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U.S. EPA Long Island Sound Office
A DECISION SUPPORT FRAMEWORK
TO FACILITATE NITROGEN LOAD REDUCTIONS
IN LONG ISLAND SOUND (LIS) WATERSHED
EPA Grant No. LI 97286104-0
Prepared By:
Kevin J. Farley, Manhattan College
and
Sri Rangarajan, HydroQual, Inc.
Project Period: 10/1/2004 – 3/31/2006
ACAD.164
November 12, 2006
ii
TABLE OF CONTENTS
Section Page
PUBLIC SUMMARY..................................................................................................................................PS-1
1 PROJECT DESCRIPTION............................................................................................................... 1-1
2 STUDY AREA DESCRIPTION ...................................................................................................... 2-1
3 SELECTION OF MODELING APPROACH.............................................................................. 3-1
4 WATERSHED MODEL CALIBRATION .................................................................................... 4-1
4.1 MODEL DATABASES.............................................................................................................. 4-1
4.2 CALIBRATION OF TEST WATERSHEDS......................................................................... 4-3
4.2.1 Hydrology Calibration..................................................................................................... 4-4
4.2.2 Water Quality Calibration............................................................................................. 4-15
5 MODEL APPLICATION TO CT/NY WATERSHEDS.......................................................... 5-28
6 MANAGEMENT TOOL DEVELOPMENT............................................................................... 6-1
6.1 AGRICULTURAL BMPs........................................................................................................... 6-2
6.2 GROUNDWATER LOAD ADJUSTMENTS....................................................................... 6-3
6.3 URBAN BMPs.............................................................................................................................. 6-4
6.4 WASTEWATER DISCHARGE REDUCTIONS ................................................................. 6-4
6.5 COST CALCULATIONS........................................................................................................... 6-5
6.6 PROGRAM EXECUTION ....................................................................................................... 6-7
7 CONCLUSIONS AND RECOMMENDATIONS....................................................................... 7-1
8 REFERENCES .................................................................................................................................... 8-1
9 ACKNOWLEDGMENTS................................................................................................................. 9-1
10 PRESENTATIONS/PUBLICATIONS/OUTREACH ............................................................. 10-1
OTHER INFORMATION
APPENDIX A – COMPARISON OF BMP MODELS
APPENDIX B – AVGWLF INPUT DATA COMPILATION
APPENDIX C – ESTIMATED NITROGEN LOADS FOR WATERSHEDS IN CT & NY
APPENDIX D – VBA SOURCE CODE FOR NITROGEN LOAD REDUCTIONS & COST
ANALYSIS
iii
LIST OF FIGURES
Figure Page
2-1. Study Area .........................................................................................................................................2-2
2-2. Distribution of Land Uses in the Study Area............................................................................... 2-3
3-1. GWLF Model Components ........................................................................................................... 3-4
4-1(a). Daily Time-Series Comparison for Salmon Watershed.............................................................. 4-9
4-1(b). Flow Duration Curve for Salmon Watershed (Monthly Time-series).................................... 4-10
4-2(a). Daily Time-series Comparison for Quinnipiac Watershed...................................................... 4-11
4-2(b). Flow Duration Curve for Quinnipiac Watershed (Monthly Time-series) ............................. 4-12
4-3(a). Daily Time-series Comparison for Norwalk Watershed .......................................................... 4-13
4-3(b). Flow Duration Curve for Norwalk Watershed (Monthly Time-series).................................. 4-14
4-4(a). Monthly TN Mass Comparison for Salmon Watershed........................................................... 4-19
4-4(b). Scatterplot of Monthly TN Mass for Salmon Watershed ........................................................ 4-20
4-4(c). TN Load Duration Curve for Salmon Watershed .................................................................... 4-21
4-5(a). Monthly TN Mass Comparison for Quinnipiac Watershed .................................................... 4-22
4-5(b). Scatterplot of Monthly TN Mass for Quinnipiac Watershed.................................................. 4-23
4-5(c). TN Load Duration Curve for Quinnipiac Watershed .............................................................. 4-24
4-6(a). Monthly TN Mass Comparison for Norwalk Watershed ........................................................ 4-25
4-6(b). Scatterplot of Monthly TN Mass for Norwalk Watershed ...................................................... 4-26
4-6(c). TN Load Duration Curve for Norwalk Watershed .................................................................. 4-27
5-1. TN Loads for Watersheds in Connecticut .................................................................................5-31
5-2. TN Loads for Watersheds in New York ....................................................................................5-32
5-3. Component TN Loads from Various Nonpoint Sources in Connecticut............................. 5-33
5-4. Component TN Loads from Various Nonpoint Sources in New York................................ 5-34
iv
LIST OF TABLES
Table Page
4-1. General Targets/Tolerances for Watershed Model Applications............................................. 4-4
4-2(a). TRANSPORT Parameters for the Salmon Watershed .............................................................. 4-6
4-2(b). Other TRANSPORT Parameters for the Salmon Watershed................................................... 4-7
4-3. Comparison of Hydrology Statistics for the Three Test Watersheds....................................... 4-8
4-4. Qualitative Comparison of Annual TN Loadings ..................................................................... 4-17
4-5. NUTRIENT (Nitrogen) Parameters for the Salmon Watershed............................................ 4-18
5-1. Weather Data Compilation for Non-Connecticut Watersheds............................................... 5-28
v
LIST OF ABBREVIATIONS
AVGWLF Arc View-based Generalized Watershed Loading Functions
AGNPS Agricultural Nonpoint Source Pollution Model
BASINS Better Assessment Science Integrating Point and Nonpoint Sources
BMPs Best Management Practices
CCMP Comprehensive Conservation and Management Plan
CLEAR Center for Land Use Education and Research
CT State of Connecticut
CTDEP State of Connecticut Department of Environmental Protection
CWA Clean Water Act
DEM Digital Elevation Model
DO Dissolved Oxygen
GIS Geographic Information Systems
GWLF Generalized Watershed Loading Functions
HSPF Hydrologic Simulation Program in FORTRAN
HUC Hydrologic Cataloguing Unit
LIS Long Island Sound
LISS Long Island Sound Study
MAGIC Map and Geographic Information Center Libraries at the University of CT
MS-EXCEL Microsoft Excel
NEIWPCC New England Interstate Water Pollution Control Commission
NHD National Hydrography Dataset
NOAA National Oceanic and Atmospheric Administration
NRCS Natural Resources Conservation Services
NY State of New York
NYSDEC/DEC New York State Department of Environmental Conservation
PLOAD Pollutant Loading Assessment Model built in EPA BASINS
PRedICT Pollution Reduction Impact Comparison Tool
SCS Soil Conservation Services
STATSGO State Soil Geographic Database
TMDL Total Maximum Daily Load
USEPA/EPA United States Environmental Protection Agency
USGS United States Geological Survey
USLE Universal Soil Loss Equation
VBA Visual Basic Application
WTM Watershed Treatment Model
PS-1
PUBLIC SUMMARY
This project was conducted to support the Long Island Sound Study (LISS) Management
Committee’s objective of estimating and tracking total nitrogen loads and potential reductions
considering both land uses and best management practices (BMPs). The critical issues pertinent to
land uses previously identified by the Committee include: (a) minimization of impacts from existing
and newer developments, and (b) exploration of region-wide and consistent land use and
management practices within the Long Island Sound (LIS) watershed that involves multiple States
and local jurisdictions.
A decision-support framework was developed and tested based on the following steps.
First, a comprehensive literature review was performed of off-the-shelf mathematical tools available
for nitrogen load estimation and tracking based on the land uses and BMPs. In consultation with
the LIS Environmental Protection Agency (EPA) and state representatives from Connecticut and
New York, the Arc View-based Generalized Watershed Loading Functions (AVGWLF) model was
chosen to estimate loadings from the contributing point and non-point sources of pollution.
Both generic (e.g., EPA Better Assessment Science Integrating Point and Nonpoint Sources
– BASINS) and specific databases available in the two states were reviewed to develop the
appropriate set of model parameters for AVGWLF. The generated streamflows were compared to
United States Geological Survey (USGS) streamflow data for a select set of watersheds. In addition,
AVGWLF flow results were compared with the previous model calibration efforts that were
conducted by the State of Connecticut Department of Environmental Protection (CTDEP) using a
more detailed and parameter-intensive Hydrologic Simulation Program in Fortran (HSPF) model
(AQUA TERRA and HydroQual, 2001). After obtaining satisfactory calibration for the AVGWLF
generated flows, water quality calibration of the AVGWLF model was initiated. Since AVGWLF
does not account for in-stream transformations and also generates monthly pollutant loadings as
output, the modeled TN loadings were compared with the loadings computed from the observed
data of daily flows and TN concentrations. Minor parameter adjustments were established in a
global manner so that the AVGWLF parameters could be applied globally for the entire LIS
watershed.
The calibrated AVGWLF model was applied to remaining watersheds in the States of New
York and Connecticut to estimate the baseline total nitrogen loadings. Many BMPs have been
installed by the agricultural and urban communities within these two states. However, due to limited
information available on the specific types of BMPs and their performances, the study team
developed baseline loadings without considering the effects of these existing BMPs.
The Management Committee envisioned a simpler management tool that used information
obtained from the AVGWLF model, to assist the state officials and local watershed and municipal/
agricultural communities in making decisions on pollution control alternatives. One of the primary
PS-2
reasons for selection of AVGWLF was the direct linkage of the program to the Pollution Reduction
Impact Comparison Tool (PRedICT) (Evans, 2003). During the course of this project, certain
deficiencies were noted in the application of PRedICT as a simple management tool to nitrogen load
reductions to LIS. For example, PRedICT required full implementation of AVGWLF for load
calculations that might be resource-intensive for intended users of this tool. Also, the optimization
tool within PRedICT was not functional when this project was conducted.
Therefore, a new management tool was developed by the study team in Microsoft Excel
(MS-Excel) to identify the potential set of BMPs that can be used to achieve the desired levels of
nitrogen load reductions. The tool offers significant flexibility for the States of New York and
Connecticut to track the current loads, modify the treatment performances of specific BMPs,
modify cost information to reflect watershed-specific construction and operation/ maintenance
costs of BMPs, and to account for nitrogen reductions resulting from both existing and future
BMPs. The tool can guide the screening and selection of BMPs to achieve the targeted overall 10%
nitrogen load reductions from the urban and rural non-point sources of pollution, and to develop
cost-effective nitrogen management strategies by exploring potential trading credits between the
point and non-point sources in order to achieve the overall goal of eliminating hypoxia in the
western end of LIS.
1-1
SECTION 1
1 PROJECT DESCRIPTION
The Long Island Sound (LIS) provides significant recreational and commercial value, with
more than 8 million people living within the watershed and millions flocking to its shores each year
for recreation. An estimated $5 billion is generated annually in the regional economy from boating,
commercial and sport fishing, swimming, and beach-going. Among the serious water quality
problems in LIS is the low dissolved oxygen (DO) level, a condition called hypoxia. Previous
studies have identified that nitrogen was the cause of hypoxia. As a result, a 58.5% reduction in
nitrogen loads was assigned through a Total Maximum Daily Load (TMDL) study conducted in
1990s to municipalities that discharge into LIS. The State of Connecticut (CT) has been developing
a trading program that will achieve an overall 64% reduction in nitrogen loads from wastewater
treatment plants with several hundreds of million dollars of savings in upgrade costs.
Similarly, the in-basin non-point sources of pollution have been targeted by the EPA and
state officials to achieve a 10% nitrogen load reduction from the contributing urban and non-urban
land uses. In addition, continuing development has altered the land uses and degraded water quality
in the 16,000 square mile LIS watershed that includes both in-basin and out-of-basin drainage areas.
The connection between current and future land uses has been established through a comprehensive
conservation and management plan (CCMP) that will influence future land uses in CT and New
York (NY) through watershed- and resource-based planning.
Characterization of nitrogen loadings from land uses and management practices is therefore
critical in the implementation of CCMP through pollution control and water quality improvement
practices (called Best Management Practices, BMPs). Some of the BMPs pertinent to urban and
rural non-point sources include: tidal wetlands/riparian wetlands restoration, education, manure
management, diversion and treatment of runoff from farmlands and confined animal feeding
operations, controlled application of lawn fertilizers, vegetated filter strips, grassed swales,
constructed wetlands, improved infiltration practices, detention and retention facilities, erosion and
sediment control, proper calibration and operation of nutrient application equipment, management
of failing or improperly maintained septic systems, and grazing management.
Previous studies such as AQUA TERRA and HydroQual (2001) and Moore et al. (2004)
have developed tools to assess nitrogen loads from tributaries that drain to LIS. The tool developed
for Connecticut Department of Environmental Protection (CTDEP) in the AQUA
TERRA/HydroQual study was a Hydrologic Simulation Program in Fortran-HSPF framework.
This model is parameter-intensive requiring significant manual and financial resources. It also
demands extensive experience for watershed managers (state and other local governments and
agricultural/ conservation staff) to allow its application for estimating and tracking nitrogen loads.
1-2
A simpler tool is more appropriate under the circumstances when there are limited resources for
application and future on-going use of the models to screen and select BMPs based on site-specific
and cost considerations.
The LISS Management Committee was interested in developing a simpler management tool
for estimating and tracking nitrogen loads and their reductions based on land uses and BMPs.
Further to an extensive review of land use and development practices, the following critical issues
have previously been identified by the Committee:
a. Reduction of impacts from existing land uses, particularly the urbanized areas, to improve
coastal water quality through non-point source management;
b. Minimization of impacts from newer developments to prevent further degradation of water
quality;
c. Region-wide planning based on effective water quality/ habitat protection, better
information, training and technical assistance, leading to consistent land use and
management practices;
d. Establishment of open space preservation and conservation practices that integrate growth
and development with water quality protection; and
e. Increased public access for enjoyment of LIS that will improve from public investments.
With these critical issues guiding the potential future uses of this management tool, the basic
requirements included incorporation of land uses and consequent nitrogen loadings and the BMPs
and associated treatment performances. The tool had to be interactive enough for the watershed
managers to evaluate loadings from existing land uses and specify various scenarios that reflect
future developments and combinations of BMPs (along with their associated costs and performance
variations). The tool should be simple so the states/ other jurisdictions can efficiently use their
financial and staff resources to develop management plans and effectively collaborate with
stakeholders (e.g., public, farmers, and environmental groups) to implement them.
In addition to the land use practices and BMPs, the LIS TMDL also calls for evaluation of
potential trading between the point and non-point sources of pollution. Therefore, the tool was
designed to be flexible enough to incorporate, in the future, the site-specific nitrogen loadings,
control costs, and nitrogen attenuation factors for individual point sources in this management
framework. Upon development, the comprehensive management tool can be used to explore and
evaluate the potential trading strategies to meet the overall nitrogen reductions required by LIS
TMDL for the point and non-point pollution sources, with the overall goal of eliminating hypoxia in
the western end of LIS.
The project was accomplished by the Manhattan College-HydroQual team in the following
sequence: (1) Review the off-the-shelf mathematical tools that can help in achieving the desired goal
- estimation and tracking of nitrogen loads and reductions based on land uses and BMPs; (2)
1-3
Consult with representatives from CT and NY and the Committee, and select a tool and modify, as
appropriate, to achieve the desired goal; (3) Verify nitrogen mass balance for existing land uses based
on estimates from previous studies and those estimated using this tool; and (4) Apply the tool to
guide future land use changes and screen/select BMPs in support of addressing the critical issues
identified by the Management Committee.
This management tool was developed to support nitrogen load estimation and tracking
within the in-basin area of LIS (State of Connecticut, Westchester/ Suffolk/ Nassau Counties in
New York State, and portions of New York City). A short description of the study area is provided
in the following section. The activities and accomplishments, and modeling are presented in Sections
3-6 as follows: screening and selection of the appropriate model for nitrogen load estimation, along
with the data requirements, are presented in Section 3; calibration of the AVGWLF model for
selected Connecticut watersheds that were calibrated using HSPF in the previous CTDEP study is
discussed in Section 4; application of AVGWLF to generate nitrogen loadings for other watersheds
in CT and NY in Section 5; and the development and application of the management tool for BMP
screening and selection are provided in Section 6.
Section 7 details the project conclusions and recommendations for further study and
application of the management tool. The literature compiled to support this study is cited in Section
8 and the acknowledgments are provided in Section 9. Finally, the information on presentations and
publications from this study are discussed in Section 10.
2-1
SECTION 2
2 STUDY AREA DESCRIPTION
The study area includes all drainage areas in the immediate vicinity of LIS, on the northern
and southern shores of the sound. The management committee has designated these areas as “in-
basin” sources, indicating that the nitrogen loads from these areas directly contribute to water quality
impairment (low DO levels) in the sound with little to no attenuation. As shown in Figure 2-1, the
in-basin areas include the entire State of Connecticut, portions of Bronx and Queens in New York
City, and northern shore of Nassau and Suffolk Counties and the entire Westchester County in the
State of New York.
The regional basins delineated during the CTDEP study for the State of Connecticut are
shown in Figure 2-1. For the State of New York, the delineation performed using the Hydrologic
Cataloging Units of the United States Geologic Survey are also shown in this figure.
Significant amounts of nitrogen are transported from other jurisdictions (e.g., Province of
Quebec in Canada, New Hampshire, Massachusetts, Vermont, and Rhode Island) through the upper
reaches of Connecticut and other river basins that drain to LIS. These drainage areas are termed
“out-of-basin” sources since the loads from such areas will undergo significant transformation and
attenuation prior to discharging to LIS. The out-of-basin sources are not studied as part of this
project.
Figure 2-2 shows the distribution of major land use categories within the study area. As
seen, the areas adjacent to shoreline are primarily urban and those in the upper reaches of the
drainage areas in Connecticut and in the northern shore of Long Island are dominated by non-urban
land uses.
2-2
Figure 2-1. Study Area
Watershed Delineations
2-3
Figure 2-2. Distribution of Land Uses in the Study Area
2-4
3-1
SECTION 3
3 SELECTION OF MODELING APPROACH
As first step in the project, the study team initiated discussions with staff from the LIS EPA,
CTDEP, New York State Department of Environmental Conservation (NYSDEC), and other
stakeholders including Westchester County and the New England Interstate Water Pollution
Control Commission (NEIWPCC) about the modeling approach. Selection of the approach and
modeling tool had to be clearly linked to the decision needs and objectives of the stakeholders in the
project.
The key factors in the tool selection and development included: (a) The ability to estimate
and track nitrogen loads from existing or future land uses and assess load reductions from BMPs, (b)
Consistency with earlier modeling studies conducted in the project area, (c) Simplicity and flexibility
to encourage its on-going and wide-spread use by state officials and local decision-makers such as
municipal managers, state conservation staff, and agricultural extension centers, and (d)
Transparency and effectiveness for communicating with the general public.
In addition to the above management factors, the following technical issues were considered:
(1) Simplicity of interfacing with Geographic Information System-GIS databases to provide data on
current and future land uses and subdivisions so the nitrogen load generation and reductions from
potential BMPs could easily be assessed; (2) Ability to use planning level construction and
maintenance costs that would guide the screening and selection of BMPs to achieve the targeted
nitrogen load reductions; and (3) Ability to incorporate variability in BMP performances based on
local geographic setting and weather conditions (precipitation, soil characteristics, slope, etc. at the
conservation district or municipality level), so the adequacy of BMPs to comply with the 10%
reduction in nitrogen loads from the non-point sources of pollution could be assessed.
Based on the team’s previous modeling experience and the critical land use-related issues
identified by the Committee, the team determined that none of the public-domain/commercial tools
could be used as a straight forward off-the-shelf application, but one or more tools were amenable
for enhancement with reasonable effort to address these critical issues. Several BMP modeling tools
available in the public and commercial domain were reviewed in terms of the factors relevant to this
study. The table in Appendix A shows a matrix of criteria versus model capabilities/ limitations.
This table was distributed to the EPA and state representatives for review and discussion.
Consequently, the AVGWLF model was selected for application in this project. One of the
perceived advantages of AVGWLF was the direct linkage to PRedICT, a module of AVGWLF that
would allow a user to evaluate the effectiveness and costs associated with the implementation of
various agricultural and urban BMPs (Evans et al., 2003) and to select an optimal set of BMPs to
achieve a desired level of pollutant load reduction.
3-2
The AVGWLF is a GIS-interface for the Generalized Watershed Loading Functions
(GWLF) developed by Haith et al. (1992). AVGWLF was developed by Pennsylvania State
University for the Commonwealth of Pennsylvania Department of Environmental Protection to
support easier pre and post-processing of data for the GWLF model. Based on EPA (1997), GWLF
is a mid-range watershed model that offers a user more capabilities to represent the climatic and
physiographic influences on pollutant loads than the simpler models such as Watershed Treatment
Model (WTM) developed by the Center for Watershed Protection and Pollutant Load Assessment
Model (PLOAD) built in EPA BASINS. On the other hand, the complex models such as HSPF
used in the CTDEP study and Agricultural Nonpoint Source Pollution Model (AGNPS) are
parameter-intensive and also require significant modeling experience and resources for successful
application of such models. Being in the mid-range, GWLF offers the following specific features
that are useful for this project:
a. Rainfall-runoff relationships account for losses such as evaporation and infiltration
b. Sediment erosion is estimated with the Universal Soil Loss Equation (USLE)
c. Nitrogen loadings from both point and non-point sources are quantified through GIS-based
land use patterns
d. Spatial variability in rainfall is considered
e. Water quality responses (loadings) to future land use scenarios can be estimated, and
f. Monthly and annual average pollutant loads are quantified for comparison with monitored
water quality data.
A brief description of the GWLF model along with the computational algorithms and input
file definitions is provided in the following section.
GWLF Description
This information is compiled from the AVGWLF 4.0 User Manual (Evans et al., 2003) and
the GWLF Version 2.0 User Manual (Haith et al., 1992). The model has the ability to simulate
runoff, sediment, and total nitrogen (along with other nutrients such as phosphorus) loads from a
watershed given the various land uses (e.g., agricultural, forested, low density, and commercial). The
built-in algorithms can account for septic system loads and point source discharges (municipal
wastewater treatment plants and industries). It is a continuous simulation model which uses daily
time steps for weather data and mass balance calculations. Sediment and total nitrogen loads are
estimated based on the daily water balance, but are tallied to monthly values in the output, allowing
monthly comparison of monitored and modeled nitrogen loads.
GWLF is a combined distributed/ lumped parameter watershed model. For pollutant
loading, the model is considered to be distributed since it allows multiple land use/cover scenarios,
but each area (e.g., sub-basin or major watershed) is assumed to be homogeneous in regard to
various attributes considered by the model. Pollutant loads from individual source areas are simply
3-3
aggregated to compute the total watershed loading. Depending on the locations of these areas with
respect to a watershed outlet, the in-stream transformations can attenuate the loading from these
areas before reaching the outlet point. GWLF does not explicitly account for spatial routing and the
in-stream transformations. Because attenuation is not considered, the nutrient mass computed using
this model may be over-estimated as compared to that calculated using field monitoring data,
particularly for larger watersheds.
For sub-surface (groundwater) flow and pollutant loads, the model uses a lumped parameter
approach involving a water balance. Figure 3-1 depicts the components of the GWLF model.
Hydrology: The daily weather data (e.g., precipitation, temperature) are used to generate
the surface runoff component of stream flow using the Soil Conservation Services (SCS) Curve
Number approach. The evapotranspiration is computed using daily weather data and a cover factor
dependent on land use and cover type. Daily water balances are computed for an unsaturated zone
and the saturated sub-surface zone as shown in Figure 3-1, in which the infiltration is calculated as
the difference between precipitation and snowmelt and other hydrologic components such as initial
unsaturated zone storage, maximum available zone storage, surface runoff and evapotranspiration.
Erosion: Erosion and sediment yield are computed using monthly erosion calculations
based on the Universal Soil Loss Equation (USLE) with the following set of parameters: monthly
rainfall-runoff coefficients, monthly composite of soil erodibility factor (K), topographic factor (LS),
crop management factor (C), and conservation practice (P) values for each source area. A sediment
delivery ratio based on the watershed size, and a transport capacity based on the average daily
runoff, are then applied to estimate the sediment yield for each source area.
Nutrient Loading: Surface nutrient losses are determined by applying dissolved nitrogen
(N) and phosphorus (P) concentrations to surface runoff for each agricultural source area. Point
source discharges can also contribute to dissolved losses and are specified in terms of kilograms per
month. Manured areas and septic systems can explicitly be considered. Urban nutrient inputs are all
assumed to be solid-phase – the model uses exponential accumulation and washoff function for
these loadings. Sub-surface losses are calculated using dissolved N and P concentrations for shallow
groundwater contributions to stream nutrient loads, and the sub-surface sub-model only considers a
single, lumped parameter contributing area.
Input Data Files: The model needs three input files containing weather, nutrient loading
and transport-related data. The weather data file (WEATHER.DAT) specifies daily average
temperature and total precipitation values for each simulation year. Multiple stations are specified
for large watersheds, and the model chooses applicable weather stations based on the proximity to a
watershed. The nutrient loading file (NUTRIENT.DAT) includes the loading parameters for the
various source areas specified in the model such as number of septic systems, urban source area
accumulation rates based on landuses, groundwater concentrations, and manure concentrations.
3-4
Finally, the transport file (TRANSPORT.DAT) defines the necessary parameters for each source
area being considered such as watershed size, curve number, and slope. It must be emphasized that
the in-stream processes are not explicitly included in this modeling framework.
Figure 3-1. GWLF Model Components
Precipitation Evapotranspiration
Forest, Agricultural
Urban, Septic, and
Other Land Uses
Unsaturated Zone
Shallow Saturated Zone
Deep Storage
Sediments,
Nutrients,
N, P, C, etc.
Point Sources
(N, P, C, etc.)
Runoff
Streamflow
Groundwater
(Shallow)
Dissolved Nutrients (N,
P, C, etc.) including
Nutrients from
septic systems
Output:
Water, Sediments
and Nutrients;
Impact of Land Use
Precipitation Evapotranspiration
Forest, Agricultural
Urban, Septic, and
Other Land Uses
Unsaturated Zone
Shallow Saturated Zone
Forest, Agricultural
Urban, Septic, and
Other Land Uses
Unsaturated Zone
Shallow Saturated Zone
Deep Storage
Sediments,
Nutrients,
N, P, C, etc.
Point Sources
(N, P, C, etc.)
Runoff
Streamflow
Groundwater
(Shallow)
Dissolved Nutrients (N,
P, C, etc.) including
Nutrients from
septic systems
Output:
Water, Sediments
and Nutrients;
Impact of Land Use
4-1
SECTION 4
4 WATERSHED MODEL CALIBRATION
As discussed earlier in this report, the overall project objective was to assemble a
management tool for tracking the total nitrogen loads from non-point sources contributing to Long
Island Sound. As such, a comprehensive model calibration involving adjustments of hydrology
parameters and pollutant loading functions from various land uses and physical processes on a finer
temporal and spatial scale was not envisioned. The project team designed a technical approach to
maximize data usage from previous model calibration efforts in the study area, and supplement with
any additional data necessary for AVGWLF model setup.
Based on earlier water quality studies in LIS, the Management Committee has identified total
nitrogen (TN) as the primary pollutant of concern leading to hypoxia in the Long Island Sound.
Although the other water quality parameters such as silica and other oxygen-demanding substances
have their own effects on the Sound, the calibration effort in this study focused on the freshwater
inflows from various tributaries and also the associated total nitrogen loadings.
The earlier CTDEP study in the State of Connecticut involved extensive data compilation
and HSPF model calibration for both flow and pollutant loads by AQUA TERRA and HydroQual
(2001). Similar level of extensive or state-wide watershed model calibration efforts have not been
performed in the State of New York. Karimipour (1997), for example, estimated nitrogen loads
discharged from the Nassau and Suffolk Counties into LIS using four watershed models. Similarly,
Mullaney et al. (2002) developed estimates of nitrogen yields and loads, using the regression-based
ESTIMATOR model, from watersheds draining to LIS in the period from 1988 and 1998. Other
studies such as Garabedian et al. (1998) focused on characterizing the overall water quality in the
Connecticut River Basin and tributaries using only the monitored data for various parameters
including total nitrogen. Therefore, the project team developed an approach to compute stream
flows for the test calibration watersheds identified in the CTDEP study and compare results with
USGS streamflow data and with results from the HSPF model. Similar comparison was made for
the nutrient loadings.
The databases compiled for setting up the AVGWLF model for the Connecticut and New
York watersheds are described in the following section. Subsequently, the calibration of flows and
nitrogen loadings and their comparison to field observations and previous modeling results are
provided.
4.1 MODEL DATABASES
The use of GIS is becoming prevalent and critical to watershed modeling efforts (Maidment,
2002). The important feature of AVGWLF is the integral use of GIS software to derive the
4-2
necessary spatial input data. A customized interface developed by Penn State for the ArcView GIS
package is used to parameterize input data for the GWLF model (Evans et al., 2002). In utilizing
this interface, the user is prompted to identify required GIS files and to provide other information
related to non-spatial model parameters (e.g., beginning and end of the growing season and the
months during which manure is spread on agricultural lands). This information is subsequently used
to automatically derive values for required model input parameters which are then written to the
TRANSPORT.DAT and NUTRIENT.DAT input files needed to execute the GWLF model. Also
the interface includes a weather database with twenty years of temperature and precipitation data for
seventy-eight (78) weather stations in the Commonwealth of Pennsylvania. The users can adopt this
weather database as a template to create the necessary databases for other geographic regions. This
database is used to create the WEATHER.DAT input file for a given watershed simulation.
The project team started with the GIS databases compiled by Penn State for the
Commonwealth of Pennsylvania, with the intent of replacing the Pennsylvania-specific databases
with those appropriate for the States of Connecticut and New York. Where applicable, federal
datasets were used, such as the National Resources Conservation Service State Soil Geographic
Database (NRCS/STATSGO), the United States Census database (US Census), and the EPA
BASINS Version 3 Digital Elevation Model (DEM) and Reach File 3 (RF3) streams GIS coverage.
For the State of Connecticut, several GIS databases existed including those compiled during
the AQUA TERRA and HydroQual (2001) study and the databases being compiled by the
University of Connecticut [MAGIC geospatial data resources - Connecticut State Coverages; and
Center for Land Use Education and Research (CLEAR) database]. The CT spatial dataset was
organized in terms of major river basins and regional sub-basins. These GIS databases were
manipulated to replace the appropriate databases in the AVGWLF framework for the State of
Connecticut, and the manipulations included consolidation of land use categories, creation of a
weather station network, re-projection of certain GIS coverages to Albers Equal Area Projection,
calculation of several soil properties and coefficients used in USLE, estimation of animal density,
number and types of septic systems, creation of point source discharges, and filling-in of missing or
unavailable data. To the extent feasible, the point source data from CTDEP study was used to
derive both flows and total nitrogen concentrations. Details about the individual datasets and their
sources are described in the data matrix presented in Appendix B.
Similar effort was pursued to compile the datasets for the State of New York. Based on the
guidance from EPA, Nassau and Suffolk counties were contacted to assemble sub-basin level GIS
coverages. This information was not made available for this study; therefore, the team assembled
datasets from the Hydrologic Cataloguing Unit (HUC) compiled on a national level. The GIS
database inventory in Westchester County was reviewed to compile the necessary datasets. This
process, again, is detailed in the data matrix in Appendix B.
4-3
4.2 CALIBRATION OF TEST WATERSHEDS
As described earlier in this section, the calibration process in this study was limited to
calibrating the AVGWLF model for the three test watersheds used in the CTDEP study, namely,
Norwalk, Quinnipiac, and Salmon. These test watersheds represent a range of land uses, including
urban, forest, and agriculture. The approach used in the selection and subsequent calibration of the
test watersheds minimized the chances of bias being associated with the land use specific parameters
that were extrapolated to non-calibration watersheds.
The test watersheds ranged in size from 61.6 square miles (39,416 acres) to 163 square miles
(104,464 acres) for the Norwalk and Quinnipiac watersheds, respectively. The watersheds are
spatially distributed across the State of Connecticut, and located within major river systems, to
reasonably represent the variation in meteorologic, hydrologic, topographic, and soil conditions
across the state. In addition, the test watersheds represent the spectrum from a relatively
undisturbed, heavily forested watershed (Salmon) to a highly disturbed, urbanized watershed
(Quinnipiac). The spatial distribution of the test watersheds and their respective land use
distributions minimized the chances of producing model parameters biased to the characteristics of
one specific watershed, which could be uniquely different from the remaining CT watersheds.
The period of calibration (1986-1995) represented the most recent time period for which the
required model input/execution data and calibration data were available and represented a wide
range of hydrologic conditions. In the CTDEP study, this 10-year dataset was used for model
calibration and verification. For simplicity sake, the entire 10-year dataset was used for calibration of
the AVGWLF model.
Model performance measures used in the CTDEP study for HPSF evaluation are not
directly applicable for AVGWLF model assessment, due to its simpler representation of physical
processes and not accounting for the in-stream transformations. Nevertheless, the same evaluation
criteria were used here to assess the adequacy of AVGWLF model calibration. These measures are
described below.
Model performance was evaluated through qualitative and quantitative measures, involving
both graphical comparisons and statistical tests. Comparison of simulated and observed state
variables were performed for monthly, annual and seasonal values, in addition to the cumulative
flow assessments over the 10-year period. The general calibration tolerances or targets developed in
the CTDEP study are summarized in Table 4-1.
It must be recognized that the tolerance ranges are applied to mean values and that
individual events or observations may show larger differences, and still be acceptable for a TMDL
analysis. In addition, the level of agreement to be expected depends on many site and application-
specific conditions, including the data quality, purpose of the study, available resources, and available
alternative assessment procedures that could meet the study objectives. Similar to the CTDEP
4-4
study, due to resource and data limitations, the focus of calibration was primarily at the monthly and
annual level of comparison of both hydrology and water quality. This was further supported by the
study objective of tracking total nitrogen loads and conducting a planning-level analysis of BMPs to
achieve the targeted 10% reduction in loads from the urban and non-urban non-point pollution
sources.
Table 4-1. General Targets/Tolerances for Watershed Model Applications
Percent Difference Between Modeled and Observed Values
Parameters
VERY GOOD GOOD FAIR
Hydrology/ Flow < 10 10-15 15-25
Sediment < 20 20-30 30-45
Water Quality/Nutrients < 15 15-25 25-35
4.2.1 Hydrology Calibration
As discussed previously, the hydrologic calibration was performed for a 10-year period from
April 1985 through March 1995, and the available flow data included continuous flow records at
three USGS gage sites in the three test watersheds. These sites included Norwalk River at South
Wilton, Quinnipiac River at Wallingford, and Salmon River near East Hampton.
The calibration process was initiated by comparing the modeled versus observed flow for
the three test watersheds using AVGWLF default parameters for the Pennsylvania watersheds. The
specific comparisons of simulated and observed flow values included: (a) annual and monthly runoff
volumes (inches); (b) time-series comparison of daily streamflow volumes (cubic feet per second,
cfs); and (c) flow frequency (flow duration) curves (cfs).
With the appropriate weather and physiographic datasets for the three watersheds, and with
default AVGWLF parameters, there were differences between modeled and observed flows in terms
of the daily peaks and monthly volumes, as well as the summer flow volumes (groundwater). In
general, AVGWLF has been documented (e.g., Triad, HydroQual and TN Associates, 2003) to be
less robust than comprehensive models such as HSPF in describing groundwater flow. Calibration
of the AVGWLF model was performed by making parameter changes, running the model,
producing the aforementioned comparisons of simulated and observed values, and interpreting the
results. Specific parameters adjusted during the calibration process were the curve numbers (CN)
for selected land uses and the groundwater recession coefficient. It is important to note that the
parameter changes were made in a global manner so that there was good agreement between
4-5
modeled and observed flows in all the three test watersheds. This process is intended to enhance
confidence in terms of the applicability of these parameters to remainder of the watersheds in CT
and NY. The TRANSPORT parameters applied for hydrologic calibration of the Salmon watershed
are shown in Tables 4-2(a) and 4-2(b).
For the Norwalk watershed, a major component of this calibration process involved a
detailed review of site-specific watershed characteristics. This was necessary because the AVGWLF
model consistently over-predicted flows for the entire 10-year calibration period. Based on
information provided by the staff from CTDEP and Norwalk 2
nd
District Water Department
(Personal Communication with Tom Villa in February 2006), the Middlebrook Diversion (including
the Pope’s Pond storage of about 318 million gallons) was identified as having a major effect on
downstream flows. For the AVGWLF model calibration, the diversion was described by data
provided by Mr. Villa for a 5-year period from 1997-2001. This improved the hydrologic calibration
for Norwalk watershed significantly as described below.
Table 4-3 shows the comparison between simulated and observed mean annual and seasonal
flows for the three test watersheds. The criteria set forth, based on Donigian (2000), for the various
hydrologic calibration metrics are also shown in this table. For each test watershed, the comparison
between simulated and observed values is shown, along with the percentage error with respect to the
observed values. Qualitative performance of the AVGWLF model is provided based on the model
performance criteria, and a comparison with the qualitative performance of the HSPF model from
the previous CTDEP study is provided for reference. For almost all hydrologic calibration metrics,
the AVGWLF model performance is very comparable to that of the HSPF model, and shows a
good to very good agreement based on annual and seasonal comparisons. As indicated earlier, the
AVGWLF is a simpler model not to be assessed by the same performance measures appropriate for
the HSPF model. Nevertheless, the AVGWLF model performance exceeded the initial expectations
set forth by the study team for the hydrologic calibration process.
Figures 4-1(a) and 4-1(b) show the time-series comparison of daily flow volumes and
monthly flow duration curves for the Salmon watershed for the 10-year model calibration period.
Similarly, the Figures 4-2(a) and 4-2(b) show the comparisons for Quinnipiac watershed, and Figures
4-3(a) and 4-3(b) show the Norwalk watershed’s model comparison with observed flows. All the
three watersheds demonstrate consistent match between the observed and modeled values, except
for small deviations in the latter part of calibration period for the Salmon watershed. This is likely
exaggerated by the lack of data on diversions and possible impacts of reservoir operating records.
Based on the hydrologic calibrations it was found that a spatiotemporally constant recession
coefficient of 0.0625/day was adequate to produce the results in Table 4.3, and was later used as a
calibrated parameter for rest of the in-basin study domain.
4-6
Table 4-2(a). TRANSPORT Parameters for the Salmon Watershed
Land Use Type Curve
Number*
Soil
Erodibility
(K)
Length-Slope
Factor (LS)
Cropping
Management Factor
(C)
Erosion Control
Factor (P)
Rural Land Use
Hay/Pasture 63 0.234 1.90 0.030 0.45
Cropland 82 0.232 4.99 0.420 0.45
Coniferous Forest 60 0.232 2.57 0.002 0.45
Deciduous Forest 60 0.236 3.02 0.002 0.45
Unpaved Roads 82 0.235 1.19 0.800 1.00
Transition 82 0.233 2.82 0.800 0.80
Urban Land Use
Low Intensity 80 0.233 1.62 0.080 0.20
High Intensity 90 0.234 2.28 0.080 0.20
Additional Watershed Parameters:
Antecedent Moisture Conditions*: Assumed 0 for all 5 days prior to GWLF model initiation.
Initial Snow Depth*: 0 centimeters (cm).
Initial Unsaturated Storage*: 10 cm.
Initial Saturated Storage*: Assumed 0 cm.
Recession Coefficient*: 0.0625/day
Deep Seepage Coefficient*: 0/day
Sediment Delivery Ratio: 0.076
Sediment A factor: 1.291E-04.
Unsaturated Available Water Capacity: 18.20 cm.
4-7
Table 4-2(b). Other TRANSPORT Parameters for the Salmon Watershed
Month Evapo-transpiration
Coefficient Daylight Hours* Growing Season* Erosivity
Coefficient
April 0.237 13 NO 0.22
May 0.688 14 YES 0.22
June 0.949 15 YES 0.22
July 1.101 15 YES 0.22
August 1.189 14 YES 0.22
September 1.240 12 YES 0.11
October 0.822 11 NO 0.11
November 0.579 10 NO 0.11
December 0.439 9 NO 0.11
January 0.205 9 NO 0.11
February 0.222 10 NO 0.11
March 0.231 12 NO 0.11
NOTE: *These global parameters are used for all watersheds, and the remaining parameters are computed based on the
climatologic and physiographic factors pertinent to each watershed.
4-8
Table 4-3. Comparison of Hydrology Statistics for the Three Test Watersheds
Total runoff, in inches 10% 258.2 269.6 4% Yes Yes
Total of highest 10% flows, in inches
15%
92.8 85.7 -8% Yes Yes/No*
Total of lowest 50% flows, in inches
10%
41.4 28.6 -31% No No
Evapotranspiration, in inches 224.0
Total storm surface runoff volume, in inches/yr
18%
2.0 2.1 3% Yes Yes/NA
Summer flow volume, in inches 2.9 2.8 -4%
Winter flow volume, in inches 8.2 9.4 15%
Summer+Winter flow volume, in inches
10%
11.0
12.1
10%
Yes
No
Total runoff, in inches
10%
266.7 266.8 0% Yes Yes
Total of highest 10% flows, in inches
15%
91.1 99.0 9% Yes No
Total of lowest 50% flows, in inches
10%
59.2 26.9 -55% No No
Evapotranspiration, in inches 231.6
Total storm surface runoff volume, in inches/yr
18%
4.9 4.7 -4% Yes Yes/NA
Summer flow volume, in inches 4.8 3.9 -18%
Winter flow volume, in inches 7.8 9.6 24%
Summer+Winter flow volume, in inches
10%
12.6
13.5
8%
Yes
Yes/No
Total runoff, in inches
10%
248.0 249.6 1% Yes Yes
Total of highest 10% flows, in inches
15%
101.0 81.9 -19% No Yes/No
Total of lowest 50% flows, in inches
10%
36.7 27.5 -25% No No
Evapotranspiration, in inches 233.9
Total storm surface runoff volume, in inches/yr
18%
3.6 3.4 -5% Yes Yes/NA
Summer flow volume, in inches 2.7 3.6 33%
Winter flow volume, in inches 7.2 10.1 41%
Summer+Winter flow volume, in inches
10%
9.9
13.8
39%
No
No
* Yes/No indicates that the criterion was met in the Calibration Period, and not in the Validation Period of the CTDEP study.
Did HSPF
meet?
Observed AVGWLF % Error Did AVGWLF
meet?
Did HSPF
meet?
Observed AVGWLF % Error Did AVGWLF
meet?
Salmon near East Hampton Criteria
Observed
Quinnipiac at Wallingford Criteria
Norwalk at South Wilton Criteria
AVGWLF % Error Did AVGWLF
meet?
Did HSPF
meet?
4-9
Figure 4-1(a). Daily Time-Series Comparison for Salmon Watershed
Salmon River Time-Series at East Hampton
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
Apr-85 Apr-86 Apr-87 Apr-88 Apr-89 Apr-90 Apr-91 Apr-92 Apr-93 Apr-94 Apr-95
Date (days)
Flow (cfs)
AVGWLF Flow
Observed Flow
4-10
Figure 4-1(b). Flow Duration Curve for Salmon Watershed (Monthly Time-series)
Salmon River Cumulative Flow Analysis
0.E+00
1.E+05
2.E+05
3.E+05
4.E+05
5.E+05
6.E+05
7.E+05
8.E+05
11/14/1984 3/29/1986 8/11/1987 12/23/1988 5/7/1990 9/19/1991 1/31/1993 6/15/1994 10/28/1995
Date
Cumulative Flow (cfs x day)
AVGWLF Flow
Observed Flow
4-11
Figure 4-2(a). Daily Time-Series Comparison for Quinnipiac Watershed
Quinnipiac River Time-Series at Wallingford
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
Apr-85 Apr-86 Apr-87 Apr-88 Apr-89 Apr-90 Apr-91 Apr-92 Apr-93 Apr-94 Apr-95
Date (days)
Flow (cfs)
AVGWLF Flow
Observed Flow
4-12
Figure 4-2(b). Flow Duration Curve for Quinnipiac Watershed (Monthly Time-series)
Quinnipiac River Cumulative Flow Analysis
0.E+00
1.E+05
2.E+05
3.E+05
4.E+05
5.E+05
6.E+05
7.E+05
8.E+05
9.E+05
11/14/1984 3/29/1986 8/11/1987 12/23/1988 5/7/1990 9/19/1991 1/31/1993 6/15/1994 10/28/1995
Date
Cumulative Flow (cfs x day)
AVGWLF Flow
Observed Flow
4-13
Figure 4-3(a). Daily Time-Series Comparison for Norwalk Watershed
Norwalk River Time-Series at South Wilton
0
200
400
600
800
1,000
1,200
1,400
1,600
Apr-85 Apr-86 Apr-87 Apr-88 Apr-89 Apr-90 Apr-91 Apr-92 Apr-93 Apr-94 Apr-95
Date (days)
Flow (cfs)
AVGWLF Flow
Observed Flow
4-14
Figure 4-3(b). Flow Duration Curve for Norwalk Watershed (Monthly Time-series)
Norwalk River Cumulative Flow Analysis
0.E+00
5.E+04
1.E+05
2.E+05
2.E+05
3.E+05
11/14/1984 3/29/1986 8/11/1987 12/23/1988 5/7/1990 9/19/1991 1/31/1993 6/15/1994 10/28/1995
Date
Cumulative Flow (cfs x day)
AVGWLF Corrected Flow
Observed Flow
4-15
4.2.2 Water Quality Calibration
The goal of the water quality calibration was to achieve acceptable comparisons of
AVGWLF model results and field observations for the three test watersheds. In this study, the
default values as recommended by the GWLF User’s Manual (Haith et al., 1992) were largely used
for concentrations and loading rates for TN. Qualitative comparisons to the previous load estimates
were also performed to further confirm the general applicability of GWLF model parameters to the
LIS study area.
The study team initially envisioned a direct comparison of nitrogen loadings from the
previous CTDEP study and AVGWLF results. The HSPF model utilized surface loading rates for
various land uses and also characterized in-stream transformations. Consequently, the in-stream
nitrogen and dissolved oxygen concentration comparisons were made in the CTDEP study. The
AVGWLF model, however, does not simulate in-stream transformations and also produces monthly
pollutant loads as output. Therefore, the study team compared AVGWLF results with the monthly
total nitrogen loads derived from the observed data at the three test watersheds.
Observed TN mass values were developed based on the daily flow and TN concentrations
observed at the monitoring stations of three test watersheds in CT by the State and the U.S.
Geological Survey. Considering the limited monitoring data, monthly average TN concentrations
were obtained from each month’s dataset and multiplied by the daily flow to obtain the daily TN
mass. In most of the months, two or more TN concentrations were available and an arithmetic
average of those concentrations was derived as the “representative” TN value for that month. For
the months with one or no observed data, it was difficult to develop or assign representative values.
Therefore, the modeled TN mass in these months were excluded from comparison with the
observed data. The representative TN value for a specific month was multiplied by the daily flow
volume observed at a monitoring station, and the daily TN mass was tallied to derive the total TN
mass within that month. The resulting data were then compared with the AVGWLF model results.
For portions of the watersheds draining to these monitoring stations, the model was run to
generate flow and nutrient loads from individual land uses. The CTDEP study dataset on
wastewater treatment plants (in terms of their effluent flows and associated TN concentrations) was
used as GIS coverage in the model to generate the point source TN loads. Finally, the groundwater
TN concentrations for each land use (Appendix B) and septic systems were used to generate the TN
mass from other contributing sources.
It should be noted that the AVGWLF calculation for loadings from agricultural areas with
manure application was found to be incorrect. This issue was brought to the attention of AVGWLF
developers at Penn State and the study team was advised that it would be fixed in a subsequent
version of the model. Keeping this in mind, the study team excluded application of manure loadings
using this seasonal-application option. Instead, the nitrogen concentrations were applied on an
4-16
additional landuse created in AVGWLF (called “Agricultural Manured Areas”) on a year-round
basis. Another issue experienced with AVGWLF was that the groundwater TN concentrations had
to be specified in integer format in the applicable GIS integer raster grid. This issue initially
restricted the study team to define fractional TN concentrations (e.g., 0.42 mgN/L – milligrams of
Total Nitrogen per liter) for groundwater. In order to specify values with greater floating point
accuracy, the units for total groundwater TN concentrations were changed from mgN/L to ugN/L
(micrograms of Total Nitrogen per liter) in the GIS integer raster grid. The concentrations were
then converted to mgN/L after the GWLF input data compilation by the ArcView interface and
prior to the GWLF model execution.
Comparisons of the monthly time-series of TN mass, scatterplot of monthly TN mass, and
cumulative TN mass over the 10-year calibration period between the AVGWLF modeled values and
observed values for the Salmon watershed are shown in Figures 4-4(a), 4-4(b), and 4-4(c),
respectively. Similar comparisons for the Quinnipiac watershed are shown in Figures 4-5(a) through
4-5(c), and for the Norwalk watershed in Figures 4-6(a) through 4-6(c). Again, it should be
emphasized that the months in which representative TN values could not be derived were ignored in
all of these comparison charts.
As can be seen in the cumulative mass comparison charts, the AVGWLF results matched
very well with the observed data from 1985 until about 1990 for both Salmon and Norwalk
watersheds. From then on, the AVGWLF model over-estimated the monthly TN mass values.
Similarly, the AVGWLF began to over-predict monthly TN mass in the Quinnipiac watershed from
about 1992, although to a lesser degree than the other two test watersheds in the same period from
1992 through 1995. The possible explanations for these differences can include, but are not limited
to, the following:
•
Lack of data on some diversions (for hydrology as well as total nitrogen load),
•
Coarser availability of actual measurements over time for the test watersheds to derive
representative TN concentrations accurately,
•
Exclusion of existing urban BMPs, which might have been installed when the Phase 1
stormwater controls were required by the EPA in early 1990s, and
•
Potential changes in the treatment processes at the publicly owned treatment plants that
might have affected the effluent TN concentrations.
In addition to the comparisons with observed data, the study team performed a qualitative
comparison of AVGWLF generated TN loadings with the annual TN loads determined from the
regression-based ESTIMATOR program (Mullaney et al., 2002). The three test watersheds are
identified by the USGS gauging station numbers in this document: Salmon River near East
Hampton (01193500), Quinnipiac River at Wallingford (01196500), and Norwalk River at
Winnipauk (01209710). Table 4-4 shows the comparison of annual nitrogen loads from Mullaney et
al. (2002) and the AVGWLF model. Although the AVGWLF loads are generally higher than those
4-17
reported in Mullaney et al. (2002), the annual TN loads are in a comparable range and provide
further confirmation of the AVGWLF generated loads.
Table 4-4: Qualitative Comparison of Annual TN Loadings
Test Watershed
(Area in mi
2
)
Annual Load
from 2002 study
(lb/mi
2
)
Annual TN
Load from 2002
Study (lb)
Cumulative TN Load
from AVGWLF for 10-
years (metric tons)
Annual TN
Load from
AVGWLF (lb)
Percent
Difference
Salmon (100) 2,000 2,00,000 47,369 3,13,056 56%
Quinnipiac (115)
10,000 1,150,000 204,900 1,355,181 18%
Norwalk (33) 3,000 99,000 18,414 121,695 23%
The concentrations and other nitrogen loading-related parameters used in the calibration
process for Salmon watershed are shown in Table 4-5. As indicated earlier, the primary source for
these values was the GWLF User’s Manual, or the applicable compiled GIS databases for the
specific watershed being modeled. Considering the use of default GWLF parameters and compiled
GIS databases, the AVGWLF model was able to reproduce the available data on flows and pollutant
loads quite remarkably. With respect to flow calibration, the AVGWLF performance was
comparable to that of the HSPF model used in CTDEP study for the three test watersheds, in spite
of its simpler formulation compared with the physical processes built within HSPF. Even the
nitrogen load calibration reproduced the observed data very well for the first five years of the 10-
year calibration period.
The study team recognized the over-estimation of TN loads for more recent years of the
calibration period. It would be ideal to review the watershed-specific factors such as BMP
implementation and modify the model parameters accordingly to see if a better fit is obtained
between observed and modeled values. With the overall goal of this project being the development
of a management tool that can be adopted by local decision-makers to estimate and track nitrogen
loads, this additional effort was not undertaken in this project. Also, the study team perceived the
over-estimation or conservative estimation of TN loads to provide certain advantages from an initial
planning perspective. Consequently, the parameters shown in Table 4-5 were applied for rest of the
watersheds in CT and NY, as described in the following section.
4-18
Table 4-5. NUTRIENT (Nitrogen) Parameters for the Salmon Watershed
(1)
Rural Land Use Dissolved N, mgN/L
Hay/Pasture 2.9
Cropland 2.9
Coniferous Forest 0.19
Deciduous Forest 0.19
Unpaved Roads 2.9
Transition 2.9
From agricultural manured areas 2.9
Urban Land Use Urban Washoff: kgN/ha/day
Low Intensity 0.012
High Intensity 0.101
Other Loading Parameters
Per Capita Septic Tank Effluent 12g/day
Growing Season Nitrogen Uptake 1.6g/day
Sediment-bound Nitrogen 3000mg/kg
Dissolved Ground Water Nitrogen 0.472903mg/L
(2)
NOTE:
(1) All nitrogen parameters are taken from GWLF default values (Haith et al., 1992) except for dissolved ground water.
(2) Dissolved ground water nitrogen concentrations are specified based on landuses. See further discussions in Section 5.
4-19
Figure 4-4(a). Monthly TN Mass Comparison for Salmon Watershed
Salmon River - Monthly Total Nitrogen Loads at East Hampton
0
500
1,000
1,500
2,000
2,500
Dec-84
Jun-85
Dec-85
Jun-86
Dec-86
Jun-87
Dec-87
Jun-88
Dec-88
Jun-89
Dec-89
Jun-90
Dec-90
Jun-91
Dec-91
Jun-92
Dec-92
Jun-93
Dec-93
Jun-94
Dec-94
Date
TN LOADS (Kg/day)
AVGWLF <C>x<Q> DATA
NOTE: The AVGWLF values are shown as bars, and the observed values in bold circles.
4-20
Figure 4-4(b). Scatterplot of Monthly TN Mass for Salmon Watershed
Salmon River near East Hampton
0
500
1000
1500
2000
2500
0 500 1000 1500 2000 2500
AVGWLF Monthly TN Load, kg/d
Observed Monthly TN Load, kg/d
<C>x<Q> DATA
4-21
Figure 4-4(c). TN Load Duration Curve for Salmon Watershed
Salmon River near East Hampton - Cumulative TN Analysis
0
100
200
300
400
500
600
700
800
900
Jan-85 Jan-86 Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92 Jan-93 Jan-94 Jan-95
Cumulative Total Nitrogen Load, Metric Tons
AVGWLF <C>x<Q>
4-22
Figure 4-5(a). Monthly TN Mass Comparison for Quinnipiac Watershed
Quinnipiac River - Monthly Total Nitrogen Loads at Wallingford
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
Dec-84
Jun-85
Dec-85
Jun-86
Dec-86
Jun-87
Dec-87
Jun-88
Dec-88
Jun-89
Dec-89
Jun-90
Dec-90
Jun-91
Dec-91
Jun-92
Dec-92
Jun-93
Dec-93
Jun-94
Dec-94
Date
TN LOADS (Kg/day)
AVGWLF <C>x<Q> DATA
4-23
Figure 4-5(b). Scatterplot of Monthly TN Mass for Quinnipiac Watershed
Quinnipiac River at Wallingford
0
1000
2000
3000
4000
5000
6000
0 1000 2000 3000 4000 5000 6000
AVGWLF Monthly TN Load, kg/d
Observed Monthly TN Load, kg/d
<C>x<Q> DATA
4-24
Figure 4-5(c). TN Load Duration Curve for Quinnipiac Watershed
Quinnipiac River at Wallingford - Cumulative TN Analysis
0
1000
2000
3000
4000
5000
6000
Jan-85 Jan-86 Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92 Jan-93 Jan-94 Jan-95
Cumulative Total Nitrogen Load, Metric Tons
AVGWLF <C>x<Q>
4-25
Figure 4-6(a). Monthly TN Mass Comparison for Norwalk Watershed
Norwalk River - Monthly Total Nitrogen Loads at Winnipauk
0
100
200
300
400
500
600
700
800
Dec-84
Jun-85
Dec-85
Jun-86
Dec-86
Jun-87
Dec-87
Jun-88
Dec-88
Jun-89
Dec-89
Jun-90
Dec-90
Jun-91
Dec-91
Jun-92
Dec-92
Jun-93
Dec-93
Jun-94
Dec-94
Date
TN LOADS (Kg/day)
AVGWLF <C>x<Q> DATA
4-26
Figure 4-6(b). Scatterplot of Monthly TN Mass for Norwalk Watershed
Norwalk River at Winnipauk
0
100
200
300
400
500
600
700
800
900
1000
0 100 200 300 400 500 600 700 800 900 1000
AVGWLF Monthly TN Load, kg/d
Observed Monthly TN Load, kg/d
<C>x<Q> DATA
4-27
Figure 4-6(c). TN Load Duration Curve for Norwalk Watershed
Norwalk River at Winnipauk - Cumulative TN Analysis
0
100
200
300
400
500
Jan-85 Jan-86 Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92 Jan-93 Jan-94 Jan-95
Cumulative Total Nitrogen Load, Metric Tons
AVGWLF <C>x<Q>
5-28
SECTION 5
5 MODEL APPLICATION TO CT/NY WATERSHEDS
The application of AVGWLF to all watersheds in the States of Connecticut and New York
requires setting up of the appropriate input files (WEATHER.DAT, TRANSPORT.DAT, and
NUTRIENT.DAT). In order to support this work, the GIS coverages for remaining watersheds
were used with the databases discussed in Appendix B to develop watershed-specific information
such as drainage area, distribution of land uses, and USLE parameters. The simulation period was
set the same as the calibration period from April 1985 through March 1995, for calculation of flows
and TN loads using the GWLF model.
For characterizing the spatial variability in rainfall, the AVGWLF model requires a network
of weather stations both within and outside of the watershed boundaries. Daily precipitation and
temperature data for CT watersheds were compiled from the CTDEP study. For other watersheds
with boundaries extending into New York, Rhode Island and Massachusetts, similar data was
collected for an additional 21 weather stations using databases available through EPA BASINS and
NOAA’s National Climatic Data Center Cooperative Summary Reference compact disks. Only two
of the 21 stations had a complete data set over the 10 year simulation period (April 1985-March
1995) including all daily maximum temperature, minimum temperature, and precipitation data. For
those stations with missing information, one or two nearby stations were chosen as surrogate
stations to fill in the data gaps. Table 5-1 summarizes the secondary and tertiary stations used to
support the primary weather station with missing data.
Table 5-1. Weather Data Compilation for Non-Connecticut Watersheds
STATION ID SECONDARY STATION TERTIARY STATION
Bridgehampton 0889 - -
Dobbs Ferry, Ardsley 2129 - -
Gardnerville 3144 Glenham Dobbs
Glenham 3259 Dobbs -
Greenport Power House 3464 Bridgehampton -
Hudson Correctional Facility 4025 Albany Airport (NY0042) -
Millbrook 5334 Bulls Bridge Dam (CT0961) Poughkeepsie
Pleasantville (precipitation only) 6674 Dobbs -
Poughkeepsie Dutchess Airport 6820 Glenham Bulls Bridge Dam (CT0961)
Riverhead Research Farm 7134 Bridgehampton -
Patchogue 2 N 6441 Bridgehampton -
Berlin 5 S (prcp only) 0641 Albany Airport (0042) -
Buffumville Lake 0998 E. Brimfield Lake Worchester Airport (9923)
E. Brimfield Lake 2107 Buffumville Lake Worchester Airport (9923)
Hardwick (precipitation only) 3401 Barre Falls Dam (0408) Worchester Airport (9923)
E. Brimfield Lake
Northbridge 2 5524 E. Brimfield Lake Worchester Airport (9923)
Holyoke (precipitation only) 3702 E. Brimfield Lake Southbridge 3 SW (7627)
5-29
Flows and TN loads from sewage treatment plants outside of the State of Connecticut were
not available from the CTDEP study. The project team reviewed the recent flow and TN
concentration data for those treatment plants from the EPA Water Discharge Permits online
database. This process is commonly used for inclusion of point source loads in TMDL or
watershed-scale studies. The point source nitrogen loads included in the GWLF model for non-
Connecticut watersheds are approximate, averaged on a temporal basis for each watershed
simulation. This representation should be adequate to provide information on the relative magnitude
of such point source loads within a specific watershed, and their importance in terms of their
contribution to the overall TN loads within that watershed. Manual adjustment (or external
calculation) of point source loads can be performed if temporal detail is of the essence.
The groundwater dissolved nitrogen grid was formulated based on the landuse grid. The
landuse grid was reclassified from the original 12 categories to 4, and each of the 4 categories was
assigned a groundwater dissolved nitrogen concentration (Table 5-2). The CT-based loading rates
were assigned to watershed areas within RI, MA, and NY (excluding Long Island). Site-specific
loading rates were used for watersheds in Long Island based on Scorca and Monti, Jr. (2001). For
each watershed, a weighted average groundwater nitrogen concentration was developed based on
the distribution of each of these four landuses within that watershed.
Table 5-2. Groundwater Dissolved Nitrogen Concentrations
Consolidated Landuse Watersheds in CT, NY, RI, MA, excluding
Long Island (mg/L)
Long Island (mg/L)
Water 0.13 0.00
Forests 1.20 1.00
Urban 4.75 3.00
Agricultural 0.13 9.90
The coverages and grids containing data related to paved and unpaved roads, septic systems,
and land use were expanded to include the non-CT portions of the watersheds using the same
techniques and data categories that were applied to the CT watersheds.
The global calibration parameters such as groundwater recession coefficient, CN for
individual land uses, and TN load/concentrations developed from the test watersheds’ calibration
process were applied to all the CT and NY watersheds. The AVGWLF interface was first used to
create the GWLF input files (weather, transport, and nutrients) for each watershed. The GWLF
model was then run to calculate the flows and TN loads.
5-30
The GWLF-calculated nitrogen loads are tabulated in Appendix C, for all watersheds in the
States of Connecticut and New York within the in-basin drainage area to Long Island Sound. These
loads, tabulated by source area or characteristic, were summarized and used as input in the Excel-
based BMP management tool described in Section 6.
Figures 5-1 and 5-2 show the TN loads from watersheds in Connecticut and New York,
respectively. From a management perspective, it will be important to review the relative
contributions of urban and non-urban non-point sources that can provide perspectives on possible
trading between such sources in the future as possible management/reduction strategy. Figures 5-3
and 5-4 show the relative urban and non-urban TN loads from Connecticut and New York,
respectively. The costs and specific performances of BMPs available for the urban and non-urban
non-point source control can guide such a decision-making process. The management tool
developed to support this decision-making process at the local watershed-level is described in the
following section.
5-31
Figure 5-1. TN Loads for Watersheds in Connecticut
0
500000
1000000
1500000
2000000
2500000
3000000
Aspetuck
Blackberry
Candlewood
Croton
Eightmile
Farmington
Fivemile
French
Hockanum
Hollenbeck
Housatonic MS
Mattabesset
Moosup
Natchaug
Naugatuck
Norwalk
NY Main Stem
Pachaug
Park
Pawcatuck MS
Pomperaug
Quinebaug
Quinnipiac
Salmon
Saugatuck
SC Shoreline
Scantic
SCE Complex
SCW Complex
SE Shoreline
SEE Complex
SEW Complex
Shepaug
Shetucket
Still
Stony Brook
SW Eastern
SW Shoreline
SWW Complex
Tenmile
Thames MS
Willimantic
Wood
Yantic
TN Load for 10-year Period (lbs)
5-32
Figure 5-2. TN Loads for Watersheds in New York
5-33
Figure 5-3. Component TN Loads from Various Nonpoint Sources in Connecticut
CT
1.3%
2.0%
3.8%
4.4%
7.0%
12.4%
53.6%
15.4%
Groundwater
Septic Systems
High Density
Other
Hay/Pasture
Low Density
Row Crops
Streambank Erosion
5-34
Figure 5-4. Component TN Loads from Various Nonpoint Sources in New York
NY
1.3%
1.3%
0.9%
0.5%
63.2%
20.0%
6.5%
6.4%
Groundwater
Septic Systems
High Density
Low Density
Hay/Pasture
Row Crops
Other
Streambank Erosion
6-1
SECTION 6
6 MANAGEMENT TOOL DEVELOPMENT
As stated previously, one of the primary reasons for selection of AVGWLF was the direct
linkage of the program to the Pollution Reduction Impact Comparison Tool (PRedICT) (Evans, et
al., 2003). This module of AVGWLF allows the user to evaluate the effectiveness and costs
associated with the implementation of various agricultural and urban BMPs. PRedICT is based on a
rather simple, cost-accounting approach to estimate load reductions and their associated costs. For
example, the user can specify various implementation scenarios based on the number of acres of
agricultural BMPs, the number of septic systems to be converted to centralized wastewater
treatment, types of sewage treatment plant upgrades, percentage of urban areas to be treated by
detention basins and wetlands, etc. This information is used along with built-in reduction
coefficients and unit costs to determine the resultant nutrient and sediment load reductions and
projected scenario costs.
During the course of the project, however, certain deficiencies were noted in application of
PRedICT as a simple management tool to assess nitrogen load reductions to Long Island Sound.
These included:
1. Application of PRedICT with direct linkage to the AVGWLF watershed modeling
system requires that all users of the management tool be able to run the full GIS-based
AVGWLF program;
2. Only a compiled version of the PRedICT source code is publicly available. This limits
any consideration for code modification (e.g., to addition of BMPs types to the model);
3. The equations for “Groundwater Load Adjustments” that are described in the
PRedICT, Version 1.0 Users Guide (Evans et al., 2003) contain several inconsistencies
related to the appropriate specification of land use and total watershed area; and
4. The optimization routine in PRedICT, Version 1.0 is not functional.
A new management tool was therefore developed by the study team to track nitrogen load
reductions. The management tool, which is essentially a “stand-alone” version of PRedICT, is
presented in a Microsoft EXCEL workbook. The EXCEL workbook includes: (1) a tabulation of
AVGWLF model results for watersheds in Connecticut and New York that impact long Island
Sound (see Section 5 for details); (2) EXCEL macros programmed in Visual Basics for Applications
(VBA) to compute total nitrogen load reductions and associated costs; and (3) a user-friendly
interface to allow easy application of the management tool within EXCEL.
6-2
Formulations for total nitrogen load reductions and costs are largely taken from the
PRedICT, Version 1.0 Users Guide (Evans et al., 2003). Annotated versions of the VBA source
code for total nitrogen load reductions and costs are given in Appendix D.
6.1 AGRICULTURAL BMPS
Total nitrogen load reductions from row crop and hay pasture acreage and streambank
erosion are based on implementation of several BMPs as outlined in Table 6-1.
Table 6-1. Agricultural BMPs and Estimated TN Reduction Efficiencies
1
BMP System BMP Number Estimated TN Reduction
Efficiency (Percent)
Permanent Vegetated Cover (through crop residue
management, cover crops) BMP 1 50
Strip-Cropping and Contour Farming BMP 2 23
Cropland Protection (through crop rotation, cover crops) BMP 3 25
Conservation Tillage (through crop rotations, crop residue
management, contour farming / strip-cropping) BMP 4 27
Terraces and Diversions BMP 5 44
Nutrient Management BMP 6 70
Grazing Land Management BMP 7 43
Vegetated Buffer Strips
2
54
Streambank Fencing
2
56
1
BMP categories and associated TN reduction efficiencies are taken from Evans et al. (2003). Reduction efficiency values represent
estimated reductions in surface runoff-associated loads only, except the value for streambank fencing, which represents reduction to
TN load generated via streambank erosion.
2
TN reduction efficiencies for vegetated buffer strips and streambank fencing are given on a “per mile” rather than a “per acre” basis.
For row crops, nutrient management (BMP 6) is applied uniformly across row crop acreage
in the watershed. Further reductions in remaining total nitrogen loads are then considered through
implementation of BMP 1-5. (Note that BMP 1-5 can only be applied individually on a given acre
of row crop and their total implementation cannot exceed the total acreage of row crop.) Finally,
TN load reduction due to vegetated buffer strips is applied to the remaining total nitrogen load
based on the percent of stream length that is protected by buffer strips.
6-3
For hay pasture, nutrient management (BMP) is again applied uniformly across hay pasture
acreage in the watershed. Further reductions in the remaining total nitrogen loads are then
considered through the implementation of BMP 5 or BMP 7. (Again, BMP 5 and 7 can only be
applied individually to a given acre of hay pasture and their total implementation can not exceed the
total acreage of hay pasture.) Finally, reduction of TN load from streambank erosion is determined
from the implementation of streambank fencing and stabilization on a “per mile” basis.
6.2 GROUNDWATER LOAD ADJUSTMENTS
In addition to reductions in surface runoff loads, implementation of agricultural BMPs can
also affect sub-surface nitrogen concentrations. The effects of BMP implementation are included by
applying “Adjustments” to TN groundwater/subsurface loads. The load adjustments are calculated
from BMP adjustment factors (Table 6-2) and the area of BMP application relative to the total
watershed area. As shown in the table, implementation of BMPs 1-5 will result in a slight increase in
groundwater / subsurface TN loads, whereas implementation of nutrient management (BMP 6) or
vegetated buffer strips will result in a reduction of TN loads. (Note that the equation for
groundwater TN load adjustment (see Appendix D) considers the BMP application area relative to
the total watershed area. This is different than the approach outline in Evans et al. (2003) which
considers the BMP application area to the total hay pasture or total agricultural acreage. This latter
approach, as outlined by Evans et al. (2003), does not show any difference in calculated
groundwater/subsurface TN load reductions for highly agricultural versus highly forested or urban
watersheds and does not appear to be properly formulated.)
Table 6-2. Adjustment Factors for Groundwater / Subsurface Nitrogen Loads
1
BMP System / Type Adjustment Factor
BMP 1 +8%
BMP 2 +8%
BMP 3 +4%
BMP 4 +6%
BMP 5 +10%
BMP 6 -50%
Vegetated Buffer Strips -40%
1
Values taken from Evans (2003)
2
All adjustment factors are applied on a “per acre” basis except for vegetated buffer strips which are applied on a “per mile” basis
6-4
6.3 URBAN BMPS
As discussed in Evans et al. (2003), implementing the use of urban BMPs within an
evaluation tool like PRedICT is difficult because “many of these practices are very site-specific (e.g.,
critical area planting) and others require more information about existing conditions (i.e., existing
stormwater sewers) than can be adequately estimated using the GIS data sets currently employed by
AVGWLF. Moreover, pollutant reduction efficiencies and cost data for many urban BMPs are not
widely available.” Given these limitations, only information on detention basins and constructed
wetlands is given in PRedICT, Version 1.0 (Evans et al., 2003). This information is summarized in
Table 6-3.
Table 6-3. Default Reduction Efficiencies (%) for Urban BMPs
1
BMP Type TN Default Reduction Efficiencies (%)
Detention Basin 51
Constructed Wetlands 51
1
Values taken from Evans et al. (2003)
In the LIS management tool, TN load reductions are calculated separately for high density
and low density urban areas. TN load reduction due to vegetated buffer strips is applied to the
remaining urban loads based on the percent of stream length that is protected by buffer strips.
6.4 WASTEWATER DISCHARGE REDUCTIONS
Specific wastewater reduction options that are being considered include: (1) conversion of
septic systems to secondary or tertiary treatment plants, (2) upgrades of primary treatment plants to
secondary or tertiary treatment, and (3) upgrades of secondary treatment to tertiary treatment.
Default reduction efficiencies for these conversions and upgrades are given in Table 6-4. The
reduction efficiencies are used along with prescribed information on the number of future septic
system conversions (given as either an increase or reduction in the number of people on septic
systems) and treatment plant upgrades to calculate TN load increases / reductions from wastewater
discharges.
6-5
Table 6-4. Default Reduction Efficiencies (%) for Septic System Conversions and Treatment Plant Upgrades
1
TN Reduction Efficiencies (%)
Septic Systems to Secondary Treatment 14
Septic Systems to Tertiary Treatment 56
Primary Treatment to Secondary Treatment 14
Primary Treatment to Tertiary Treatment 56
Secondary Treatment to Tertiary Treatment 42
1
Values taken from Evans et al. (2003)
6.5 COST CALCULATIONS
Cost calculations are performed for a given scenario based on application on agricultural and
urban BMPs, and wastewater reductions (Sections 6.1 – 6.4) and unit costs. For agricultural BMPs,
unit costs are provided for specific management options as described in Table 6-5. Costs for urban
BMPs that are currently considered are given in Table 6-6. Finally, unit costs for wastewater
reduction options are given in Table 6-7. Note that for wastewater reductions, the equation on page
39 of the PRedICT Manual (Evans et al., 2003) appears to have an error in the placement of
parentheses. In addition, the cost associated with upgrading wastewater from septic conversions to
tertiary treated wastewater should be based on the number of people affected by septic conversion
(and not the number of converted septic systems).
6-6
Table 6-5. Unit Costs for Agricultural BMPs
Values given
in PRedICT
1
BMP 1 Crop Residue Management
Cover Crops
$30 / acre
$20 / acre
BMP 2 Strip-cropping / Contour Farming $7.50 / acre
BMP 3 Cover Crops
Crop Rotation
($20 / acre)
$30 / acre
BMP 4 Crop Residue Management
Strip-cropping / Contour Farming
Crop Rotation
($30 / acre)
($7.50 / acre)
($30 / acre)
BMP 5 Terraces and Diversions $170 / acre
BMP 6 Nutrient Management $110 / acre
BMP 7 Grazing Land Management $360 / acre
Stream Costs Vegetated Buffer Strips
Streambank Fencing
$180 / mile
$2,000 / mile
1
Values from Evans et al. (2003). Values in parentheses are repeated from previously assigned values.
Table 6-6. Unit Costs for Urban BMPs
BMP Type Values given in PRedICT
1
Detention Basin (wet pond) $15,000 / acre
Constructed Wetland $25,000 / acre
1
Values from Evans et al. (2003). Values are based on per acre of constructed pond or wetland.
6-7
Table 6-7. Unit Costs for Wastewater Reduction Options
Values given in PRedICT
1
Septic to Sewer System Conversions $15,000 / home
Primary to Secondary Treatment Upgrade $250 / capita
Primary to Tertiary Treatment Upgrade $300 / capita
Secondary to Tertiary Treatment Upgrade $150 / capita
1
Values from Evans et al. (2003).
6.6 PROGRAM EXECUTION
The “stand-alone” version of PRedICT that was developed as part of this project is run
through Microsoft EXCEL. In this format, a single watershed, a grouping of watersheds, or all
Connecticut and New York State watersheds draining into Long Island Sound can be selected for
program execution from a “checklist” form. An EXCEL worksheet is then constructed
automatically listing the specified watersheds across the top and the BMP/Wastewater Reduction
parameters down the side. The user can enter appropriate BMP/Wastewater Reduction application
parameters for a given scenario on the “Input – BMP Appl. & Unit Costs” worksheet. Information
on unit costs of the various BMP / Wastewater Reduction options is also entered at the bottom of
the worksheet. Nitrogen load reductions and associated costs of the specified BMP/Wastewater
Reduction scenario are then calculated by executing a VBA-programmed macro by clicking the
“PRedICT RUN” button. (Annotated versions of the VBA source code for nitrogen load
reductions and cost analysis are given in Appendix D.) Results are given in tabular form on the
“Results – N Reductions & Costs” worksheet.
7-1
SECTION 7
7 CONCLUSIONS AND RECOMMENDATIONS
In this project, a management tool has developed to support the estimation and tracking of
nutrient loadings, from urban and rural non-point sources of pollution, based on land use changes
and BMPs. The framework consists of an AVGWLF front-end that characterizes the nutrient
loadings from specific land use and other physiographic and climatologic factors. Secondly, an MS-
Excel based spreadsheet tool allows the evaluation of nutrient load reduction strategies based on the
BMP effectiveness and cost data specific to individual watersheds. It accounts for local climatic and
geographic conditions, and can integrate site-specific aspects such as BMP types and their
performances and costs, and future land uses.
The tool is flexible and user-friendly for local decision-makers such as state/county staff and
watershed managers to evaluate loadings from future land uses or characterize loads from existing
land uses. The intended uses of this tool are land use planning and BMP site and technology
selection and tracking the loads from existing and future land uses in order to achieve the desired
water quality goals (e.g., 10% reductions for the in-basin non-point sources of pollution). The
control of nutrients using BMPs may involve tens of millions of dollars of investment from
stakeholders such as farm communities and municipalities. It is expected that the tool presented in
the study will assist in the appropriate investment of such funds, and can be used to enhance
communication and transparency of the screening process. The major advantage of this
management tool is its simplicity and interactive setup to assess nutrient reductions and promote
cost-effective nitrogen control.
Overall, the management tool can help the local decision-maker in evaluating pollution
control alternatives and associated costs. An interactive version of the tool is provided as
deliverable that can potentially be distributed to the state/county staff and watershed managers.
With further enhancement of the tool to include specific point source TN loadings, it can
help in the establishment of potential effluent trading credits between point and non-point sources
of pollution so that cost-effective nitrogen reduction programs can be developed. The tool can be
further enhanced through more detailed consideration of point source loads, characterization of in-
basin nutrient attenuation, incorporation of applicable diversion data, and, moreover, inclusion of
the already existing BMPs and their performances. This will help not only in the on-going planning
at the state/county level or by the Management Committee, but also in the implementation aspects
with respect to TN reductions and associated improvements in LIS water quality.
The following recommendations are provided, from a research and implementation
perspective, to further refine the databases setup for this project and also to further enhance the tool
7-2
for site-specific planning and management. Some of the recommendations are also pertinent to
enhancing the user’s confidence in the application of this tool.
a. In addition to the three test watersheds, conduct additional flow and water quality
calibration in selected watersheds in Connecticut and New York, where there are
available data from previous studies;
b. Compile more recent GIS coverages for New York watersheds to refine their
representations, similar to the Connecticut coverages that were made available for this
study;
c. Conduct additional analysis on groundwater nitrogen concentrations, as the groundwater
appears to be a significant source to Long Island Sound;
d. Enhance the tool to account for existing BMPs and their performances, so the watershed
managers can evaluate additional BMPs to achieve the desired TN reduction goals; and
e. Enhance the tool to include nitrogen attenuation factors and point source discharges, so
the watershed managers can explore nitrogen reductions through trading between point
and non-point sources, or between non-point sources.
8-1
SECTION 8
8 REFERENCES
AQUA TERRA and HydroQual, 2001. Modeling Nutrient Loads to Long Island Sound from
Connecticut Watersheds, and Impacts of Future Buildout and Management Scenarios,
CTDEP Bureau of Water Management, Hartford, CT.
Donigian, Jr., A.S., 2000. HSPF Training Workshop Handbook and CD. Lecture #19. Calibration
and Verification Issues, Slide #L-19-22. EPA Headquarters, Washington Information
Center, 10-14 January 2000. Presented and prepared for U.S. EPA, Office of Water, Office
of Science and Technology, Washington, DC.
EPA, 1997. Compendium of Tools for Watershed Assessment and TMDL Development, EPA 841-
B-97-006. U.S. Environmental Protection Agency, Washington, DC.
Evans, B.M., S.A. Sheeder, K.J. Corradini, and W.S. Brown, 2003. “AVGWLF Version 5.0 Users
Guide.”
Evans, B.M., D.W. Lehning, K.J. Corradini, G.W. Peterson, E. Nizeyimana, J.M. Hamlett, P.D.
Robillard, and R.L. Day, 2002. A Comprehensive GIS-Based Modeling Approach for
Predicting Nutrient Loads in Watershed. J. Spatial Hydrology, Vol. 2, No.2.
Garabedian, S.P., J.F. Coles, S.J Grady, E.C.T. Trench, and M.J. Zimmerman, 1998. Water Quality in
the Connecticut, Housatonic, and Thames River Basins, Connecticut, Massachusetts, New
Hampshire, New York, and Vermont, 1992-95. U.S. Geological Survey Circular 1155.
Haith, Douglas A., R. Mandel, and R. Shyan Wu, 1992. “GWLF: Generalized Watershed Loading
Functions, Version 2.0, User’s Manual”. Department of Agricultural & Biological
Engineering, Cornell University, Riley-Robb Hall, Ithaca NY.
Karimipour, S., 1997. Estimates of Nonpoint Source Nitrogen Loading to Long Island Sound,
Nassau and Suffolk Counties: New York State Department of Environmental Conservation,
47 pages.
Maidment, D.R., 2002. Arc Hydro: GIS for Water Resources, ESRI Press, Redlands CA, 220 pages.
Moore, R.B., C.M. Johnston, K.W. Robinson, and J.R. Deacon, 2004. Estimation of Total Nitrogen
and Phosphorus in New England Streams Using Spatially Referenced Regression Models,
Scientific Investigations Report 2004-5012, U.S. Geological Survey.
8-2
Mullaney, J.R., G.E. Schwartz, and E.C.T. Trench, 2002. Estimation of Nitrogen Yields and Loads
from Basins Draining to Long Island Sound, 1988-98, Water Resources Investigations
Report 02-4044, US Geological Survey.
New York State Department of Environmental Conservation and Connecticut Department of
Environmental Protection, 2000. A Total Maximum Daily Load Analysis to achieve Water
Quality Standards for Dissolved Oxygen in Long Island Sound.
Scorca, M.P. and J. Monti, Jr., (2001). Estimates of Nitrogen Loads Entering Long Island Sound
from Ground Water and Streams on Long Island, New York, 1985-96. U.S. Geological
Survey, Water Resources Investigations Report 00-4196.
Triad Engineering, HydroQual, and TN Associates, 2003. Trail Creek E-Coli TMDL Report,
Indiana Department of Environmental Management.
9-1
SECTION 9
9 ACKNOWLEDGMENTS
This project was performed through a non-construction federal grant awarded to Manhattan
College (New York) from the Long Island Sound Office of the United States Environmental
Protection Agency (Federal Domestic Assistance Number 66-437; Cooperative Agreement LI
97286104-0). Dr. Kevin J. Farley, Professor of Civil and Environmental Engineering at the School
of Engineering, served as the Principal Investigator of this study. He directed all components of this
study and also was directly responsible for development of the Microsoft EXCEL-based
management tool. Dr. Farley was assisted by student interns at the Manhattan College, specifically,
the contributions of Ms. Kathleen Munson towards development of the Visual Basic Application is
greatly appreciated.
HydroQual, Inc. worked as a sub-consulting organization in the project. Dr. Sri Rangarajan,
Ph.D., P.Eng., served as technical lead for the overall project and directed the selection of
appropriate modeling tool (AVGWLF) and its application to test watersheds and remaining
watersheds in the States of Connecticut and New York. Mr. Nickitas Georgas, M.Sc., led the
AVGWLF model calibration efforts, with assistance from Ms. Dawn Henning and student interns.
Mr. Charles L. Dujardin, P.E., served as the Quality Control officer for the project.
The guidance, efforts, and contributions provided by Mr. Mark Tedesco, the Director of the
Long Island Sound Program, and Mr. Paul Stacey from the State of Connecticut Department of
Environmental Protection were immensely valuable for successful completion of this project. With
the turn over of staff resources, the study team greatly acknowledges the project extension provided
by Mr. Tedesco.
We also want to acknowledge the support provided by several individuals during the data
compilation stages of this project, including Professor Douglas A. Haith at Cornell University, Mr.
Tom Villa of Norwalk 2
nd
District Water Department, James Hurd of the Center for Land Use
Education and Research (CLEAR) of the University of Connecticut, Tony Donigian of AQUA
TERRA, and Dr. Barry Evans at Pennsylvania State University.
10-1
SECTION 10
10 PRESENTATIONS/PUBLICATIONS/OUTREACH
A presentation was made at the TMDL 2005 conference held in Philadelphia (Pennsylvania)
hosted by the Water Environment Federation on the screening of various mathematical tools
available in the public and commercial-domain and selection of the AVGWLF model for this
project. A copy of the paper, previously submitted to Mr. Mark Tedesco (Project Officer), on the
screening and selection of the mathematical model for this project is attached to this report.
The project team is planning to prepare an abstract to the Water Environment Federation
for a possible presentation at the TMDL 2007 conference to be held in the State of Washington.
A-1
APPENDIX A
COMPARISON OF BMP MODELS
A-2
Model Attributes
MODEL
Public
Domain
Land
Use
Hydrology
Processes/
Complexity
Spatial
Scale
(Land
uses)
GIS-
Integration
Temporal
Scale
Pollutant
Load
Process
Flow/WQ
Routing
Comparison
with
Monitored
Data
Compliance
Assessment
Sensitivity/
Uncertainty
Analysis
Costs
Inclusion
for Trading
Evaluation
ANSWERS Yes Agricul-
tural Detailed Any Yes Any
UAL,
USLE,
B&W
Yes Coarse No No External
Auto-QI Yes Urban Simple Any External Any UAL No No No No External
AVGWLF Yes Mixed Mid-range Any Yes Daily UAL Yes Daily No Yes Yes
EPA Region
5 Yes Agricul-
tural Simple Any External Annual
RUSLE,
GEE,
UAL
No No No No External
HSPF Yes Mixed Detailed Any Yes Hourly UAL,
B&W Yes Yes No Yes External
LIFE No Urban Detailed Any Yes Any UAL,
B&W Yes Yes Yes Yes Yes
LSPC Yes Mixed Detailed Any Yes Hourly UAL,
B&W Yes Yes No Yes External
MUSIC No Urban Mid-range Any Yes Hourly UAL Yes Yes No Yes Yes
P-8 Yes Urban Simple, SCS Any External Continuous UAL Yes Coarse No No External
PLOAD Yes Mixed Simple Any Yes Annual UAL No No No No External
Simple
Method Yes Urban Simple Large External Event-based UAL No No No No External
SIMPTM Yes Urban Simple Any External Any UAL No Coarse No No External
SLAMM Yes Urban Simple, SCS Small External Continuous UAL No Coarse No No External
SPARROW Yes Mixed Simple Large External Annual,
Monthly UAL Yes Coarse No Yes External
STEPL Yes Mixed Simple Any External Annual UAL,
USLE No No No No External
SWAT Yes Agricul-
tural Detailed Any Yes Daily
USLE,
UAL,
B&W
Yes Daily No Yes External
SWMM Yes Urban Detailed Any External Any UAL,
B&W Yes Yes No Yes External
WEPP Yes Agricul-
tural Detailed Any Yes Hourly UAL,
B&W Yes Coarse No Yes External
WTM No Mixed Simple Any External Annual UAL No Coarse No No External
A-3
KEY TO THE MODEL MATRIX
Abbreviations
B&W – Buildup and Washoff
GEE – Gully Erosion Equation
SCS – Soil Conservation Service
UAL – Unit Area Loading (e.g., lb/acre/year)
USLE – Universal Soil Loss Equation
RUSLE – Revised Universal Soil Loss Equation
Model Details
ANSWERS – Areal Nonpoint Source Watershed Environment Response Simulation Model
Auto-QI – Developed by Illinois State Water Survey
AVGWLF – ArcView based Generalized Watershed Loading Functions – developed by Cornell University, and
interface developed by Pennsylvania State University
EPA Region 5 Model – Available within EPA’s Section 319 Grants Reporting and Tracking System (GRTS),
initially developed by Indiana Department of Environmental Management
HSPF – Hydrologic Simulation Program in Fortran – built in EPA BASINS
LIFE – Low Impact Feasibility Evaluation model developed by CH2M HILL
LSPC – Loading Simulation Program in C++ - built in the EPA Region 4 Toolbox
MUSIC – Model for Urban Stormwater Improvement Conceptualizations developed by Monash University and
Catchment Research Center
P-8 – Program for Predicting Polluting Particle Passage Through Pits, Puddles, and Ponds
PLOAD – Pollutant Load generation model – built in EPA BASINS
Simple Method – Developed by Tom Schuler at the Center for Watershed Protection for urban areas in and around
Washington DC.
SIMPTM – Simplified Particulate Transport Model
SLAMM – Source Loading and Management Model developed by Robert Pitt
SPARROW – Pollutant load generation Model developed by USGS
STEPL – Spreadsheet Tool for Estimating Pollutant Loads available within GRTS
SWAT – Soil and Water Assessment Tool – built in EPA BASINS
SWMM – Storm Water Management Model developed by U.S. EPA essentially for urban watersheds
WEPP – Water Erosion Prediction Project developed by U.S. Forest Service
WTM – Watershed Treatment Model developed by Center for Watershed Protection
B-1
APPENDIX B
AVGWLF INPUT DATA COMPILATION
B-2
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
WEATHER
Daily
temperature
and
precipitation
Historical
weather data
from NWS
monitoring
stations
within PA
CONNECTICUT
AQUA TERRA and HydroQual, 2001 for the 1981-1995
period. Temperature range was from primary stations Wigwam
Reservoir and West Thompson Lake. Two secondary stations
used one of these temperature ranges to adjust their mean
temperatures, based on proximity. All other tertiary stations
used the four primary/secondary time series based on the
three-zonal CT historic isotherm map. Gaps in rain data were
filled by assigning nearby station values, interpolating, or
regressing.
NEW YORK
Stations were selected from the National Climatic Data Center
CDs to represent precipitation and temperature data for the
NY watersheds, including Suffolk, Nassau, and Westchester
Counties.
Mean daily
temperature in
degrees F; total
daily
precipitation in
inches
TMAX, TMIN,
PRCP in
specific CSV
format.
Feature data source:
Point shape file.
Since AVGWLF looks
for stations outside the
watershed boundaries,
artificial stations were
created with data from
adjacent stations in
order to make the
model runs.
TRANSPORT
Basin Size GIS/derived
from basin
boundaries
CONNECTICUT
Subregional, regional, and major basins from the AQUA
TERRA and HydroQual, 2001 (CTDEP; University of
Connecticut MAGIC databases UCONN-MAGIC). Inputs
developed for basins (subregional), rbasins (regional), and
mbasins (major basins).
NEW YORK
Basins were developed using the Reach File 3 in EPA
BASINS and the hydrologic unit category (HUC-14?) basins
developed by the USGS?
For AVGWLF,
areas in m
2
. For
GWLF, area in
hectares
(=10,000 m
2
)
Area, in m
2
, and
perimeter, in m.
Land
use/cover
GIS/derived
from land
CONNECTICUT
1995 land use from UCONN-MAGIC - The only one
Land use type
delineations and
15 specific
categories +
Raster data source:
Integer grid file. Should
B-3
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
layer use/cover
map
completed with high/low development subcategories. Most
CTDEP land uses did not distinguish between low and high
development.
NEW YORK
Derived from the EPA BASINS databases and consolidated
into the subcategories of AVGWLF.
attributes one unclassified
+ unpaved
roads.
look like palumrlc in
[PA]/Landuse.
Curve
numbers by
source area
GIS/derived
from land
cover and
soil maps
CONNECTICUT and NEW YORK
STATSGO database to define the land cover and associated
curve number. For the hydrologic soil group of “water”, a
default value of C as in Pennsylvania studies.
Non-
dimensional
For the soil
group type, a
weighted
average of
components
was taken to
characterize the
dominant type
of hydrologic
soil group (A-
D) in a soil
type.
Internally computed in
AVGWLF based on
STATSGO soil group
type and the raster land
use/cover type.
USLE factors
(KLSCP) by
source area:
- Soil
erodibility, K,
-Stream slope
length,
L=2SD/A,
- Slope, S,
- Cropping
management,
C, and,
- Erosion
Control
Practice, P
GIS/derived
from:
- K:
STATSGO
soil,
- S: DEM,
- SD: “Blue
stream density”
from 1:24000
USGS topos,
- A: Watershed
areas, and,
- C,P: PA-
based estimates
CONNECTICUT and NEW YORK
STATSGO/Basins soils for K, Basin streams for L, DEM
for S.
• K: Only the value of KFFACTOR for the upper
sediment layer is used for erodibility calculations
(Evans et al., 2003). Results for K range from 0.01-0.49,
close to Evans’ 0.10-0.50.
• L: Stream Length, calculated for EPA Region 1-2 RF3
streams.
• S: From EPA Basins DEM.
• For C and P we used the same values as the PA file:
Same for everywhere for C_CROP=0.42;
C_PAST=0.03; C_WOOD=0.002, P1=0.52, P2=0.45,
P3=0.52, P4=0.66, P5=0.74.
- K: non-
dimensional
- L and S are
internally
computed in the
correct units
- C and P are
fractions less
than 1, with
unity signifying
NO reduction in
sediment yield
due to practices
of crop/land
management.
- K: in soils it is
called MU_KF,
found in
STATSGO as
KFFACTOR
(adjusted as free
of rock
fragments).
- L: in streams
LENGTH_M,
LENGTH_MI,
LENGTH_FT.
- CP: in counties.
The starting values used
are a C of 0.09 (highest
estimate – Table B-12
of Haith et al, 1992) and
a P of 1.0.
B-4
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
ET cover
coefficients
GIS/derived
from land
cover
CONNECTICUT and NEW YORK
Built-in look up table based on land use. See comments.
Non-
dimensional
One area-weighted
average per month.
Based on land
use/cover type, and
Haith et al. (1992) Table
B-8 (0.3;1.0).
Rainfall
erosivity
coefficients
GIS/derived
from
physiography
map
CONNECTICUT and NEW YORK
Modified counties map based on GWLF’s recommendations
(see comments). Mid-Atlantic and New England with 5 zones
(17, 30, 31, 32, 33). CT is mostly zone 33: 0.11 cool / 0.22
warm.
Unknown.
Probably non-
dimensional.
The rainfall
erosivity units
are
(MJ/ha)*(mm/h
r), as in SI
AREA,
PERIMETER,
GWRECESS
(initially 0.10 as
in PA),
RAIN_COOL
and
RAIN_WARM
based on
erosivity zones
(GWLF).
The rainfall erosivity
factor has been mapped
for the whole United
States. Hartford, CT is
in zone 33, with a
t
=0.11
for the cool and 0.22 for
the warm seasons,
respectively. Each
period (warm/cool) has
a value.
Daylight hrs
by month
Computed
automatically
for state
CONNECTICUT and NEW YORK
Same as PA database.
Hours Different for each
month based on latitude
of centroid.
Growing
season
months
Input by
user. May-
Sep.
May-Oct. Based on the 1950-2002 average monthly
temperature records of 3 stations surrounding the LIS
watershed (Groton, CT, Stamford, CT, and Setauket Strong,
NY), temperatures are generally greater than 10 C from May
through October.
Specified directly by the
user.
Antecedent
moisture
conditions
Antecedent
rainfall;
Default
values of 0
for all 5 days
Same values used in CT and NY. cm The first year is always a
spin-up.
B-5
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
Initial snow
amount
Default
value of 0
Same value used in CT and NY. cm Same as above.
Initial
unsaturated
storage
Default
value of 0
Same value used in CT and NY. cm
Initial
saturated
storage
Default
value of 10
Same value used in CT and NY. cm Linear reservoir initial
condition.
Recession
coefficient
Default
value of
0.10
For the in-basin source areas, value changed to 0.0625/day
based on test-watershed calibration. Rest of New England left
at 0.10.
1/day GWRECESS in
“physiographic
provinces” –
Look also at
rainfall
erosivity.
Linear reservoir
coefficient for ground
water discharge of initial
and percolated moisture
in the saturated zone.
Ranges from 0.01-0.20.
In the Northeast, a
value of 0.10 is
common.
Seepage
coefficient
Default
value of 0
Same value used in CT and NY. cm The conservative
approach is to not allow
seepage of saturated
zone moisture to the
deep aquifer, as this
would be a loss from
the groundwater base
flow.
Sediment
delivery ratio
GIS/based
on basin
size
Same value used in CT and NY. Non-
dimensional
Empirical relation by
Varoni (1975);
SDR=0.451*b
0.298
where
b is the basin size in
km
2
.
B-6
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
Soil water
(available soil
moisture
capacity in
unsaturated
zone soils),
U*. Also
known as
“available
water-holding
capacity).
GIS/derive
d from soil
map
MU_AWC = SUM
layers,components
[ (awch+awcl)/2 * (laydeph-
laydepl) * 2.54 cm/inch ].
From STATSGO data use information (pgs11-17): AWCH,
AWCL are the high and low values for the range of available
water capacity of each soil layer or horizon (inch/inch) in
STATSGO, respectively, and the laydepl and laydeph are the
beginning and ending depths of that soil layer measured from
the soil surface, in inches. Total is sum over all soil layers (1, 2,
etc.) and weighted-average of all components (comp%;
seqnum) to give one value per MUID (map unit identifier).
Results range from 1.4-51.6cm, close to the Evans et al. (2003)
of 10-50cm.
cm MU_AWC
Area-weighted value of
the computed, soil-type-
based values that is
added as an attribute to
the STATSGO soils
theme. A value of 10cm
is assumed for pervious
areas, corresponding to
a 100cm rooting depth
and a 0.1 cm/cm
volumetric available
water capacity, typical
for a wide range of
plants and soils. One
area-weighted value.
Lateral
(Stream bank)
Erosion Rate,
LER=a*q
0.6
GIS/derived
from:
• %
developed
land in
watershed,
• Average
AEU,
• Average
CN,
• Average
soil K
factor,
• Average
slope
CONNECTICUT
CTDEP + Modified ZIP code + STATSGO + DEM.
Average of bdh and bd of the first soil layer, then weighted
average through component soils to get one value per soil
type. Values of 1.5 were assigned just to be mentally
consistent with the assumption on the right. The wet bulk
density ranges from 0.4-1.4 g/cm
3
(400-1,400 kg/m
3
).
NEW YORK
Similar database was constructed from EPA BASINS and
STATSTO databases.
Unknown Dry bulk (not
wet bulk)
density is
required as two
input fields in
soils (MU_BD
and Surf_bd).
“a” is automatically
calculated based on the
attributes to the left
(a=0.0004-0.000005).
After LER is calculated,
the total sediment load
for the watershed
generated by stream
bank erosion is LER x
total length of streams
(from streams.shp) x
average stream bank
height (assumed 1.5m) x
average soil bulk density
(assumed 1,500 kg/m3).
B-7
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
NUTRIENTS
Dissolved
N/P in
runoff by
land cover
type
Default
values
Same values used in CT and NY. mg/L Default values for
manure free areas can
be edited if needed.
Manure
spreading
months
Input by
user
Same values used in CT and NY. Usually, no manure
spreading is simulated, so the two periods have no relevance as
long as the user uses the dissolved N/P concentrations in
agricultural runoff with and without manure.
Specified directly by the
user.
Dissolved
N/P in
runoff from
manure areas
Default
values /
adjusted per
AEU
Manually adjusted! For no manure spreading simulation, the
values should be equal to the dissolved N/P concentrations in
agricultural areas. If manure spreading needs to be simulated,
manually adjusted upwards by AEU.
AEU: By county, estimates based on USGS 1992 farm animal
population data for the US: AEU= # of animals in county *
average animal weight (in 1,000 lbs) summed over animal
categories. Divided by each county’s acreage to get
AEU_ACRE.
mg/l AEU_ACRE Default values for
agricultural areas where
manure is applied can
be edited if needed.
Adjusted for AEUs
(1AEU=1,000animal-
lbs/acre).
N/P buildup
(accumulation)
rate in urban
areas
Two
default
values
(Virginia
State)
“from
GWLF
manual”
Same values used in CT and NY. kg/ha-day 0.012 [U] for N in low
intensity development;
0.101 [U] for N in high
intensity development.
Values may be edited
based on Table B-17 of
Haith et al. (1992).
N/P point
source loads
GIS/Derive
d from
NPDES
CONNECTICUT
AQUA TERRA and HydroQual (2001) for 1990-1995.
Average values for significant treatment plants listed in that
kg/year TOTAL_N,
TOTAL_P.
Annual loads read from
the point source theme.
B-8
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
point
coverage
study.
NEW YORK
Compiled from EPA BASINS databases.
Background
N/P
concentrations
in GW
GIS/Deriv
ed from
new
backgroun
d Nitrogen
map for
PA
GIS grid in ug/L! Designated by land use for Connecticut:
130ug/L forested-other, 1200ug/L Urban, and 4750ug/L
agriculture, based on the analysis of TN USGS data from
surficial wells in Connecticut, excluding K-test, log-
transformed outliers. For Long Island, created based on the
USGS 2001 report “Estimates of Nitrogen Loads Entering LIS
from Ground Water and Streams on LI, NY, 1985-96.”
Different concentrations for sewered areas (1.9mg/L), non-
sewered developed areas (3.7mg/L), agricultural areas
(9.9mg/L), low impact areas (forest areas and other)
(1.0mg/L), and water (0.0mg/L), rounded to integer. Two
themes, one with the sewer network of 1997, and one
including proposed updates.
mg/L For Connecticut, the
user should change the
units to mg/L by
dividing AVGWLF
output (GWLF input
concentration) by 1,000!
Background
N/P
concentrations
in soil
(sediment)
Based on
map in
GWLF
manual
Nitrogen is 3,000 mg/kg. Phosphorus is as follows: From
Haith et al. (1992) Fig. B-4, P
2
O
5
is ~0.145% of the surface
30cm of CT/WC/LI soils (0.10%-0.19% range). From
AVGWLF, P
soils
=0.145% * 1,000,000 mg/kg * 43% P/P2O5 *
2.0 representative enrichment ratio=1,247 mg/kg.
mg/kg N is default. P is
an integer grid,
uniform value
(1247) for CT,
Westchester & LI
3,000 mg/kg for N.
Figure B-3. Same for
most of the North East.
Population
on septic
systems
GIS/derive
d from 1990
population
census tract
Census 1990 tract data for public, septic, and other sewers,
merged on 2000 tracts. As in PA, the septic category is used as
normal systems, and the other category is used as short-
circuited systems.
# SEW_PUB,
SEW_SEPT,
SEW_OTHR
Same attributes (normal
sys / pond sys / short
circ sys / discharge sys)
as census tract theme.
Per capita
septic system
(tank
effluent)
loads (N/P)
Default
values from
GWLF
manual
Same. grams/day 12 g/d for N. 2.5 g/d
for P.
B-9
Required
Data
PA data
source Data Source for This Study Units Attributes Comments
Growing
season N/P
uptake by
plants over
the septic
system
Default
values taken
from
GWLF
manual
Same. g/d 1.6 g/d for N. 0.4 g/d
for P.
ADDITIONAL DATA-SPECIFIC REFERENCES
• Scorca, Michael P., Monti, Jack Jr. 2001. “Estimates of Nitrogen Loads Entering Long Island Sound from Ground Water and Streams on Long
Island, New York, 1985-1996.” USGS, Water Resources Investigations Report 00-4196. In cooperation with NYSDEC, USEPA. Coram, NY.
• USGS National Water Quality Assessment (NAWQA) Data Warehouse. Groundwater nitrogen concentrations cross-tab query.
http://infotrek.er.usgs.gov/traverse/f?p=NAWQA:8:9500854782789278765 USGS. Data available from 1994 to 2004.
• University of Connecticut Libraries. “Magic geospatial data resources. Connecticut State Coverages.” http://magic.lib.uconn.edu/cgi-
bin/MAGIC_DBsearch3.pl?Geography=37800&Loc=0000
• NOAA, Climate Prediction Center. “102-year (1895-1996) historic average temperature by climate division.”
http://www.cpc.ncep.noaa.gov/products/predictions/threats2/enso/elnino/ndstat/ct0.gif
• EPA Basins Version 3 (Better Assessment Science Integrating Point and Non-Point Sources).
http://www.epa.gov/docs/ostwater/BASINS/metadata.htm. Used for DEM and RF3 streams.
• University of Connecticut. Center for Land Use Education and Research (CLEAR) / Non-point education for municipal officials (NEMO).
http://clear.uconn.edu/, http://web.uconn.edu/nemo/index2.htm
• 1990 US Census of Population and Housing. Summary Tape File 3 (STF3). Decennial Programs.
http://factfinder.census.gov/servlet/QTGeoSearchByListServlet?ds_name=DEC_1990_STF3_&_lang=en&_ts=137337184218
• NRCS-NCGS. State Soil Geographic Database (STATSGO). http://www.ncgc.nrcs.usda.gov/products/datasets/statsgo
• USGS, 1998. Puckett L., Hitt K., and Alexander R. “County based estimates of nitrogen and phosphorus content of animal manure in the United
States for 1982, 1987, and 1992. Edition 1.0.0. USGS. Reston, Virginia, US. http://water.usgs.gov/lookup/getspatial?manure Used for Animal
Equivalence Units.
• Growing Season: Williams, C.N., Jr., M.J. Menne, R.S. Vose, and D.R. Easterling. 2005. United States Historical Climatology Network Monthly
Temperature and Precipitation Data. ORNL/CDIAC-118, NDP-019. Available on-line [
http://cdiac.ornl.gov/epubs/ndp/ushcn/usa_monthly.html ] from the Carbon Dioxide Information Analysis Center, Oak Ridge National
Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.
C-1
APPENDIX C
ESTIMATED NITROGEN LOADS FOR
WATERSHEDS IN CT AND NY
D-1
APPENDIX D
VBA SOURCE CODE FOR NITROGEN LOAD
REDUCTIONS AND COST ANALYSIS
D-2
SETUP
Sub Setup()
'Definitions
Dim a As Integer
Dim b As Integer
Dim RCLoad As Single
Dim HPLoad As Single
Dim HDULoad As Single
Dim LDULoad As Single
Dim OLoad As Single
Dim SELoad As Single
Dim GSLoad As Single
Dim PSLoad As Single
Dim SSLoad As Single
Dim TotLoad As Single
Dim RCArea As Single
Dim HPArea As Single
Dim HDUArea As Single
Dim LDUArea As Single
Dim TotArea As Single
Dim ALOS As Single
Dim SLA As Single
Dim SLHDU As Single
Dim SLLDU As Single
Dim SLTot As Single
Dim BMP1 As Single
Dim BMP2 As Single
Dim BMP3 As Single
Dim BMP4 As Single
Dim BMP5 As Single
Dim BMP6 As Single
Dim BMP7 As Single
Dim VBS As Single
Dim SF As Single
Dim SS As Single
Dim CW As Single
Dim DB As Single
Dim BMP1RC As Single
Dim BMP2RC As Single
Dim BMP3RC As Single
Dim BMP4RC As Single
Dim BMP5RC As Single
Dim BMP5HP As Single
Dim BMP6RC As Single
Dim BMP6HP As Single
Dim BMP7HP As Single
Dim VBSA As Single
Dim VBSHDU As Single
Dim VBSLDU As Single
Dim SFA As Single
Dim SSA As Single
Dim CWHDU As Single
Dim CWLDU As Single
Dim DBLDU As Single
Dim DBHDU As Single
D-3
'Percent removal inputs
Worksheets("Percent Removals").Select
Cells.Select
Selection.Font.Name = "Courier New"
Range("A:A").Select
Selection.ColumnWidth = 45
Cells(1, 1) = "LOAD REDUCTION EFFICIENCY INPUT"
Cells(3, 1) = "BMP 1: Permanent Vegetative Cover"
Cells(4, 1) = "BMP 2: Strip Cropping & Contour Farming"
Cells(5, 1) = "BMP 3: Cropland Protection"
Cells(6, 1) = "BMP 4: Conservation Tillage"
Cells(7, 1) = "BMP 5: Terraces & Diversions"
Cells(8, 1) = "BMP 6: Nutrient Managment"
Cells(9, 1) = "BMP 7: Grazing Land Management"
Cells(10, 1) = "Vegetated Buffer Strips"
Cells(11, 1) = "Streambank Fencing"
Cells(12, 1) = "Streambank Stabilization"
Cells(13, 1) = "Constructed Wetlands"
Cells(14, 1) = "Detention Basins"
Cells(3, 2) = 50
Cells(4, 2) = 23
Cells(5, 2) = 25
Cells(6, 2) = 27
Cells(7, 2) = 44
Cells(8, 2) = 70
Cells(9, 2) = 43
Cells(10, 2) = 54
Cells(11, 2) = 56
Cells(12, 2) = 95
Cells(13, 2) = 51
Cells(14, 2) = 51
Range("C:I").Select
Selection.ColumnWidth = 21
Cells(2, 2) = "%"
Cells(1, 3) = "PERCENTAGE OF AREA TO APPLY BMP"
Cells(2, 3) = "Row Crops"
Cells(2, 4) = "Hay/Pasture"
Cells(2, 5) = "Low Density Urban"
Cells(2, 6) = "High Density Urban"
Cells(2, 7) = "Agricultural"
For b = 3 To 8
Cells(b, 3).Select
Selection.Interior.ColorIndex = 42
Next b
For b = 7 To 9
Cells(b, 4).Select
Selection.Interior.ColorIndex = 42
Next b
Cells.Select
For b = 13 To 14
Cells(b, 5).Select
Selection.Interior.ColorIndex = 42
Cells(b, 6).Select
Selection.Interior.ColorIndex = 42
Next b
D-4
For b = 5 To 7
Cells(10, b).Select
Selection.Interior.ColorIndex = 42
Next b
Cells(11, 7).Select
Selection.Interior.ColorIndex = 42
Cells(12, 7).Select
Selection.Interior.ColorIndex = 42
Cells(20, 1) = "ESTIMATED LOAD REDUCTIONS"
Cells(22, 1) = "Row Crops"
Cells(23, 1) = "Hay/Pasture"
Cells(24, 1) = "High Density Urban"
Cells(25, 1) = "Low Density Urban"
Cells(26, 1) = "Other"
Cells(27, 1) = "Streambank Erosion"
Cells(28, 1) = "Groundwater/Subsurface"
Cells(29, 1) = "Point Source Discharges"
Cells(30, 1) = "Septic Systems"
Cells(31, 1) = "TOTAL"
Cells(21, 3) = "Existing Load (lbs)"
Cells(21, 4) = "Future Load (lbs)"
'Cost Inputs
Worksheets("Cost Analysis").Select
Cells.Select
Selection.Font.Name = "Courier New"
Range("A:A").Select
Selection.ColumnWidth = 47
Range("B:B").Select
Selection.ColumnWidth = 12
Selection.NumberFormat = "#,##0.00"
Cells(1, 1) = "BMP COST EDITOR"
Cells(2, 1) = "Crop Residue Management (per acre)"
Cells(3, 1) = "Cover Crop (per acre)"
Cells(4, 1) = "Grazing Land Managment (per acre)"
Cells(5, 1) = "Strip Cropping/Contour Farming (per acre)"
Cells(6, 1) = "Streambank Fencing (per mile)"
Cells(7, 1) = "Streambank Stabilization (per foot)"
Cells(8, 1) = "Vegetated Buffer Strip (per mile)"
Cells(9, 1) = "Terraces & Diversions (per acre)"
Cells(10, 1) = "Nutrient Management (per acre)"
Cells(11, 1) = "Crop Rotation (per acre)"
Cells(12, 1) = "Constructed Wetlands (per acre)"
Cells(13, 1) = "Detention Basins (per acre)"
Cells(2, 2) = 30
Cells(3, 2) = 20
Cells(4, 2) = 360
Cells(5, 2) = 7.5
Cells(6, 2) = 2000
Cells(7, 2) = 25
Cells(8, 2) = 180
Cells(9, 2) = 170
Cells(10, 2) = 110
Cells(11, 2) = 30
Cells(13, 2) = 15000
Cells(12, 2) = 25000
Cells(1, 2) = "Cost ($)"
D-5
Cells(19, 1) = "TOTAL COST"
Worksheets("Input").Select
End Sub
PREDICT
Sub Predict()
'Definitions
Dim a As Integer
Dim b As Integer
Dim RCLoad As Single
Dim HPLoad As Single
Dim HDULoad As Single
Dim LDULoad As Single
Dim OLoad As Single
Dim SELoad As Single
Dim GSLoad As Single
Dim PSLoad As Single
Dim SSLoad As Single
Dim TotLoad As Single
Dim RCArea As Single
Dim HPArea As Single
Dim HDUArea As Single
Dim LDUArea As Single
Dim TotArea As Single
Dim ALOS As Single
Dim SLA As Single
Dim SLHDU As Single
Dim SLLDU As Single
Dim SLTot As Single
Dim BMP1 As Single
Dim BMP2 As Single
Dim BMP3 As Single
Dim BMP4 As Single
Dim BMP5 As Single
Dim BMP6 As Single
Dim BMP7 As Single
Dim VBS As Single
Dim SF As Single
Dim SS As Single
Dim CW As Single
Dim DB As Single
Dim BMP1RC As Single
Dim BMP2RC As Single
Dim BMP3RC As Single
Dim BMP4RC As Single
Dim BMP5RC As Single
Dim BMP5HP As Single
Dim BMP6RC As Single
Dim BMP6HP As Single
Dim BMP7HP As Single
Dim VBSA As Single
Dim VBSHDU As Single
Dim VBSLDU As Single
Dim SFA As Single
Dim SSA As Single
Dim CWHDU As Single
D-6
Dim CWLDU As Single
Dim DBLDU As Single
Dim DBHDU As Single
'Input data from BMPtest-sum.dat file. File must be open and have that name.
Windows("Predict_Spreadsheet").Activate
Worksheets("Input").Select
Cells.Select
Selection.Font.Name = "Courier New"
Range("A:A").Select
Selection.ColumnWidth = 41
Range("B:B").Select
Selection.ColumnWidth = 6
Cells(2, 1) = "TN Load from Row Crops"
Cells(3, 1) = "TN Load from Hay/Pasture"
Cells(4, 1) = "TN Load from High Density Urban"
Cells(5, 1) = "TN Load from Low Density Urban"
Cells(6, 1) = "TN Load from Other"
Cells(7, 1) = "TN Load from Streambank Erosion"
Cells(8, 1) = "TN Load from Groundwater/Subsurface"
Cells(9, 1) = "TN Load from Point Source Discharges"
Cells(10, 1) = "TN Load from Septic Systems"
Cells(11, 1) = "Total Basin TN Load"
Cells(12, 1) = "Row Crop Acreage"
Cells(13, 1) = "Hay/Pasture Acreage"
Cells(14, 1) = "High Density Urban Acreage"
Cells(15, 1) = "Low Density Urban Acreage"
Cells(16, 1) = "Total Basin Area"
Cells(17, 1) = "Drainage area/Wetland"
Cells(18, 1) = "Agricultural Land on Slope >3%"
Cells(19, 1) = "Stream Length in Agricultural Areas"
Cells(20, 1) = "Stream Length in High Density Urban"
Cells(21, 1) = "Stream Length in Low Density Urban"
Cells(22, 1) = "Total Stream Length"
Cells(23, 1) = "Peak Flow"
Cells(24, 1) = "Settling Velocity"
b = 2
For a = 1 To 10
Cells(b, 2) = "lbs."
b = b + 1
Next a
For a = 1 To 7
Cells(b, 2) = "acres"
b = b + 1
Next a
For a = 1 To 4
Cells(b, 2) = "miles"
b = b + 1
Next a
For a = 1 To 2
Cells(b, 2) = "in/hr"
b = b + 1
Next a
Windows("BMPtest-sum.csv").Activate
RCLoad = Cells(50, 7)
HPLoad = Cells(49, 7)
HDULoad = Cells(56, 7)
D-7
LDULoad = Cells(55, 7)
OLoad = Cells(51, 7) + Cells(52, 7) + Cells(53, 7) + Cells(54, 7)
SELoad = Cells(57, 7)
GSLoad = Cells(58, 7)
PSLoad = Cells(59, 7)
SSLoad = Cells(60, 7)
TotLoad = RCLoad + HPLoad + HDULoad + LDULoad + OLoad + SELoad + GSLoad + PSLoad + SSLoad
RCArea = Cells(50, 2)
HPArea = Cells(49, 2)
HDUArea = Cells(56, 2)
LDUArea = Cells(55, 2)
TotArea = RCArea + HPArea + HDUArea + LDUArea + Cells(51, 2) + Cells(52, 2) + Cells(53, 2) + Cells(54, 2)
Windows("Predict_Spreadsheet").Activate
Worksheets("Input").Select
'The variable "a" must be changed with each new watershed to be put in a different column.
a = 46
Cells(2, a) = RCLoad
Cells(3, a) = HPLoad
Cells(4, a) = HDULoad
Cells(5, a) = LDULoad
Cells(6, a) = OLoad
Cells(7, a) = SELoad
Cells(8, a) = GSLoad
Cells(9, a) = PSLoad
Cells(10, a) = SSLoad
Cells(11, a) = TotLoad
Cells(12, a) = RCArea
Cells(13, a) = HPArea
Cells(14, a) = HDUArea
Cells(15, a) = LDUArea
Cells(16, a) = TotArea
Cells(23, a) = 1
Cells(17, a) = 10
Cells(24, a) = 104.33
For b = 18 To 22
Cells(b, a).Select
Selection.Interior.ColorIndex = 42
Next b
'Percent removal inputs
Worksheets("Percent Removals").Select
Cells.Select
Selection.Font.Name = "Courier New"
Range("A:A").Select
Selection.ColumnWidth = 45
Cells(1, 1) = "LOAD REDUCTION EFFICIENCY INPUT"
Cells(3, 1) = "BMP 1: Permanent Vegetative Cover"
Cells(4, 1) = "BMP 2: Strip Cropping & Contour Farming"
Cells(5, 1) = "BMP 3: Cropland Protection"
Cells(6, 1) = "BMP 4: Conservation Tillage"
Cells(7, 1) = "BMP 5: Terraces & Diversions"
Cells(8, 1) = "BMP 6: Nutrient Managment"
Cells(9, 1) = "BMP 7: Grazing Land Management"
Cells(10, 1) = "Vegetated Buffer Strips"
Cells(11, 1) = "Streambank Fencing"
Cells(12, 1) = "Streambank Stabilization"
Cells(13, 1) = "Constructed Wetlands"
D-8
Cells(14, 1) = "Detention Basins"
Cells(3, 2) = 50
Cells(4, 2) = 23
Cells(5, 2) = 25
Cells(6, 2) = 27
Cells(7, 2) = 44
Cells(8, 2) = 70
Cells(9, 2) = 43
Cells(10, 2) = 54
Cells(11, 2) = 56
Cells(12, 2) = 95
Cells(13, 2) = 51
Cells(14, 2) = 51
Range("C:I").Select
Selection.ColumnWidth = 21
Cells(2, 2) = "%"
Cells(1, 3) = "PERCENTAGE OF AREA TO APPLY BMP"
Cells(2, 3) = "Row Crops"
Cells(2, 4) = "Hay/Pasture"
Cells(2, 5) = "Low Density Urban"
Cells(2, 6) = "High Density Urban"
Cells(2, 7) = "Agricultural"
For b = 3 To 8
Cells(b, 3).Select
Selection.Interior.ColorIndex = 42
Next b
For b = 7 To 9
Cells(b, 4).Select
Selection.Interior.ColorIndex = 42
Next b
Cells.Select
For b = 13 To 14
Cells(b, 5).Select
Selection.Interior.ColorIndex = 42
Cells(b, 6).Select
Selection.Interior.ColorIndex = 42
Next b
For b = 5 To 7
Cells(10, b).Select
Selection.Interior.ColorIndex = 42
Next b
Cells(11, 7).Select
Selection.Interior.ColorIndex = 42
Cells(12, 7).Select
Selection.Interior.ColorIndex = 42
Cells(20, 1) = "ESTIMATED LOAD REDUCTIONS"
Cells(22, 1) = "Row Crops"
Cells(23, 1) = "Hay/Pasture"
Cells(24, 1) = "High Density Urban"
Cells(25, 1) = "Low Density Urban"
Cells(26, 1) = "Other"
Cells(27, 1) = "Streambank Erosion"
Cells(28, 1) = "Groundwater/Subsurface"
Cells(29, 1) = "Point Source Discharges"
Cells(30, 1) = "Septic Systems"
Cells(31, 1) = "TOTAL"
D-9
Cells(21, 3) = "Existing Load (lbs)"
Cells(21, 4) = "Future Load (lbs)"
'Cost Inputs
Worksheets("Cost Analysis").Select
Cells.Select
Selection.Font.Name = "Courier New"
Range("A:A").Select
Selection.ColumnWidth = 47
Range("B:B").Select
Selection.ColumnWidth = 12
Selection.NumberFormat = "#,##0.00"
Cells(1, 1) = "BMP COST EDITOR"
Cells(2, 1) = "Crop Residue Management (per acre)"
Cells(3, 1) = "Cover Crop (per acre)"
Cells(4, 1) = "Grazing Land Managment (per acre)"
Cells(5, 1) = "Strip Cropping/Contour Farming (per acre)"
Cells(6, 1) = "Streambank Fencing (per mile)"
Cells(7, 1) = "Streambank Stabilization (per foot)"
Cells(8, 1) = "Vegetated Buffer Strip (per mile)"
Cells(9, 1) = "Terraces & Diversions (per acre)"
Cells(10, 1) = "Nutrient Management (per acre)"
Cells(11, 1) = "Crop Rotation (per acre)"
Cells(12, 1) = "Constructed Wetlands (per acre)"
Cells(13, 1) = "Detention Basins (per acre)"
Cells(2, 2) = 30
Cells(3, 2) = 20
Cells(4, 2) = 360
Cells(5, 2) = 7.5
Cells(6, 2) = 2000
Cells(7, 2) = 25
Cells(8, 2) = 180
Cells(9, 2) = 170
Cells(10, 2) = 110
Cells(11, 2) = 30
Cells(13, 2) = 15000
Cells(12, 2) = 25000
Cells(1, 2) = "Cost ($)"
Cells(19, 1) = "TOTAL COST"
Worksheets("Input").Select
End Sub
D-10
COST MODULE
Sub PredictCost()
Dim a As Integer
Dim nwatersheds As Integer 'Number of Watersheds
' Dim WSName As Name 'Watershed Name
'Unit Costs: Input from 'Cost Analysis' Worksheet
Dim CRMCost As Single 'Cost of Crop Residual Management
Dim CCCost As Single 'Cost of Cover Crops
Dim GLMCost As Single 'Cost of Grazing Land Management
Dim SCCFCost As Single 'Cost of Strip-Cropping / Contour Farming
Dim SSCost As Single 'Cost of Streambank Stabilization
Dim SFCost As Single 'Cost of Streambank Fencing
Dim VBSCost As Single 'Cost of Vegetated Buffer Strips (VBS)
Dim TDCost As Single 'Cost of Terraces and Diversions
Dim NMCost As Single 'Cost of Nutrient Management
Dim CRCost As Single 'Cost of Crop Rotation
Dim DBCost As Single 'Cost of Detention Basins
Dim CWCost As Single 'Cost of Constructed Wetlands
Dim Sep2SewCost As Single 'Conversion Cost from Septic to Sewer System
'Watershed Parameters: from 'AVGWLF Results' Worksheet
Dim RCArea As Single 'Row Crop Area
Dim HPArea As Single 'Hay Pasture Area
Dim HDUArea As Single 'High Density Urban Area
Dim LDUArea As Single 'Low density Urban Area
Dim TotArea As Single 'Total Watershed Area
Dim ALOS As Single 'Agricultural Land on Slope >3%
Dim SLA As Single 'Stream Length in Agricultural Areas
Dim SLHDU As Single 'Stream Length in High Density Urban
Dim SLLDU As Single 'Stream Length in Low Density Urban
Dim SLTot As Single 'Total Stream Length
Dim DAtoCWArea As Single 'Service drainage area to constructed wetland area
' (default = 10 in PRedICT)
Dim PeakFlow As Single 'Peak flow for detentio basins (in / hr)
' (default = 1 in / hr in PRedICT)
Dim SettVel As Single 'Settling velocity in detention basins in in / hr
' (default = 103.33 in / hr in PRedICT)
Dim SewerPeople As Single 'Number of People on Sewer System
'BMP Applications / Wastewater Reductions: from 'Percent Reduction' Worksheet
Dim BMP1RC As Single 'BMP1 Row Crop % Area Application
Dim BMP2RC As Single 'BMP2 Row Crop % Area Application
Dim BMP3RC As Single 'BMP3 Row Crop % Area Application
Dim BMP4RC As Single 'BMP4 Row Crop % Area Application
Dim BMP5RC As Single 'BMP5 Row Crop % Area Application
Dim BMP5HP As Single 'BMP5 Hay Pasture % Area Application
Dim BMP6RC As Single 'BMP6 Row Crop % Area Application
Dim BMP6HP As Single 'BMP6 Hay Pasture % Area Application
Dim BMP7HP As Single 'BMP7 Hay Pasture % Area Application
Dim VBSLDU As Single 'VBS (LDU) % Stream Length Application
Dim CWLDU As Single 'Constructed Wetlands (LDU) % Area Application
D-11
Dim DBLDU As Single 'Detention Basins (LDU) % Area Application
Dim VBSHDU As Single 'VBS (HDU) % Stream Length Application
Dim CWHDU As Single 'Constructed Wetlands (HDU) % Area Application
Dim DBHDU As Single 'Detention Basins (HDU) % Area Application
Dim VBSA As Single 'VBS (Agric.) % Stream Length Application
Dim SFA As Single 'Streambank Fencing (Agric.) % Stream Length Appl.
Dim SSA As Single 'Streambank Stab. (Agric.) % Stream Length Appl.
Dim FutSepticPop As Single 'Future Population (# of people) on Septic Systems
Dim ExSepticPop As Single 'Future Population (# of people) on Septic Systems
Dim Sep2TT As Single 'Septic conversions that will receive tertiary treat. (%)
'Calculated Parameters for Urban BMP Applications
Dim DBAreaHDU As Single 'Area of Detention Basins (HDU)
Dim DBAreaLDU As Single 'Area of Detention Basins (LDU)
Dim CWAreaHDU As Single 'Area of Constructed Wetlands (HDU)
Dim CWAreaLDU As Single 'Area of Constructed Wetlands (LDU)
Dim VBSLengthHDU As Single 'Length of Vegetated Buffer Strips (HDU)
Dim VBSLengthLDU As Single 'Length of Vegetated Buffer Strips (LDU)
'Variable Names for Calculated Costs of Agric. / Urban BMPs & Wastewater Reductions
Dim BMP1Cost As Single 'Aggregate Cost for Applying BMP 1
Dim BMP2Cost As Single 'Aggregate Cost for Applying BMP 2
Dim BMP3Cost As Single 'Aggregate Cost for Applying BMP 3
Dim BMP4Cost As Single 'Aggregate Cost for Applying BMP 4
Dim BMP5Cost As Single 'Aggregate Cost for Applying BMP 5
Dim BMP6Cost As Single 'Aggregate Cost for Applying BMP 6
Dim BMP7Cost As Single 'Aggregate Cost for Applying BMP 7
Dim StreamCost As Single 'Cost of Streambank Fencing and Statbilization
Dim AgriCost As Single 'Total Cost for Agricultural BMPs
Dim UrbanDBCost As Single 'Total Cost of Urban Detention Basins
Dim UrbanCWCost As Single 'Total Cost of Urban Construction BAsins
Dim UrbanVBSCost As Single 'Total Cost of Urban VBS
Dim UrbanCost As Single 'Total Cost of Urban BMPs
Dim SepticCost As Single 'Total Costs of Septic Conversions
Dim UpGradPT2ST As Single 'Costs for upgrading from primary to secondary treat.
Dim UpGradPT2TT As Single 'Costs for upgrading from primary to tertiary treat.
Dim UpGradST2ST As Single 'Costs for upgrading from secondary to tertiary treat.
Dim UpGradSep2TT As Single 'Costs for upgrading from septic to tertiary treat.
Dim WWRedCost As Single 'Total Costs of Wastewater Reductions
Dim TotalCost As Single 'Total Cost for Each Watershed
Dim Cum_TotalCost As Single 'Cumulative Costs for All Selected Watersheds
'Read Inputs from "AVGWLF Results", "Percent Removals" and "Costs Analysis" worksheets
Worksheets("Input - BMP Appl. & Unit Costs").Select
nwatersheds = Cells(1, 2)
CumCost = 0
For i = 1 To nwatersheds
Worksheets("Input - BMP Appl. & Unit Costs").Select
n = Cells(2, 2 + i)
WSName = Cells(3, 2 + i)
D-12
a = 2 + i
b = 2 + n
'Read Input from "AVGWLF Results"
Worksheets("AVGWLF Results").Select
RCArea = Cells(12, b)
HPArea = Cells(13, b)
HDUArea = Cells(14, b)
LDUArea = Cells(15, b)
TotArea = Cells(16, b)
DAtoCWArea = Cells(17, b)
ALOS = Cells(18, b)
SLA = Cells(19, b)
SLHDU = Cells(20, b)
SLLDU = Cells(21, b)
SLTot = Cells(22, b)
PeakFlow = Cells(23, b)
SettVel = Cells(24, b)
SewerPeople = Cells(27, b)
'Read Input for Future Land Usage from "Percent Removals"
Worksheets("Input - BMP Appl. & Unit Costs").Select
BMP1RC = Cells(6, a)
BMP2RC = Cells(7, a)
BMP3RC = Cells(8, a)
BMP4RC = Cells(9, a)
BMP5RC = Cells(10, a)
BMP6RC = Cells(11, a)
BMP5HP = Cells(13, a)
BMP6HP = Cells(14, a)
BMP7HP = Cells(15, a)
VBSLDU = Cells(17, a)
CWLDU = Cells(18, a)
DBLDU = Cells(19, a)
VBSHDU = Cells(21, a)
CWHDU = Cells(22, a)
DBHDU = Cells(23, a)
VBSA = Cells(25, a)
SFA = Cells(26, a)
SSA = Cells(27, a)
FutSepticPop = Cells(33, a) + Cells(36, a)
ExSepticPop = Cells(32, a) + Cells(35, a)
Sep2TT = Cells(42, a)
ExPrimary = Cells(44, a)
ExSecondary = Cells(45, a)
ExTertiary = Cells(46, a)
'Read Input for Cost from "Cost Analysis"
Worksheets("Input - BMP Appl. & Unit Costs").Select
CRMCost = Cells(59, 2)
CCCost = Cells(60, 2)
GLMCost = Cells(61, 2)
SCCFCost = Cells(62, 2)
SFCost = Cells(63, 2)
SSCost = Cells(64, 2)
VBSCost = Cells(65, 2)
D-13
TDCost = Cells(66, 2)
NMCost = Cells(67, 2)
CRCost = Cells(68, 2)
CWCost = Cells(69, 2)
DBCost = Cells(70, 2)
Sep2SewCost = Cells(71, 2)
'Cost Calculations for Agricultural BMPs (from eqs on pages 35-37 PRedICT Manual)
'BMP1 cost: based on crop residue management and cover crops
'BMP2 cost: based on strip-cropping/contour farming
'BMP3 cost: based on cover crops and crop rotation
'BMP4 cost: based on crop residue management, strip-cropping/contour farming
' and crop rotation
'BMP5 cost: based on terraces and diversions
'BMP6 cost: based on nutrient management
'BMP7 cost: based on grazing land management
'StreamCost: based on VBS and stream fencing on a 'per mile' basis
BMP1Cost = ((BMP1RC / 100) * RCArea) * (CRMCost + CCCost)
BMP2Cost = (BMP2RC / 100) * RCArea * SCCFCost
BMP3Cost = ((BMP3RC / 100) * RCArea) * (CCCost + CRCost)
BMP4Cost = ((BMP4RC / 100) * RCArea) * (CRMCost + SCCFCost + CRCost)
BMP5Cost = TDCost * (((BMP5RC / 100) * RCArea) + ((BMP5HP / 100) * HPArea))
BMP6Cost = NMCost * (((BMP6RC / 100) * RCArea) + ((BMP6HP / 100) * HPArea))
BMP7Cost = (BMP7HP / 100) * HPArea * GLMCost
StreamCost = ((VBSA / 100) * SLA) * VBSCost + ((SSA / 100) * SLA) * SSCost
StreamCost = StreamCost + ((SFA / 100) * SLA) * SFCost
AgriCost = BMP1Cost + BMP2Cost + BMP3Cost + BMP4Cost + BMP5Cost + BMP6Cost
AgriCost = AgriCost + BMP7Cost + StreamCost
'Cost Calculations for Urban BMPs (from eqs on pg 37-38 PRedICT Manual)
'Detenion Basin Area is based on the watershed area serviced by detention basins
' times the Peak Flow and divided by the Settling Velocity
DBAreaHDU = (HDUArea * (DBHDU / 100)) * PeakFlow / SettVel
DBAreaLDU = (LDUArea * (DBLDU / 100)) * PeakFlow / SettVel
'Constructed Wetlands Area is based on the watershed area serviced by wetlands
' divided by the service drainage area to constructed wetland ratio (e.g., 10)
CWAreaHDU = (HDUArea * (CWHDU / 100)) / DAtoCWArea
CWAreaLDU = (LDUArea * (CWLDU / 100)) / DAtoCWArea
'Length of VBS is based on the miles of riverbank with VBS
VBSLengthHDU = SLHDU * (VBSHDU / 100)
VBSLengthLDU = SLLDU * (VBSLDU / 100)
'Cost of Urban BMPs (Detention Basins, Constructed Wetlands, VBS)
UrbanDBCost = DBCost * (DBAreaHDU + DBAreaLDU)
UrbanCWCost = CWCost * (CWAreaHDU + CWAreaLDU)
UrbanVBSCost = VBSCost * (VBSLengthHDU + VBSLengthLDU)
UrbanCost = UrbanDBCost + UrbanCWCost + UrbanVBSCost
'Cost Calculations for Wastewater Pollution Reduction (from eqs on pg 38-40 PRedICT Manual)
'Costs for Septic to Sewer System Conversions
If (FutSepticPop) < (ExSepticPop) Then
SepticCost = ((ExSepticPop - FutSepticPop) / 4) * Sep2SewCost
End If
D-14
'Costs for Treatment Upgrades
UpGradPT2ST = (ExPrimary / 100) * SewerPeople * (PT2ST / 100) * PT2STCost
UpGradPT2TT = (ExPrimary / 100) * SewerPeople * (PT2TT / 100) * PT2TTCost
UpGradST2TT = (ExSecondary / 100) * SewerPeople * (ST2TT / 100) * ST2TTCost
'Additional Costs for Treating Wastewater from Septic Conversions
' Equation is PRedICT appears to have an error in paratheneses.
' Also, equation is (erroneously) based on # of conversions and not # of people
' (i.e., the division by '4' (people per septic system)' does not seem appropriate
'For our equation, we assumed that the additional costs associated with treating
' wastewater from septic conversions is based on the # of people.
If (FutSepticPop) < (ExSepticPop) Then
UpGradSep2TT = (ExSepticPop - FutSepticPop) * (Sep2TT / 100) * ST2TTCost
End If
WWRedCost = SepticCost + UpGradPT2ST + UpGradPT2TT + UpGradST2TT + UpGradSep2TT
'Total Cost for Nitrogen Load Reduction
TotalCost = AgriCost + UrbanCost + WWRedCost
Worksheets("Results - N Reductions & Costs").Select
Cells(41, a) = BMP1Cost
Cells(42, a) = BMP2Cost
Cells(43, a) = BMP3Cost
Cells(44, a) = BMP4Cost
Cells(45, a) = BMP5Cost
Cells(46, a) = BMP6Cost
Cells(47, a) = BMP7Cost
Cells(48, a) = StreamCost
Cells(49, a) = AgriCost
Cells(52, a) = UrbanDBCost
Cells(53, a) = UrbanCWCost
Cells(54, a) = UrbanVBSCost
Cells(55, a) = UrbanCost
Cells(58, a) = SepticCost
Cells(59, a) = UpGradPT2ST
Cells(60, a) = UpGradPT2TT
Cells(61, a) = UpGradST2TT
Cells(62, a) = UpGradSep2TT
Cells(63, a) = WWRedCost
Cells(65, a) = TotalCost
Cum_BMP1Cost = Cum_BMP1Cost + BMP1Cost
Cum_BMP2Cost = Cum_BMP2Cost + BMP2Cost
Cum_BMP3Cost = Cum_BMP3Cost + BMP3Cost
Cum_BMP4Cost = Cum_BMP4Cost + BMP4Cost
Cum_BMP5Cost = Cum_BMP5Cost + BMP5Cost
Cum_BMP6Cost = Cum_BMP6Cost + BMP6Cost
Cum_BMP7Cost = Cum_BMP7Cost + BMP7Cost
Cum_StreamCost = Cum_StreamCost + StreamCost
D-15
Cum_AgriCost = Cum_AgriCost + AgriCost
Cum_UrbanDBCost = Cum_UrbanDBCost + UrbanDBCost
Cum_UrbanCWCost = Cum_UrbanCWCost + UrbanCWCost
Cum_UrbanVBSCost = Cum_UrbanVBSCost + UrbanVBSCost
Cum_UrbanCost = Cum_UrbanCost + UrbanCost
Cum_SepticCost = Cum_SepticCost + SepticCost
Cum_UpGradPT2ST = Cum_UpGradPT2ST + UpGradPT2ST
Cum_UpGradPT2TT = Cum_UpGradPT2TT + UpGradPT2TT
Cum_UpGradST2TT = Cum_UpGradST2TT + UpGradST2TT
Cum_UpGradSep2TT = Cum_UpGradSep2TT + UpGradSep2TT
Cum_WWRedCost = Cum_WWRedCost + WWRedCost
Cum_TotalCost = Cum_TotalCost + TotalCost
Next i
Cells(41, 2) = Cum_BMP1Cost
Cells(42, 2) = Cum_BMP2Cost
Cells(43, 2) = Cum_BMP3Cost
Cells(44, 2) = Cum_BMP4Cost
Cells(45, 2) = Cum_BMP5Cost
Cells(46, 2) = Cum_BMP6Cost
Cells(47, 2) = Cum_BMP7Cost
Cells(48, 2) = Cum_StreamCost
Cells(49, 2) = Cum_AgriCost
Cells(52, 2) = Cum_UrbanDBCost
Cells(53, 2) = Cum_UrbanCWCost
Cells(54, 2) = Cum_UrbanVBSCost
Cells(55, 2) = Cum_UrbanCost
Cells(58, 2) = Cum_SepticCost
Cells(59, 2) = Cum_UpGradPT2ST
Cells(60, 2) = Cum_UpGradPT2TT
Cells(61, 2) = Cum_UpGradST2TT
Cells(62, 2) = Cum_UpGradSep2TT
Cells(63, 2) = Cum_WWRedCost
Cells(65, 2) = Cum_TotalCost
End Sub
D-16
EXECUTION
Sub PredictRun()
Dim a As Integer
Dim b As Integer
Dim nwatersheds As Integer 'Number of Watersheds
' Dim WSName As Characters 'Watershed Name
Dim RCLoad(1 To 100) 'TN Load from Row Crop
Dim HPLoad(1 To 100) 'TN Load from Hay Pasture
Dim HDULoad(1 To 100) 'TN Load from High Density Urban
Dim LDULoad(1 To 100) 'TN Load from Low Density Urban
Dim OLoad(1 To 100) 'TN Load from Other Sources
Dim SELoad(1 To 100) 'TN Load from Streambank Erosion
Dim GSLoad(1 To 100) 'TN Load from Groundwater/Subsurface
Dim PSLoad(1 To 100) 'TN Load from Point Source Discharges
Dim SSLoad(1 To 100) 'TN Load from Septic Systems
Dim TotLoad(1 To 100) 'Total Basin TN Load
Dim FNLoadRC(1 To 100) 'Future N Load from Row Crop
Dim FNLoadHP(1 To 100) 'Future N Load from Hay Pasture
Dim FNLoadHDU(1 To 100) 'Future N Load from High Density Urban (HDU)
Dim FNLoadLDU(1 To 100) 'Future N Load from Low Density Urban (LDU)
Dim FNLoadO(1 To 100) 'Future N Load from Other Sources
Dim FNLoadSE(1 To 100) 'Future N Load from Streambank Erosion
Dim FNLoadGW(1 To 100) 'Future N Load from Groundwater/Subsurface
Dim FNLoadPS(1 To 100) 'Future N Load from Point Source Discharges
Dim FNLoadSS(1 To 100) 'Future N Load from Septic Systems
Dim FNLoadTot(1 To 100) 'Future N Load Total (Basin)
Dim BMP1 As Single 'BMP 1 (Permanent Vegetative Cover) % TN Removal
Dim BMP2 As Single 'BMP 2 (Strip Cropping & Contour Farming)% TN Removal
Dim BMP3 As Single 'BMP 3 (Cropland Protection) % TN Removal
Dim BMP4 As Single 'BMP 4 (Conservation Tillage) % TN Removal
Dim BMP5 As Single 'BMP 5 (Terraces & Diversions) % TN Removal
Dim BMP6 As Single 'BMP 6 (Nutrient Managment) % TN Removal
Dim BMP7 As Single 'BMP 7 (Grazing Land Management) % TN Removal
Dim VBS As Single 'Vegetated Buffer Strips (VBS) % TN Removal
Dim SF As Single 'Streambank Fencing % TN Removal
Dim SS As Single 'Streambank Stabilization % TN Removal
Dim CW As Single 'Constructed Wetlands % TN Removal
Dim DB As Single 'Detention Basins % TN Removal
Dim BMP1RC As Single 'BMP1 Row Crop % Area Application
Dim BMP2RC As Single 'BMP2 Row Crop % Area Application
Dim BMP3RC As Single 'BMP3 Row Crop % Area Application
Dim BMP4RC As Single 'BMP4 Row Crop % Area Application
Dim BMP5RC As Single 'BMP5 Row Crop % Area Application
Dim BMP5HP As Single 'BMP5 Hay Pasture % Area Application
Dim BMP6RC As Single 'BMP6 Row Crop % Area Application
Dim BMP6HP As Single 'BMP6 Hay Pasture % Area Application
Dim BMP7HP As Single 'BMP7 Hay Pasture % Area Application
Dim VBSA As Single 'VBS (Agric.) % Stream Length Application
Dim VBSHDU As Single 'VBS (HDU) % Stream Length Application
D-17
Dim VBSLDU As Single 'VBS (LDU) % Stream Length Application
Dim SFA As Single 'Streambank Fencing (Agric.) % Stream Length Appl.
Dim SSA As Single 'Streambank Stabilization (Agric.) % Stream Length Appl.
Dim CWHDU As Single 'Constructed Wetlands (HDU) % Area Application
Dim CWLDU As Single 'Constructed Wetlands (LDU) % Area Application
Dim DBLDU As Single 'Detention Basins (LDU) % Area Application
Dim DBHDU As Single 'Detention Basins (HDU) % Area Application
Dim RBMP6RC As Single 'TN Reduction by BMP6 Row Crop
Dim LRBMP6RC As Single 'TN Remaining from Row Crop after BMP6
Dim RBMP1RC As Single 'TN Reduction by BMP1 Row Crop
Dim RBMP2RC As Single 'TN Reduction by BMP2 Row Crop
Dim RBMP3RC As Single 'TN Reduction by BMP3 Row Crop
Dim RBMP4RC As Single 'TN Reduction by BMP4 Row Crop
Dim RBMP5RC As Single 'TN Reduction by BMP5 Row Crop
Dim LRBMP16RC As Single 'TN Remaining from Row Crop after BMP 1-6
Dim RVBSA As Single 'TN Reduction by VBS (Agricultural)
Dim RBMP6HP As Single 'TN Reduction by BMP6 Hay Pasture
Dim LRBMP6HP As Single 'TN Remaining from Hay Pasture after BMP6
Dim RBMP5HP As Single 'TN Reduction by BMP5 Hay Pasture
Dim RBMP7HP As Single 'TN Reduction by BMP7 Hay Pasture
'delete Dim TotBMPArea As Single
Dim RCWHDU As Single 'TN Reduction by Constructed Wetlands in HDU Areas
Dim RCWLDU As Single 'TN Reduction by Constructed Wetlands in LDU Areas
Dim RDBHDU As Single 'TN Reduction by Detention Basins in HDU Areas
Dim RDHLDU As Single 'TN Reduction by Detention Basins in LDU Areas
Dim RVBSHDU As Single 'Further Reduction in TN HDU Load by VBS
Dim RVBSLDU As Single 'Further Reduction in TN LDU Load by VBS
Dim HDUC1 As Single 'TN Remaining from HDU Areas after Urban BMPs (CW, DB)
Dim LDUC1 As Single 'TN Remaining from LDU Areas after Urban BMPs (CW, DB)
Dim SepticPeopleN As Integer 'Number of Persons on Septic Systems (Normal)
Dim SepticPeopleSC As Integer 'Number of Persons on Septic Systems (Short-Circuiting)
Dim SewerPeople As Integer 'Number of Persons on Public Sewers
Dim SepticFutureN As Integer 'Future Number of Persons on Septic Systems (Normal)
Dim SepticFutureSC As Integer 'Future Number of Persons on Septic Systems (Short-Circuiting)
Dim SewerFuture As Integer 'Future Number of Persons on Public Sewers
Dim SEP2ST As Single 'Septic Systems Converted to Secondary Treatment
Dim Sep2TT As Single 'Septic Systems Converted to Tertiary Treatment
Dim SStoSWTP As Single 'Septic System Conversion to Secondary Treatment (# People)
Dim SStoTWTP As Single 'Septic System Conversion to Tertiary Treatment (# People)
Dim PRILoad1 As Single 'TN Load from Primary Wastewater Treatment Plants
Dim SECLoad1 As Single 'TN Load from Secondary Wastewater Treatment Plants
Dim TERLoad1 As Single 'TN Load from Tertiary Wastewater Treatment Plants
Dim Primary As Single 'Percent TN Point Source Load from Primary WWTPs
Dim Secondary As Single 'Percent TN Point Source Load from Secondary WWTPs
Dim Tertiary As Single 'Percent TN Point Source Load from Tertiary WWTPs
Dim LoadPT2ST As Single 'TN Load Reduction from Primary to Secondary Treatment Upgrade
Dim LoadPT2TT As Single 'TN Load Reduction from Primary to Tertiary Treatment Upgrade
Dim LoadST2TT As Single 'TN Load Reduction from Secondary to Tertiary Treatment Upgrade
Dim PT2ST As Single 'Primary Wastewater Upgraded to Secondary Treatment (%)
Dim PT2TT As Single 'Primary Wastewater Upgraded to Tertiary Treatment (%)
Dim ST2TT As Single 'Secondary Wastewater Upgraded to Tertiary Treatment (%)
Dim CoefSS2ST As Single 'TN Removal from Septic System to Secondary Treatment Upgrade (%)
D-18
Dim CoefSS2TT As Single 'TN Removal from Septic System to Tertiary Treatment Upgrade (%)
Dim CoefPT2ST As Single 'TN Removal from Primary to Secondary Treatment Upgrade (%)
Dim CoefPT2TT As Single 'TN Removal from Primary to Tertiary Treatment Upgrade (%)
Dim CoefST2TT As Single 'TN Removal from Secondary to Tertiary Treatment Upgrade (%)
'Read Inputs from "AVGWLF Results" and "Percent Removals" worksheets
'The variable a must be changed depending on what watershed you're working on.
Worksheets("Input - BMP Appl. & Unit Costs").Select
nwatersheds = Cells(1, 2)
For i = 1 To nwatersheds
Worksheets("Input - BMP Appl. & Unit Costs").Select
n = Cells(2, 2 + i)
WSName = Cells(3, 2 + i)
a = 2 + i
b = 2 + n
' Windows("Predict_Spreadsheet").Activate
Worksheets("AVGWLF Results").Select
RCLoad(i) = Cells(2, b)
HPLoad(i) = Cells(3, b)
HDULoad(i) = Cells(4, b)
LDULoad(i) = Cells(5, b)
OLoad(i) = Cells(6, b)
SELoad(i) = Cells(7, b)
GSLoad(i) = Cells(8, b)
PSLoad(i) = Cells(9, b)
SSLoad(i) = Cells(10, b)
TotLoad(i) = Cells(11, b)
RCArea = Cells(12, b)
HPArea = Cells(13, b)
HDUArea = Cells(14, b)
LDUArea = Cells(15, b)
TotArea = Cells(16, b)
ALOS = Cells(18, b)
SLA = Cells(19, b)
SLHDU = Cells(20, b)
SLLDU = Cells(21, b)
SLTot = Cells(22, b)
SepticPeopleN = Cells(25, b)
SepticPeopleSC = Cells(26, b)
SewerPeople = Cells(27, b)
Worksheets("Input - BMP Appl. & Unit Costs").Select
BMP1 = Cells(6, 2)
BMP2 = Cells(7, 2)
BMP3 = Cells(8, 2)
BMP4 = Cells(9, 2)
BMP5 = Cells(10, 2)
BMP6 = Cells(11, 2)
BMP7 = Cells(15, 2)
VBS = Cells(17, 2)
SF = Cells(26, 2)
SS = Cells(27, 2)
CW = Cells(18, 2)
DB = Cells(53, 2)
D-19
BMP1RC = Cells(6, a)
BMP2RC = Cells(7, a)
BMP3RC = Cells(8, a)
BMP4RC = Cells(9, a)
BMP5RC = Cells(10, a)
BMP6RC = Cells(11, a)
BMP5HP = Cells(13, a)
BMP6HP = Cells(14, a)
BMP7HP = Cells(15, a)
VBSLDU = Cells(17, a)
CWLDU = Cells(18, a)
DBLDU = Cells(19, a)
VBSHDU = Cells(21, a)
CWHDU = Cells(22, a)
DBHDU = Cells(23, a)
VBSA = Cells(25, a)
SFA = Cells(26, a)
SSA = Cells(27, a)
' Cells(18, 4) = SepticPeopleN
' Cells(18, 5) = SepticPeopleSC
' Cells(20, 4) = SewerPeople
SepticFutureN = Cells(33, a)
SepticFutureSC = Cells(36, a)
SewerFuture = Cells(39, a)
SEP2ST = (Cells(41, a)) / 100
Sep2TT = (Cells(42, a)) / 100
Primary = (Cells(44, a)) / 100
Secondary = (Cells(45, a)) / 100
Tertiary = (Cells(46, a)) / 100
PT2ST = (Cells(48, a)) / 100
PT2TT = (Cells(49, a)) / 100
ST2TT = (Cells(50, a)) / 100
CoefSS2ST = Cells(41, 2)
CoefSS2TT = Cells(42, 2)
CoefPT2ST = Cells(48, 2)
CoefPT2TT = Cells(49, 2)
CoefST2TT = Cells(50, 2)
'Calculations for reductions from Row Crop (from eqs on page 22 PRedICT Manual)
'Calculation is performed by considering application of BMP 6 (Nutrient Management)
'to a percentage of TN Load from Row Crop.
RBMP6RC = ((BMP6RC / 100) * RCLoad(i)) * (BMP6 / 100)
LRBMP6RC = RCLoad(i) - RBMP6RC
'Additional reductions in TN Load from BMP 1-5 is then computed for the remaining
'TN Load. (NOTE: Summation of %Reductions from BMP 1-5 can not exceed 100%.)
RBMP1RC = ((BMP1RC / 100) * LRBMP6RC) * (BMP1 / 100)
D-20
RBMP2RC = ((BMP2RC / 100) * LRBMP6RC) * (BMP2 / 100)
RBMP3RC = ((BMP3RC / 100) * LRBMP6RC) * (BMP3 / 100)
RBMP4RC = ((BMP4RC / 100) * LRBMP6RC) * (BMP4 / 100)
RBMP5RC = ((BMP5RC / 100) * LRBMP6RC) * (BMP5 / 100)
LRBMP16RC = LRBMP6RC - (RBMP1RC + RBMP2RC + RBMP3RC + RBMP4RC + RBMP5RC)
'Additional reductions in TN Load from Vegetated Buffer Strips is then computed
'for the remaining TN Load.
RVBSA = (VBSA / 100) * LRBMP16RC * (VBS / 100)
FNLoadRC(i) = LRBMP16RC - RVBSA
'Calculations of reductions from Hay Pasture (from eqs on page 23 of PRedICT Manual)
'Calculation is performed by considering application of BMP 6 (Nutrient Management)
'to a percentage of TN Load from Hay Pasture.
RBMP6HP = ((BMP6HP / 100) * HPLoad(i)) * (BMP6 / 100)
LRBMP6HP = HPLoad(i) - RBMP6HP
'Additional reductions in TN Load from BMP 5 and 7 is then computed for the remaining
'TN Load. (NOTE: Summation of %Reductions from BMP 5 and 7 can not exceed 100%.)
RBMP5HP = ((BMP5HP / 100) * LRBMP6HP) * (BMP5 / 100)
RBMP7HP = ((BMP7HP / 100) * LRBMP6HP) * (BMP7 / 100)
FNLoadHP(i) = LRBMP6HP - (RBMP5HP + RBMP7HP)
'Calculations of reductions from Streambank Erosion by Streambank Fencing and Stabilization
'(from eqs on page 23 of PRedICT Manual)
FNLoadSE(i) = SELoad(i) - (((SFA / 100) * SELoad(i)) * (SF / 100))
FNLoadSE(i) = FNLoadSE(i) + (((SSA / 100) * SELoad(i)) * (SS / 100))
'Calculations of Groundwater Load Adjustments (from eqs on page 25-28 of PRedICT Manual)
'Calculations include increases in GW Loads due to applications of BMP 1-5 and
' descreases in GW Loads due to applications of BMP 6 (Nutrient Management and
' vegetated buffer strips.
'Calculations as presented in the PRedICT Manual were modifiied to account GW load
' increases from BMP 1-5 as a portion of the Total (and not Row Crop + Hay Pasture)
' Area. Also, the PRedICT equation was modified/corrected to decrease GW load
' as a portion of the Total (and not the Row Crop) Area. Finally, adjustment
' factors for BMP 6 and Vegetated Buffer Strips, as given in Table 8 on page 26
' of the PRedICT Manual, are not consistent with values given in the formulas.
' The values given in the formulas and in the note (i.e., adjustment factors of
' 0.5 and 0.4 for vegetated buffer strips and BMP 6 (nutrient management), respectively
' are assumed to be correct.
FNLoadGW(i) = GSLoad(i) + 0.08 * ((BMP1RC / 100) * RCArea) / TotArea * GSLoad(i)
FNLoadGW(i) = FNLoadGW(i) + 0.08 * ((BMP2RC / 100) * RCArea) / TotArea * GSLoad(i)
FNLoadGW(i) = FNLoadGW(i) + 0.04 * ((BMP3RC / 100) * RCArea) / TotArea * GSLoad(i)
FNLoadGW(i) = FNLoadGW(i) + 0.06 * ((BMP4RC / 100) * RCArea) / TotArea * GSLoad(i)
FNLoadGW(i) = FNLoadGW(i) + 0.1 * (((BMP5RC / 100) * RCArea) + ((BMP5HP / 100) * HPArea)) / TotArea
* GSLoad(i)
D-21
FNLoadGW(i) = FNLoadGW(i) - 0.4 * (((BMP6RC / 100) * RCArea) + ((BMP6HP / 100) * HPArea)) / TotArea
* GSLoad(i)
FNLoadGW(i) = FNLoadGW(i) - 0.5 * ((VBSA / 100) * SLA) / SLTot * GSLoad(i)
'Calculations of Urban Load Reductions (from eqs on page 29 of PRedICT Manual)
'Constructed Wetlands Load Reductions
RCWHDU = ((CWHDU / 100) * HDULoad(i)) * (CW / 100)
RCWLDU = ((CWLDU / 100) * LDULoad(i)) * (CW / 100)
'Detention Basins Load Reductions
RDBHDU = ((DBHDU / 100) * HDULoad(i)) * (DB / 100)
RDBLDU = ((DBLDU / 100) * LDULoad(i)) * (DB / 100)
'Remaining High Density Urban and Low Density Urban Loads
HDUC1 = HDULoad(i) - (RCWHDU + RDBHDU)
LDUC1 = LDULoad(i) - (RCWLDU + RDBLDU)
'Further Reductions from Urban Areas by Vegetated Buffer Strips
RVBSHDU = ((VBSHDU / 100) * HDUC1) * (VBS / 100)
RVBSLDU = ((VBSLDU / 100) * LDUC1) * (VBS / 100)
FNLoadHDU(i) = HDUC1 - RVBSHDU
FNLoadLDU(i) = LDUC1 - RVBSLDU
'Calculations of Wastewater Reductions (from page 31-35 of PRedICT Manual)
'For TN Load increases or decreases from Septic Systems, no distinction is
' made between normal and short-circuiting septic systems. Therefore,
' calculations are performed using total number of people on septic systems.
SepticPeople = SeptecPeopleN + SepticPeopleSC
SepticFuture = SeptecFutureN + SepticFutureSC
If (SepticFuture) > (SepticPeople) Then
FNLoadSS(i) = ((SepticFuture / SepticPeople)) * SSLoad(i)
Else
SStoSWTP = (1 - (SepticFuture / SepticPeople)) * SSLoad(i) * SEP2ST
SStoTWTP = (1 - (SepticFuture / SepticPeople)) * SSLoad(i) * Sep2TT
FNLoadSS(i) = SSLoad(i) - (SStoSWTP + SStoTWTP)
End If
'Initial TN Point Source Loads Based on Wastewater Treatment Plant Type
PRILoad1 = PSLoad(i) * Primary
SECLoad1 = PSLoad(i) * Secondary
TERLoad1 = PSLoad(i) * Tertiary
'Future TN Reductions based on Treatment Plant Upgrades
LoadPT2ST = PRILoad1 * PT2ST
LoadPT2TT = PRILoad1 * PT2TT
LoadST2TT = SECLoad1 * ST2TT
'Final Point Source Load Based on Septic System Conversions & Treatment Upgrades
FNLoadPS(i) = (PRILoad1 - (LoadPT2ST + LoadPT2TT))
D-22
FNLoadPS(i) = FNLoadPS(i) + SECLoad1 + (LoadPT2ST * (1 - CoefPT2ST))
FNLoadPS(i) = FNLoadPS(i) + (SStoSWTP * (1 - CoefSS2ST)) - LoadST2TT
FNLoadPS(i) = FNLoadPS(i) + TERLoad1 + (LoadPT2TT * (1 - CoefPT2TT))
FNLoadPS(i) = FNLoadPS(i) + (LoadST2TT * (1 - CoefST2TT))
FNLoadPS(i) = FNLoadPS(i) + (SStoTWTP * (1 - CoefSS2TT))
'Final TN Load
FNLoadTot(i) = FNLoadRC(i) + FNLoadHP(i) + FNLoadHDU(i) + FNLoadLDU(i)
FNLoadTot(i) = FNLoadTot(i) + OLoad(i) + FNLoadSE(i) + FNLoadGW(i)
FNLoadTot(i) = FNLoadTot(i) + FNLoadPS(i) + FNLoadSS(i)
'Output
Worksheets("Results - N Reductions & Costs").Select
Cells(2, a) = WSName
Cells(4, a) = RCLoad(i)
Cells(5, a) = HPLoad(i)
Cells(6, a) = HDULoad(i)
Cells(7, a) = LDULoad(i)
Cells(8, a) = OLoad(i)
Cells(9, a) = SELoad(i)
Cells(10, a) = GSLoad(i)
Cells(11, a) = PSLoad(i)
Cells(12, a) = SSLoad(i)
Cells(13, a) = TotLoad(i)
Cells(16, a) = FNLoadRC(i)
Cells(17, a) = FNLoadHP(i)
Cells(18, a) = FNLoadHDU(i)
Cells(19, a) = FNLoadLDU(i)
Cells(20, a) = OLoad(i)
Cells(21, a) = FNLoadSE(i)
Cells(22, a) = FNLoadGW(i)
Cells(23, a) = FNLoadPS(i)
Cells(24, a) = FNLoadSS(i)
Cells(25, a) = FNLoadTot(i)
Cells(28, a) = (1 - FNLoadRC(i) / RCLoad(i)) * 100
Cells(29, a) = (1 - FNLoadHP(i) / HPLoad(i)) * 100
Cells(30, a) = (1 - FNLoadHDU(i) / HDULoad(i)) * 100
Cells(31, a) = (1 - FNLoadLDU(i) / LDULoad(i)) * 100
Cells(32, a) = (1 - OLoad(i) / OLoad(i)) * 100
Cells(33, a) = (1 - FNLoadSE(i) / SELoad(i)) * 100
Cells(34, a) = (1 - FNLoadGW(i) / GSLoad(i)) * 100
If (PSLoad(i) > 0) Then Cells(35, a) = (1 - FNLoadPS(i) / PSLoad(i)) * 100
If (SSLoad(i) > 0) Then Cells(36, a) = (1 - FNLoadSS(i) / SSLoad(i)) * 100
Cells(37, a) = (1 - FNLoadTot(i) / TotLoad(i)) * 100
Cum_RCLoad = Cum_RCLoad + RCLoad(i)
Cum_HPLoad = Cum_HPLoad + HPLoad(i)
Cum_HDULoad = Cum_HDULoad + HDULoad(i)
Cum_LDULoad = Cum_LDULoad + LDULoad(i)
Cum_OLoad = Cum_OLoad + OLoad(i)
Cum_SELoad = Cum_SELoad + SELoad(i)
Cum_GSLoad = Cum_GSLoad + GSLoad(i)
Cum_PSLoad = Cum_PSLoad + PSLoad(i)
D-23
Cum_SSLoad = Cum_SSLoad + SSLoad(i)
Cum_TotLoad = Cum_TotLoad + TotLoad(i)
Cum_FNLoadRC = Cum_FNLoadRC + FNLoadRC(i)
Cum_FNLoadHP = Cum_FNLoadHP + FNLoadHP(i)
Cum_FNLoadHDU = Cum_FNLoadHDU + FNLoadHDU(i)
Cum_FNLoadLDU = Cum_FNLoadLDU + FNLoadLDU(i)
Cum_OLoad = Cum_OLoad + OLoad(i)
Cum_FNLoadSE = Cum_FNLoadSE + FNLoadSE(i)
Cum_FNLoadGW = Cum_FNLoadGW + FNLoadGW(i)
Cum_FNLoadPS = Cum_FNLoadPS + FNLoadPS(i)
Cum_FNLoadSS = Cum_FNLoadSS + FNLoadSS(i)
Cum_FNLoadTot = Cum_FNLoadTot + FNLoadTot(i)
Next i
Cells(4, 2) = Cum_RCLoad
Cells(5, 2) = Cum_HPLoad
Cells(6, 2) = Cum_HDULoad
Cells(7, 2) = Cum_LDULoad
Cells(8, 2) = Cum_OLoad
Cells(9, 2) = Cum_SELoad
Cells(10, 2) = Cum_GSLoad
Cells(11, 2) = Cum_PSLoad
Cells(12, 2) = Cum_SSLoad
Cells(13, 2) = Cum_TotLoad
Cells(16, 2) = Cum_FNLoadRC
Cells(17, 2) = Cum_FNLoadHP
Cells(18, 2) = Cum_FNLoadHDU
Cells(19, 2) = Cum_FNLoadLDU
Cells(20, 2) = Cum_OLoad
Cells(21, 2) = Cum_FNLoadSE
Cells(22, 2) = Cum_FNLoadGW
Cells(23, 2) = Cum_FNLoadPS
Cells(24, 2) = Cum_FNLoadSS
Cells(25, 2) = Cum_FNLoadTot
Cells(28, 2) = (1 - Cum_FNLoadRC / Cum_RCLoad) * 100
Cells(29, 2) = (1 - Cum_FNLoadHP / Cum_HPLoad) * 100
Cells(30, 2) = (1 - Cum_FNLoadHDU / Cum_HDULoad) * 100
Cells(31, 2) = (1 - Cum_FNLoadLDU / Cum_LDULoad) * 100
Cells(32, 2) = (1 - Cum_OLoad / Cum_OLoad) * 100
Cells(33, 2) = (1 - Cum_FNLoadSE / Cum_SELoad) * 100
Cells(34, 2) = (1 - Cum_FNLoadGW / Cum_GSLoad) * 100
If (Cum_PSLoad > 0) Then Cells(35, 2) = (1 - Cum_FNLoadPS / Cum_PSLoad) * 100
If (Cum_SSLoad > 0) Then Cells(36, 2) = (1 - Cum_FNLoadSS / Cum_SSLoad) * 100
Cells(37, 2) = (1 - Cum_FNLoadTot / Cum_TotLoad) * 100
Cells(1, 1).Select
End Sub