HR: 1340h
AN: H33C-0485    [Abstracts]
TI: Runoff Variability in Field-scale Catchments and the Implications for Rainffall-Runoff Modeling
AU: * Zhang, Y
EM: zhang.yu@agu.gov
AF: Oak Ridge Institute for Science and Education, USEPA-NRMRL, Sustainable Environments Branch, ML 498 26 W Martin Luther King, Cincinnati, OH 45220
AU: Shuster, W
EM: shuster.william@epa.gov
AF: USEPA, USEPA-NRMRL, Sustainable Environments Branch, ML 498 26 W Martin Luther King, Cincinnati, OH 45220
AB: In this study long-term rainfall runoff records for two agricultural catchments (ca. 0.5 ha) in the USDA - Agricultural Research Service North Appalachian Experimental Watershed (Coshocton, OH) network were used to address the inter-event and inter-catchment variability of field-scale runoff processes. Through analyses of flood frequency and flow duration, the adjacent fallowed watersheds (WS106 and WS121) were found to be similar in terms of annual flood peaks, but less so in terms of the distribution of their discharge rates. Further investigation was focused on event-scale variations of runoff response and whether these variations can be effectively captured by rainfall-runoff models, which included: a) TR-20 (a lumped model); b) EPA-SWMM (a semi-distributed model); and c) GSSHA (a grid-based, fully distributed model). Each model was used to simulate 41 selected runoff episodes recorded in each of the two catchments, and subsequently calibrated to yield parameter values that maximize the correlation between the simulated and observed runoff peaks. Our results indicate that, despite calibration, the hydrographs derived from all models deviated considerably from actual observations, and on the basis of inter-event fluctuations, which furthermore lacked a conspicuous dependence on the magnitude of runoff peaks. Our findings suggest that, in the absence of information on rainfall distribution and soil moisture, distributed models may not be superior to lumped ones in forecasting runoff responses of field scale catchments; and the correspondence between runoff mechanisms and model representations needs to be better understood and accounted for in order to limit the uncertainties of model predictions.
DE: 1800 HYDROLOGY
DE: 1854 Precipitation (3354)
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting