Nutrient and Sediment Estimation Tools for Watershed Protection
September 25, 2017
This document does not confer legal rights or impose legal obligations on any member of the public. The
EPA has made every effort to ensure the accuracy of the technical information in this document.
Depending on individual circumstances, the general information and descriptions provided here may not
apply to a given situation. Decision makers retain the discretion to adopt approaches on a case-by-case
basis that differ from the approaches described in this document.
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Nutrient and Sediment Estimation Tool for Watershed Protection
Introduction
Nutrient and sediment pollution affects many of our local streams, lakes and can lead to adverse impacts
such as algal blooms, fish kills, and dead zones. Given the growing importance of managing nutrient and
sediment pollution there is interest in tools that can help estimate and track nutrient losses as well as
provide decision support for policy or investment options. The purpose of this document is to identify and
catalog many of the tools that are currently in use to estimate nitrogen, phosphorus, and sediment losses
and to identify the uses for which these tools are most appropriate. Estimation tools can vary widely in
terms of the land uses to which they are applicable, the scale at which they can estimate losses, the data
requirements, and the sophistication of their estimates. Deciding which tool is appropriate for a given
project will depend largely on the purpose of the project and understand llie iradcoffs of data and level
effort vs. accuracy.
Nutrient and sediment loss estimation tools have been applied to help manage and H ack nutrients and/or
provide decision support for policymakers and investors: examples include:
Watershed Scale Planning - Watershed scale tools vary in their capability of assessing the
effectiveness of multiple best management praclices or agricultural conservation practices
(BMPs). The size of the watershed will drive the need lor accuracy, and higher or lower data
needs and level of effort to operate the tool may van
Scenario Building - Scenario building refers to process of identifying one or multiple sets of
BMPs to achieve a desired load reduction. This can occur at llie field or watershed scale.
Consider a tool capable of estimating a wide range of BMPs llml has sufficient accuracy to
meaningfully compare one scenario against the oilier
Water Quality Trading and Other Market-based Programs These programs involve
financial payment to landowners in return for a load reduction outcome; tools to support these
programs are at the field scale and should be capable of routing flow through BMPs and
calculating reduction estimates from a wide range of BMPs at high levels of accuracy. This
implies that higher data needs and level of effort to operate the tool may be justified.
Targeting Targeting BMPs that offer the largest load reductions and/or most cost effective load
reductions will guide implemenlalion to the lands most in need of treatment. Scenario building
lools arc best suiled in appropruilcly target BMPs.
Tracking and Reporting Reporting results, to programs and/or the public, requires tracking
and reporting the cumulali ve load reductions from implementation over variable time scales at the
watershed scale, tracking tools are estimators and the outputs do not necessarily require
watershed allributcs as inputs.
This document provides a framework for comparing models in terms of scale, sophistication, sector
applicability and ability to model best management practices (BMPs) that reduce nutrient losses. This
document also provides model descriptions for each of the models in the comparison table (Table 1).
Please note the list of estimation tools discussed in this document is not exhaustive, nor are the
comparison criteria used in the comparison table (Table 1).
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Nutrient and Sediment Estimation Tool for Watershed Protection
Models for Estimating Nutrient Loads and Load Reductions
Table 1, below, provides a comparison of many of the models currently in use for estimating nutrient
loads and load reductions. Comparison categories include:
Field or Watershed: identifies whether the tool is suited to field-scale or watershed-scale estimates. Field
scale estimates typically estimate loads at the edge of a farm field or urban segment prior to then entering
the waterbody. Watershed scale estimates typically estimate loads that enter the waterbody and flow
within in the stream or river.
Land Use Urban or Rural: identifies the type of land use to which the lool is applicable.
Pollutant: indicates which pollutant(s) that the tool is able to estimate. Some lools estimate other loads as
well but are not listed.
Event or Continuous: describes the duration of time that the model estimates. When using event-based
models (e.g., for simulating individual representative storms during the year), the user mu\ w ish to
extrapolate results (e.g., either by summing the results of all simulated events, or multipK ing the results
of the representative storm by the average number of occurrences) in arrive at a monthly or annual total
load reductions. The preferred approach for monthly or annual loads would be to use a tool identified as
continuous, meaning it uses hourly or daily simulation that is then summarized within the tool itself.
BMP: identifies at a cursory level if the tool is able in simulate a comprehensive, moderate, or simple list
of best management practices (BMPs). The tools can usualK estimate loads reductions from one BMP
(e.g., a cover crop on a farm field, or stormwater retention on a parking lot) or multiple BMPs.
Data Needs: provides a general i/.ed eslimale the amount of dala llial is needed to provision the tool (high,
medium or low).
Level of Effort provides a general eslimale of die overall level of effort and sophistication required to
operate the tool
Table 1. Comparison of mode
s lor estimating nutrient loads anc
load reductions
Model
Field or
\\ iilershed
Land Use
U rban or
Rural
Pollutant1
Event or
Continuous
BMP2
Data
Needs3
Level of
Effort4
Simple
CAST
1 !olh
Both
P, N, S
Event
O
O
O
LTHIA
1 >olh
Both
N, P, S
Event
O
o
NCANAT
Field
Rural
N, P, S
Event
O
o
o
Region 5
Field
Both
P, N, S
Event
o
o
o
SELDM
Both
Urban
N, P
Event
o
o
o
Simple Method
Watershed
Urban
N, P
Event
o
o
o
STEPL
Both
Both
P, N, S
Event
o
o c
o c
Mid-Range
AGNPS
Both
Rural
N, P, S
Both
o
o
APEX
Field
Rural
N, P, S
Continuous
c
EPIC
Field
Rural
N, P, S
Continuous
c
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Nutrient and Sediment Estimation Tool for Watershed Protection
Model
Field or
Watershed
Land Use
Urban or
Rural
Pollutant1
Event or
Continuous
BMP2
Data
Needs3
Level of
Effort4
GWLF
Watershed
Both
N, P, S
Both
O
O C
o c
MapShed
Watershed
Both
N, P, S
Both
O
o c
o c
NTT
Field
Rural
N, P, S
Continuous
c
c
c
WARMF
Watershed
Both
N, P, S
Continuous
c
c
Detailed/Complex
AGWA
Both
Both
N, P, S
Both
o
o
o
GLEAMS
Field
Rural
N, P, S
Both
o
o
HSPF
Both
Both
N, P, S
Both
o
o
KINEROS2
Both
Both
S
Event
c
LSPC
Both
Both
N, P, S
Continuous
o
o
Opti-Tool
Watershed
Urban
N, P, S
Both
o
o
o
P8-UCM
Watershed
Urban
N, P, S
Continuous
©
c
PRMS
Watershed
Both
S
Both
i
o
REMM5
Field
Rural
N, P, S
Continuous
RZWQM2
Field
Rural
N
Event
f
o
SPARROW
Watershed
Both
N, P, S
Continuous
o
c
SUSTAIN
Watershed
Urban
N, P, S
Both
SWAT
Both
Rural
V P. s
Both
c
c
SWMM
Both
Urban
N. P. S
Both
f
c
o
TBET
Field
Rural
N. P. S
Both
f
c
c
WEPP
Both
Rural
S
Continuous
o
o
Modeling Systems
BASINS
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Nutrient and Sediment Estimation Tool for Watershed Protection
Simple Models
CAST. The Chesapeake Assessment and Scenario Tool (CAST) is a web-based nitrogen, phosphorus and
sediment load estimator tool that streamlines environmental planning. CAST was originally developed in
2011 with funding provided by the EPA, to provide local jurisdictions with a tool to provide input into the
Chesapeake Bay TMDL watershed implementation process. The Chesapeake Bay Program released an
update in 2017 to reflect the conversion to the Phase 6 Chesapeake Bay watershed model (Chesapeake
Bay Program 2017). The tool requires the user to specify a geographic area (such as a county), and then
select BMPs to apply on that area, with options for urban, septic, forest, agriculture, animals, and manure
transport. The estimated cost of BMPs is also provided by the tool, so users max select the most cost-
effective practices to reduce pollutant loads. The user may alternatively pro\ ide their own estimated cost
data. CAST builds the scenario and provides estimates of nitrogen, phosphorus, and sediment load
reductions from all sectors and sources, acres of each BMP. and costs for ihe scenario. These loads are
consistent with the Chesapeake Bay Program's Watershed Model. Users can create their own scenarios to
develop an implementation strategy, calculate loading reductions and costs, or compare and modify
existing scenarios to customize a watershed implementation analysis. CAST is five in ihe public and can
be accessed at http://cast.chesapeakebav.net/.
A variation of this tool allows users to define the boundaries ol'a parcel and the land use areas within that
parcel, called the Chesapeake Bay Facility Assessment Scenario Tool (BavFAST).
(http://www.bavfast.org'). There is also a Virginia-specific tool called. Virginia Assessment Scenario Tool
(VAST - www¦vasttool.org') that is merged with CAST. The Mar\ land Scenario Assessment Tool
(MAST) is the Maryland-specific version of CAST (:=;;; Eg). MAST has some
Maryland-specific geographies available through the interface and also has loads available for historical
years to assist with local TMDL watershed planning.
L-THIA. The Long Term Hydrologic Impact Analysis (L-THIA) model, developed by Purdue
University, is a quick and accessible tool to estimate runoff, recharge, and nonpoint source (NPS)
pollution resulting from past or proposed land use changes. L-THIA is available in three forms: L-THIA
WWW, a spreadsheet version that models runoff and NPS pollution changes; ArcL-THIA, a set of
Avenue scripts that automate the process of runoff impact modeling within ArcGIS (Park et al. 2013); and
L-THIA GTS WWW. a form of L-THIA CIS that allows interactive mapping of an area of interest with a
custom Java uilciface within a web browser (Lim et al 1999). L-THIA produces long-term average annual
runoff, and associated nitrogen, phosphorus and suspended sediment loads (as well as bacteria and
metals) lor a given land use configuration based on long-term climate data for that area. Due to the use of
long-term dala. L-THIA focuses on average impact as opposed to a specific storm or an extreme year.
Model inputs include location dala, land use data, hydrologic soil groups, and land area. The model also
produces graphical and tabular representations of output data to assist in the interpretation of results and
to compare outpuls from several runs to determine the best possible land use scenario. More information
about L-THIA and L-1111 \ \\ WW can be found: https://en.gineering.purdue.edu/~lthia/. ArcL-THIA can
be downloaded from: igineering.purdiie.edu/mapserve/LTHIA7/arclthia/.
NCANAT. The North Carolina Nutrient Assessment Tool is a North Carolina-specific model that
contains two agricultural field-scale tools, a Nitrogen Loss Estimation Worksheet (NLEW) and
Phosphorus Loss Assessment Tool (PLAT). NCANAT was developed by North Carolina State University
in collaboration with the North Carolina Department of Agriculture & Consumer Services, North Carolina
Department of Environment and Natura Resources, and US Department of Agriculture (USDA) - Natural
Resources Conservation Service (The N.C. PLAT Committee 2005). The agricultural nitrogen accounting
tool, NLEW, uses a modified N-balance equation that accounts for nitrogen inputs and nitrogen
reductions from nutrient management and BMPs. NLEW works at the field and county-level scales.
PLAT is a mechanistic model that estimates potential loss of phosphorus from a field by considering
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Nutrient and Sediment Estimation Tool for Watershed Protection
particulate phosphorus, dissolved phosphorus, leachate phosphorus, and phosphorus source effects on
phosphorus loss. The model allows you to run each tool independently or together. Inputs include crop
and field information, BMP types, nutrient application rate, soil data, drainage information, and
hydrologic conditions. The outputs are phosphorus indexed ratings for each of the four loss pathways
expressed verbally and numerically, total phosphorus rating, and total nitrogen loss for the various BMP
scenarios. To find more information and download the model, visit:
http://nutrients.soil.ncsu.edu/software/ncanat/
Region 5 Model. Region 5 Model (MDEQ 1999) is an Excel workbook that provides a gross estimate of
sediment and nutrient load reductions from the implementation of agricultural and urban BMPs. The
algorithms for non-urban BMPs are based on the "Pollutants controlled: Calculation and documentation
for Sectic /atersheds training manual". The algorithms for urban BMPs arc based on the data and
calculations developed by Illinois EPA. A recent version of the Region 5 model estimates the flow
volume captured and treated by urban stormwater controls (infiltration practices) and adds the
functionality of estimating baseline load based on the annual rainfall and event mean concentration in the
surface runoff. The Region 5 model is available to the public at http://it.tetrateel 'steplweb.
SELDM. The Stochastic Empirical Loading and Dilution Model (SELDM), an update lu the FHWA
Pollutant Loading Model for Highway Stormwater Runoff, was de\ eloped jointly by IJSGS and Federal
Highway Administration (FHWA) in 2013 (Granato 2013). The new model incorporates the existing
model in a new software platform and calculates the risk of exceeding water quality criteria with and
without defined BMPs. SELDM calculates annual runoff loads and can run simple annual lake-loading
analyses. The model provides information on the probability distribulions of ihc following: precipitation
characteristics, highway runoff volumes, highwa\ runoff concentrations, upslream flow, upstream
receiving-water concentrations, and structural BMP performance Through USGS, national data sets are
available for users to choose the most representative data for their site to use in the model. The available
data includes highwav-runoff qualih. precipitation, streamflow. runoff coefficients, and background
water quality. The most recent version includes a different formula to calculate exceedance percentiles.
More information is available on the USGS site:
https://webdmamrl.er.usgs.gov/gl/ggranato/Software/seldm.html
Simple Method. The Simple Method (Schucler 11>N7) is an empirical approach developed for estimating
pollutant export from urban and developing areas. It is used at the site-planning level to predict pollutant
loadings under a variety of de\ elopment scenarios. This method is best used for a development site,
watershed or subwatershed and w hen data availability is limited, as it requires a modest amount of
information The inputs include drainage area, pollutant concentrations, a runoff coefficient, which uses
impervious co\ er (.lata, and precipitation data. Pollutant concentrations of phosphorus, nitrogen, chemical
oxygen demand, biochemical owgen demand, and metals are calculated from flow-weighted
concentration values for new suburban areas, older urban areas, central business districts, hardwood
forests, and urban highwa\ s The method relies on the National Urban Runoff Program (NURP) data for
default values. Information on The Simple Method can be found at the following web locations.
https://www.des.nh.gov/organization/divisions/water/stormwater/documen.ts/wd-08-20a ch8.pdf or
https://www.hvdrocad.net/pdf/NY-Simple-Method.pdf
STEPL. Spreadsheet Tool for Estimating Pollutant Load (STEPL) employs simple algorithms to
calculate nutrient and sediment loads from different land uses and the load reductions that would result
from the implementation of various BMPs (Tetra Tech 2011). STEPL provides a user-friendly Visual
Basic (VB) interface to create a customized spreadsheet-based model in Microsoft (MS) Excel. It
computes watershed surface runoff; nutrient loads, including nitrogen, phosphorus, and 5-day biological
oxygen demand (B0D5); and sediment delivery based on various land uses and management practices.
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Nutrient and Sediment Estimation Tool for Watershed Protection
For each watershed, the annual nutrient loading is calculated based on the runoff volume and the pollutant
concentrations in the runoff water as influenced by factors such as the land use distribution and
management practices. The annual sediment load (sheet and rill erosion only) is calculated based on the
Universal Soil Loss Equation (USLE) and the sediment delivery ratio. The sediment and pollutant load
reductions that result from the implementation of BMPs are computed using the known BMP efficiencies.
The STEPL package is available to the public at http://it.tetratech-ffx.com/steplweb.
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Nutrient and Sediment Estimation Tool for Watershed Protection
Mid-Range Models
AGNPS. Agricultural Non-Point Source Pollution Model (AGNPS) (Young 1989), developed by the
USDA Agricultural Research Service (ARS), is designed to estimate loads from agricultural watersheds
and to assess the relative effects of alternative management programs. The term "AGNPS" no longer
refers to the single event AGNPS of the mid-1990's, but now refers to the system of modeling
components. The model simulates surface water runoff along with nutrient (nitrogen, phosphorus, and
organic carbon) and sediment constituents associated with agricultural nonpoint sources, as well as point
sources such as feedlots, wastewater treatment plants, and streambank or gully erosion.
Several versions that integrate the model with geographic information s\ sicm (G1S) and Windows-based
graphical user interfaces are available. For instance, the Annualized AGNPS (Ann AGNPS) is a
continuous-simulation, multi-event modification of the single-event model AGNPS, which can be used to
estimate annualized loads and load reductions (Binger, Theurer and Yuan 2d 15) AnnAGNPS versions
5.0 and later incorporate enhanced features for many input and output options including ephemeral
gullies, automated calibration for pollutants, actual or potential evapotranspiration climate files, and the
ability to enter unlimited climate stations with any naming convention. AnnAGNPS also now has the
capabilities of the revised universal soil loss equation (Rl SI.E). an erosion model that evaluates the
degree of soil erosion caused by rainfall and associated (norland llow and which is often used as a
regulatory and conservation planning tool. Additionally, the capability of importing RUSLE2 databases
into AnnAGNPS is now available. RUSLE2 is the advanced erosion model that extends the basic USLE
structure but with a more user-friendly interface and that uses more ph> sicallv meaningful input values
that are widely available and easily obtained
AnnAGNPS can now run more comprehensn e e\ alualions of si ream s\ stems in regard to channel
evolution, erosion, or in-stream structures with the integration of a channel network evolution model,
CCHE1D, and a stream corridor model. ( ONCEPTS. The most recent version of AnnAGNPS also
includes an updated output processor. I-'or more information, visit
https: //www ,nrcs.usda.g( s/detailful l/null/?cid=s 1.042468
APEX. The Agricultural Polic\ I in\ iron menial eXlender (APEX) model (Gassman et al., 2010) was
developed by the Blackland Research and l\lension Center in Temple, Texas
("http://epicapex.iamu ) The API X model is a flexible and dynamic tool that can perform long-
term simulations to addresses the impacts of management on environmental and production issues for
whole farms and small watersheds The modeling framework can evaluate a wide array of management
strategies applied to crop, paslure. and grazing lands and estimates long-term sustainability of land
management with respect to erosion due to water and wind, economics, water supply, water quality, soil
quality, plant competition, weather and pests for crop land as well as grazing and pasture land.
Management capabilities simulated include: irrigation; surface and subsurface drainage; furrow diking;
buffer strips; terraces, waterways; windbreaks; fertilization and manure management, lagoons and water
retention reservoirs, crop selection and rotation; fertilizer, nutrient and pesticide fate and application;
grazing management; tillage timing and intensity; and harvest timing and methods. Furthermore, APEX
can address strategic implications of global climate/CCh changes; confined animal feeding facilities,
production systems for bioenergy; and other spin off applications.
APEX's unique feature is the ability to subdivide farms or fields by soil type, landscape position, surface
hydrology or management configuration represent crop diversity and landscape characteristics within a
field or farm. Each subarea may be linked with each other according to the water routing direction in the
farm or watershed, starting from the most distant subarea towards the watershed outlet. Several APEX
interfaces and tools have been developed to support the development of APEX application such as
iAPEX, ArcGIS APEX, WinAPEX-GIS, and SWAT-APEX. A brief description of these tools can be
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Nutrient and Sediment Estimation Tool for Watershed Protection
found in Gassman et al., 2010. The APEX model can be downloaded from
http://epicapex.tamu.edii/model-executables/.
EPIC. The Erosion Productivity Impact Calculator (EPIC) is a field-scale continuous simulation model
that assesses the effects of soil erosion on agricultural productivity and water quality (Sharpley and
Williams 1990). It can predict the effects of management decisions on soil, water, nutrient, and pesticide
movements and their combined impacts on soil loss, water quality, and crop yields for areas of
homogeneous soils and management. The model includes two options of estimating the peak runoff rate -
the modified rational formula and the SCS TR-55 method. The EPIC wind erosion model, WECS (Wind
Erosion Continuous Simulation), is used to calculate wind characteristics, including erosion due to wind.
The model simulates several contamination processes including denitrification. mineralization, nitrate
losses, organic nitrogen transport, nitrification, soluble phosphorus loss in surface runoff, and mineral
phosphorus cycling. All forms of phosphorus can be differentiated within llie model. EPIC has been
improved over the years through additions of algorithms to simulate w ater qualih. nitrogen and carbon
cycling, climate change, and the effects of atmospheric carbon dioxide. The model can be configured for a
wide range of crop rotations and other vegetative systems, tillage systems, and oilier management
practices. The model can also assess the cost of erosion for determining optimal management strategies. A
copy of EPIC can be obtained from httpV/epicapex.t'.;:.'-.. ¦=: ;nodel~6xeeu tables/.
GWLF. The Generalized Watershed Loading Functions (GWLF) model was developed at Cornell
University to assess the point and nonpoint loadings of nitrogen and phosphorus from a relatively large,
agricultural and urban watershed and evaluate the effectiveness of ccriain land use management practices
(Haith and Shoemaker. 1997). One advantage of this model is that it was w rillen with the express purpose of
requiring no calibration, making extensive use of defaull parameters. The (iW I F model includes
rainfall/runoff and erosion and sediment generation componenls. lotal and dissolved nitrogen and
phosphorus loadings, and septic system loads and point source discharge data. The simulation results can be
used to identify and rank pollution sources and evaluate basin-w ide management programs and land use
changes. The model also includes se\ eral reporting and graphical representations of simulation output to aid
in interpretation of the refills For more information, download the document from this link
http ://cwam .ucdavis.e iWLF.pdf.
Versions that iniegrale llie model with GIS and Windows-based graphical user interfaces are available.
BasinSIM 1.0 is a model lliat was de\ eloped at the Virginia Institute of Marine Science, College of William
and Mary (http:// -.edu/bio _..a/bsabout.html). which predicts sediment and nutrient loads for
small lo mid-sized watersheds using the GWLF. a graphic Windows interface, and extensive databases. An
in-stream routing and sedimenl iransport component in BasinSIM 1.0 employs the algorithms in
AnnAGNPS lo simulate sedimenl iransport.
MapShed. Penns\ l\ ania State I m versity developed a GIS-based tool that incorporates GWLF and
enhances the functional il\ using a free GIS software package called MapWindow (Evans and Corradini
2016). MapShed replaces AVGWLF, which used proprietary ArcView software. Moving the tool to a free
GIS platform makes it more accessible to a larger number of users. MapShed has enhanced capabilities,
such as improved simulation of pollutant transport processes in urban settings, improved assessment of the
effects of BMPs on pollutant load reduction, and the inclusion of streambank erosion, agricultural tile
drainage routines. The tool automatically derives values for the required model input parameters for the
watershed model. Through the interface the user can also access regional climate data to create weather data
for a given watershed simulation. The latest version of MapShed includes more direct simulation of loads
from farm animals and a new pathogen load estimation. MapShed also includes the GWLF-e model, which
uses the algorithms previously included in PRedlCT to evaluate the implementation of both rural and
urban pollution reduction strategies at the watershed level. GWLF-e compares point and nonpoint
pollution loads between scenarios of current and "future" conditions. Future scenarios could include
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Nutrient and Sediment Estimation Tool for Watershed Protection
different pollution reduction strategies, stream protection activities, septic system conversions to
centralized wastewater treatment, and treatment plant upgrades. For more information, visit
http ://www. mapshed .psu .edu/index.htm.
MapShed is scheduled to be phased out by late 2018 and replaced by a web-based platform called Model
My Watershed, which is a component of a larger application called Wikiwatershed. More information on
these tools can be found at wikiwatershed.org.
NTT. The Nutrient Tracking Tool is a farm-scale tool developed by the Texas Institute of Applied
Environmental Research (TIAER) at Tarleton State University in collaboration with USDA-NRCS (Saleh
et al., 2011 and 2015). NTT is a user-friendly web-based platform to access llie underlying APEX
(Agricultural Policy Environmental extender) tool, which is a process-based model that uses soil, weather
and management information to estimate on farm losses of sediment, nitrogen and phosphorus, through
leaching and runoff, and to predict yields on cropland and pasture. APEX is described in more detail
elsewhere within this document. NTT was designed to be accessible to the t\ pica I fanner and features a
user-friendly interface and simplified inputs. The NTT interface allows users to delineate their field(s)
using an interactive map for any location in the mainland U.S. and Puerto Rico. The interactive map
captures the soils, slope, and weather specific to the selected area. The user can enter field management
characteristics, including crop schedule, planting and har\ esliny dales, grazing operations,
fertilizer/manure operations and tillage operations. The user m;i\ also indicate one or more conservation
practices present on the field, including tile drains, irrigation, buffers. etc. In addition, there are many
conservation practices that arc represented as part of the field management information entered by the
user, e.g. tillage, nutrient management and cover crops. NTT allows llie user lo enter multiple
management scenarios for any field and compare losses between the baseline and conservation
management scenarios. Users may choose to run fields indiv idualK. or simulate routing by linking the
fields. The estimated losses arc the result of a 30+ year simulation o\ er historic weather and thus
represent the average annual losses for the field given the crop rotation and management practices.
Simulation results can be viewed as monthly averages or annual averages. The model can be accessed at
http://nn.tarleton.edu
WARMF. The Watershed Anal\ sis Risk Management Framework was developed by Systech Water
Resources lo support a watershed approach to simulating hvdrologic, physical, chemical and biological
processes lo help users understand llieir watershed (Svstech Engineering 2001). The model has agraphic
user interlace making il user-friendl\ Land uses are represented at the catchment scale and multiple land
uses, including urban and agricultural l> pes. can be represented as a percentage of each catchment; point
and non-point sources are represented spatially; and the user defines the routing through the watershed.
Watershed ph\ Meal processes can he simulated on a one minute up to a daily time step. Water volume and
approximateh 4<) water qualil\ parameters, including pH, metals, pesticides, nutrients, turbidity, algae,
bacteria and mercuiy bioaccumulalion. are simulated. WARMF can represent land use, river segments,
canopy, bed sediment, and up lo five soil layers. CE-QUAL-W2 was added to WARMF to include 2D
reservoir modeling. The TMDL module allows users to define target criteria and WARMF to calculate the
point and non-point source loading reductions and whether criteria are met. Multiple allocation scenarios
can be run and displayed in the Consensus module, which presents the modeled data in a format suitable for
technical and non-technical stakeholders. More information and a copy of the WARMF can be obtained at
http://svstechwater.com/warmf software/.
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Nutrient and Sediment Estimation Tool for Watershed Protection
Complex Models
AGWA. Automated Geospatial Watershed Assessment (AGWA), developed by the USDA-ARS
Southwest Watershed Research Center, in cooperation with the EPA Landscape Ecology Branch, is
designed to automate the transformation of spatial datasets into model input files for either KINEROS2 or
SWAT and evaluate the model results (USDA, USEPA, University of Wyoming, n.d.). AGWA is a GIS-
based system that can be used as an event-oriented or continuous daily time step model, depending on
which watershed runoff and erosion simulation model the user chooses. AGWA is useful as a research
tool for hydraulic modeling, but can also be used as a watershed assessment tool using hydraulic response
as the metric of change. The effects of land use change can be assessed 111 small watershed to basin-scale
studies, if multiple land cover data sets are available. AGWA can generale allernative future land-
use/cover scenarios and display differences between simulation outputs designed to provide decision
support when combined with planning efforts. AGWA docs require a large set of GIS data and assumes
the user has previously compiled the necessary GIS data layers. An AGWA Tools extension is available
for ArcGIS and ArcView. AGWA 3.x utilizes new features in ArcGIS 10.x that are nol a\ aikible in
ArcView 3.x. More information can be found here: https://www.epa.gov/water-rese nated-
geospatial-watershed-assessment-agwa-tool-hydrologic-modeling-and-watershed.
GLEAMS. Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) is a
continuous simulation, field scale model, which was developed as an extension of the Chemicals, Runoff
and Erosion from Agricultural Management Systems (CREAMS) model (Leonard et al. 1987). GLEAMS
can be used to estimate surface runoff, sediment, nutrient, and pesticide losses from the field (e.g., edge-
of-field) and nutrient leaching within, through and below the root zone. GI.LAMS can provide estimates
of the impact of management systems, such as planting dales, cropping systems, irrigation scheduling,
and tillage operations, on the potential for chemical movement. Application rates, methods, and timing
can be altered to account for these systems and to reduce the possibility of root zone leaching. The model
also accounts for varying soils and weather in determining leaching potential. Erosion in overland flow
areas is estimated using a modified Universal Soil Loss Equation (USLE). GLEAMS was not developed
with the intention to be an absolute predictor of pollutant loading; it is a tool for comparative analysis of
complex pesticide chemistry, soil properties, and climate. More information can be found at:
https:" " )lains-area/temple-tx/grassland-soil-and-water-research-
labor ¦ and http://www.tifton.uga.edu/sewrl/Gleams/gleams v2k update .Mm.
HSPI-". The Hydrological Simulation Program-FORTRAN (HSPF) is a comprehensive package
developed b\ Aqua Terra Consul Lints for EPA and USGS for simulating water quantity and quality for a
wide range of organic and inorganic pollutants from complex watersheds to receiving waters (Bicknell et
al. 2001). It is a coni|nehensi\ e model of watershed hydrology and water quality that allows the
integrated simulalion of land and soil contaminant runoff processes with in-stream hydraulic and
sediment-chemical mleiaclions. The model uses continuous simulations of water balance, pollutant
generation, transformation, and transport and incorporates the watershed-scale Agricultural Runoff
Management Model (ARM) and Nonpoint Source Runoff Model (NPS) model. HSPF uses such
information as the time series of rainfall, temperature, evaporation, and parameters related to land use
patterns, soil characteristics, and agricultural practices to simulate watershed processes. Runoff flow rate,
sediment loads, nutrients, pesticides, toxic chemicals, and other quality constituent concentrations can be
predicted. The model uses these results and stream channel information to simulate instream processes.
HSPF contains three application modules that simulate the hydrologic/hydraulic and water components of
the watershed. One capability of the modules is the routing of phosphorus. PERLND, IMPLND, and
RCHRES work together to model phosphorus behavior and balances along overland flow, interflow,
groundwater flow, urban areas, and through stream channel networks and reservoirs. HSPF is one of the
supported models of the EPA Better Assessment Science for Point and Nonpoint Sources, BASINS
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Nutrient and Sediment Estimation Tool for Watershed Protection
system and the Window-based HSPF model (WinHSPF) can be downloaded from the BASINS Web site
at https://www.epa.gov/exposiire-assessment-models/basins.
In addition, web-based HSPF tools were developed to extend the model's application to urban watersheds
with sewer system networks and to areas with flow-modifying BMPs, such as detention basins. The
Green Tool represents infiltration-based stormwater control practices while the Gray Tool represents
sewer networks and storage-based stormwater control structures. The toolkit can be used in low impact
development (LID) modeling applications. More information about HSPF can be found at:
https://www.epa.gov/exposure-assessment-models/lispf.
KINEROS2. Kinematic Runoff and Erosion Model 2 (KINER0S2) is an e\ enl-oriented, physically-
based model that describes the processes of interception, infiltration, surface runoff, and erosion from
small agricultural and urban watersheds (Woolhiser et al. 1990). The model allows for pipe flow and pond
elements, as well as infiltrating surfaces and includes a partially paved element lor use in urban area
simulation. The model can be used to determine the effects of urban devclopmeni. small detention
reservoirs or lined channels on flood hydrographs and sediment yield. Both splash erosion and hydraulic
erosion are simulated and soil and sediment can be distributed into up to five particle si/.e classes. New
features in KINER0S2 include an infiltration algorithm that handles a two-layer soil profile and
incorporates anew method to redistribute soil water during rainfall interruptions. A detention pond model
is also included in the new features and incorporates seepage through the wetted area, rainfall on the pond
itself, and initial storage. The open channel algorithm in the model has been extended to allow a
compound cross section where one section can differ in parameters from the other. Time varying inflow
from external sources can also be included in llie model system classes The model is available from
http://www.tucson.ars.ag.gov/kineros/.
LSPC. Loading Simulation Program in C++ (LSPC) is a watershed modeling system that includes
streamlined Hydrologic Simulation Program FORTRAN (HSPF) algorithms for simulating hydrology,
sediment, and general water quality on land, as well as a simplified stream transport model (Tetra Tech
2009). Land processes for pervious and impervious areas are simulated through water budget, sediment
generation and transport, and water quality constituent generation and transport. Sediment production is
based on detachment and/or scour from a soil matrix and transport by overland flow in pervious areas.
Solids buildup and washoff is simulated for impervious areas. LSPC does not simulate BMPs explicitly;
however, the essential functions of BMPs (such as detention, infiltration, and evapotranspiration losses),
can be represented in LSPC through se pa rale configuration of land and intermediate channel routing
segmenls More information can lie found al
https://cti 3v/si/si pi record Keport.cfm?dirEntrvId=75860&C -884508&CFTQKEN
=982I o obtain the model executable files and source codes, contact the EPA lead Tim Wool at
wool.tim@et
Opti-Tool. Stormwater Nutrient Management Optimization Tool (Opti-Tool), developed by Tetra Tech
for EPA Region 1, is a spreadsheet-based tool that provides both a planning level and an implementation
level analysis to assist stormwater managers in developing technically sound and economically feasible
management plans to address stormwater impacts and reduce excessive nutrient loadings (Tetra Tech
2016). The planning level analysis uses BMP performance curves and Excel Solver to identify an optimal
solution. The implementation level analysis calls the SUSTAIN (System for Urban Stormwater Treatment
and Analysis Integration) dynamic link library to estimate BMP performance and retrieve optimization
results to provide cost-effective BMP sizing strategies.
Opti-Tool consists of a Microsoft-Excel platform and external EPA SUSTAIN BMP process and
optimization modules. The user interacts with the Excel platform for data input, and can direct Excel to
call the SUSTAIN module to estimate BMP performance and provide optimization at a given assessment
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Nutrient and Sediment Estimation Tool for Watershed Protection
point in the watershed. The user-friendly tool provides the ability to evaluate options for determining the
best mix of structural BMPs in a particular geographic area to achieve quantitative water resource goals.
The tool incorporates long-term runoff responses (Hydrologic Response Unit (HRU) time series) for
regional climate conditions that are calibrated to regional monitored stormwater data and annual average
load export rates from 9 major land uses. Also, the tool includes regionally representative BMP cost
functions and regionally calibrated BMP performance parameters for 4 pollutants including total
phosphorus and total nitrogen to calculate long-term cumulative load reductions for a variety of structural
controls (Tetra Tech, 2010). Structural controls simulated by the tool include LID and green infrastructure
(GI) practices such as infiltration systems, biofiltration and gravel wetlands.
Opti-Tool is designed to provide a flexible and yet consistent platform for local decision-makers and
stormwater practitioners to develop and implement technically sound and robust nutrient management
plans capable of demonstrating accountable progress and compliance wilh permit requirements based on
TMDLs that include stormwater impacts and excessive nutrient loadings. The default data used in the tool
is customized for New England region, but the data can easily be updated to use lor any other location
outside the New England region. The Opti-Tool package is available to the public al
https://www.epa.gov/npdes-permits/massachusetts-small-ms4-general-permit.
P8-UCM. Program for Predicting Polluting Particle Passage through Pits. Puddles, and Ponds - Urban
Catchment Model (P8-UCM) predicts the generation and transport of stormwater pollutants in urban
watersheds (Walker and Walker 2015). Continuous water balance and mass balance calculations are
performed on a user-defined system consisting of ualershcds. treatment devices (such as runoff storage,
treatment areas, and BMPs), particle classes, and water quality components. Simulations are driven by
continuous hourly rainfall and daily air temperature lime series data. The model simulates pollutant
transport and removal in a variety of treatment devices (BMPs). including swales, buffer strips, detention
ponds, flow splitters, and infiltration basins, pipes and aquifers. Water quality components include total
suspended solids, broken into five si/.e classes, total phosphorus, total Kjeldahl nitrogen, copper, lead,
zinc and hydrocarbons. Version 3 5 has been updated to be compatible with Excel versions up to 2013
and Windows 7, 8 or 10. This version also supports the conversion of temperature and precipitation files
from Excel formats. This model is available from http://www.wwwalker.net/p8/.
PRMS. The Precipitation-Runoff Modeling System is a modular-design, deterministic, distributed-
parameter, physical-process watershed model that was developed to evaluate the effects of various
comb inal mns of precipitation, climate, and land use on watershed response (Leavesley et al. 2005).
Each watershed is divided into hulrologicallv homogeneous units, based on slope, aspect, elevation,
vegetation, soils and precipitation distribution. These units are known as hydrologic response units
(HRUs). The response from all I IRUs is summed to develop the system response and streamflow.
Watershed response can be simulated at both a daily and a storm time scale. Response to normal and
extreme rainfall and snowmell can be simulated to evaluate changes in water-balance relations, flow
regimes, flood peaks and \ oluines, soil-water relations, sediment yields, and ground-water recharge. PRMS
was redesigned and is now a component of the USGS Modular Modeling System (MMS), which has a GIS
interface. Version 4.0.3 was released in June 2017. A copy of the model can be obtained from
https://wwwbrr.cr.usgs.gov/proiects/SW MoWS/PRMS.htrol.
REMM. Riparian Ecosystem Management Model (REMM) is a tool to quantify the water quality benefits
of riparian buffers (Lowrance et al. 2000). REMM simulates movement and water storage in a process-
based two-dimensional water balance. The model simulates the movement of surface and subsurface water,
sediment transport and deposition, nutrient transport, sequestration and cycling, and vegetative growth in
riparian forest systems on a daily timestep. Each riparian system is comprised of three zones between the
field and the waterbody. The zones consist of undisturbed forest, managed forest, and runoff control.
Together the three zones include litter, three soil layers, and a plant community with six plant types in two
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Nutrient and Sediment Estimation Tool for Watershed Protection
canopy levels. REMM can be used to quantify nitrogen and phosphorus trapping in the riparian buffer
zone, to determine buffer effectiveness, to investigate the long-term fate of nutrients in the buffer zones,
to evaluate the influence of vegetation type on buffer effectiveness, and to determine the impacts of
harvesting on buffer effectiveness. Future modifications include aims to adequately represent variations in
riparian slope shape - convergence/divergence, spatial variation in streambank flooding, as well as to
include an ArcView interface to incorporate the spatial variability. REMM can be downloaded at:
http://www.tifton.uga.edu/remmwww/.
RZWQM2. The Root Zone Water Quality Model, developed by the USDA Agricultural Research
Service, is a one-dimensional (vertical in the soil profile) process-based model that simulates the growth
of the plant and the movement of water, nutrients and pesticides over, wiilun and below the crop root
zone within an agricultural cropping area ( ^WQM webs:Q. R/WOV12 (Ma et al. 2012) is the
revised and enhanced version of the model, which was developed to include ihe DSSAT 4.0 Cropping
System Models with the cooperation of the University of Georgia and DSSAT modeling group.
RZWQM2 has a quasi-two-dimensional macro pore/lateral flow component. The primary function of the
model is to assess the effects of alternative agricultural management strategies on mi rate and pesticide
loading to groundwater, and by extension the nonpoint source runoff loading to surface waters. Tile
drainage can be simulated. Alternative management strategies in the model include eonserx alion plans,
tillage and residue practices, crop rotation, planting data and densil\. and irrigation, fertilizer and
pesticide application, amount and timing. Six sub-processors represent physical processes (hydraulic,
infiltration, chemical transport during infiltration and runoff, soil heal flow, etc.), plant growth processes
(carbon dioxide assimilation, carbon allocation, dark respiration, morlalily. root growth, etc.), soil
chemical processes (soil pH, solution concernralions of ions, and adsorbed cations on the exchange
complex), nutrient processes ( carbon and nitrogen transformation - mineralization, nitrification,
immobilization, denitrification and volatilization), pesticide processes (pesticide fate, transformation,
degradation, etc.) and management processes (tillage practices and the impacts on surface roughness, soil
bulk density; fertilizer, pesticide and manure applications: crop planting, irrigation schedules and BMP
algorithms for dynamic nitrogen-rate determination). The Generic Crop Growth model is parameterized
to simulate corn, soybean and wheat fields, however, users may parameterize their own generic crop. The
DSSAT Cropping System Models simulate growth and development of 23 crop species with many
varieties each. Frozen soil dynamics are not represented. A copy of the model can be obtained from
https://www.ars.iisda.gov/plaitis-area/fort-colliiii snter-for-agricultural-resources-research/rangeland-
resou rce s-svstem s -re search/docs/svstem/rzwq m/.
SPARROW . SPAtiallv Referenced Regression On Watershed attributes (SPARROW) is an empirical,
rcgrcssion-lxised model using mass balance calculations to relate in-stream water quality measurements to
spatially referenced characteristics of watersheds (Smith et al. 1997). Riverine pollutant loading rate
predictions can lie made for sediment, nutrients and other contaminants. Pollutants can be simulated at
different spatial scales, depending on the level of detail in the datasets, and different temporal scales,
either annually or for a user-defined modeling period. National level datasets such as RF1 (stream reach
file), NLCD (USGS land use. land cover) and STATSGO (NRCS soil data) can be used. Estimates of
pollutant loads and fate/transport characteristics are somewhat coarse due to the use of national and
regional water quality datasets to develop the statistical relationship between stream processes and the
model outputs. More information can be found here: https://water.usgs.gov/nawqa/sparrow/.
SUSTAIN. System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) is a decision
support system to facilitate selection and placement of BMPs and LID techniques at strategic locations in
urban watersheds (Shoemaker, et. al., 2009). Tetra Tech designed and developed the tool for the EPA,
Office of Research and Development (ORD). SUSTAIN was designed for use by watershed and
stormwater practitioners to develop, evaluate, and select optimal BMP combinations at various watershed
scales on the basis of cost and effectiveness at protecting source waters and meeting water quality goals.
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Nutrient and Sediment Estimation Tool for Watershed Protection
SUSTAIN is a tool for answering the following questions: (1) How effective are BMPs in reducing runoff
and pollutant loadings? (2) What are the most cost-effective solutions for meeting objectives? and (3)
Where, what type, and how big should BMPs be?
Various practitioners, municipalities, and watershed groups at the regional and local levels can use
SUSTAIN to address a variety of stormwater management planning questions on: (1) developing TMDL
implementation plans, (2) identifying management practices to achieve pollutant reductions in an area
under an MS4 stormwater permit, (3) determining upstream source control strategies for reducing volume
and peak flows to CSO systems, and (4) evaluating the benefits of distributed BMP implementation on
water quantity and quality in urban streams. SUSTAIN has seven key components: framework manager
with ArcGIS 9.3 interfaces, BMP siting tool, land module, BMP module, conveyance module,
optimization module, and post-processor. They are integrated under a common ArcGIS platform.
SUSTAIN supports evaluation of BMP placement at multiple scales from a low city blocks to large
watersheds. SUSTAIN provides a public domain tool that incorporates the be si available research that
could be practically applied to decision making including the tested algorithms from SWMM, HSPF, and
other BMP modeling techniques. Linking those methods into a seamless system pro\ ides a balance
between computational complexity and practical problem solving. The modular approach used in
SUSTAIN facilitates updates as new solutions become available. The software and the lechmcal reports
(Shoemaker, et. al., 2009, 2012, and 2013) are available for download at: http://www.ee /water-
research/svstern~urban~stormwater~treatment~and~analvsis~irt°f"~'t;"r'-sustain.
SWAT. The Soil and Water Assessment Tool (SWAT) is a mer ba>m or watershed scale model that can
be used to predict the impact of land management practices on water, sediment and agricultural chemical
yields in complex watersheds with varying soils, land use and managemenl conditions over long periods
of time (Neitsch etal. 2011). The model is continuous, plnsically-based. and requires specific
information about weather, soil properties, topography, v egelalion. and land management practices
occurring in the watershed. The physical processes associated with water movement, sediment
movement, crop growth, nutrient cycling, etc. are directly modeled by SWAT using this input data. The
model offers many agricultural BMPs and practices, but limited urban BMPs. Current urban BMPs
include detention basins, infiltration practices, vegetative filter strips, street sweeping, and wetlands.
SWAT is one of the supported models of EPA BASINS 4.1 system. The model can be downloaded at
http: //swat m ode 1. tarn ii.edu.
SWMM. The EPA Storm Water Management Model (SWMM) is a comprehensive watershed model
which is w idelv used for anal\ sis of water quality and quantity problems related to stormwater runoff,
combined sewers, sanitary sewers, and other drainage systems in urban areas, with many applications in
non-urban areas as well, including floodplain hydraulics and analysis (Rossman 2015). SWMM simulates
hydrographs and pollulographs (concentration vs. time) at any point in the drainage system. Rainfall/runoff
simulation is accomplished b\ ihe nonlinear reservoir approach. The lumped storage scheme is applied for
soil/groundwater modeling. For impervious areas, a linear formulation is used to compute daily/hourly
increases in particle accumulation. For pervious areas, a modified USLE determines sediment load.
SWMM can be used to e\ aluate the effectiveness of BMPs for reducing wet weather pollutant loadings,
reduction in dry-weather buildup due to street cleaning, reduction in constituent concentration through
treatment in storage units or by natural processes in pipes and channels, and designing control strategies for
minimizing combined sewer overflows. SWMM is available for download at: htips://www.epa.gov/water-
research/storm~water~roanageroent~roodel~swmro. The updated model allows engineers and planners to
accurately represent any combination of LID controls within an area to evaluate their effectiveness in
regard to stormwater and combined sewer overflow management.
TBET. Texas Best Management Practice Evaluation Tool (TBET) is a simplified graphic user interface
for SWAT and developed for field-scale application in Texas (White and Harmel 2012). TBET is an
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Nutrient and Sediment Estimation Tool for Watershed Protection
input/output interpreter that uses a simpler version of SWAT that predicts mean annual runoff, sediment,
nitrogen, and phosphorus losses from agricultural fields under various agricultural BMP scenarios and
conservation practices. Each farm is limited to 10 fields, and each field is limited to 3 soil types. Internal
databases account for local climate, soils, topography, and management. The most recent version of the
tool can be downloaded: https://nlet.brc.tamus.edu/Home/Other. More information can be found:
https://nlet.brc.tamus.edu/data/Other/Users%20Man.ual.pdf.
WEPP. The Watershed Erosion Prediction Project (WEPP) is a process-based, distributed parameter,
continuous simulation model that can be used to estimate soil erosion and sediment delivery from
hillslope profiles, as well as for simulation of the hydrologic and erosion processes on small watersheds
(USDA Agricultural Research Service 1995). Processes considered in hi I Islope profile model applications
include rill and inter-rill erosion, sediment transport and deposition, infillmlion. soil consolidation,
residue and canopy effects on soil decomposition, percolation, evaporation, iranspiration, snow melt,
frozen soil effects on infiltration and erodibility, climate, tillage effects on soil properties, effects of soil
random roughness, and contour effects including potential overtopping of contour ndges. In watershed
applications, the model allows linkage of hillslope profiles to channels and impoundments. The latest
version of the WEPP model including a Windows version and related utilities (e.g.. climate generator) can
be downloaded from http://www.ars.usda.gov/Research/docs.htm?docid= 10621. Simpler and w eb-based
versions of the WEPP model mainly targeted for specific BM Ps in lorests arc also available on the Web
site. Version 2012.8 of the model includes updates such as new channel routing code, water balance
updates involving tile drainage, additional frozen soil hydraulic conductivity factors, and fixed model
bugs.
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Nutrient and Sediment Estimation Tool for Watershed Protection
Watershed Modeling Systems
BASINS. Better Assessment Science Integrating point and Nonpoint Sources (BASINS) is a
multipurpose environmental analysis system designed for watershed and water quality-based studies.
BASINS works with a GIS framework and consists of: (1) national databases; (2) assessment tools; (3) a
watershed delineation tool; (4) classification utilities; (5) characterization reports; (6) watershed loading
and transport models HSPF and SWAT; (7) a simplified GIS-based model (PLOAD) that estimates
annual average nonpoint source pollutant loads; (8) the Automated Geospatial Watershed Assessment
(AGWA) tool, a GIS-based hydrologic modeling tool; and (9) the Parameter Estimation (PEST) tool for
model calibration. BASINS has the flexibility to perform simple watershed-level screening analysis or
detailed water quality modeling. Unlike previous versions, BASINS 4 <) runs on non-proprietary, open
source GIS system architecture. However, v4.0 does not include linkages in AGWA and SWAT models.
Versions 3.1 and 4.0 can coexist in the same folder and still function pioperK. BASINS version 4.1 is
built upon the latest stable version of the open-source MapWindow GIS. The interface of BASINS 4.1
has changed from BASINS 4.0, however, the functions remain the same. BASINS 4 I also includes
updated watershed delineation tools that use version 5 of Terrain Analysis Using Digilal Elevation Model
(TauDEM) from Utah State University. The newest version of BASINS also uses DI'I.OW. a tool to
estimate design stream flows for use in water quality studies. The latest version of BASINS can be
downloaded from https://www.epa.gov/exposure-assessment-models/basins.
TMDL Modeling Toolbox. The TMDL Modeling Toolbox is a collection of models, tools and databases
used in the development of Total Maximum Daily Loads (TMDLs). The Toolbox provides the capability
to more readily integrate watershed loading models with receiving water applications. Although each
model is a stand-alone application, the Toolbox provides an exchange of information between the models
through common linkages. Models and tools included in the Toolbox arc the Gray Tool, the Green Tool,
Desktop HDFT, HDFT Web Version, and HSPF. More information about the Toolbox can be found at:
https://www.epa. """ ' 0/documents/toolbox-ovemew.pdf. The Toolbox can
be accessed at liti ssment-models/tmdl-models-and-tools.
Solocliii" ;i lool for your needs
Since all eslimalion inn Is are indeed estimates. you should emphasize this when talking to the public or
your stakeholders and pim ide an explanalion why having such estimates is better than not having them.
Also. \ nu or your organi/alinn shnukl decide up front, before projects are implemented, how to later
assess whelher projects are implemented as intended, and ways to measure or monitor their actual
effectiveness in comparison In w hat the modeling tools initially estimated. Measurement and monitoring
are beyond the scope nf this document, but is important for maintaining public trust and support, and in
refining estimates 11' necessary
Once you decide which lool(s) or category of tools (e.g., simple vs complex) may fit your needs
(remember that this list provided is not exhaustive), you should talk to an expert that can help make a
final decision. That person should understand what it means that the "Simple" tools (see comparison
matrix) often use algorithms such as Curve Number, Even Mean Concentration, and Loading Rate,
whereas the "Mid-range" and "Complex" tools simulate runoff, delivery, and pollutant transport in more
detail spatially (e.g., grid cells), temporally (e.g., continuous hourly simulation), and by considering
individual process components such as infiltration, evapotranspiration, and nutrient cycling.
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Nutrient and Sediment Estimation Tool for Watershed Protection
References
Bicknell, B.R., J.C. Imhoff, J.L. Kittle, Jr., T.H. Jobes, and A.S. Donigian, Jr. 2001. Hydrological
Simulation Program - FORTRAN (HSPF) Version 12 User's Manual. Prepared for U.S. Geological
Survey, Hydrologic Analysis Software Support Program, Reston, VA and U.S. Environmental Protection
Agency, Office of Research and Development, Athens, GA. Prepared by AQUA TERRA Consultants,
Mountain View, CA.
Binger, R.L., F.D. Theurer, and Y. Yuan. 2015. AnnAGNPS Technical Processes Documentation Version
5.4.
Chesapeake Bay Program. 2017. Chesapeake Assessment and Scenario lool (CAST) Version 2017.
Chesapeake Bay Program Office. http://cast.chesapeakebav.net/Aboiit.
Evans, B.M. and K. J. Corradini. 2016. MapShed Version 1.5 Users Guide. Pivpaivd lor Perm State
Institutes of Energy and the Environment. University Park. PA.
Evans. B.M., D.W. Lehning, K.J. Corradini, G.W. Petersen. E. Nizeyimana. J.M. Hamlell. P.I) Robillard,
R.L. Day. 2002. A comprehensive GIS-based modelling approach lor predicting nutrienl loads in
watersheds. Journal of Spatial Hydrology. 2(2).
Foster, G. R., L. J. Lane, J. D. Nowlin, J. M. 1 .aflen. and R. A. Young 11>80. A model to estimate
sediment yield from fieldsize areas: Dcvclopmenl of model In CRE IMS . 1 l-'ield-Scale Model for
Chemicals, Runoff and Erosion from Agricultural Management Systems. 36-64. W. G. Knisel, ed.
Conservation Research Report No. 26. Washington. I) ( I SDA Science and Education Administration.
Gassman, P.W., J.R. Williams. X Wang, A. Saleh. E. Osei, L. Hauck, C. Izaurralde, and J. Flowers.
2010. The Agricultural Policy En\ iron mental Extender (APEX) Model: An emerging tool for landscape
and watershed environmental analyses Techn ical Report. Center for Agricultural and Rural
Development, Iowa State I m\eisil\. Ames. Iowa. Published in the American Society of Agricultural and
Biological Engineers ISS\2151-in2. Vol 53(3) 71 1-740.
Gowda, P. H.. B. J. Dalzell. and I) J \lulla. 2007. Model-based nitrate TMDLs for two agricultural
watersheds of southeastern \linnesoia .loiirihil of the American Water Resources Association. 43(1): 1-10.
Granato. (i L 2013. Stochastic empirical loading and dilution model (SELDM) version 1.0.0. U.S.
Geological Survey Techniques and Methods, Book 4, Chapter C3, pp.112.
Haith, D.A. and I.I. Shoemaker [987. Generalized watershed loading functions for stream flow
nutrients. Water Resources Bulletin. 23(3):471-478.
Knisel, W. G., R. A. Leonard, and F. M. Davis. 1993. The GLEAMS Model Plant Nutrient Component:
Part P. Model Documentation. Tifton, Ga.: University of Georgia, Department of Agricultural
Engineering.
Leavesley, G.H., S. L. Markstrom, R. J. Viger, and L. E. Hay (2005), USGS Modular Modeling System
(MMS) - Precipitation-Runoff Modeling System (PRMS) MMS-PRMS, in Singh, V., and Frevert, D.,
eds., Watershed Models. Boca Raton, FL, CRC Press, p. 159-177.
Leonard, R. A., W. G. Knisel, and D. A. Still. 1987. GLEAMS: Groundwater loading effects of
agricultural management systems. Trans. ASAE 30(5): 1403-1418.
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Nutrient and Sediment Estimation Tool for Watershed Protection
Lim, K.J., Engel, B.A., Kim,Y., Bhaduri, B. and J. Harbor. 1999. Development of the Long Term
Hydrologic Impact Assessment (L THIA) WWW Systems. Soil Conservation Organization Meeting, May
24-29, 1999. p.1018-1023.
Lowrance, R., L.S. Altier, R.G. Williams, S.P. Inamdar, J.M. Sheridan, D.D. Bosch, R.K. Hubbard, and
D.L. Thomas. 2000. REMM: The Riparian Ecosystem Management Model. Journal of Soil and Water
Conservation. 55(l):27-34.
Ma, L., L.R. Ahuja, B.T. Nolan, R.W. Malone, T.J. Trout and Z. Qi. 2012. Root zone water quality model
(RZWQM2): model use, calibration, and validation. Transactions oi'ihc . IS.lBJi. 55(4): 1425-1446.
MDEQ (Michigan Department of Environmental Quality). 1999. Pollutants ('onlrolled Calculation and
Documentation for Section 319 Watersheds Training Manual. Lansing. \ 11
Neitsch, S.L., J.G. Arnold, J.R. Kiniry, J.R. Williams. 2011. Soil and Water Assessment Tool Theoretical
Documentation Version 2009. Texas Water Resources Institute Technical Report No 4<)(i Texas A&M
University System, College Station, TX.
Park, Y.S., K.J. Lim, L. Theller, and B.A. Engel. 2013. L-THI. I (US Manual. Department of Agricultural
and Biological Engineering, Purdue University.
Rossman, L.A. 2015. Storm Water Management Model User's Manual Version 5.1. U.S. Environmental
Protection Agency, Office of Research and l)c\clo|-imcnl. National Risk Management Laboratory.
Cincinnati, OH.
Saleh, A. O. Gallego. and E. Osci 2<) 15. Evaluating Nutrient Tracking Tool and Simulated Conservation
Practices. Journal of Soil and Water Conservation. 70(5): 115A-120A.
Saleh, A., O. Gallego. E. Osci. 11 l.al. ( Gross. S. McKinney, andH. Cover. 2011. Nutrient Tracking
Tool -a user-friendly tool lor calculating nutrient reductions for water quality trading. Journal of Soil and
Water Conservation 66((i) 4<)(i-4 In
Schueler. T. 1987. ('on/rolling Urban Runoff: A Practical Manual for Planning and Designing Urban
BMPs Metropolitan Washington ( ouncil of Governments. Washington, DC.
Sharpley, A.N and J.R. Williams, eds. 1990. EPIC- Erosion/Productivity Impact Calculator: 1 Model
Documentation I S Department of Agriculture Technical Bulletin No. 1768. Agricultural Research
Service.
Shoemaker, L., J. Rhcrson. k. Alvi, J. X. Zhen, R. Murphy, B. Wood. 2013. StormwaterManagement
for TMDLs in an Arid Climate: A Case Study Application of SUSTAIN in Albuquerque, New Mexico.
EPA/600/R-13/004. U.S. Environmental Protection Agency, Water Supply and Water Resources
Division, National Risk Management Research Laboratory, Cincinnati, OH.
Shoemaker, L., J. Riverson, K. Alvi, J. X. Zhen, and R. Murphy. 2012. Report on Enhanced Framework
(SUSTAIN) and Field Applications to Placement of BMPs in Urban Watersheds. EPA/600/R-11/144. U.S.
Environmental Protection Agency, Washington, DC.
19
-------
Nutrient and Sediment Estimation Tool for Watershed Protection
Shoemaker, L., J. Riverson, K. Alvi, J. X. Zhen, S. Paul, and T. Rafi. 2009. SUSTAINA Framework for
Placement of Best Management Practices in Urban Watersheds to Protect Water Quality. EPA/600/R-
09/095. U.S. Environmental Protection Agency, Washington, DC.
Skaggs, R. W. 1980. A Water Management Model for Artificially Drained Soils. Tech. Bulletin No. 267.
Raleigh, N.C.: North Carolina State University, North Carolina Agricultural Research Service.
Smith, R.A., G.E. Schwarz, and R.B. Alexander. 1997. Regional interpretation of water quality
monitoring data. Water Resources Research. 33(12):2781-2798.
Systech Engineering. 2001. Watershed Analysis Risk Management Framework: Update One: A Decision
Support System for Watershed Analysis and Total Maximum Daily Load Calculation, Allocation and
Implementation. Prepared for EPRI, Palo Alto, CA. Prepared by Svslech I Engineering, San Ramon, CA.
Tetra Tech, Inc. 2009. Loading Simulation Program in C i i (LSP(') Version 3.1 User's Manual. Fairfax,
VA.
Tetra Tech, Inc. 2010. Stormwater Best Management Pniciiccs (BMP) Performance . I ihi/ysis Prepared
for: U.S. EPA Region 1, Boston, MA. Prepared by: Tetra l ech. Inc I 'airfax. VA.
Tetra Tech, Inc. 2011. User's Guide Spreadsheet Tool for the Estimation of Pollutant Load (STEPL)
Version 4.1. Prepared for U.S. Environmental Proieclion Agenc\. W ashington. DC. Prepared by Tetra
Tech, Inc. Fairfax, VA.
Tetra Tech, Inc. 2016. Opti-Tool for Stormwater and Nutrient Management User's Guide. Prepared for
U.S. Environmental Protection Agency, Region 1. Boston. M A Prepared b\ Tetra Tech, Inc., Fairfax,
VA.
The N.C. PLAT Comnullee 2UU5 Yorili (\ troIina Phosphorus Loss Assessment: I. Model Description
and II. Scientific Basis and Supporting Literature. North Carolina Agricultural Research Service
Technical Bulletin 323. Norlh Carolina Slale I niversitv, Raleigh, NC.
USDA Agricultural Research Ser\ ice (ARS). RZVYQM - Root Zone Water Quality Model website.
http://wv\ u ars.usda.^n\ Main/dues him Ylocid= 17740. Last accessed June 02, 2017.
USDA ARS National Soil Erosion Research Laboratory. 1995. Technical Documentation USDA-Water
Erosion Pra/iciion Project (ll 'LI'P). West Lafayette, IN.
USDA ARS Soulhuesi \Yalershed Research Center, USEPA Office of Research and Development and
University of Wyoming Rangeland Ecology and Watershed Management. N.D. Automated Geospatial
Watershed Assessment (ACiNYA) 3.X User Guide.
Walker, W.W. and J.D. Walker. 2015. P8 Urban Catchment Model Version 3.5. Concord, MA.
White, M. and D. Harmel. 2012. Texas BMP Evaluation Tool (TBET) Users Guide Version 0.2. U.S.
Department of Agriculture Grassland Soil and Water Research Laboratory. Temple, TX.
Woolhiser, D.A., R.E. Smith, and D.C. Goodrich. 1990. KINEROS, A Kinematic Runoff and Erosion
Model: Documentation and User Manual. U.S. Department of Agriculture, Agricultural Research
Service, ARS-77, 130pp.
20
-------
Nutrient and Sediment Estimation Tool for Watershed Protection
Young, R.A., C.A. Onstad, D.D. Bosch, and W.P. Anderson. 1989. AGNPS: A nonpoint-source pollution
model for evaluating agricultural watersheds. Journal of Soil and Water Conservation. Vol 44 (2) 168-
173.
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