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Bacteria modeling with SWAT for assessment and remediation studies – a review

Baffaut, C., Sadeghi, A.
ARS USDA Submissions 2010 v.53 no.5 pp. 1585
Soil and Water Assessment Tool model, animal manures, bacteria, bacterial contamination, cattle, environmental assessment, environmental fate, environmental monitoring, equations, land use, nonpoint source pollution, point source pollution, prediction, remediation, runoff, simulation models, streams, surface water, urban areas, water pollution, watersheds, wildlife, France, Georgia, Kansas, Missouri
A module to simulate bacteria fate and transport in watersheds was first tested in SWAT 2000 and fully integrated into the SWAT2005 code. Since then, few investigators have utilized SWAT to model bacteria fate and transport in spite of bacteria being a major cause of streams impairment in the U.S. In this article, bacteria equations are briefly presented. Modeling applications, which range from 16 to 3,870 km2, from Missouri, Kansas, and Georgia in the U.S. and from Brittany in France, are reviewed, highlighting the modeling successes and the challenges. In all cases, land use included agricultural and forested land with a mix of point and nonpoint sources. Nonpoint sources included indirect (manure deposited on land) and direct contributions from cattle or wildlife to the streams. In some cases, urban and residential contributions were included. Strategies to represent the different sources, calibration methods, and goodness of fit were compared. Changes to the model's code that were necessary to handle contributions from urban areas were reviewed. Overall, SWAT reasonably simulated the range and frequencies of bacteria concentrations. In all cases, direct bacteria inputs into streams appeared to have a major impact on the model results. This review also indicates that the model processes that simulate the release and transport of bacteria in surface runoff may need to be revisited. This improvement could enable SWAT to be more reliable for predicting bacteria concentrations and evaluating the impact of different management scenarios on bacteria contributions to surface water resources.