Literature DB >> 32763592

Evaluation of the soil and water assessment tool (SWAT) for simulating E. coli concentrations at the watershed-scale.

Robert A Sowah1, Kenneth Bradshaw2, Blake Snyder3, David Spidle3, Marirosa Molina4.   

Abstract

Water quality management at the watershed level requires a framework to identify sources, apportion water quality risks and develop mitigation strategies to reduce health risks. Watershed-scale models have been used as a support tool to understand the sources, fate and transport of fecal bacteria and pathogens in the environment. The Soil and Water Assessment Tool (SWAT) model was applied in this study to understand the sources and drivers of microbial water quality in the Clouds Creek watershed in Georgia, USA. A criterion to evaluate the performance of the SWAT bacterial model was also developed in this study using the Nash-Sutcliffe Efficiency (NSE) performance measure. The SWAT model was successfully calibrated and validated for flow with Nash-Sutcliffe Efficiency (NSE) of 0.81 and 0.55, respectively. Escherichia coli (E. coli) predictions were good with NSE of 0.32 and 0.34 for the calibration and validation timeframes, respectively. Based on the criteria developed in this study, SWAT bacterial model for E. coli and fecal coliform can be judged as "satisfactory" when NSE > 0.20. The contribution of sources followed this order: in-stream cattle manure deposition > cattle manure application > poultry manure application > septic systems > wildlife manure, suggesting that a reduction in livestock access to streams would be the most effective approach to reduce fecal bacterial loads in this watershed and others impacted by fecal contamination. Finally, our results suggest that the SWAT model is capable of simulating E. coli dynamics in the Clouds Creek watershed and can provide insights into source impacts for risk management.
Copyright © 2020. Published by Elsevier B.V.

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Year:  2020        PMID: 32763592      PMCID: PMC8804978          DOI: 10.1016/j.scitotenv.2020.140669

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  14 in total

1.  The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA.

Authors:  Kyung Hwa Cho; Yakov A Pachepsky; Joon Ha Kim; Jung-Woo Kim; Mi-Hyun Park
Journal:  Water Res       Date:  2012-06-28       Impact factor: 11.236

2.  Evaluating the influence of climate change on the fate and transport of fecal coliform bacteria using the modified SWAT model.

Authors:  Dong Jin Jeon; Mayzonee Ligaray; Minjeong Kim; Gayoung Kim; Gil Lee; Yakov A Pachepsky; Dong-Hyun Cha; Kyung Hwa Cho
Journal:  Sci Total Environ       Date:  2018-12-14       Impact factor: 7.963

3.  Characterizing relationships among fecal indicator bacteria, microbial source tracking markers, and associated waterborne pathogen occurrence in stream water and sediments in a mixed land use watershed.

Authors:  J Kenneth Bradshaw; Blake J Snyder; Adelumola Oladeinde; David Spidle; Mark E Berrang; Richard J Meinersmann; Brian Oakley; Roy C Sidle; Kathleen Sullivan; Marirosa Molina
Journal:  Water Res       Date:  2016-05-13       Impact factor: 11.236

Review 4.  Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities.

Authors:  Kyung Hwa Cho; Yakov A Pachepsky; David M Oliver; Richard W Muirhead; Yongeun Park; Richard S Quilliam; Daniel R Shelton
Journal:  Water Res       Date:  2016-04-29       Impact factor: 11.236

5.  Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments.

Authors:  David M Oliver; Kenneth D H Porter; Yakov A Pachepsky; Richard W Muirhead; Sim M Reaney; Rory Coffey; David Kay; David G Milledge; Eunmi Hong; Steven G Anthony; Trevor Page; Jack W Bloodworth; Per-Erik Mellander; Patrice E Carbonneau; Scott J McGrane; Richard S Quilliam
Journal:  Sci Total Environ       Date:  2015-12-03       Impact factor: 7.963

6.  Using SWAT, Bacteroidales microbial source tracking markers, and fecal indicator bacteria to predict waterborne pathogen occurrence in an agricultural watershed.

Authors:  Steven K Frey; Edward Topp; Thomas Edge; Claudia Fall; Victor Gannon; Cassandra Jokinen; Romain Marti; Norman Neumann; Norma Ruecker; Graham Wilkes; David R Lapen
Journal:  Water Res       Date:  2013-08-19       Impact factor: 11.236

7.  Modelling Cryptosporidium oocysts transport in small ungauged agricultural catchments.

Authors:  Jialiang Tang; Stephen McDonald; Xinhua Peng; Sukha R Samadder; Thomas M Murphy; Nicholas M Holden
Journal:  Water Res       Date:  2011-04-23       Impact factor: 11.236

8.  Modeling the Effects of Onsite Wastewater Treatment Systems on Nitrate Loads Using SWAT in an Urban Watershed of Metropolitan Atlanta.

Authors:  Nahal Hoghooghi; David E Radcliffe; Mussie Y Habteselassie; Jaehak Jeong
Journal:  J Environ Qual       Date:  2017-05       Impact factor: 2.751

9.  Source specific fecal bacteria modeling using soil and water assessment tool model.

Authors:  Prem B Parajuli; Kyle R Mankin; Philip L Barnes
Journal:  Bioresour Technol       Date:  2008-08-13       Impact factor: 9.642

10.  Recovery of thermophilic Campylobacter by three sampling methods from river sites in Northeast Georgia, USA, and their antimicrobial resistance genes.

Authors:  R J Meinersmann; M E Berrang; J K Bradshaw; M Molina; D E Cosby; L L Genzlinger; B J Snyder
Journal:  Lett Appl Microbiol       Date:  2019-11-04       Impact factor: 2.813

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  1 in total

1.  Sediment and fecal indicator bacteria loading in a mixed land use watershed: Contributions from suspended sediment and bedload transport.

Authors:  J Kenneth Bradshaw; Blake Snyder; David Spidle; Roy C Sidle; Kathleen Sullivan; Marirosa Molina
Journal:  J Environ Qual       Date:  2021-04-22       Impact factor: 3.866

  1 in total

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