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Title: The impact of watershed diversity on SWAT model uncertainty: A comparison across USDA-ARS watersheds

item Veith, Tameria - Tamie
item VAN LIEW, M - DEQ
item Bosch, David - Dave
item Arnold, Jeffrey

Submitted to: Soil and Water Conservation Society
Publication Type: Abstract Only
Publication Acceptance Date: 1/24/2007
Publication Date: 7/25/2007
Citation: Veith, T.L., Van Liew, M.W., Bosch, D.D., Arnold, J.G. 2007. The impact of watershed diversity on SWAT model uncertainty: A comparison across USDA-ARS watersheds [abstract]. Soil and Water Conservation Society. p.36

Interpretive Summary: An interpretive summary is not required.

Technical Abstract: The ability to assess and compare the effectivenesses of agricultural management practices depends on the distinguishing capabilities of the tool(s) used. At the watershed-level, water quality models such as the Soil and Water Assessment Tool (SWAT) are commonly used to capture the relative effects of conservation practices. For example, watersheds across the United States have recently been evaluated using SWAT and other models as part of the USDA-ARS Conservation Effects Assessment Program (CEAP). When using models, however, one must remember that in addition to any uncertainty in field data collection and processing there are also model parameter uncertainties and uncertainties related to the attempt to mathematically replicate the complexity and stochasicity of the natural physical system. The SWAT Autocalibration Tool provides a mechanism for quantifying model uncertainty resulting from application of SWAT to a watershed. This tool is applied to several USDA-ARS watersheds. Results are compared and interpreted with regard to specific watershed characteristics and commonalities across watersheds. A better understanding of the level of model uncertainty to be expected for a given type of watershed provides a better understanding of the sensitivity of the model output to various conservation practices. Also, better understanding of SWAT's responses aids in future model enhancement and development.