HR: 1330h
AN: H12D-1018    [PDF]
TI: Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling
AU: * Yilmaz, K K
EM: yilmazk@uci.edu
AF: Department of Civil and Environmental Engineering, University of California, Irvine, E/4130 Engineering Gateway, Irvine, CA 92697-2175 United States
AU: Hogue, T S
EM: thogue@seas.ucla.edu
AF: Department of Civil and Environmental Engineering, UCLA, 5732C Boelter Hall, Los Angeles, CA 90095-1593 United States
AU: Hsu, K
EM: kuolinh@uci.edu
AF: Department of Civil and Environmental Engineering, University of California, Irvine, E/4130 Engineering Gateway, Irvine, CA 92697-2175 United States
AU: Gupta, H V
EM: hoshin@hwr.arizona.edu
AF: Department of Hydrology and Water Resources, University of Arizona, 1133 E. North Campus Drive Harshbarger Bldg, Tucson, AZ 85721 United States
AU: Mahani, S E
EM: mahani@ce.engr.ccny.cuny.edu
AF: International Center for Environmental Resources and Development, The City College of New York, New York, NY 10031 United States
AU: Sorooshian, S
EM: soroosh@uci.edu
AF: Department of Civil and Environmental Engineering, University of California, Irvine, E/4130 Engineering Gateway, Irvine, CA 92697-2175 United States
AB: The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.
DE: 1854 Precipitation (3354)
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2003 Fall Meeting