
entrainment for Delta smelt. This example shows results for each location for a year with fair
performance. Dots are colored based on expected entrainment. Green dots are less than
5%, yellow dots are 5 – 25% and red dots are greater than 25%. Dots are also scaled
based on their spatial weight. Note that locations closer to the water export facilities
generally have high entrainment and low spatial weights.

Chapter 2: Ecological Flow Needs Considered
68 | Page
Figure 2.18: An example screen capture from the Annual Spatial report for DS4: Index of risk
of entrainment for Delta smelt, showing the performance at each location. Dots
are colored based on the magnitude of entrainment. Green dots are locations
where expected entrainment of smelt larvae in those areas are less than 5%,
yellow dots are 5 – 25% and red dots are more than 25%. Dot-sizes also reflect
their spatial weight (i.e., the average relative abundance of smelt present in the
different index areas).
2.7.8 Development of Target Ecological Flow Criteria
Results for EFT's 25 functional performance indicators can be analyzed to identify the
emergent preferred ecological conditions and rule-sets that support favorable relative
suitability ratings (presented in detail in Appendix I). A fundamental step in this process
involves analysis of flow traces (or traces of water temperature or other physical drivers)
that are associated with favorable suitability. These eco-friendly rule-sets can then be
incorporated and tested within external modeling platforms capable of handling the
necessary resolution of these rules.
Section 2.9 elaborates how we use EFT eco-friendly rule-sets and incorporate them into
other systems operation models (CALSIM example). In Section 3.4, we present results of a
first pilot study to apply some of these EFT derived rule-sets to CALSIM.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
69 | Page
2.8 Structured Comparisons & EFT Analysis Steps
There are a very large number of ways to explore and compare operation/conveyance
effects and climate effects for the Sacramento River and Delta amongst EFT's multiple
species and indicators. In the case of EFT's salmonid indicators, there are over 200
possible “effects” comparisons. To systematically manage this daunting task, our analyses
follow a structured approach. A fundamental element of this approach involves making
comparisons with a defined reference case. As described below, the nature of the reference
case and study scenarios determines whether an analysis is focused on
operation/conveyance effects or climate change effects.
2.8.1 Role of the Reference Case
A challenge and frequent controversy surrounding National Environmental Policy Act
(NEPA) and California Environmental Quality Act (CEQA) effects investigations is the
establishment of a reference case for the comparison of alternatives and the analysis of the
effects of alternative project implementations on priority species (Mount et al. 2013). The
reference case represents a chosen point of comparison, or baseline, which embeds any
number of assumptions about the level of human development, climate change, and
baseline system operations. Using a reference case provides relative simplicity and side-
steps questions related to the absolute predictive accuracy of models by focusing
exclusively on the difference between study scenarios compared to the reference case,
isolating the impacts of the alternatives in question. This is the common approach adopted
by DWR in many analyses of BDCP alternatives as well as in previous analyses of NODOS
project alternatives.
This practice notwithstanding, use of a historical reference case was recommended by the
Delta Science Panel in its review of BDCP (DSP 2014), even though the approach is
unwelcome by some who feel that the historical record is a flawed reference given that it
includes numerous shifts in operational standards and climate. The counterpoint is that use
of a historical reference case enables study of the level of cumulative change (regardless of
whether it is produced by climate change, changes in operations and conveyance, or
increasing patterns of human water demand).
When interested in the cumulative level of change, EFT effects analyses that use historical
conditions as the reference case (Section 3.4 includes examples of this reference
comparison) provide managers with supplementary information and perspective about the
degree to which proposed future actions may contribute toward the recovery of priority
species. For example, knowing that three study comparisons differ in their indicator effects
by 5% versus a future reference case, while a historical reference is 25% different, provides
perspective on the magnitude of cumulative change already "ratcheted into" the system.

Chapter 2: Ecological Flow Needs Considered
70 | Page
2.8.2 Operation and Conveyance Effects
In traditional comparisons, effects analyses use a standard No Action Alternative (NAA)
reference case16 with study scenarios (or alternatives) matched to the equivalent time
period. Therefore, these comparisons hold climate and demand effects fixed and
differences reflect only the signal associated with the alternative operations and
conveyance details amongst the scenarios. In this report, this is called an operation and
conveyance effect. While it ignores cumulative changes, this is the comparison that is
typically of regulatory interest in CEQA/NEPA EIS/R studies.
2.8.3 Future Climate and Water Demand Effects
In our EFT effects analyses of selected BDCP alternatives, we also assess the effect of
climate change and future levels of development and water demand on EFT species and
performance indicators by comparing the NAA-Current to NAA-ELT (Early Long Term) to
NAA-LLT (Late Long Term) study scenarios. These comparisons isolate the effect of
varying future climate, water demand, and development (while holding operation and
conveyance changes constant).
2.8.4 Cumulative Change
As mentioned above, to demonstrate how historical conditions can provide supplementary
information to EFT analyses, our Pilot Analysis of ecological flows (Section 3.4) includes a
historical reference case alongside the more typical simulated reference case. This
comparison illustrates the degree of cumulative system change.
2.8.5 Water Year Effects
Another comparison that can be structured is to stratify outputs according to Water Year
Type. Comparisons like those found in Section 3.3.3 show the effect of particular categories
of water supply, regardless of climate and operation/conveyance assumptions.
2.8.6 Typical EFT Effects Analysis Steps
All comparative analyses (including those in Chapter 3) generally follow a systematic
presentation that:
1. starts with a high level summary of overall findings;
2. compares changes in the driving physical variables themselves (flow, water
temperature, salinity, etc.);
3. examines the changes to species functional performance indicators using different
methods;
16 These acronyms are all defined in detail in Section 3.3.2.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
71 | Page
4. provides indicator level summaries using RS outputs and associated synthesis
method;
5. provides indicator level summaries using the ES outputs and associated synthesis
method; and
6. ends with a weight of evidence net effect score that combines the RS and ES
results.
All these components are described in detail below, with Section 3.3.3 providing a detailed
study of the sequential, structured approach applied to selected BDCP alternatives.
Physical Change
Our EFT subcomponent effects analyses typically proceed in four stages. First, we conduct
an assessment of the degree of physical change amongst the alternative scenarios. This is
an essential first step, since any lack of contrast in fundamental flow, water temperature,
San Joaquin-Sacramento Delta salinity, etc. means that there will be no reason to expect
meaningful changes in EFT performance indicators. For both the Sacramento River and
Delta ecoregions, we identify a small number of representative physical locations and
review the median and percent differences in key physical variables on a monthly basis.
Comparisons among months are expressed as percentage difference based on the
difference between the median of the study scenario compared to the median of the
reference case. To help detect patterns and differences, green and red shading is used to
highlight three levels of positive and negative changes: 5-10%, 10-20% and >20%. Monthly
exceedance plots are also available.
Application of Relative Suitability (RS)
As the second step, we screen alternatives for high-level effects using the Relative
Suitability (RS) synthesis method. Details of the strengths and limitations of this method are
described in detail in Section 2.7.2. The RS method is a comparison of the percentage of
years with a favorable relative suitability classification for the study scenario, compared to
the percentage of favorable years in a reference case scenario.
This method will generally show higher sensitivity to changes in the upper (or lower) tail of
performance distributions rather than the central tendency of performance.
As a convention, we use ±10% difference in the percentage of favorable years between
scenarios as a signal of potentially meaningful change when summarizing findings using the
RS method. More granular presentations using the RS method use six levels of positive and
negative changes: ≤-10%; -5% to -10%; -4%; -3% to +4%; +5% to +10%; and ≥10%.

Chapter 2: Ecological Flow Needs Considered
72 | Page
Application of Effect Size (ES)
In the third step, alternatives are screened for high-level effects using multi-year median
Effect Size (ES) synthesis method. Details of the strengths and limitations of this method
are described in detail in Section 2.7.5. The ES method measures the change in the median
value of the multi-year set of results, comparing results of each study scenario with a
reference case scenario. Because it is focused on the median of a multi-year distribution
(over all locations), the ES method will tend to show smaller changes when compared to the
RS method, which measures changes to the tails of the distribution and can be sensitive to
boundary effects.
As a convention, we use a ±5% change in the median multi-year performance of a given
indicator to signal a potentially meaningful change when summarizing findings using the ES
method. In general, the ES comparisons with a 5% threshold for median change generally
produce a smaller, more stringent set of differences as compared to the RS method.
We stress that these two methods (RS and ES) are complementary and do not provide
equivalent, interchangeable effects information. Further, our ±10% (RS) and ±5% (ES)
change levels are conventions. As with EFT's default suitability thresholds, these levels can
easily be changed/customized.
Net Effect Score (NES)
Relying on either the RS or ES method may limit the ability to detect meaningful differences
between scenarios. To address uncertainty in the overall assessment, including the
challenge of integrating multiple attributes (indicators) for single species, we calculate a Net
Effects Score (NES). The NES is based on a consistent logic that considers the weight of
evidence provided by the RS and ES methods, penalizing discrepancies when our two
major effects analysis methods differ.
Effects analysis results that show potentially meaningful levels of change for both RS and
ES comparisons receive a higher qualitative ranking for strength of evidence. We also
provide a mechanism for lowering the score for results that have large uncertainty around
the ES (all-years median) effect, and raising the score when the uncertainty is smaller.
Finally, when the fundamental scenario definition includes actions that on first principles
provide a clear explanatory mechanism (e.g., notching of Fremont Weir), if either our RS or
ES method shows a potentially meaningful effect, those cases receive a higher NES (Table
3.35). While many important nuances are not visible in this type of presentation, this
nevertheless provides an executive level summary of heuristic conclusions based on our
best judgment interpreting EFT effects analysis results.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
73 | Page
Definition of Net Effect Scores (NES)
The highest NES is a 6. NES scores increase when the RS and ES methods both agree
that there is a potentially meaningful effect. Scores further increase when results have less
variation around the mean effect size. The definitions for all possible NES scores are:
 Blank/No Score: Neither the RS nor ES summary method generates a potential
change that passes our ±10% and ±5% thresholds. No meaningful effect.
 +/- Mixed effects -- indicators for same species show benefits and penalties (i.e.,
Chinook/steelhead), but the net effect is difficult to determine.
 1-RS RS summary method shows a potential effect (passes ±10% threshold).
However, the results are highly variable.
 1-ES ES summary method shows a potential effect (passes ±5% threshold).
However, the results are highly variable.
 2-RS RS summary method shows a potential effect of ±10% change or more in
favorable years, with clear signal to noise (less variability), yet the ES summary view
shows the inverse effect (potentially contradictory evidence).
 2-ES ES summary method shows a potential effect of ±5% change in absolute
median effect size, with clear signal to noise (less variability), yet the RS summary
view shows the inverse effect (potentially contradictory evidence).
 3-RS RS summary method shows a potential effect of ±10% change or more in
favorable years, with clear signal to noise (less variability), and the ES summary
view does not meet threshold (no contradictory evidence).
 3-ES ES summary method shows a potential effect of ±5% change in absolute
median effect size, with clear signal to noise (less variability), and the RS summary
view does not meet threshold (no contradictory evidence).
 4 Both summary views agree on the direction of the potential effect, and both pass
the threshold for a potentially meaningful effect. However, both show a highly
variable spread in results.
 5 Both summary views agree on the direction of the potential effect, and both pass
the threshold for a potentially meaningful effect with clear signal to noise (less
variability).
 6 Either category "3","4" or "5" + a fundamental, clear mechanistic link to scenario
description.

Chapter 2: Ecological Flow Needs Considered
74 | Page
Table 2.13 shows a partial example of an NES analysis. Higher numeric NES scores
indicate greater confidence in the significance of positive or negative change in the study
scenario, compared to the reference case.
Table 2.13: An example showing the result of the Net Effect Score (NES) analysis applied to
one of a suite of BDCP case studies. A complete table of NES results is
presented in Table 3.35. Shading indicates positive (green) and negative (red)
changes from the reference case.
Early Long Term (ELT) Studies
Relative to NAA-ELT Reference Case
Sacramento River Ecoregion
ESO
LOS
HOS
+
–
+
–
+
–
Fall
5
5
5
Late Fall
1-ES
1-ES
Spring
3-ES
5
3-RS
Winter
2-ES
2-ES
5
Steelhead
1-ES
Bank swallow
Green Sturgeon
Cottonwood
1-ES
1-ES
Woody Debris
1-RS
1-RS
Delta Ecoregion
Fall
Late Fall
+/–
+/–
+/–
Spring
Winter
+/–
+/–
+/–
Steelhead
3-ES
3-ES
2-ES
Splittail
6
6
6
Delta smelt
6
Longfin smelt
6
Invasives
3-ES
4
3-ES
Tidal wetlands
Interpretation
To interpret the meaning and mechanisms behind stronger NES signals requires digging
into the specific EFT indicators, the physical changes which are relevant to the specific
indicators, and the potential mechanisms by which the physical drivers interact with the
indicator. Many of these deeper analyses can be done using the more detailed

Final Report
Application of EFT to Complement Water Planning for Multiple Species
75 | Page
presentations of physical change and the RS/ES analysis which underlies the high level
score. Some very fine-scale analyses of daily-scale events may require further investigation
through a study of the model design documents (ESSA 2011, 2013) coupled with a study of
within-year daily results by location.
2.9 Integrating EFT with Systems Operations Models
The general steps and methods required to create and test the linkage between EFT eco
rule-sets and system operations models are outlined below.
In Section 3.4 we present results of this first pilot study to apply EFT derived rule-sets to
CALSIM. Hence, this methods section, and Section 3.4 are intended to be read together.
2.9.1 Definition of Ecological Flow Criteria
For the majority of EFT's 25 performance indicators, we analyzed results to create a
summary of preferred ecological flow rule-sets (presented in detail in Appendix I). A
fundamental step is analysis of flow traces (or water temperature or other physical driver
results) associated with favorable suitability. Leveraging the EFT relational database, and
data analysis exercises like those shown in Figure 2.19, help the EFT investigators identify
flow patterns and timing that were correlated with favorable outcomes for each species and
performance indicator.
Figure 2.19: Example flow traces underpinning EFT Ecological Flows criteria and rule-sets.
Individual water year traces are colored based on the indicator’s relative
performance suitability in EFT. For winter-run Chinook suitable spawning habitat
(CS1), good performance years are bounded by average flows between 5,000
and 12,000 cfs (left panel). For juvenile stranding risk (CS4), poor performance is
associated with flows below 7,000 cfs (right panel).
Based on flow (or other) trace analysis and conceptual model interpretation, criteria and
rule-sets were then summarized using the standardized format shown in Table 2.14 and
given in Appendix I (timing, magnitude of minimum and maximum flows, location and other
properties). EFT eco rule-set analyses show that rules for driving physical data are

Chapter 2: Ecological Flow Needs Considered
76 | Page
sometimes clearly correlated with the favorable outcome, while others such as redd
dewatering (CS5) have no obvious relationship with flow.
2.9.2 Selection of Subset of Ecological Flow Criteria for Pilot Application
Our initial pilot study (Section 3.4) reduced EFT's 25 indicators to flow criteria for two
species: winter-run Chinook (Table 2.14) and Delta smelt (Table 2.15). These species were
chosen based on their threatened status and because one was found in the Upper
Sacramento and the other the Delta.
Table 2.14: Initial EFT Ecological Flow rules for winter-run Chinook.
Sacramento River
Chinook (winter-run)
Indicator
CS1-CS6
Integrated
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Range
12
12
CS1: Spawning WUA, Max
5
5
CS1: Spawning WUA, Min
CS3: Thermal Egg Mortality, no constraint
CS6: Redd Dewatering, no constraint
CS5: Redd Scour, no constraint
CS4: Juvenile Stranding, Max no constraint
7
7
7
7
7
CS4: Juvenile Stranding, Min
8
8
8
8
8
CS2: Rearing WUA , Max
3.5
3.5
3.5
3.5
3.5
CS2: Rearing WUA, Min
8
8
8
12
12
8
8
Integrated: Max
7
7
7
5
5
7
7
Integrated: Min
Location
Sacramento River above Clear Creek (RM290)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
77 | Page
Table 2.15: Initial EFT Ecological Flow rules for Delta smelt entrainment risk.
San Joaquin-Sacramento Delta
Delta smelt
Indicator
DS4
Entrainment index
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Locations
Combined Old + Middle River
(OLD R A BACON ISLAND CA, ROLD024, 11313405) + (MIDDLE R AT MIDDLE RIVER
CA, RMID015, 11312676)
Variable & Condition
≤ Normal WYT: Qavg > –2,000cfs
> Normal WYT: Qavg > 0cfs
Other Triggers
Juvenile smelt detected through trawls
Recurrence
Annually
Potential conflicts & trade-offs
May conflict with export objectives
References
Kimmerer and Nobriga (2008)
The pilot rules shown in these tables were subsequently "downgraded" to a coarser monthly
resolution on which CALSIM II operates (see Section 2.6.1), and include the following basic
properties:
1. Minimum and maximum flows;
2. Two locations: Sacramento River at Keswick flows (winter-run Chinook) and
combined Old and Middle River flows (Delta smelt entrainment);
3. When cold water storage criteria are not met, and during drought conditions, our
EFT rule-sets are not triggered (“Off-ramping”); and
4. Use of maximum flow limits in non-target months to save water for minimum flows in
subsequent simulation years (“water banking”).
An initial exploration of rules for bank swallow (Table 2.16) was discontinued when it was
apparent that the downscaling of the flow requirements for bank swallow habitat was too
complex for an initial exploratory study.

Chapter 2: Ecological Flow Needs Considered
78 | Page
Table 2.16: Summary of ecological flow criteria for protection of Sacramento River bank
swallow habitat potential. WYT = Water Year Type.
2.9.3 Selection of Reference Study
The selection of the reference study is described in Section 3.4.2.
2.9.4 Implementation of CALSIM Rules
The pilot monthly ecological flow criteria were integrated into CALSIM using CALSIM’s
native WRESL language and integrated with the over 700 existing WRESL files containing
existing CALSIM rules. In this way coarse-scale EFT-derived operational rules are inserted
into the existing CALSIM rule-set, and then tested to see whether the system responds to
the candidate ecological flow criteria for the target EFT species indicators (as well as non-
target EFT indicators).
Minimum ecological flow criteria for winter-run Chinook were implemented for Sacramento
River at Keswick and included as two separate CALSIM actions for May to June and August
to December (Figure 2.20). The minimum flow criterion was modified so that it was not
implemented if it would meaningfully impact cold water storage (“cold water storage rule”) or
under drought conditions (“off-ramping rule”) (Figure 2.21). Both of these rules are common
in other CALSIM actions and were adopted to avoid improving one indicator to a meaningful
level while penalizing another indicator, such as egg-stage thermal survival.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
79 | Page
Figure 2.20: The pilot monthly ecological flow criterion was integrated into CALSIM using
CALSIM’s native WRESL language and integrated with the over 700 existing
WRESL files containing existing CALSIM rules. The EFT WRESL files are
highlighted in red.
Figure 2.21: CALSIM operation rules written as WRESL-language statements for minimum
flows. Four rules are implemented: minimum flow for two different time periods, a
“cold water storage rule” and an “off-ramping rule”. See text for details.
During initial (and iterative) test screening of CALSIM, we found that minimum flows could
not be met due to lack of water in Shasta Reservoir unless water was held back early in the
water year. This led to the creation and implementation of a “water banking rule” (Figure
2.22) which holds water back in January to April and July by introducing a maximum flow
not directly related to the ecological flow criteria developed. Introducing a “water bank” rule
meaningfully improved performance toward achieving target minimum flows.

Chapter 2: Ecological Flow Needs Considered
80 | Page
Figure 2.22: CALSIM rules as WRESL-statements for maximum flows. Three rules are
implemented: maximum flow for two different time periods and a “water banking
rule”. See text for details.
Priority weights for each rule are an important element of CALSIM that influences how the
model optimizes operations. The EFT rule-sets for winter-run Chinook and Delta smelt used
in our pilot study were assigned the same weight as the existing CALSIM minimum flow
criteria for other tributaries and species (i.e., we did not change/increase priorities for our
EFT criteria).
2.9.5 Iterative Scenario Screening
The scenarios were screened using five CALSIM models of increasing complexity, ranging
from a model of the Upper Sacramento River only to the full CALSIM model (Table 2.17).
The screening steps were introduced to reduce computation time and study different ways
of CALSIM rule implementation. It was during the learning period associated with this
iterative approach, that the development of a “water bank” rule took place.
Before settling on the final rules, we iteratively screened draft rule-sets based on their ability
to meet the EFT ecological flow criteria, as well as their impact on storage and exports
(Figure 2.23). Any scenarios that made conditions worse than the reference case under
drought conditions (e.g., drawing reservoirs further down) were rejected. Next, the
scenarios were compared side-by-side to evaluate which scenario was meeting the flow
criteria more frequently, including a focus on improving performance in months that were
not doing well in the reference case. Finally, our screening evaluated changes to Delta
exports to avoid any clearly unrealistic reductions. For example, zero exports in any given
month would likely lead to human health consequences and were cause for rejection,
resulting in a further search for operational rules that were able to jointly meet ecological
and hydrosystem requirements.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
81 | Page
Table 2.17: CALSIM screening models. Five CALSIM models of increasing complexity were
used to screen different implementations of the monthly ecological flow criteria.
Screening model
Description
Upper Sacramento River Model
without non-EFT objectives
Includes Sac R Reservoirs and River down to Knights Landing;
Weights for objectives not related to EFT rules and reservoir operations set
to zero
Upper Sacramento River Model
Includes Sac R Reservoirs and River down to Knights Landing
Delta Model
Simulates 4 of 17 CALSIM full-model steps
Includes Delta and Reservoirs (operated for the Delta)
Fixed set of allocations (CVP, SWP)
Does not include San Joaquin, fixed set of Vernalis salinities/flows
All CALSIM regions
Simulates 4 of 17 CALSIM full-model steps, all regions
Full model
Similar to DRR study; all full-model steps, all regions
Figure 2.23: Scenarios were screened based on their ability to meet the ecological flow criteria
(upper left panel), their impact on storage (upper right panel) and exports (lower
panel).

Chapter 3: Effects Analysis Application of EFT
82 | Page
3 Recent EFT Applications
3.1 Overview
State and Federal agencies have requested EFT be used to evaluate future operational
changes to existing water projects as well as new water projects. To date, these include:
North-of-the-Delta Offstream Storage, Shasta Lake Water Resources Investigation, the Bay
Delta Conservation Plan, and the System Reoperation Program. EFT’s applications are of
direct relevance to the Department of Water Resources, the U.S. Bureau of Reclamation,
the State Water Resources Control Board, and potentially several other State and Federal
Agencies (U.S. Fish and Wildlife Service, U.S. Army Corp of Engineers) engaged in
environmental water planning and ecological effects analysis. Chapter 3 of this report
provides an updated effects analysis for selected San Joaquin-Sacramento Delta
Conservation Plan alternatives. Ecological effects analysis projects we have completed to
date are listed below, along with those that are in progress, sorted by primary agency
sponsor.
California Department of Water Resources
1. North-of-the-Delta Offstream Storage Investigation (NODOS, or Sites Reservoir)
www.water.ca.gov/storage/northdelta/index.cfm
In 2011, at the request of DWR, TNC analyzed the interim proposed operations for Sites
Reservoir. Our analyses of the proposed operations were considered in the Administrative
Draft of the joint EIS/R produced by the Bureau of Reclamation and DWR (TNC and ESSA
2012). This previous application of SacEFT to interim NODOS alternatives is very briefly
summarized in Section 3.2.
The focus of Chapter 3 is on results of the first complete SacEFT and DeltaEFT effects
analysis for selected BDCP alternatives, as well as presenting results of a pilot investigation
applying EFT derived eco-friendly rule-sets to CALSIM. Neither of these two later
applications have previously been documented.
2. Bay Delta Conservation Plan (BDCP)
http://baydeltaconservationplan.com/Home.aspx
TNC has been working with DWR since mid-2012 to analyze the BDCP alternatives. Under
guidance from TNC, ESSA was contracted with SAIC (Science Applications International
Corporation) and more recently ICFI (ICF International), contractors to DWR, to provide
upstream effects analyses on Sacramento River fisheries related to the BDCP. We provided
SacEFT effects analyses of draft alternatives in the fall of 2012, restricted to upstream

Final Report
Application of EFT to Complement Water Planning for Multiple Species
83 | Page
salmonid and green sturgeon impacts. BDCP consultants incorporated their interpretation of
these results into the fall 2013 EIR/EIS which accompanies the BDCP studies.
Section 3.3 of this report provides the first complete effects analysis of selected
BDCP alternatives for all SacEFT and DeltaEFT species and indicators.
3. System Reoperation Program
www.water.ca.gov/system_reop
DWR has requested TNC explore opportunities for how EFT may be used in DWR’s System
Reoperation Program. Authorized by the California legislature, the program directs DWR to
conduct planning and feasibility studies to identify potential options for the reoperation of the
state's flood protection and water supply systems that will optimize the use of existing
facilities and groundwater storage capacity. Studies carried out during the reoperation
program shall incorporate appropriate climate change scenarios and be designed to
determine the potential to achieve the following objectives:
 water supply reliability;
 flood hazard reduction; and
 ecosystem protection and restoration.
These objectives will be achieved by:
 integrating flood protection and water supply systems;
 re-operating the existing system in conjunction with effective groundwater
management; and
 improving existing water conveyance systems.
State Water Resources Control Board (SWRCB)
4. Instream Flow Requirements and Delta Flow Criteria [In progress]
www.waterboards.ca.gov/waterrights/water_issues/programs/instream_flows
At the request of the SWRCB, TNC staff made presentations throughout 2012 to SWRCB
staff charged with creating in-stream flow requirements for a suite of streams in California,
and supporting Delta Flow Criteria development and review.
The purpose of these presentations was to educate SWRCB staff about how EFT works
and how it may help the SWRCB formulate flow criteria.
Chapter 3 also presents results of our initial pilot study of how to formulate and simplify
instream flow requirements for consideration by the SWRCB and other parties.

Chapter 3: Effects Analysis Application of EFT
84 | Page
U.S. Bureau of Reclamation
5. Shasta Lake Water Resources Investigation (SLWRI)
http://www.usbr.gov/mp/slwri/
SacEFT version 1 was applied to early versions of proposed operations related to raising
Shasta Dam under the previous Flows Study (circa 2005) (see TNC et al. 2008). The
SLWRI is proposing to increase the size of Shasta Lake and implement significant changes
to the Sacramento and Delta flow regime. These changes could have significant positive
and negative impacts to both Sacramento River and Delta dependent species and habitat
forming processes.
6. Central Valley Project/State Water Project Coordinated Operation Criteria,
Biological Opinions (USFWS, NMFS), Remand
In 2008, the U.S. Fish and Wildlife Service (USFWS) issued its Biological Opinion (BO) on
the effects of the Coordinated Operation of the Central Valley Project (CVP) and State
Water Project (SWP) in California. The USFWS BO concluded that as proposed, the
coordinated operation of the CVP and SWP is likely to jeopardize the continued existence of
Delta smelt and adversely modify Delta smelt critical habitat. The USFWS BO included a
Reasonable and Prudent Alternative (RPA) designed to allow the projects to continue
operating without causing jeopardy or adverse modification. On December 15, 2008 the
Bureau of Reclamation provisionally accepted and then implemented the USFWS RPA. The
National Marine Fisheries Service (NMFS) issued its final BO on the effects of the long-term
operation of the CVP and SWP in June 2009. The NMFS BO concluded that the long-term
operation of the CVP and SWP, as proposed, was likely to jeopardize the continued
existence of listed salmonids, green sturgeon, and Southern resident killer whale (Orcinus
orca), and destroy or adversely modify associated critical habitat. Some of the BO
measures have subsequently been Remanded by the courts, and are the subject of ongoing
review and negotiation.
EFT would provide directly relevant effects analysis support for the species covered by this
type of investigation on the Sacramento River and Delta.
3.2 Effects Analysis Application of SacEFT to North-of-the-Delta
Offstream Storage Investigation
3.2.1 Introduction
TNC and ESSA (2012) provided a SacEFT effects analysis evaluation of the interim North-
of-the-Delta Offstream Storage (NODOS) Investigation prior to the detailed NODOS EIS/R
and Feasibility Report. That report presented detailed modeling results on how a set of focal

Final Report
Application of EFT to Complement Water Planning for Multiple Species
85 | Page
species associated with the Sacramento River may be impacted (negatively and positively)
by the Investigation’s alternatives. Information on other measures (rip rap removal and
gravel augmentation) were also included.
The North-of-the-Delta Offstream Storage (NODOS) Investigation is evaluating potential
offstream surface water storage by constructing Sites Reservoir near the Sacramento River,
downstream from Shasta Dam and west of Maxwell California (Figure 3.1). The high-level
NODOS objectives are to:
 improve water supply reliability for agricultural, urban, and environmental uses;
 improve drinking, agricultural and environmental water quality in the Delta;
 provide flexible hydropower generation to support integration of renewable energy
sources; and
 increase survival of anadromous and endemic fish populations.
The proposed interim NODOS alternatives include a number of Ecosystem Enhancement
Actions. Using SacEFT, we evaluated three interim study alternatives (Table 3.1) versus
two reference cases (current conditions and an NAA alternative). Additional details on the
study alternatives are summarized in TNC and ESSA (2012).

Chapter 3: Effects Analysis Application of EFT
86 | Page
Table 3.1: Interim Plan Formulation Alternatives – NODOS Investigation. Details subject to
change. Information provided by the NODOS investigation planning team, DWR
(August 2011).
Alternative
A
B
C
Storage Capacity
Sites Reservoir
1.27 MAF
1.81 MAF
1.81 MAF
Conveyance Capacities (to Sites Reservoir)1
Tehama-Colusa Canal
2,100 cfs
2,100 cfs
2,100 cfs
Glenn Colusa Irrigation District Canal
1,800 cfs
1,800 cfs
1,800 cfs
New Delevan Pipeline2
Diversion
Release
2,000 cfs
1,500 cfs
0 cfs 3
1,500 cfs
2,000 cfs
1,500 cfs
Operations Priorities (Primary Planning Objectives)
Long Term (all years)
EESA4
Power5
EESA4
Power5
EESA4
Power5
Driest Periods (drought years)
M&I
M&I
M&I
Average to Wet Periods
(non-drought years)
Water Quality
Level 4 Refuge
Agricultural
Water Quality
Level 4 Refuge
Agricultural
Water Quality
Level 4 Refuge
Agricultural
Notes:
1. Diversions through the TC Canal, Glenn-Colusa Irrigation District (GCID) Canal, and Delevan Pipeline are allowed in any
month of the year.
2. New Delevan Pipeline can be operated June through March (April and May are reserved for maintenance).
3. A pump station, intake, and fish screens are not included for the Delevan Pipeline for Alternative B. For Alternative B, the
Delevan Pipeline will be operated for releases only from Sites Reservoir to the Sacramento River year round.
4. Ecosystem Enhancement Storage Account (EESA) related operations are a function of specific conditions, and operating
criteria that are defined uniquely for each action.
5. Includes dedicated pump/generation facilities with an additional dedicated after-bay/fore-bay (enlarged Funks Reservoir) used
for managing conveyance of water between Sites Reservoir and river diversion locations.
Key:
cfs = cubic feet per second
CVP = Central Valley Project
EESA = ecosystem enhancement storage account
MAF = million acre-feet
M&I = municipal and industrial
SWP = State Water Project
TAF = thousand acre-feet

Final Report
Application of EFT to Complement Water Planning for Multiple Species
87 | Page
Our NODOS ecological effects analysis was organized by species for the following eight
comparisons:
Comparison
NODOS Alternative (SacEFT ID)
Compared to (SacEFT ID)
1
No Action Alternative (134)
Existing Conditions (132)
2
A (136)
Existing Conditions (132)
3
A (136)
No Action Alternative (134)
4
B (139)
Existing Conditions (132)
5
B (139)
No Action Alternative (134)
6
C (140)
Existing Conditions (132)
7
C (140)
No Action Alternative (134)
8 δ
No Action Alternative (134)
Historic conditions (118)
δ Comparison 8 was not used in our report to assess NODOS effects. Instead, it provided a reference case for cumulative
effects.
(b)
Figure 3.1: Artist’s rendition of the Sites Reservoir location relative to the Sacramento River.
This figure is for illustration purposes only and is not intended to represent the
final or preferred Plan Alternative.

Chapter 3: Effects Analysis Application of EFT
88 | Page
3.2.2 Summary of Findings
Relative to the existing conditions reference case, study comparisons #1, #2, #4 and #6
reveal mixed results depending on the species and performance indicator (PI) (see TNC
and ESSA (2012) for details). In all cases, performance indicators relating to thermally
modulated egg mortality (GS1, ST3, CH4) showed either no appreciable impact owing to
any of the NODOS Investigation study alternatives (A, B, C) or a small beneficial impact.
Relative to steelhead and Chinook salmon, green sturgeon eggs (GS1) received the largest
benefits in terms of thermal egg mortality reduction.
Overall, steelhead appeared to be most favored by NODOS Alternative B (TNC and ESSA
2012). NODOS Alternative A favored fall Chinook, followed closely by NODOS Alternative
B. Late fall-run Chinook are least impacted by NODOS Alternative B. Spring-run Chinook
clearly encounter a higher proportion of favorable conditions under NODOS Alternative B.
Acknowledging the downward performance of rearing WUA (CH2), winter-run Chinook
experience the highest proportion of favorable conditions under NODOS Alternative C.
NODOS Alternative A was the next most favorable for winter-run Chinook.
Overall, riparian focal species performance indicators (FC1, FC2, BASW2 and BASW1)
appeared to see most benefit from NODOS Alternative C, followed by NODOS Alternative A
(TNC and ESSA 2012).
For steelhead and winter-run Chinook, juvenile stranding changes (ST4/CH4) were
inversely related relative to rearing WUA (ST2/CH2) (TNC and ESSA 2012). These effects
are partially offsetting, but the exact outcome depends on the response of steelhead and
winter-run Chinook to stage recession events (worse during day than at night) and on the
survival benefits attributable to better rearing habitat conditions.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
89 | Page
Table 3.2: Operation and conveyance effects are shown for different NODOS scenarios in
the Sacramento River ecoregion using the change in the percentage of favorable
years relative to existing conditions (RS method). Numbers in brackets refer to
the increased percentage of simulation years having a favorable rating. **Results
of these meander/erosion model dependent performance indicators are for the
Sacramento River channel with existing revetment (no revetment removal).
Focal
species
Performance indicator
Action Alternatives
vs. Existing Conditions
NAA
(comparison 1)
Alt A
(comparison 2)
Alt B
(comparison 4)
Alt C
(comparison 6)
Fremont
Cottonwood
Initiation success (FC1)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Post-initiation scour risk
(FC2)
+ (+9)
++ (+20)
ni (+2)
++ (+25)
Bank
Swallows
Habitat potential/suitability
(BASW1)**
ni (+/-0)
- (-4)
- (-5)
ni (- 3)
Peak flow during nesting
period (BASW2)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Western Pond
Turtles
Large Woody Debris
Recruitment (LWD)**
ni (-3)
ni (-3)
ni (-3)
ni (-3)
Green
Sturgeon
Egg temperature preferences
(GS1)
ni (+1)
+ (+6)
+ (+8)
+ (+8)
Steelhead
Spawning WUA (ST1)
ni (+/- 0)
ni (+2)
ni (+2)
ni (+2)
Thermal egg mortality (ST3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Redd Dewatering (ST6)
ni (+/-0)
+ (+5)
+ (+6)
+ (+5)
Redd Scour (ST5)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (ST4)
ni (+/-0)
- (-6)
- (-4)
- (-7)
Rearing WUA (ST2)
ni (-3)
+ (+5)
+ (+5)
+ (+5)
Fall Chinook
Spawning WUA (CH1)
ni (+2)
ni (-2)
ni (-2)
- (-5)
Thermal egg mortality (CH3)
ni (+1)
ni (+3)
ni (+1)
ni (+3)
Redd Dewatering (CH6)
ni (+/-0)
+ (+4)
ni (+2)
+ (+4)
Redd Scour (CH5)
ni (+/-0)
ni (+/-0)
ni (-1)
ni (-1)
Juvenile Stranding (CH4)
ni (+/-0)
ni (-3)
- (-4)
- (-4)
Rearing WUA (CH2)
ni (+/-0)
+(+7)
+ (+7)
+ (+7)
Late Fall
Chinook
Spawning WUA (CH1)
ni (+/-0)
ni (-3)
ni (-3)
ni (-3)
Thermal egg mortality CH3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Redd Dewatering (CH6)
ni (+/-0)
ni (+2)
ni (+3)
ni (+2)
Redd Scour (CH5)
ni (+/-0)
ni (+2)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (CH4)
ni (-3)
- (-9)
- (-6)
- (-9)
Rearing WUA (CH2)
ni (-1)
ni (+3)
+ (+5)
ni (+2)
Spring
Chinook
Spawning WUA (CH1)
ni (+/-0)
ni (+3)
ni (+3)
ni (+2)
Thermal egg mortality (CH3)
ni (-2)
ni (+3)
+ (+4)
ni (+3)

Chapter 3: Effects Analysis Application of EFT
90 | Page
Focal
species
Performance indicator
Action Alternatives
vs. Existing Conditions
NAA
(comparison 1)
Alt A
(comparison 2)
Alt B
(comparison 4)
Alt C
(comparison 6)
Redd Dewatering (CH6)
ni (-1)
++ (+11)
++ (+12)
+ (+9)
Redd Scour (CH5)
ni (+2)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (CH4)
ni (-1)
ni (+2)
ni (+2)
ni (+2)
Rearing WUA (CH2)
ni (+1)
- (-8)
- (-8)
- (-8)
Winter
Chinook
Spawning WUA (CH1)
- (-5)
++ (+10)
+ (+9)
++ (+10)
Thermal egg mortality (CH3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+2)
Redd Dewatering (CH6)
ni (-1)
+ (+4)
+ (+4)
+ (+4)
Redd Scour (CH5)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (CH4)
+ (+4)
ni (+3)
ni (+3)
+ (+8)
Rearing WUA (CH2)
- (-8)
- (-4)
- (-8)
- (-5)
Legend
++
+
ni
-
--
strong beneficial impact owing to project alternative
small beneficial impact owing to project alternative
negligible detected impact owing to project alternative
small negative impact owing to project alternative
strong negative impact owing to project alternative
Table 3.3: Operation and conveyance effects are shown for different NODOS scenarios in
the Sacramento River ecoregion using the change in the percentage of favorable
years relative to the No Action Alternative (RS method). Numbers in brackets
refer to the increased percentage of simulation years having a favorable rating.
**Results of these meander/erosion model dependent performance indicators are
for the Sacramento River channel with existing revetment (no revetment
removal).
Focal species
Performance indicator
Action Alternatives
vs. No Action Alternative
Existing
(comparison 1)
Alt A
(comparison 3)
Alt B
(comparison 5)
Alt C
(comparison 7)
Fremont
Cottonwood
Initiation success (FC1)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Post-initiation scour risk
(FC2)
- (-9)
++ (+11)
- (-7)
++ (+16)
Bank Swallows
Habitat potential/suitability
(BASW1)**
ni (+/-0)
- (-4)
- (-5)
ni (-3)
Peak flow during nesting
period (BASW2)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Western Pond
Turtles
Large Woody Debris
Recruitment (LWD)**
ni (+3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Green Sturgeon
Egg temperature preferences
(GS1)
ni (-1)
+ (+5)
+ (+7)
+ (+7)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
91 | Page
Focal species
Performance indicator
Action Alternatives
vs. No Action Alternative
Existing
(comparison 1)
Alt A
(comparison 3)
Alt B
(comparison 5)
Alt C
(comparison 7)
Steelhead
Spawning WUA (ST1)
ni (+/- 0)
ni (+2)
ni (+2)
ni (+2)
Thermal egg mortality (ST3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Redd Dewatering (ST6)
ni (+/-0)
+ (+5)
+ (+6)
+ (+5)
Redd Scour (ST5)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (ST4)
ni (+/-0)
- (-6)
- (-4)
- (-7)
Rearing WUA (ST2)
ni (+3)
+ (+8)
+ (+8)
+ (+8)
Fall Chinook
Spawning WUA (CH1)
ni (-2)
- (-4)
- (-4)
- (-7)
Thermal egg mortality (CH3)
ni (-1)
ni (+2)
ni (+/-0)
ni (+2)
Redd Dewatering (CH6)
ni (+/-0)
+ (+4)
ni (+2)
+ (+4)
Redd Scour (CH5)
ni (+/-0)
ni (+/-0)
ni (-1)
ni (-1)
Juvenile Stranding (CH4)
ni (+/-0)
ni (-3)
- (-4)
- (-4)
Rearing WUA (CH2)
ni (+/-0)
+ (+7)
+ (+7)
+ (+7)
Late Fall
Chinook
Spawning WUA (CH1)
ni (+/-0)
ni (-3)
ni (-3)
ni (-3)
Thermal egg mortality (CH3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Redd Dewatering (CH6)
ni (+/-0)
ni (+2)
ni (+3)
ni (+2)
Redd Scour (CH5)
ni (+/-0)
ni (+2)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (CH4)
ni (+3)
- (-6)
ni (-3)
- (-6)
Rearing WUA (CH2)
ni (+1)
+ (+4)
+ (+6)
ni (+3)
Spring Chinook
Spawning WUA (CH1)
ni (+/-0)
ni (+3)
ni (+3)
ni (+2)
Thermal egg mortality (CH3)
ni (+2)
+ (+5)
+ (+6)
+ (+5)
Redd Dewatering (CH6)
ni (+1)
++ (+12)
++ (+13)
++ (+10)
Redd Scour (CH5)
ni (-2)
ni (-2)
ni (-2)
ni (-2)
Juvenile Stranding (CH4)
ni (+1)
ni (+3)
ni (+3)
ni (+3)
Rearing WUA (CH2)
ni (-1)
- (-9)
- (-9)
- (-9)
Winter Chinook
Spawning WUA (CH1)
+ (+5)
++ (+15)
++ (+14)
++ (+15)
Thermal egg mortality (CH3)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+2)
Redd Dewatering (CH6)
ni (-1)
+ (+5)
+ (+5)
+ (+5)
Redd Scour (CH5)
ni (+/-0)
ni (+/-0)
ni (+/-0)
ni (+/-0)
Juvenile Stranding (CH4)
- (-4)
ni (-1)
ni (-1)
+ (+4)
Rearing WUA (CH2)
+ (+8)
+ (+4)
ni (+/-0)
ni (+3)
Legend
++
+
ni
-
--
strong beneficial impact owing to project alternative
small beneficial impact owing to project alternative
negligible detected impact owing to project alternative
small negative impact owing to project alternative
strong negative impact owing to project alternative

Chapter 3: Effects Analysis Application of EFT
92 | Page
Overall
Overall, the rank order preferred NODOS action alternative (i.e., highest proportion of
favored conditions / least impact across all performance indicators) by focal species group
is provided in Table 3.4. Table 3.4 also illustrates that, as currently defined, none of the
interim NODOS alternatives favor all SacEFT focal species.
Table 3.4: Rank order performance of interim NODOS alternatives by SacEFT focal species
or group.
Focal Species (group)
Most favorable NODOS
alternative
Next most favorable NODOS alternative
Riparian focal species
NODOS Alternative C
NODOS Alternative A
Green Sturgeon
No significant difference in performance amongst NODOS A, B or C
Steelhead
NODOS Alternative B
n/a
Fall Chinook
NODOS Alternative A
n/a
Late Fall Chinook
NODOS Alternative B
n/a
Spring Chinook
NODOS Alternative B
Winter Chinook
NODOS Alternative C
NODOS Alternative A
That no one alternative was beneficial for all focal species considered in SacEFT was not
surprising, given that different species, and even different life stages of a given species, are
responsive to different conditions and habitat attributes.
With respect to fisheries resources, we recommend that the detailed results presented in
TNC and ESSA (2012) be considered in conjunction with the results from other modeling
exercises (weight of evidence).
For terrestrial species, which are being given less consideration outside of SacEFT, we
were concerned with Alternative B which, according to SacEFT, has the most negative
impacts relative to Alternatives A and C. Alternative B, which does not include the
construction of a pumping station and the Delevan Pipeline, is expected to adversely impact
bank swallows and not yield the benefits to cottonwood that are found in Alternatives A and
C.
These results suggest that from an ecosystem management standpoint, it is favorable to
include a diversion point that is far downstream of the Glenn-Colusa Irrigation District
(GCID) diversion. Doing so would allow water to be routed through a relatively longer reach
of the Middle Sacramento River before being withdrawn for the new storage facility.
Allowing water to remain in the river as long as possible before diverting it to the storage
facility would enhance geomorphic processes such as bank erosion and sediment
deposition, both of which are important for creating nesting cutbanks for swallows and
appropriate recruitment sites for cottonwoods.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
93 | Page
3.3 Effects Analysis Application of EFT to Selected Bay Delta
Conservation Plan Scenarios
3.3.1 Introduction
The Bay Delta Conservation Plan (BDCP) is one of the largest Habitat Conservation Plans
ever envisioned. In a letter addressed to the Deputy Secretary of the U.S. Department of
Interior, BDCP was characterized as "...a multi-generational bulwark against climate
change’s impacts to the foundational water supply for 25 million people and three million
acres of farmland." BDCP was developed to reconcile the co-equal goals of improving water
supply reliability while ensuring recovery and protection of aquatic and riparian species,
including endangered species permit requirements for operations of the Federal Central
Valley Project (CVP) and the State Water Project (SWP). The Plan includes proposals for
new points of diversion in the North Delta, new operations criteria, extensive floodplain and
tidal marsh restoration, and new governance, oversight and some contemplation of adaptive
management and related science programs. The Plan applicants are seeking Habitat
Conservation Plan (HCP)/Natural Communities Conservation Plan (NCCP) permits that will
guide water exports and habitat management for 50 years (BDCP 2013).
Once a vast marsh and floodplain with meandering channels and sloughs, the Delta did,
and though diminished, still does, provide a vital migratory corridor and dynamic rearing
habitat for a rich diversity of fish, wildlife, and plants. The Delta today is vastly altered by a
system of manmade levees and dredged waterways constructed to support farming and
urban development, and to provide flood protection for local towns and cities. The natural
flows in the Delta have also been substantially altered by operation of the dams and
diversions of the State Water Project (SWP) and Central Valley Project (CVP), which deliver
water to millions of Californians. In certain portions of the Delta, fish are pulled toward and
into the export pumps where they can become impinged, disoriented and trapped. In
addition to flows, many other factors affect species productivity and resilience in the Delta,
including: water quality issues (e.g., salinity, dissolved oxygen and toxic substances); an
alarming array of nonnative species; hatchery management; overfishing; and complex
interacting, non-stationary food webs, and related primary production and predation
dynamics.
With so many unprecedented and relentless changes, California has struggled for several
decades to balance competing demands for the Delta’s resources. Several Delta species
are now listed under state and federal laws to prevent extinction, and they have come to
symbolize the estuary’s compromised ecology. At stake are California’s natural heritage and
its water, food and economic security. In response to these challenges, the BDCP includes
67 goals and 165 objectives for 56 fish and terrestrial species, their habitats, and the Delta
ecosystem. The BDCP goes on to detail 22 separate conservation measures intended to
reverse the decline of the Delta’s native fish, plant and wildlife species (BDCP 2013). To do
so, nested within the SWP/CVP's acutely constrained regulatory environment, these

Chapter 3: Effects Analysis Application of EFT
94 | Page
measures include attempts to improve more ecologically functional flow patterns through
the Delta, as well as measures for accelerated habitat restoration (30,000 acres of aquatic
habitat over the next 15 years), including reconnecting floodplains and tidal habitats. BDCP
documentation suggests that as conservation measures are being implemented and
monitoring data become available, an adaptive management and coordinated science
process will be used to inform whether adjustments to the conservation measures (including
flow management) are necessary to improve their effectiveness. The initial analysis of these
measures and associated alternatives and impacts to humans and the environment are
described in a separate document – the Bay Delta Conservation Plan Environmental Impact
Report/Environmental Impact Statement (BDCP 2013).
While portions of SacEFT were used as part of the larger upstream effects analysis of
BDCP, this Chapter represents the first complete effects analysis using EFT (SacEFT and
DeltaEFT) of selected BDCP alternatives. Rather than being limited to a few species and
the relative suitability outputs of EFT, our BDCP effects analysis provides a deeper
exploration using all EFT performance indicators and outputs to provide new insights about
Sacramento River and Delta effects and trade-offs.
3.3.2 Reference Case & Alternative Scenarios
From among the numerous scenarios developed and assessed over the course of the
BDCP EIS/R (Table 3.6), a subset of four scenarios emerged as leading candidates for
future water conveyance, capacity, operation and habitat restoration. These four are the
scenarios that have been used in our EFT effects analysis. Specifically, we evaluated the
performance of: a No Action Alternative (NAA) with existing conveyance infrastructure; an
Expected Starting Operation (ESO); a High Outflow Scenario (HOS) where the facilities are
operated in a way that allows for occasional high spring and fall outflows; and a Low
Outflow Scenario (LOS) with lower spring and fall outflows. Further details on these
alternatives are described below in Table 3.6.
The effects analysis portion of BDCP is one of the most complex modeling efforts of its kind,
and certainly the most complex ever attempted in the Delta. The basis for the BDCP
analysis is hydrologic simulation modeling that provides flow, water elevations, temperature
and salinity at various locations throughout the Delta and its upstream areas. All BDCP
hydrosystem simulations are founded on the use of the CALSIM II model, disaggregating its
monthly output into daily flow and temperature using the USRDOM and USRWQM models
(see Section 2.6). The DSM2 model is used to simulate the hydrosystem-ocean system
downstream of Sacramento, including Fremont Weir and Yolo Bypass. The HYDRO and
QUAL modules of DSM2 provide flow and stage, and temperature and electroconductivity,
respectively (Section 2.6). The simulations are based on a set of CALSIM and DSM2 input
files provided by DWR and described in BDCP (2012b).
Currently, the preferred alternative is to construct a new point of diversion in the North Delta
on the Sacramento River near Freeport, with the goal of completion in 2025. This diversion

Final Report
Application of EFT to Complement Water Planning for Multiple Species
95 | Page
is to have three screened intakes that will divert water into forebays and a pair of 40 foot
diameter tunnels (side by side, buried more than 150 feet below ground) capable of
transmitting a maximum of 9,000 cfs by gravity feed. These tunnels will link to existing SWP
and CVP export facilities located in the South Delta (Figure 3.2). The construction and
combined operations of these facilities — typically referred to as dual facilities (new North
Delta and existing South Delta export pumps) — are the foundation of the plan. In addition
to more eco-friendly water operations, BDCP pairs construction of this infrastructure with
extensive physical conservation measures to mitigate impacts of the project and recover
and protect 'covered' species (e.g., Table 3.5). The primary difference among the BDCP
alternatives is the timing and magnitude of pumping and releases. The BDCP calls for
increasing exports in wet years and reducing them in dry years, taking advantage of the
increased operational flexibility provided by two new points of diversion. If this operational
approach were followed in real-world practice, this would reduce stress on Delta
ecosystems during drier periods.
Figure 3.2: General map showing proposed (August 2013) North Delta point of diversion and
new conveyance tunnels to State and Federal pumping plants in the South Delta
[Source:http://baydeltaconservationplan.com/Libraries/Dynamic_Document_
Library/ Map_of_Proposed_BDCP_Changes_8-15-13.sflb.ashx].

Chapter 3: Effects Analysis Application of EFT
96 | Page
The habitat restoration features shown below (Table 3.5) are common to all the BDCP
alternatives, all of which are absent from the NAA simulations. These restoration activities
are independent of the conveyance options and hydrosystem operation.
Table 3.5: Summary of BDCP physical restoration actions.
65,000 acres of restored freshwater and brackish tidal habitat within the BDCP Restoration Opportunity
Areas
10,000 acres of seasonally inundated floodplain habitat within the North, East, and/or South Delta
20 linear miles of channel margin habitat enhancement in the Delta
5,000 acres of restored valley/foothill riparian habitat
2,000 acres of restored grassland and 8,000 acres of protected or enhanced grassland within BDCP
Conservation Zones 1, 8, and/or 11
Restored vernal pool complex to achieve no net loss and 600 acres of protected vernal pool complex
within Conservation Zones 1, 8, and/or 11
400 acres of restored non-tidal freshwater marsh within Conservation Zones 2 and 4
400 acres of protected alkali seasonal wetland complex in Conservation Zones 1, 8, and 11
17,000 – 33,000 acres of protected agricultural habitat areas
While EFT does consider restoration, flows and water temperatures in the Yolo Bypass,
EFT does not address the potential benefits of other physical habitat restoration measures.
While a major feature carried forward in the BDCP alternatives is the voluminous current
operational obligations (e.g., "Operate in accordance with State Water Board D-1641"), the
BDCP alternatives do include some additional hydrosystem changes in some scenarios,
which have significant potential for biological impacts. These include: the addition of a notch
to Fremont Weir17; changes to the management of the Delta Cross Channel gate; changes
to exports; and the inclusion of Fall X2 management (Table 3.6).
When present, Fall X2 management is intended to increase fall outflow, improving habitat
for Delta smelt in wet years. BDCP operational changes also include criteria for: operation
of Fremont Weir/Yolo Bypass; Delta inflow and outflow; Delta Cross Channel gate
operations; Rio Vista minimum instream flows; and Delta water quality and residence time.
Specific details are only documented directly in CALSIM II WRESL files and cannot be
ascertained from the publically available BDCP documentation.
The BDCP scenarios attempt to account for and isolate the effect of future climate and
anticipated levels of development and water demand by simulating two sets of plausible
future conditions. The first snapshot-in-time is “Early Long Term” (ELT), which represents
17 Fremont Weir is notched in some scenarios to provide a more consistent water supply at the southern end of Yolo Bypass,
improving habitat for splittail.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
97 | Page
an ensemble-forecast (BDCP 2012a) future climate around the year 2025, at which time a
substantial number of habitat restoration activities will have taken place and a new dual
conveyance system will be in operation. The second snapshot-in-time is “Late Long Term”
(LLT), which represents an ensemble-forecast future climate around the year 2060, along
with full implementation and operation of the BDCP conservation strategy. Both the ELT
and LLT projections include the effect of climate change in seasonal hydrology (amount and
timing of runoff), changes to seasonal air temperature, and increase in sea level.
To provide a reference case against which the BDCP simulations can be compared, three
“No Action Alternative” (NAA) simulations are used. The NAA alternatives (for different time
periods) represent water conveyance and operation without the addition of a new
conveyance system or restoration. NAA-Current represents near-present (2015) conditions,
while the NAA-ELT and NAA-LLT scenarios represent conditions around 2025 and 2060,
respectively, including climate change and sea level rise. By comparing the NAA
simulations with the action alternatives (ESO, HOS and LOS), it is possible to identify
changes due solely to climate/sea level and those due to the operational features of the
action alternative.
The key features of the BDCP alternatives and NAA simulations are listed below (Table
3.6). As noted above, all BDCP scenarios share the same habitat remediation measures to
reduce other stressors. Each action alternative also includes operational criteria for water
supply infrastructure, habitat conservation components, and measures to reduce the impact
of other stressors on other species. Outside of water exports and habitat conditions,
stressors that are considered by the larger BDCP EIS/R (but are not considered by EFT)
include exposure to contaminants, competition, predation and changes to the ecosystem
and food web caused by non-native species.

Chapter 3: Effects Analysis Application of EFT
98 | Page
Table 3.6: Summary of reference case (NAA: No Action Alternative) scenario and three
BDCP action alternatives (ESO: Expected Starting Operations; LOS: Low Output
Spring; HOS: High Output Spring). Three time periods are present in combination
with the scenarios: Current (2015), Early Long Term (ELT, 2025) and Late Long
Term (LLT, 2060).
Name
Conveyance
modifications
Level of human
demand
Climate change
Major operational features
NAA-Current
= No Action
Alternative
= EBC2
Current hydrosystem:
no changes to
size/number of dams,
capability of Delta
pumps, gates.
Fremont Weir NOT
notched.
Current (2015)
demand
Current climate
(2015), inflows
and sea level
conditions
The BDCP reference case for
the hydrosystem without
changes to conveyance or
habitat; habit conservation
components described
above not present.
No High Spring X2 outflow
No High Fall X2 outflow
NAA-ELT
2025 projected
level of
development
and demand
Future climate
centered on
ensemble
prediction for
2025 period; 15
cm mean sea level
rise
Operations based on State
Water Board D-1641, USFWS
(2008), NMFS (2009)
No High Spring X2 outflow
High Fall X2 outflow
NAA-LLT
2060 projected
level of
development
and demand
Future climate
centered on
ensemble
prediction for
2060 period; 45
cm mean sea level
rise
ESO-ELT
= Expected
Starting
Operations
= H3
= Alt 4
9,000 cfs via three
intakes of 3,000 cfs
each between
Clarksburg and
Walnut Grove in the
North Delta, feeding
two 40-ft diameter
gravity fed tunnels
buried more than
150ft below ground,
and running approx.
30 miles to South
Delta pumps.
2025 projected
demand
Future climate
centered on
ensemble
prediction for
2025 period; 15
cm mean sea level
rise
Operations based on State
Water Board D-1641, USFWS
(2008), NMFS (2009)
New intake facility
operational
Restoration actions not fully
implemented
No High Spring X2 outflow
High Fall X2 outflow
ESO-LLT
= Expected
Starting
Operations
= H3
= Alt 4
2060 projected
demand
Future climate
centered on
ensemble
prediction for
2060 period; 45
cm mean sea level
rise

Final Report
Application of EFT to Complement Water Planning for Multiple Species
99 | Page
Name
Conveyance
modifications
Level of human
demand
Climate change
Major operational features
LOS-ELT
= Low Output
Spring
= H1
Fremont Weir
modified (notched).
Currently flow onto
the Yolo Bypass only
occurs when the
Verona gauge exceeds
55,000 cfs.
Modifications to the
Fremont Weir would
allow 1,000 cfs to flow
onto the floodplain
when flow at Verona
exceeds 25,000 cfs.
Flow through the Weir
would climb to 6,000
cfs when the river
approaches 55,000
cfs.
2025 projected
demand
Future climate
centered on
ensemble
prediction for
2025 period; 15
cm mean sea level
rise
Operations based on State
Water Board D-1641, USFWS
(2008), NMFS (2009)
New intake facility
operational
Restoration actions not fully
implemented
No High Spring X2 outflow
No High Fall X2 outflow
HOS-ELT
= High Output
Spring
= H4
2025 projected
Future climate
centered on
ensemble
prediction for
2025 period; 15
cm mean sea level
rise
Operations based on State
Water Board D-1641, USFWS
(2008), NMFS (2009)
New intake facility
operational
Restoration actions not fully
implemented
High Spring X2 outflow
High Fall X2 outflow
What may not be clear from the short descriptions of these alternatives is that upstream
reservoir operations and Delta export operations are highly constrained by a myriad of
upstream and downstream consumptive uses and related flow and water quality
regulations. These constraints significantly reduce the operational flexibility of the dual
facilities, greatly limiting the degree of contrast in the simulated results for these BDCP
scenarios, which reduces contrast in the EFT effects analysis results. The current regulatory
and infrastructure constraints on operations limit the ability of BDCP to fully explore
compatible options for meeting the co-equal export and ecosystem objectives. The action
alternatives admitted into the BDCP analysis represent a fraction of the solution space that
is truly available to realize objectives.
3.3.3 BDCP Results and Discussion
Presenting EFT findings requires describing results for two ecoregions (Sacramento River
and Delta), 13 species, 25 performance indicators, multiple driving physical datasets and
the emergent synthesis of alternatives given by two companion methods (RS, ES methods).
Given the breadth of results, we organize EFT effects analysis outcomes in the following
structured order:

Chapter 3: Effects Analysis Application of EFT
100 | P a g e
1. First, we look at the degree of physical change amongst alternative scenarios
being evaluated (median changes in flow, water temperatures, salinity at select
index locations).
2. Next, we present high level effect roll-ups based on the Relative Suitability (RS)
synthesis methodology (see Section 2.7.2), which compares changes in the
proportion of favorable years amongst alternatives.
3. Third, we perform a companion synthesis where the raw (no suitability scoring
assigned) multi-year median values are compared amongst alternatives (termed
Effect Size (ES) results, see Section 2.7.5). Correspondence between the RS and
ES methods adds additional confidence in conclusions beyond the signal from either
method alone.
4. Finally, we conclude with a species net effect summary, looking at the number of
performance indicators that surpass our chosen thresholds for meaningful change
(either a ±10% change in count of favorable values for RS, or a ±5% change in
median values for the ES synthesis method). This is a preliminary step leading to the
overall Net Effect Score (NES) for each species. NES addresses uncertainty in the
overall assessment, including the challenge of integrating multiple independent
attributes (indicators) for single species. The NES is based on a consistent logic that
considers the weight of evidence provided by the RS and ES methods, penalizing
discrepancies when the two major effects analysis methods differ.
Physical Changes among Alternative Scenarios
The material in this section summarizes key flow, water temperature and salinity changes
associated with the selected BDCP alternatives. We first establish the general nature of
these physical changes prior to venturing into biological interpretation.
Sacramento River
Flow
For the early long-term (2025) alternatives, Table 3.7 shows median May and June flows
are higher under LOS-ELT alternative and lower in November relative to the NAA-ELT
reference scenario. All three alternatives (ESO-ELT, LOS-ELT and HOS-ELT) generate
lower median flows in September and November relative to NAA-ELT.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
101 | P a g e
Table 3.7: Flow values at Keswick and Hamilton City are shown for selected BDCP
scenarios at the Early Long Term (ELT) future climate period. 
Month
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Flow - Keswick
January
4,226
4,120
(-2.5%)
4,383
(3.7%)
4,097
(-3.0%)
February
4,151
4,294
(3.4%)
4,181
(0.7%)
3,985
(-4.0%)
March
4,379
4,442
(1.4%)
4,380
(0.0%)
4,391
(0.3%)
April
5,465
5,512
(0.9%)
5,639
(3.2%)
5,446
(-0.3%)
May
7,082
7,310
(3.2%)
7,474
(5.5%)
7,173
(1.3%)
June
10,502
11,031
(5.0%)
11,070
(5.4%)
10,503
(0.0%)
July
13,810
14,081
(2.0%)
14,144
(2.4%)
13,861
(0.4%)
August
10,139
10,015
(-1.2%)
9,922
(-2.1%)
10,482
(3.4%)
September
7,017
6,182
(-11.9%)
6,202
(-11.6%)
6,103
(-13.0%)
October
5,936
5,858
(-1.3%)
5,976
(0.7%)
6,115
(3.0%)
November
5,420
4,549
(-16.1%)
4,468
(-17.6%)
4,597
(-15.2%)
December
4,025
4,060
(0.9%)
4,139
(2.8%)
3,980
(-1.1%)
Month
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Flow - Hamilton City
January
9,950
10,362
(4.1%)
10,628
(6.8%)
10,131
(1.8%)
February
12,602
12,662
(0.5%)
12,755
(1.2%)
12,545
(-0.5%)
March
10,716
10,903
(1.7%)
10,969
(2.4%)
10,775
(0.5%)
April
6,348
6,356
(0.1%)
6,475
(2.0%)
6,402
(0.8%)
May
6,645
6,948
(4.6%)
7,031
(5.8%)
6,699
(0.8%)
June
7,931
8,302
(4.7%)
8,356
(5.4%)
7,949
(0.2%)
July
10,455
10,604
(1.4%)
10,503
(0.5%)
10,203
(-2.4%)
August
7,626
7,501
(-1.6%)
7,432
(-2.5%)
7,834
(2.7%)
September
6,880
5,971
(-13.2%)
6,036
(-12.3%)
5,923
(-13.9%)
October
5,926
5,862
(-1.1%)
6,022
(1.6%)
6,149
(3.8%)
November
7,079
5,852
(-17.3%)
5,512
(-22.1%)
5,860
(-17.2%)
December
6,858
6,628
(-3.4%)
7,034
(2.6%)
6,703
(-2.3%)
 The NAA-ELT scenario serves as a comparative reference case, with percentage differences shown below absolute median
effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in comparison to the
reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-20% and
>20%.
For the late long-term (2060s) climate change period, median flow is higher April - June and
reduced in August and November under the ESO-LLT scenario relative to NAA-LLT (Table
3.8).

Chapter 3: Effects Analysis Application of EFT
102 | Page
Table 3.8: Flow values at Keswick and Hamilton City are shown for selected BDCP
scenarios at the Late Long Term (LLT) future climate period. 
Month
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Keswick
January
4,219
4,281
(1.5%)
February
4,059
4,199
(3.5%)
March
4,347
4,445
(2.2%)
April
5,493
5,710
(4.0%)
May
6,820
7,479
(9.7%)
June
10,994
12,126
(10.3%)
July
14,236
13,988
(-1.7%)
August
10,521
9,872
(-6.2%)
September
6,737
7,069
(4.9%)
October
6,521
6,586
(1.0%)
November
5,071
4,588
(-9.5%)
December
3,939
4,047
(2.8%)
Month
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Hamilton City
January
10,176
10,003
(-1.7%)
February
12,519
12,673
(1.2%)
March
10,654
10,812
(1.5%)
April
6,414
6,807
(6.1%)
May
6,796
7,619
(12.1%)
June
8,496
9,407
(10.7%)
July
10,940
10,682
(-2.4%)
August
8,080
7,373
(-8.8%)
September
6,623
6,951
(5.0%)
October
6,580
6,520
(-0.9%)
November
7,181
5,846
(-18.6%)
December
6,772
6,844
(1.1%)
 The NAA-LLT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of months measured as percentages are based on the simple
arithmetic difference in comparison to the reference case. Green and red shadings are used to highlight 3
levels of positive and negative changes: 5-10%, 10-20% and >20%.
Table 3.9 most clearly shows the expected change in median flow associated with climate
change. With NAA-Current as the reference case, there is a progressive reduction in
median flows February to May, with increased flows June to November (exclusive of
August) as one moves from the early long term to late long term.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
103 | Page
Table 3.9: Flow values at Keswick and Hamilton City are shown for three future climate and
demand scenarios. 
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Flow - Keswick
January
4,190
4,226
(0.9%)
4,219
(0.7%)
February
4,323
4,151
(-4.0%)
4,059
(-6.1%)
March
4,312
4,379
(1.5%)
4,347
(0.8%)
April
5,956
5,465
(-8.3%)
5,493
(-7.8%)
May
7,648
7,082
(-7.4%)
6,820
(-10.8%)
June
10,415
10,502
(0.8%)
10,994
(5.6%)
July
13,061
13,810
(5.7%)
14,236
(9.0%)
August
10,476
10,139
(-3.2%)
10,521
(0.4%)
September
6,040
7,017
(16.2%)
6,737
(11.5%)
October
6,043
5,936
(-1.8%)
6,521
(7.9%)
November
5,009
5,420
(8.2%)
5,071
(1.2%)
December
4,274
4,025
(-5.8%)
3,939
(-7.9%)
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Flow - Hamilton City
January
9,917
9,950
(0.3%)
10,176
(2.6%)
February
12,655
12,602
(-0.4%)
12,519
(-1.1%)
March
11,063
10,716
(-3.1%)
10,654
(-3.7%)
April
6,556
6,348
(-3.2%)
6,414
(-2.2%)
May
6,749
6,645
(-1.5%)
6,796
(0.7%)
June
7,857
7,931
(0.9%)
8,496
(8.1%)
July
9,533
10,455
(9.7%)
10,940
(14.8%)
August
7,901
7,626
(-3.5%)
8,080
(2.3%)
September
5,831
6,880
(18.0%)
6,623
(13.6%)
October
5,970
5,926
(-0.7%)
6,580
(10.2%)
November
6,047
7,079
(17.1%)
7,181
(18.8%)
December
7,005
6,858
(-2.1%)
6,772
(-3.3%)
 The NAA-Current scenario serves as a comparative reference case, with percentage differences shown below absolute
median effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in
comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-
10%, 10-20% and >20%.
The Cumulative Excess Streampower, defined as the sum of flows above a threshold of 425
cms at Hamilton City and strongly correlated with river meander migration, is relatively
similar between the BDCP scenarios at approximately 2.5 million cms (Table 3.10).
Counterintuitively, the Cumulative Excess Streampower increases in the Early and Late
Long Term future climate period by 4.9% and 8.9% respectively.

Chapter 3: Effects Analysis Application of EFT
104 | P a g e
Table 3.10: Excess Cumulative Streampower at Hamilton City (Cumulative Excess
Streampower is defined as the sum of flows above a threshold of 425 cms).
NAA-ELT
Referenc
e case
(233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Excess Cumulative Streampower
Total
2,515,800
2,550,698
(1.4%)
2,579,698
(2.5%)
2,543,941
(1.1%)
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Excess Cumulative Streampower
Total
2,399,198
2,515,800
(4.9%)
2,612,365
(8.9%)
Water Temperature
For the early long-term (2025) alternatives, and using NAA-ELT as the reference case,
simulated median water temperatures are expected to remain relatively constant between
project alternatives, with a maximum difference between the BDCP alternative and NAA-
ELT of approximately 3% for both the Keswick and Hamilton City locations. The maximum
difference between ESO-LLT and NAA-LLT in the Late Long Term future climate period is
approximately 2% for both the Keswick and Hamilton City locations.
Relative to near current conditions (NAA-current reference case), median water
temperatures become progressively warmer in all months, especially August to February
(Table 3.11). The predicted maximum median increase in temperature is 1.6°C (12.9%) in
October.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
105 | Page
Table 3.11: Water temperature values (degrees C) at Keswick and Hamilton City are shown
for three future climate and demand scenarios.
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Temperature - Keswick
January
7.9
8.3
(4.5%)
8.8
(10.4%)
February
7.6
8.1
(6.0%)
8.5
(12.0%)
March
8.2
8.6
(5.2%)
9.1
(11.3%)
April
8.9
9.4
(4.9%)
9.9
(10.3%)
May
9.5
10.0
(5.2%)
10.4
(9.3%)
June
10.0
10.3
(3.1%)
10.6
(6.0%)
July
10.5
10.8
(2.8%)
11.4
(8.5%)
August
11.2
11.8
(5.9%)
12.6
(12.4%)
September
12.3
12.8
(4.5%)
13.6
(11.0%)
October
12.2
13.0
(6.4%)
13.8
(12.9%)
November
11.6
12.2
(5.3%)
12.9
(11.2%)
December
9.9
10.3
(3.8%)
10.8
(9.4%)
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Temperature - Hamilton City
January
7.0
7.5
(7.0%)
8.0
(15.1%)
February
8.2
8.7
(6.7%)
9.2
(12.6%)
March
10.3
10.7
(4.3%)
11.3
(9.8%)
April
12.9
13.4
(3.8%)
14.0
(8.6%)
May
15.0
16.0
(6.3%)
16.4
(9.2%)
June
15.9
16.5
(4.0%)
17.0
(7.0%)
July
16.4
16.8
(2.7%)
17.5
(6.5%)
August
16.7
17.6
(5.2%)
18.4
(10.3%)
September
16.4
16.9
(3.0%)
17.9
(9.0%)
October
13.3
14.1
(6.3%)
14.8
(11.8%)
November
10.2
10.9
(6.9%)
11.6
(13.6%)
December
7.6
8.0
(5.9%)
8.6
(13.9%)
 The NAA-Current scenario serves as a comparative reference case, with percentage differences shown below absolute
median effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in
comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-
10%, 10-20% and >20%.
San Joaquin-Sacramento Delta
Flow
For the early long-term (2025) alternatives, median flows are generally higher October to
January and June (except LOS-ELT in November, which shows a reduction in flow at
Mallard Island), and lower in July and August (Table 3.12). ESO-ELT and LOS-ELT produce
lower March to May flows (Table 3.12). Median flow at Old and Middle River is more
positive for all BDCP scenarios relative to the NAA-ELT in all months except April and May
(Table 3.12).

Chapter 3: Effects Analysis Application of EFT
106 | Page
These patterns are generally preserved when comparing ESO-LLT relative to the NAA-LLT
(Table 3.13).
Table 3.12: Flow values at Mallard Island and Old and Middle River are shown for selected
BDCP scenarios at the Early Long Term (ELT) future climate period. 
Mon
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Flow - Mallard Island
Jan
16,617
17,771
(6.9%)
18,649
(12.2%)
18,672
(12.4%)
Feb
19,449
19,718
(1.4%)
19,783
(1.7%)
19,817
(1.9%)
Mar
29,135
27,564
(-5.4%)
27,837
(-4.5%)
27,864
(-4.4%)
Apr
15,904
14,791
(-7.0%)
14,791
(-7.0%)
16,220
(2.0%)
May
11,719
10,833
(-7.6%)
10,841
(-7.5%)
12,068
(3.0%)
Jun
7,638
8,164
(6.9%)
8,281
(8.4%)
8,072
(5.7%)
Jul
7,176
5,864
(-18.3%)
6,046
(-15.8%)
5,705
(-20.5%)
Aug
4,024
3,401
(-15.5%)
3,440
(-14.5%)
3,395
(-15.6%)
Sep
8,752
8,648
(-1.2%)
3,668
(-58.1%)
8,731
(-0.2%)
Oct
3,668
6,736
(83.6%)
6,595
(79.8%)
6,499
(77.2%)
Nov
8,316
9,957
(19.7%)
7,627
(-8.3%)
9,848
(18.4%)
Dec
7,295
9,668
(32.5%)
9,895
(35.6%)
9,496
(30.2%)
Mon
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Flow - Old and Middle River
Jan
-3,779
-1,709
(54.8%)
-1,888
(50.0%)
-1,441
(61.9%)
Feb
-3,314
-1,930
(41.8%)
-1,796
(45.8%)
-1,824
(45.0%)
Mar
-1,997
-861
(56.9%)
-836
(58.1%)
-671
(66.4%)
Apr
189
-550
(-390.3%)
-667
(-452.1%)
-311
(-264.1%)
May
-394
-862
(-119.0%)
-862
(-118.9%)
-564
(-43.3%)
Jun
-3,339
-2,103
(37.0%)
-2,096
(37.2%)
-1,660
(50.3%)
Jul
-9,618
-7,462
(22.4%)
-7,279
(24.3%)
-4,482
(53.4%)
Au
-9,314
-4,160
(55.3%)
-4,052
(56.5%)
-4,503
(51.7%)
Sep
-6,711
-3,612
(46.2%)
-4,607
(31.3%)
-3,387
(49.5%)
Oct
-5,294
-2,148
(59.4%)
-2,359
(55.4%)
-2,090
(60.5%)
Nov
-4,923
-3,445
(30.0%)
-4,541
(7.8%)
-3,265
(33.7%)
Dec
-6,562
-5,168
(21.2%)
-5,091
(22.4%)
-5,072
(22.7%)
 The NAA-ELT scenario serves as a comparative reference case, with percentage differences shown below absolute median
effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in comparison to the
reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-20% and
>20%.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
107 | Page
Table 3.13: Flow values at Mallard Island and Old and Middle River are shown for selected
BDCP scenarios at the Late Long Term (LLT) future climate period. 
Month
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Mallard Island
January
17,359
18,238
(5.1%)
February
19,858
19,954
(0.5%)
March
29,511
26,743
(-9.4%)
April
15,793
14,587
(-7.6%)
May
11,479
10,853
(-5.5%)
June
8,003
7,635
(-4.6%)
July
8,540
5,904
(-30.9%)
August
4,191
2,916
(-30.4%)
September
9,102
9,802
(7.7%)
October
5,640
7,516
(33.3%)
November
7,986
9,410
(17.8%)
December
8,255
9,717
(17.7%)
Month
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Old and Middle River
January
-3,678
-2,293
(37.7%)
February
-3,264
-1,972
(39.6%)
March
-2,174
-1,276
(41.3%)
April
-672
-1,003
(-49.3%)
May
-1,026
-1,404
(-36.8%)
June
-3,191
-2,382
(25.4%)
July
-7,504
-4,728
(37.0%)
August
-7,539
-3,904
(48.2%)
September
-4,978
-2,003
(59.8%)
October
-4,178
-1,952
(53.3%)
November
-4,418
-2,963
(32.9%)
December
-5,574
-4,098
(26.5%)
 The NAA-LLT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of months measured as percentages are based on the simple
arithmetic difference in comparison to the reference case. Green and red shadings are used to highlight 3
levels of positive and negative changes: 5-10%, 10-20% and >20%.
Table 3.14 shows the expected change in median flow associated with climate change.
Monthly median patterns are less coherent, with the exception of increasing flows
September to November, and a tendency for decreased flows February to June and August.

Chapter 3: Effects Analysis Application of EFT
108 | P a g e
Table 3.14: Flow values at Mallard Island and Old and Middle River are shown for three
future climate and demand scenarios. 
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Flow - Mallard Island
January
16,281
16,617
(2.1%)
17,359
(6.6%)
February
20,170
19,449
(-3.6%)
19,858
(-1.6%)
March
31,947
29,135
(-8.8%)
29,511
(-7.6%)
April
16,104
15,904
(-1.2%)
15,793
(-1.9%)
May
11,819
11,719
(-0.8%)
11,479
(-2.9%)
June
8,703
7,638
(-12.2%)
8,003
(-8.0%)
July
6,217
7,176
(15.4%)
8,540
(37.4%)
August
4,725
4,024
(-14.8%)
4,191
(-11.3%)
September
5,637
8,752
(55.3%)
9,102
(61.5%)
October
3,198
3,668
(14.7%)
5,640
(76.3%)
November
6,253
8,316
(33.0%)
7,986
(27.7%)
December
7,442
7,295
(-2.0%)
8,255
(10.9%)
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Flow - Old and Middle River
January
-3,897
-3,779
(3.0%)
-3,678
(5.6%)
February
-3,156
-3,314
(-5.0%)
-3,264
(-3.4%)
March
-2,239
-1,997
(10.8%)
-2,174
(2.9%)
April
-518
189
(136.5%)
-672
(-29.6%)
May
-910
-394
(56.7%)
-1,026
(-12.7%)
June
-3,358
-3,339
(0.6%)
-3,191
(5.0%)
July
-8,912
-9,618
(-7.9%)
-7,504
(15.8%)
August
-7,425
-9,314
(-25.4%)
-7,539
(-1.5%)
September
-6,485
-6,711
(-3.5%)
-4,978
(23.2%)
October
-6,380
-5,294
(17.0%)
-4,178
(34.5%)
November
-5,923
-4,923
(16.9%)
-4,418
(25.4%)
December
-5,601
-6,562
(-17.2%)
-5,574
(0.5%)
 The NAA-Current scenario serves as a comparative reference case, with percentage differences shown below absolute
median effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in
comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-
10%, 10-20% and >20%.
Water Temperature
For the Early Long Term (2025) alternatives, and using NAA-ELT as the reference case,
simulated median water temperatures are expected to remain relatively constant between
project alternatives with differences between the BDCP alternative and NAA being 0.5°C or
less for both the Port Chicago and Terminous locations for both the ELT and LLT future
climate periods.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
109 | Page
Moving from the Early Long Term to the Late Long Term, median water temperatures
become progressively warmer, especially September to May (Table 3.15). Median water
temperatures show the least change (though still warmer) June to August (Table 3.15).
Table 3.15: Water temperature values (degrees C) at Port Chicago and Terminous are shown
for three future Climate and Demand scenarios. 
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Temperature - Port Chicago
January
9.2
9.4
(2.0%)
9.9
(6.8%)
February
10.8
11.2
(3.4%)
11.4
(5.6%)
March
13.2
13.5
(2.3%)
13.9
(4.7%)
April
14.9
15.5
(4.3%)
15.7
(5.6%)
May
17.3
17.9
(3.5%)
18.1
(4.6%)
June
19.4
19.8
(2.4%)
20.1
(3.6%)
July
20.6
21.1
(2.2%)
21.4
(3.5%)
August
20.5
20.9
(1.9%)
21.2
(3.5%)
September
19.6
19.9
(1.2%)
20.5
(4.3%)
October
17.5
17.9
(2.1%)
18.2
(4.2%)
November
14.6
14.8
(1.3%)
15.2
(3.8%)
December
10.5
10.9
(3.3%)
11.2
(6.5%)
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Temperature - Terminous
January
9.8
10.3
(5.0%)
10.5
(7.4%)
February
11.6
11.9
(3.2%)
12.1
(4.4%)
March
13.8
14.1
(2.5%)
14.5
(5.5%)
April
14.9
15.7
(5.4%)
16.0
(7.2%)
May
17.5
18.3
(4.3%)
18.5
(5.5%)
June
19.7
20.2
(2.7%)
20.6
(4.4%)
July
21.2
21.9
(2.9%)
22.3
(4.8%)
August
21.0
21.5
(2.2%)
22.0
(4.7%)
September
19.8
20.2
(1.9%)
20.9
(5.5%)
October
17.2
17.9
(4.2%)
18.3
(6.8%)
November
14.1
14.4
(2.1%)
15.1
(6.6%)
December
10.3
10.6
(3.4%)
11.2
(9.6%)
 The NAA-Current scenario serves as a comparative reference case, with percentage differences shown below absolute
median effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in
comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-
10%, 10-20% and >20%.

Chapter 3: Effects Analysis Application of EFT
110 | P a g e
Salinity
Median salinity (measured as EC) at Collinsville (Table 3.16) is lower under the ESO-ELT
scenario relative to the NAA-ELT in January, July, and October to December, and higher in
February to May. Median salinity is lower under the LOS-ELT scenario relative to the NAA-
ELT in January, July and October, and higher in February to May, September and
November to December. Median salinity is lower under the HOS-ELT scenario relative to
the NAA-ELT in January, May, and October to December, and higher in February to April
and July to August.
The difference between BDCP scenarios is that median salinity is lower in May and higher
in July for the HOS-ELT scenario than the other two alternatives, and salinity is higher in
September, November and December for the LOS-ELT scenario than the other two
alternatives.
Median salinity (measured as EC) at Port Chicago (Table 3.16) is lower under the ESO-ELT
scenario relative to the NAA-ELT in January and October to December, and higher in
February to April. Median salinity is lower under the LOS-ELT scenario relative to the NAA-
ELT in January and October, and higher in February to April and November to December.
Median salinity is lower under the HOS-ELT scenario relative to the NAA-ELT in January
and October to December, and higher in February and March.
The difference between BDCP scenarios is that median salinity is higher in March and lower
in April for the HOS-ELT scenario than the other two alternatives, and salinity is higher in
November and December for the LOS-ELT scenario than the other two alternatives.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
111 | P a g e
Table 3.16: EC (a proxy for salinity) values at Collinsville and Port Chicago are shown for
selected BDCP scenarios at the Early Long Term (ELT) future climate period. 
Mon
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
EC - Collinsville
Jan
2,325
1,292
(-44.4%)
1,359
(-41.5%)
1,306
(-43.8%)
Feb
523
569
(8.9%)
592
(13.3%)
563
(7.7%)
Mar
223
269
(20.3%)
272
(21.6%)
279
(24.7%)
Apr
419
504
(20.2%)
505
(20.4%)
450
(7.4%)
May
1,090
1,267
(16.2%)
1,260
(15.6%)
973
(-10.7%)
Jun
2,838
2,715
(-4.3%)
2,741
(-3.4%)
2,703
(-4.7%)
Jul
4,342
3,979
(-8.4%)
3,992
(-8.1%)
4,617
(6.3%)
Aug
5,878
6,159
(4.8%)
6,065
(3.2%)
6,273
(6.7%)
Sep
7,822
8,185
(4.6%)
8,832
(12.9%)
8,213
(5.0%)
Oct
8,501
5,133
(-39.6%)
6,129
(-27.9%)
5,113
(-39.9%)
Nov
5,343
4,479
(-16.2%)
6,353
(18.9%)
4,541
(-15.0%)
Dec
3,972
3,456
(-13.0%)
5,434
(36.8%)
3,404
(-14.3%)
Mon
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
EC - Port Chicago
Jan
9,525
7,978
(-16.2%)
8,086
(-15.1%)
7,945
(-16.6%)
Feb
3,910
4,354
(11.4%)
4,418
(13.0%)
4,343
(11.1%)
Mar
1,947
2,148
(10.3%)
2,216
(13.8%)
2,437
(25.1%)
Apr
4,000
4,630
(15.7%)
4,601
(15.0%)
4,137
(3.4%)
May
6,990
7,244
(3.6%)
7,174
(2.6%)
6,680
(-4.4%)
Jun
10,873
10,435
(-4.0%)
10,380
(-4.5%)
10,395
(-4.4%)
Jul
12,982
12,700
(-2.2%)
12,748
(-1.8%)
13,194
(1.6%)
Aug
15,154
15,257
(0.7%)
15,162
(0.1%)
15,402
(1.6%)
Sep
17,075
17,293
(1.3%)
17,609
(3.1%)
17,334
(1.5%)
Oct
17,480
14,402
(-17.6%)
15,536
(-11.1%)
14,614
(-16.4%)
Nov
13,732
12,094
(-11.9%)
15,314
(11.5%)
12,037
(-12.3%)
Dec
13,092
12,208
(-6.8%)
14,823
(13.2%)
12,074
(-7.8%)
 The NAA-ELT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of months measured as percentages are based on the simple arithmetic
difference in comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive
and negative changes: 5-10%, 10-20% and >20%.
Median salinity (measured as EC) at Collinsville (Table 3.17) is lower under the ESO-LLT
scenario relative to the NAA-LLT in January and September to December, and higher in
March to August. Median salinity at Port Chicago is lower under the ESO-LLT scenario
relative to the NAA-LLT in January and October to December, and higher in February to
April and August.

Chapter 3: Effects Analysis Application of EFT
112 | Page
Table 3.17: EC (a proxy for salinity) values at Collinsville and Port Chicago are shown for
selected BDCP scenarios at the Late Long Term (LLT) future climate period. 
Month
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
EC - Collinsville
January
2,422
1,358
(-43.9%)
February
633
660
(4.3%)
March
238
310
(30.4%)
April
504
640
(26.9%)
May
1,694
1,789
(5.6%)
June
2,822
3,091
(9.5%)
July
3,569
4,902
(37.3%)
August
5,521
6,926
(25.4%)
September
8,070
7,247
(-10.2%)
October
6,369
3,656
(-42.6%)
November
5,670
3,845
(-32.2%)
December
4,233
3,458
(-18.3%)
Month
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
EC - Port Chicago
January
9,979
7,973
(-20.1%)
February
4,468
4,727
(5.8%)
March
2,410
2,901
(20.4%)
April
4,747
5,105
(7.5%)
May
8,103
8,359
(3.2%)
June
10,992
10,879
(-1.0%)
July
12,774
13,365
(4.6%)
August
14,829
16,058
(8.3%)
September
17,258
16,529
(-4.2%)
October
15,687
12,101
(-22.9%)
November
13,620
11,542
(-15.3%)
December
13,293
12,101
(-9.0%)
 The NAA-LLT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of months measured as percentages are based on the simple
arithmetic difference in comparison to the reference case. Green and red shadings are used to highlight 3
levels of positive and negative changes: 5-10%, 10-20% and >20%.
Median salinity (measured as EC) at Collinsville is lower in November and December, and
higher in January, February, and April to June in the Early Long Term future climate period
relative to current (Table 3.18). Median salinities are lower July and October to December,
and higher in January to June in the Late Long Term future climate period relative to
current.
Median salinity (measured as EC) at Port Chicago is lower in November and December,
and higher in January to June in the Early Long Term future climate period relative to

Final Report
Application of EFT to Complement Water Planning for Multiple Species
113 | Page
current (Table 3.18). Median salinities are lower October to December, and higher in
January to June in the Late Long Term future climate period relative to current.
Table 3.18: EC (a proxy for salinity) values at Collinsville and Port Chicago are shown for
three future Climate and Demand scenarios. 
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
EC - Collinsville
January
1,800
2,325
(29.2%)
2,422
(34.6%)
February
418
523
(25.1%)
633
(51.4%)
March
214
223
(4.2%)
238
(11.0%)
April
354
419
(18.5%)
504
(42.6%)
May
907
1,090
(20.1%)
1,694
(86.7%)
June
2,512
2,838
(13.0%)
2,822
(12.4%)
July
4,396
4,342
(-1.2%)
3,569
(-18.8%)
August
5,636
5,878
(4.3%)
5,521
(-2.0%)
September
7,815
7,822
(0.1%)
8,070
(3.3%)
October
8,564
8,501
(-0.7%)
6,369
(-25.6%)
November
8,859
5,343
(-39.7%)
5,670
(-36.0%)
December
5,454
3,972
(-27.2%)
4,233
(-22.4%)
Month
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
EC - Port Chicago
January
8,916
9,525
(6.8%)
9,979
(11.9%)
February
2,937
3,910
(33.1%)
4,468
(52.1%)
March
1,269
1,947
(53.4%)
2,410
(89.8%)
April
3,473
4,000
(15.2%)
4,747
(36.7%)
May
6,245
6,990
(11.9%)
8,103
(29.7%)
June
10,015
10,873
(8.6%)
10,992
(9.8%)
July
13,026
12,982
(-0.3%)
12,774
(-1.9%)
August
14,856
15,154
(2.0%)
14,829
(-0.2%)
September
16,721
17,075
(2.1%)
17,258
(3.2%)
October
17,471
17,480
(0.0%)
15,687
(-10.2%)
November
17,376
13,732
(-21.0%)
13,620
(-21.6%)
December
14,918
13,092
(-12.2%)
13,293
(-10.9%)
 The NAA-Current scenario serves as a comparative reference case, with percentage differences shown below absolute
median effects. Comparisons of months measured as percentages are based on the simple arithmetic difference in
comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-
10%, 10-20% and >20%.
Ecoregion & Indicator Specific High-level Summary of Relative Suitability
The following high level effect roll-ups are tied to the RS methodology described in Section
2.8.6. Table 3.19 to Table 3.21 show results of this summary methodology for the
Sacramento River ecoregion, based on the EFT relative suitability definition and the change
in the percentage of years assigned to a favorable outcome. A further synthesis of these
tabular results is the subject of Table 3.35 and its associated summary.

Chapter 3: Effects Analysis Application of EFT
114 | P a g e
Sacramento River (SacEFT)
Table 3.19: Operation and conveyance effects are shown for selected BDCP scenarios in the
Sacramento River ecoregion at the Early Long Term (ELT) future climate period
using the change in the percentage of favorable years reported for each indicator
(RS method). 
Focal species
Performance indicator
BDCP Scenario (3 columns below)
vs. NAA-ELT Reference case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1)
15
16
15
Thermal egg-to-fry survival (CS3)
1
0
1
Redd dewatering (CS6)
-3
3
-5
Redd scour risk (CS5)
0
0
0
Juvenile stranding (CS4)
1
4
-2
Suitable rearing habitat (CS2)
0
-4
-1
Late Fall Chinook
Suitable spawning habitat (CS1)
-3
-5
-2
Thermal egg-to-fry survival (CS3)
0
0
0
Redd dewatering (CS6)
0
-2
0
Redd scour risk (CS5)
-1
-1
-1
Juvenile stranding (CS4)
-7
-8
-2
Suitable rearing habitat (CS2)
-3
-9
0
Spring Chinook
Suitable spawning habitat (CS1)
-2
28
-6
Thermal egg-to-fry survival (CS3)
-7
-5
3
Redd dewatering (CS6)
-3
12
-4
Redd scour risk (CS5)
0
0
0
Juvenile stranding (CS4)
-1
-6
0
Suitable rearing habitat (CS2)
9
4
10
Winter Chinook
Suitable spawning habitat (CS1)
-9
-8
0
Thermal egg-to-fry survival (CS3)
0
3
3
Redd dewatering (CS6)
-3
-9
0
Redd scour risk (CS5)
0
0
0
Juvenile stranding (CS4)
-14
-18
-17
Suitable rearing habitat (CS2)
10
26
4
Steelhead
Suitable spawning habitat (CS1)
-1
-1
0
Thermal egg-to-fry survival (CS3)
0
0
0
Redd dewatering (CS6)
0
0
-2
Redd scour risk (CS5)
0
0
0

Final Report
Application of EFT to Complement Water Planning for Multiple Species
115 | Page
Focal species
Performance indicator
BDCP Scenario (3 columns below)
vs. NAA-ELT Reference case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Upper and Middle Sacramento River Indicators
Juvenile stranding (CS4)
-5
-2
-2
Suitable rearing habitat (CS2)
3
5
2
Bank Swallow
Suitable potential habitat (BASW1)
2
2
2
Nest inundation/sloughing (BASW2)
0
0
0
Green Sturgeon
Egg-to-larval survival (GS1)
3
2
2
Fremont Cottonwood
Cottonwood initiation index(FC1)
0
0
0
Risk scour after initiation (FC2)
1
-2
0
Large Woody Debris
Old vegetation recruited to river (LWD1)
3
2
2
 The NAA-ELT scenario serves as a comparative reference case. The sign of the difference depends on whether the indicator
improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow and red shading are used
to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% = Pink, –4% = Yellow, –3% to +4% = White,
+5% to +9% = Light Green, 5-10%, ≥10% = Dark Green.
Table 3.20: Operation and conveyance effects are shown for selected BDCP scenarios in the
Sacramento River ecoregion at the Late Long Term (LLT) future climate period
using the change in the percentage of favorable years reported for each indicator
(RS method). 
Focal species
Performance indicator
BDCP Scenario (1 column below)
vs. NAA-LLT Reference case (243)
ESO-LLT
(244)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1)
19
Thermal egg-to-fry survival (CS3)
0
Redd dewatering (CS6)
3
Redd scour risk (CS5)
-2
Juvenile stranding (CS4)
5
Suitable rearing habitat (CS2)
-2
Late Fall Chinook
Suitable spawning habitat (CS1)
0
Thermal egg-to-fry survival (CS3)
0
Redd dewatering (CS6)
2
Redd scour risk (CS5)
0
Juvenile stranding (CS4)
0
Suitable rearing habitat (CS2)
-14

Chapter 3: Effects Analysis Application of EFT
116 | Page
Focal species
Performance indicator
BDCP Scenario (1 column below)
vs. NAA-LLT Reference case (243)
ESO-LLT
(244)
Upper and Middle Sacramento River Indicators
Spring Chinook
Suitable spawning habitat (CS1)
-3
Thermal egg-to-fry survival (CS3)
-12
Redd dewatering (CS6)
-1
Redd scour risk (CS5)
0
Juvenile stranding (CS4)
-5
Suitable rearing habitat (CS2)
10
Winter Chinook
Suitable spawning habitat (CS1)
-9
Thermal egg-to-fry survival (CS3)
-2
Redd dewatering (CS6)
-2
Redd scour risk (CS5)
0
Juvenile stranding (CS4)
-12
Suitable rearing habitat (CS2)
5
Steelhead
Suitable spawning habitat (CS1)
-5
Thermal egg-to-fry survival (CS3)
0
Redd dewatering (CS6)
4
Redd scour risk (CS5)
0
Juvenile stranding (CS4)
-5
Suitable rearing habitat (CS2)
1
Bank Swallow
Suitable potential habitat (BASW1)
2
Nest inundation/sloughing (BASW2)
0
Green Sturgeon
Egg-to-larval survival (GS1)
-1
Fremont Cottonwood
Cottonwood initiation index(FC1)
0
Risk scour after initiation (FC2)
-7
Large Woody Debris
Old vegetation recruited to river (LWD1)
-3
 The NAA-LLT scenario serves as a comparative reference case. The sign of the difference depends on whether the indicator
improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow and red shading are used
to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% = Pink, –4% = Yellow, –3% to +4% = White,
+5% to +9% = Light Green, 5-10%, ≥10% = Dark Green.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
117 | Page
Table 3.21: Climate and demand effects are shown for selected No Action Alternative (NAA)
scenario at two future climate periods in the Sacramento River ecoregion using
the change in the percentage of favorable years reported for each indicator (RS
method). 
Focal species
Performance indicator
BDCP Scenario (2 columns below)
vs. NAA-Current Reference case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1)
-6
-13
Thermal egg-to-fry survival (CS3)
-6
-25
Redd dewatering (CS6)
2
-1
Redd scour risk (CS5)
-4
-2
Juvenile stranding (CS4)
-8
-10
Suitable rearing habitat (CS2)
2
4
Late Fall Chinook
Suitable spawning habitat (CS1)
-5
-5
Thermal egg-to-fry survival (CS3)
0
0
Redd dewatering (CS6)
-7
-6
Redd scour risk (CS5)
-2
-6
Juvenile stranding (CS4)
-5
-18
Suitable rearing habitat (CS2)
19
17
Spring Chinook
Suitable spawning habitat (CS1)
-14
-22
Thermal egg-to-fry survival (CS3)
-21
-52
Redd dewatering (CS6)
-11
-20
Redd scour risk (CS5)
0
0
Juvenile stranding (CS4)
0
-3
Suitable rearing habitat (CS2)
-3
-7
Winter Chinook
Suitable spawning habitat (CS1)
-12
-26
Thermal egg-to-fry survival (CS3)
-9
-23
Redd dewatering (CS6)
5
5
Redd scour risk (CS5)
0
0
Juvenile stranding (CS4)
5
5
Suitable rearing habitat (CS2)
-24
-31
Steelhead
Suitable spawning habitat (CS1)
1
3
Thermal egg-to-fry survival (CS3)
0
0
Redd dewatering (CS6)
-1
-4
Redd scour risk (CS5)
-3
-3
Juvenile stranding (CS4)
0
0
Suitable rearing habitat (CS2)
-2
-6
Bank Swallow
Suitable potential habitat (BASW1)
1
4
Nest inundation/sloughing (BASW2)
1
1
Green Sturgeon
Egg-to-larval survival (GS1)
-21
-56

Chapter 3: Effects Analysis Application of EFT
118 | P a g e
Focal species
Performance indicator
BDCP Scenario (2 columns below)
vs. NAA-Current Reference case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Upper and Middle Sacramento River Indicators
Fremont Cottonwood
Cottonwood initiation index(FC1)
-2
-6
Risk scour after initiation (FC2)
4
4
Large Woody Debris
Old vegetation recruited to river (LWD1)
2
5
 The NAA-Current scenario serves as a comparative reference case. The sign of the difference depends on whether the
indicator improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow and red shading
are used to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% = Pink, –4% = Yellow, –3% to +4%
= White, +5% to +9% = Light Green, 5-10%, ≥10% = Dark Green.
San Joaquin-Sacramento Delta (DeltaEFT)
High level effect roll-ups are closely tied to the RS methodology described in Section 2.8.6.
Table 3.22 to Table 3.24 show results of this methodology for the Sacramento River
ecoregion, based on the EFT relative suitability definition and the change in the percentage
of years assigned to a favorable outcome. A synthesis of these tabular results is presented
in Table 3.35.
Table 3.22: Operation and conveyance effects are shown for selected BDCP scenarios in the
Delta ecoregion at the Early Long Term (ELT) future climate period using the
change in the percentage of favorable years reported for each indicator (RS
method). 
Focal species
Performance indicator
BDCP Scenario (3 columns below)
vs. NAA-ELT Reference case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Delta Indicators
Fall Chinook
Smolt weight gain (CS7)
6
6
6
Smolt predation risk (CS9)
0
0
0
Smolt temperature stress (CS10)
0
0
0
Late Fall Chinook
Smolt weight gain (CS7)
50
50
44
Smolt predation risk (CS9)
-6
-6
-6
Smolt temperature stress (CS10)
-6
-6
-6
Spring Chinook
Smolt weight gain (CS7)
6
6
6
Smolt predation risk (CS9)
0
0
0
Smolt temperature stress (CS10)
0
0
6
Winter Chinook
Smolt weight gain (CS7)
37
37
43
Smolt predation risk (CS9)
0
0
0

Final Report
Application of EFT to Complement Water Planning for Multiple Species
119 | Page
Focal species
Performance indicator
BDCP Scenario (3 columns below)
vs. NAA-ELT Reference case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Delta Indicators
Smolt temperature stress (CS10)
-12
-12
0
Steelhead
Smolt weight gain (CS7)
6
6
13
Smolt predation risk (CS9)
-6
-6
-6
Smolt temperature stress (CS10)
0
0
0
Splittail
Proportion max spawning habitat (SS1)
82
82
82
Delta Smelt
Spawning success (DS1)
0
0
6
Habitat suitability index (DS2)
6
0
6
Larval & juvenile entrainment (DS4)
0
0
0
Longfin Smelt
Abundance index (LS1)
0
0
0
Invasive Deterrence
Brazilian waterweed suppression (ID1)
-6
-12
-6
Overbite clam suppression (ID2)
-6
-6
-6
Asiatic clam suppression (ID3)
0
0
0
Tidal Wetlands
Brackish wetland area (TW1)
0
0
0
Freshwater wetland area (TW2)
–
–
–
 The NAA-ELT scenario serves as a comparative reference case. The sign of the difference depends on whether
the indicator improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow
and red shading are used to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% =
Pink, –4% = Yellow, –3% to +4% = White, +5% to +9% = Light Green, 5-10%, ≥10% = Dark Green.
Table 3.23: Operation and conveyance effects are shown for selected BDCP scenarios in the
Delta ecoregion at the Late Long Term (LLT) future climate period using the
change in the percentage of favorable years reported for each indicator (RS
method). 
Focal species
Performance indicator
BDCP Scenario (1 column below)
vs. NAA-LLT Reference case (243)
ESO-LLT
(244)
Delta Indicators
Fall Chinook
Smolt weight gain (CS7)
6
Smolt predation risk (CS9)
-6
Smolt temperature stress (CS10)
0
Late Fall Chinook
Smolt weight gain (CS7)
31
Smolt predation risk (CS9)
0
Smolt temperature stress (CS10)
0
Spring Chinook
Smolt weight gain (CS7)
0
Smolt predation risk (CS9)
0

Chapter 3: Effects Analysis Application of EFT
1 2 0 | Page
Focal species
Performance indicator
BDCP Scenario (1 column below)
vs. NAA-LLT Reference case (243)
ESO-LLT
(244)
Delta Indicators
Smolt temperature stress (CS10)
0
Winter Chinook
Smolt weight gain (CS7)
31
Smolt predation risk (CS9)
0
Smolt temperature stress (CS10)
-6
Steelhead
Smolt weight gain (CS7)
-6
Smolt predation risk (CS9)
0
Smolt temperature stress (CS10)
0
Splittail
Proportion max spawning habitat (SS1)
82
Delta Smelt
Spawning success (DS1)
6
Habitat suitability index (DS2)
0
Larval & juvenile entrainment (DS4)
11
Longfin Smelt
Abundance index (LS1)
0
Invasive Deterrence
Brazilian waterweed suppression (ID1)
6
Overbite clam suppression (ID2)
-6
Asiatic clam suppression (ID3)
0
Tidal Wetlands
Brackish wetland area (TW1)
-59
Freshwater wetland area (TW2)
-35
 The NAA-LLT scenario serves as a comparative reference case. The sign of the difference depends on whether the indicator
improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow and red shading are used
to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% = Pink, –4% = Yellow, –3% to +4% = White,
+5% to +9% = Light Green, 5-10%, ≥10% = Dark Green.
Table 3.24: Climate and demand effects are shown for selected No Action Alternative (NAA)
scenario at two future climate periods in the Delta ecoregion using the change in
the percentage of favorable years reported for each indicator (RS method). 
Focal species
Performance indicator
BDCP Scenario (2 columns below)
vs. NAA-Current Reference case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Delta Indicators
Fall Chinook
Smolt weight gain (CS7)
-17
-23
Smolt predation risk (CS9)
0
0
Smolt temperature stress (CS10)
-6
-12
Late Fall Chinook
Smolt weight gain (CS7)
-12
-12
Smolt predation risk (CS9)
0
-6

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 2 1 | Page
Focal species
Performance indicator
BDCP Scenario (2 columns below)
vs. NAA-Current Reference case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Delta Indicators
Smolt temperature stress (CS10)
0
-6
Spring Chinook
Smolt weight gain (CS7)
-6
0
Smolt predation risk (CS9)
-7
-7
Smolt temperature stress (CS10)
-12
-12
Winter Chinook
Smolt weight gain (CS7)
-6
-6
Smolt predation risk (CS9)
0
0
Smolt temperature stress (CS10)
-19
-25
Steelhead
Smolt weight gain (CS7)
-13
-7
Smolt predation risk (CS9)
0
-6
Smolt temperature stress (CS10)
-6
-6
Splittail
Proportion max spawning habitat (SS1)
2
2
Delta Smelt
Spawning success (DS1)
2
-4
Habitat suitability index (DS2)
0
0
Larval & juvenile entrainment (DS4)
11
0
Longfin Smelt
Abundance index (LS1)
-6
-6
Invasive Deterrence
Brazilian waterweed suppression (ID1)
6
-6
Overbite clam suppression (ID2)
0
0
Asiatic clam suppression (ID3)
0
0
Tidal Wetlands
Brackish wetland area (TW1)
-35
-35
Freshwater wetland area (TW2)
-23
-29
 The NAA-Current scenario serves as a comparative reference case. The sign of the difference depends on whether the
indicator improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow and red shading
are used to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% = Pink, –4% = Yellow, –3% to +4%
= White, +5% to +9% = Light Green, 5-10%, ≥10% = Dark Green.
Ecoregion & Indicator Specific Effect Size Results
Sacramento River (SacEFT)
Operation and Conveyance Effects
Operation and conveyance effect size results presented below are based on the ES
methodology described in Section 2.8.6. Table 3.25 and Table 3.26 show results of this
methodology for the Sacramento River ecoregion. The following section summarizes BDCP
effects in which the median effect differs by more than 5% from the reference case. A
further synthesis of these effects is the subject of Table 3.35 and its associated summary.

Chapter 3: Effects Analysis Application of EFT
1 2 2 | Page
Table 3.25: Operation and conveyance effect sizes are shown for selected BDCP scenarios
at the Early Long Term (ELT) future climate period using the median difference
Effect Size (ES) method (preserving the native units of each indicator). 
Focal species
Performance indicator
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
3,738
4,081
(9.2%)
4,069
(8.9%)
3,998
(6.9%)
Thermal egg-to-fry survival (CS3, proportion)
0.996
0.996
(0.0%)
0.996
(0.0%)
0.997
(0.1%)
Redd dewatering (CS5; proportion)
0.050
0.040
(0.9%)
0.039
(1.0%)
0.040
(0.9%)
Redd scour risk (CS6; scour days)
0
0
0
0
Juvenile stranding index (CS4)
0.166
0.166
(0.0%)
0.166
(0.0%)
0.165
(0.1%)
Suitable rearing habitat (CS2; 000s ft2)
62,761
62,000
(-1.2%)
60,347
(-3.8%)
62,601
(-0.3%)
Late Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,272
1,195
(-6.0%)
1,187
(-6.7%)
1,232
(-3.1%)
Thermal egg-to-fry survival (CS3, proportion)
1.000
1.000
(0.0%)
1.000
(0.0%)
1.000
(0.0%)
Redd dewatering (CS5; proportion)
0.053
0.054
(-0.1%)
0.060
(-0.7%)
0.054
(0.0%)
Redd scour risk (CS6; scour days)
0
0
0
0
Juvenile stranding index (CS4)
0.045
0.048
(-0.3%)
0.045
(0.0%)
0.046
(0.1%)
Suitable rearing habitat (CS2; 000s ft2)
52,573
52,050
(-1.0%)
51,374
(-2.3%)
52,274
(-0.6%)
Spring Chinook
Suitable spawning habitat (CS1; 000s ft2)
914
1,009
(10.4%)
1,048
(14.7%)
896
(-2.0%)
Thermal egg-to-fry survival (CS3, proportion)
0.979
0.965
(-1.4%)
0.971
(-0.7%)
0.978
(0.0%)
Redd dewatering (CS5; proportion)
0.055
0.068
(-1.3%)
0.044
(1.1%)
0.069
(-1.3%)
Redd scour risk (CS6; scour days)
0
0
0
0
Juvenile stranding index (CS4)
0.201
0.224
(-2.3%)
0.202
(-0.1%)
0.224
(-2.3%)
Suitable rearing habitat (CS2; 000s ft2)
66,998
68,136
(1.7%)
65,610
(-2.1%)
68,559
(2.3%)
Winter Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,447
1,418
(-2.0%)
1,419
(-1.9%)
1,446
(0.0%)
Thermal egg-to-fry survival (CS3, proportion)
0.997
0.995
(-0.2%)
0.997
(0.0%)
0.996
(-0.1%)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 2 3 | Page
Focal species
Performance indicator
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Upper and Middle Sacramento River Indicators
Redd dewatering (CS5; proportion)
0.014
0.017
(-0.2%)
0.015
(-0.1%)
0.015
(-0.1%)
Redd scour risk (CS6; scour days)
0
0
0
0
Juvenile stranding index (CS4)
0.085
0.106
(-2.1%)
0.094
(-0.9%)
0.101
(-1.6%)
Suitable rearing habitat (CS2; 000s ft2)
37,153
37,602
(1.2%)
37,804
(1.8%)
37,101
(-0.1%)
Steelhead
Suitable spawning habitat (CS1; 000s ft2)
72
70
(-2.8%)
70
(-2.0%)
70
(-2.7%)
Thermal egg-to-fry survival (CS3, proportion)
1.000
1.000
(0.0%)
1.000
(0.0%)
1.000
(0.0%)
Redd dewatering (CS5; proportion)
0.050
0.050
(0.0%)
0.047
(0.3%)
0.048
(0.1%)
Redd scour risk (CS6; scour days)
0
0
0
0
Juvenile stranding index (CS4)
0.397
0.417
(-2.0%)
0.407
(-1.0%)
0.406
(-0.9%)
Suitable rearing habitat (CS2; 000s ft2)
133,901
137,065
(2.4%)
136,015
(1.6%)
134,725
(0.6%)
Bank Swallow
Suitable potential habitat (BASW1; length, m)
35,316
35,197
(-0.3%)
34,734
(-1.6%)
35,280
(-0.1%)
Nest inundation/sloughing risk (BASW2)
13,976
14,068
(-0.7%)
14,141
(-1.2%)
13,905
(0.5%)
Green Sturgeon
Egg-to-larval survival (GS1; proportion)
0.967
0.970
(0.2%)
0.967
(0.0%)
0.968
(0.1%)
Fremont Cottonwood
Cottonwood initiation index (FC1)
24
26
(8.3%)
26
(6.3%)
24
(0.0%)
Risk scour after initiation (FC2)
Large Woody Debris
Old vegetation recruited to river (LWD1; ha)
1.25
1.41
(13.2%)
1.25
(0.2%)
1.41
(13.1%)
 The NAA-ELT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of indicators measured as percentages or proportions are based on the
simple arithmetic difference in comparison to the reference case; all other indicators are based on the
proportional difference in comparison to the reference case. The sign of the difference depends on whether the
indicator improves (more is better) or declines (more is worse) relative to the reference case. Green and red
shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-20% and >20%.

Chapter 3: Effects Analysis Application of EFT
1 2 4 | Page
Table 3.26: Operation and conveyance effect sizes are shown for selected BDCP scenarios
at the Late Long Term (LLT) future climate period using the median difference
Effect Size (ES) method (preserving the native units of each indicator). 
Focal species
Performance indicator
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
3,729
4,003
(7.4%)
Thermal egg-to-fry survival (CS3, proportion)
0.981
0.976
(-0.5%)
Redd dewatering (CS5; proportion)
0.056
0.048
(0.7%)
Redd scour risk (CS6; scour days)
0
0
Juvenile stranding index (CS4)
0.173
0.172
(0.1%)
Suitable rearing habitat (CS2; 000s ft2)
62,279
61,665
(-1.0%)
Late Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,304
1,268
(-2.8%)
Thermal egg-to-fry survival (CS3, proportion)
0.999
0.999
(0.0%)
Redd dewatering (CS5; proportion)
0.063
0.060
(0.3%)
Redd scour risk (CS6; scour days)
0
0
Juvenile stranding index (CS4)
0.056
0.057
(-0.1%)
Suitable rearing habitat (CS2; 000s ft2)
53,088
51,009
(-3.9%)
Spring Chinook
Suitable spawning habitat (CS1; 000s ft2)
867
860
(-0.8%)
Thermal egg-to-fry survival (CS3, proportion)
0.892
0.843
(-4.9%)
Redd dewatering (CS5; proportion)
0.070
0.075
(-0.5%)
Redd scour risk (CS6; scour days)
0
0
Juvenile stranding index (CS4)
0.220
0.216
(0.4%)
Suitable rearing habitat (CS2; 000s ft2)
64,986
68,257
(5.0%)
Winter Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,407
1,383
(-1.7%)
Thermal egg-to-fry survival (CS3, proportion)
0.981
0.978
(-0.4%)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 2 5 | Page
Focal species
Performance indicator
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Upper and Middle Sacramento River Indicators
Redd dewatering (CS5; proportion)
0.014
0.015
(-0.1%)
Redd scour risk (CS6; scour days)
0
0
Juvenile stranding index (CS4)
0.092
0.090
(0.2%)
Suitable rearing habitat (CS2; 000s ft2)
36,695
36,723
(0.1%)
Steelhead
Suitable spawning habitat (CS1; 000s ft2)
74
72
(-2.7%)
Thermal egg-to-fry survival (CS3, proportion)
0.999
1.000
(0.0%)
Redd dewatering (CS5; proportion)
0.050
0.048
(0.2%)
Redd scour risk (CS6; scour days)
0
0
Juvenile stranding index (CS4)
0.405
0.411
(-1.3%)
Suitable rearing habitat (CS2; 000s ft2)
133,719
134,602
(0.7%)
Bank Swallow
Suitable potential habitat (BASW1; length, m)
35,090
35,643
(1.6%)
Nest inundation/sloughing risk (BASW2)
14,079
14,447
(-2.6%)
Green Sturgeon
Egg-to-larval survival (GS1; proportion)
0.935
0.933
(-0.2%)
Fremont Cottonwood
Cottonwood initiation index (FC1)
25
29
(16.0%)
Risk scour after initiation (FC2)
Large Woody Debris
Old vegetation recruited to river (LWD1; ha)
1.30
1.06
(-18.6%)
 The NAA-LLT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of indicators measured as percentages or proportions are based
on the simple arithmetic difference in comparison to the reference case; all other indicators are based on
the proportional difference in comparison to the reference case. The sign of the difference depends on
whether the indicator improves (more is better) or declines (more is worse) relative to the reference
case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-
20% and >20%.

Chapter 3: Effects Analysis Application of EFT
1 2 6 | Page
Salmonids
Median suitable spawning habitat (CS1) rises relative to NAA-ELT for fall-run Chinook
under all BDCP scenarios: 9.2%, 8.9% and 6.9% for ESO-ELT, LOS-ELT and HOS-ELT
respectively (Figure 3.3).
Figure 3.3: Fall-run Chinook spawning habitat (CS1) area under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario.
Median suitable spawning habitat (CS1) declines relative to NAA-ELT for late fall-run
Chinook under the ESO-ELT and LOS-ELT BDCP scenarios: –6.0% and –6.7%
respectively (Figure 3.4). There is considerable variation within each project level.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 2 7 | Page
Figure 3.4: Late fall-fun Chinook spawning habitat (CS1) area under three BDCP scenarios,
in comparison to the NAA-ELT baseline scenario.
Median suitable spawning habitat (CS1) increases relative to NAA-ELT for spring-run
Chinook under two BDCP scenarios: 10.4% and 14.7% for ESO-ELT and LOS-ELT (Figure
3.5).
Figure 3.5: Spring-run Chinook spawning habitat (CS1) area under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario.

Chapter 3: Effects Analysis Application of EFT
1 2 8 | Page
Green Sturgeon
The median green sturgeon egg survival (GS1) is expected to remain fairly constant under
all BDCP project scenarios. Median project mortality differs from the reference case of
96.7% survival by at most 0.2% (Table 3.25). Comparisons using an LLT reference case
are similarly very small (Table 3.26).
Fremont Cottonwood
The median Fremont cottonwood initiation (FC1) is expected to remain fairly constant under
all BDCP project scenarios, with slight improvement under ESO-ELT and LOS-ELT (8% and
6% respectively) (Figure 3.6). The HOS-ELT scenario produces no effect.
Figure 3.6: Fremont cottonwood initiation success (FC1) under three BDCP scenarios, in
comparison to the NAA-ELT baseline scenario.
Bank Swallow
The median suitable potential habitat (BASW1) for bank swallows is expected to remain
relatively constant between project alternatives at approximately 35 km.
The median nest inundation/sloughing risk (BASW2) for bank swallows is expected to
remain relatively constant between project alternatives.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 2 9 | Page
Large Woody Debris Recruitment
For old vegetation recruitment, we expected different results than for bank swallow habitat,
as bank swallow habitat needs to be eroded to a minimum of 1 m which requires a minimum
increase in stream power.
The median annual input of old vegetation recruited to the river (LWD) is expected to
increase relative to NAA-ELT under two BDCP scenarios: 13.1% and 13.2% for ESO-ELT
and HOS-ELT, respectively (Figure 3.7, upper left panel). The expected increases are small
relative to annual variations (expected increase is 0.16 ha, high quartile above 5 ha) and the
individual water year differences may not be meaningful (Figure 3.7, upper right panel).
The median input of old vegetation recruited to the river (LWD) is expected to decrease for
ESO-LLT relative to NAA-ELT by 18.6% (Figure 3.7, lower left panel). The expected
decreases are small relative to annual variations (expected increase is 0.24 ha, high
quartile above 5 ha) and the individual water year differences do not appear to be
meaningful (Figure 3.7, lower right panel).

Chapter 3: Effects Analysis Application of EFT
1 3 0 | Page
Figure 3.7: Median large woody debris input (LWD1) to the river under three BDCP
scenarios, in comparison to the NAA-ELT baseline scenario (upper left panel)
and under one BDCP scenario in comparison to the NAA-LLT baseline scenario
(lower left panel). Individual year differences for the ELT and LLT periods are
shown in the upper right and lower right panels, respectively.
Future climate and demand effects
Climate and demand effect size results are closely tied to the ES methodology described in
Section 2.8.6. Table 3.27 shows results of this methodology for the Sacramento River
ecoregion. The following section summarizes Climate/Demand effects in which the median

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 3 1 | Page
effect differs by more than 5% from a reference case comparative response. A synthesis of
these effects is presented in Table 3.35.
Table 3.27: Climate and demand effect sizes are shown for the No Action Alternative (NAA)
scenario at three future climate periods using the median difference Effect Size
(ES) method (preserving the native units of each indicator). 
Focal species
Performance indicator
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
3,876
3,738
(-3.6%)
3,729
(-3.8%)
Thermal egg-to-fry survival (CS3, proportion)
0.999
0.996
(-0.3%)
0.981
(-1.9%)
Redd dewatering (CS5; proportion)
0.053
0.050
(0.3%)
0.056
(-0.3%)
Redd scour risk (CS6; scour days)
0
0
0
Juvenile stranding index (CS4)
0.153
0.166
(-1.3%)
0.173
(-2.0%)
Suitable rearing habitat (CS2; 000s ft2)
61,935
62,761
(1.3%)
62,279
(0.6%)
Late Fall Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,352
1,272
(-5.9%)
1,304
(-3.6%)
Thermal egg-to-fry survival (CS3, proportion)
1.000
1.000
(0.0%)
0.999
(-0.1%)
Redd dewatering (CS5; proportion)
0.044
0.053
(-1.0%)
0.063
(-2.0%)
Redd scour risk (CS6; scour days)
0
0
0
Juvenile stranding index (CS4)
0.033
0.045
(-1.2%)
0.056
(-2.3%)
Suitable rearing habitat (CS2; 000s ft2)
50,703
52,573
(3.7%)
53,088
(4.7%)
Spring Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,058
914
(-13.6%)
867
(-18.1%)
Thermal egg-to-fry survival (CS3, proportion)
0.997
0.979
(-1.9%)
0.892
(-10.5%)
Redd dewatering (CS5; proportion)
0.044
0.055
(-1.1%)
0.070
(-2.6%)
Redd scour risk (CS6; scour days)
0
0
0
Juvenile stranding index (CS4)
0.201
0.201
(0.0%)
0.220
(-0.9%)
Suitable rearing habitat (CS2; 000s ft2)
63,130
66,998
(6.1%)
64,986
(2.9%)

Chapter 3: Effects Analysis Application of EFT
1 3 2 | Page
Focal species
Performance indicator
NAA-
Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Upper and Middle Sacramento River Indicators
Winter Chinook
Suitable spawning habitat (CS1; 000s ft2)
1,471
1,447
(-1.7%)
1,407
(-4.4%)
Thermal egg-to-fry survival (CS3, proportion)
1.000
0.997
(-0.3%)
0.981
(-1.9%)
Redd dewatering (CS5; proportion)
0.016
0.014
(0.1%)
0.014
(0.1%)
Redd scour risk (CS6; scour days)
0
0
0
Juvenile stranding index (CS4)
0.092
0.085
(0.7%)
0.092
(0.2%)
Suitable rearing habitat (CS2; 000s ft2)
37,953
37,153
(-2.1%)
36,695
(-3.3%)
Steelhead
Suitable spawning habitat (CS1; 000s ft2)
72
72
(-0.5%)
74
(2.2%)
Thermal egg-to-fry survival (CS3, proportion)
1.000
1.000
(0.0%)
0.999
(-0.1%)
Redd dewatering (CS5; proportion)
0.043
0.050
(-0.7%)
0.050
(-0.7%)
Redd scour risk (CS6; scour days)
0
0
0
Juvenile stranding index (CS4)
0.393
0.397
(-0.4%)
0.405
(-1.2%)
Suitable rearing habitat (CS2; 000s ft2)
134,213
133,901
(-0.2%)
133,719
(-0.4%)
Bank Swallow
Suitable potential habitat (BASW1; length, m)
34,782
35,316
(1.5%)
35,090
(0.9%)
Nest inundation/sloughing risk (BASW2)
13,673
13,976
(-2.2%)
14,079
(-3.0%)
Green Sturgeon
Egg-to-larval survival (GS1; proportion)
0.989
0.967
(-2.2%)
0.935
(-5.4%)
Fremont Cottonwood
Cottonwood initiation index (FC1)
23.5
24
(2.1%)
25
(6.4%)
Risk scour after initiation (FC2)
Large Woody Debris
Old vegetation recruited to river (LWD1; ha)
1.27
1.25
(-1.8%)
1.30
(2.6%)
 The NAA-Current scenario serves as a comparative reference case with percentage differences shown below absolute
median effects. Percentage differences for indicators measured as proportions are based on the simple arithmetic difference
in comparison to the reference case; all other indicators are based on the proportional difference in comparison to the
reference case. The sign of the difference depends on whether the indicator improves (more is better) or declines (more is
worse) relative to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes:
5-10%, 10-20% and >20%.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 3 3 | Page
Salmonids
Median suitable spawning habitat (CS1) of late fall-run Chinook is reduced by 5.9% from
NAA-Current to NAA-ELT (Figure 3.8).
Figure 3.8: Late fall-run Chinook suitable spawning habitat (CS1) area under the NAA-ELT
and NAA-LLT scenarios, compared to the NAA-Current reference case.
Median spring-run Chinook spawning habitat (CS1) is reduced by 13.6% and 18.1% in
NAA-ELT and NAA-LLT, respectively compared to NAA-Current reference case. Median
egg-stage thermal mortality (CS3) increases by 10.5% in the NAA-LLT scenario, relative to
the same reference case. Median juvenile rearing habitat (CS2) increases by 6.1% in the
NAA-ELT scenario (Figure 3.9).

Chapter 3: Effects Analysis Application of EFT
1 3 4 | Page
Figure 3.9: Spring-run Chinook suitable spawning habitat area (CS1, upper left panel),
thermal egg-to-fry survival (CS3, upper right panel), and juvenile rearing habitat
(CS2, lower left panel) under the NAA-ELT and NAA-LLT scenarios, compared to
the NAA-Current reference case.
Green Sturgeon
Median green sturgeon egg survival (GS1) is meaningfully altered in the NAA-LLT scenario,
declining by 5.4%, from 98.9% in the NAA-Current reference case scenario to 93.5%
survival in the 2060 period (Figure 3.10, Table 3.27). A less meaningful 2.2% reduction is
also seen in the intermediate NAA-ELT (2030) scenario. These results agree with High level
Effect Roll-up analyses (RS method) where the number of favorable years is reduced by
21% and 56% for ELT and LLT, respectively (Table 3.21).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 3 5 | Page
Figure 3.10: Green sturgeon egg survival (GS1) under the NAA-ELT and NAA-LLT scenarios
compared to the NAA-Current reference case.
Fremont Cottonwood
Fremont cottonwood initiation comparisons involving future LLT climate (as represented in
BDCP alternatives) do not show meaningful change.
Bank Swallow
The median suitable potential habitat (BASW1) for bank swallows is expected to remain
relatively constant under different future climates and demands at approximately 35 km.
The median nest inundation/sloughing risk (BASW2) for bank swallows is expected to
remain relatively constant under different future climates and demands.
Large Woody Debris Recruitment
The median large woody debris (LWD) input to the Sacramento River is expected to remain
relatively constant under different future climates and demands at approximately 1.25 ha.

Chapter 3: Effects Analysis Application of EFT
1 3 6 | Page
Water year characterization
Although they cannot be compared directly to a reference case, for many indicators, Water
Year effects are larger than operation and conveyance effects. The following section
describes these effects indicator by indicator.
Salmonids
Differences among water years are seen for most salmonid indicators, with one or two
simple patterns that are quite consistent across all run types. These are summarized in
Table 3.28. The most meaningful indicator for Water Year effects is the juvenile stranding
index (CS4). This index behaves in a straightforward manner based on the relationship
between channel bathymetry and flow (see short description in Section 2.2.12). During low
flow periods, preferred juvenile habitat can change markedly with small changes to flow,
due to the wetted channel being confined near the flatter bottom portion of the overall
channel.
Table 3.28: Summary of Water Year patterns observed for salmonid indicators from the
Sacramento River ecoregion.
Indicator
Run type
Pattern
Explanation
Typical Boxplot
Suitable
spawning
habitat
(CS1)
All
Declining
in wetter
years
Peak salmonid
spawning habitat
occurs at lower flow
Thermal
egg-to-fry
survival
(CS3)
Fall,
Spring,
Winter
More
variable in
Critically
Dry,
Above
Normal
years
High between-year
flow variability for
salmonids with an
egg period outside
spring
Late fall,
Steelhead
Negligible
Salmonid egg
period coincides
with consistent cool
high spring flow
(see Table 2.4)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 3 7 | Page
Indicator
Run type
Pattern
Explanation
Typical Boxplot
Redd
dewatering
(CS6)
Fall,
Spring,
Winter
Fairly
insensitive
Flow variability is
similar across
Water Year types
for salmonids with
an egg period
outside the spring
Late fall,
Steelhead
Increasing
in wetter
years
Flow variability is
highest in wetter
years for salmonids
with an egg period
during the spring
Redd scour
risk (CS5)
Fall,
Spring,
Winter
Highest in
Extremely
Wet
High risk in very
wet years for
salmonids with an
egg period in lower
flow seasons
Late fall,
Steelhead
Negligible
Egg period
coincides with
consistent high cool
flow in spring
Juvenile
stranding
index (CS4)
All
Declining
in wetter
years
Channel
bathymetry is more
sensitive to
fluctuations in drier
years, when flow is
near the bottom of
the channel
Suitable
rearing
habitat
(CS2)
All
Declining
in wetter
years
Peak salmonid
rearing habitat
occurs at lowerer
flow

Chapter 3: Effects Analysis Application of EFT
1 3 8 | Page
Green Sturgeon
Green sturgeon egg survival (GS1) is meaningfully lower in critically dry water years (Figure
3.11) and highest in normal Water Year types.
Figure 3.11: Median green sturgeon egg survival (GS1) by Water Year type.
Fremont Cottonwood
Median Fremont cottonwood initiation (FC1) was significantly higher in extremely wet water
years, but otherwise relatively constant (Figure 3.12). Interestingly, the lowest median
initiation was observed in normal water years relative to dry years. This may be explained
by different operational rules in normal years that are associated with more rapid rates of
hydrograph recession.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 3 9 | Page
Figure 3.12: Median Fremont cottonwood initiation (FC1) by Water Year type.
Bank Swallow
The median suitable potential habitat (BASW1) for bank swallows is meaningfully lower in
critically dry years when the weighted suitable length is almost half of the estimate length in
extremely wet years (Figure 3.13, left panel).
The median nest inundation/sloughing risk (BASW2) for bank swallows increases in wetter
water year types (Figure 3.13, right panel).

Chapter 3: Effects Analysis Application of EFT
1 4 0 | P a g e
Figure 3.13: Median suitable potential habitat (BASW1) for bank swallows by Water Year type,
showing suitable potential habitat (left panel) and nest inundation/sloughing risk
(right panel).
Large Woody Debris Recruitment
The median large woody debris (LWD) input increases meaningfully in wetter water year
types, with the median for extremely wet water years being approximately five times higher
than the overall median (Figure 3.14).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 4 1 | P a g e
Figure 3.14: Median large woody debris input (LWD1) to the Sacramento River by Water Year
type.
San Joaquin-Sacramento Delta (DeltaEFT)
Operation and conveyance effects
Effect size results are based on the ES methodology described in Section 2.8.6. Table 3.29
and Table 3.30 show results of this methodology for the Delta ecoregion. The following
section summarizes BDCP effects in which the median effect differs by more than 5% from
a reference case comparative response. A synthesis of these effects is presented in Table
3.35.

Chapter 3: Effects Analysis Application of EFT
1 4 2 | Page
Table 3.29: Operation and conveyance sizes are shown for selected BDCP scenarios at the
Early Long Term (ELT) future climate period using the median difference Effect
Size (ES) method (preserving the native units of each indicator). 
Focal species
Performance indicator
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Delta Indicators
Fall Chinook
Smolt weight gain (CS7; %)
19.1
19.6
(0.4%)
19.5
(0.4%)
19.4
(0.2%)
Smolt predation risk (CS9; passage days)
15.5
16.1
(-3.9%)
16.1
(-3.6%)
16.0
(-2.8%)
Smolt temperature stress (CS10; degree day)
113.4
117.9
(-3.9%)
117.9
(-3.9%)
116.7
(-2.9%)
Late Fall Chinook
Smolt weight gain (CS7; %)
29.0
34.2
(5.2%)
34.2
(5.2%)
34.3
(5.3%)
Smolt predation risk (CS9; passage days)
15.6
16.1
(-3.6%)
16.5
(-5.9%)
16.3
(-4.4%)
Smolt temperature stress (CS10; degree day)
60.8
66.0
(-8.6%)
66.9
(-10.1%)
66.6
(-9.7%)
Spring Chinook
Smolt weight gain (CS7; %)
23.0
25.0
(2.0%)
24.7
(1.7%)
24.8
(1.8%)
Smolt predation risk (CS9; passage days)
15.6
15.8
(-1.4%)
15.7
(-0.8%)
16.0
(-2.7%)
Smolt temperature stress (CS10; degree day)
87.1
88.8
(-2.0%)
88.7
(-1.8%)
90.4
(-3.9%)
Winter Chinook
Smolt weight gain (CS7; %)
30.3
35.1
(4.8%)
35.2
(4.9%)
35.0
(4.7%)
Smolt predation risk (CS9; passage days)
14.7
15.4
(-5.2%)
15.4
(-4.9%)
15.4
(-5.2%)
Smolt temperature stress (CS10; degree day)
42.5
47.3
(-11.3%)
47.2
(-11.2%)
47.1
(-11.0%)
Steelhead
Smolt weight gain (CS7; %)
17.7
18.4
(0.7%)
18.3
(0.6%)
18.5
(0.8%)
Smolt predation risk (CS9; passage days)
15.8
16.2
(-2.7%)
16.0
(-1.8%)
16.4
(-4.2%)
Smolt temperature stress (CS10; degree day)
113.3
122.1
(-7.7%)
121.9
(-7.6%)
123.9
(-9.3%)
Splittail
Proportion max spawning habitat (SS1)
0.000
0.156
(15.6%)
0.160
(16.0%)
0.182
(18.2%)
Delta Smelt
Spawning success (DS1; optimal days)
33.0
33.4
(1.2%)
33.4
(1.2%)
33.4
(1.2%)
Habitat suitability index (DS2)
3,456
3,514
(1.7%)
3,047
(-11.8%)
3,501
(1.3%)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 4 3 | Page
Focal species
Performance indicator
NAA-ELT
Reference
case (233)
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Delta Indicators
Larval & juvenile entrainment proportion (DS4)
0.054
0.055
(0.0%)
0.055
(-0.1%)
0.051
(0.4%)
Longfin Smelt
Abundance index (LS1)
66.6
65.6
(-1.4%)
63.8
(-4.2%)
72.8
(9.4%)
Invasive Deterrence
Brazilian waterweed suppression (ID1)
9.1
8.9
(-2.1%)
8.9
(-2.1%)
8.9
(-2.7%)
Overbite clam larval suppression (ID2)
2.7
3.3
(-25.2%)
3.3
(-25.4%)
3.3
(-25.0%)
Asiatic clam larval suppression (ID3)
9.1
8.9
(-2.1%)
8.9
(-2.1%)
8.9
(-2.7%)
Tidal Wetlands
Brackish wetland area (TW1; ha)
705.5
672.2
(-4.7%)
672.2
(-4.7%)
672.2
(-4.7%)
Freshwater wetland area (TW2; ha)
283.7
273.7
(-3.5%)
273.7
(-3.5%)
273.7
(-3.5%)
 The NAA-ELT scenario serves as a comparative reference case, with percentage differences shown below absolute median
effects. Comparisons of indicators measured as percentages or proportions are based on the simple arithmetic difference in
comparison to the reference case; all other indicators are based on the proportional difference in comparison to the
reference case. The sign of the difference depends on whether the indicator improves (more is better) or declines (more is
worse) relative to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes:
5-10%, 10-20% and >20%.

Chapter 3: Effects Analysis Application of EFT
1 4 4 | Page
Table 3.30: Operation and conveyance sizes are shown for selected BDCP scenarios at the
Late Long Term (LLT) future climate period using the median difference Effect
Size (ES) method (preserving the native units of each indicator).
Focal species
Performance indicator
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Delta Indicators
Fall Chinook
Smolt weight gain (CS7; %)
17.7
18.2
(0.5%)
Smolt predation risk (CS9; passage days)
15.7
16.3
(-4.1%)
Smolt temperature stress (CS10; degree day)
115.1
120.7
(-4.9%)
Late Fall Chinook
Smolt weight gain (CS7; %)
28.3
32.9
(4.6%)
Smolt predation risk (CS9; passage days)
15.5
16.1
(-3.9%)
Smolt temperature stress (CS10; degree day)
64.3
68.6
(-6.6%)
Spring Chinook
Smolt weight gain (CS7; %)
22.1
24.2
(2.1%)
Smolt predation risk (CS9; passage days)
15.6
15.8
(-1.4%)
Smolt temperature stress (CS10; degree day)
88.1
92.3
(-4.8%)
Winter Chinook
Smolt weight gain (CS7; %)
29.6
34.7
(5.1%)
Smolt predation risk (CS9; passage days)
14.7
15.3
(-3.7%)
Smolt temperature stress (CS10; degree day)
46.1
51.1
(-10.8%)
Steelhead
Smolt weight gain (CS7; %)
16.4
16.9
(0.5%)
Smolt predation risk (CS9; passage days)
15.7
16.0
(-2.5%)
Smolt temperature stress (CS10; degree day)
119.4
126.7
(-6.1%)
Splittail
Proportion max spawning habitat (SS1)
0.000
0.153
(15.3%)
Delta Smelt
Spawning success (DS1; optimal days)
33.7
34.3
(1.8%)
Habitat suitability index (DS2)
3,423
3,655
(6.8%)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 4 5 | Page
Focal species
Performance indicator
NAA-LLT
Reference
case (243)
ESO-LLT
(243)
Delta Indicators
Larval & juvenile entrainment proportion (DS4)
0.062
0.060
(0.1%)
Longfin Smelt
Abundance index (LS1)
59.0
55.9
(-5.1%)
Invasive Deterrence
Brazilian waterweed suppression (ID1)
8.9
8.9
(-0.3%)
Overbite clam larval suppression (ID2)
2.9
3.5
(-21.4%)
Asiatic clam larval suppression (ID3)
8.9
8.9
(-0.3%)
Tidal Wetlands
Brackish wetland area (TW1; ha)
773.1
657.5
(-15.0%)
Freshwater wetland area (TW2; ha)
302.3
266.5
(-11.8%)
 The NAA-LLT scenario serves as a comparative reference case, with percentage differences shown below
absolute median effects. Comparisons of indicators measured as percentages or proportions are based
on the simple arithmetic difference in comparison to the reference case; all other indicators are based on
the proportional difference in comparison to the reference case. The sign of the difference depends on
whether the indicator improves (more is better) or declines (more is worse) relative to the reference
case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-
20% and >20%.
Salmonids
No meaningful effects are seen for fall-run Chinook. Median smolt weight gain in Yolo
Bypass (CS7) improves markedly for late fall-run Chinook under all project scenarios,
increasing by 5.2% for ESO-ELT and LOS-ELT, and by 5.3% under the HOS-ELT scenario
(Figure 3.15, upper left panel, Figure 3.16, Figure 3.17). Exposure to smolt predation (CS9)
increases by 5.9% in the LOS-ELT scenario, compared to the NAA-ELT reference case.
The other project scenarios also increase slightly. Smolt temperature stress (CS10)
becomes more extreme under all BDCP scenarios, increasing by 8.6%, 10.1% and 9.7%
under the ESO-ELT, LOS-ELT and HOS-ELT scenarios respectively (Figure 3.15). A similar
6.6% operation and conveyance effect also exists for the LLT comparison under the ESO-
LLT comparison.

Chapter 3: Effects Analysis Application of EFT
1 4 6 | Page
Figure 3.15: Late fall-run Chinook smolt weight gain (CS7, upper left panel), smolt predation
risk (CS9, upper right panel), and smolt temperature stress (CS10, lower left
panel) under three BDCP scenarios compared to the NAA-ELT reference case.
The lower right panel shows smolt temperature stress (CS10) effects for the
ESO-LLT scenario, compared to the NAA-LLT reference.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 4 7 | Page
Figure 3.16: Composite view of a detailed Excel report created by EFT software, showing
details of smolt weight gain in Yolo Bypass (CS7) under the NAA-ELT scenario in
WY1986. In this year the performance of late fall-run Chinook is driven by the
high proportion of the cohort travelling via the main-stem. The shaded region in
the upper left panel shows the proportion of the year-cohort travelling this route,
and the heavy yellow line shows percent weight gain for each day-cohort along
that route. Flow and temperature (degrees C) experienced by each day-cohort
are shown in the lower left panel. The smaller proportion travelling via Fremont
Weir is shown by the shaded area in the upper right panel, along with percent
weight gain on that route. The small proportion of the year-cohort travelling via
Sacramento Weir is not shown here, but the overall outcome for the year is given
a fair (Yellow) ranking, based on 30.2% weight gain overall, comprised of 25%
gain for 88% travelling through the mainstem, 89% gain for 9% travelling via
Fremont Weir, and 57% for 2% travelling via Sacramento Weir.

Chapter 3: Effects Analysis Application of EFT
1 4 8 | P a g e
Figure 3.17: Detailed visualization report show locations of smolt weight gain in Yolo Bypass
(CS7) under the NAA-ELT scenario in WY1986. In this year, weight gain in late
fall-run Chinook is driven by the high proportion of the cohort travelling via the
main-stem (heavy yellow line), improved by the small proportion which migrates
via Fremont Weir and Sacramento Weir (fine green lines), resulting in a fair
(Yellow) year overall.
Median smolt weight gain in Yolo Bypass (CS7) improves for winter-run Chinook under the
ESO-LLT scenario, increasing by 5.1% compared to the NAA-LLT reference case (Figure
3.18). In the same figure, median smolt predation risk (CS9) increases meaningfully by
5.2% in the ESO-ELT and HOS-ELT scenarios, compared to the NAA-ELT reference case.
Smolt temperature stress (CS10) becomes more extreme for winter-run Chinook under all
BDCP scenarios, increasing by 11.3%, 11.2% and 11.0% under the ESO-ELT, LOS-ELT
and HOS-ELT scenarios respectively (Figure 3.18). A similar 10.8% operation and
conveyance effect increase also is seen for the LLT comparison under the ESO-LLT
scenario.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 4 9 | Page
Figure 3.18: Winter-run Chinook smolt weight gain (CS7) under the ESO-LLT scenario
compared to the NAA-ELT reference case (upper left panel). Winter-run Chinook
smolt predation risk (CS9, upper right panel) and smolt temperature stress
(CS10, lower left panel) under three BDCP scenarios compared to the NAA-ELT
reference case. Smolt temperature stress (CS10) effects for the ESO-LLT
scenario, compared to the NAA-LLT reference case (lower right panel).
Median smolt temperature stress (CS10) becomes more extreme for steelhead under all
BDCP Early Long Term (ELT, 2030) scenarios, increasing by 7.7%, 7.6% and 9.3% under
the ESO-ELT, LOS-ELT and HOS-ELT scenarios respectively (Figure 3.19 left panel,
Figure 3.20 and Figure 3.21). A similar 6.1% operation and conveyance effect also exists
for the ESO-LLT scenario, compared to the NAA-LLT reference case.

Chapter 3: Effects Analysis Application of EFT
1 5 0 | Page
Figure 3.19: Steelhead smolt temperature stress (CS10) effects under three BDCP scenarios
compared to the NAA-ELT reference case (left panel); and for the ESO-LLT
scenario compared to the NAA-LLT reference case (right panel).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 5 1 | Page
Figure 3.20: Composite view of a detailed Excel report created by EFT software, showing
details of smolt temperature stress (CS10) under the NAA-ELT scenario in
WY1980. In this year the performance of steelhead is driven by the higher
proportion of the cohort travelling in more western routes (left panel, see Figure
3.21). The shaded region in the upper left panel shows the proportion of the year-
cohort travelling in the western route B1, and the heavy yellow line shows thermal
stress for each day-cohort along that route. Flow and temperature (degrees C)
experienced by each day-cohort are shown in the lower left panel. A meaningful
proportion travels through an eastern route through Georgiana Slough (E2),
where thermal stress is higher due to increased temperature near the end of the
migration period. The overall outcome for the year is given a fair (Yellow) ranking,
based on 98 °C-days overall, comprised of 85 °C-days for 17% of the year cohort
travelling along route B1, 143 °C-days for 12% of the year cohort traveling along
route E1%, with the remainder divided among the four other routes. The overall
annual stress for the year-cohort is 98 °C-days.

Chapter 3: Effects Analysis Application of EFT
1 5 2 | Page
Figure 3.21: Detailed visualization report show locations of smolt temperature stress (CS10)
under the NAA-ELT scenario in WY1980. In this year temperature stress in
steelhead is driven by the high proportion of the cohort travelling via the main-
stem and more western routes (yellow lines), but degraded in the more easterly
routes (red lines), resulting in a fair (Yellow) year overall.
Splittail
The median proportion of maximum spawning habitat for splittail (SS1) is expected to
increase meaningfully relatively to NAA-ELT under all three BDCP scenarios, from 0 to
0.156, 0.160 and 0.182 for ESO-ELT LOS-ELT and HOS-ELT (Figure 3.22, left panel). The
change is expected to be meaningful as the changes in all individual water years are above
zero (Figure 3.22, right panel). The change is most likely due to a notch constructed in the
Fremont Weir as part of the BDCP scenarios (Section 3.3.2).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 5 3 | Page
Figure 3.22: Median proportion of maximum spawning habitat for splittail (SS1) under three
BDCP scenarios (left panel) compared to the NAA-ELT reference case, and
showing annual differences relative to the NAA-ELT baseline scenario (right
panel).
Delta Smelt
The median spawning success for Delta smelt (DS1) is expected to remain relatively
constant between project alternatives at approximately 33 days of optimal spawning
conditions annually.
The median habitat suitability index for Delta smelt (DS2) is expected to decrease relative to
NAA-ELT under the LOS-ELT BDCP scenario by 11.8% (Figure 3.23, upper left panel). The
change is expected to be meaningful since most individual water year differences are
meaningfully negative (Figure 3.23, upper right panel).
The median habitat suitability index is expected to increase relative to NAA-LLT under the
ESO-LLT scenario by 6.8% (Figure 3.23, lower left panel). The change is most likely
meaningful since the distribution of individual water year differences is skewed towards
positive (Figure 3.23, lower right panel).
The entrainment risk for Delta smelt (DS4) is expected to remain relatively constant
between project alternatives. A proportion of 0.055 of the population of larvae and juvenile
Delta smelt is estimated to be entrained and differences between estimated entrainment
proportions for project alternatives are expected to be less than 0.004.

Chapter 3: Effects Analysis Application of EFT
1 5 4 | Page
Overall, Delta smelt are expected to do worse in the LOS scenario in the Early-Long Term,
and better in the ESO scenario in the Late-Long Term, making the ESO scenario preferable
for Delta smelt.
Figure 3.23: Median Delta smelt habitat suitability index (DS2) under three BDCP scenarios
relative to NAA-ELT baseline (upper left panel), and the ESO-LLT scenario
relative to the NAA-LLT baseline (lower left panel). Individual year differences for
the ELT and LLT periods are shown in the upper right and lower right panels,
respectively.
Longfin Smelt
The median abundance index for longfin smelt (LS1) is expected to increase relative to
NAA-ELT under the HOS-ELT BDCP scenario by 9.4% (Figure 3.24, upper left panel). The
change is most likely meaningful since most individual water year differences are positive

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 5 5 | Page
(Figure 3.24, upper right panel). The improvement is most likely due to the occasional high
spring outflows included only in the operations of the HOS scenario (Chapter 3.2).
The median abundance index is expected to decrease slightly relative to NAA-LLT under
the ESO-LLT BDCP scenario, i.e., by 5.1% (Figure 3.24, lower left panel). The change is
most likely not meaningful since individual water year differences are both positive and
negative (Figure 3.24, lower right panel).
Figure 3.24: Median longfin smelt abundance index (LS1) under three BDCP scenarios
relative to the NAA-ELT baseline (upper left panel), and ESO-LLT relative to the
NAA-LLT baseline (lower left panel). Individual year differences for the ELT and
LLT periods are shown in the upper right and lower right panels, respectively.

Chapter 3: Effects Analysis Application of EFT
1 5 6 | Page
Invasive Deterrence
The index of median Brazilian waterweed suppression (ID1) is expected to remain relatively
constant between project alternatives with an estimated maximum three month average
salinity from May to October of 8.9‰ for the ‘Chipps Island to Oakley’ region.
The median overbite clam larval suppression (ID2) is expected to decrease relative to NAA-
ELT for all three BDCP scenarios as estimated minimum three month average salinities
increase from December to April from 2.7‰ to 3.3‰ for the ‘680 Bridge to Chipps Island’
region (Figure 3.25, left panel). The change is expected to be meaningful since almost all
individual water year differences are positive (Figure 3.25, right panel). This increase in
average salinity is due to the increased salinity at Port Chicago in February and March for
all BDCP scenarios, and also in April for ESO and LOS (Table 3.16).
The median Asiatic clam larval suppression (ID3) is expected to remain relatively constant
between project alternatives with an estimated maximum three month average salinity from
May to October of 8.9‰ for the ‘Chipps Island to Oakley’ region.
Figure 3.25: Median overbite clam larval suppression (ID2) under three BDCP scenarios
relative to the NAA-ELT baseline (left panel), and showing individual year
differences relative to the ELT baseline (right panel).
Tidal Wetlands
The median brackish wetland area (TW1) is expected to remain relatively constant between
project alternatives in the Early Long Term with an estimated area of approximately 700 ha.
The median brackish wetland area is expected to decrease in the Late Long Term for ESO-
LLT relative to NAA-LLT by 9% (Figure 3.26, upper left panel). The difference is expected to

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 5 7 | Page
be meaningful as all individual water year differences are negative (Figure 3.26, upper right
panel).
The median freshwater wetland area (TW2) is expected to remain relatively constant
between project alternatives in the Early Long Term with an estimated area of
approximately 280 ha. The median Freshwater wetland area is expected to decrease in the
Late Long Term for ESO-LLT relative to NAA-LLT by 5.9% (Figure 3.26, lower left panel).
The difference is expected to be meaningful as all individual water year differences are
negative (Figure 3.26, lower right panel).
Figure 3.26: Median brackish (TW1) and freshwater (TW2) wetland area in the Late Long
Term for ESO-LLT relative to NAA-LLT (upper left and lower left panels,
respectively), and showing individual year differences relative to the LLT base
case (upper and lower right panels).

Chapter 3: Effects Analysis Application of EFT
1 5 8 | Page
Future climate and demand effects
Climate and demand effect size results are closely tied to the ES methodology described in
Section 2.8.6. Table 3.31 shows results of this methodology for the Delta ecoregion. The
following section summarizes Climate/Demand effects in which the median effect differs by
more than 5% from a reference case comparative response. A synthesis of these effects is
presented in Table 3.35.
Table 3.31: Climate and demand effect sizes are shown for the No Action Alternative (NAA)
scenario at three future climate periods using the median difference Effect Size
(ES) method, preserving the native units of each indicator. 
Focal species
Performance indicator
NAA-Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Delta Indicators
Fall Chinook
Smolt weight gain (CS7; %)
21.2
19.1
(-2.0%)
17.7
(-3.4%)
Smolt predation risk (CS9; passage days)
15.3
15.5
(-1.5%)
15.7
(-2.5%)
Smolt temperature stress (CS10; degree day)
101.7
113.4
(-11.6%)
115.1
(-13.2%)
Late Fall Chinook
Smolt weight gain (CS7; %)
29.8
29.0
(-0.8%)
28.3
(-1.4%)
Smolt predation risk (CS9; passage days)
15.7
15.6
(0.7%)
15.5
(1.1%)
Smolt temperature stress (CS10; degree day)
58.2
60.8
(-4.3%)
64.3
(-10.4%)
Spring Chinook
Smolt weight gain (CS7; %)
24.2
23.0
(-1.3%)
22.1
(-2.1%)
Smolt predation risk (CS9; passage days)
15.4
15.6
(-1.4%)
15.6
(-1.2%)
Smolt temperature stress (CS10; degree day)
84.2
87.1
(-3.4%)
88.1
(-4.5%)
Winter Chinook
Smolt weight gain (CS7; %)
30.4
30.3
(-0.1%)
29.6
(-0.7%)
Smolt predation risk (CS9; passage days)
14.5
14.7
(-1.2%)
14.7
(-1.7%)
Smolt temperature stress (CS10; degree day)
39.6
42.5
(-7.3%)
46.1
(-16.5%)
Steelhead
Smolt weight gain (CS7; %)
19.7
17.7
(-2.0%)
16.4
(-3.3%)
Smolt predation risk (CS9; passage days)
15.6
15.8
(-0.8%)
15.7
(-0.2%)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 5 9 | Page
Focal species
Performance indicator
NAA-Current
Reference
case (225)
NAA-ELT
(233)
NAA-LLT
(243)
Delta Indicators
Smolt temperature stress (CS10; degree day)
106.7
113.3
(-6.2%)
119.4
(-11.8%)
Splittail
Proportion max spawning habitat (SS1)
0.000
0.000
0.000
Delta Smelt
Spawning success (DS1; optimal days)
33.3
33.0
(-0.8%)
33.7
(1.2%)
Habitat suitability index (DS2)
3,023
3,456
(14.3%)
3,423
(13.2%)
Larval & juvenile entrainment proportion (DS4)
0.059
0.054
(0.4%)
0.062
(-0.3%)
Longfin Smelt
Abundance index (LS1)
95.8
66.6
(-30.5%)
59.0
(-38.5%)
Invasive Deterrence
Brazilian waterweed suppression (ID1)
9.1
9.1
(0.4%)
8.9
(-1.4%)
Overbite clam larval suppression (ID2)
2.1
2.7
(-25.7%)
2.9
(-36.9%)
Asiatic clam larval suppression (ID3)
9.1
9.1
(0.4%)
8.9
(-1.4%)
Tidal Wetlands
Brackish wetland area (TW1; ha)
750.7
705.5
(-6.0%)
647.8
(-13.7%)
Freshwater wetland area (TW2; ha)
288.9
283.7
(-1.8%)
194.6
(-32.6%)
 The NAA-Current scenario serves as a comparative reference case with percentage differences shown below absolute
median effects. Percentage differences for indicators measured as proportions are based on the simple arithmetic difference
in comparison to the reference case; all other indicators are based on the proportional difference in comparison to the
reference case. The sign of the difference depends on whether the indicator improves (more is better) or declines (more is
worse) relative to the reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes:
5-10%, 10-20% and >20%.
Salmonids
Median smolt temperature stress (CS10) for fall-run Chinook becomes more extreme under
the two future scenarios, increasing by 11.6% and 13.2% under the NAA-ELT and NAA-LLT
scenarios respectively (Figure 3.27).
Late fall-run Chinook smolts experience a 10.4% increase in median thermal stress (CS10)
in the NAA-LLT scenario, compared to the NAA-Current scenario (Figure 3.27).
Winter-run Chinook smolts experience similar increases in median thermal stress (CS10) of
7.3% and 16.5% in the NAA-ELT and NAA-LLT scenarios, compared to the reference case
(Figure 3.27).

Chapter 3: Effects Analysis Application of EFT
1 6 0 | Page
Steelhead smolts experience similar increases in median thermal stress (CS10) of 6.2%
and 11.8% in the NAA-ELT and NAA-LLT scenarios, compared to the reference case
(Figure 3.27).
Figure 3.27: Smolt temperature stress (CS10) in the Early Long Term (ELT, 2030) and Late
Long Term (LLT, 2060) period compared to the NAA-Current reference case for
fall-run Chinook (upper left panel), late fall-run Chinook (upper right panel),
winter-run Chinook (lower left panel), and steelhead (lower right panel).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 6 1 | Page
Splittail
The median proportion of maximum spawning habitat for splittail (SS1) is expected to
remain constant under different future climates and demands.
Delta Smelt
The median spawning success for Delta smelt (DS1) is expected to remain relatively
constant under different future climates and demands at approximately 33 optimal days.
The median habitat suitability index for Delta smelt (DS2) is expected to increase relative to
the NAA-Current scenario under future climates and demands: 14.3% and 13.2% for NAA-
ELT and NAA-LLT (Figure 3.28, left panel). The change is expected to be meaningful since
the majority of individual water year differences are positive (Figure 3.28, right panel). The
improvement is most likely due to the inclusion of Fall X2 actions under the ELT and LLT
scenarios for NAA (Chapter 3.2).
The entrainment risk for Delta smelt (DS4) is expected to remain relatively constant under
different future climates and demands at approximately 0.055.
Figure 3.28: Median Delta smelt habitat suitability index (DS2) under future climate and
demand relative to the NAA-Current baseline (left panel), showing individual year
differences relative to the baseline scenario (right panel).
Longfin Smelt
The median abundance index for longfin smelt (LS1) is expected to decrease relative to the
NAA-Current scenario under the future climate and demand scenarios: 30.5% and 38.5%
for NAA-ELT and NAA-LLT (Figure 3.29, left panel).The change is expected to be

Chapter 3: Effects Analysis Application of EFT
1 6 2 | Page
meaningful since almost all of individual water year differences are negative (Figure 3.29,
right panel). The deterioration is most likely due to the increased salinity in Suisun Bay
caused by sea level rise (Chapter 3.2).
Figure 3.29: Median longfin smelt abundance index (LS1) under future climate and demand
relative to the NAA-Current baseline (left panel), showing individual year
differences relative to the baseline (right panel).
Invasive Deterrence
The median Brazilian waterweed suppression (ID1) is expected to remain relatively
constant under future climates and demands with an estimated maximum three month
average salinity from May to October of 8.9‰ for the ‘Chipps Island to Oakley’ region.
The median overbite clam larval suppression (ID2) is expected to decrease relative to NAA-
Current for future climates and demands. The estimated minimum three month average
salinity from December to April increases from 2.1‰ in the current future climate period to
2.7‰ in the Early Long Term and 2.9‰ in the Late Long Term for the ‘680 Bridge to Chipps
Island’ region (Figure 3.30, left panel). The change is expected to be meaningful since
almost all individual water year differences are positive (Figure 3.30, right panel). The
deterioration is most likely due to the increased salinity in Suisun Bay caused by sea level
rise (Chapter 3.2).
The median Asiatic clam larval suppression (ID3) is expected to remain relatively constant
under future climates and demands with an estimated maximum three month average
salinity from May to October of 8.9‰ for the ‘Chipps Island to Oakley’ region.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 6 3 | Page
Figure 3.30: Median overbite clam larval suppression (ID2) under future climate and demand
relative to the NAA-Current baseline (left pane), showing individual year
differences relative to the baseline (right panel).
Tidal Wetlands
The median brackish wetland area (TW1) is expected to decrease relative to NAA-Current
under future climates and demands: 6.0% and 13.7% for NAA-ELT and NAA-LLT (Figure
3.31, upper left pane). The change is expected to be meaningful since almost all individual
water year differences are negative for NAA-ELT and all water year differences are negative
for NAA-LLT (Figure 3.31, upper right pane). This change is driven by sea-level rise.
The median freshwater wetland area (TW2) is expected to decrease in the Late Long Term
by 32.6% for NAA-LLT relative to NAA-Current (Figure 3.31, lower left pane). The change is
expected to be meaningful since all water year differences are negative for NAA-LLT
(Figure 3.31, lower right pane).
Note, these projected changes do not consider the potential opportunity for physical
restoration to offset or reverse these losses.

Chapter 3: Effects Analysis Application of EFT
1 6 4 | Page
Figure 3.31: Median brackish (TW1) and freshwater (TW2) wetland area under future climate
and demand scenarios relative to the NAA-Current baseline (upper left and lower
left panels, respectively), showing individual year differences relative to the
baseline (upper and lower right panels ).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 6 5 | Page
Water year characterization
Although they cannot be compared directly to a reference case, for many indicators, Water
Year effects are larger than operation and conveyance effects. The following section
describes these effects indicator by indicator.
Salmonids
Differences among water years are seen for all salmonid indicators in the Delta ecoregion,
with simple patterns that are consistent across all run types. These are summarized in
Table 3.32. One of the more interesting patterns is for smolt weight gain (CS7), which
benefits in both low and high flow years, for reasons that are given in the table.
Table 3.32: Summary of Water Year patterns observed for salmonid indicators from the San
Joaquin-Delta ecoregion.
Indicator
Run type
Pattern
Explanation
Typical Boxplot
Smolt weight
gain (CS7)
All
Improved
in
extreme
years
Peak salmonid growth
is enhanced with
longer residence time
(lower flow dry years)
and more substantial
proportion of the
cohort in Yolo (wetter
years).
Smolt
predation risk
(CS9)
All
Declining
in wetter
years
Predation risk is
reduced in high flow
years with shorter
passage time
Smolt
temperature
stress (CS10)
All
Declining
in wetter
years
Smolt stress is
reduced in cooler high
flow years
Splittail
The median proportion of maximum spawning habitat for splittail (SS1) increases
meaningfully in wetter Water Year types, with the median for extremely wet water years

Chapter 3: Effects Analysis Application of EFT
1 6 6 | Page
being almost twice the amount expected in normal and drier Water Year types (Figure
3.32).
Figure 3.32: Median proportion of maximum spawning habitat for splittail (SS1) by Water Year
type.
Delta Smelt
The median spawning success for Delta smelt (DS1) is expected to remain relatively
constant between Water Year types.
The median habitat suitability index for Delta smelt (DS2) is expected to increase
meaningfully in above normal and extremely wet water years (Figure 3.33, left panel) with
median habitat suitability index in extremely wet water years being more than twice the
value of normal and drier Water Year types.
The entrainment risk for Delta smelt (DS4) is expected to decrease meaningfully in above
normal and extremely wet water years (Figure 3.33, right panel) with median entrainment
risk in extremely wet water years being almost half the value of normal and drier Water Year
types.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 6 7 | Page
Figure 3.33: Median habitat suitability index for Delta smelt (DS2, left panel) and entrainment
risk for Delta smelt (DS4, right panel) by Water Year type.
Longfin Smelt
The median abundance index for longfin smelt (LS1) is expected to be relatively higher in
above normal and extremely wet Water Year types (Figure 3.34) with median abundance
index values being approximately twice that of drier years.

Chapter 3: Effects Analysis Application of EFT
1 6 8 | Page
Figure 3.34: Median abundance index for longfin smelt (LS1) by Water Year type.
Invasive Deterrence
The median Brazilian waterweed suppression (ID1) is expected to decrease in wetter Water
Year types as maximum three month average salinity from May to October decreases for
the ‘Chipps Island to Oakley’ region (Figure 3.35, upper left panel).
The median overbite clam larval suppression (ID2) is expected to increase meaningfully in
wetter Water Year types as minimum three month average salinity from December to April
decreases for the ‘680 Bridge to Chipps Island’ region (Figure 3.35, upper right panel).
The median Asiatic clam larval suppression (ID3) is expected to decreases in wetter Water
Year types as maximum three month average salinity from May to October decreases for
the ‘Chipps Island to Oakley’ region (Figure 3.35, lower left panel).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 6 9 | Page
Figure 3.35: Median Brazilian waterweed suppression (ID1, upper left panel), overbite clam
larval suppression (ID2, upper right panel), and Asiatic clam larval suppression
(ID3, lower left panel) by Water Year type.
Tidal Wetlands
Both the brackish (TW1) and freshwater (TW2) wetland area remains highly variable in all
Water Year types without any distinguishable pattern.
Summary of Species Net Effects
Table 3.34 and Table 3.33 demonstrate that among the salmonids, fall-run Chinook, spring-
run Chinook (LSO alternative only), and late fall-run Chinook benefit from BDCP

Chapter 3: Effects Analysis Application of EFT
1 7 0 | Page
alternatives. Fall-run Chinook (all three alternatives) and spring-run Chinook (LOS
alternative only) are beneficiaries that show meaningful improvement in suitable spawning
habitat (CS1). Likewise, late fall-run Chinook benefit from improvements to flows during
rearing (CS2, CS7) relative to current conditions (this is in part associated with the
conditions in the NAA-ELT reference case itself, not from any additional features of the
three operational alternatives). Some of the improvement in Delta rearing habitat conditions
(and pre-smolt growth, CS7) for late fall-run Chinook may be offset by increased
temperature stress (CS10). Overall Net Effect Scores (NES) are provided in Table 3.35.
EFT results show that overall, the LOS BDCP alternative is preferable for species
completing life-history stages in the Sacramento River (especially fall-run Chinook, late fall-
run Chinook and spring-run Chinook) while the HOS BDCP alternative is preferable for San
Joaquin-Delta species (especially longfin smelt and, to a lesser degree, Delta smelt) (Table
3.36). Fall-run Chinook, late fall-run Chinook, and splittail do better under all BDCP
alternatives considered ("winners"), while green sturgeon, deterrence of invasives and
brackish wetland habitats are expected to experience deteriorating conditions (Table 3.36).
Overall, the HOS alternative is likely the most preferable in terms of delivering ecological
benefits. While LOS ecosystem benefits are superior for species in the Sacramento River,
results from HOS are generally very similar. EFT results suggest the HOS is more likely to
benefit Delta smelt and the LOS is predicted to be detrimental to longin smelt.
In general, results for winter-run Chinook, steelhead, bank swallows, Fremont cottonwood
and large woody debris recruitment do not show any clear discriminatory results amongst
these BDCP alternatives. Fremont cottonwood initiation (FC1) and vegetation recruitment to
the mainstem Sacramento River (LWD1) show only small marginal responses to BDCP
alternatives without any clear large differential effects amongst the alternatives considered.
Spring-run Chinook are expected to do the most poorly under ESO and HOS alternatives in
terms of spawning habitat (CS1), egg-to-fry survival (CS3), and redd dewatering (CS6).
In general, juvenile stranding (CS4) losses increase, particularly for winter-run Chinook.
Delta temperature stress (CS10) on winter-run Chinook also increases over all ELT
alternatives. Likewise, Delta temperature stress (CS10) is also elevated over all ELT
alternatives for steelhead.
Green sturgeon are expected to do worse under future climate conditions due to rising
water temperatures (GS1).
Splittail are clear winners in all BDCP scenarios. For splittail, this is due to the Fremont Weir
notch included in all project alternatives. Sacramento River large woody debris improves
under the ESO and HOS scenarios according to the ES method, but not when looking at the
RS difference.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 7 1 | Page
Results suggest Delta smelt habitat (DS2) is reduced under LOS, although the magnitude of
this reduction is marginal, while longfin smelt does better under HOS (ES results) relative to
the other alternatives.
The ability to suppress overbite clam larvae (ID2) is weakened under all BDCP scenarios.
Likewise, Brazilian waterweed suppression (ID1) is reduced somewhat under the LOS
scenario.
Brackish wetland area shows considerable declines owing to sea level rise under the ELT
climate future (noting that EFT results do not include potential benefits of physical habitat
restoration).
The impact of future climate and demand is significantly stronger than the impact from
alternative operations and conveyance. The negative effects of future climate and demand
are readily apparent, particularly in the LLT period (Table 3.35). Spring-run Chinook in
particular suffer under projected future climate conditions, with most notable effects on all
temperature sensitive species (especially the CS10 indicator). Steelhead, bank swallow,
Fremont cottonwood, large woody debris, and splittail do not show meaningful effects under
the future climate and demand scenarios considered here.
While compensation is not the general outcome, the BDCP alternatives do provide some
offsetting benefits to help cope with climate change effects. In particular spawning habitat
(CS1) is improved by the conveyance and operations in BDCP alternatives for fall-run
Chinook and spring-run Chinook (LOS alternative only). Delta rearing conditions (CS7) are
improved by notching of the Fremont Weir associated with the ESO, LOS and HOS BDCP
alternatives, offsetting losses that are otherwise expected for late fall-run, winter-run and, to
a lesser degree, spring-run Chinook. Spring-run Chinook also receive compensatory offsets
of otherwise detrimental climate change effects from the LOS scenario, in terms of
reductions to redd dewatering losses (CS6) and improved Sacramento river rearing
conditions (CS2).
Delta smelt habitat shows improvement using the ES method for both future epochs, due to
a change in operations as Fall X2 action is assumed implemented in the ELT and LLT
epochs.

Chapter 3: Effects Analysis Application of EFT
1 7 2 | Page
Table 3.33: Summary of Project vs Climate/Demand effects for Sacramento River and Delta
ecoregion, as measured by the RS difference .
Project
Relative to
NAA-ELT
Climate & Demand
Relative to
NAA-Current
Upper & Middle Sacramento River Ecoregion
ESO
LOS
HOS
ELT
LLT
+
–
+
–
+
–
+
–
+
–
Fall
1*
1*
1*
1*,3,4
Late Fall
2
2
4
Spring
1*,6*
2
1,3,6
1,3,6
Winter
2*
4
2*
4
4
1,2*
1,2,3
Steelhead
Bank swallow
Green Sturgeon
1
1
Cottonwood
Woody Debris
Delta Ecoregion
Fall
7
7,10
Late Fall
7
7
7
7
7
Spring
10
10
Winter
7
10
7
10
7
10
10
Steelhead
7
7
Splittail
1
1
1
Delta smelt
4
Longfin smelt
Invasives
1
Tidal wetlands
1
1,2
 Numbers indicate the number of the indicator with a meaningful (>10%) positive or negative change for each comparison;
shaded green in ‘+’ columns and red in ‘–‘ columns. Key to salmonid indicators: 1 = suitable spawning habitat, 2 = suitable
rearing habitat, 3 = thermal egg-to-fry survival, 4 = juvenile stranding index, 6 = redd dewatering, 7 = smolt weight gain, 10 =
smolt temperature stress. Key to Cottonwood indicators: 1 = initiation. Key to Delta smelt indicators: 4 = larval and juvenile
entrainment. Key to invasives indicators: 1 = Brazilian waterweed suppression. Key to tidal wetlands: 1 = brackish, 2 =
freshwater. "*" refers to an indicator result where ESO/LOS/HOS conveyance and operations largely compensate for
expected climate change losses expected between the current and ELT time frame.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 7 3 | Page
Table 3.34: Summary of Project vs Climate/Demand effects for Sacramento River and Delta
ecoregion, as measured by the ES method .
Project
Relative to
NAA-ELT
Climate & Demand
Relative to
NAA-Current
Upper & Middle Sacramento River Ecoregion
ESO
LOS
HOS
ELT
LLT
+
–
+
–
+
–
+
–
+
–
Fall
1
1
1
Late Fall
1
1
1
Spring
1
1
2
1
1,3
Winter
Steelhead
Bank swallow
Green Sturgeon
1
Cottonwood
1
1
1
Woody Debris
1
1
Delta Ecoregion
Fall
10
10
Late Fall
7
10
7
9,10
7
10
10
Spring
Winter
9,10
10
9,10
10
10
Steelhead
10
10
10
10
10
Splittail
1
1
1
Delta smelt
2
2
2
Longfin smelt
1
1
1
Invasives
2
2
2
2
2
Tidal wetlands
1
1,2
 Numbers indicate the number of the indicator with a meaningful (>5%) positive or negative change for each comparison;
shaded green in ‘+’ columns and red in ‘–‘ columns. Key to salmonid indicators: 1 = suitable spawning habitat, 2 = suitable
rearing habitat, 3 = thermal egg-to-fry survival, 4 = juvenile stranding index, 7 = smolt weight gain, 9 = smolt predation risk;
10 = smolt temperature stress. Key to Cottonwood indicators: 1 = initiation. Key to Delta smelt indicators: 2 = habitat
suitability. Key to invasives indicators: 2 = overbite clam larval suppression. Key to tidal wetlands: 1 = brackish, 2 =
freshwater.

Chapter 3: Effects Analysis Application of EFT
1 7 4 | P a g e
Table 3.35: Overall weight of evidence and assessment of net effects by species, Sacramento River Ecoregion and Delta
Ecoregion. Refer to legend below the table. The asterisk (*) indicates where ESO/LOS/HOS conveyance and
operations partially offset expected climate change losses anticipated between the current and ELT time frame.
Project
Climate & Demand
Relative to NAA-ELT
Relative to NAA-Current
Upper & Middle Sacramento River Ecoregion
ESO
LOS
HOS
ELT
LLT
+
–
+
–
+
–
+
–
+
–
Fall
5
5
5
3-
RS*
Late Fall
(Benefits from ELT
baseline)
1-ES
1-ES
+/–
+/–
Spring
3-ES
5
3-RS
2-RS*
5
Winter
1-RS
1-RS
3-RS*
3-RS
Steelhead
Bank swallow
Green Sturgeon
(Negative changes
caused by ELT baseline)
3-RS
3-RS
3-RS
3-ES
5
Cottonwood
1-ES
1-ES
1-ES
Woody Debris
1-RS
1-RS
Delta Ecoregion
Fall
+/–
+/–
+/–
5
5
Late Fall
3-ES
3-ES
2-ES
3-RS*
5
Spring
+/–
+/–
+/–
3-RS
3-RS
Winter
3-ES
3-ES
2-ES
5
5
Steelhead
3-ES
3-ES
2-ES
5
3-ES
Splittail
6
6
6

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 7 5 | P a g e
Delta smelt
6
6
6
Longfin smelt
6
3-ES
3-ES
Invasives
3-ES
4
3-ES
3-ES
3-ES
Tidal wetlands
3-RS
3-RS
3-RS
5
5
Neither the RS nor ES summary method generates a potential change that passes our ±10% and ±5% thresholds. No meaningful
effect.
+/-
Mixed effects -- indicators for same species show benefits and penalties (i.e., Chinook/steelhead), but the net effect is difficult
to determine.
1-RS
RS summary method shows a potential effect (passes ±10% threshold). However, the results are highly variable.
1-ES
ES summary method shows a potential effect (passes ±5% threshold). However, the results are highly variable.
2-RS
RS summary method shows a potential effect of ±10% change or more in favorable years, with clear signal to noise (less
variability), yet the ES summary view shows the inverse effect (potentially contradictory evidence).
2-ES
ES summary method shows a potential effect of ±5% change in absolute median effect size, with clear signal to noise (less
variability), yet the RS summary view shows the inverse effect (potentially contradictory evidence).
3-RS
RS summary method shows a potential effect of ±10% change or more in favorable years, with clear signal to noise (less
variability), and the ES summary view does not meet threshold (no contradictory evidence).
3-ES
ES summary method shows a potential effect of ±5% change in absolute median effect size, with clear signal to noise (less
variability), and the RS summary view does not meet threshold (no contradictory evidence).
4
Both summary views agree on the direction of the potential effect, and both pass the threshold for a potentially meaningful
effect. However, both show a highly variable spread in results.
5
Both summary views agree on the direction of the potential effect, and both pass the threshold for a potentially meaningful
effect with clear signal to noise (less variability).
6
Either category "3","4" or "5" + a fundamental link to scenario description.

Chapter 3: Effects Analysis Application of EFT
1 7 6 | P a g e
Table 3.36: Overall summary of "winners and losers" for the selected BDCP alternatives.
Sacramento
River species
San Joaquin-
Delta species
Focal species
All
Alternatives
ESO-ELT
(237)
LOS-ELT
(238)
HOS-ELT
(242)
Primary
benefit /
[Challenge]
Caveats
Fall Chinook
↑
CS1
Late Fall Chinook
↑
<benefit from ELT baseline conditions,
not the alternatives>
CS2, CS7
[CS10]
Delta thermal stress
(CS10)
Spring Chinook
↓
↑
↓
CS1, CS6,
CS2
Winter Chinook
No clear discriminatory results/preferences amongst
alternatives (though some evidence conditions better
under HOS)
Delta thermal stress
(CS10)
Steelhead
No clear discriminatory results/preferences amongst
alternatives
Delta thermal stress
(CS10)
Bank Swallows
No clear discriminatory results/preferences amongst alternatives
Green sturgeon
↓
[GS1]
Fremont cottonwood
No clear discriminatory results/preferences amongst alternatives
Large woody debris
No clear discriminatory results/preferences amongst alternatives
Splittail
↑
Fremont weir notch included in all project
alternatives
Delta Smelt
↓
[DS2]
Longfin Smelt
↑
LS1
Invasive Deterrence
↓
[ID2]
Tidal Wetlands
↓
We do not consider physical habitat
restoration effects in this EFT analysis
(did not have post restoration DEM)
3.3.4 Caveats & Limitations
There are approximately 22 different conservation measures in BDCP, many of which were
not evaluated using EFT. EFT focuses on effects of flow operations, and also includes Yolo
Bypass fisheries enhancement. However, we did not consider the potential food web effects

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 7 7 | P a g e
of restoring 55,000 acres of tidal freshwater and brackish marsh, nor related effects of
restoring 10,000 acres of transitional habitat (BDCP conservation measures 4 and 5), nor
channel margin enhancements (BDCP conservation measure 6) (BDCP 2013). EFT
analyses do not consider the issue of pelagic food webs. These BDCP physical restoration
actions propose to improve zooplankton food sources for pelagic fish by helping to
subsidize the lower trophic levels of pelagic food webs. The magnitude of any
phytoplankton and zooplankton subsidy resulting from restored habitat depends on many
factors and assumptions, none of which are presently included in EFT. Indeed there
remains considerable uncertainty over the likely benefits of physical habitat restoration, and
whether such actions are more likely sources or sinks for zooplankton that will result in food
web pathways that benefit smelt and other target species (Mount et al. 2013; DSP 2014).
Our effects analysis does not address effects on every important species; instead we focus
on the 13 species and habitats described in Chapter 2. For the species that are included,
portions of the life-cycle are not included, e.g., the ocean phase of salmonid life-cycle is
ignored for all Chinook run-types and for steelhead.
EFT's results are based on outputs from external hydrologic models (CALSIM, DSM2, etc.)
These modeling tools contain high uncertainties when applied to future conditions such as
sea level rise and water temperatures, and they do not include hydrodynamic effects of
future tidal and intertidal restored lands (DSP 2014). The physical modeling suite used for
BDCP involves exchanges of inputs and assumptions, including hand-offs between 1-, 2-,
and 3-dimentional models, which creates error. These models also contain assumptions
about assumed levels of operational "foresight" that can differ from what a real-world
operator may have available. Further, the physical models used to assess BDCP only
considered one configuration of future Restoration Opportunity Areas, but these simulations
were not made available for use in our EFT effects analyses (we instead assumed the
current Delta configuration under sea level rise). To date, there is no assessment of these
model errors and how they impact BDCP results (Mount et al. 2013; DSP 2014). Any such
errors or biases will be propagated forward into EFT ecological effects analysis results.
Another limitation of our analysis (not of EFT), is that the operational criteria embedded in
the BDCP physical modeling were highly constrained, reducing assessment of a more
complete range of operational flexibility at major reservoirs. Amongst others, these
constraints included SWRCB water rights decision D1641, reservoir constraints (carry over
storage, cold water pool management), and Biological Opinions (USFWS 2008 and NMFS
2009). These regulatory, operational and infrastructure constraints limit the ability of BDCP
to fully explore and realize operations that may improve ecosystem conditions (Mount et al.
2013), and importantly, account for the sometimes "low contrast" in EFT effect size results.
In other words, when the system is operated according to a rigid set of fixed, layered
constraints, there are trade-offs managers simply cannot get around. Moreover, our findings
should be accompanied with this caveat: EFT results apply only if the system were actually
operated to achieve the flows indicated by the hydrosystem models. If rules are not in place

Chapter 3: Effects Analysis Application of EFT
1 7 8 | P a g e
to ensure Delta flows would actually be managed in the manner prescribed by the modeling,
the potential effects shown by EFT will not be realized.
Hatchery programs in the Central Valley may pose threats to Chinook salmon stock genetic
integrity (NMFS 2009, 2007). The long history of dependence on hatchery production to
mitigate for habitat loss is a threat having deleterious genetic effects on wild stocks
(Goodman 2005; Akari et al. 2008; Chilcote et al. 2011). The capacity for hatchery
introgression to genetically interrupt local adaptation in naturally reproducing populations is
particularly troubling because it likely reduces the capacity of “wild” stocks to track changes
to physical habitats. The effects of hatchery propagation on "wild" Chinook and steelhead
populations is not included in EFT effects analyses.
An estimated 5,000 to 40,000 tons of contaminants enter the Bay-Delta system annually
(CALFED 2000). Contaminants entering the system are distributed by complex flow
patterns influenced by inflow from the rivers and the amount of water being pumped from
the Delta. Contaminants include inorganic substances such as heavy metals, nitrates and
phosphates, organic contaminants such as PCBs, pesticides, plastics, detergents and
fertilizers, and biological pathogens such as bacteria, viruses and protozoans (CALFED
2000). Effects of these point and non-point sources of contaminants are not considered in
EFT.
Finally, flow management alone is not the complete answer to reconciling species to
conditions in the Sacramento River and Delta. Non-flow actions such as physical habitat
restoration, rip-rap removal, gravel augmentation, water quality improvement efforts, and
removal of invasive species are an important part of an overall comprehensive rehabilitation
plan.
3.4 Pilot Investigation: Incorporating EFT Derived Ecological Flow
Criteria to CALSIM
3.4.1 Introduction
EFT development has concentrated on getting the science right: integrating multiple focal
species indicators and their important habitats at a sufficient level of detail. Like other
ecological models, EFT is applied “reactively” as a second stage effects analysis of CALSIM
(or equivalent model) output. Until recently, loose coupling of EFT with other physical
models, and serial simulations (CALSIM  USRDOM  Meander Migration/Bank Erosion
 DSM2 EFT) have restricted EFT modeling to the type of post-processing effects
analysis and trade-off evaluation described in Section 3.3. As-is, this "one-way
communication" limits opportunities to fully realize the goals of this tool. For some time,
TNC and ESSA have envisioned running EFT in “prospective” or “proactive” mode by
inserting simplified (but relevant) rule-sets for multiple functional species needs (derived

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 7 9 | P a g e
from analysis of EFT output) into the physical driving models themselves. The ability to
directly insert the additional insights obtained from EFT on preferred ecological rules into
the hydrologic planning models themselves is an important "full circle" application of our
research.
In this phase of the Project we: 1) summarized simplified but meaningful ecological flow
rule-sets for all species and indicators in EFT; 2) initiated a pilot study where we selected
two of these species performance indicators (one set of rules for a Sacramento River target,
another for a Delta target) to insert into CALSIM II (while preserving rules that protected
Shasta storage and Delta exports); and finally 3) imported these CALSIM results into EFT
and performed an effects analysis for all species and performance indicators. Ultimately, we
explored whether it is possible to improve ecological conditions for the two target indicators
without creating negative consequences on non-target species and water supply objectives.
3.4.2 Pilot EFT Rule-Set Alternative Compared with Reference Case & Historical
Scenarios
Due to confidentiality issues associated with the BDCP EIS/R, we were unable to access
WRESL configuration files for the BDCP CALSIM II model. Instead, our Ecological Flows
pilot study was based on the simulations used to complete the 2011 Delivery Reliability
Report [DRR 2011] (DWR 2010a, 2010b, 2012), an analysis of current and near future
demand needs which is updated every two years by DWR (see Table 3.37). We used this
publically available DRR future (2031) scenario as our system operation reference case, to
test and compare our attempts to insert new ecological flow (Pilot Study) rule-sets on top of
the DRR CALSIM II configuration. We subsequently applied EFT to analyze effects both for
the DRR reference case and the Pilot Study ecological rule-sets we inserted to modify this
reference case.
The DRR (2011) future scenario includes anticipated demand conditions for the year 2031,
incorporating current operating restrictions caused by the Biological Opinions (BOs) issued
in December 2008 and June 2009 by the U.S. Fish and Wildlife Service (USFWS) and
National Marine Fisheries Service (NMFS), which govern State Water Project (SWP) and
Central Valley Project (CVP) operations. The scenario features improved adherence to the
existing BOs and changes in system operation for current conditions. Of particular note, the
2011 DRR scenarios calculate daily spills at the Fremont and Sacramento weirs, which are
of particular use for EFT simulations.
Future (2031) conditions are based on anticipated future demand only, and neither climate
change nor sea level rise is included in the simulation.18 A detailed discussion of the model
18 Draft DRR 2013 simulations include climate change and sea level rise, but have not yet been released.

Chapter 3: Effects Analysis Application of EFT
180 | P a g e
assumptions used for DRR studies, including the BOs and an overview of the CALSIM II
software, can be found in the 2009 Delivery Reliability Report (DWR 2010a, 2010b).19
Use of a historical reference case has been recommended by the Delta Science Panel.
Such a comparison provides perspective on how much cumulative change has already
been "locked in" and allows for assessment of total cumulative change (relative to the
historical reference case). While it may be impractical to return to past levels of
development and of demand and operations, using a sufficiently long historical reference
case informs managers about the degree to which proposed future actions (e.g., including
the conditions associated with the chosen reference case) may contribute towards recovery
of priority species, and provides context for ongoing efforts to improve habitat and to
rehabilitate fish populations.
Results in this section include comparison of historical conditions with the DRR 2011
reference case to illustrate this form of change. However, we excluded comparison of
historical conditions for EFT performance indicators when any of the following occurred:
1. Historical time series were too short (the historical simulation included fewer than
half the years present in the simulated reference case scenario20);
2. The frequency of dry or wet water years was substantively different between the
historical simulation and the simulated reference case scenario;
3. There were substantial differences between the physical locations used in the
historical simulation vs. the reference case simulation.
19 A technical addendum for the DRR 2011 study has not been posted by DWR.
20 If the historical simulation included twenty or more years, it was not excluded based on this criterion.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
181 | P a g e
Table 3.37: Summary of conditions used for the reference case ecological flow scenario and
the modified version including pilot study rule-sets for winter-run Chinook and
Delta smelt.
Name
Conveyance
modifications
Level of human
demand
Climate change
Major operational features
Reference
case:
2011
DWR
Delivery
Reliability
Operations
(DRR)
None. Current
hydrosystem
(as of 2011).
No changes to
size/number of
dams,
capability of
Delta pumps,
gates
Future (2031)
demand
Does not include
climate change
or sea level rise
Incorporates State Water Board D-
1641 including NMFS Biological
Opinions (2008, 2009)
Simulations also include San Joaquin
restoration actions and improved
daily simulation of Fremont and
Sacramento Weir spills
No notch in Fremont Weir
High Fall X2 outflow
As above +
EFT Pilot
Study
rule-sets
for Winter
Chinook and
Delta smelt
As above
As above
As above
As above and
Winter Chinook:
Flow at Clear Creek
Aug to Dec: 7,000 – 8,000 cfs
May to Jun: 5,000 – 12,000 cfs
Delta smelt:
Combined Old and Middle River flow
Normal and wetter Water Year
Types Apr & June: > 0 cfs
Below Normal Water Year Types:
Apr & Jun: > 2,000 cfs
“Off-ramping” and “water banking”
strategies for drought years and
low-flow months
3.4.3 EFT Ecological Flow Criteria & Initial Rule-sets Tested
For this pilot analysis, we used EFT to derive ecologically beneficial rule-sets for winter-run
Chinook and Delta smelt. Winter-run Chinook and Delta smelt were chosen based on their
threatened status and differing location: Upper Sacramento and Delta. Specifically, we
implemented flows that would provide more beneficial conditions for winter-run Chinook
spawning WUA (CS1), juvenile stranding (CS4) and rearing WUA (CS2). Thermal egg
mortality (CS3), redd dewatering (CS6) and redd scour (CS5) were not targeted for
improvement in our EFT rule-set because all three sources of mortality were either relatively

Chapter 3: Effects Analysis Application of EFT
182 | P a g e
low or impossible to address using a monthly model (CALSIM). Entrainment risk (DS4) was
targeted for Delta smelt. Actions were already included in the DRR reference case to
improve spawning success (DS1) and habitat suitability (DS2). Based on the selected
species and performance indicators, EFT rule-sets that targeted more beneficial flows were
established for May, June and August to December for the Sacramento River, and from
April to June for changes to Old and Middle River flows in the Delta (see Section 2.9.2;
Table 2.14 and Table 2.15). Additional details of this important step are described in Section
2.7.8.
3.4.4 Results and Discussion
The results from this pilot study have shown that, even though the California water system
is highly constrained, there is still room to improve conditions for various species by
changing operations without undue effects on water supply. However, the results also
reinforce the challenge of trade-offs between species, and the absence of a singular win-
win-win option.
The implementation of the proposed EFT flow targets in CALSIM generated altered flows in
the Sacramento River in July to December, from April to May, and again from September to
December in the Old and Middle River in the Delta. CALSIM-modeled Sacramento River
flows did not experience a meaningful change (relative to the DRR baseline) in May and
June because the reference scenario flows were already commonly in the preferred flow
range during these months. Hence, we found that conditions could potentially be improved
for winter-run Chinook spawning by focusing on a narrower range of flows. The EFT rule-set
applied to CALSIM also decreased Sacramento River flows in July and August relative to
the reference scenario (that in the baseline case, were often above 8 kcfs recommended for
winter-run Chinook rearing WUA). In September to December, when Sacramento River
flows were typically below the 7 kcfs recommended for winter-run Chinook juvenile
stranding, the EFT rule-set generated the desired increased flows.
The pilot EFT rule-set improved performance for winter-run Chinook juvenile stranding, but
not for spawning WUA. The modified flows reduced juvenile stranding by lessening the
month to month changes. Winter-run Chinook spawning WUA did not improve because the
recommended flows were already being achieved using the rule-set in the reference DRR
scenario. Winter-run Chinook juvenile rearing habitat did not benefit because the EFT rule-
set generated higher August to December flows. The lack of improvement for winter-run
Chinook rearing WUA was also a trade-off with juvenile stranding, as lower flows in August
to December are assumed to increase rearing WUA and worsen juvenile stranding. With
additional iteration, this issue could potentially be refined in future EFT ecological rule-sets.
In the Delta, our EFT rule-set generated some delays in water exports from spring to fall,
leading to more positive flow in the Old and Middle River in April to June and more negative
flows from September to December. Although the pilot EFT rule-set did result in more
positive flows in April, May and June in the Old and Middle River, the reduction in Delta

Final Report
Application of EFT to Complement Water Planning for Multiple Species
183 | P a g e
smelt entrainment was small. This is most likely because reverse flows are already
uncommon in April and May under the reference case scenario, and the improvement the
EFT rule-set generates in June has limited benefit on entrainment as most spawning is
already over (only 16% of spawning occurs in June).
Effects on non-target species
While they were not specifically targeted, some other species also benefited from the
changes caused by the pilot EFT rule-set. Bank swallow nest inundation/sloughing risk
decreased, most likely due to the lower flows in July, which were much higher in the
reference scenario. The benefit to bank swallows is due to holding back water in the
reservoirs (known as “water banking”, see Section 2.9.4) for release later in the water year,
a subsidiary rule we established both to manage Shasta water storage and support
achievement of winter-run Chinook ecological flows.
The improvements for winter-run Chinook and bank swallows generated by the pilot EFT
rule-set reduced suitable spawning habitat (CS1) for fall-run and spring-run Chinook, both of
which decline by about 10% (lower WUA in August to October as flows increase to support
flows for the targeted winter-run Chinook and Delta smelt indicators). With the initial EFT
rule-set, spring-run Chinook experienced a mix of positive and negative effects.
Level of Physical Change among Alternatives
Sacramento River
Flow
Median flows are lower for the pilot study scenario relative to the reference case in July and
August, and higher in September to December, for both Keswick and Hamilton City (Table
3.38).
Median flows were higher historically from water years 1939 to 2004 relative to the
reference case in January to May, September and December, and lower in July for Keswick
(Table 3.38). Median flows were higher historically from water years 1939 to 2004 relative to
the reference case in January to September and December, and lower in November for
Hamilton City.

Chapter 3: Effects Analysis Application of EFT
184 | P a g e
Table 3.38: Flow at Keswick and Hamilton City is shown for the reference case, pilot study
and historical scenarios with percentage differences shown next to absolute
flows. 
Mon
Reference
case (229)
Pilot
(231)
Historical
(118)
Keswick
Jan
4,073
4,122
(1.2%)
6,260
(53.7%)
Feb
4,327
4,398
(1.6%)
7,360
(70.1%)
Mar
4,450
4,453
(0.1%)
5,990
(34.6%)
Apr
5,290
5,350
(1.1%)
6,560
(24.0%)
May
6,604
6,614
(0.1%)
8,950
(35.5%)
Jun
10,674
10,680
(0.1%)
10,200
(-4.4%)
Jul
13,160
11,354
(-13.7%)
11,500
(-12.6%)
Aug
10,604
9,648
(-9.0%)
10,700
(0.9%)
Sep
6,767
7,814
(15.5%)
7,770
(14.8%)
Oct
6,083
7,009
(15.2%)
5,830
(-4.2%)
Nov
5,441
7,020
(29.0%)
5,395
(-0.8%)
Dec
4,298
6,369
(48.2%)
5,990
(39.4%)
Mon
Reference
case (229)
Pilot
(231)
Historical
(118)
Hamilton City
Jan
8,875
8,899
(0.3%)
10,400
(17.2%)
Feb
11,481
11,643
(1.4%)
13,747
(19.7%)
Mar
10,645
10,761
(1.1%)
11,450
(7.6%)
Apr
6,930
6,947
(0.3%)
8,970
(29.4%)
May
6,428
6,439
(0.2%)
9,939
(54.6%)
Jun
8,137
8,094
(-0.5%)
9,295
(14.2%)
Jul
9,386
7,768
(-17.2%)
9,905
(5.5%)
Aug
7,749
6,995
(-9.7%)
9,274
(19.7%)
Sep
6,353
7,325
(15.3%)
7,095
(11.7%)
Oct
5,848
6,956
(19.0%)
5,760
(-1.5%)
Nov
7,149
8,610
(20.4%)
6,390
(-10.6%)
Dec
7,269
8,703
(19.7%)
8,241
(13.4%)
 Comparison of months measured as percentages are based on the simple arithmetic difference in comparison to the
reference case. Green and red shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-20% and
>20%.
Water Temperature
Median water temperature is 5.1% lower in September under the pilot EFT rule-set for
Keswick (Table 3.39). Downstream at Hamilton City, temperatures are similar for the two
scenarios with the maximum temperature difference for the pilot EFT rule-set being 0.7°C
(less than 5%) higher median temperatures in July.
Median water temperatures were higher historically from 1970 to 2001 relative to the
reference case in January, February and December for Keswick (Table 3.39). Historical
temperatures for Hamilton City were unavailable for comparison.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
185 | P a g e
Table 3.39: Temperature (degrees C) at Keswick is shown for the reference case, pilot study
and historical scenarios with percentage differences shown next to absolute
temperatures. 
Month
Reference
case (229)
Pilot (231)
Historical
(118)
Temperature - Keswick
January
8.0
8.0
(0.2%)
9.2
(16.0%)
February
7.7
7.7
(0.1%)
8.5
(10.9%)
March
8.4
8.4
(0.2%)
8.7
(3.9%)
April
9.3
9.3
(0.0%)
9.3
(-0.3%)
May
9.8
9.8
(-0.1%)
9.8
(-0.8%)
June
10.2
10.3
(0.5%)
10.4
(1.4%)
July
10.8
11.1
(2.8%)
11.0
(2.0%)
August
11.4
11.3
(-0.9%)
11.5
(1.2%)
September
12.3
11.7
(-5.1%)
12.0
(-2.3%)
October
12.5
12.0
(-3.9%)
12.3
(-1.9%)
 Comparison of months measured as percentages are
based on the simple arithmetic difference in
comparison to the reference case. Green and red
shadings are used to highlight 3 levels of positive and
negative changes: 5-10%, 10-20% and >20%.
November
11.7
11.7
(-0.8%)
12.0
(2.3%)
December
9.9
9.9
(0.6%)
10.8
(9.1%)
San Joaquin-Sacramento Delta
Flow
At Mallard Island in Suisun Bay, the only difference is higher flows in June and December
for the pilot EFT rule-set relative to the reference case (Table 3.40). For the Old and Middle
River location, which is primarily controlled by the operations of the water export facilities,
flows are more positive in April to June and more negative in September to December for
the pilot EFT rule-set relative to the reference case.
Historical flows for Mallard Island and Old and Middle river were unavailable for
comparison.

Chapter 3: Effects Analysis Application of EFT
186 | P a g e
Table 3.40: Flow values at Mallard Island and Old and Middle River are shown for the
reference case and pilot EFT rule-set with percentage differences shown next to
absolute flows. 
Month
Reference
case (229)
Pilot (231)
Mallard Island
January
16,763
16,468
(-1.8%)
February
20,281
20,234
(-0.2%)
March
29,977
30,440
(1.5%)
April
16,332
16,619
(1.8%)
May
11,968
12,046
(0.6%)
June
8,975
10,732
(19.6%)
July
6,501
6,297
(-3.1%)
August
4,588
4,517
(-1.6%)
September
9,714
9,534
(-1.9%)
October
4,096
4,183
(2.1%)
November
8,400
8,594
(2.3%)
December
8,250
8,978
(8.8%)
Month
Reference
case (229)
Pilot (231)
Old and Middle River
January
-4,208
-4,294
(-2.0%)
February
-3,222
-3,202
(0.6%)
March
-2,000
-2,035
(-1.7%)
April
112
339
(201.6%)
May
-326
137
(142.1%)
June
-3,479
-1,782
(48.8%)
July
-
10,140
-10,107
(0.3%)
August
-9,935
-9,935
(0.0%)
September
-6,949
-7,656
(-10.2%)
October
-6,086
-6,730
(-10.6%)
November
-5,206
-5,617
(-7.9%)
December
-6,385
-7,437
(-16.5%)
 Comparison of months measured as percentages are based on the simple arithmetic difference in
comparison to the reference case. Green and red shadings are used to highlight 3 levels of positive and
negative changes: 5-10%, 10-20% and >20%.
Water Temperature
Median temperatures in the San Joaquin-Sacramento Delta are almost identical between
the two scenarios at both Port Chicago in Suisun Bay and Terminous in the Eastern Delta,
with differences being less than 0.1°C.
Historical temperatures for Port Chicago and Terminous were unavailable for comparison
due to gaps in historical records.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
187 | P a g e
Salinity
Median salinity (measured as EC) is lower in June, November and December for the pilot
EFT rule-set at the Collinsville location (Table 3.41). Downstream at the Pittsburg location in
Suisun Bay, salinity is lower in May, November and December under the pilot EFT rule-set.
Historical salinities for Collinsville were unavailable for comparison. Median salinities were
lower historically from 1997 to 2011 relative to the reference case in January, February,
May and August and higher in March, April, June, July November and December for
Pittsburg (Table 3.41). The reason Pittsburg is more saline in the fall relative to the
reference case is most likely that the reference case includes the Fall X2 action (see
Chapter 3.4.2) which was introduced in 2008 and not considered for most of the historical
years.
Table 3.41: Salinity (measured as EC) values at Collinsville and Port Pittsburg are shown for
the reference case, pilot study and historical scenarios with percentage
differences shown below the absolute EC. 
Month
Reference
case (229)
Pilot (231)
EC - Collinsville
January
1,466
1,477
(0.8%)
February
511
499
(-2.3%)
March
216
216
(0.0%)
April
350
340
(-2.8%)
May
880
858
(-2.5%)
June
2,413
2,223
(-7.9%)
July
4,156
4,205
(1.2%)
August
5,321
5,243
(-1.5%)
September
6,812
6,536
(-4.0%)
October
7,819
7,516
(-3.9%)
November
6,915
5,922
(-14.4%)
December
3,698
3,177
(-14.1%)
Month
Reference
case (229)
Pilot
(231)
Historical
(118)
EC - Pittsburg
January
2,604
2,624
(0.8%)
1,716
(-34.1%)
February
906
927
(2.3%)
779
(-14.0%)
March
261
259
(-0.5%)
478
(83.4%)
April
627
602
(-3.9%)
1,485
(137.0%)
May
1,653
1,563
(-5.4%)
1,527
(-7.6%)
June
3,813
3,643
(-4.5%)
4,450
(16.7%)
July
6,295
6,347
(0.8%)
6,768
(7.5%)
August
7,546
7,487
(-0.8%)
7,083
(-6.1%)
September
9,262
9,010
(-2.7%)
9,127
(-1.5%)
October
10,489
10,084
(-3.9%)
10,233
(-2.4%)
November
9,592
8,472
(-11.7%)
12,081
(25.9%)
December
5,752
5,126
(-10.9%)
9,671
(68.1%)

Chapter 3: Effects Analysis Application of EFT
188 | P a g e
 Comparison of months measured as percentages are based on the simple arithmetic difference
in comparison to the reference case. Green and red shadings are used to highlight 3 levels of
positive and negative changes: 5-10%, 10-20% and >20%.
Ecoregion & Indicator Specific High-level Summary of Relative Suitability
The high level effect roll-ups in this section are tied to the RS methodology described in
Section 2.8.6. Table 3.42 and Table 3.43 show the results of applying this methodology to
the Sacramento River and Delta ecoregions in the pilot study, based on the EFT relative
suitability definition and the change in the percentage of years assigned to a favorable
outcome. A synthesis of these tabular results is presented in Table 3.46.
Sacramento River (SacEFT)
Table 3.42: Ecological flow effects are shown for selected pilot study and historical scenarios
in the Sacramento River ecoregion, using the change in the percentage of
favorable years reported for each indicator (RS method). 
Focal species
Performance indicator
EFT Pilot Rule-Set & Historical Flow
vs. DRR 2011 Reference case (229)
Pilot (231)
Historical
(118)
Upper and Middle Sacramento River Indicators
Fall Chinook
Spawning WUA (CS1)
-14
17
Thermal egg survival (CS3)
4
-7
Redd Dewatering (CS6)
-1
19
Redd Scour (CS5)
0
6
Juvenile Stranding (CS4)
0
26
Rearing WUA (CS2)
-5
6
Late Fall Chinook
Spawning WUA (CS1)
-2
-11
Thermal egg survival (CS3)
0
0
Redd Dewatering (CS6)
1
5
Redd Scour (CS5)
0
13
Juvenile Stranding (CS4)
0
7
Rearing WUA (CS2)
3
-30
Spring Chinook
Spawning WUA (CS1)
-15
3
Thermal egg survival (CS3)
11
-8
Redd Dewatering (CS6)
45
-22
Redd Scour (CS5)
2
2
Juvenile Stranding (CS4)
5
22
Rearing WUA (CS2)
-12
13
Winter Chinook
Spawning WUA (CS1)
35
19
Thermal egg survival (CS3)
2
-1
Redd Dewatering (CS6)
26
22

Final Report
Application of EFT to Complement Water Planning for Multiple Species
189 | P a g e
Focal species
Performance indicator
EFT Pilot Rule-Set & Historical Flow
vs. DRR 2011 Reference case (229)
Pilot (231)
Historical
(118)
Upper and Middle Sacramento River Indicators
Redd Scour (CS5)
0
6
Juvenile Stranding (CS4)
34
-5
Rearing WUA (CS2)
-10
-10
Steelhead
Spawning WUA (CS1)
-1
-14
Thermal egg survival (CS3)
0
0
Redd Dewatering (CS6)
-3
2
Redd Scour (CS5)
3
15
Juvenile Stranding (CS4)
2
30
Rearing WUA (CS2)
-13
6
Bank Swallow
Habitat Potential (BASW1)
0
23
Flow Suitability (BASW2)
0
-33
Green Sturgeon
Egg Temperature Preference (GS1)
-7
13
Fremont Cottonwood
Seedling Initiation (FC1)
–
11
Scour Risk (FC2)
7
19
Large Woody Debris
LWD Recruitment (LWD)
-
17
 The DRR (2011) scenario serves as a comparative reference case. The sign of the difference depends on whether
the indicator improves (more is better) or declines (more is worse) relative to the reference case. Green, yellow
and red shading are used to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% =
Pink, –4% = Yellow, –3% to +4% = White, +5% to +9% = Light Green, ≥10% = Dark Green.
San Joaquin-Sacramento Delta (DeltaEFT)
Table 3.43: Ecological flow effects are shown for selected pilot study and historical scenarios
in the Delta ecoregion, using the change in the percentage of favorable years
reported for each indicator (RS method). 
Focal species
Performance indicator
EFT Pilot Rule-Set & Historical Flow
vs. DRR 2011 Reference case (229)
Pilot
(231)
Historical
(118)
Delta Indicators
Fall Chinook
Yolo Bypass Rearing (CS7)
-6
N/A
Predation Risk (CS9)
0
Thermal Stress (CS10)
0
Late Fall Chinook
Yolo Bypass Rearing (CS7)
-6
Predation Risk (CS9)
0

Chapter 3: Effects Analysis Application of EFT
1 9 0 | P a g e
Focal species
Performance indicator
EFT Pilot Rule-Set & Historical Flow
vs. DRR 2011 Reference case (229)
Pilot
(231)
Historical
(118)
Delta Indicators
Thermal Stress (CS10)
0
Spring Chinook
Yolo Bypass Rearing (CS7)
0
Predation Risk (CS9)
0
Thermal Stress (CS10)
0
Winter Chinook
Yolo Bypass Rearing (CS7)
-6
Predation Risk (CS9)
7
Thermal Stress (CS10)
0
Steelhead
Yolo Bypass Rearing (CS7)
-7
Predation Risk (CS9)
0
Thermal Stress (CS10)
0
Splittail
Spawning Habitat (SS1)
0
-2
Delta Smelt
Spawning Success (DS1)
0
N/A
Habitat Quality (DS2)
0
Entrainment Risk (DS4)
6
-9
Longfin Smelt
Abundance Index (LS1)
-
N/A
Invasive Deterrence
Egeria suppression (ID1)
6
Corbula suppression (ID2)
0
Corbicula suppression (ID3)
-
Tidal Wetlands
Brackish area (TW1)
NULL
Freshwater area (TW2)
NULL
 The DRR (2011) scenario serves as a comparative reference case. The sign of the difference depends on whether the
indicator improves (more is better) or declines (more is worse) relative to the reference case. Green, yello w and red shading
are used to highlight 6 levels of positive and negative changes: ≤ –10% = Red, –5% to –10% = Pink, –4% = Yellow, –3% to +4%
= White, +5% to +9% = Light Green, ≥10% = Dark Green. Cells marked ‘N/A’ are missing either because a scenario was not
simulated, or because the results were removed following the screening process described in Section 3.4.2
Ecoregion & Indicator Specific Effect Size Results
Pilot study effect size results are tied to the ES methodology described in Section 2.8.6.
Table 3.44 and Table 3.45 show the results of this methodology applied to the Sacramento
River and Delta ecoregions, respectively. The following sections summarize BDCP effects
in which the median effect differs by more than 5% from a reference case comparative
response. A synthesis of these effects is presented in Table 3.34.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 9 1 | P a g e
Sacramento River (SacEFT)
Table 3.44: Pilot study, historical and reference case flow effect sizes are shown for using the
median difference Effect Size (ES) method (preserving the native units of each
indicator). The DRR 2011 scenario serves as a reference case, with percentage
differences shown below absolute median effects. 
Focal species
Performance indicator
Reference
case (229)
Pilot
(231)
Historical
(118)
Upper and Middle Sacramento River Indicators
Fall Chinook
Suitable spawning habitat (000s ft2)
3,681
3,356
(-8.8%)
4,022
(9.2%)
Thermal egg-to-fry survival (proportion)
0.999
1.000
(0.1%)
0.994
(-0.5%)
Redd dewatering (proportion)
0.049
0.064
(-1.6%)
0.028
(2.0%)
Redd scour risk (scour days)
1
1
0
Juvenile stranding index
0.182
0.180
(0.2%)
0.136
(4.6%)
Suitable rearing habitat (000s ft2)
64,205
63,605
(-0.9%)
58,498
(-8.9%)
Late Fall Chinook
Suitable spawning habitat (000s ft2)
1,449
1,403
(-3.2%)
1,250
(-13.7%)
Thermal egg-to-fry survival (proportion)
1.000
1.000
(0.0%)
1.000
(0.0%)
Redd dewatering (proportion)
0.045
0.044
(0.0%)
0.039
(0.6%)
Redd scour risk (scour days)
0
0
0
Juvenile stranding index
0.082
0.083
(-0.1%)
0.067
(1.5%)
Suitable rearing habitat (000s ft2)
52,598
53,362
(1.5%)
49,549
(-5.8%)
Spring Chinook
Suitable spawning habitat (000s ft2)
988
868
(-12.1%)
945
(-4.4%)
Thermal egg-to-fry survival (proportion)
0.998
1.000
(0.2%)
0.989
(-0.8%)
Redd dewatering (proportion)
0.045
0.017
(2.8%)
0.070
(-2.5%)
Redd scour risk (scour days)
0
0
0
Juvenile stranding index
0.213
0.185
(2.8%)
0.179
(3.4%)
Suitable rearing habitat (000s ft2)
65,224
61,630
(-5.5%)
70,715
(8.4%)
Winter Chinook
Suitable spawning habitat (000s ft2)
1,440
1,493
(3.7%)
1,462
(1.5%)

Chapter 3: Effects Analysis Application of EFT
1 9 2 | P a g e
Thermal egg-to-fry survival (proportion)
0.999
1.000
(0.0%)
0.999
(0.0%)
Redd dewatering (proportion)
0.016
0.012
(0.3%)
0.013
(0.3%)
Redd scour risk (scour days)
0
0
0
Juvenile stranding index
0.083
0.045
(3.8%)
0.080
(0.3%)
Suitable rearing habitat (000s ft2)
37,222
37,075
(-0.4%)
37,223
(0.0%)
Steelhead
Suitable spawning habitat (000s ft2)
76
75
(-0.8%)
70
(-8.4%)
Thermal egg-to-fry survival (proportion)
1.000
1.000
(0.0%)
1.000
(0.0%)
Redd dewatering (proportion)
0.045
0.050
(-0.5%)
0.039
(0.6%)
Redd scour risk (scour days)
0
0
0
Juvenile stranding index
0.432
0.404
(2.8%)
0.399
(3.3%)
Suitable rearing habitat (000s ft2)
134,566
131,309
(-2.4%)
132,450
(-1.6%)
Bank Swallow
Suitable potential habitat (length, m)
Nest inundation/sloughing risk
12,870
10,890
(15.4%)
10,284
(20.1%)
Green Sturgeon
Egg-to-larval survival (proportion)
0.987
0.977
(-1.0%)
1.000
(1.3%)
Fremont Cottonwood
Cottonwood initiation index
21
21
(0.0%)
30.5
(45.2%)
Risk scour after initiation
Large Woody Debris
Old vegetation recruited to river (ha)
0.30
0.30
(0.0%)
 Comparisons of indicators measured as percentages or proportions are based on the simple arithmetic
difference in comparison to the reference case; all other indicators are based on the proportional difference in
comparison to the reference case. The sign of the difference depends on whether the indicator improves
(more is better) or declines (more is worse) relative to the reference case. Green and red shading s are used to
highlight 3 levels of positive and negative changes: 5-10%, 10-20% and >20%.
Salmonids
Median suitable spawning habitat (CS1) declines by 8.8% relative to the DRR 2011
reference case for fall-run Chinook (Figure 3.36). Both the reference case and pilot EFT
rule-set are lower than historical spawning habitat, which is about 9% above the reference
case.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 9 3 | P a g e
Figure 3.36: Fall-run Chinook spawning habitat (CS1) area for historical and preferred
scenarios relative to the DRR 2011 reference case scenario.
Late fall-run Chinook indicators are not meaningfully different from one another for the DRR
reference case and pilot EFT rule-sets. However, compared to the historical scenario, both
DRR scenarios show declines of over 10% for suitable spawning habitat (CS1) and around
5% for suitable rearing habitat (CS2) (Figure 3.37).

Chapter 3: Effects Analysis Application of EFT
1 9 4 | P a g e
Figure 3.37: Late fall-run Chinook suitable spawning habitat (CS1, left panel) and suitable
rearing habitat (CS2, right panel) for both DRR simulations relative to the
historical scenario.
Median suitable spawning habitat (CS1) declines by 12.1% relative to the DRR 2011
reference case and historical scenario for spring-run Chinook (Figure 3.38). Median juvenile
rearing habitat (CS2) declines by 5% relative to the DRR reference case, and both DRR
scenarios provide about 5% less rearing habitat than the historical scenario.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 9 5 | P a g e
Figure 3.38: Spring-run Chinook spawning habitat (CS1, left panel) and juvenile rearing
habitat (CS2, right panel) for both DRR simulations relative to the historical
scenario.
Steelhead median suitable spawning habitat (CS1) is improved for both DRR scenarios
relative to the historic scenario (Figure 3.39), but the two DRR scenarios are not
meaningfully different from one another.

Chapter 3: Effects Analysis Application of EFT
1 9 6 | P a g e
Figure 3.39: Suitable spawning habitat for steelhead (CS1) for both DRR simulations relative
to the historical scenario.
Green Sturgeon
Green sturgeon egg survival (GS1) is not meaningfully affected by the pilot EFT rule-set,
improving very slightly by 1% relative to the DRR 2011 reference case (Table 3.44). The
reference case is also not meaningfully different from the historical scenario.
Bank swallow
The median suitable potential habitat (BASW1) for bank swallows is not simulated for the
pilot study.
The median nest inundation/sloughing risk (BASW2) for bank swallows is expected to
decrease by 15.4% under the pilot EFT rule-set (Figure 3.40, left panel). The median nest
inundation/sloughing risk was historically 20.1% lower than the reference case. The change
under the pilot EFT rule-set is expected to be meaningful since most individual water year
differences are negative (Figure 3.40, right panel). Historical individual water years cannot
be compared to reference case.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 9 7 | P a g e
Figure 3.40: Median nest inundation/sloughing risk (BASW2) for bank swallow under the pilot
EFT rule-set relative to reference case and historical scenarios (left panel),
showing individual year differences relative to base case scenario (right panel).
Fremont Cottonwood
As shown in Table 3.44, Fremont cottonwood initiation did not change between the pilot
EFT rule-set and the reference case. However, cottonwood initiation is 45% higher under
historical conditions compared to the reference case (Figure 3.41). While numerous factors
(operations, climate and water demand) have changed between 1943 and 2004, the
historical comparison illustrates the degree of cumulative change locked into the 2011 DRR
reference case and the expected direction of the effect of these changes on Fremont
cottonwood initiation (Figure 3.41).

Chapter 3: Effects Analysis Application of EFT
1 9 8 | P a g e
Figure 3.41: Median Fremont cottonwood initiation success (FC1) for the pilot EFT rule-set
relative to the reference case and the historical (1943-2004) scenario.
Large woody debris recruitment
Not simulated for the pilot study.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
1 9 9 | P a g e
San Joaquin-Sacramento Delta (DeltaEFT)
Table 3.45: Pilot study and historical flow effect sizes are shown for the median difference
Effect Size (ES) method (preserving the native units of each indicator). The DRR
2011 scenario serves as a comparative reference case, with percentage
differences shown below absolute median effects. 
Focal species
Performance indicator
Reference
case (229)
Pilot
(231)
Historical
(118)
Bay Delta Indicators
Fall Chinook
Smolt weight gain (%)
20.2
18.6
(-1.6%)
N/A
Smolt predation risk (passage days)
15.2
15.3
(-1.0%)
N/A
Smolt temperature stress (degree day)
105.1
106.8
(-1.6%)
N/A
Late Fall Chinook
Smolt weight gain (%)
29.1
28.8
(-0.3%)
N/A
Smolt predation risk (passage days)
15.5
15.3
(1.4%)
N/A
Smolt temperature stress (degree day)
57.3
56.6
(1.2%)
N/A
Spring Chinook
Smolt weight gain (%)
23.6
22.4
(-1.2%)
N/A
Smolt predation risk (passage days)
15.3
15.5
(-1.3%)
N/A
Smolt temperature stress (degree day)
84.3
87.2
(-3.4%)
N/A
Winter Chinook
Smolt weight gain (%)
29.7
29.6
(-0.1%)
N/A
Smolt predation risk (passage days)
14.4
14.3
(0.9%)
N/A
Smolt temperature stress (degree day)
40.3
40.0
(0.8%)
N/A
Steelhead
Smolt weight gain (%)
19.3
17.6
(-1.7%)
N/A
Smolt predation risk (passage days)
15.5
15.8
(-2.2%)
N/A
Smolt temperature stress (degree day)
109.4
112.2
(-2.5%)
N/A
Splittail
Proportion max spawning habitat
0.000
0.000
0.000
Delta Smelt
Spawning success (optimal days)
34.3
34.1
(-0.5%)
N/A

Chapter 3: Effects Analysis Application of EFT
2 0 0 | P a g e
Habitat suitability index
3,653
3,724
(1.9%)
3,260
(-10.7%)
Larval & juvenile entrainment proportion
0.053
0.051
(0.2%)
0.095
(-4.1%)
Longfin Smelt
Abundance index
N/A
N/A
N/A
Invasive Deterrence
Brazilian waterweed suppression
8.8
8.7
(-1.5%)
N/A
Overbite clam larval suppression
2.7
2.6
(3.8%)
N/A
Asiatic clam larval suppression
8.8
8.7
(-1.5%)
N/A
Tidal Wetlands
Brackish wetland area (ha)
N/A
N/A
N/A
Freshwater wetland area (ha)
N/A
N/A
N/A
 Comparisons of indicators measured as percentages or proportions are based on the simple arithmetic
difference in comparison to the reference case; all other indicators are based on the proportional
difference in comparison to the reference case. The sign of the difference depends on whether the
indicator improves (more is better) or declines (more is worse) relative to the reference case. Green and
red shadings are used to highlight 3 levels of positive and negative changes: 5-10%, 10-20% and >20%.
Cells marked ‘N/A’ are missing either because a scenario was not simulated, or because the results were
removed following the screening process described in Section 3.4.2
Salmonids
Under the pilot EFT rule-set there are no meaningful improvements or declines to any
salmonid run-type in the Delta ecoregion. Comparisons with historic data are not possible
due to the short time series of data.
Splittail
The median proportion of maximum spawning habitat for splittail (SS1) is expected to
remain constant under all three scenarios.
Delta Smelt performance indicators
The median spawning success for Delta smelt (DS1) is expected to remain relatively
constant between project alternatives at approximately 34 days of optimal spawning
conditions annually.
The median habitat suitability index for Delta smelt (DS2) is expected to remain relatively
constant between project alternatives at approximately 3,700. The median historical habitat
suitability index was 10.7% lower than the reference case (Figure 3.42). This is most likely
due to historically higher salinities in Suisun Bay relative to the reference case (Chapter 3.2)
caused by the inclusion of Fall X2 action under the reference case, which was only in effect

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 0 1 | P a g e
for a few of the historical years (Chapter 3.4.2). The change is expected to be significant
due to the decrease in both median and variation.
Figure 3.42: Median historical habitat suitability index (DS2) relative to reference and preferred
scenarios.
Longfin Smelt
Not simulated for the pilot study.
Invasive deterrence
The median Brazilian waterweed suppression (ID1) is expected to remain relatively
constant between project alternatives with an estimated maximum three month average
salinity from May to October of approximately 8.8‰ for the ‘Chipps Island to Oakley’ region.
The median overbite clam larval suppression (ID2) is expected to remain relatively constant
between project alternatives with an estimated minimum three month average salinity from
December to April of approximately 2.7‰.

Chapter 3: Effects Analysis Application of EFT
2 0 2 | P a g e
The median Asiatic clam larval suppression (ID3) is expected to remain relatively constant
between project alternatives with an estimated maximum three month average salinity from
May to October of approximately 8‰ for the ‘Chipps Island to Oakley’ region.
Tidal wetlands
Not simulated for the pilot study.
Summary of Species Net Effects
Table 3.46 provides differing views on the benefits and costs of the pilot EFT rule-set (and
historical conditions) compared to the 2011 DRR reference case. The pilot EFT rule-set is
expected to substantively improve conditions for winter-run Chinook and bank swallows in
the Sacramento River. Delta smelt entrainment was slightly improved using the pilot EFT
rule-set but the absolute effect was less than 5% (because reverse flows are already
uncommon in April and May under the reference case scenario). However, the pilot EFT
rule-set leads to deterioration in performance for fall-run Chinook and steelhead in the
Sacramento River relative to the reference case (Table 3.47). Conditions for all other
species are expected to remain largely unchanged.
The EFT rule-set in particular targeted improving suitable spawning habitat for winter-run
Chinook (CS1). When evaluated with the RS method, this indicator showed marked
improvement: a 35% increase in the number of favorable years, while the absolute all-year
median increase in suitable spawning area was just under 5%. Further, benefits generated
by the EFT rule-set for winter-run Chinook came at the expense of lower suitable spawning
habitat (CS1) for fall-run and spring-run Chinook, both of which decline by about 10%.
Unlike fall-run Chinook, which are maintained by large-scale hatchery supplementation, and
spring-run Chinook, which make extensive use of tributaries and do not rely on the
mainstem Sacramento River for spawning, winter-run Chinook make extensive use of the
mainstem Sacramento River upstream of Red Bluff.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 0 3 | P a g e
Table 3.46: Summary of pilot study and historical effects for Sacramento River and Delta
ecoregion, as measured by the RS (left) and ES (right) methods. 
RS Methodology
Sacramento River Ecoregion
Reference case:
DRR baseline
Pilot EFT
rule-set
Historical
+
–
+
–
Fall
1
1,4,6
Late Fall
5
1,2
Spring
3,6
1,2
2,4
6
Winter
1,4,6
1,6
2
Steelhead
2
4,5
1
Bank swallow
Green
Sturgeon
Cottonwood
Woody Debris
Delta Ecoregion
Minor improvement (reduction) in Delta
Smelt entrainment, otherwise, no
meaningful change
ES Methodology
Sacramento River Ecoregion
Reference case:
DRR baseline
Pilot EFT
rule-set
Historical
+
–
+
–
Fall
1
1
2
Late Fall
1,2
Spring
1,2
2
Winter
Steelhead
2
1
Bank swallow
2
1,2
Green
Sturgeon
Cottonwood
1
Woody Debris
N/A
N/A
Delta Ecoregion
Minor improvement (reduction) in Delta
Smelt entrainment, otherwise, no
meaningful change
 Numbers indicate the internal PI-number of the indicator with a meaningful (>10%) positive or negative change for each
comparison; shaded green in ‘+’ columns and red in ‘ –‘ columns. Key to salmonid indicators: 1 = suitable spawning habitat, 2
= suitable rearing habitat, 3 = thermal egg-to-fry survival, 4 = juvenile stranding index, 5 = redd scour, 6 = redd dewatering
risk. Cells marked ‘N/A’ are missing either because a scenario was not simulated, or because the results were removed
following the screening process described in Section 3.4.2.
Reduction of larval and juvenile entrainment of Delta smelt was also targeted for
improvement by the EFT ecological flow rules. Although the pilot EFT rule-set does result in
more positive flows in April, May and June (Table 3.40), and results in an improvement in all
water years (Figure 3.43 and Figure 3.44), the median reduction of entrainment is expected
to be small. This is most likely because reverse flows are already uncommon in April and
May under the reference case scenario, and the meaningful improvement in June has little
impact on entrainment as most spawning is already over (only 16% of spawning occurs in
June).

Chapter 3: Effects Analysis Application of EFT
2 0 4 | P a g e
Figure 3.43: Median Delta smelt entrainment risk (DS4) relative to the DRR 2011 reference
case scenario (left panel), showing individual year difference relative to baseline
scenario (right panel).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 0 5 | P a g e
Figure 3.44: Example DS4 results for the same sample year before/after EFT rule-set. The
graphs show OMR reverse flows and Delta smelt entrainment were in some
years improved under the pilot EFT rule-set (absolute median effect was less
than 5%).
Step 5
Results for “C: the species indicators we actually targeted?” [detail level]
Pilot EFT
Baseline
DS4 example
•Positive OMR flow in
June in Pilot EFT flows
scenario
•Entrainment reduced
from 5.3% to 3.9%
•June weighting is only
16%

Chapter 3: Effects Analysis Application of EFT
2 0 6 | P a g e
Table 3.47: Overall weight of evidence and assessment of net effects by species,
Sacramento River Ecoregion and Delta Ecoregion. Refer to legend below the
table.
Scenario
Relative to
DRR 2011
Sacramento River Ecoregion
Pilot Study
Historical
+
–
+
–
Fall
5
3-RS
Late Fall
5
Spring
+/–
+/–
Winter
3-RS
+/–
Steelhead
3-RS
+/–
Bank Swallow
3-ES
Green Sturgeon
Cottonwood
Woody Debris
Delta Ecoregion
No meaningful change
N/A
Neither the RS nor ES summary method generates a potential change that passes our ±10% and
±5% thresholds. No meaningful effect.
+/-
Mixed effects -- indicators for same species show benefits and penalties (i.e.,
Chinook/steelhead), but the net effect is difficult to determine.
1-RS
RS summary method shows a potential effect (passes ±10% threshold). However, the results are
highly variable.
1-ES
ES summary method shows a potential effect (passes ±5% threshold). However, the results are
highly variable.
2-RS
RS summary method shows a potential effect of ±10% change or more in favorable years, with
clear signal to noise (less variability), yet the ES summary view shows the inverse effect
(potentially contradictory evidence).
2-ES
ES summary method shows a potential effect of ±5% change in absolute median effect size, with
clear signal to noise (less variability), yet the RS summary view shows the inverse effect
(potentially contradictory evidence).
3-RS
RS summary method shows a potential effect of ±10% change or more in favorable years, with
clear signal to noise (less variability), and the ES summary view does not meet threshold (no
contradictory evidence).
3-ES
ES summary method shows a potential effect of ±5% change in absolute median effect size, with
clear signal to noise (less variability), and the RS summary view does not meet threshold (no
contradictory evidence).
4
Both summary views agree on the direction of the potential effect, and both pass the threshold
for a potentially meaningful effect. However, both show a highly variable spread in results.
5
Both summary views agree on the direction of the potential effect, and both pass the threshold
for a potentially meaningful effect with clear signal to noise (less variability).
6
Either category "3","4" or "5" + fundamental link to scenario description.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 0 7 | P a g e
3.4.5 Caveats & Limitations
This was only our first pilot effort and considered merely two species: Delta smelt and
winter-run Chinook. Our initial results highlight the opportunity for additional improvement by
further refining the implementation of our EFT rule-sets and including additional species.
Future work will consider additional species, and emphasize dynamic, state-dependent
rules that do not attempt the same static optimization for every objective.
Other general caveats and limitations are described in Section 3.3.4.

Chapter 4: Where to From Here?
2 0 8 | P a g e
4 Where to From Here?
With the aid of over 70 scientists and managers since 2004, our Project team was amongst
the first to quantify how multiple components of the Sacramento River and San Joaquin-
Sacramento Delta flow regimes can be modified to promote key ecosystem functions in
support of smarter, more eco-friendly flow management (TNC et al. 2008). Unlike
approaches which focus on a small number of simplified and static ecosystem needs, EFT
describes 25 site specific, functional flow algorithms (conceptual models) for 13
representative species and key habitats across the Sacramento River and Delta
ecoregions. We include life-history stage indicators for both listed and non-listed riparian
and aquatic species and habitats. EFT's life-history stage conceptual models are then
coupled with multiple physical models of flow, water temperature, salinity, stage, channel
migration, and sediment transport to enable ecological effects analyses. From the
beginning, a high priority of the EFT team has been to select representative species and
ecological indicators that capture the essence of existing scientific understanding and
ecosystem range. We have aimed for a multi-species, multi-indicator approach while being
careful to avoid pitfalls caused by too broad a sphere of concern or too much detail on any
one species.
This Chapter does not attempt to survey or "pick the best solution" for reconciling the vexing
challenge of managing the Sacramento River and Delta for people and environmental
values. We instead isolate the biggest lessons learned over more than 10 years of work,
and plot a course for the next phase of coupled, multi-species, ecological flow decision
support for the Sacramento River and Delta.
Our recommended ecological flow action agenda follows.
4.1 A New Paradigm: Flexible Ecosystem Priorities
The enduring challenge confronting the management of water in the Sacramento-San
Joaquin Delta is deciding how to balance and reconcile trade-offs amongst inversely
correlated ecosystem values and water supply needs. Indeed the Sacramento San-Joaquin
Delta is universally regarded to be in “crisis” because of an inability to find "balance" in the
trade-offs among competing objectives and resource demands21.
The detailed applications of EFT presented in Chapter 3 crystalize the fact that it is
impossible to achieve all ecosystem objectives –– let alone the co-equal goals of balancing
human and ecosystem needs –– each and every year. There are plain, irreconcilable and
ceaseless trade-offs that must be tracked and confronted, with winners and losers in
21 Delta Science Council, 2013 Year in Review.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 0 9 | P a g e
different years, depending on hydrologic conditions and priorities. These trade-offs do not
occur because of a failure to create clever enough models that magically find the optimal
solution. Rather, they exist because a single, unchanging optimal solution does not exist.
For example, restored floodplains may require higher flows at some locations and times to
seasonally activate, creating conditions which are not ideal for mainstem Sacramento River
spawning flows. Alternatively, non-natural flow patterns might sometimes be useful in
suppressing invasive species but create conditions which are not favorable for other
indicator species.
The paradigm shift which we propose requires seeing balance as a condition which does
not involve the same species or objectives losing (or winning) unnecessarily often. The EFT
pilot investigation described in Section 3.4 illustrates that the operation of the California
water system can be changed to make timing of releases from Shasta Dam more beneficial
to selected species without adverse consequences on storage and water exports. However,
it also highlights the inherent trade-offs between species and life-stages, and how applying
the same rule-set for a given water year type every year actually constrains options and
contributes to the inability to adequately balance ecosystem trade-offs.
For its part, BDCP did not consider the full range of reservoir operational modifications
possible. Instead, it focused on a very narrow range of optimizations related to Delta
exports rather than a more complete, more flexible analysis of system-wide reservoir re-
operation. In particular, it placed constraints on Sacramento River reservoir operations
associated with existing regulations on water temperature and downstream flow
requirements. The objective for BDCP was to fix these established regulations, and
evaluate how the new conveyance facilities could be used to maximize Delta exports within
these constraints. This was the primary reason that the differences amongst BDCP
alternatives were not large (see Section 3.3.3).
Using daily resolution modeling tools, our approach emphasizes a bottom-up assessment of
opportunities to achieve ecosystem flow needs. This includes relaxing traditional constraints
(e.g., precise timing of exports) as part of the initial search, while still meeting the primary
flood safety and water supply requirements related to carry-over storage and export
volumes. This approach would create a far better opportunity to discover sets of beneficial
multi-objective outcomes.
There is a pressing need to develop greater awareness of the value of flexibility to manage
ecosystem trade-offs over time. California’s native fish and riparian species have adapted to
the State's widely variable climate. These evolutionary adaptations have helped species
persist during extended droughts and other forms of extreme water fluctuation. As examples
of natural flexibility, there are four run-types of Chinook salmon, each of which is adapted to
a different season and habitat that overlap in both. Adults can return from the ocean
anywhere from two to six years of age. Juvenile Chinook may choose to hold in cold water
refuge habitat or migrate immediately to the ocean. While the ability to exploit their adaptive
range is now limited by dams that block cold-water refuge habitats, simplified channelized

Chapter 4: Where to From Here?
2 1 0 | P a g e
disconnected habitats, hatcheries that are simplifying life-history variations, and a Delta full
of alien predators –– some residual adaptive capacity nevertheless remains.
4.1.1 Smart, State-dependent Priorities
The adaptive range possessed by many species allows for a reasoned level of flexibility
when approaching ecosystem flow management. This feature of species life-history
adaptation can be exploited to develop 'state-dependent' priorities. Instead of one-size-fits-
all solution, establishing state-dependent priorities require tracking the recent history of
water availability and related habitat conditions experienced by priority species and then
dynamically adjusting priorities based on this history (Figure 4.1). For example, favorable
Fremont cottonwood initiation does not need to happen every year to sustain a healthy
population: a decadal frequency is perhaps sufficient. Correlated with this statement, the
natural hydrologic conditions necessary to support a strong cohort of initiating Fremont
cottonwood are also infrequent. It therefore makes sense for water operations to take
advantage of water years that are conducive to establishing cottonwood seedlings at the
sufficient frequency of recurrence. This will mean that other ecological objectives, such as
objectives for salmon or smelt will need to be reduced or even turned off when the history of
conditions develop to favor another heretofore neglected species. In contrast, three
consecutive years of poor spawning or rearing conditions for salmonids should logically
prompt a substantial increase in efforts to intervene to improve conditions before there is
risk of losing an entire cohort.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 1 1 | P a g e
Existing paradigm
New paradigm
Figure 4.1: Hypothetical example of state-dependent priorities (for illustrative purposes only,
not a realistic prescription). The existing paradigm attempts to optimize releases
for all species in all years (with rules based on water-year type). Under state-
dependent priorities, flows are optimized for different species according to the
recurrence interval necessary to support healthy population conditions (e.g., in
this example, every 10 years for Fremont cottonwoods, for Chinook and Delta
smelt in 3 out of 4 years and for bank swallows every 4 years). The choice of
priority would also depend on the water availability conditions in any given year.
4.1.2 Recognize Multiple, Equally Acceptable Solutions Exist
Further advancing our pilot ecological flow study (Section 3.4), evaluating "optimal" water
operations for the full suite of EFT species indicators, including introduction of state-
dependent priorities, will require a different approach. In our pilot study, target flows were
described as a range of flows beneficial to a species and life-stage, e.g., winter-run Chinook
spawning habitat performance was found to be good if flows were between 5 and 12 kcfs in
May and June (Appendix I). In the pilot study, flow optimization was a manual process
where native CALSIM WRESL files were edited to achieve EFT target flows (Section 2.9.1;
Appendix I). In this way, we did not identify optimal single-objective solutions. This would

Chapter 4: Where to From Here?
2 1 2 | P a g e
require evaluating the effect of alternative flows on the raw calculated values of each
species/habitat performance indicator (raw effect size). Further, finding optima also
generally requires modeling hundreds of simulations to find convergence (our pilot study
performed manual what-if simulations).
When considering multiple and often inversely correlated objectives, there is no single
optimal solution (set of rules). Instead, there exists a set of candidate solutions that are all
considered equally desirable (Figure 4.2, panel c). Identifying the full set of equally
desirable solutions allows managers to select among alternatives after seeing the nature of
the relationship amongst trade-offs. Lastly, the existing type of single-objective analysis also
has the disadvantage of forcing us to decide which objective is more important a priori.
(a) Brute force
(b) Single objective
(c) Multi-objective
Figure 4.2: Hypothetical trade-off example for two different species objectives. The brute
force approach (a) involves a search that generates many sub-optimal solutions.
The single objective approach (the current paradigm) identifies only one
candidate solution, but doesn’t allow managers and scientists to evaluate the full
range of trade-offs (b). The multi-objective approach (c) allows managers to
select the most appropriate trade-off from the full set of equally suitable solutions.
In our intial pilot study (Section 3.4), flow optimization was a manual process where native
CALSIM WRESL files were edited based on the expected response of EFT performance
indicators to flow patterns (Figure 4.3, upper panel). While many elements (including EFT)
will continue to be used, implementing this new paradigm will require a very different
modeling system capable of running hundreds of simulations in parallel. We recommend an
automated implementation that uses a batch run coordinator with a multiple-objective
optimization algorithm (Figure 4.3, lower panel).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 1 3 | P a g e
Figure 4.3: Recommended multiple objective, state-dependent ecological flow optimization
system (lower panel) vs. approach used in pilot study (upper panel). In the pilot
study, the flow optimization was largely a manual process (upper panel) where an
operator would edit native CALSIM WRESL files. In the recommended system
(lower panel) the modeling suite would be automated by a batch run coordinator
so hundreds of scenarios can be simulated. In addition to the batch run
coordinator, a key feature would be a new multi-objective analysis engine with
implementation of state-dependent priorities. The optimization engine would
communicate with the batch run coordinator and store histories of trial flow
releases and related multi-species responses.

Chapter 4: Where to From Here?
2 1 4 | P a g e
The batch run coordinator would send monthly releases from Shasta Dam to CALSIM using
a lookup table that is accessed from CALSIM using logic that would be implemented so that
CALSIM does not need to be recompiled. The batch run coordinator would then trigger the
full modeling suite (CALSIM, USRDOM, SRWQM, DSM2 and EFT) and keep track of
indicator responses (in raw units) to the alternative monthly releases in a given water year.
This will allow each model in the modeling suite to be run individually and potentially in
parallel. As new results become available from the coordinator, the optimization engine
would use them to create the next generation of improved scenarios (scoring and tracking
results for all performance indicators).
The new state-dependent priority component would be based on how frequently a species
requires favorable conditions in order to sustain a healthy population. For example, Fremont
cottonwood initiation does not need to happen every year to sustain a healthy population
(once a decade is generally considered sufficient). Under the existing paradigm, a one-size-
fits-all approach to water releases is assumed, which attempts to achieve the same targets
based on the water year type but not on the recent history experienced by different species.
Our recommended smart, state-dependent paradigm will prioritize releases based on the
time since a species has last experienced favorable conditions relative to the recurrence
necessary to maintain a healthy population. The multi-objective optimization engine will
penalize alternatives that fail to meet the target return frequency of beneficial flows for a
given species and performance indicator. Additionally, solutions will also be influenced by
the state of natural inflows.
4.2 Other Promising Avenues
4.2.1 Sustained Refinement & Application of EFT
The Ecological Flows Tool has successfully coupled models of operations and
hydrodynamics with multi-species ecosystem and geomorphic response models across a
geographic area which spans the Sacramento River and Delta. It provides a very successful
and rare example of the synthesis and integration of a vast amount of scientific knowledge
across multiple disciplines. Given the advances that have been made since 2004,
leveraging the investment in EFT through continued development and application will be far
more cost-effective than duplication or re-invention.
The approach adopted in the development of EFT is precisely the kind envisioned by the
CALFED Science Advisory Panel in 2008, and subsequently by the Delta Science Council
and a variety of other cross-disciplinary researchers (e.g., PPIC, UC Davis). More than
ever, there is value in coupled modeling tools that promote experts and resource managers
coming together to explore, develop, test and improve solutions to California's water
management problems.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 1 5 | P a g e
The magnitude of Sacramento San-Joaquin Delta challenges, the scientific uncertainties,
and the time required to learn and iterate means developing ecological flow
recommendations will take many years and undergo periods of surprise and change.
Hence, the tools used to harness and synthesize this knowledge must also be continuously
updated and maintained.
Scientists (and modelers) are expected to observe, hypothesize (model), predict, check
evidence, change, revise hypotheses (models), and repeat. As with any quantitative
decision support tool, the knowledge it contains comes from a particular point in time and
must be adaptively updated. It is imperative to continuously learn and periodically adapt
EFT so that it continues to track the always evolving state of science. This will require
ongoing funding investments.
In EFT, we intentionally use a functional flow approach that emphasizes specific cause-
effect linkages. This formulation of EFT's indicators is open to testing and adaptation
through time as experiments are completed and new data and understanding emerge. A
logical place to start reviewing hypotheses and data used in EFT would include the advice
and candidate suggestions received from invited experts during a technical review
workshop of DeltaEFT held in January 2013.
Isolate & Branch Individual Submodels
Some stakeholders have expressed an interest in being able to run individual SacEFT
components for smaller, specific, targeted analyses, e.g., applying the SacEFT submodels
of soil erosion, bank swallow, and large woody debris recruitment. With a relatively small
amount of effort, these submodels could be designed to run in a standalone form, without
any requirement to install SacEFT itself, while still remaining fully integrated within EFT.
This would support opportunities for light-weight screening analyses prior to evaluation of
multi-species effects.
Managed Hosting & Maintenance
Beyond making an install pack available, most software systems require dedicated ongoing
managed hosting, updating, and support for tool users. Consideration should be given to a
long-term plan for management and updating of the EFT software. Without a basic
commitment to long-term maintenance, software tools eventually dwindle into
obsolescence.
Training
Securing funding investments to create and deliver training courses on the appropriate use
and application of EFT in detailed effects analyses and related investigations should be
considered.

Chapter 4: Where to From Here?
2 1 6 | P a g e
4.2.2 Even More Attention to Climate Change Mitigation
Results of EFT BDCP analyses for the anticipated late long term (LLT) (2060) period
climate conditions (see Section 3.3.3) highlight the need for more focus on efforts to
mitigate for climate change itself, not just whether certain operations are better/worse
relative to a worsening future baseline. The climate change signal and effects in the BDCP
study generally dwarfed the operational alternatives considered.
Studies that only use baselines based on future (deteriorated) conditions and constraints
shift attention away from cumulative total change in ecological conditions. Such
administrative decisions may mask what can often be striking differences between historic
operations and those proposed. Use of a historical reference case was recommended by
the Delta Science Panel in its review of BDCP (DSP 2014), even though the approach is
unwelcome by some who feel that use of a historical record is a flawed reference given that
it includes numerous shifts in operational standards and climate. The counterpoint to this
argument is that the use of a historical reference case enables study of the level of
cumulative change, regardless of whether it is produced by climate change, changes in
operations and conveyance, or increasing human water demand.
4.2.3 Don't Just Plan: Implement Real-time Ecological Modeling
While both are important, there is a disproportionate amount of effort devoted to water
planning models in California. More effort should be invested in real-time, in-season
operational tools that incorporate multiple ecological flow needs. Planning models like
CALSIM, DSM2 and related planning models do not and cannot capture behavioral
uncertainty, nor can they represent the true operational flexibility that exists. For example,
Mount et al. (2013) were concerned that some of the modeled flow operations for certain
BDCP scenarios would not actually occur in real operations. Indeed the degree to which
actual operations follow simulated operations can vary substantially (especially as the
resolution of most of the planning models is monthly).
More fundamentally, in-season modeling tools that are used by operators day to day have a
greater impact on actual, on-the-ground decisions22. If real-time operational tools do not
adequately build-in ecological flow guidelines and targets derived from related modeling
(including results from EFT and other studies) then planning tools will remain academic.
4.2.4 Leadership Coalescence
The management of river and estuarine ecosystems to protect valued species and habitats
is one of California's least coordinated water management activities. Too many agencies
and groups have roles leading to fragmentation of leadership and responsibility. Successful
environmental flow management is more likely to occur if there is a transparent and
22 e.g., the Okanagan Fish/Water Management Tool (www.douglaspud.org/Pages/where-did-all-of-these-sockeye-come-from.aspx)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 1 7 | P a g e
science-based program linked to relevant decision support tools and the outcomes of
adaptive management and monitoring. This ought to include the creation of a real-time,
Ecological Water Operations Management Team (E-WOMT)23. Members of the E-WOMT
would include those with deep background and experience in aquatic ecology in addition to
traditional hydrologists and engineers familiar with CVP and SWP coordinated operations.
A functioning E-WOMT, informed by both a rigorous adaptive management program and a
package of appropriate integrated decision support tools (including new real-time ecological
modeling tools), would be a giant step forward in routinely doing multiple objective trade-off
decision-making.
23 In a recent blog post, Dr. Peter Moyle suggested forming a triage panel: convening a panel of state and federal fishery scientists
with authority to decide which species are in greatest need of “environmental flows” from reoperation of dams.
http://californiawaterblog.com/2014/02/17/why-and-how-to-save-native-salmon-during-a-severe-drought

Chapter 4: Where to From Here?
2 1 8 | P a g e
Acknowledgements
We would like to extend our thanks to the Ecosystem Restoration Program for funding this
work and for all their assistance managing Grant ERP-07D-P06; E0720044 to The Nature
Conservancy. Mary Dunne, the ERP grant manager, provided excellent grant management
services during the course lifetime of the grant to TNC.
We thank The Nature Conservancy for providing grant managmenet support. Ryan Luster
was The Nature Conservancy project manager for this project. Greg Golet, Maurice Hall,
Rodd Kelsey, Ryan Luster, and Jeanette Howard provided valuable reviews of this Final
Report. Wendie Duron provided grant support. Finally, The Nature Conservancy provided
invaluable conduits for obtaining data and making contacts with key researchers and
agency management.
We thank the over 70 scientists (listed in Appendix C: Delta Ecological Flows Tool
Backgrounder Report) who have contributed to the EFT project over the years through
participating in our workshops and reviewing documents. You provided invaluable time to
the EFT project for which we are very grateful.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
2 1 9 | P a g e
5 References and Further Reading
Abell, R., M. Thieme, E. Dinerstien, and D. Olson. 2002. A sourcebook for conducting biological
assessments and developing biodiversity visions for ecoregion conservation. Volume II:
Freshwater ecoregions. World Wildlife Fund, Washington, D.C.
Alexander, C.A.D. 2004. Riparian initiation, scour and Chinook egg survival models for the
Trinity River. Notes from a model review meeting held September 3rd to 5th, 2003. 2nd
Draft prepared by ESSA Technologies Ltd., Vancouver, BC for McBain and Trush, Arcata,
CA. 29 p.
Alexander, C.A.D., C.N. Peters, D.R. Marmorek, and P. Higgins. 2006. A decision analysis of
flow management experiments for Columbia River mountain whitefish (Prosopium
williamsoni) management. Canadian Journal of Fisheries and Aquatic Sciences 63: 1142-
1156.
Alexander, C.A.D., E. Olson, J. Carron. 2013. Integrated Water Management in the Colorado
River Basin: Evaluation of Decision Support Platforms and Tools. Final Report. Prepared
by ESSA Technologies Ltd. and Hydros Consulting for the Colorado River Program of The
Natural Conservancy. Boulder, Colorado. 107 pp. + appendices.
Anderson, R. and G. Stewart. 2007. Impacts of stream flow alterations on the native fish
assemblage and their habitat availability as determined by 2D modeling and the use of fish
population data to support instream flow recommendations for the sections of the Yampa,
Colorado, Gunnison and Dolores Rivers in Colorado. Colorado Division of Wildlife Aquatic
Wildlife Research. Special Report Number 80.
Arthington A.H., J.M. King, J.H. O’Keefe, S.E. Bunn, J.A. Day, B.J. Pusey, D.R. Bluhdorn, and
R. Tharme. 1991. Development of a holistic approach for assessing environmental flow
requirements of riverine ecosystems. In Water Allocation for the Environment:
Proceedings of an International Seminar and Workshop, J.J. Pigram and B.A. Hooper
(eds). The Centre for Water Policy Research, University of New England Armidale,
Australia: 69-76.
Arthington A.H., S.E. Bunn, N.L. Poff, and R.J. Naiman. 2006. The challenge of providing
environmental flow rules to sustain river ecosystems. Ecological Applications 16: 1311-
1318.
Bartholow, J.M. and V. Heasley. 2006. Evaluation of Shasta Dam scenarios using a salmon
production model. Draft Report to U.S. Geological Survey. 110 pp.
BDCP (Bay Delta Conservation Plan). 2013. Public Review Draft BDCP EIR/EIS.
http://baydeltaconservationplan.com/Home.aspx. Many thousands of pages and
Appendices.
Example sub-elements24:
BDCP (Bay Delta Conservation Project). 2012a. BDCP effects analysis Appendix 5.A.2 –
Climate Change Approach and Implications for Aquatic Species. 126 p.
[http://baydeltaconservationplan.com/Libraries/Dynamic_Document_Library/Public_Draft_BDCP_A
24 We do not attempt a comprehensive citation of all BDCP documents. The bulk of what is relevant in this report relates to the
BDCP Effects Analyses (Appendix 5).

Chapter 5: References and Further Reading
220 | P a g e
ppendix_5A_-_2_-_Climate_Change_Approach_and_Implications_for_Aquatic_Species.sflb.ashx;
accessed 12-February-2014]
BDCP (Bay Delta Conservation Project). 2012b. BDCP effects analysis-Appendix C.A –
CALSIM and DSM2 Results. 286 p.
[http://baydeltaconservationplan.com/Libraries/Dynamic_Document_Library/BDCP_Effects_Analysi
s_-_Appendix_5_C_-_Attachment_C_A_-
_CALSIM_and_DSM2_Modeling_Results_for_the_Evaluated_Starting_Operations_Scenarios_3-
27-13.sflb.ashx; accessed 12-February-2014]
Benigno, G.M. and T.R. Sommer. 2009. Just add water: sources of chironomid drift in a large
river floodplain. Hydrobiologia 600: 297-305.
Bennett, W.A. 2005. Critical assessment of the Delta smelt population in San Francisco estuary,
California. San Francisco Estuary and Watershed Science 3(2): Article 1.
[http://repositories.cdlib.org/jmie/sfews/vol3/iss2/art1/; accessed 20-November-2008]
Bestgen, K.R., P. Budy, and W.J. Miller. 2011. Status and trends of flannelmouth sucker
Catostomus latipinnis, bluehead sucker Catostomus discobolus, and roundtail chub Gila
robusta, in the Dolores River, Colorado, and opportunities for population improvement:
Phase II Report. Final report submitted to the Lower Dolores Plan Working Group-
Legislative Committee. Larval Fish Laboratory Contribution 166 and Intermountain Center
for River Rehabilitation and Restoration 2011(2): 1-55 + appendices.
Bovee, K.D. 1982. A guide to stream habitat analysis using the instream flow incremental
methodology. Instream Flow Information Paper 12. FWS/OBS-82/26. U.S. Department of
Fisheries and Wildlife Services, Washington, D.C.
Bovee, K.D., B.L. Lamb, J.M. Bartholow, C.B. Stalnaker, J. Taylor, and J. Henriksen. 1998.
Stream habitat analysis using the instream flow incremental methodology. Biological
Resources Division Information and Technology Report United States Geological Survey,
Fort Collins, Colorado.
Bradford, M.J., Taylor, G.C., Allan, J.A., and P.S. Higgins. 1995. An experimental study of the
stranding of juvenile Coho salmon and Rainbow trout during rapid flow decreases in winter
conditions. North American Journal of Fisheries Management 15: 473-479.
CALFED. 2000. Ecosystem Restoration Program Plan Volume 1 Ecological Attributes of the San
Francisco Bay-Delta Watershed Final Programmatic EIS/EIR.
Carlisle D., D. Wolock, and M. Meador. 2010. Alteration of stream flow magnitudes and potential
ecological consequences: a multiregional assessment. Frontiers in Ecology and the
Environment. doi: 10.1890/100053.
Cole, T.M. and S.A. Wells. 2003. CE-QUAL-W2—A two-dimensional, laterally averaged,
hydrodynamic and water quality model, version 3.2: Vicksburg, MS, U.S. Army
Engineering and Research Development Center, Instruction Report EL-03-01.
Conallin J., E. Boegh, and J.K. Jensen. 2010. Instream physical habitat modelling types: an
analysis as stream hydromorphological modelling tools for EU water resource managers.
International Journal of River Basin Management 8: 93-107.
Cooper, D.J. and D.C. Andersen. 2012. Novel plant communities limit the effects of a managed
flood to restore riparian forests along a large regulated river. River Research and
Applications 28(2): 204-215.
Cooper, D.J., D.C. Andersen, and R.A. Chimner. 2003. Multiple pathways for woody plant
establishment on floodplains at local to regional scales. Journal of Ecology 91(2): 182-196.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
221 | P a g e
Cross, W. F., C.V. Baxter, K.C. Donner, E.J. Rosi-Marshall, T.A. Kennedy, R.O. Hall Jr., R.S.
Rogers, et al. 2011. Ecosystem ecology meets adaptive management: food web response
to a controlled flood on the Colorado River, Glen Canyon. Ecological Applications 21(6):
2016-2033.
CRSCI. 2013. Map available online at: http://www.crcsi.com.au/Research/Commissioned-
Research/Remote-Sensing-for-MDBA
Cui, Y. 2007. The Unified Gravel-Sand (TUGS) Model: Simulating sediment transport and
gravel/sand grain size distributions in gravel-bedded rivers. Water Resources Research
43:W10436, doi:10.1029/2006WR005330.
DSP (Delta Science Panel). 2014. Delta Science Panel Independent Review Panel Report:
BDCP Effects Analysis Review, Phase 3. Report to the Delta Science Program. Prepared
by Parker, A., C. Simenstad, T.L. George, N. Monsen, G. Ruggerone, and J. Skalksi. Delta
Stewardship Council Delta Science Program. Sacramento, California. 80 pp. +
appendices.
Delta Smelt Biological Opinion. 2008. The Sacramento Fish and Wildlife Office’s Biological
Opinion (BiOp) on the Long-Term Operational Criteria and Plan (OCAP) effects on Delta
Smelt. U.S. Department of the Interior, Fish and Wildlife Service. December 15, 2008.140
pp. [http://www.fws.gov/sfbaydelta/documents/SWP-CVP_OPs_BO_12-15_final_OCR.pdf;
accessed 28-September-2012]
Draper, A.J., A. Munévar, S.K. Arora, E. Reyes, N.L. Parker, F.I. Chung, and L.E. Peterson.
2004. CALSIM: Generalized Model for Reservoir System Analysis. American Society of
Civil Engineers, Journal of Water Resources Planning and Management 130(6).
DWR (California Department of Water Resources). 2010a. The State Water Project Delivery
Reliability Report 2009: State of California, Natural Resources Agency, Department of
Water Resources, Sacramento, CA. August 2010. 58 pp. + appendices.
[http://baydeltaoffice.water.ca.gov/swpreliability/Reliability2010final101210.pdf; accessed
05-February-2014]
DWR (California Department of Water Resources). 2010b. The State Water Project Delivery
Reliability Report 2009: Technical Addendum, State of California, Natural Resources
Agency, Department of Water Resources, Sacramento, CA. August 2010.
DWR (California Department of Water Resources). 2012. The State Water Project Final Delivery
Reliability Report 2011, State of California, Natural Resources Agency, Department of
Water Resources, Sacramento, CA. June 2012. 63 pp. + appendices.
[http://baydeltaoffice.water.ca.gov/swpreliability/FINAL_2011_DRR.pdf; accessed 05-
February-2014]
Ellison, A.M., M.S. Bank, B.D. Clinton, E.A. Colburn, K. Elliott, C.R. Ford, et al. 2005. Loss of
foundation species: consequences for the structure and dynamics of forested ecosystems.
Frontiers in Ecology and the Environment 3: 479-486.
ESSA (ESSA Technologies Ltd.). 2005. Sacramento River Decision Analysis Tool: Workshop
Backgrounder. Prepared for The Nature Conservancy, Chico, CA. 75 pp.
ESSA (ESSA Technologies Ltd.). 2008. Delta Ecological Flows Tool: Backgrounder (Final
Draft). Prepared by ESSA Technologies Ltd., Vancouver, BC for The Nature Conservancy,
Chico, CA. 121 pp.
ESSA (ESSA Technologies Ltd.). 2011. Sacramento River Ecological Flows Tool (SacEFT):
Record of Design (v.2.00). May 2011 revision. Prepared by ESSA Technologies Ltd.,
Vancouver, BC for The Nature Conservancy, Chico, CA. 111 p. + appendices.

Chapter 5: References and Further Reading
222 | P a g e
ESSA (ESSA Technologies Ltd.). 2013. The Delta Ecological Flows Tool: Record of Design
(v.1.1). Final. December 2013 revision. Prepared by ESSA Technologies Ltd., Vancouver,
BC for The Nature Conservancy, Chico, CA. 142 pp. + appendix.
ESSA (ESSA Technologies Ltd.). 2014. Ecological Flows Tool Reader (v 4) – User Guide.
Prepared for The Nature Conservancy, Chico, CA. 28 pp.
Fleenor, W., W. Bennett, P. Moyle, and J. Lund. 2010. On developing prescriptions for
freshwater flows to sustain desirable fishes in the Sacramento-San Joaquin Delta.
Submitted to the State Water Resources Control Board regarding flow criteria for the Delta
necessary to protect public trust resources. Center for Watershed Sciences, University of
California, Davis. 46pp.
Feyrer, F., T. Sommer, and W. Harrell. 2006. Managing floodplain inundation for native fish:
production dynamics of age-0 splittail (Pogonichthys macrolepidotus) in California’s Yolo
Bypass. Hydrobiologia 573: 213-226.
Haines, G.B., D. Irving, and T. Modde. 2004. White River Base Flow Study for Endangered Fish,
Colorado and Utah, 1995-1996. Final Report prepared for the Upper Colorado River
Endangered Fish Recovery Program, Denver, CO.
Halleraker, J.H., S.J. Saltveit, A. Harby, J.V. Arnekliev, H.P. Fjeldstad, and B. Kohler. 2003.
Factors influencing stranding of wild juvenile Brown trout (Salmo trutta) during rapid and
frequent flow decreases in an artificial stream. River Research and Applications 19: 589-
603.
Harper, E.B., J.C. Stella, and A.K. Fremier. 2011. Global sensitivity analysis for complex
ecological models: a case study of riparian cottonwood population dynamics. Ecological
Applications 21(4): 1225-1240.
Hilborn, R. and M. Mangel. 1997. The ecological detective: confronting models with data.
Monographs in Population Biology No. 28, Princeton University Press, Princeton, New
Jersey. 315 pp.
Higgins, J. and R. Esselman (eds.). 2006. Ecoregional Assessment and Biodiversity Toolbox.
The Nature Conservancy. Arlington, Virginia.
Hoey, T.B. and R.I. Ferguson. 1994. Numerical simulation of downstream fining by selective
transport in gravel bed rivers: Model development and illustration. Water Resources
Research 30: 2251-2260.
Hughes, F.M.R., W.M. Adams, E. Muller, C. Nilsson, K.S. Richards, N. Barsoum, et al. 2001.
The importance of different scale processes for the restoration of floodplain woodlands.
Regulated Rivers–Research and Management 17: 325-345.
Huizinga, M. and R.A. Fridell. 2012. Trends in the native fish assemblage and identification of
temperature and flow limiting factors in the Virgin River between Pah Tempe Hot Springs
and the Washington Fields Diversion 2002-2010. Publication Number 11-35. Utah
Department of Natural Resources, Division of Wildlife Resources. Salt Lake City, Utah.
Instream Flow Council (IFC). 2002. Instream Flows for Riverine Resource Stewardship. 410 pp.
Johannesson, H. and G. Parker. 1989. Linear theory of river meanders. In River Meandering, S.
Ikeda and G. Parker G (eds.). Water Resources Monographs, 12. AGU: Washington; 181–
214.
Jowett I.G. and A.J.H. Davey. 2007. A comparison of composite habitat suitability indices and
generalized additive models of invertebrate abundance and fish presence–habitat
availability. Transactions of the American Fisheries Society 136: 428-444.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
223 | P a g e
Katz, J., P.B. Moyle, R.M. Quiñones, J. Israel, and S. Purdy. 2013. Impending extinction of
salmon, steelhead, and trout (Salmonidae) in California. Environmental biology of fishes
96(10-11): 1169-1186.
Kaval, P. 2011. Ecosystem Service Valuation of the Colorado River Basin. Prepared for the
Nature Conservancy. 92 pp.
Kimmerer, W.J. and M.L. Nobriga. 2008. Investigating particle transport and fate in the
Sacramento-San Joaquin Delta using a particle tracking model. San Francisco Estuary
and Watershed Science 6(1) Article 4.
Larsen, E.W. 1995. Mechanics and modeling of river meander migration. Ph.D. Dissertation.
Civil Engineering.
Larsen, E.W. and S.E. Greco. 2002. Modeling channel management impacts on river migration:
a case study of Woodson Bridge State Recreation Area, Sacramento River, California,
USA. Environmental Management 30: 209.224.
Larsen, E.W., A.K. Fremier, and S.E. Greco. 2006a. Cumulative effective stream power and
bank erosion on the Sacramento River, CA, USA. Journal of American Water Resources
Association 42: 1077-1097.
Larsen, E.W., E. Girvetz, and A. Fremier. 2006b. Assessing the effects of alternative setback
levee scenarios employing a river meander migration model. Environmental Management
37: 880-897.
Lund, J., E. Hanak, W. Fleenor, W. Bennett, R. Howitt, J. Mount, and P. Moyle. 2010.
Comparing Futures for the Sacramento-San Joaquin Delta. Berkeley, CA. University of
California Press and Public Policy Institute of California.
Lytle, D.A. and D.M. Merritt. 2004. Hydrologic regimes and riparian forests: a structured
population model for cottonwood. Ecology 85: 2493-2503.
Mahoney, J. and S. Rood. 1998. Streamflow Requirements for Cottonwood Seedling
Recruitment—An Integrative Model. Wetlands 18(4): 634-645. doi:10.1007/BF03161678.
Merritt, D.M. and N.L.R. Poff. 2010. Shifting dominance of riparian Populus and Tamarix along
gradients of flow alteration in western North American rivers. Ecological Applications 20:
135-152.
Michener, W.K. and R. Haeuber. 1998. Flooding: natural and managed disturbances.
BioScience 48: 677-680.
Mount, J., W. Fleenor, B. Gray, B. Herbold, and W. Kimmerer. 2013. Panel review of the draft
Bay Delta Conservation Plan. Saracino & Mount LLC, Sacramento, CA. 152 pp.
Moyle, P.B. 2002. Inland fishes of California. Revised edition. University of California Press,
Berkeley.
Moyle, P.B., B. Herbold, D.E. Stevens, and L.W. Miller. 1992. Life-history and status of Delta
smelt in the Sacramento-San Joaquin estuary, California. Transactions of the American
Fisheries Society 121: 67-77.
Moyle, P.B., J.A. Israel, and S.E. Purdy. 2008. Salmon, Steelhead, and Trout in California:
Status of an Emblematic Fauna. Center for Watershed Sciences, University of California
Davis. A report commissioned by California Trout.
Moyle, P.B., J.V.E. Katz, and R.M. Quiñones. 2011. Rapid decline of California’s native inland
fishes: a status assessment. Biological Conservation 144: 2414-2423.

Chapter 5: References and Further Reading
224 | P a g e
Moyle, P., W. Bennett, J. Durand, W. Fleenor, B. Gray, E. Hanak, J. Lund, and J. Mount. 2012.
Where the wild things aren’t: making the Delta a better place for native species. Public
Policy Institute of California. San Francisco, CA. 55 pp.
[http://www.ppic.org/main/publication.asp?i=1025; accessed 19-February-2014].
Moyle, P.B., J.D. Kiernan, P.K. Crain, and R.M. Quiñones. 2013. Climate change vulnerability of
native and alien freshwater fishes of California: a systematic assessment approach. PLoS
One. doi: 10.1371/journal.pone.0063883.
NMFS (National Marine Fisheries Service). 1997. Proposed Recovery Plan for the Sacramento
River Winter ‐ Run Chinook Salmon. Long Beach, CA: National Marine Fisheries Service,
Southwest Region.
NMFS (National Marine Fisheries Service). 2009. Biological Opinion and Conference Opinion on
the long-term operations of the Central Valley Project and State Water Project. United
States Department of Commerce, National Oceanic and Atmospheric Administration,
National Marine Fisheries Service Southwest Region. Long Beach, CA. 844pp + 5
appendices.
NMFS (National Marine Fisheries Service). 2009. Public Draft Recovery Plan for the
Evolutionarily Significant Units of Sacramento River winter ‐ run Chinook salmon and
Central Valley spring ‐ run Chinook salmon and the distinct population segment of Central
Valley steelhead. Sacramento Protected Resources Division. October 2009.
Nowak, K., J. Prairie, B. Rajagopalan, and U. Lall. 2010. A nonparametric stochastic approach
for multisite disaggregation of annual to daily stream flow. Water Resources Research 46
(W08529). doi:10.1029/2009WR008530.
Olden J.D. and N.L. Poff. 2003. Redundancy and the choice of hydrologic indices for
characterizing stream flow regimes. River Research and Applications 19: 101-121.
Oreskes, N., K. Schrader-Frechette, and K. Belitz. 1994. Verification, validation, and
confirmation of numerical models in the earth sciences. Science 263: 641-646.
Parasiewicz P. 2001. MesoHABSIM: a concept for application of instream flow models in river
restoration planning. Fisheries 26: 6-13.
Parasiewicz P. and M.J. Dunbar. 2001. Physical habitat modelling for fish: a developing
approach. Large Rivers/ Supplement to Archiv für Hydrobiologie 12/135: 239-268.
Patten D.T. 1998. Riparian ecosystems of semi-arid North America: diversity and human
impacts. Wetlands 18: 498-512.
Perry, W.R., J.R. Skalski, P.L. Brandes, P.T. Sandstrom, A.P. Klimley, A. Ammann, and B.
MacFarlane. 2010. Estimating survival and migration route probabilities of juvenile
Chinook salmon in the Sacramento-San Joaquin River delta. North American Journal of
Fisheries Management 30: 142-156.
Petts, G.E. 2009. Instream Flow Science for Sustainable River Management. Journal of the
American Water Resources Association (JAWRA) 45(5): 1071-1086. doi: 10.1111 ⁄ j.1752-
1688.2009.00360.x.
Podger, G., A. Yang, A. Brown, J. Teng, R. Power, and S. Seaton. 2010. Proposed River
Modelling Methods and Integrated River System Modelling Framework Design for use in
Basin Plan Modelling. CSIRO: Water for a Healthy Country National Research Flagship.
Poff, N.L., J.D. Allan, M.B. Bain, J.R. Karr, K.L. Prestegaard, B.D. Richter, R.E. Sparks, and J.C.
Stromberg. 1997. The natural flow regime: a paradigm for river conservation and
restoration. Bioscience 47: 769-784.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
225 | P a g e
Poff, N.L. and J.Z.H. Zimmerman. 2010. Ecological responses to altered flow regimes: a
literature review to inform the science and management of environmental flows.
Freshwater Biology 55: 194-205. doi: 10.1111/j.1365– 2427.2009.02272.x.
Poff, N.L., B.D. Richter, A.H. Arthington, S.E. Bunn, R.J. Naiman, E. Kendy, M. Acreman, C.
Apse, B.P. Bledsoe, M.C. Freeman, J. Henriksen, R.B. Jacobson, J.G. Kennen, D.M.
Merritt, J.H. O’Keeffe, J.D. Olden, K. Rogers, R.E. Tharme, and A. Warner. 2010. The
ecological limits of hydrologic alteration (ELOHA): a new framework for developing
regional environmental flow standards. Freshwater Biology 55: 147-170.
Postel, S. and B. Richter. 2003. Rivers for life: managing water for people and nature. Island
Press.
Quartarone, F. 1993. Historical accounts of upper Colorado River basin endangered fish. Final
Report Submitted to Recovery Implementation Program for the Endangered Fishes of the
Upper Colorado River Basin, U.S. Fish and Wildlife Service, Denver, CO. 66 pp.
Rapport, D.J., R. Costanza, and A.J. McMichael. 1998. Assessing ecosystem health. Trends in
Ecology and Evolution 13: 397-402.
Richter, B.D., J.V. Baumgartner, J. Powell, and D.P. Braun. 1996. A method for assessing
hydrologic alteration within ecosystems. Conservation Biology 10: 1163-1174.
Richter, B.D, J.V. Baumgartner, R. Wigington, and D.P. Braun. 1997. How much water does a
river need? Freshwater Biology 39: 231-249.
RMA (Resource Management Associates, Inc.). 2003. Draft Upper Sacramento River Water
Quality Modeling with HEC-5Q: Model Calibration and Validation. December 2003.
Roberts, M.D. 2003. Beehive Bend subreach addendum to: a pilot investigation of cottonwood
recruitment on the Sacramento River. Prepared by The Nature Conservancy. Chico, CA.
Roberts, M.D., D.R. Peterson, D.E. Jukkola, and V.L. Snowden. 2002. A pilot investigation of
cottonwood recruitment on the Sacramento River. Prepared by The Nature Conservancy.
Chico, CA.
Roni, P., G.R. Pess, T.J. Beechie, and S.A. Morley. 2011. Estimating salmon and steelhead
response to watershed restoration: How much restoration is enough? North American
Journal of Fisheries Management 30: 1469-1484.
Sanderson, J.S., N. Rowan, T. Wilding, B.P. Bledsoe, W.J. Miller, and N.L. Poff. 2011. Getting
to scale with environmental flow assessment: the Watershed Flow Evaluation Tool. River
Research and Applications 28(9): 1369-1377. doi: 10.1002/rra.1542.
Scott, M.L., G.T. Auble, and J.M. Friedman. 1997. Flood dependency of cottonwood
establishment along the Missouri River, Montana, USA. Ecological Applications 7: 677-
690.
Scruton, D.A., L.M.N. Ollerhead, K.D. Clarke, C. Pennell, K. Alfredsen, A. Harby, and D. Kelley.
2003. The behavioural response of juvenile Atlantic salmon (Salmo salar) and Brook trout
(Salvelinus fontinalis) to experimental hydropeaking on a Newfoundland (Canada) river.
River Research and Applications 19: 577-587.
Shafroth, P.B., J.C. Stromberg, and D.T. Patten. 1998. Establishment of woody vegetation in
relation to annual patterns of streamflow, Bill Williams River, Arizona. Wetlands 18: 557-
590.
Shafroth, P.B., J.C. Stromberg, and D.T. Patten. 2002. Riparian vegetation response to altered
disturbance and stress regimes. Ecological Applications 12: 107-123.

Chapter 5: References and Further Reading
226 | P a g e
Shafroth P.B., A.C. Wilcox, D.A. Lytle, J.T. Hickey, D.C. Andersen, V.B. Beauchamp, A.
Hautzinger, L.E. McMullen, and A. Warner. 2010. Ecosystem effects of environmental
flows: modelling and experimental floods in a dryland river. Freshwater Biology 55: 68-85.
Shelbourn, J.E., J.R. Brett, and S. Shirahat. 1973. Effect of temperature and feeding regime on
specific growth-rate of sockeye salmon fry (Oncorhynchus nerka), with a consideration of
size effect. Journal of the Fisheries Research Board of Canada 30: 1191-1194.
Shelby, B., J.J. Vaske, and M.P. Donnely. 1996. Norms, standards and natural resources.
Leisure Sciences 18: 103-123.
Sommer, T., L. Conrad, G. O’Leary, F. Feyrer, and W.C. Harrell. 2002. Spawning and rearing of
splittail in a model floodplain wetland. Transactions of the American Fisheries Society 131:
966-974.
Sommer, T., R. Baxter, and B. Herbold. 1997. Resilience of splittail in the Sacramento-San
Joaquin Estuary. Transactions of the American Fisheries Society 126: 961-976.
Southwick Associates. 2012. Economic contributions of outdoor recreation on the Colorado
River and its tributaries. Prepared for Protect The Flows. May 3 2012. 53 pp.
Stanford JA, J.V. Ward, W.J. Liss, C.A. Frissell, R.N. Williams, J.A. Lichatowich, and C.C.
Coutant. 1996. A general protocol for restoration of regulated rivers. Regulated Rivers:
Research and Management 12: 391-413.
Stella, J.C., J.J. Battles, J.R. McBride, and B.K. Orr. 2010. Riparian seedling mortality from
simulated water table recession, and the design of sustainable flow regimes on regulated
rivers. Restoration Ecology 18(s2): 284-294.
Stella, J.C., M.K. Hayden, J.J. Battles, H. Piégay, S. Dufour, and A.K. Fremier. 2011. The role of
abandoned channels as refugia for sustaining pioneer riparian forest ecosystems.
Ecosystems 14(5): 776-790.
Stevens Jr., D.L. and A.R. Olsen. 2004. Spatially balanced sampling of natural resources.
Journal of the American Statistical Association 99(465): 262-278.
Stillwater Sciences. 2007. Linking biological responses to river processes: Implications for
conservation and management of the Sacramento River—a focal species approach. Final
Report. Prepared by Stillwater Sciences, Berkeley for The Nature Conservancy, Chico,
California.
Stromberg, J.C., D.T. Patten, and B.D. Richter. 1991. Flood flows and dynamics of Sonoran
riparian forests. Rivers 2: 221-235.
Taylor J.P., D.B. Wester, and L.M. Smith. 1999. Soil disturbance, flood management, and
riparian woody plant establishment in the Rio Grande floodplain. Wetlands 19: 372-382.
Tennant, D.L. 1976. Instream Flow Regimes for Fish, Wildlife, Recreation and Related
Environmental Resources. Fisheries 1(4): 6-10.
Tharme, R.E. 2003. A global perspective on environmental flow assessment: emerging trends in
the development and application of environmental flow methodologies for rivers. River
Research and Applications 19(5‐6): 397-441.
TNC (The Nature Conservancy). 2012. Flow Recommendations for Endangered Fish on the
White River – Response to Major Concerns.
TNC and ESSA (The Nature Conservancy and ESSA Technologies Ltd.). 2012. SacEFT
Analysis of the North-of-the-Delta Offstream Storage Investigation. The Nature
Conservancy, Chico, CA. 73pp + appendices.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
227 | P a g e
TNC et al. (The Nature Conservancy, Stillwater Sciences and ESSA Technologies Ltd.). 2008.
Sacramento River Ecological Flows Study: Final Report. Prepared for CALFED Ecosystem
Restoration Program. Sacramento, CA. 72 pp.
Toro-Escobar, C.M., G. Parker, and C. Paola. 1996. Transfer function for the deposition of
poorly sorted gravel in response to streambed aggradation. Journal of Hydraulic Research
34: 35-54.
Trush, W.J., S.M. McBain, and L.B. Leopold. 2000. Attributes of an alluvial river and their
relation to water policy and management. Proceedings of the National Academy of
Sciences USA 97: 11858-11863.
Unger, P.A. 1994. Quantifying salinity habitat of estuarine species. IEP Newsletter 7(Autumn): 7-
10. Available from: California Dept. of Water Resources, Division of Environmental
Services. Sacramento, California.
USBR (U.S. Bureau of Reclamation). 2012. Colorado River Basin Water Supply and Demand
Study. U.S. Department of the Interior, Bureau of Reclamation. 1697 pp.
USBR (U.S. Bureau of Reclamation). 2008a. Central Valley Project and State Water Project
Operations Criteria and Plan Biological Assessment, Appendix D CALSIM-II Model, May
2008.
USBR (U.S. Bureau of Reclamation). 2008b. 2008 Central Valley Project and State Water
Project Operations Criteria and Plan Biological Assessment, Appendix H Reclamation
Temperature Model and SRWQM Temperature Model.
USBR (U.S. Bureau of Reclamation). 2008c. Central Valley Project and State Water Project
Operations Criteria and Plan Biological Assessment, Appendix F DSM2 Model, May 2008.
USBR (U.S. Department of Interior). 2006. Operation of Flaming Gorge Dam, Final
Environmental Impact Statement. United States Department of Interior, Bureau of
Reclamation. Salt Lake City, Utah.
USFWS (U.S. Fish and Wildlife Service). 2013. Environmental Conservation Online System:
Threatened and Endangered Species. [http://ecos.fws.gov; accessed 15-July-2013]
USFWS (U.S. Fish and Wildlife Service). 2008. The Sacramento Fish and Wildlife Office’s
Biological Opinion (BiOp) on the Long-Term Operational Criteria and Plan (OCAP) effects
on Delta Smelt. U.S. Department of the Interior, Fish and Wildlife Service. December 15,
2008. 396 pp. [http://www.fws.gov/sfbaydelta/documents/SWP-CVP_OPs_BO_12-
15_final_OCR.pdf; accessed 12-February-2014]
USFWS (U.S. Fish and Wildlife Service). 2006. Relationships between flow fluctuations and
redd dewatering and juvenile stranding for Chinook salmon and steelhead in the
Sacramento River between Keswick Dam and Battle Creek. Report prepared by the
Energy Planning and Instream Flow Branch, U.S. Fish and Wildlife Service. Sacramento,
CA. 94pp.
USFWS (U.S. Fish and Wildlife Service). 2005a. Flow-habitat relationships for fall-run Chinook
salmon spawning in the Sacramento River between Battle Creek and Deer Creek. Report
prepared by the Energy Planning and Instream Flow Branch, U.S. Fish and Wildlife
Service. Sacramento, CA. 104pp.
USFWS (U.S. Fish and Wildlife Service). 2005b. Flow-habitat relationships for fall-run Chinook
salmon rearing in the Sacramento River between Keswick Dam and Battle Creek. Report
prepared by the Energy Planning and Instream Flow Branch, U.S. Fish and Wildlife
Service. Sacramento, CA. 258pp.

Chapter 5: References and Further Reading
228 | P a g e
USFWS (U.S. Fish and Wildlife Service). 2005c. Final Programmatic Biological Opinion on the
Management Plan for Endangered Fishes in the Yampa River Basin. U.S. Department of
the Interior, Fish and Wildlife Service. Denver, Colorado.
USFWS (U.S. Fish and Wildlife Service). 2003. Flow-habitat relationships for steelhead and fall,
late-fall and winter-run Chinook salmon spawning in the Sacramento River between
Keswick Dam and Battle Creek. Report prepared by the Energy Planning and Instream
Flow Branch, U.S. Fish and Wildlife Service. Sacramento, CA. 79pp.
USGS (U.S. Geological Survey). 2006. Defining Ecosystem Flow Requirements for the Bill
Williams River, Arizona. U.S. Geological Survey Open File Report 2006-1314, 135 pp.
[http://www.fort.usgs.gov/products/publications/21745/21745.pdf]
Vogel, D.A. and K.R. Marine. 1991. Guide to upper Sacramento River Chinook salmon life-
history. CH2M HILL, Redding, California. Produced for the U.S. Bureau of Reclamation
Central Valley Project. 55pp + appendices.
Walters, C., J. Korman, L.E. Stevens, and B. Gold. 2000. Ecosystem modeling for evaluation of
adaptive management policies in the Grand Canyon. Conservation Ecology 4(2): 1.
[http://www.consecol.org/vol4/iss2/art1/]
Whittaker, D., B. Shelby, W. Jackson, and R. Beschta. 1993. Instream flows for recreation: a
handbook on concepts and research methods. U.S. Department of Interior, National Park
Service, Anchorage, AK.
Wilcock, P.R. and J.C. Crowe. 2003. Surface-based transport model for mixed-size sediment.
Journal of Hydraulic Engineering 129: 120-128.
Wilding, T.K. and J. Sanderson. 2010. Riparian vegetation methods for the watershed flow
evaluation tool. A report to the non-consumptive needs committee of the Colorado Basin
Roundtable. 42 pp.
Wilding, T.K. 2012. Regional methods for evaluating the effects of flow alteration on stream
ecosystems. Ph.D. Dissertation. Colorado State University. 194 pp. Adviser: Nathan
LeRoy Poff. DAI/B 74-01(E), Oct 2012 / 3523829.
Williams, C.A. and D.J. Cooper. 2005. Mechanisms of riparian cottonwood decline along
regulated rivers. Ecosystems 8: 382-395.
Williams, J.E., A.L. Haak, N.G. Gillespie, and W.T. Colyer. 2007. The Conservation Success
Index: synthesizing and communicating salmonid condition and management needs.
Fisheries 32(10): 477-493.
Williams, J.G. 1996. Lost in space: minimum confidence intervals for idealized PHABSIM
studies. Transactions of the American Fisheries Society 125: 458-465.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
A - 1 | P a g e
Appendix A: Sacramento River Ecological Flows Tool
Backgrounder Report
ESSA Technologies Ltd. 2005. Sacramento River Decision Analysis Tool: Workshop
Backgrounder. Prepared for The Nature Conservancy, Chico, CA. 75 p.
PDF available from: http://www.wildlife.ca.gov/erp/erp_proj_delta_eft.aspx

Appendix A: Sacramento River Ecological Flows Tool Backgrounder Report .
A - 2 | P a g e
[Page Intentionally Blank]

Final Report
Application of EFT to Complement Water Planning for Multiple Species
B - 1 | P a g e
Appendix B: Sacramento River Ecological Flows Tool
(SacEFT v.2) Record of Design
ESSA Technologies Ltd. 2011. Sacramento River Ecological Flows Tool (SacEFT):
Record of Design (v.2.00). May 2011 revision. Prepared by ESSA Technologies Ltd.,
Vancouver, BC for The Nature Conservancy, Chico, CA. 111 p. + appendices.
PDF available from: http://www.wildlife.ca.gov/erp/erp_proj_delta_eft.aspx

Appendix B: Sacramento River Ecological Flows Tool (SacEFT v.2) Record of Design
B - 2 | P a g e
[Page Intentionally Blank]

Final Report
Application of EFT to Complement Water Planning for Multiple Species
C - 1 | P a g e
Appendix C: Delta Ecological Flows Tool Backgrounder
Report
ESSA Technologies Ltd. 2008. Delta Ecological Flows Tool: Backgrounder (Final Draft).
Prepared by ESSA Technologies Ltd., Vancouver, BC for The Nature Conservancy, Chico,
CA. 121 p.
PDF available from: http://www.wildlife.ca.gov/erp/erp_proj_delta_eft.aspx

Appendix C: Delta Ecological Flows Tool Backgrounder Report .
C - 2 | P a g e
[Page Intentionally Blank]

Final Report
Application of EFT to Complement Water Planning for Multiple Species
D - 1 | P a g e
Appendix D: The Delta Ecological Flows Tool (DeltaEFT
v.1.1) Record of Design
ESSA Technologies Ltd. 2013. The Delta Ecological Flows Tool: Record of Design (v.1.1).
Final. December 2013 revision. Prepared by ESSA Technologies Ltd., Vancouver, BC for
The Nature Conservancy, Chico, CA. 142 p.+ Appendix
PDF available from: http://www.wildlife.ca.gov/erp/erp_proj_delta_eft.aspx

Appendix D: The Delta Ecological Flows Tool (DeltaEFT v.1.1) Record of Design ESSA Technologies Ltd.
D - 2 | P a g e
[Page Intentionally Blank]

Final Report
Application of EFT to Complement Water Planning for Multiple Species
E - 1 | P a g e
Appendix E: EFT Reader Software – User’s Guide
ESSA Technologies Ltd. 2014. Ecological Flows Tool Reader (v 4) – User Guide.
Prepared for The Nature Conservancy, Chico, CA. 28 p.
See: http://eft-userguide.essa.com/
PDF available from: http://www.wildlife.ca.gov/erp/erp_proj_delta_eft.aspx

Appendix E: EFT Reader Software – User’s Guide ESSA Technologies Ltd.
E - 2 | P a g e
[Page Intentionally Blank]

Final Report
Application of EFT to Complement Water Planning for Multiple Species
F - 1 | P a g e
Appendix F: Indicator Screening & Selection Criteria
Every decision support modeling exercise must include assumptions about what is included
and excluded in order to keep the effort tractable. This involves seeking a balance of
representative indicators given the state of scientific knowledge, the types of decisions the
tool is meant to support, and budgetary resources. Our study team recognizes it will be
unrealistic to eliminate large-scale confounding influences that surround flow-related
modeling in the Delta: e.g., changing oceanographic conditions, seismic threats,
progression of invasive species regimes, changes in food web structure, or to account for
potential release of contaminants from newly restored wetlands. Hence, there is a practical
need to constrain our modeling efforts to a domain well inside the universe of “all things that
might matter”. Indeed government agencies act all the time with imperfect information on all
sorts of portfolios, including non-environmental subjects such as the economy. Our project
team appreciates the importance of the larger picture, but that does not mean we can (or
even need to) model it. Hence, the indicators that emerge from the criteria described below
take an “all else equal” stance on potentially confounding factors. This allows us to avoid
the paralysis that comes with trying to cover everything. This in no way suggests that these
outside-DeltaEFT factors are unimportant, just that our universe of concern in developing
the first version of the tool must, for practical reasons, be selective.
In support of the Sacramento River Ecological Flows Study (TNC et al. 2008), a set of
selection criteria were developed as part of the Linkages Report component (Stillwater
Sciences 2007). The application of these criteria on the Sacramento River allowed for
standardized comparisons to be drawn among a pool of candidate habitat and focal species
considerations, thus clarifying the selection process for the indicators chosen for SacEFT.
Below, we adopt this approach for use in the Delta, with important additional considerations
based on insights from recent multi-disciplinary synthesis activities (e.g., DRERIP) and our
own experience (Figure F.1). While restoration priorities will continue to evolve in the Delta,
the suite of focal habitats and indicators that are ultimately selected using these criteria
should be representative of a number of the current and ongoing species needs. As with
SacEFT, we approach the question of ecological water management needs from the
perspective of focusing on specific life-history requirements of target species and/or
ecosystem functions instead of addressing a set of population goals (e.g., we do not
attempt to answer the question “tell me how many more fish I get for x acre-feet of water”).
Our modeling emphasizes performance indicators (linked to management actions that
humans can influence) for some of the most important general conditions needed for a
target species to persist. While this does not rule out compensation in other parts of the life-
cycle, we believe this approach is reasonable to assert that – all else equal – a particular
set of hydrodynamic conditions are better than another.

Appendix F: Indicator Screening & Selection Criteria .
F - 2 | P a g e
Figure F.1: Focal habitat, species filtering and screening criteria (vetting process) for EFT.
Species or habitat historically existed
within the Bay-Delta estuary
Yes
No
1
DROP
Species is invasive with clear evidence it is
suppressing threatened or endangered
native species
Or
Non-native species that has achieved high
economic or public interest value
Yes
Species (and by extension its primary
habitat) is listed or proposed for listing
under Endangered Species regulations
2
No
Species or habitat meets several of the
following criteria:
Has high economic or public interest value
Has narrow habitat requirements
Is a weak disperser
Wider population over geographic range is
threatened or declining
Has distinctive habitat needs relative to
other species in its trophic caste (don’t
include species from a guild that is already well
represented)
Is believed to be a strong interactor or
keystone species dictating local food web
dynamics
Habitat quantity or quality or at least one
life-history stage strongly governed by
in-Delta, flow-related management
actions
Yes
NoDROP
No DROP
Yes
Yes
NoDROP
3
Final ranking and selection of candidates based on technical
feasibility details:
Can define (index) locations of importance
Local data, rather than literature values from elsewhere are available
Acquisition & manipulation of physical data needed to compute
performance indicator(s) does not use up a disproportionate amount of
project budget
Yes
5
4
7
Focal habitat or
species indicator
..reasonable
..unreasonable Another
project or
phase
Available information on habitat or species is sufficient to allow
at least qualitative assessment of how flow-related actions that
would tend to generate improvement or deterioration (all else
equal)
Evaluate technical clarity behind DRERIP “fat green arrows”
6
...Or...

Final Report
Application of EFT to Complement Water Planning for Multiple Species
F - 3 | P a g e
Step 1: The habitat or species historically existed within the Delta estuary
The first step of the vetting process involved determining if a candidate habitat or focal
species existed historically within the study area. Under most circumstances, we assume
these species will be those of primary ecological concern. This also allows for the re-
introduction of an extirpated species, which can be a goal of a restoration program.
Because the Delta currently supports many invasive species, this first step of the vetting
process does not eliminate non-native species from consideration. Instead, invasive species
may be included in one of two ways, either (a) as species to include for the purpose of
deterrence (reducing competitive advantage vs. native species) (e.g., overbite clam) or (b)
as a valued species (e.g., striped bass) that has achieved high economic or other value to
people. Though it is often infeasible to eradicate a non-native species once it has become
widely established, management actions may help to control the abundance or distribution
of targeted non-native species so that their adverse ecological effects are reduced, or, in
the case of valued species, so that their benefits to society are increased.
Step 2: Is the species listed as endangered or threatened?
The second step of the vetting process acknowledged that the recovery of listed species
constitutes a high social priority, both economically and ecologically. It also recognizes that
listed species are often at the center of resource management conflicts, so that recovery of
the species can be an important management goal as a means of reducing these conflicts
that place restrictions on human activities. The endangered and threatened species that
occur in an ecosystem often serve as focal species; however, the number of listed species
that occur in the Delta area precludes the selection of every listed species. One of the
functions of the focal species approach is to facilitate the organization and synthesis of a
suite of broadly representative ecological indicators; however, this process can be
undermined by the selection of too many focal species.
Step 3: Additional criteria for non-listed species
A series of criteria for non-listed species is available to enable capture of habitat or focal
species indicators that are important even if that species is not listed. It is important to
include non-listed species in order to capture potential ecosystem changes that tend to
reduce these populations, which may in the future necessitate additional listings or
otherwise exacerbate resource conflicts. Metaphorically speaking, “it is often better to place
resources on stopping a neighborhood from catching on fire rather than sending all the fire
trucks to put out the out-of-control blaze.” Criteria used to make these selections are:
 High economic or public interest value. This criteria recognizes the economic or
social importance of certain species, such as species that are the focus of
commercial fisheries (e.g., salmon) and sport fish that are the focus of recreational
angling (e.g., steelhead, sturgeon).

Appendix F: Indicator Screening & Selection Criteria .
F - 4 | P a g e
 Narrow habitat requirements. The second criterion tests whether a species has
narrow habitat requirements such that loss of that habitat type would pose a
significant threat to the health of the population. For example, bank swallows nest in
fresh vertical cut-banks composed of soils with a loamy-sandy texture and at least
1m in height, which represents a stringent mix of habitat conditions. Bank swallow
colony sites also have a limited lifespan (< 5 years) because of bank slumping,
rodent burrowing, and possibly parasite infestation. Consequently, activities that
affect the frequency of bank erosion in zones of appropriately textured soils (e.g.,
bank protection, flow regulation, land conversion) can combine with the narrow
habitat requirements of bank swallow to create a significant threat to population
recruitment. For this reason and others, the bank swallow was selected as a focal
species for SacEFT.
 Weak disperser. The third criterion identifies species that have difficulty dispersing
to new areas, which prevents a species from establishing new sub-populations that
can help mitigate the loss of an existing breeding population from a catastrophic
event or persistent chronic mortality agent. For example, even though green
sturgeon migrate thousands of miles through rivers, estuaries, and ocean, there are
only three known spawning populations of green sturgeon, which suggests that the
species has difficulty establishing new spawning sub-populations outside of the
current populations in the Sacramento, Rogue, and Klamath rivers. As a
consequence, a natural or anthropogenic event that eliminates habitat in one of
these three river systems could dramatically reduce the range of the species.
 Regional population declines. This criterion acknowledges that population
abundance and distribution provide two of the key metrics for assessing the health of
a species. Regional population declines provide a warning signal that the species is
under stress, thus providing a stimulus for identifying the factors affecting these
populations, and revisiting the level of protection afforded to individual population hot
spots. Continued population declines can also necessitate eventual protection under
the Endangered Species Act, which generally intensifies conflicts over natural
resources.
 Distinctive habitat requirements relative to other species under consideration
for protection. This criterion extends the second, in that it is more valuable to
choose species that utilize unique habitats (especially if these habitat needs are
narrow) than to choose several different species with requirements for the same type
of habitat.
 Strong interactor. The sixth criterion indicates that particular species can
significantly influence natural communities through ecological interactions with other
species. For example, a species may serve as an important prey species for a
number of other species, such that a decline in its population can reduce the food

Final Report
Application of EFT to Complement Water Planning for Multiple Species
F - 5 | P a g e
base for other species and depress the abundance of an entire community (keystone
species). Similarly, other species can affect a community by monopolizing available
habitat and resources or by preying on a wide variety of species (e.g., the threat
posed by an introduction of northern pike (Esox lucius) in Central Valley rivers).
Other species can change the very nature of an ecosystem (e.g., Asian clam
(Potamocorbula amurensis) converting portions of the Delta estuary from a pelagic
to a benthic based ecosystem).
Step 4: Invasive species issues – deterrence or acceptance
This consideration supplements step 1, so that focal species are not limited to native
species. Because the Delta currently supports many invasive species, invasive species may
be included in one of two ways, either: (a) as species to include for the purpose of
deterrence (reducing competitive advantage vs. native species); or (b) as a species that has
achieved high economic or other value to people.
Step 5: Importance of in-Delta flow-related management actions on habitat
quality, quantity or life-stage survival
DeltaEFT emphasizes evaluation of ecological flow management actions. It is not a system
intended to simulate or predict population level consequences, food web dynamics, life-time
fate and effects of contaminant mixtures, etc. As a simplifying principle, we adopt an “all
else equal” approach, where we aim to synthesize, link and clearly present how a
representative suite of ecological targets would tend to improve or degrade if more or less
flow moved past/through/around different regions and structures in the Delta at particular
times. Clearly, other important cause-effect pathways will modulate these outcomes in
nature. Nevertheless, for the indicators in DeltaEFT it should be scientifically credible to
state that if a certain Delta flow regime were repeated year over year, the indicator would be
clearly pushed towards a more or less desirable state. In short, we are focused on variables
that will allow target habitats and focal species indicators to trend upward. Therefore, focal
habitat and species indicators that are not strongly governed by flow actions in at least one
critical life-history stage, fall outside our sphere of consideration in DeltaEFT version 1.
The flow management focused DeltaEFT will therefore serve as a companion framework
alongside other existing tools and research initiatives focused on generating resource
management advice in the Delta.
Step 6: Availability of information
This step assessed the technical feasibility and effort associated with generating the
indicator. At a minimum, we must understand the general habitat requirements and life-
history stages of the species for it to function as a focal species. Although it is preferable if
this information is specific to the Sacramento-San Joaquin River Delta study area,
knowledge of how a species interacts with its environment in a similar system is also of

Appendix F: Indicator Screening & Selection Criteria .
F - 6 | P a g e
value. Passing beyond this step requires an ability to draw a conceptual box-arrow model
for the indicator, moving from flow related management actions, to habitat forming
processes or physical habitat quality/quantity, to one or more life-history survival
mechanisms, and finally to the indicator itself.
Not re-inventing wheels: DRERIP “fat green arrows”
The CALFED Science Program has worked with the CALFED Ecosystem Restoration
Program implementing agencies (DFG, USFWS, and NOAA Fisheries) on the Delta
Regional Ecosystem Restoration Implementation Plan (DRERIP). The main DRERIP
product is a series of species, physical process, habitat and chemical stressor conceptual
models which collectively articulate the current (as of 2008) scientific understanding of
important aspects of the Sacramento-San Joaquin River Delta ecosystem. DRERIP
conceptual models are not quantitative, numeric computer models that can be “run” to
determine the effects of actions. Rather they are designed to help inform discussions
regarding expected outcomes resulting from restoration actions and document the scientific
basis for those expectations. Some of the DRERIP models should also help serve as the
basis for future development of more explicit, (semi-)quantitative models like DeltaEFT.
All DRERIP conceptual model pathways are coded according to “Importance”,
“Predictability”, and “Understanding” of the linkages between drivers and outcomes. These
definitions of importance, predictability, and understanding apply to each linkage, or cause-
effect relationship, between an individual driver and individual outcome described in the
conceptual models. The graphical forms of the conceptual models apply line color,
thickness, and style to represent these three terms.
DRERIP Importance: “The degree to which a linkage controls the outcome relative to other
drivers and linkages affecting that same outcome.”
4 = High importance: expected sustained major population level effect, e.g., the outcome addresses a key limiting factor, or
contributes substantially to a species population’s natural productivity, abundance, spatial distribution and/or diversity (both
genetic and life-history diversity) or has a landscape scale habitat effect, including habitat quality, spatial configuration
and/or dynamics.
3 = Medium importance: expected sustained minor population effect or effect on large area or multiple patches of habitat

Final Report
Application of EFT to Complement Water Planning for Multiple Species
F - 7 | P a g e
2 = Low importance: expected sustained effect limited to small fraction of population, addresses productivity and diversity in
a minor way, or limited spatial or temporal habitat effects
1 = Minimal or no importance: Conceptual model indicates little or no effect
DRERIP Understanding: “The degree to which the performance or the nature of the
outcome can be predicted from the driver.”
4 = High predictability: Understanding is high and nature of outcome is largely unconstrained by variability in ecosystem
dynamics, other external factors, or is expected to confer benefits under conditions or times when model indicates greatest
importance.
3 = Medium predictability: Understanding is high but nature of outcome is dependent on other highly variable ecosystem
processes or uncertain external factors.
OR
Understanding is medium and nature of outcome is largely unconstrained by variability in ecosystem dynamics or other
external factors
2 = Low predictability: Understanding is medium and nature of outcome is greatly dependent on highly variable ecosystem
processes or other external factors
OR
Understanding is low and nature of outcome is largely unconstrained by variability in ecosystem dynamics or other external
factors
1 = Little or no predictability: Understanding is lacking
OR
Understanding is low and nature of outcome is greatly dependent on highly variable ecosystem processes or other external
factors
DRERIP Predictability: “A description of the known, established, and/or generally agreed
upon scientific understanding of the cause-effect relationship between a single driver and a
single outcome.”
4 = High understanding: Understanding is based on peer-reviewed studies from within system and scientific reasoning
supported by most experts within system.
3 = Medium understanding: Understanding based on peer-reviewed studies from outside the system and corroborated by non
peer-reviewed studies within the system.
2 = Low understanding: Understanding based on non peer-reviewed research within system or elsewhere.
1 = Little or no understanding: Lack of understanding. Scientific basis unknown or not widely accepted.
Within this framework, “fat green arrows” represent cause-effect pathways comprised of
high-to-medium importance, understanding and predictability. Consideration of the technical

Appendix F: Indicator Screening & Selection Criteria .
F - 8 | P a g e
clarity behind DRERIP conceptual models fat green arrows was a component of our
DeltaEFT vetting process.
Step 7: Priority ranking of species
The information produced for each candidate habitat or species indicator in Steps 3, 5 and 6
facilitates a general ranking of species in this last step of the vetting process. These
rankings are nominal: high, medium, low priority. Species receiving high rankings need to
have adequate information available (Step 6), have to be officially listed or meet 3 or more
criteria listed under Step 3. High ranked indicators must also be able to provide statements
of:
 the index locations that are important;
 a clear, specific statement of the availability of any physical driving data needed from
other models to compute the indicator; and
 the acquisition of this data must be believed to be practical, and not require a
disproportionate amount of time (multiple months/years) or project resources (e.g.,
prohibitive $$ to pay for brand new hydrodynamic modeling)
Selection of the final suite of focal species therefore involved judgment, including giving
thought to the representation of different assemblages or guilds and species that utilize a
wide range of habitat types within the study area. The suite of indicators chosen for
DeltaEFT should be relevant to a broad range of species. This breadth must be balanced
with selecting too many focal species, which undermines the purpose of a focal species
approach.
Overall indicator classification nomenclature for DeltaEFT
Keeping in mind the criteria above and our experience gained in the design and
development of SacEFT, we adopted our own categorization scheme that is in several
regards similar to the DRERIP scheme (Table F.1). This indicator classification and
prioritization system is used from this point forwards in this document.
Table F.1: Classification concepts employed for the evaluation of EFT performance
indicators.
Label
Explanation
Levels
I
Importance
The degree to which a
linkage (functional
relationship) controls
the outcome relative to
other drivers and
linkages affecting that
same outcome.
4 = High: Expected sustained major population level effect, e.g., the
outcome addresses a key limiting factor, or contributes substantially to a
species population’s natural productivity, abundance, spatial distribution
and/or diversity (both genetic and life-history diversity) or has a landscape
scale habitat effect, including habitat quality, spatial configuration and/or
dynamics.
3 = Medium: Expected sustained minor population effect or effect on large
area or multiple patches of habitat.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
F - 9 | P a g e
Label
Explanation
Levels
2 = Low: Expected sustained effect limited to small fraction of population,
addresses productivity and diversity in a minor way, or limited spatial or
temporal habitat effects.
1 = Minimal: Conceptual model indicates little or no effect.
U
Understanding
(“Clarity”)
The degree to which
the performance
indicator can be
predicted from the
defined linkage
(functional relationship)
and its driver(s).
4 = High: Understanding is high and nature of outcome is largely
unconstrained by variability in ecosystem dynamics, other confounding
external factors.
3 = Medium: Understanding is high but nature of outcome is moderately
dependent on other variable ecosystem processes or uncertain external
confounding factors.
2 = Low: Understanding is moderate or low and/or nature of outcome is
greatly dependent on highly variable ecosystem processes or other
external confounding factors. Many important aspects are subject of active
ongoing research.
1 = Minimal: Understanding is lacking. Mainly subject of active ongoing
primary research.
R
Rigor
(“Predictability”)
The degree to which
the scientific evidence
supporting our
understanding of a
cause-effect
relationship (linkage) is
contested in the
scientific literature or
confounded by other
information.
4 = High: Is generally accepted, peer reviewed empirical evidence, strong
predictive power and understanding, evidence not contested or
confounded. Data in support of the functional relationship is derived from
direct Bay-Delta field observations.
3 = Medium: Strong evidence but not conclusive, only medium strength
predictive power, some evidence for competing hypotheses and/or
confounding factors. Data in support of the functional relationship is derived
from direct Bay-Delta field observations OR from field observations outside
the Bay-Delta estuary.
2 = Low: Theoretical support with some evidence, semi-quantitative
relationships, several alternative hypotheses and/or confounding factors.
Data in support of the functional relationship is derived from lab or
theoretical studies without field evidence.
1 = Minimal: Hypothesized based on theory and/or professional judgment,
purely qualitative predictions, many alternative hypotheses and/or
confounding factors. Support for the functional relationship is largely
hypothetical and based on first principles.
F
Feasibility
The degree to which
input data necessary to
calculate the proposed
performance indicator
can be delivered in a
timely fashion (without
external bottlenecks)
and the amount of effort
(relative to other
possible indicators)
needed to implement
the cause-effect linkage
in a computer model.
4 = High: Input data currently exists in a format easy to disseminate, can
be delivered readily and the effort (time) associated with implementing the
cause-effect linkage easily falls within project budget without sacrificing
other indicators.
3 = Medium: Input data currently exists (or can readily be generated by
new model runs), and while it might need some additional formatting, can
be delivered readily. The effort (time) associated with implementing the
cause-effect linkage will fall within project budget subject to prioritization
decisions elsewhere that remove some other indicators from consideration.
2 = Low: Input data does not currently exist, but can be generated through
additional analyses or external model runs. The time before this external
work could be completed is or may be uncertain. The effort (time)
associated with implementing the cause-effect linkage could be
accommodated within the project budget, but a number of other indicators
would need to be eliminated from consideration.

Appendix F: Indicator Screening & Selection Criteria .
F - 10 | P a g e
Label
Explanation
Levels
1 = Minimal: Input data does not currently exist, and it is not clear if it can
be generated through additional analyses or external model runs. The time
before this external work could be completed is unacceptably long. The
effort (time) associated with implementing the cause-effect linkage would
take up a disproportionately high amount of the project budget, and the
majority of other indicators would need to be eliminated.
P
Priority
Overall priority ranking for including in DeltaEFT: High; Medium; Low.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
G - 1 | P a g e
Appendix G: Default Relative Suitability Thresholds
On the following pages, indicator specific tables provide all SacEFT and DeltaEFT
performance indicator relative suitability threshold values for both Daily and Annual Roll-up
of indicators. These thresholds are not a statement of "absolute" suitability. Values are
fully configurable in the EFT database. The summary tables below are drawn from indicator
relative suitability threshold descriptions in ESSA (2011, 2013). We highlight cases where
there are major gradients in performance indicator thresholds. For detailed information on
these relative suitability thresholds, readers should refer to ESSA Technologies (2011,
2013).
Sacramento River (SacEFT)
Chinook/Steelhead CS1 – Area suitable spawning habitat
Suitability thresholds: Based on historical distribution of flows from 1939-2002 (64-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
430060
195486
483840
415800
 Criteria: statistical distribution
discontinuities
 “More” is better
 Units: square feet
 Flow, spawning period, habitat
preferences, affect distribution
Spring Chinook
607975
217913
448525
367675
Fall Chinook
1006472
299678
779240
506000
Late fall Chinook
520424
280581
446250
289800
Steelhead
18692
13447
24435
19186
Chinook/Steelhead CS3 – Thermal egg-to-fry survival
Suitability thresholds: Based on 90% and 95% survival
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
95
90
95
90
 Criteria: absolute values
 Units: % survival
 Common threshold for all run-
types
Spring Chinook
95
90
95
90
Fall Chinook
95
90
95
90
Late fall Chinook
95
90
95
90
Steelhead
95
90
95
90

Appendix G: Default Relative Suitability Thresholds .
G - 2 | P a g e
Chinook/Steelhead CS5 – Redd scour
Suitability thresholds: Distribution based on 5,000 and 10,000 cfs flow
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
N/A
N/A
5000
10000
Criteria: calibrated to 80RS years,
“less” is better
Units: index flow (cfs)
No daily estimate
Common physical threshold for all
run-types
Very low risk for spring- , winters
Spring Chinook
N/A
N/A
5000
10000
Fall Chinook
N/A
N/A
5000
10000
Late fall Chinook
N/A
N/A
5000
10000
Steelhead
N/A
N/A
5000
10000
Chinook/Steelhead CS6 – Redd dewatering
Suitability thresholds: Based on historical distribution of flows from 1971-2002 (32-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
3.976E-06
4.042E-05
0.015
0.03
 Criteria: statistical distribution
discontinuities, “less” is better
 Daily units: proportion stranded
 Roll-up units: cumulative
proportion stranded
 Flow, spawning period, habitat
preferences, affect distribution
 Very low risk for winter
 Higher sensitivity/risk for Late-fall
run Chinook.
Spring Chinook
6.184E-05
7.333E-04
0.07
0.13
Fall Chinook
1.597E-05
1.910E-04
0.05
0.09
Late fall Chinook
1.336E-05
1.846E-04
0.12
0.22
Steelhead
1.181E-05
1.428E-04
0.10
0.17
Chinook/Steelhead CS2 – Area suitable rearing habitat
Suitability thresholds: Based on tercile distribution of flows from 1939-2002 (64-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
32532
9662
7497758
7350129
 Criteria: statistical distribution,
terciles, “more” is better
 Daily units: square feet
 Roll-up units: cumulative square
feet
 Flow, number of reaches affect
distribution
Spring Chinook
98352
29539
18885832
13958748
Fall Chinook
48166
17573
14717925
10624775
Late fall Chinook
43604
13801
10107957
9109028
Steelhead
123583
30142
47816590
41352564
Chinook/Steelhead CS4 – Juvenile Stranding
Suitability thresholds: Based on tercile distribution of flows from 1971-2002 (32-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
3.992E-05
3.017E-04
0.0516
0.1112
 Criteria: statistical distribution
terciles, “less” is better
 Daily units: index
 Roll-up units: cumulative index
 Flow, number of reaches affect
distribution
 Late-fall may be more sensitive-
responsive
Spring Chinook
1.279E-04
9.165E-04
0.1199
0.2149
Fall Chinook
9.742E-05
5.464E-04
0.1065
0.2034
Late fall Chinook
5.109E-05
1.963E-04
0.0551
0.0710
Steelhead
1.417E-04
1.628E-03
0.3261
0.4141

Final Report
Application of EFT to Complement Water Planning for Multiple Species
G - 3 | P a g e
Bank swallow BASW1 – suitable habitat potential
Suitability thresholds: Terciles based on historical distribution of flows from 1940-1994 (55-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Habitat potential
N/A
N/A
36882
27000
 Criteria: statistical distribution
discontinuities, “more” is better
 Units: meters suitable habitat
 No daily estimate
Bank swallow BASW2 – inundation/sloughing risk
Suitability thresholds: Flow thresholds based on expert opinion
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Nesting Peak Flow
0.1
0.01
 2
 1 (zero)
 “less” is better
 Daily units: flow suitability index
 Roll-up units: count of locations
assigned Good rating within a
year.
Green sturgeon GS1 – Egg-to-larval survival
Suitability thresholds: Based on 90% and 95% survival
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Thermal Egg Mortality
N/A
N/A
95
90
 “less” is better
 Units: % mortality
Fremont cottonwood FC1 – cottonwood seedling initiation
Suitability thresholds: Terciles based on historical distribution of flows from 1943-2004 (62-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Riparian Initiation Success
N/A
N/A
53
36
 Criteria: thresholds based on
expert opinion and observation
of Good initiation years, “more”
is better
 Units: count of cross section
nodes with surviving stems or
seedlings.
 No daily estimate
Fremont cottonwood FC2 – scour risk after initiation
Suitability thresholds: 80,000 cfs and 90,000 cfs scour flows based on expert opinion
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Riparian Scour Risk
N/A
N/A
80000
90000
 Criteria: thresholds based on
expert opinion of scour events,
“less” is better
 Units: flow (cfs)
 No daily estimate

Appendix G: Default Relative Suitability Thresholds .
G - 4 | P a g e
Large woody debris LWD1 – old vegetation recruited to river
Suitability thresholds: Terciles based on historical distribution of flows from 1940-1994 (55-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Large Woody Debris
recruitment
N/A
N/A
53333
11233
 “more” is better
 Units: square meters riparian
forest eroded to mainstem
Sacramento River having forests
taller than 34 ft. (height class 4
or higher).
 No daily estimate
San Joaquin-Sacramento Delta (DeltaEFT)
Chinook/Steelhead CS7 – Juvenile development in Yolo Bypass
Suitability thresholds: Based on historical distribution of flows from 2002-2007 (6-yrs) and NAA-Current
scenario from 1976-1991 (22-yrs) [total 28-yrs]
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
32
24
32
24
 Criteria: statistical distribution
discontinuities, “more” is better
 Units: % weight gain
 Flow, weir notching affect
residency
Spring Chinook
32
24
32
24
Fall Chinook
23
16
23
16
Late fall Chinook
32
24
32
24
Steelhead
23
16
23
16
Chinook/Steelhead CS9 – Juvenile predation risk
Suitability thresholds: Based on historical distribution of flows from 2002-2007 (6-yrs) and NAA-Current
scenario from 1976-1991 (22-yrs) [total 28-yrs]
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
12
16
12
16
 Criteria: statistical distribution
discontinuities, “less” is better
 Units: residency days
 High flow reduces exposure
Spring Chinook
12
16
12
16
Fall Chinook
12
16
12
16
Late fall Chinook
12
16
12
16
Steelhead
12
16
12
16
Chinook/Steelhead CS10 – Juvenile temperature stress
Suitability thresholds: Based on historical distribution of flows from 2002-2007 (6-yrs) and NAA-Current
scenario from 1976-1991 (22-yrs) [total 28-yrs]
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Winter Chinook
39
53
39
53
 Criteria: statistical distribution
discontinuities, “less” is better
 Units: degree-days difference
from physiol. optimum
 Higher flows better (cooler), but
trade-off with weight gain (time)
Spring Chinook
68
100
68
100
Fall Chinook
68
100
68
100
Late fall Chinook
39
53
39
53
Steelhead
68
100
68
100

Final Report
Application of EFT to Complement Water Planning for Multiple Species
G - 5 | P a g e
Splittail smelt SS1 – Proportion of maximum spawning habitat
Suitability thresholds: Terciles based on historical data from 1989-2010 (22-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Spawning Success
0.05
0.02
0.05
0.02
 “more” is better
 Units: proportion of maximum
habitat area
Delta smelt DS1 – Spawning success
Suitability thresholds: Terciles based on historical distribution of flows from 2002-2010 (9-yrs)
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Spawn Success
N/A
N/A
36
25
 Criteria: statistical distribution,
terciles, “more” is better
 Units: longest duration of optimal
days
Delta smelt DS2 – Habitat suitability index
Suitability thresholds: Based on literature value (Delta smelt BiOp 2008) for X2 at 74 and 81km
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Habitat Quality Index
N/A
N/A
7261
4835
 “more” is better
 Units: N/A
Delta smelt DS4 – Larval & juvenile entrainment
Suitability thresholds: Terciles based on historical distribution of flows from 1998-2000 (9-yrs) and
NAA-Current flows from 1975 to 1991 (17-yrs) [total 26-yrs]
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Entrainment Risk
N/A
N/A
0.04
0.1
 “less” is better
 Units: %
Longfin smelt LS1 – Abundance
Suitability thresholds: Terciles based on historical distribution of flows from 2002-2008 (7-yrs) and
NAA-Current flows from 1975 to 1991 (17-yrs) [total 26-yrs]
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
Abundance Index
N/A
N/A
725
225
 Criteria: statistical distribution,
terciles, “more” is better
 Units: N/A

Appendix G: Default Relative Suitability Thresholds .
G - 6 | P a g e
Invasive deterrence - Suppression
Suitability thresholds: Uses literature values and expert opinion
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
ID1: Egeria densa
N/A
N/A
> 10 for 3+
months
> 5 for 2+
months
 Units: average salinity (‰)
 Location roll-up: Annual
performance is based on the
most important region
 Most important region: ‘Chipps
Island To Oakley’ for ID1 and
ID3, ‘680 Bridge to Chipps
Island’ for ID2
ID2: Corbula
N/A
N/A
< 3 or  30
for 3+
months
< 5 or  25
for 2+
months
ID3: Corbicula
N/A
N/A
> 12 for 3+
months
> 7 for 2+
months
Tidal Wetlands
Suitability thresholds:
TW1: Terciles based on historical distribution of stage from 2002-2006 (5-yrs) and NAA-Current stage
from 1975 to 1991 (17-yrs) [total 22-yrs]
TW2: Terciles based on historical distribution of stage from 1997-2010 (14-yrs) and NAA-Current stage
from 1975 to 1991 (17-yrs) [total 31-yrs]
Daily
Roll-up
Notes
Good-Fair
Fair-Poor
Good-Fair
Fair-Poor
TW1: Brackish
N/A
N/A
7600000
7450000
 “more” is better
 Units: m2
TW2: Freshwater
N/A
N/A
2960000
2780000

Final Report
Application of EFT to Complement Water Planning for Multiple Species
H - 1 | P a g e
Appendix H: Master Register of EFT Input and Output Locations
This table shows all input and output locations used in the SacEFT and DeltaEFT ecoregions. EFT Short Names are intended to provide concise labels for figures, tables and text. Gauge or Common Name
locations refer to point locations, usually used as input to EFT and represented either by a physical gauge or alternatively, by a modeled location within a simulation system such as CALSIM, DSM2 or EFT.
Specifically, SacEFT currently uses either USRDOM or SRWQM daily modeled flows. DeltaEFT currently uses DSM2 for flows, electroconductivity, water temperature and stage. Daily water temperatures for
SacEFT are provided by SRWQM. Location names assigned by DSM2 and CDEC are not fully standardized. Shading and Dots shown at some locations indicate gauges (actual or simulate) used as input to an
indicator. Letter Codes for input variables for the indicators are: F=flow; T=temperature; E=electroconductivity; S=stage. Cells marked with shading only indication locations used as an output for the indicator.
Regional and Route locations are collections of modeled points used to aggregate detailed location-based EFT output into meaningful geographic units. River Codes: FAL - False River; MID - Middle River; MOK -
Mokelumne River; OLD - Old River; SAC - Sacramento River; SAN - San Juan River. Slough Codes: BAS - Barker Slough; CAS - Cache Slough; CBS - Chadbourne Slough; DUS - Dutch Slough; GES -
Georgiana Slough; GYS - Goodyear Slough; MZS - Montezuma Slough; PRS - Piper Slough; SUS - Sutter Slough; STS - Steamboat Slough; SNS - Suisan Slough; YOL - Yolo Bypass.
SacEFT Ecoregion Locations
EFT Short Name
Gauge or Common Name Location
River
Code
RM
DSM2
Name
CDEC
Name
Gauge
Owner
Native Code
CS1
CS3
CS6
CS5
CS4
CS2
GS1
BASW1
BASW2
FC1
FC2
LWD1
F
T
T
F
F
F
F
T
F
F
F
F
F
Keswick (RM301)
SACRAMENTO R A KESWICK CA
SAC
301
USGS
11370500
●
●
●
●
●
●
●
Clear Crk (RM289)
Clear Creek
SAC
288.9
●
●
●
●
●
●
●
Cow Crk (RM280)
Cow Creek
SAC
280.2
●
●
●
●
●
●
●
Balls Fy (RM277)
SACRAMENTO R A BALLS FERRY
SAC
277
CDEC
402507122113201
●
●
●
●
●
●
●
Cottonwood Crk (RM273)
Cottonwood Creek
SAC
273.3
●
●
●
●
●
●
●
Jellys Fy (RM267)
Jelly's Ferry
SAC
267
●
●
●
●
●
●
●
Bend Bridge (RM260)
SACRAMENTO R AB BEND BRIDGE NR RED BLUFF CA
SAC
260
USGS
11383730
●
●
●
●
●
●
●
●
Red Bluff (RM243)
SACRAMENTO R NR RED BLUFF CA
SAC
243
USGS
11378000
Hamilton City (RM199)
SACRAMENTO R NR HAMILTON CITY CA
SAC
199
USGS
11383800
●
●
●
●
●
●
Butte City (RM168)
SACRAMENTO R A BUTTE CITY CA
SAC
168
USGS
11389000
●
●
Vina-Woodson
SACRAMENTO R A VINA BRIDGE NR VINA CA (Woodson Bridge)
SAC
???
USGS
11383730
●
●
●
●
●
Tisdale
SAC_AT_TISDALE
SAC
???
Colusa (RM143)
SACRAMENTO R A COLUSA CA
SAC
143
USGS
11389500
EFT Short Name
Region or Route Location
River
Code
RM
DSM2
Name
CDEC
Name
Gauge
Owner
Native Code
BASW - RM168
BASW2 - RM168
SAC
168
BASW - RM197
BASW2 - RM197
SAC
197
BASW - RM242
BASW2 - RM242
SAC
242
BASW - RM292
BASW2 - RM292
SAC
292
CS - RM217-242
CS Reach 2
SAC
217-242
CS - RM252-272
CS Reach 3
SAC
252-272
CS - RM272-280
CS Reach 4
SAC
272-280
CS - RM280-298
CS Reach 5
SAC
280.2 298.5
CS - RM298-302
CS Reach 6
SAC
298.5-302
FC - RM164
Fremont - HR164
SAC
164
FC - RM165
Fremont - HR165
SAC
165
FC - RM172
Fremont - HR172
SAC
172
FC - RM185
Fremont - HR185.5
SAC
185.5
FC - RM195
Fremont - HR195.75
SAC
195.75

Appendix H: Master Register of EFT Input and Output Locations
H - 2 | P a g e
FC - RM199
Fremont - HR199.75
SAC
199.75
FC - RM206
Fremont - HR206
SAC
206
FC - RM208
Fremont - HR208.25
SAC
208.25
FC - RM172
Fremont - RM172
SAC
172
FC - RM183
Fremont - RM183
SAC
183
FC - RM192
Fremont - RM192
SAC
192
Ord-Butte MM Bnd 1
Ord Bend - Butte City - Bend 1
SAC
170-185
Ord-Butte MM Bnd 2
Ord Bend - Butte City - Bend 2
SAC
170-185
Ord-Butte MM Bnd 3
Ord Bend - Butte City - Bend 3
SAC
170-185
Ord-Butte MM Bnd 4
Ord Bend - Butte City - Bend 4
SAC
170-185
Ord-Butte MM Bnd 5
Ord Bend - Butte City - Bend 5
SAC
170-185
Ord-Butte MM Bnd 6
Ord Bend - Butte City - Bend 6
SAC
170-185
Ord-Butte MM Bnd 7
Ord Bend - Butte City - Bend 7
SAC
170-185
Ord-Butte MM Bnd 8
Ord Bend - Butte City - Bend 8
SAC
170-185
Ord-Butte MM Bnd 9
Ord Bend - Butte City - Bend 9
SAC
170-185
Ord-Butte MM Bnd 10
Ord Bend - Butte City - Bend 10
SAC
170-185
Ord-Butte MM Bnd 11
Ord Bend - Butte City - Bend 11
SAC
170-185
Hamilton-Ord MM Bnd 1
Hamilton City - Ord Bend - Bend 1
SAC
185-201
Hamilton-Ord MM Bnd 2
Hamilton City - Ord Bend - Bend 2
SAC
185-201
Hamilton-Ord MM Bnd 3
Hamilton City - Ord Bend - Bend 3
SAC
185-201
Hamilton-Ord MM Bnd 4
Hamilton City - Ord Bend - Bend 4
SAC
185-201
Hamilton-Ord MM Bnd 5
Hamilton City - Ord Bend - Bend 5
SAC
185-201
Hamilton-Ord MM Bnd 6
Hamilton City - Ord Bend - Bend 6
SAC
185-201
Hamilton-Ord MM Bnd 7
Hamilton City - Ord Bend - Bend 7
SAC
185-201
Hamilton-Ord MM Bnd 8
Hamilton City - Ord Bend - Bend 8
SAC
185-201
Hamilton-Ord MM Bnd 9
Hamilton City - Ord Bend - Bend 9
SAC
185-201
Hamilton-Ord MM Bnd 10
Hamilton City - Ord Bend - Bend 10
SAC
185-201
Hamilton-Ord MM Bnd 11
Hamilton City - Ord Bend - Bend 11
SAC
185-201
Hamilton-Ord MM Bnd 12
Hamilton City - Ord Bend - Bend 12
SAC
185-201
Vina-Wdsn MM Bnd 1
MM Segment 3 - Vina - Bend 1
SAC
201-218
Vina-Wdsn MM Bnd 2
MM Segment 3 - Vina - Bend 2
SAC
201-218
Vina-Wdsn MM Bnd 3
MM Segment 3 - Vina - Bend 3
SAC
201-218
Vina-Wdsn MM Bnd 4
MM Segment 3 - Vina - Bend 4
SAC
201-218
Vina-Wdsn MM Bnd 5
MM Segment 3 - Vina - Bend 5
SAC
201-218
Vina-Wdsn MM Bnd 6
MM Segment 3 - Vina - Bend 6
SAC
201-218
Vina-Wdsn MM Bnd 7
MM Segment 3 - Vina - Bend 7
SAC
201-218
Vina-Wdsn MM Bnd 8
MM Segment 3 - Vina - Bend 8
SAC
201-218
Vina-Wdsn MM Bnd 9
MM Segment 3 - Vina - Bend 9
SAC
201-218
Vina-Wdsn MM Bnd 10
MM Segment 3 - Vina - Bend 10
SAC
201-218
Vina-Wdsn MM Bnd 11
MM Segment 3 - Vina - Bend 11
SAC
201-218
Vina-Wdsn MM Bnd 12
MM Segment 3 - Vina - Bend 12
SAC
201-218
Vina-Wdsn MM Bnd 13
MM Segment 3 - Vina - Bend 13
SAC
201-218
Vina-Wdsn MM Bnd 14
MM Segment 3 - Vina - Bend 14
SAC
201-218

Final Report
Application of EFT to Complement Water Planning for Multiple Species
H - 3 | P a g e
DeltaEFT Ecoregion Locations
EFT Short Name
Gauge or Common Name Location
River
Code
RM
RKI
DSM2
Name
CDEC
Name
Gauge
Owner
Native Code
CS7
CS9
CS10
DS1
DS2
DS4
SS1
LF1
TW1
TW2
ID1
ID2
ID3
F
T
F
F
T
T
E
E
F
F
E
S
E
S
E
E
E
Knight
BUTTE CITY and SUTTER BYPASS
SAC
168
KNL
USGS
11389000
●
●
Verona
SACRAMENTO R A VERONA CA
SAC
VON
USGS
11425500
●
Sacramento (IST178)
SACRAMENTO R A SACRAMENTO CA
SAC
59.5
178
RSAC178
IST
USGS
11447500
●
Freeport (FPT155)
SACRAMENTO R A FREEPORT CA
SAC
155
RSAC155
FPT
USGS
11447650
●
Hood (SRH142)
SACRAMENTO RIVER AT HOOD
SAC
142
RSAC142
SRH
CDEC
382205121311300
●
●
Above DCC (SDC128)
SACRAMENTO R AB DELTA CROSS CHANNEL CA
SAC
128
RSAC128
SDC
USGS
11447890
●
●
●
●
●
Sac blw Georgina (GSS123)
SACRAMENTO R BL GEORGIANA SLOUGH CA
SAC
123
RSAC123
GSS
USGS
11447905
●
●
●
●
●
●
●
Rio Vista (RVB101)
SACRAMENTO R A RIO VISTA CA
SAC
101
RSAC101
RVB,RIV
USGS
11455420
●
●
●
●
●
●
●
Ryer Isld
CACHE SLOUGH A RYER ISLAND
CAS
CACHE_RYER
USGS
11455350
●
●
Emmaton (EMM92)
EMMATON (USBR)
SAC
92
RSAC092
EMM
●
●
●
●
●
●
●
●
●
●
●
Collinsville (CSE81)
COLLINSVILLE ON SACRAMENTO RIVER
SAC
81
RSAC081
CSE
●
●
●
●
●
●
Sutter Sl (SBP)
SUTTER BYPASS AT RD 1500 PUMP
SUS
SUT_US_MIN
SBP
●
Steamboat Sl
Steamboat Slough
STS
STMBT_S
●
Pittsburg (PTS77)
SAN FRANCISCO BAY A PITTSBURG CA
SAC
77
RSAC077
PTS
CDEC
380300121524201
●
●
●
●
●
●
●
Mallard (MAL75)
SUISUN BAY A MALLARD IS CA
SAC
75
RSAC075
MAL
USGS
11185185
●
●
●
●
●
●
●
●
●
●
DCC
Delta Cross Channel
SAC
DCC
●
●
●
●
●
Georgiana Sl (GGS)
GEORGIANA SLOUGH NR SACRAMENTO R
GES
50
GEORG_SL
GGS
USGS
11447903
●
●
●
●
Fremont Weir (FRE244)
FREMONT WEIR SPILL TO YOLO BYPASS NR VERONA CA
SAC
244
RSAC244
FRE
USGS
11391021
●
●
Sacramento Weir (182)
SACRAMENTO WEIR SPILL TO YOLO
SAC
182
RSAC182
USGS
11426000
●
●
Walnut Grove (19)
N MOKELUMNE NR WALNUT GROVE CA
NMK
19
RMKL019
USGS
11336685
●
●
●
●
Little Potato (STI8)
LITTLE POTATO SLOUGH NR TERMINOUS CA
SMK
8
RSMKL008
STI
USGS
11336800
●
●
●
●
Port Chicago (PCT64)
PORT CHICAGO
SAC
64
RSAC064
PCT
●
●
●
●
●
●
●
●
Jersey Point (JER18)
SAN JOAQUIN R A JERSEY POINT CA
SAN
18
RSAN018
JER
USGS
11337190
●
●
●
●
●
Antioch (ANH7)
SAN JOAQUIN R A ANTIOCH CA
SAN
7
RSAN007
ANH
USGS
11337200
●
●
●
●
●
Tracy (MTB27)
MIDDLE RIVER AT TRACY BLVD
MID
27
RMIS027
MTB
●
●
Rough & Ready (RRI58)
ROUGH AND READY ISLAND
SAN
58
RSAN058
RRI
●
●
Martinez (MRZ54)
CARQUINEZ STRAIT A MARTINEZ CA
SAC
54
RSAC054
MRZ
USGS
11182450
●
●
●
●
●
Venice Isld (VNI43)
SAN JOAQUIN R A VENICE ISLAND - TIDE GAUGE CA
SAN
43
RSAN043
VNI
CDEC
380301121294500
●
●
San Andreas (SAL32)
SAN ANDREAS LANDING
SAN
32
RSAN032
SAL
●
●
●
●
●
●
●
Bacon Isld (BAC24)
OLD R A BACON ISLAND CA
OLD
24
ROLD024
OBI,BAC
USGS
11313405
●
●
●
Borden (VIC23)
MIDDLE R AT BORDEN HWY NR TRACY CA
MID
23
RMID023
VIC
USGS
11312674
Stockton (SJG)
SAN JOAQUIN R BL GARWOOD BR A STOCKTON
SAN
SJG
USGS
11304810
●
●
Middle R (MDM15)
MIDDLE R AT MIDDLE RIVER CA
MID
15
RMID015
MDM
USGS
11312676
●
●
●
●
●
●
Holland Cut (HLL14)
HOLLAND CUT NR BETHEL ISLAND CA
OLD
14
ROLD014
HLL
USGS
11313431
●
Beldon (BDL11)
BELDON LANDING
MZS
11
SLMZU011
BDL
●
●
●
●
●
●
Steamboat-Sutter (SSS11)
DWR-CD 1479, 11km up Steamboat Slough, below Sutter Slough
SUS
11
SLSBT011
SSS
●
●
●
●
Farrar (FRP9)
FARRAR PARK
DUS
9
SLDUT009
FRP
●
●
●
●
Barker (BKS2)
BARKER SLOUGH PUMPING PLANT (KG000000)
BAS
2
SLBAR002
BKS
●
●
●
Bethel Isld (BET3)
BETHEL ISLAND
PRS
3
SLPPR003
BET
Goodyear (GYS3)
GOODYEAR SLOUGH
GYS
3
SLGYR003
GYS
Sunrise (SNC2)
SUNRISE CLUB
CBS
2
SLCBN002
SNC
●
National Steel (NSL25)
NATIONAL STEEL
MZS
25
SLMZU025
NSL
●
Volanti (VOL12)
VOLANTI
SNS
12
SLSUS012
VOL
●
Yolo
YOLO BYPASS NR WOODLAND CA
YOL
BYOLO040
YBY
USGS
11453000
Chipps
SUISUN BAY AT CHIPPS ISLAND CA
SAC
0
CDEC
380245121551001
Webb
USBR station, False River at Webb Tract
FAL
8
RFAL008

Appendix H: Master Register of EFT Input and Output Locations
H - 4 | P a g e
Oakley?
CONTRA COSTA CN NR OAKLEY CA
6
CHCC006
CNT
USGS
11337000
Holt
TURNER CUT NR HOLT CA
CFTRN000
USGS
11311300
Turner
USGS SJR-TC, San Joaquin River between Turner Cut and Columbia Cut
SAN
46
RSAN046
EFT Short Name
Region or Route Location
River
Code
RM
RKI
DSM2
Name
CDEC
Name
Gauge
Owner
Native Code
Interior Rgn
Oakley To Interior Delta
Oakley Rgn
Chipps Island to Oakley
Suisun Rgn
680 Bridge to Chipps Island
Big Break Wtld
Big Break Wetland
Montezuma Wtld
Montezuma Slough Wetland
Ryer Wtld
Ryer Island Wetland
Skinkee Wtld
Skinkee Tract Wetland
Grizzly Wtld
Grizzly Bay Wetland
Hood-RioVista Rte
Sacramento R - Hood to Rio Vista
Knight-RioVista Rte
Sacramento R - Knights Ldg - Rio Vista
Knight-Frmt Weir Rte
Sacramento R - Knights Ldg - Yolo via Fremont - Rio Vista
Knight-Sac Weir Rte
Sacramento R - Knights Ldg - Yolo via Sacramento Weir - Rio Vista
Western B1 Rte
Eastern Delta - through Sutter Slough to Suisun (B1)
Western B2 Rte
Eastern Delta - through Steamboat Slough to Suisun (B2
Eastern C Rte
Eastern Delta - through Georgiana Slough to Suisun (C)
Eastern D Rte
Eastern Delta - through Georgiana Slough to Suisun (D)
Eastern E1 Rte
Eastern Delta - through DCC, east branch to Georgiana to Suisun (E1)
Eastern E2 Rte
Eastern Delta - through DCC, west branch to Georgiana to Suisun (E2)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 1 | P a g e
Appendix I: EFT Derived Flow Needs
The tables in this Appendix provide a compressed summary of the alternative formulations
of EFT derived ecological flow needs (rule-sets). As described in section 2.9.1, a
fundamental step is analysis of flow traces (or water temperature or other physical driver
results) associated with favorable suitability. Leveraging the EFT relational database, data
analysis exercises like those shown in Figure 2.19 help the EFT investigators identify flow
patterns and timing that are correlated with favorable outcomes for each species and
performance indicator.
Based on flow (or other physical) trace analysis and conceptual model interpretation, criteria
and rule-sets are summarized using the standardized format shown in the series of tables
below. These tables identify:
1. The focal species and indicator.
2. The objective and rationale for the indicator.
3. The critical life-history timing.
4. The key index locations that can be used to support the indicator.
5. A short description of the target ecological flow variables, target condition(s).
6. Additional details and other triggers (e.g., water year type).
7. The frequency of recurrence (many functional flow targets need not be achieved
every year).
8. A short summary of potential conflicts and trade-offs with other objectives and EFT
performance indicators.
9. List of foundational science references (taken from SacEFT and DeltaEFT Records
of Design).
The standard design of these tables enables readers unfamiliar with the details to more
quickly compare and contrast different ecological flow guidelines. Our EFT eco rule-set
analyses show that rules for driving physical data are sometimes clearly correlated with the
favorable outcome, while others such as redd dewatering (CS5) have no obvious simple
relationship with flow.

Appendix I: EFT Derived Flow Needs
I - 2 | P a g e
CS1-6, Winter-run Chinook
The goal of this action is to provide a strong cohort year for winter-run Chinook, attempting to provide monthly minimum and maximum average daily flows
that will satisfy the requirements of all performance indicators (CS1-CS6). Winter-run Chinook are selected since they have the highest threat status of the
five salmonid run types. The table shows draft average flows (kCFS) for each month that satisfy the CS1 – CS6 criteria for winter-run Chinook. There are no
constraints for CS3, CS6 and CS5. Data are taken from more detailed analyses of each run-type and from study of flow-traces.
Sacramento River
Chinook & Steelhead (Winter Run)
Indicator
CS1-CS6
Integrated
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Range
12
12
CS1: Spawning WUA, Max
5
5
CS1: Spawning WUA, Min
CS3: Thermal Egg Mortality, no constraint
CS6: Redd Dewatering, no constraint
CS5: Redd Scour, no constraint
CS4: Juvenile Stranding, Max no constraint
7
7
7
7
7
CS4: Juvenile Stranding, Min
8
8
8
8
8
CS2: Rearing WUA , Max
3.5
3.5
3.5
3.5
3.5
CS2: Rearing WUA, Min
8
8
8
12
12
8
8
Integrated: Max
7
7
7
5
5
7
7
Integrated: Min
Location
Sacramento River below Clear Creek (RM290)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 3 | P a g e
Sacramento River
Bank Swallow
Indicator
BASW1
Habitat potential
Objective & Rationale
Maximize availability of suitable nesting habitat
(SacEFT Design Document Section 4.3.3, pp. 86-92)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Location
Hamilton City (RM199, SACRAMENTO R NR HAMILTON CITY CA, 11383800)
Variable & Condition
<N WYT: Release a volume of 0.28 MAF above 18,000 cfs if target not met in preceding two years
≥N WYT: Release a volume of 2.8 MAF above 18,000 cfs if target not met in preceding two years
See Additional Details below
Other Triggers
Attempt for WYT < N if target not met in preceding two years
Recurrence
At least every 3 years
Potential conflicts & trade-offs
Avoid during Bank Swallow nesting period (BASW2).
Reservoir water supply management (draw-down/drought management).
BASW1 also benefits Large Woody Debris recruitment.
References
Stillwater Sciences (2007)

Appendix I: EFT Derived Flow Needs
I - 4 | P a g e
Sacramento River
Bank Swallow
Indicator
BASW1
Habitat potential
Additional Details
The daily volume in cubic feet is calculated as the volume released above the 18.000cfs threshold:
 








 400,86000,18
000,180
scfsQ
cfsQif
eDailyVolum
The Cumulative Volume over the water year is the sum of all Daily Volumes converted to MAF.
MAF
ft
10 × 2.3 3
11-
365
1
 
ii
eDailyVolumVolumeCumulative
Example of cumulative volume above threshold of 18,000 cfs for water year 1989. The continuous blue line shows
daily flow, the stippled blue line marks the threshold and the filled blue areas show the daily volume released above
the threshold. The continuous black line shows the cumulative volume of water released once the threshold has
been reached; which in this year exceeds the threshold of 0.28 MAF for dry and critical years, shown by the stippled
black line.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 5 | P a g e
Sacramento River
Bank Swallow
Indicator
BASW2
Peak flow during nesting period
Objective & Rationale
Minimize risk of nest inundation and bank sloughing during nesting
(SacEFT Design Document Section 4.3.3, pp. 92-95)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Location
Hamilton City (RM199, SACRAMENTO R NR HAMILTON CITY CA, 11383800)
Variable & Condition
Q ≤ 50,000 cfs
Other Triggers
–
Recurrence
tbd
Potential conflicts & trade-offs
Reservoir flood storage management
References
Stillwater Sciences (2007)

Appendix I: EFT Derived Flow Needs
I - 6 | P a g e
Sacramento River
Fremont Cottonwood
Indicator
FC1
Relative initiation success
Objective & Rationale
Periodically provide recession flows that support areas for riparian initiation (as indexed by Fremont cottonwoods) in
the target zone for initiation (i.e., riparian channel bank areas above 8,500 cfs elevation + 3ft). Seeds that land on
non-inundated ground begin to grow roots downward from the elevation at which they were deposited. While
accounting for average capillary fringe height along the cross section (e.g., 30 cm), the rate of stage decline
determines whether the cottonwood’s root is able to maintain contact with the water table. As soon as the root
depth is above the surface elevation + capillary fringe height, the seedling becomes non-viable (dies). Hence for
successful initiation, the rate of stage decline cannot occur at a rate faster than the taproot growth rate (we use a
taproot growth rate of 22 mm/day). In SacEFT, Cottonwood seedlings whose roots reach a depth of 50 cm are
assumed to be successful in reaching some type of ephemeral groundwater moisture sufficient to keep them alive
through the remainder of their first year. (SacEFT Design Document Section 4.3.4, pp. 96-100.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Location
Hamilton City (RM199, SACRAMENTO R NR HAMILTON CITY CA, 11383800)
Butte City (RM168, SACRAMENTO R A BUTTE CITY CA, 11389000)
Variable & Condition
76 out of 108 days of flows (70%) at Hamilton City (RM199) between Apr-15 (105) and July-31 (212) equal or exceed
flows predicted by the following equation:
Min. target Q (cfs) = 0.5971x2 - 243.962x + 34399 (where x = Julian day)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 7 | P a g e
Other Triggers
–
Recurrence
At least once every 8 years.
Potential conflicts & trade-offs
References
Mahoney and Rood 1998; Roberts et al. 2002; Roberts 2003; HEC-RAS supplemented stage-discharge relations;
Alexander 2004
0
5000
10000
15000
20000
25000
30000
35000
40000
'Oct-10
'Oct-20
'Oct-30
'Nov-09
'Nov-19
'Nov-29
'Dec-09
'Dec-19
'Dec-29
'Jan-08
'Jan-18
'Jan-28
'Feb-07
'Feb-17
'Feb-27
'Mar-08
'Mar-18
'Mar-28
'Apr-07
'Apr-17
'Apr-27
'May-07
'May-17
'May-27
'Jun-06
'Jun-16
'Jun-26
'Jul-06
'Jul-16
'Jul-26
'Aug-05
'Aug-15
'Aug-25
'Sep-04
'Sep-14
'Sep-24
Discharge (cfs)
Fremont Cottonwood success initiation years (green lines) and min.
recommended target recession f low [Hamilton City index point
(RM199, Sacramento NR Hamilton City, 11383800)]
y = 0.5971x2-243.962x + 34399
R² = 0.9988
7500
10000
12500
15000
17500
20000
105
110
115
120
125
130
135
140
145
150
155
160
165
170
175
180
185
190
195
200
205
210
Discharge (cfs)
Julian Day
Fremont Cottonwood initiation --min. flows Hamilton City
index point (RM199, Sacramento NR Hamilton City, 11383800)

Appendix I: EFT Derived Flow Needs
I - 8 | P a g e
Sacramento River
Fremont Cottonwood
Indicator
FC2
Young of year cottonwood seedling scour risk
Objective & Rationale
Based on recommendations from the SacEFT refinements workshop, a second performance indicator has been
included in SacEFT v.2 to capture the effects of scour events following riparian initiation. The rationale for including
this second performance indicator is that gains made after successful riparian initiation (FC1 success) are moot if the
seedlings are scoured out in the following year, i.e., there is no point expending large volumes of water to achieve
riparian initiation, and then wiping out these benefits in year t+1 with a scouring flow. (SacEFT Design Document
Section 4.3.4, pp. 96-102.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Location
Hamilton City (RM199, SACRAMENTO R NR HAMILTON CITY CA, 11383800)
Butte City (RM168, SACRAMENTO R A BUTTE CITY CA, 11389000)
Variable & Condition
From August-1 in any year t that has successfully met the FC1 criterion, until July-31 year t+1, flows at Hamilton City
(RM199) never exceed 85,000 cfs.
Other Triggers
Only relevant in year following successful achievement of FC1 flows (i.e., want to apply meaningful weighting to this
criterion based on state of FC1).
Recurrence
n/a (minimize / avoid following successful FC1 initiation year)
Potential conflicts & trade-offs
Impossible to avoid during uncontrolled flood situations.
References
Recommendations from Riparian ecologists at the SacEFT v.1 peer review and refinements workshop (see SacEFT
Design Document Section 4.3.4, pp. 96-102).

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 9 | P a g e
Sacramento River
Chinook & Steelhead
Indicator
CS1
Spawning Habitat (WUA)
Objective & Rationale
Spawning Weighted Usable Area (WUA) is calculated using daily cohorts of spawners based on bathymetry and 2D
flow modeling at up to 5 intensively measured river segments. Gauges provide daily average flow over the spawning
period for each location and run-type, predicting WUA (ft2). The indicator accounts for spawning area only:
subsequent exposure to thermal mortality or redd dewatering is not included. (SacEFT Design Document Section
4.3.1, pp.54-59.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Sacramento River below Clear Creek (RM290)
Variable & Condition
6,000 < Qavg < 10,000 cfs (weak R band at high Q)
Spring
4,000 < Qavg < 8,000 cfs (R bands at low, high Q)
Fall
3,500 < Qavg < 8,000 cfs (R band at high Q)
Late-fall
5,000 < Qavg < 12,000 cfs (R bands at low, high Q)
Winter
3,500 < Qavg < 10,000 cfs (R band at high Q)
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
4
3.5
3.5
3.5
5
5
6
Qmin kcfs
8
8
8
10
12
12
10
Qmax kcfs
Other Triggers
–
Recurrence
2 out of 3 years
Potential conflicts & trade-offs
References
Vogel and Marine (1991), USFWS (2003, 2005a)

Appendix I: EFT Derived Flow Needs
I - 10 | P a g e
Sacramento River
Chinook & Steelhead
Indicator
CS6
Redd dewatering
Objective & Rationale
Redd dewatering is modeled using daily declining changes in discharge over the egg development period for each
location and run-type combination, to calculate estimates of proportional redd loss. The indicator is based on the
spawning calendar (CS1) and temperature-drive emergence (CS3), conditioned on previous dewatering events.
(SacEFT Design Document Section 4.3.1, pp.76-80.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Sacramento River below Clear Creek ( RM290)
Variable & Condition
Qmax< 10,000 cfs (R band above Qmax)
Spring
Fall
Late-fall
No Q-rule defined
Winter
Qmax< 15,000 cfs (R band above Qmax)
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
Qmin kcfs
10
10
10
10
10
10
10
15
15
10
Qmax kcfs
Other Triggers
Daily time-scale recession; Winter-run especially sensitive
Recurrence
2 out of 3 years
Potential conflicts & trade-offs
Dewatering positively correlated with high spawning flow, daily recession
References
USFWS (2006)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 11 | P a g e
Sacramento River
Chinook & Steelhead
Indicator
CS5
Redd scour
Objective & Rationale
Redd scour risk is based on the daily proportion of eggs present by run type and location coupled to categorical
hazard classes at times when flow exceeds user-configured threshold values. Threshold values corresponding to the
90th percentile of 10-year peak flow (75,000 cfs) and 80th percentile of 5-year peak flow (55,000 cfs) define the
Fair/Poor and Good/Fair thresholds, respectively. The daily proportion of eggs present is based on the spawning
calendar (CS1) and temperature-based emergence (CS3). (SacEFT Design Document Section 4.3.1, pp.73-76.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Sacramento River below Clear Creek ( RM290)
Variable & Condition
No Q-rule defined
Spring
Jan: Qmax < 15,000 cfs (minimize R/G misclassification)
Fall
Feb: Qmax < 30,000 cfs (minimize R/G misclassification)
Late-fall
No Q-rule defined
Winter
Mar: Qmax < 25,000 cfs (minimize R/G misclassification)
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
Qmin kcfs
15
30
25
Qmax kcfs
Other Triggers
–
Recurrence
2 out of 3 years
Potential conflicts & trade-offs
References

Appendix I: EFT Derived Flow Needs
I - 12 | P a g e
Sacramento River
Chinook & Steelhead
Indicator
CS4
Juvenile stranding
Objective & Rationale
Juvenile stranding is modeled using daily declining changes in discharge over the juvenile rearing period, for each
location and run-type combination. The initial daily distribution of rearing juveniles is based on the temperature-
drive emergence function (see CS3) and the juvenile rearing WUA distribution (see CS2). Stranding for each day-
cohort is cumulatively based on prior stranding events. (SacEFT Design Document Section 4.3.1, pp.68-73.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Sacramento River below Clear Creek ( RM290)
Variable & Condition
Jan: Qmin > 5,000 cfs (minimize R/G misclassification)
Spring
No Q-rule defined
Fall
Sep: Qmin > 7,000 cfs (minimize R/Y misclassification)
Late-fall
Winter
Sep: Qmin > 8,500 cfs (minimize R/G misclassification)
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
5
8.5
Qmin kcfs
Qmax kcfs
Other Triggers
–
Recurrence
2 out of 3 years
Potential conflicts & trade-offs
Negatively correlated with juvenile rearing (CS2)
References
USFWS (2006)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 13 | P a g e
Sacramento River
Chinook & Steelhead
Indicator
CS2
Rearing habitat (WUA)
Objective & Rationale
Rearing WUA is calculated using daily cohorts of juveniles after emergence, for each run-type at up to 5 river
segments. Juvenile emergence is derived from daily average temperature applied to a temperature-driven egg-
emergence function using the run-type’s spawning calendar (see CS3). Chinook run-types remain in the system for
90 days following emergence; steelhead remain for one year. (SacEFT Design Document Section 4.3.1, pp.59-63.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Sacramento River below Clear Creek ( RM290)
Variable & Condition
Jan: 3,500 < Qmax< 6,000 cfs (minimize R/G misclassification)
Spring
No Q-rule defined
Fall
Sep: 3,500 < Qmax< 9,000 cfs
Late-fall
Sep: 3,500 < Qmax< 8,000 cfs
Winter
Sep: 3,500 < Qmax< 9,700 cfs
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
3.5
3.5
Qmin kcfs
6
8
Qmax kcfs
Other Triggers
Daily time-scale recession
Recurrence
2 out of 3 years
Potential conflicts & trade-offs
Negatively correlated with juvenile stranding (CS4)
References
USFWS (2005b)

Appendix I: EFT Derived Flow Needs
I - 14 | P a g e
San Joaquin-Sacramento Delta
Chinook & Steelhead
Indicator
CS7
Juvenile rearing habitat (Yolo Bypass)
Objective & Rationale
During sustained high flow events, Yolo Bypass can provide a high quality environment for extended rearing and enhanced growt h
(Benigno and Sommer 2009, Sommer et al. 2001). These benefits become greater for juvenile Chinook and steelhead the longer
they are able to take advantage of the productive food web available in the flooded Bypass. Besides additional food sources, the
unique temperature and flow regime of the Bypass may confer additional benefits, such as additional time for growth, or a
temperature environment that is closer to the optimum, compared to the mainstem. (DeltaEFT Design Document Section 2.2.1, pp.
40-54.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Fremont Weir (FREMONT WEIR SPILL TO YOLO BYPASS NR VERONA CA, RSAC155, 11391021)
Variable & Condition
Qavg > 5,000 cfs spill for any continuous 30-day interval. See Additional Details on next page
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
5
5
5
Qmin kcfs
Qmax kcfs
Other Triggers
Sacramento River Tavg < 55 °F during spill period
Recurrence
2 out of 3 years (Fleenor)
Potential conflicts & trade-offs
Inversely correlated with Juvenile rearing habitat (CS7); should not attempt to concurrently achieve CS7 and CS9 flows in same
year and same run-type. Inversely correlated with Chinook/Steelhead predation risk (CS9): increased Yolo flow typically reduces
mainstem flow. With current Fremont weir elevation, flows required to accomplish this objective would cause mortality of nesting
Bank Swallows (BASW2). Under some future climate change scenarios warm temperature can push juveniles above their
physiological limit, and they may lose weight in Yolo. There may be bioenergetic trade-offs.
References
Benigno and Sommer (2009), Sommer et al. (2001)
Additional Details
Analysis of EFT results from Historical and NAA scenarios suggests a minimum flow of 13,000 cfs. However, based on the flow
recommended by Fleenor (ref.), an even lower minimum flow of 5,000 cfs actually confers greater potential for growth by
increasing residency time from about 26 to 33 days. There is a trade-off between the cost of providing water, the benefit to
individual juveniles at 5,000 cfs and aggregate benefit to a larger portion of the year-cohort at higher flow.

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 15 | P a g e
San Joaquin-Sacramento Delta
Chinook & Steelhead
Indicator
CS9
Predation Risk (mainstem)
Objective & Rationale
Juvenile salmonids migrating downstream they may experience mortality from bass. Juvenile passage time was
selected as index to this predation risk. (DeltaEFT Design Document Section 2.2.1, pp. 54-60.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Hood (SACRAMENTO RIVER AT HOOD, RSAC142, 382205121311300)
Variable & Condition
Qavg > 11,000 cfs (between Qavg R/Y)
Spring
Qavg > 17,000 cfs (between Qavg R/Y)
Fall
Late-fall
Winter
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
17
17
17
17
17
17
17
17
Qmin kcfs
Qmax kcfs
Other Triggers
Not in conflict with CS7 goal
Recurrence
1 out of 3 years (based on non-conflict with 2-out-of-3-years CS7 goal)
Potential conflicts & trade-offs
Inversely correlated with Juvenile rearing habitat (CS7); should not attempt to concurrently achieve CS7 and CS9
flows in same year and same run-type.
DCC preferably closed to avoid exposure to interior Delta. Even if DCC open, mainstem velocity generally fast enough
to result in fast transit times.
References
Bartholow and Heasley (2006)

Appendix I: EFT Derived Flow Needs
I - 16 | P a g e
San Joaquin-Sacramento Delta
Chinook & Steelhead
Indicator
CS10
Thermal stress (eastern delta)
Objective & Rationale
The approach quantifies the absolute value of the difference between daily temperature and the optimum-growth
temperature at the peak of a dome-shape rate-of-gain function. Even though Delta water temperatures are largely
driven by weather and this stress cannot currently be managed, future management actions could conceivably result
in changes to location preferences which could reduce temperature stress. The indicator includes six routes through
the eastern Delta. (DeltaEFT Design Document Section 2.2.1, pp. 61-70.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Spring
Fall
Late-fall
Winter
Steelhead
Location
Above Delta Cross Channel (SACRAMENTO R AB DELTA CROSS CHANNEL CA, RSAC128, 11447890)
Variable & Condition
May: Qavg > 7,000 cfs (between R/Y)
Spring
Apr: Qavg > 15,000 cfs (between R/Y)
Fall
Mar: Qavg > 27,000 (between R/Y)
Late-fall
Apr: Qavg > 15,000 cfs (between R/Y)
Winter
Steelhead
Joint Timing
O
N
D
J
F
M
A
M
J
J
A
S
27
15
7
Qmin kcfs
Qmax kcfs
Other Triggers
Not in conflict with CS7 goal
Recurrence
1 out of 3 years (based on non-conflict with 2-out-of-3-years CS7 goal)
Potential conflicts & trade-offs
Inversely correlated with Juvenile rearing habitat (CS9); should not attempt to concurrently achieve CS7 and CS9
flows in same year and same run-type. DCC preferably closed to avoid exposure to interior Delta. Even if DCC open,
mainstem velocity generally fast enough to result in fast transit times.
References
Shelbourn et al. (1973), Perry et al. (2010)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 17 | P a g e
San Joaquin-Sacramento Delta
Splittail
Indicator
SS1
Spawning habitat extent (Yolo)
Objective & Rationale
Providing adequate spawning and rearing habitat is key to the long-term conservation of splittail (Moyle et al. 2004);
consequently maintaining flow regimes that result in periodic inundation of riparian and floodplain habitat during
winter and spring is important for splittail viability. When flooded, the majority of splittail spawning habitat is
located in Yolo bypass, consequently inundation of the floodplain plays a large role in determining the extent of
available spawning habitat. Inundation is defined as a depth of water <2m (Sommer et al. 2002). Total inundated
area of the floodplain <2m deep is an index of the amount of shallow water spawning habitat. The proportion of
spawners on a given day was estimated by fitting a normal distribution to spawn date data from Feyrer et al. (2006)
using the year 1998. (DeltaEFT Design Document Section 2.2.3, pp. 100-105.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
(Feb 21)
Location
Fremont Weir (FREMONT WEIR SPILL TO YOLO BYPASS NR VERONA CA, RSAC155, 11391021)
Variable & Condition
100 < Qavg< 2000 cfs for at least 75% of the period shown (approx. four weeks within this period)
Other Triggers
Recurrence
4 out of 10 years
Potential conflicts & trade-offs
Notching Fremont Weir should provide habitat
References
Sommer et al. (2002), Feyrer et al. (2006)

Appendix I: EFT Derived Flow Needs
I - 18 | P a g e
San Joaquin-Sacramento Delta
Delta Smelt
Indicator
DS1
Index of spawning success
Objective & Rationale
Spring water temperature affects spawning success, and extended periods with cool water typically result in more
spawning events and larger cohorts (Bennett 2005). A longer spawning period is made possible by an earlier
spawning start date, which increases the probability of reaching spawning maturity in that year and of spawning
multiple times in a single season. Adults spawn in freshwater during late winter and spring months, with the
majority occurring from March – April (Moyle 2002). Peak occurrence of ripe females occurs at 12-16°C (Nobriga,
pers. comm.), with highest hatch success at about 15°C. Delta smelt distribution is closely tied to the low salinity
zone and tidal freshwater areas of the Delta, with over 90% occurring at < 6‰ (Bennett 2005) and salinities > 19‰
being lethal. (Design Document Section 2.2.2, pgs. 71-81.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Location
Suisun Bay at Mallard Island (RSAC075, MAL, 11185185)
Water Year Types
≥ Normal WY
Variable & Condition
X2avg is ≤ 74km
Other Triggers
≥ Normal WY; 54°F< Tavg< 61°F.
Recurrence
Every other year
Potential conflicts & trade-offs
Requires high Delta outflow, which can impact reservoir storage and exports
References
Bennett (2005)

Final Report
Application of EFT to Complement Water Planning for Multiple Species
I - 19 | P a g e
San Joaquin-Sacramento Delta
Delta Smelt
Indicator
DS2
Index of habitat suitability
Objective & Rationale
Habitat largely consists of open water away from shorelines and vegetated inshore areas, except during spawning
(Delta Smelt BiOp 2008), including Suisun Bay and the deeper areas of many larger channels. However, habitat is
most strongly determined by water quality (salinity, turbidity and temperature), with low salinity being a key variable
(Bennett 2005). Therefore, freshwater flow into the estuary strongly influences Delta smelt habitat location and
extent. Habitat extends from the tidal freshwater reaches of the Delta seaward to 19‰ salinity with water
temperatures <25°C (Bennett 2005). In general, larger habitat volume is better because of reduced crowding and
improved opportunities to avoid localized sources of mortality. Unger (1994) showed that the overall surface area of
good habitat is maximized when X2 is located in Suisun Bay, although this relationship can be highly variable. (Moyle
et al. 1992). (Design Document Section 2.2.2, pp. 81-89.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Location
Fall X2
Variable & Condition
≥ Normal WYT: X2avg ≤ 74km
< Normal WYT: X2avg ≤ 81km
Other Triggers
Recurrence
Annually (based on BiOp RPA)
Potential conflicts & trade-offs
Requires high Delta outflows, which can impact reservoir storage and exports.
Inversely correlated with ID1,ID3
References
Feyrer et al. (2011), Moyle et al. (1992)

Appendix I: EFT Derived Flow Needs
I - 20 | P a g e
DS4, Delta smelt entrainment
The goal of this action is to minimize entrainment through the management of negative flow in the Old and Middle River.
San Joaquin-Sacramento Delta
Delta Smelt
Indicator
DS4
Entrainment index
Objective & Rationale
The indicator simulates entrainment risk from the CVP and SWP export operations. Low flow years historically have
higher incidences of entrainment than high flow years because fish are distributed closer to the points of diversion in
low flow years, when a higher proportion of juveniles rear in the Delta (Moyle 1992; Sommer et al. 1997). The greatest
entrainment risk from export operations is thought to occur during winter, but juveniles are also vulnerable; with peak
of risk in May-June (Nobriga et al. 2001). The indicator is based on the results of a Particle Tracking Model (PTM)
experiment (Kimmerer and Nobriga 2008), which simulates the fate of particles released in the Delta under a range of
inflows and exports. In order to satisfy the PTM assumptions, the indicator applies only to the larval and juvenile life
stages. (Design Document Section 2.2.2, pp. 89-100.)
Timing
O
N
D
J
F
M
A
M
J
J
A
S
Recommended
Used in Pilot
Locations
Combined Old + Middle River
(OLD R A BACON ISLAND CA, ROLD024, 11313405) + (MIDDLE R AT MIDDLE RIVER CA, RMID015, 11312676)
Variable & Condition
≤ Normal WYT: Qavg > –2,000cfs
> Normal WYT: Qavg > 0cfs
Recommended
≤ Normal WYT: Qavg > 2,000cfs
> Normal WYT: Qavg > 0cfs
Used in Pilot
Other Triggers
Juvenile smelt detected through trawls
Recurrence
Annually
Potential conflicts & trade-offs
May conflict with export objectives
References
Kimmerer and Nobriga (2008)

[Page Intentionally Blank]

Error! Reference source not found. September 12, 2013 Workshop Participants ESSA Technologies Ltd.
I - 2 | P a g e
Final Report
Environmental & Cumulative
Effects Assessment
Climate Change Adaptation &
Risk Reduction
Aquatic Species at Risk &
Water Resource Management
Terrestrial Ecology &
Forest Resource Management