Modeling the Dispersion of E. coli in Waterbodies Due to Urban Sources: A Spatial Approach

Kyna Borel,Cherish Vance,Raghupathy Karthikeyan,Vaishali Swaminathan,Galen Roberts,Raghavan Srinivasan

doi:10.3390/w9090665

Kyna Borel, Cherish Vance + Show 4 more

Open Access

https://doi.org/10.3390/w9090665

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Journal: Water	Publication Date: Sep 2, 2017
Citations: 3	License type: CC BY 4.0

Affiliation: Texas A&M University, Texas Water Development Board

Abstract

In the United States, pathogens are the leading cause for rivers and streams to exceed water quality standards. The Spatially Explicit Load Enrichment Calculation Tool (SELECT) was developed to estimate bacterially contaminated water bodies based on spatial factors such as land use, soil, and population density. SELECT was originally automated using Visual Basics for Applications (VBA), which is no longer supported by the current version of ArcGIS. The aim of this research was to develop a new SELECT interface, pySELECT, using the Python programming language and to incorporate a rainfall-runoff E. coli transport module to simulate E. coli loads resulting from urban sources, such as dogs and on-site wastewater treatment systems. The pySELECT tool was applied to Lavon Lake, a semi urban study watershed in Northeast Texas. The highest potential E. coli loads were in the areas closest to the Dallas-Fort Worth metroplex, and the highest transported loads were located downstream from those identified hotspots or where the most runoff was generated. Watershed managers can use pySELECT to develop best management practices on the specific areas and fecal sources that contribute fecal contamination into a waterbody.

Highlights

In the United States, 54% of assessed rivers and streams are considered impaired, exceeding regulatory standards for contaminants
Four modules are included in pySELECT: Rainfall runoff (USDA-NRCS curve number), E. coli transport, and potential E. coli load
The areas with the highest potential E. coli load due to failing on-site wastewater treatment systems (OWTS) were located in the subwatersheds to the west of Lavon Lake (Figure 7c)

Summary

Introduction

In the United States, 54% of assessed rivers and streams are considered impaired, exceeding regulatory standards for contaminants. Among these impaired rivers and streams, pathogens are the leading cause of impairment [1]. Complex mechanistic models such as Hydrologic Simulation Program. Fortran (HSPF) and Soil Water Assessment Tool (SWAT) simulate the fate and transport of bacteria. These models require large amounts of input data, which is difficult in areas with limited monitoring records [2,3,4,5]. In lieu of complex mechanistic models, SELECT was developed as an estimation tool to inform watershed management decisions

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