Distributed Hydrologic Prediction: Sensitivity to Accuracy of Initial Soil Moisture Conditions and Radar Rainfall Input
Publication: Journal of Hydrologic Engineering
Volume 14, Issue 7
Abstract
The aim of this study is to evaluate prediction accuracy and sensitivity of a distributed hydrologic model. Accurate predictions of runoff are needed where reservoir operations are used to control flooding and to manage water resources. The study area consists of watershed areas that are influent to reservoirs in the Yongdam basin, and the Namgang basin located on the Korean Peninsula. For these basins with complex terrain, a physics-based distributed hydrologic model is set up with geospatial data, calibrated, and used to test sensitivity to accuracy of radar and rain gauge input and initial conditions. The events studied range in magnitude from 86 to over and include two typhoons and two heavy rainfall events. Radar reflectivity is converted to rainfall rates using relationships, and then corrected for bias using a spatially variable correction derived from the rain gauge networks that cover both basins. Adjustment of assumed model parameters for the Namgang and Yongdam watersheds improves hydrograph peak and volume. The prediction accuracy of the model is also evaluated using rainfall estimated with uncorrected radar and with rain gauge data as model input. Use of gauge-corrected radar results in better prediction accuracy than was achieved with raw radar or gauge-only input. The sensitivity of the watershed response to the initial degree of saturation is dependent on event magnitude but becomes increasingly sensitive at higher degrees of initial saturation. In both watersheds, the initial saturation of the soil affects prediction accuracy more than the uncertainty caused by model parameters or gauge-only input.
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Acknowledgments
Support for this project from K-water is gratefully acknowledged.
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Published In
Journal of Hydrologic Engineering
Volume 14 • Issue 7 • July 2009
Pages: 671 - 689
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© 2009 ASCE.
History
Received: May 4, 2007
Accepted: Oct 5, 2008
Published online: Mar 5, 2009
Published in print: Jul 2009
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