Scale dependencies of hydrologic models to spatial variability of precipitation

This study is focused on analyses of scale dependency of lumped hydrologica l models with different formulations of the infiltration processes. Three l umped hydrological models of differing complexity were used in the study: t he SAC-SMA model, the Oregon State University (OSU) model, and the simple w ater balance (SWB) model. High-resolution (4 x 4 km) rainfall estimates fro m the next generation weather radar (NEXRAD) Stage III in the Arkansas-Red river basin were used in the study. These gridded precipitation estimates a re a multi-sensor product which combines the spatial resolution of the rada r data with the ground truth estimates of the gage data. Results were gener ated from each model using different resolutions of spatial averaging of ho urly rainfall. Although all selected models were scale dependent, the level of dependency varied significantly with different formulations of the rain fall-runoff partitioning mechanism. Infiltration-excess type models were th e most sensitive. Saturation-excess type models were less scale dependent. Probabilistic averaging of the point processes reduces scale dependency, ho wever, its effectiveness varies depending on the scale and the spatial stru cture of rainfall. (C) 1999 Elsevier Science B.V. All rights reserved.