Spatially Explicit Load Enrichment Calculation Tool to Identify Potential E. coli Sources in Watersheds

Abstract

In 2006, bacterial pathogens were the leading cause of water quality concerns in the U.S. With more than 300 water bodies in the state of Texas failing to meet water quality standards because of bacteria, managing bacteria pollution commanded the attention of regulatory agencies, researchers, and stakeholders across Texas. In order to assess, monitor, and manage water quality, it was necessary to characterize the sources of pathogens within the watershed. The objective of this study was to develop a spatially explicit method to estimate potential E. coli loads in Plum Creek watershed in east central Texas. Locations of contributing non-point and point sources in the watershed were defined using Geographic Information Systems (GIS). By distributing livestock, wildlife, wastewater treatment plants, septic systems, and pet sources, the bacterial load in the watershed was spatially characterized. Contributions from each source were quantified by applying source specific bacterial production rates, and ranking of each contributing source was assessed for the entire watershed. Cluster and discriminant analyses were used to identify similar regions within the watershed for selecting appropriate best management practices. Based on the statistical analysis and the spatially explicit method, four clusters of subwatersheds were found and characterized. The analysis provided a basis for development of spatially explicit identification of best management practices (BMPs) to be applied within the Watershed Protection Plan (WPP).

Growth Kinetics of Wildlife <i>E. coli</i> Isolates in Soil and Water

“…Water quality and watershed modeling tools such as Spatially Explicit Load Enrichment Calculation Tool (SELECT), Hydrological Simulation Program-Fortran (HSPF), and Soil and Water Assessment Tool (SWAT) are used in the bacterial Total Maximum Daily Load (TMDL) process to characterize E. coli sources in a watershed and estimate the required reductions in E. coli loads [27][28][29][30]. In rural watersheds, wildlife can contribute a majority of the fecal pollution and should be considered [31].…”

Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed‐Use Watersheds

“…The BSLC uses externally generated inputs, such as land use distribution and livestock, wildlife, and human population estimates, to calculate monthly bacterial land loadings and hourly bacterial stream loadings. Teague et al (2009) presented SELECT (Spatially Explicit Load Enrichment Calculation Tool) to identify potential Escherichia coli sources in watersheds that estimate the daily average potential E. coli production from livestock, wildlife, wastewater treatment plants, septic systems, and pet sources. Taken together, these findings reveal that microbial fate parameters along with the load parameters appear to be critical for modeling results.…”

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

“…However, 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 SELECT was developed to characterize E. coli sources based on spatial factors such as land use, source population density, and soil [6]. SELECT has been used to assess potential hotspots and sources of bacterial contamination in watersheds as part of watershed protection plan and total maximum daily load projects [6][7][8][9][10][11][12][13].…”

“…In lieu of complex mechanistic models, SELECT was developed as an estimation tool to inform watershed management decisions SELECT was developed to characterize E. coli sources based on spatial factors such as land use, source population density, and soil [6]. SELECT has been used to assess potential hotspots and sources of bacterial contamination in watersheds as part of watershed protection plan and total maximum daily load projects [6][7][8][9][10][11][12][13]. SELECT was originally automated within Geographic Information Systems (GIS) using Visual Basics for Applications (VBA).…”