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• W2885181145 abstract "Terrestrial fate and transport processes of E. coli can be complicated by human activities like urbanization or livestock grazing. There is a critical need to address contributing sources of bacterial contamination, properly assess the management of critical sources, and ultimately reduce E. coli concentrations in impaired water bodies. In particular, characterization of wildlife animal contributions and other “background” input sources of microbial pollution are highly uncertain and data are scarce. This study attempts to identify critical sources of E. coli and the efficacy of conservation practices for mitigating E. coli concentrations in the Arroyo Colorado watershed, Texas, using a process-based hydrologic and water quality model. We propose to incorporate a bacterial source tracking assessment into the modeling framework to fill the gap in data on wildlife and human contribution. In addition, other sources identified through a GIS survey, national census, and local expert knowledge were incorporated into the model as E. coli sources. Results suggest that simulated distribution of E. coli sources significantly improved after incorporating this enhanced data on E. coli sources into the model (R2 = 0.90) compared to the SWAT result without BST (R2 = 0.59). Scenario assessments indicate that wildlife contributions may remain significant despite land use change and urbanization, expected to mostly occur in agricultural and range lands. A combination of nonpoint source management measures, voluntary implementation of advanced treatment by wastewater plants where possible, and installation of aerators in the zone of impairment were demonstrated to be effective measures for restoring the recreation and aquatic life uses of the Arroyo Colorado." @default.
• W2885181145 created "2018-08-22" @default.
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• W2885181145 date "2019-01-01" @default.
• W2885181145 modified "2023-10-18" @default.
• W2885181145 title "Linking watershed modeling and bacterial source tracking to better assess E. coli sources" @default.
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• W2885181145 doi "https://doi.org/10.1016/j.scitotenv.2018.08.097" @default.
• W2885181145 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30114587" @default.
• W2885181145 hasPublicationYear "2019" @default.
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