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Quality Assurance Project Plan Puget Sound Dissolved Oxygen Modeling Study: Intermediate-scale Model Development

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Publication and Contact Information
This plan is available on the Department of Ecology‟s website at
Data for this project will be available on Ecologys Environmental Information Management
(EIM) website at Search User Study ID, xxxx. [NB: no data
collection for this project]
Ecologys Project Tracker Code for this study is 09-503-02.
Waterbody Number: WA-PS-010 through WA-PS-0300 (entire Puget Sound estuary system)
For more information contact:
Carol Norsen
Environmental Assessment Program
P.O. Box 47600
Olympia, WA 98504-7600
Phone: 360-407-7486
Washington State Department of Ecology -
o Headquarters, Olympia 360-407-6000
o Northwest Regional Office, Bellevue 425-649-7000
o Southwest Regional Office, Olympia 360-407-6300
o Central Regional Office, Yakima 509-575-2490
o Eastern Regional Office, Spokane 509-329-3400
Any use of product or firm names in this publication is for descriptive purposes only
and does not imply endorsement by the author or the Department of Ecology.
If you need this publication in an alternate format, call Carol Norsen at 360-407-7486.
Persons with hearing loss can call 711 for Washington Relay Service.
Persons with a speech disability can call 877- 833-6341.
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Quality Assurance Project Plan
Puget Sound Dissolved Oxygen Modeling Study:
Intermediate-scale Model Development
January 2009
Approved by:
Brandon Sackmann, Principal Investigator and Author, EAP
Mindy Roberts, Project Manager, EAP
Karol Erickson, Unit Supervisor, EAP
Will Kendra, Section Manager, EAP
Bob Cusimano, Section Manager for Project Study Area, EAP
Andrew Kolosseus, EAP Client, WQP
Bill Kammin, Ecology Quality Assurance Officer
Signatures are not available on the Internet version.
EAP – Environmental Assessment Program
WQP – Water Quality Program
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Table of Contents
Abstract ................................................................................................................................5
Background and Project Overview ......................................................................................5
Project Goals and Objectives .........................................................................................9
Organization and Schedule ..........................................................................................10
Capabilities for a DO Model of Puget Sound ....................................................................11
Hydrodynamics ............................................................................................................12
Water Quality ...............................................................................................................13
Ability to Incorporate Nearshore Processes at High Resolution .................................13
Sediment Contamination and Toxics Fate and Transport ............................................14
Summary ......................................................................................................................14
Recommendation for Model Selection and Model Approach ...........................................14
Hydrodynamic Model Setup ..............................................................................................16
Water Quality Model Setup ...............................................................................................17
Loading Estimation ............................................................................................................18
Available Data Sources ......................................................................................................21
Acceptance criteria .......................................................................................................21
Data set descriptions ....................................................................................................21
Canadian data set descriptions .....................................................................................24
Model Calibration and Evaluation .....................................................................................25
Sensitivity and Uncertainty Analyses ................................................................................26
Model Scenarios.................................................................................................................27
Model Output Quality (Usability) Assessment ..................................................................28
Project Deliverables and Schedule.....................................................................................28
References ..........................................................................................................................30
1. Puget Sound Dissolved Oxygen Modeling Model Technical Advisory Committee Model
Selection Workshop Summary (4 November 2008).
2. Evaluation of features of hydrodynamic model.
3. Evaluation of features of water quality modeling system (hydrodynamic and water
quality model).
4. Descriptions of available data sources.
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Ecology is developing an intermediate-scale model for the entire Puget Sound estuary system to
further our understanding of processes that affect dissolved oxygen (DO). This project will help
determine if current nitrogen loadings from point and nonpoint sources into Puget Sound are
significantly impacting water quality at a large scale and what level of nutrient reductions are
necessary to reduce or eliminate human impacts to DO levels in sensitive areas. The northern
boundary will be set at the entrance to Johnstone Straits past the Fraser River north of Vancouver
B.C. The model resolution will be finer than the large-scale box model, being developed in
tandem with this model, ensuring reasonable representation of the various sub basins within
Puget Sound.
The model will simulate full eutrophication kinetics. Nutrient loads will be specified as input
variables for all important sources. The objective of this intermediate-scale hydrodynamic and
water quality model is to develop a large scale understanding of nutrient assimilation capacity of
Puget Sound. The preference is to develop the water quality model in a de-coupled configuration
so that it may be applied repeatedly using previously computed hydrodynamic solutions. The
water quality model will be calibrated using data collected in Puget Sound from 1999-2008 and
will be used to simulate the effects of alternative nutrient loading scenarios.
Each study conducted by the Washington State Department of Ecology (Ecology) must have an
approved Quality Assurance (QA) Project Plan. The plan describes the objectives of the study
and the procedures to be followed to achieve those objectives. After completion of the study, a
final report describing the study results will be posted to the Internet.
Background and Project Overview
Nutrient pollution is considered one of the largest threats to Puget Sound (Figure 1). Recognized
nation-wide, the following characteristics of nitrogen pollution apply equally and imperatively to
Puget Sound (Glibert et al., 2005; Howarth, 2006; Howarth and Marino, 2006):
Human acceleration of the nitrogen cycle over the past 40 years is far more rapid than
almost any other aspect of global change.
Nutrient pollution leads to hypoxia and anoxia, degradation of habitat quality, loss of
biotic diversity, and increased harmful algal blooms.
Technical solutions exist and should be implemented, but further scientific work can best
target problems and solutions, leading to more cost effective solutions.
While eutrophication can be a natural process, anthropogenic nutrient pollution can cause
cultural eutrophication which is the process of enhanced eutrophication resulting from human
activity. Both natural and cultural eutrophication occur when a body of water becomes enriched
with nutrients which, in turn, stimulate excessive algal growth. Oxygen consumption resulting
from the subsequent decomposition and respiration of the excess algae by bacteria leads to
dissolved oxygen (DO) depletion in areas that are not well ventilated (e.g., quiescent bays and
near-bottom waters).
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Nutrient inputs from oceanic sources, tributary inflows, point source discharges, nonpoint source
inputs, sediment-water exchange, and atmospheric deposition determine the loads to Puget
Sound. Hydrodynamic characteristics, such as tides, stratification, mixing, and freshwater
inflows, govern transport of nutrients and other parameters. Photosynthetic rates (influenced by
light and nutrient availability, temperature, and algal species assemblages) and other processes
(growth, death, respiration, settling, and bacterial decomposition) determine nutrient
transformations and the degree of DO depletion.
In general, large-scale eutrophication in Puget Sound has been thought to be unlikely for two
reasons. First, Puget Sound receives relatively high concentrations of nutrients from the Pacific
Ocean so incremental nutrient additions were thought to do little to influence overall
phytoplankton productivity. Second, estuarine circulation and tidal mixing throughout much of
Puget Sound ensures a rapid exchange of water (approximately 1 year turnover time). Vertical
mixing, especially in Central Puget Sound, further limits exposure of phytoplankton to light and
therefore reduces algal growth and biomass accumulation (Mackas and Harrison, 1997).
These characteristics of Central Puget Sound were responsible for the successful diversion of
sewage from Lake Washington to West Point (Puget Sound) in the late 1950‟s (Edmondson,
1991). While nutrient loading to Lake Washington caused excessive algal growth in the lake, the
same loading at West Point did not appear to enhance algal growth in marine waters. Much of
the current understanding of Puget Sound phytoplankton dynamics has been based on modeling
and measurements of ambient productivity and nutrients at West Point (Winter et al., 1975).
In contrast, a more recent study by Newton and Van Voorhis (2002) observed substantial
increases in algal primary production when water samples from Central Puget Sound and
Possession Sound were artificially enriched with nutrients. Nutrient-enhanced production was
observed at all stations but the degree of enhancement varied both spatially and temporally
suggesting that the system is more complex and that there are likely to be a diversity of
responses to nutrient addition. These responses are expected to manifest differently at different
times and locations within greater Puget Sound.
Mackas and Harrison (1997) evaluated the issue of eutrophication in the Strait of Juan de Fuca,
Georgia Strait, and Puget Sound. They judged potential impacts from eutrophication of Central
Puget Sound to be relatively low. However, they reported that the most sensitive sub-regions are
likely to be small tributary inlets and fjords that have low flushing rates and that adjoin urbanized
shorelines. They speculated that the “early warning signs of eutrophication” were already
becoming evident in these areas. At present, most of these areas lie along the south and west
margins of Puget Sound.
Bricker et al. (1999) later reported the overall level of expression of eutrophic conditions to be
moderate in Central Puget Sound and Whidbey Basin and high in Hood Canal and South Puget
Sound. They predicted conditions to worsen, especially in Hood Canal and South Puget Sound,
due to increasing population pressures. In response to the increasing threat of nutrient-stimulated
eutrophication in Puget Sound, Ecology has both initiated and been actively involved with the
continuation of focused water quality studies in these specific areas (Roberts et al., 2008a;
Albertson et al., 2007; Roberts et al., 2005b; Albertson et al., 2002).
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This project capitalizes on what has been learned in these prior studies and seeks to expand this
foundation to develop a unified water quality model applicable to the entire Puget Sound estuary
system. As part of mandates under the Clean Water Act to manage pollutant loading to meet
water quality standards, U.S. EPA, Pacific Northwest National Laboratory (PNNL), and Ecology
have jointly initiated this water quality model development project to address the following
specific nutrient management questions.
Are human sources of nutrients in and around Puget Sound significantly impacting water
How much do we need to reduce human sources of nutrients to protect water quality in
Puget Sound?
PNNL is tasked with the development of the hydrodynamic and water quality models for use by
the agencies to evaluate the effect of human sources of nutrients on dissolved oxygen across
Puget Sound and to define potential Puget Sound-wide nutrient management strategies and
decisions. The model development will occur in PNNL‟s Marine Sciences Laboratory, through
an intergovernmental agreement between PNNL and Ecology. This document describes the
development of this intermediate-scale model of Puget Sound. A complementary QA Project
Plan has been created which details development of the large-scale screening model (Sackmann,
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Figure 1. Map of western Washington and lower British Columbia, Canada. Shaded region
defines the Puget Sound Action Area. Thick black lines outline the domain of the intermediate-
scale model. Thick red lines outline Puget Sound and the domain of the large-scale screening
model. Major rivers have been labeled, but the models will include others. Only major
Canadian rivers in watersheds that share a border with the U.S.A. have been shown.
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Project Goals and Objectives
Mechanistic models provide the quantitative framework necessary to integrate the diverse
physical, chemical, and biological information that constitute complex environmental systems
and provide a vehicle for an enhanced understanding of how the environment works as a unit
(Chapra, 1997). For example, complexities such as the impact of the temporal and spatial
distribution of nutrient additions, of when freshwater inputs occur and how that alters circulation
patterns, and of co-limitation of production by nutrient and sunlight cannot be determined
without a quantitative approach. In this study the water quality models to be developed will
identify and assess factors and processes that influence water quality in Puget Sound on a
significant scale.
The overall goal of this project by Ecology is to work collaboratively with U.S. EPA, PNNL, and
a Project Advisory Committee (PAC) to conduct DO modeling in Puget Sound in a manner that
complements and supports concurrent management initiatives. This project consists of the
following components:
1. Two multi-purpose hydrodynamic models for the entire Puget Sound, one at a large scale
(based on Babson et al., 2006) and one at an intermediate scale. These models can also
serve as community tools for other purposes.
2. The large-scale model (also called “box model”) will be used to produce a screening-
level evaluation of nutrient effects on DO, Puget-Sound-wide. The results of this effort
will inform the intermediate-scale model.
3. The intermediate-scale model (also called the “intermediate-grid model”) will be used to
evaluate the effect of human-caused nutrient enrichment on DO across Puget Sound.
This model will help inform potential Puget-Sound-wide management strategies and
decisions and would support site-specific detailed work that may be completed beyond
this project.
4. QA Project Plan for a detailed site-specific analysis for one Puget Sound basin (e.g.
Whidbey basin) to determine the nutrient loading reductions needed to meet water quality
The scope and focus of this QA Project Plan is limited to the development of the intermediate-
scale model (i.e., items 1 and 3 above) only. The development strategy for the large-scale model
is described in a separate QA Project Plan (Sackmann, 2008). Objectives specific to this project
are as follows:
Develop an intermediate-scale water quality model, calibrated to conditions observed in
Puget Sound from 1999-2008.
Estimate effects of nutrient loading on DO and apply the model to various nutrient
loading scenarios.
Evaluate sensitivity of the model to various input parameters and boundary conditions.
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Organization and Schedule
The following individuals are involved in this project (Table 1). Except as noted, all are
employees of the Washington State Department of Ecology, Environmental Assessment Program
Table 1. Organization of project staff and responsibilities.
(all are EAP except as noted*)
Brandon Sackmann
MIS Unit
Statewide Coordination Section
(360) 407-6684
Writes the QAPP, develops model and nutrient
loading input files, analyzes and interprets model
results, runs model scenarios, and writes the draft and
final report.
Mindy Roberts
MIS Unit
Statewide Coordination Section
(360) 407-6804
Project Manager
Develops and oversees all project-related activities,
and provides technical guidance and oversight to aid
model development and subsequent refinement.
Karol Erickson
MIS Unit
Statewide Coordination Section
(360) 407-6694
Unit Supervisor for
the Project Manager
Reviews and approves the QAPP and approves the
Will Kendra
MIS Unit
Statewide Coordination Section
(360) 407-6698
Section Manager for
the Project Manager
Reviews the project scope and budget, tracks progress,
reviews and approves the QAPP.
Greg Pelletier
MIS Unit
Statewide Coordination Section
(360) 407-6485
Technical Advisor
Provides technical guidance and oversight to aid
model development and subsequent refinement.
Ben Cope*
(206) 553-1442
Technical Advisor
Provides technical guidance and oversight to aid
model development and subsequent refinement.
Tarang Khangaonkar*
(206) 528-3053
Model Lead
Develops hydrodynamic and water quality models,
performs model calibration/evaluation and sensitivity
analyses, and writes reports for Ecology.
Bob Cusimano
Western Operations Section
(360) 407-6596
Section Manager for
the Study Area
Reviews the project scope and budget, tracks progress,
reviews and approves the QAPP.
Andrew Kolosseus*
Watershed Planning Unit
Water Quality Program
(360) 407-7543
EAP Client
Clarifies scope of the project, provides internal review
of the QAPP, and approves the final QAPP.
William R. Kammin
(360) 407-6964
Ecology Quality
Assurance Officer
Reviews and approves the QAPP.
EPA – Environmental Protection Agency
PNNL – Pacific Northwest National Laboratory
MIS – Modeling and Information Support
QAPP – Quality Assurance Project Plan
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Table 2 summarizes the expected project schedule. Tasks are limited to the development of the
intermediate-scale model only.
Table 2. Proposed schedule for completing modeling work and reports.
Hydrodynamic model report (PNNL)
Author lead
Draft to Ecology
April 2009
Draft due to client/peer and external
May 2009
Final report due on web
July 2009
Water quality model report (PNNL)
Author lead
Draft to Ecology
October 2009
Draft due to client/peer and external
November 2009
Final report due on web
January 2010
Final report
Author lead
Brandon Sackmann (Ecology)
Draft due to supervisor and project
February 2010
Draft due to client/peer and external
March 2010
Final report due on web
June 2010
Focus Sheet
Author lead
Brandon Sackmann (Ecology)
Draft due to supervisor and project
March 2010
Final version due on web
June 2010
Capabilities for a DO Model of Puget Sound
Success of marine circulation and water quality model development can be affected by the
choice of the software tool and modeling framework. Ecology assembled a Model Technical
Advisory Committee (MTAC) to seek input on modeling approaches given the project goals and
resources. The MTAC is comprised of a group of modeling professionals and is separate from
the PAC, although some membership does overlap. The MTAC was tasked with evaluation of
key processes needed in the model, extent of model domain, the level of detail, model framework
comparison (pros/cons), and model applicability to other Puget Sound projects. Ecology
convened a MTAC workshop on 4 November 2008 which was attended by modeling experts and
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the project team. The information and feedback received has been summarized and is attached
as Appendix 1.
While Ecology is responsible for the final model selection in consultation with the project team
and MTAC, Ecology has requested that PNNL also provide input on model selection separately,
in the capacity of team member responsible for the model development and implementation.
Recommendations are based on Puget Sound hydrodynamic features, experience with various
models and tools available, and understanding of project goals. PNNL‟s assessment of the
model performance requirements is provided below. Models and software tools are limited to
those available in the public domain, and commercial models such as Delft-3D, WQMAP,
MIKE, and other similar tools were not included in this assessment. If the results are used for
regulatory purposes, all model information must be available to interested parties, and
proprietary or commercial models do not satisfy this need.
Puget Sound is a large estuarine system bounded by 2,597 miles of complex shorelines and
consists of several sub basins and many large estuaries with distinct properties of their own. It is
the largest such body of water in the contiguous forty-eight states. Pacific Ocean water enters
the Puget Sound estuary system and the Georgia Strait through the Strait of Juan de Fuca (SJF)
entrance at Neah Bay. SJF is also the outlet for most of the freshwater discharged from the
Puget Sound and from the Fraser River in British Columbia.
Admiralty Inlet links the three major branches of Puget Sound together and serves as the primary
outlet to the SJF and ultimately the Pacific Ocean. The three main branches of Puget Sound
include the deep Main Basin and the shallower South Sound (separated from the Main Basin by a
sill and constriction at the Narrows), Hood Canal, and Whidbey Basin. The only other outlet to
SJF is the extremely narrow Deception Pass located at the northern end of Whidbey Basin
(Figure 1).
The large freshwater discharge from the Fraser River affects stratification and currents in the
adjacent waters of the Strait of Juan de Fuca and Georgia Strait including waters around San
Juan Islands and the Cherry Point coastline near the United States/Canada border. There is
considerable interest in the circulation and transport in the entire region spanning the U.S. and
Canadian waters for the assessment of fish migration patterns and pathways. Although not the
primary focus, there is also an interest in understanding the effect of nutrient loads entering
Puget Sound from Canadian waters. Therefore, there is a need to ensure that the study domain
extends well north into Canadian waters to Johnstone Strait near the entrance to Discovery
The circulation in this estuary shows distinct fjordal three dimensional (3D) characteristics with
mean outflow in the surface layers and inflow in the lower layers. Near the mouths of the
individual estuaries there is stratification due to freshwater discharge and complex circulation
patterns induced by cross flow as the river plumes encounter Puget Sound tidal influences. The
model selected must therefore be capable of simulating 3D baroclinic (density-induced)
circulation affected by freshwater inflows over shallow mudflats and sharp change in bathymetry
to deep fjordal depths of Puget Sound. The currents are also affected by local winds.
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A number of models such as EFDC (Roberts et al., 2005a; Khangaonkar and Yang, 2004; King
County, 1999), CH3D (Johnston et al., 2007), POM (Kawase, 1998), SUNTANS (Wang et al.,
2008), FVCOM (Finite Volume Community Ocean Model; Yang and Khangaonkar, 2008),
RMA10 (Breithaupt et al., 1999), UnTRIM (Joshberger, 2005), and ROMS (Bahng et al., 2007)
available in the market are capable of addressing the above characteristics and are being used
successfully on various studies in progress in Puget Sound and are possible candidates for this
Water Quality
The focus of this project is on simulating the response of DO concentrations to nutrient loading.
Eutrophication and algal kinetics are of major interest because they are the links between
nutrients and dissolved oxygen. Parts of Puget Sound such as the Hood Canal and the nearshore
estuarine and riverine reaches have shown evidence of hypoxia. A full listing of various
processes of interest and variables which need to be simulated is discussed in Puget Sound
Dissolved Oxygen Modeling Model Technical Advisory Committee Model Selection Workshop
Summary (Appendix 1) and is not repeated here.
The selected model must have the ability to simulate full eutrophication kinetics including the
ability to incorporate point sources, address multiple algal groups, nutrient cycling, and include
sediment oxygen demand (SOD) and biochemical oxygen demand (BOD) processes. Nutrient
loads will be specified as input variables for all important sources. These loads will be estimated
by Ecology using data from the National Pollutant Discharge Elimination System (NPDES)
database, the river and stream monitoring network data, and the South Puget Sound Dissolved
Oxygen Study (Roberts et al., 2008b).
Most of the models described above such as EFDC, CH3D, ROMS, FVCOM, and RMA10 have
sophisticated water quality modules which may be applied for this study. In models other than
RMA10, the water quality modules are embedded within the codes, coupled to hydrodynamics,
and could impose a considerable computational burden. CH3D and EFDC models have been
used in decoupled mode with stand alone water quality simulation programs such as WASP
(Wool et al., 2006) and CE-QUAL-ICM (Cerco and Cole, 1995).
Ability to Incorporate Nearshore Processes at High
This phase of the project seeks to establish a model at an intermediate-scale improving in
resolution over the large-scale model (also called “box model”) of Puget Sound (Babson et al.,
2006). It will be set up at a resolution sufficient for addressing the large-scale questions on the
assimilative capacity of Puget Sound. However, the model could be used subsequently to
address localized higher resolution processes including the effects of point source discharges and
water quality impairment in the nearshore regions associated with sediment and bacteria
contamination. Ability of the model to improve resolution as required through the use of nested
grid techniques or the use of unstructured grids is considered essential for future applications in
Puget Sound such as total maximum daily load (TMDL) calculations or sediment impact zone
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(SIZ) assessment for remedial investigations. Therefore, model capabilities to address additional
parameters beyond DO are considered but are not essential.
Sediment Contamination and Toxics Fate and Transport
While the project goals clearly focus on DO, this project presents an opportunity to select and
establish a tool which can address Puget Sound community needs over the long term. Although
not a part of this study, the ability of the model to conduct toxics fate and transport (metals and
organics) and address sediment contamination issues will be a major advantage.
Appendices 2 and 3 show a listing of available hydrodynamic and water quality modeling tools,
their capabilities, and ranking based on comments provided by the MTAC. As seen in Appendix
2, hydrodynamic models are largely divided into structured grid models (POM, EFDC, ROMS,
CH3D and GEMSS) and unstructured grid models (FVCOM, UnTRIM, ADCIRC, and SELFE).
Most of them use high-order transport schemes, wetting/drying option, and sigma-grid system.
These models are well known, well tested, and have been applied on many projects. Many of
these models have active user groups, and provide well-organized technical documentation.
Recommendation for Model Selection and
Model Approach
If the selection were based on immediate project goals and model skill and capabilities alone, a
number of available models discussed above could provide the required performance. However,
our interest in developing a tool which could be used over a long term by a broader community
of scientists requires consideration of the following additional points.
Applicability to Ecosystem Model Development Efforts: A number of agency groups
including NOAA Fisheries and King County are engaged in developing an ecosystem / food
web model of Puget Sound. A Puget Sound DO / Water Quality Model could be used as a
source of information on temperature, salinity, nutrient concentrations, DO and other
conventional water quality variables which are desired inputs to ecosystem modeling efforts.
In addition, the ability of this model to also provide information about metals, organics, and
sediment contamination levels will be a major plus with respect to supporting sediment
Ability to Conduct Long-Duration Model Runs: Effect of climate change and sea level rise
are issues of considerable interest. Ability of the model to be used in the future to conduct
simulations over 10 to 100 year time frames is an important consideration.
Wetting and Drying, Mudflats, and Nearshore Circulation: Much of the effort in connection
with restoration of Puget Sound is focused on the nearshore. The question often posed is
“can we achieve beneficial restoration outcomes at the fine local scale, as well as at a large
estuary-wide scale?” Capabilities of the model for simulating the important nearshore
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processes, such as circulation in complex multiple tidal channels, wetting and drying of tide
flats, and water quality and sediment transport are essential both for immediate DO
simulation needs and for potential long term modeling needs of this region.
Based on model performance requirements discussed in the previous section and additional
points listed above, model recommendations are as follows:
1. Unstructured Grid Framework: The model framework must incorporate an
unstructured grid framework to be able to address nearshore processes adequately
while simultaneously assessing the circulation and water quality of the entire Puget
Sound. The ability to modify the grid efficiently as new information and data become
available is considered essential for developing a model of a complex water body
such as Puget Sound.
2. Comprehensive Water Quality Model Decoupled from Hydrodynamics: It is
unlikely that an complete water quality model will be developed through a single
effort. It is likely that more features and processes will be added through subsequent
project applications. Multiple users may wish to apply the modeling framework to
look at other parameters of interest (bacteria, toxics, submerged aquatic vegetation,
etc.). It is therefore important to select a water quality model framework with the
ability to address a wide range of processes. From a computational efficiency
standpoint, access to a water quality module which is independent of the
hydrodynamic tool is highly recommended.
PNNL reviewed a number of unstructured grid models and personally contacted the authors to
discuss the strengths and weaknesses of their tools. These included the leading 3D unstructured
grid models including RMA10 (King, 1998), ADCIRC (Leuttich et al., 1992), ELCIRC (Zhang
et al., 2004), SELFE (Zhang and Baptista, 2008), UnTRIM (Casulli and Walters, 2000), and
FVCOM (Chen et al., 2003).
The SUNTANS model discussed in the previous section is considered under development with
respect to its ability to handle shallow mudflats and wetting and drying and does not include
associated water quality. The ADCIRC model is popular for storm surge modeling in barotropic
mode but the baroclinic version of the model is not yet available. The UnTrim model is not
generally available in public domain. The ELCIRC model of Columbia River and Washington
Coast previously developed by Oregon Graduate Institute had a strict limiting requirement of
orthogonal grid cells, and has now been replaced by SELFE. The water quality module of
SELFE is still under development. PNNL is closely following the development of SELFE and
SUNTANS unstructured grid hydrodynamic modeling tools.
Based on testing and application on numerous projects, Ecology recommends the FVCOM
model for this project. FVCOM simulates water surface elevation, velocity, temperature,
salinity, and sediment and water quality constituents in an integral form by computing fluxes
between non-overlapping, horizontal, triangular control volumes. This finite-volume approach
combines the advantages of finite-element methods for fitting complex boundaries and finite-
difference methods for simple discrete structures and computation efficiency. A sigma-stretched
coordinate is used in the vertical plane to better represent the irregular bottom topography.
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Unstructured triangular cells are used in the horizontal plan. Key features of FVCOM on which
the selection is based are detailed in Appendices 2 and 3 but are summarized as follows.
Unstructured grid modeling frame work.
Ability to simulate baroclinic circulation.
Finite volume technique with good mass conservation properties.
Wetting and drying simulation.
Parallelized code (hydrodynamics) for cluster computing.
Availability of water quality, sediment transport, and particle tracking.
Public domain and well-tested code on multiple projects with an active research
Although a water quality component (NPZD) is available through FVCOM, Ecology
recommends selection and application of a water quality tool which may be applied independent
of the hydrodynamic model in a decoupled mode. WASP and CE-QUAL-ICM are two water
quality models which have been extensively used in the U.S. The coupled water quality modules
in many of the tools discussed previously are based on these two models. The models are
applicable over an unstructured hydrodynamic model grid, and incorporate a comprehensive
suite of water quality processes including conventional eutrophication, and toxics fate and
transport kinetics. The CE-QUAL-ICM model provides added capabilities with respect to
sediment diagenesis and the ability to incorporate submerged aquatic vegetation.
Based on the above considerations, Ecology‟s selections for the Puget Sound Do model are as
Hydrodynamics – An intermediate-scale hydrodynamic model of Puget Sound using
the FVCOM model developed by the University of Massachusetts.
Water quality – A decoupled application of the U.S. Army Corps of Engineers‟ CE-
QUAL-ICM model to be operated using the FVCOM model grid and pre-computed
hydrodynamic solution.
Ecology will work with PNNL, U.S. EPA, and the MTAC to develop an approach for model
setup including grid resolution (vertical and horizontal), selection of input and output data,
model calibration / evaluation, and application.
Hydrodynamic Model Setup
Development of the intermediate-scale hydrodynamic model will consist of several steps
including model grid development, model setup involving specification of boundary conditions
for the selected period, calibration and sensitivity analysis, and application for scenarios. The
grid development activity and preparation of model input files are part of the model setup and are
specific to the modeling system selected.
PNNL has previously developed a high resolution model of the Puget Sound. In doing so, a
detailed bathymetry file for Puget Sound using a combination of digital elevation maps, LiDAR
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data, and hydrographic surveys has been prepared. Using this data set, the Puget Sound domain
will be re-gridded extending from the mouth of the Strait of Juan de Fuca to South Puget Sound.
The northern boundary will be set at the entrance to Johnstone Straits past the Fraser River north
of Vancouver B.C. (Figure 1). The resolution selected will be considerably finer than the large-
scale model ensuring reasonable representation of the various sub basins within the Puget Sound.
However, the grid will be coarse relative to the PNNL Puget Sound model, which has a
resolution as fine as 30 ft in certain sub-basins.
We expect that the model will be set up with sufficient layers (10 to 30) in the vertical to address
the highly stratified nature of residual circulation in Puget Sound. In Puget Sound, a synoptic
data set for currents and tides covering the entire domain is not available. Therefore the
hydrodynamic model setup will need to be tested against the multiple periods of 9/96, 9/04,
10/06, and 9/07 during which data were collected. These periods also match the calibration
periods for the fine resolution PNNL hydrodynamic model previously completed.
There are 17 major rivers that discharge into Puget Sound and its adjacent waters. Most of these
rivers have real time USGS stream flow gages. Contributions from the rest of the land surface
will also be included for completeness but not necessarily representing each stream mouth. The
model will be set up with flows from these rivers included as boundary source terms. However,
the estuarine circulation, the movement of salt wedge, and the upstream tidal intrusion generated
by these river inflows are beyond the scope of the intermediate-scale model.
Tidal elevations at the open boundaries will be specified using the XTIDE predictions based on
NOAA National Oceanic Service algorithms. At the water surface, wind stress will be specified.
Wind will be included for completeness with wind stress being initially applied uniformly across
the entire model domain for simplicity. Meteorological forcing terms including wind and heat
flux or air temperature and solar radiation will be specified using either direct measurements or
using MM5 or WRF meteorological model simulations if the latter are sufficient for this model
Model calibration, described below, will be conducted by comparing the predicted tides,
currents, and salinity and temperature profiles to observed data. The process of calibration will
consist of steps such as refining the model grid as required, adjusting bottom roughness and
friction, and varying tidal phase along open boundaries. Once the model calibration is completed,
sensitivity analysis will be performed testing the stability and reliability of the model to a wide
range of inputs. Tidal residual calculations will also be performed as part of the sensitivity
Water Quality Model Setup
The objective of this intermediate-scale water quality and nutrient model is to develop a large-
scale understanding of nutrient assimilation capacity of Puget Sound. The selected water quality
model will simulate conventional water quality constituents such as nitrogen, phosphorus,
dissolved oxygen, BOD, SOD, phytoplankton, and temperature. The focus of this modeling
effort is on the response of the above listed variables to nutrient loads, which is conventionally
known as the eutrophication cycle. Nutrient loads will be specified as input variables for all
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important sources. These loads will be estimated by Ecology using data from the National
Pollutant Discharge Elimination System (NPDES) database and river and stream monitoring
network data.
PNNL will set up the selected model over the same domain and grid developed for the
hydrodynamic model. The initial preference is to develop the water quality model in a de-
coupled configuration so that it may be applied repeatedly using previously computed
hydrodynamic solutions. Although this not a requirement, it does provide benefits in terms of
model runtimes.
Loading Estimation
Excess nitrogen can come from a variety of sources. The term nonpoint is used to describe
diffuse sources that do not come through a pipe (such as rainfall runoff from agricultural fields
and residential yards) and groundwater (including contributions from septic systems). Most of
the nonpoint nitrogen loading from the watersheds surrounding Puget Sound enters via rivers and
The term point source generally refers to sources that are regulated under the federal Clean
Water Act through the NPDES. NPDES permits are issued to municipal and industrial
wastewater treatment and stormwater systems, constructions sites, boatyards, salmon net pens,
and other facilities. With respect to point sources, municipal wastewater treatment plants that
discharge directly to Puget Sound are thought to represent the largest anthropogenic source of
direct nitrogen loading from the watershed to the Sound. A few industrial facilities discharge
directly to Puget Sound, and these will be included where discharge information is available or
can be estimated. Point source loads will be estimated using data from the NPDES database and
the South Puget Sound Dissolved Oxygen Study (Roberts et al., 2008b). In some cases, smaller
wastewater discharges may be lumped as for the smaller streams.
While all rivers are generally considered nonpoint sources, some have upstream wastewater
treatment plants that discharge to freshwater. For this project, upstream wastewater treatment
plants will not be separated out of the river and stream inputs. In addition, rivers and streams
receive discharges from other permitted areas, such as municipal stormwater, which are
considered point sources. Again, for this project, permitted sources will not be separated out of
the river and stream inputs.
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A major activity as part of the model setup will be developing nutrient loading input files for all
major wastewater treatment plants and rivers. Ecology‟s goal is to develop these files as a
separate stand-alone product to facilitate their use by other projects and agencies. This project
will require the following information for specifying nutrient loads from all sources including all
major effluent dischargers and river loads:
Flow rates and temperature data
Organic phosphorus (particulate and dissolved)
Dissolved phosphorus (soluble reactive phosphorus)
Organic nitrogen (particulate and dissolved)
Ammonia nitrogen
Nitrate + Nitrite nitrogen
Dissolved oxygen (DO)
Total organic carbon (TOC)
Dissolved organic carbon (DOC)
Carbonaceous biochemical oxygen demand (CBOD to be estimated from DOC or
DOC to be estimated from CBOD, as needed)
When available, measured effluent quality for a particular point source will be used to estimate
its constituent loadings. If such data are not available for a particular source, it will be necessary
to estimate effluent quality based on measurements from similar facilities.
Organic nitrogen may be estimated as the difference between total Kjeldahl nitrogen and
ammonia nitrogen for wastewater treatment plants and between total nitrogen and the sum of
ammonium, nitrate, and nitrite for rivers. Organic phosphorus may be estimated as the
difference between total phosphorus and orthophosphate phosphorus.
As mentioned earlier under „Hydrodynamics Model Setup‟, there are 17 major rivers that
discharge into Puget Sound and its adjacent waters, most of which have real time USGS
streamflow gages. Calculation of river loads requires both constituent-concentration and
streamflow data. As part of the USGS National Water Quality Assessment, Embrey and Inkpen
(1998) estimated nutrient loads to Puget Sound from several major rivers based on existing
nutrient concentrations and discharge data for the period 1980-1993. Using an analogous
approach, time-resolved stream loads will be estimated for the time period from 1999-2008 using
constituent-concentration data compiled from databases maintained by agencies operating water-
quality monitoring stations in the Puget Sound Basin and streamflow estimates made at the time
of water-quality sample collection (Appendix 4).
The intermediate-scale model will be set up with flows from rivers included as boundary source
terms. The model will require daily time series of flows, temperature, DO, pH and nutrient loads
from discrete watershed inflow points to simulate seasonal and subseasonal variations in Puget
Sound water quality. The total ungaged discharge to Puget Sound may be as high as 10% of the
total gaged inflow but with potentially higher nutrient concentrations due to agricultural and
urban runoff. Flows from ungaged rivers will be estimated by first choosing a representative
gaged reference river based upon its similarity to an ungaged area and then multiplying the
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reference flow by the ratio of the ungaged to gaged areas (Lincoln, 1977). In cases where rivers
are gaged well upstream from the river mouth the drainage area downstream of the station is
used as the ungaged area in the calculation and the estimated flow is added to the gaged flow to
obtain total discharge for that river.
Following Mohamedali (2008) and Roberts and Pelletier (2001) daily time series of various
parameters and nutrient concentrations will be estimated using multiple linear regressions
(Cohen et al., 1992). This analysis is based on the premise that parameter concentrations can be
predicted based on flow and time of year. The multiple linear regression equation to be used in
this analysis is given by:
log(c) = b
+ b
log(Q/A) + b
+ b
) + b
) + b
) + b
) (1)
where c is the observed parameter concentration (mg/L) or in the case of temperature or pH it is
C and pH units (respectively), Q is discharge (m
/s), A is the area drained by the monitored
location (km
), f
is the year fraction (dimensionless, varies from 0 to 1), and b
are the best-fit
regression coefficients.
All six variables in the above equation are known values (from available concentration data,
streamflow data, watershed area and time of year) except for the coefficients (b
). The multiple
linear regression model attempts to solve equation (1) and determine the optimum combination
of b
coefficients that will yield the best fit between predicted and observed concentrations of a
specific parameter. Once these coefficients are determined, the above equation can be used to
predict parameter concentrations continuously over any time period, for example, at a daily
interval. Daily concentrations will be multiplied with daily streamflow data to predict daily
loads for time periods of interest.
In previous applications of this regression model methodology certain water quality parameters
were better characterized by the regression model than others, particularly those highly
influenced by flow and seasonality. Though the statistical results from some parameters
suggested a poor fit for concentration, predicted daily loads often compared well with observed
loads for most parameters across a wide variety of streams.
There is also evidence that groundwater may contribute significant amounts of freshwater to
some basins and should be evaluated as a potential source of distributed nutrients (e.g., Hood
Canal). One proposed application of the model will be to test the relative sensitivity of this
source, using published and/or order-of-magnitude groundwater flow estimates, to the overall
nutrient and DO balance of Puget Sound (Simonds et al., 2008).
Loads from Canadian sources will be calculated to determine Puget Sound‟s sensitivity to
nutrients coming into the system through its northern boundary. Daily loads will be estimated
using methods analogous to those used in Puget Sound. However, initially loads will only be
estimated for major rivers and wastewater treatment plants (WWTP) which are likely to include
(but will not be limited to) loads from the Fraser river, Victoria-area WWTP, and Vancouver-
area WWTP. Should the water quality model results in Puget Sound prove sensitive to these
Canadian sources then additional analyses will be performed to more accurately quantify and
include the effects from more of the smaller rivers/streams and WWTP within the model domain.
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Available Data Sources
Acceptance criteria
No data collection is planned for this project and specific quality objectives are not being
specified for existing data or for modeling results. However, data from existing repositories will
be used for model calibration and evaluation purposes and the following acceptance criteria will
be applied:
Data Reasonableness. Data quality of existing data will be evaluated where available. Best
professional judgment will be used to identify erroneous or outlier data and these
observations will be removed from the data set.
Data Representativeness. Data will be used that are reasonably complete and representative of
the location or time period under consideration. Incomplete data sets will be used if they are
considered representative of conditions during the period of interest. Data from outside the
period of interest will be used only if no other data are available. In this case, best
professional judgment will be used to determine the utility of the available data.
Data Comparability. Long-term water quality monitoring programs often collect, handle,
preserve, and analyze samples using methodologies that evolve over time. Best professional
judgment will be used to determine whether/if data sets can be compared. The final project
report will detail any caveats or assumptions that were made when using data collected with
differing sampling or analysis techniques.
Data set descriptions
This list identifies those repositories that contain relevant data; however, additional sources of
information may be considered as needed and/or as new sources are identified. Below is a
description of each repository identified in Appendix 4 along with a URL describing each
program in more detail. In most cases data are available in electronic format.
Ecology Marine Waters Monitoring Data
The Department of Ecology has monitored water quality at approximately 40 stations within
Puget Sound on a monthly basis since 1975. Some stations are monitored every year while some
are monitored on a rotating schedule.
URL: wat/mwm intr.html
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Ecology South Puget Sound Field Studies
Ecology has been conducting a water quality study focused on low DO levels in South Puget
Sound. Field surveys occurred from 1994 to 2007. Data include both river and wastewater
treatment plant effluent water quality.
URL: sound/dissolved oxygen study.html
Ecology Central Basin/Possession Sound Primary Production Study
From October 1998 through October 2001 Ecology conducted a study to assess whether primary
production in Central Puget Sound and Possession Sound would be affected by the addition of
nutrients (Newton and Van Voorhis, 2002). Data collected during this study will provide rate
estimates for algal production as a function of light, season, and other controlling factors.
Ecology Puget Sound Mooring Data
Since 2005 the Department of Ecology has maintained three moorings in Puget Sound in order to
provide continuous data for investigation of status and trends of marine water quality. The
moorings are located at piers and docks in Budd Inlet, Squaxin Passage, and Clam Bay and
provide 15-minute values for temperature, conductivity (used to calculate salinity), DO, and
chlorophyll a fluorescence.
Ecology Freshwater Ambient Monitoring Data
Ecology maintains a freshwater ambient monitoring network that includes numerous sites on
rivers and streams within the greater Puget Sound area.
URL: riv/rv main.html
Hood Canal Dissolved Oxygen Program
Hood Canal Dissolved Oxygen Program (HCDOP) is a partnership of 28 organizations that
conducts monitoring and analysis to determine sources of and potential corrective actions for the
low DO in Hood Canal and its effects on marine life. HCDOP monitors marine water quality as
well as water quality in rivers, streams, and groundwater sources that discharge into Hood Canal.
Monitoring of present-day water properties in the canal is done using a combination of target
field efforts, citizen volunteers, and by moorings with near-realtime data transmission
capabilities (see description of „APL ORCA Mooring Data‟ below).
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APL ORCA Mooring Data
Oceanic Remote Chemical Analyzers (ORCA) are autonomous moored profiling systems that
provide real-time data streams of water and atmospheric conditions. They consist of a profiling
underwater sensor package and a surface mounted weather station. Currently there are four
ORCA mooring systems deployed, all in Hood Canal. Past deployments of the ORCA system
have been in South Puget Sound (Carr Inlet) and in Central Puget Sound (near Point Wells).
UW PRISM Field Studies
In partnership with Ecology, the University of Washington PRISM (Puget Sound Regional
Synthesis Model) program conducted approximately twice-annual monitoring cruises
encompassing approximately 40 stations located throughout Puget Sound starting in June 1998
and continuing through July 2004.
King County DNR Puget Sound Marine Monitoring Data
King County‟s Marine and Sediment Assessment Group supports a comprehensive, long-term
marine monitoring program that assesses water quality in Central Puget Sound. Their program
consists of offshore water quality, beach water quality, intertidal sediment, algae, and clam
King County DNR Stream and River Monitoring Data
Many streams and rivers in the King County service area are assessed as part of the routine
monitoring efforts by the King County Major Lake and Stream Monitoring Program. Monthly
baseflow water quality samples have been collected at many of these sites since 1976. Data are
analyzed to characterize the general water quality of the stream, determine if applicable state and
federal water quality criteria are met, and to identify long-term water quality trends.
USGS Freshwater River/Stream Data
The United States Geological Survey maintains a network of streamflow gaging stations,
including sites in the study area.
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Sinclair/Dyes Inlet Flow Data
The U.S. Navy‟s Puget Sound Naval Shipyard, in partnership with a variety of federal, state, and
local governments, tribes, and community groups, developed and maintained a flow network for
streams and creeks tributary to Sinclair and Dyes Inlets from 2001 to 2005 (May et al., 2005).
dyes inlets/sinclair cd/DATA/Data Directory.html
Wastewater treatment plant monthly data reported under National Pollution Discharge
Elimination System (NPDES) permits are available through Water Quality Permit Life Cycle
System (WPLCS).
Canadian data set descriptions
This list identifies those repositories that contain relevant data for Canadian waters; however,
additional sources of information may be considered as needed and/or as new sources are
identified. A URL has been provided that describes each program in more detail. In most cases
data are available in electronic format.
Water Survey of Canada National Water Quantity Survey Program Data
The Water Survey of Canada (WSC) is the national agency responsible for the collection,
interpretation and dissemination of standardized water resource data and information in Canada
which includes data on aquatic quality, water quantity and sediment transport. The Water
Survey of Canada provides real-time, current year and historical information for a network of
over 2,200 sites in Canada and maintains a database containing historic data for some 5,300 non-
active sites for the country.
Environment Canada Municipal Water and Wastewater Survey Data
The Municipal Water and Wastewater Survey (MWWS) provides basic data on municipal water
and wastewater. It is the latest in a series of such surveys. Survey information is available on a
municipality specific basis.
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Environment Canada Pacific and Yukon Region Water Quality Monitoring Program Data
Pacific and Yukon Region's Environment Canada has been monitoring surface water quality for
many years throughout British Columbia and the Yukon Territory. The larger part of the
program is implemented with the BC Ministry of Environment in BC, with a smaller program
being conducted with the Yukon Territory or solely by Environment Canada. These monitoring
programs play an important role in determining long term trends in water quality, identifying
emerging issues related to the aquatic environment and providing information to Canadians.
Model Calibration and Evaluation
Once the model setup is completed, the model will be calibrated through comparison with
observed data collected in Puget Sound. The term calibration is defined as the process of
adjusting model parameters within physically defensible ranges until the resulting predictions
give the best possible match with observed data. In some disciplines, calibration is also referred
to as parameter estimation. Model evaluation is defined as the process used to generate
information to determine whether a model and its analytical results are of a quality sufficient to
serve as the basis for a decision and whether the model is capable of approximating the real
system of interest (USEPA, 2008). In some disciplines, evaluation is also referred to as
validation, confirmation, or verification.
To help ensure that the process of model calibration and evaluation remain independent, a subset
of the available data will be withheld during model calibration. The withheld data will be used
to evaluate the model output. In situations involving data scarcity it may be necessary to use all
available data for calibration purposes. The final report will detail those data sets (or subsets
thereof) that were used for both calibration and evaluation of the model.
Model calibration is an iterative procedure that is achieved using a combination of best
professional judgment and quantitative comparison with a subset of the measured data. For
example, the nitrogen balance will involve adjustment of nitrification and organic nitrogen
hydrolysis rates, as well as uptake rates by phytoplankton. The phosphorus balance will include
adjustment of organic phosphorus decay rate and uptakes rates by phytoplankton. Chlorophyll a
data will represent phytoplankton density and will be used to adjust algal growth, die-off,
respiration, and settling. Finally, phytoplankton growth, re-aeration, and BOD
in combination
with nearshore SOD, will be specified to obtain the best match with observed DO data. When
possible, direct measurements of the rate constants for key processes will be used to calibrate the
model (e.g., maximum growth rates of phytoplankton, half-saturation constants, etc.).
Both calibration and evaluation of the model will rely on a combination of quantitative statistics
for goodness-of-fit and visual comparison of predicted and observed time series and depth
profiles (Krause et al., 2005). This methodology is consistent with the standard of practice that
has been established for similar modeling programs and other detailed studies such as the Hood
Canal Dissolved Oxygen Program, the UW PRISM Modeling Program, the Budd Inlet Scientific
Study (Aura Nova Consultants et al., 1998), the Deschutes River/Capitol Lake/Budd Inlet Water
Page 26 - DRAFT
Quality Study (Roberts et al., 2008a), and the South Puget Sound Dissolved Oxygen Study
(Roberts et al., 2008b). Bias will likely be measured by the average residual of paired values
(predicted-observed) and precision by the root mean square error of paired values. Numeric
targets for precision and bias are not specified but it is our intention to minimize these
discrepancies between observed and modeled data as much as possible, consulting with U.S.
EPA (2008) and the MTAC.
Data for model calibration and evaluation will be used in a hierarchal fashion. Preference will be
to use data that are coincident in both time and space (i.e., Puget Sound from 1999-2008) to the
model simulations. If data are scarce then only spatially coincident data may be considered (i.e.,
Puget Sound from any time period). Should data or published guidance for a particular
parameter value be lacking entirely for Puget Sound (or a region thereof) then published values
from similar aquatic systems may be used. In all cases, best professional judgment will be used
for the final determination of what data are used to calibrate and evaluate the model, and the
process will be documented in the final reports.
Sensitivity and Uncertainty Analyses
To evaluate model performance and the variability of results, sensitivity and uncertainty analyses
will be carried out. Uncertainty can arise from a number of sources that range from errors in the
input data used to calibrate the model, to imprecise estimates for key parameters, to variations in
how certain processes are parameterized in the model domain. Regardless of the underlying
cause it is good practice to evaluate these uncertainties and reduce them if possible (USEPA,
2008; Taylor, 1997; Beck, 1987).
A model‟s sensitivity describes the degree to which results are affected by changes in a selected
input parameter. In contrast, uncertainty analysis investigates the lack of knowledge about a
certain population or the real value of model parameters. Although sensitivity and uncertainty
analyses are closely related, uncertainty is parameter specific, and sensitivity is algorithm-
specific with respect to model variables. By investigating the relative sensitivity of model
parameters, a user can become knowledgeable of the relative importance of parameters in the
model. By knowing the uncertainty associated with parameter values and the sensitivity of the
model to specific parameters, a user will be more informed regarding the confidence that can be
placed in the model results (USEPA, 2008).
During the calibration process the responsiveness of the model predictions to various
assumptions and rate constants specified will be evaluated. The model setup will likely include
parameters based on literature recommendations and best professional judgment, and estimates
of loads in the absence of data. Specific areas to address with sensitivity and uncertainty
analyses include boundary conditions, meteorologic forcing, sediment fluxes, watershed loads, as
well as process rate parameters. Fundamental parameters will be varied by increasing and
decreasing by a factor of two or an order of magnitude, and the resulting predictions compared to
understand whether a factor has a discernible effect on circulation or water quality predictions.
The final report will document the parameters that are varied and will identify any parameters
that have great uncertainty and strongly influence the results.
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Model Scenarios
After sensitivity analyses have been performed, the calibrated model will be used to evaluate
water quality conditions observed in Puget Sound from 1999 – 2008 and to simulate the effects
of various alternative nutrient loading scenarios. Results from this time period will also be
compared to estimated natural background conditions. Natural conditions are characterized by
the absence of human impacts on the nutrient loading and DO regime.
Modeling natural conditions typically involves creating a natural background model run
corresponding to the existing conditions model run, except that estimated human influences have
been removed as much as possible. Generally, this means removing all point sources and setting
tributaries to natural loads. Accurate estimation of pre-development conditions may be difficult,
so reasonable estimation methods will need to be developed. One possible strategy would be to
set nutrient levels using reference streams/rivers in Puget Sound with the lowest (or nearly the
lowest) nutrient levels observed from 1999 – 2008. Additional, more statistically sophisticated
methods are also being considered. Some of the constituents may remain unchanged between
natural and existing if no information is available to estimate pre-development conditions. The
current marine boundary will be assumed to be natural for the purposes of this study.
Ecology will use the model to determine the impact of human activities on DO concentrations in
Puget Sound. Using the initial calibration to the current point and nonpoint source loads the
model will be applied to 4 to 6 alternate scenarios. The exact scenarios to be evaluated may
change during the project, but likely candidates are as follows:
o Scenario 1 – Natural conditions.
o Scenario 2 – Current rivers and no point sources.
o Scenario 3 – Current point sources and natural conditions for rivers.
o Scenario 4 – Current rivers and maximum permitted point sources.
o Scenario 5 – Current rivers and point sources at projected loadings in 25 years.
Scenario results will be evaluated both as predicted patterns for that scenario and as differences
between scenarios. The water quality standards call for no more than 0.2 mg/L degradation
below water quality standards, or below natural conditions if natural conditions result in
concentrations that are less than the values used to define the water quality standards (WAC 173-
201A). It is expected that Ecology will apply the model for numerous scenarios and longer
durations in the future.
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Model Output Quality (Usability) Assessment
Final assessment of model performance will be conducted and summarized in the final report.
This summary will evaluate whether the outcomes have met the project‟s original objectives.
Criteria to be evaluated include whether or not the water quality model:
Behaves in a manner that is consistent with the current understanding of processes known
to affect water quality in the Puget Sound estuary system.
Realistically reproduces variations in water quality observed within individual sub basins
of Puget Sound on inter-annual, seasonal, and possibly intra-seasonal timescales.
Project Deliverables and Schedule
The following deliverables will be developed for this project according to the schedule presented
in Table 2:
Hydrodynamic model report (PNNL).
Water quality model report (PNNL).
Final project report and summary (including detailed documentation of the results and
methods used to estimate loading from nonpoint and point sources).
Focus sheet.
PNNL will prepare a draft report summarizing the development of the hydrodynamic model of
Puget Sound. The report will present a review of available data used in model development.
Model setup section will include a summary of bathymetry data, model grid, and a description of
initial and boundary conditions. Qualitative and quantitative calibration of the model will be
discussed along with model behavior and the ability to reproduced salient Puget Sound features.
PNNL will also prepare a draft report summarizing the development of the nutrients and water
quality model of Puget Sound. The report will present a review of available data used in model
development. The model setup section will include a summary of the point source and the
tributary load data, the model grid, and a description of initial and boundary conditions. The
qualitative and quantitative calibration of the model will be discussed along with a description of
the model behavior and its ability to reproduce the salient Puget Sound features. The
responsiveness of the model and the uncertainty associated with the model predictions will be
discussed to summarize the sensitivity analysis results. Also, application of the model for the
selected scenarios will be included along with a discussion of the implication of the results.
For each of PNNL report outlined above a draft report will be provided to Ecology for
comments; once these comments are addressed, revised draft reports will be distributed to the
PAC, and possibly the MTAC, for additional comments. Final reports will be prepared after
incorporating Ecology‟s and the PAC‟s comments on draft reports.
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Ecology will prepare a draft report summarizing the development of the intermediate-scale
hydrodynamic and water quality models for Puget Sound. The report will present a
comprehensive overview and synthesis of the two PNNL reports outlined above and serve as
final documentation for the project. Following internal review by the project team and the
Department of Ecology, the project report will be sent to the PAC for external review. After
external review comments are addressed, the comprehensive Ecology report will be finalized. A
focus sheet will then be created to summarize and highlight major findings from the project.
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Albertson, S.L., J. Bos, K. Erickson, C. Maloy, G. Pelletier, and M.L. Roberts, 2007. South
Puget Sound Water Quality Study, Phase 2: Dissolved Oxygen. Washington State Department
of Ecology, Olympia, WA. Publication No. 07-03-101.
Albertson, S. L, K. Erickson, J. A. Newton, G. Pelletier, R. A. Reynolds, and M. L. Roberts,
2002. South Puget Sound Water Quality Study, Phase 1. Washington State Department of
Ecology, Olympia, WA. Publication No. 02-03-021.
Aura Nova Consultants, Brown and Caldwell, Inc., Evans-Hamilton, Inc., J.E. Edinger and
Associates, Washington State Department of Ecology, and A. Devol, University of Washington
Department of Oceanography, 1998. Budd Inlet Scientific Study. Prepared for LOTT
Wastewater Management District. 300 pp.
Babson A., M. Kawase, and P. MacCready, 2006. Seasonal and Interannual Variability in the
Circulation of Puget Sound, Washington: A Box Model Study. Atmosphere-Ocean 44(1): 29-45.
Bahng, B., M. Kawase, J. Newton, A. Devol, and W. Reuf, 2007. Numerical Simulation of
Hypoxia in Hood Canal, Washington. Proceedings of the 2007 Georgia Basin/Puget Sound
Research Conference, Vancouver, British Columbia.
Beck, M.B., 1987. Water Quality Modeling: A Review of the Analysis of Uncertainty. Water
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Breithaupt, S., T. Khangaonkar, S. Liske, and J. Takekawa, 1999. Hydrodynamic and Sediment
Transport Modeling of the Nisqually River Delta to Evaluate Habitat Restoration Alternatives.
Proceedings of the 1999 International Water Resources Conference, Seattle, WA.
Bricker, S.B., C.G. Clement, D.E. Pirhalla, S.P. Orlando, and D.R.G. Farrow, 1999. National
Estuarine Eutrophication Assessment: Effects of Nutrient Enrichment in the Nation‟s
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Casulli, V. and R.A. Walters, 2000. An Unstructured, Three-Dimensional Model Based on the
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Chapra, S.C., 1997. Surface Water-Quality Modeling. WCB/McGraw-Hill, Boston, MA.
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Primitive Equation Ocean Model: Application to Coastal Ocean and Estuaries. Journal of
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Cohen, T.A., D.L. Caulder, E.J. Gilroy, L.D. Zynjuk, and R.M. Summers, 1992. The validity of
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nutrient loads entering Chesapeake Bay. Water Resources Research 28(9), 2353-2363.
Edmondson, W.T., 1991. The Uses of Ecology: Lake Washington and Beyond. University of
Washington Press, Seattle, WA.
Embrey, S.S. and E.L. Inkpen, 1998. Water-Quality Assessment of the Puget Sound Basin,
Washington, Nutrient Transport in Rivers, 1980-93. U.S. Geological Survey Water-Resources
Investigations Report 97-4270, Tacoma, WA. 30 pp.
Glibert, P.M., S. Seitzinger, C.A. Heil, J.M. Burkholder, M.W. Parrow, L.A. Codispoti, and V.
Kelly, 2005. The Role of Eutrophication in the Global Proliferation of Harmful Algal Blooms:
New Perspectives and New Approaches. Oceanography 18(2), 198-209.
Howarth, R., 2006. From presentation to the White House Office of Science and Technology
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... The study area and human uses are outlined in Sackmann (2009). The Washington State Blue Ribbon Panel on Ocean Acidification (2012) describes when and how ocean acidification concerns were first identified as well as the state of knowledge at that time. ...
... While our current focus is on Puget Sound, the model extends to the Straits of Juan de Fuca and Georgia ( Figure 3b); therefore, we refer to the model as the Salish Sea Model (SSM). This project builds on related work on dissolved oxygen (Sackmann, 2009;Khangaonkar et al., 2012a,b;Roberts et al., 2015), and a previously published model approach document . Bianucci et al. (2017) describe setup and calibration of the Ocean Acidification Module of the SSM. ...
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Major El Niño events and oceanic heat waves are linked to the range expansion of many marine species. For the shores of the northeast Pacific, we compared range expansion in the European green crab, Carcinus maenas , which was introduced to San Francisco Bay prior to 1990, to that of the native lined-shore crab, Pachygrapsus crassipes, which has existed on the coast since at least the end of the last Ice Age (>10,000 years ago). The initial northern range limit of these species was central California and central Oregon, respectively. Both species increased their northern range along the open coast to northern Oregon, Washington and Vancouver Island after strong El Niño events. C. maenas , however, in just a matter of decades, successfully established populations in inlets on the west coast of Vancouver Island, and possibly also in the Salish Sea, while P. crassipes, in thousands of years, never has. We hypothesize that this difference in invasion success is due to the shorter larval duration of C. maenas , < 2 months, compared to that of P. crassipes , 3-4 months and timing of larval release, winter for both species. Because the residency times of water in the inlets of the west coast of Vancouver Island are ~1-2 months, they can act as an incubator for the larvae of C. maenas , while those of P. crassipes are likely flushed out to the open sea before they can complete their development.
We consider the appropriateness of "rating curves" and other log linear models to estimate the fluvial transport of nutrients. Split-sample studies using data from tributaries to the Chesapeake Bay reveal that a minimum variance unbiased estimator (MVUE), based on a simple log linear model, provides satisfactory load estimates, even in some cases where the model exhibited significant lack of fit. For total nitrogen (TN) the average difference between the MVUE estimates and the observed loads ranges from -8% to +2% at the four sites. The corresponding range for total phosphorus (TP) is -6% to +5%. None of these differences is statistically significant. The observed variability of the MVUE load estimates for TN and TP, which ranges from 7% to 25% depending on the case, is accurately predicted by statistical theory.
Conference Paper
Puget Sound is a complex fjordal estuarine system located in the Northwest Pacific coast of the state of Washington. It is one of the most pristine estuarine systems in the United States that provide marine habitats for salmon and marine wildlife. Circulation in Puget Sound exhibits fjordal characteristics, dominated by tides propagating from Pacific Ocean through the Strait of Juan de Fuca and freshwater discharges from various rivers and runoff. Local circulation patterns in the major sub-basins within Puget Sound are complex and different from each other due to their distinct features such as complex coastlines, existence of mudflats, freshwater inflows, presence of islands, and man-made shoreline modifications. Over the last century, considerable nearshore tidal marshland habitats have been lost due to historical diking and agricultural land use. A number of habitat restoration projects focused on restoring estuarine functions such as tidal flushing, brackish nearshore environment, supply of nutrients and sediment have been proposed with an overall goal of recovering fish stocks. To better understand the details of circulation characteristics in Puget Sound, and to help assess the feasibility of the proposed restoration actions, a hydrodynamic model for the entire Puget Sound with high resolution in the nearshore regions was needed. In this paper, we present the development of a three-dimensional circulation model of Puget Sound using an unstructured finite volume framework (FVCOM). The model has been constructed with sufficient resolution in the nearshore region to address the complex coastline, multi-tidal channels and tidal flats. To account for the influences of ocean water intrusion from the Strait of Juan de Fuca and the Fraser River plume from the Georgia Strait, model open boundaries are extended to the entrance of the Strait of Juan de Fuca and the north end of the Georgia Strait. The model is driven by tides, meteorological forcing and river inflows. Model results for circulation patterns, freshwater plumes and particle trajectories are presented and discussed. Preliminary results show that the model successfully reproduces general features such as propagation of tides, currents, in the main basin as well as wetting and drying, freshwater plumes, and nearshore salinity distribution.
Conference Paper
A 3-D hydrodynamic circulation and effluent transport model was developed using a combination of the far field model (EFDC) and near-field plume models for the 9 miles of Cherry Point coastline from Point Whitehorne to Sandy Point in the Strait of Georgia, Washington. This study was initiated by the Cherry Point Industries to specifically evaluate the potential for cumulative effects from multiple sources of industrial effluent in the study area. The EFDC model was setup and calibrated using oceanographic data that was collected specifically for the model development. Sensitivity analysis was conducted to evaluate the importance of baroclinic forcing in comparison to barotropic motion. The near-field dilution and farfield effluent plume transport components were calibrated using historical dye study, data from the site. The study showed conclusively that accumulation of effluent does not occur. Effluent concentrations reach a dynamic steady state within a few days from the start of the discharge. The distribution patterns for all constituents consistently indicate that water quality standards will not be exceeded in the study area due to the Cherry Point discharges.
This paper argues in favor of four criteria for assessing the performance of the Office of Science and Technology Policy (OSTP) within the Executive Office of the US President: trying to killing bad ideas (and sometimes succeeding), mobilizing expertise and confidence to support crisis response, identifying new issues and developing presidential policy initiatives, and catalyzing and coordinating multi-agency science and technology activities, especially in response to presidential goals. These criteria are illustrated with episodes from OSTP’s history. They place OSTP in a variety of roles, ranging from disinterested broker of expertise to policy entrepreneur, but always as an agent of the President. Although a full assessment using these criteria may not be feasible due to data limitations, their identification is nonetheless valuable in order to spark scholarly debate and further research and to support planning by OSTP staff and their interlocutors inside and outside of government.
A numerical modeling is applied to study the time-space variation of dissolved oxygen (DO) in Hood Canal, Washington, USA. The tool is a bio-geochemical subsystem, coupled within an exchange circulation model. It is a simple nitrogen-based model to resolve DO, nutrients, phytoplankton, zooplankton and detritus. Regional Ocean Modeling System was used to simulate exchange circulation. The base goal of the modeling is to hindcast long-term mean seasonal variation of DO. The circulation was forced by salinity at the open boundary, river discharge and 6-constituent tides, and the bio-geochemical subsystem by solar radiation at the surface. Long-term mean seasonal climatology of the open boundary conditions and forcing conditions were prepared from historical data. The model was initially spun up for 9 months with physics only. Afterwards, the bio-geochemical sub-system was spun up for about 3 months (~ a little longer than residence time for a conservative passive tracer), and integrated for two more model years. The simulation results compare with the data from a moored profiler, Ocean-Remote- Chemical Analyzer (ORCA), at one station in Southern Hood Canal. The comparison is summed up as follows: 1. Salinity reached to an equilibrium state, implying that the salinity-driven exchange circulation is in equilibrium. 2. Bio-geochemical subsystem is still under adjustment towards an equilibrium state. Average nitrogen concentration in the whole Canal tends to approach to the average at the open boundary. The adjustment time scale is of years, significantly longer than the residence time scale of purely passive tracers (~months). 3. Despite under the longer-term adjustment, the pattern, in seasonality and vertical distribution, of chlorophyll and DO compares well with the one from a moored profiler. Overall, however, magnitudes of model chlorophyll and DO are off: model chlorophyll value is significantly lower than the observed near the surface, while model DO shows higher than the observed near the bottom. 4. The sustainability of the spring bloom is significantly shorter than the observed: the spring bloom does not sustain as much as in the observation. In the model, the short sustainability is clearly associated with nutrient limitation right after the short bloom. The interim results indicate 4 conclusive aspects: 1. A short-term (1 ~ 2 year long) simulation may not be enough to calibrate a bio- geochemical subsystem, coupled within a circulation model due to incomplete equilibrium.
This paper reviews the role of uncertainty in the identification of mathematical models of water quality and in the application of these models to problems of prediction. More specifically, four problem areas are examined in detail: uncertainty about model structure, uncertainty in the estimated model parameter values, the propagation of prediction errors, and the design of experiments in order to reduce the critical uncertainties associated with a model. Enclosed is the main body of the review dealing in turn with (1) identifiability and experimental design, (2) the generation of preliminary model hypotheses under conditions of sparse, grossly uncertain field data, (3) the selection and evaluation of model structure, (4) parameter estimation (model calibration), (5) checks and balances on the identified model, i. e. , model 'verification' and model discrimination, and (6) prediction error propagation.