A MONTE-CARLO STUDY OF RAINFALL SAMPLING EFFECT ON A DISTRIBUTED CATCHMENT MODEL

A Monte Carlo study of a physically based distributed-parameter hydrologic model is described. The catchment model simulates overland flow and streamflow, and it is based on the kinematic wave concept. Soil Conservation Service curves are used to model rainfall excess within the basin. The model was applied to the Ralston Creek watershed, a small (7.5 km2) rural catchment in eastern Iowa. Sensitivity of the model response with respect to rainfall-input spatial and temporal sampling density was investigated. The input data were generated by a space-time stochastic model of rainfall. The generated rainfall fields were sampled by the varied-density synthetic rain gauge networks. The basin response, based on 5-min' increment input data from a network of high density with about 1 gauge per 0.1 km2, was assumed to be the "ground truth," and other results were compared against it. Included in the study was also a simple lumped parameter model based on the unit hydrograph concept. Results were interpreted in terms of hydrograph characteristics such as peak magnitude, time-to-peak, and total runoff volume. The results indicate higher sensitivity of basin response with respect to the temporal resolution than to the spatial resolution of the rainfall data. Also, the frequency analysis of the flood peaks shows severe underestimation by the lumped model. This may have implications for the design of hydraulic structures.