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dc.contributor.authorLin, Z.
dc.contributor.authorRadcliffe, David E.
dc.contributor.editorHatcher, Kathryn J.en_US
dc.date.accessioned2013-06-17T14:40:45Z
dc.date.available2013-06-17T14:40:45Z
dc.date.issued2005-04
dc.identifier.urihttp://hdl.handle.net/1853/47764
dc.description.abstractA two-stage routine has been developed for automatic calibration of the Soil Water Assessment Tool (SWAT, a semi-distributed watershed model) that finds the best values for the model parameters, preserves the spatial variability in essential parameters, and leads to a measure of the model prediction uncertainty. We calibrated the stream flow in the Etowah River measured at Canton, GA (a watershed area of 1,580 km2) for the years 1983-1992 and used the years 1993-2001 for validation. Calibration for daily and monthly flow produced a very good fit to the measured data. Nash-Sutcliffe coefficients for daily and monthly flow over the calibration period were 0.60 and 0.86, respectively; they were 0.61 and 0.87 respectively over the validation period. Regardless of the level of model-to-measurement fit, non-uniqueness of the optimal parameter values necessitates uncertainty analysis for model prediction. The nonlinear prediction uncertainty analysis showed that caution must be exercised when using the SWAT model to predict short-term (7-day average) flows, especially under low and high flow conditions.en_US
dc.description.sponsorshipSponsored by: Georgia Environmental Protection Division U.S. Geological Survey, Georgia Water Science Center U.S. Department of Agriculture, Natural Resources Conservation Service Georgia Institute of Technology, Georgia Water Resources Institute The University of Georgia, Water Resources Facultyen_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesGWRI2005. Ground water and coastalen_US
dc.subjectWater resources managementen_US
dc.subjectAutomatic calibrationen_US
dc.titleAutomatic calibration and predictive uncertainty analysis of a semi-distributed watershed modelen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameUniversity of Georgia. Dept. of Crop and Soil Sciencesen_US
dc.publisher.originalInstitute of Ecology, The University of Georgiaen_US
dc.embargo.termsnullen_US


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