ABSTRACT Title of Thesis: CALIBRATING SHENANDOAH WATERSHED SWAT MODEL USING A NONLINEAR GROUNDWATER ALGORITHM

Title of Thesis: CALIBRATING SHENANDOAH WATERSHED SWAT MODEL USING A NONLINEAR GROUNDWATER ALGORITHM Yan Wang, Master of Science, 2011 Directed By: Dr. Kaye Brubaker Water Resources Engineering Department of Civil and Environmental Engineering This study contributes to a project with the Interstate Commission on the Potomac River Basin to build a model of the Potomac watershed using the Soil Water Assessment Tool (SWAT). The 2,937 mi Shenandoah watershed represents about 40% of the Potomac Basin by area. The model subdivides the Shenandoah watershed into 28 subwatersheds and 489 hydrologic response units. SWAT‘s linear-reservoir groundwater algorithm is modified into a new nonlinear method. Modeled flows are compared to observations (dating from 1996 to 2006) at 15 USGS stream gages. The model is auto-calibrated using the Parameter Estimation Software (PEST), experimenting with options to improve model performance. The best model results are obtained by applying ordinal weights to the observation groups, decreasing from headwaters to outlet, and pre-calibrating the roughness coefficients using empirical equations. The calibrated model will contribute to understanding hydrological processes and predicting the effects of land use and climate change in the watershed. CALIBRATING SHENANDOAH WATERSHED SWAT MODEL USING A NONLINEAR GROUNDWATER ALGORITHM