Technical Papers
Aug 6, 2012

Estimating Watershed-Scale Precipitation by Combining Gauge- and Radar-Derived Observations

Publication: Journal of Hydrologic Engineering
Volume 18, Issue 8

Abstract

Watershed modeling requires accurate estimates of precipitation; however, in some cases it is necessary to simulate streamflow in a watershed for which there is no precipitation gauge records within close proximity to the watershed. For such cases, we propose an approach to estimating watershed-scale precipitation by combining (or fusing) gauge-based precipitation time series with radar-based precipitation time series in a way that seeks to match input precipitation for the watershed model with observed streamflow at the watershed outlet. We test the proposed data fusion approach through a case study where the Soil and Water Assessment Tool (SWAT) model is used to simulate streamflow for a portion of the Eno River Watershed located in Orange County, North Carolina. Results of this case study show that the proposed approach improved model accuracy (E=0.60; R2=0.74; PB=10.2) when compared to a model driven by gauge data only (E=0.50; R2=0.54; PB=25.5) or radar data only (E=0.33; R2=0.61; PB=13.7). While this result is limited to a single watershed case study, it suggests that the proposed approach could be a useful tool for hydrologic engineers in need of retrospective precipitation estimates for watersheds that suffer from inadequate gauge coverage.

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Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 18Issue 8August 2013
Pages: 983 - 994

History

Received: Dec 23, 2011
Accepted: Jul 5, 2012
Published online: Aug 6, 2012
Discussion open until: Jan 6, 2013
Published in print: Aug 1, 2013

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Authors

Affiliations

Mehmet B. Ercan
M.ASCE
Graduate Research Assistant, Dept. of Civil and Environmental Engineering, College of Engineering and Computing, Univ. of South Carolina, 300 Main St., Columbia, SC 29208.
Jonathan L. Goodall [email protected]
A.M.ASCE
Assistant Professor, Dept. of Civil and Environmental Engineering, College of Engineering and Computing, Univ. of South Carolina, 300 Main St., Columbia, SC 29208 (corresponding author). E-mail: [email protected]

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