Demonstration of ArcGIS as a Tool to Predict
Pollutant Loading in Stormwater Discharges
Jesse S. Dickson
CE 547: GIS in Water Resources
Dr. J. Coonrod
May 6, 2011
Introduction
In order to address the more restrictive goals of the EPA’s NPDES Phase 2 discharge permits,
municipalities need a cheap and effective means to characterize pollutant loads generated within
their watersheds. The purpose of this paper is to demonstrate how ArcGIS can be used to predict
pollutant concentrations as a potential planning tool for municipalities and flood control
authorities. See Appendix C – Background for additional information pertaining to NPDES
regulations.
Methods
The methods used for determination of an ultimate pollutant load originating from non-point
sources in a watershed are fairly straight-forward. While the algorithm for modeling transport of
pollutants can be somewhat involved, as demonstrated by the transport model described below,
the algorithm itself is made up of a series of simple calculations comprised mostly of vector
algebra, conversion of polygons to rasters, and joining tables to feature classes.
Data Sources
Data sources for the project, although compiled in a zip file, are all either available from via the internet
from data clearinghouses such as RGIS, USGS, and PRISM, or capable of being created as a fairly simple
.dbf file. For instance, the EMC field (described in Appendix A, III.B below) for pollutant concentrations
based on land use, can be readily approximated and compiled in tabular (i.e., .dbf) form from information
available in various locations on the internet, such as the Spreadsheet Tool for Estimated Pollutant Load
(STEPL), located at: http://it.tetratech-ffx.com/steplweb/models$docs.htm. Additionally, a more accurate
runoff model could be generated for areas with detailed topographic information (as opposed to the
regression equations used in this project for generation of runoff data).
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Projection
The projection used for this project is the ___________. There is no overriding reason for using this
projection, other than it accurately displays and represents the large land area (approximately _______
square miles) analyzed in this project. If the project had been a smaller land area, particularly one with a
predominantly north-south oriented floodplain, a UTM projection with state plane coordinates would
have been a more appropriate.
Software Environment
Most of the procedures performed in the course of this project were executed in the ArcView
environment, and drawing heavily from the Spatial Analyst features found in the ArcToolbox sidebar.
Although the compiled data provided both the .dbf file and model toolbar used in the pollutant raster
creation and transport model, these features would need to be created using ArcCatalog and Model
Builder, respectively. It is noted that scripting (presumably Python) was used to create the .dll files
needed to link data from the routed runoff portion of the model to the routed (i.e., degradation of pollutant
concentrations based on various decay parameters) pollutant concentration portion of the model.
Although the Model Builder feature is not strictly required to perform the calculations necessary the
transport of contaminants from each watershed to their ultimate point of discharge, by automating the
algorithm in Model Builder, ArcGIS facilitates the ease of replicating calculations with a minimum of
effort. This allows for quickly calculating results for multiple scenarios, including a changes in pollutant
concentration or maintaining a database that tracks historical pollutant loading.
Results
This project resulted in a combination of . Although the process of creating the various rasters and
raster manipulations necessary to create pollutant load concentrations
Unfortunately, however, the failure of the model to run properly did not provide the
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Conclusions
ArcGIS provides a powerful tool in assessing pollutant loads in stormwater discharges a wide
geographical area. By characterizing pollutant discharges based on land use, ArcGIS can be
used to model pollutant concentrations to specific locations in a watershed. Municipalities and
flood control authorities can use this information as a planning tool to prioritize potential
treatment facilities by determining where such facilities should be located to achieve maximum
benefit when treating stormwater for pollutants. Additionally, after construction of treatment
facilities ArcGIS can be used to track pollutant removal and demonstrate that measureable goals
in stormwater treatment have been met.
Future Research
Future research that would be helpful to this end would include locally applicable studies of
pollutant loading based on land use. For smaller – but more complex – watersheds such as the
Albuquerque area, a detailed stormwater model that includes local stormwater facilities (e.g.,
conveyance structures, detention facilities, etc.) would provide a much more accurate
representation of discharges that carry pollutants to the Rio Grande. Such a water model would
provide much more accurate data for pollutant concentrations. Finally, the failure of the .dll files
to properly link the various inputs in the Transport Model illustrate the need to have a
understanding of the scripting language used to create an intricate model. As with any modeling
software, it is imperative for the user to have a firm grasp of the algorithm at the core of the
model. This serves two functions: first, it allows the user to adjust the framework of the model
when a processing error occurs. Second, and perhaps most importantly, it allows the user to
ascertain—particularly in the absence of a processing error—when the algorithm has run
correctly. In the case of this project, if the transport model had run to completion without
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generating an error, but used a .dll file incorrectly (e.g., linked pollutant decay coefficients
incorrectly), my unfamiliarity with the script used to generate the .dll file would likely cause the
error to go unnoticed. While this is a concern that is important to any software that utilizes
programming scripts, it is particularly noteworthy in ArcGIS since so many open source Python
scripts are available (like the one used in the project) via the internet.
.
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Appendix A – Procedure
The following procedures were applied to obtain the reported results:
I.
Acquire Data
A. Data used in the presented results were compiled and stored in a zip file at the primary
source for the research of the project. This file also contains the transport algorithm used
to model transport of pollutants and is located at:
http://www.ce.utexas.edu/prof/maidment/giswr2005/ex6/BacterialModel.zip
B. Watershed Data: USGS Hydrologic Unit Code mapping:
http://water.usgs.gov/GIS/huc.html
C. Rainfall Data: PRISM Climate Group
http://www.prism.oregonstate.edu/
D. Land Use Data: NRCS Data
http://www.nrcs.usda.gov/technical/NRI/maps/aboutmaps/coverages.html
E. Pollutant Data Based on LULC – “Estimation of Fecal Coliform Loadings to Galveston
Bay” (Zoun, 2003)
F. After extracting the zip file, install the DLL files required for the transport model using
“Install.BAT”
II.
Calculate Runoff
A. Runoff is calculated using derived empirical equations particular to the area. Other
regression equations for all states can be found at: http://water.usgs.gov/software/NFF/
B. Convert PRISM rainfall data to raster using the FEATURE TO RASTER command in
ArcToolbox
C. Use RASTER CALCULATOR to create precipitation raster for each LULC raster.
D. Use RASTER CALCULATOR and regression equations to create runoff raster from each
precipitation raster (generated in step C)
E. Use MOSAIC TO NEW RASTER to compile runoff rasters into one raster.
F. Use ZONAL STATISTICS and watershed feature as an input and “Junction ID” as zone
field to create runoff per basin.
III.
Create Pollutant Concentration Raster
A. Using the previously created .dbf file, join the Concentration table to LULC polygon
B. Create pollutant raster based on EMC field.
IV.
Create Non-Point Pollutant Load Raster
A. Use RASTER CALCULATOR to multiply the runoff raster by the pollutant concentration
raster to get a raster for the mass loading of pollutant.
B. Note that results of the initially created raster contained negative numbers for
concentration when applied to step C. It was determined that the values were larger than
allowed, even using “float” domain. Therefore, the values were divided by 106 using
RASTER CALCULATOR to get smaller concentration values.
C. Use ZONAL STATISTICS AS TABLE with watershed feature to generate pollutant load
per year for each basin.
V.
Model Transport of Pollutant Load
A. Populate the “IncVal” field of the previously created chemaNode feature by JOIN with
table created in IV.C. and watershed.
B. Add the previously created transport model to the ArcToolbox.
C. Run the Model.
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D. Note that the model runs and appears to populate the SchemaLink feature class, but fails
to carry generated data to the SchemaNode feature class.
E.
Appendix B – Datasets (attached digitally)
Appendix C – Background
The EPA’s Clean Water Act (CWA) applies not only to wastewater, but as of amendments
enacted in 1987, also to stormwater runoff. The CWA created the National Pollutant Discharge
Elimination System (NPDES), which grants permits to discharge into waters of the US. Phase 1
of the 1987 amendments to the CWA regulated stormwater discharged from industrial sites and
from “Municipal Separate Storm Sewer Systems” (MS4) for cities with populations greater than
100,000 people. The first NPDES stormwater permits were issued in the early 1990s and for the
most part, the only requirements of the MS4 permits were to conduct studies and monitor
stormwater quality. In Phase 2 of the NPDES stormwater regulations, permits were to become
much more restrictive, identifying specific and quantifiable treatment goals. Discharge permits
in Phase 2 of the NPDES are specific to the MS4 requesting permission to discharge, and can
apply to several MS4 whose stormwater originates in a single watershed. For instance, the
permit to which Albuquerque must adhere will likely be a regional permit, which will apply to
several MS4 in the Middle Rio Grande Valley, including Corrales, Bernalillo, and Sandia
Pueblo. Since Phase 2 permits are watershed-specific, the treatment goals of each permit will
depend on the contaminants of concern to a particular to a given watershed.
Although many Phase 2 permits have not yet been issued, municipalities with MS4 have an
idea of the treatment goals that will be required, based on analysis of stormwater that was
completed in Phase 1. As stated above, the character of stormwater is unique to the watershed
that generated it, but can be generalized based on land use. Table 1 below shows average
contaminant concentrations for stormwaters generated by several MS4 across the US.
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Table 1: Average Contaminant Concentrations
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