SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Spatially Explicit Load Enrichment Calculation Tool to Indentify Potentail E. Coli Sources in Watersheds 
Authors:Teague, A., R. Karthikeyan, M. Babbar-Sebens, R. Srinivasan and R.A. Persyn 
Year:2009 
Journal:Transactions of the ASABE 
Volume:52(4) 
Pages:1109-1120 
Article ID: 
DOI:10.13031/2013.27788 
URL (non-DOI journals):http://www-ssl.tamu.edu/media/11291/select-aarin.pdf 
Model:none 
Broad Application Category:interface tool and/or other software 
Primary Application Category:data/component contribution to SWAT 
Secondary Application Category:computational efficiency 
Watershed Description:1028 km^2 Plum Creek Watershed in east central Texas 
Calibration Summary: 
Validation Summary: 
General Comments: 
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). 
Language:English 
Keywords:Cluster analysis, Fecal bacteria, Impaired streams, Spatial statistics, TMDL