A noncalibrated rainfall-runoff model for large, arid catchments

A distributed, field-based rainfall-runoff model was developed for the 1400-km(2) arid catchment of Nahal Zin, Israel. No calibration with measured flow data was performed. The model used rainfall radar input applied over a catchment that was spatially disaggregated into different terrain types according to hydrologically relevant surface characteristics. Hortonian overland flow generation on each type was parameterized independently using values of initial loss and temporal decay of infiltration determined from existing field experiments. Delimited by topography, this catchment wide pattern of rainfall excess was distributed over 850 tributary catchments (model elements). Runoff delivery from the model elements to the adjoining channel segments was timed by applying a mean response function determined in an environmentally similar experimental catchment. Inside the channel network the MVPMC3 method of the Muskingum-Cunge technique was used for streamflow routing, accounting for channel dimensions and roughness. For each channel segment a constant infiltration rate was applied to account for transmission losses and discontinued when the wetting front reached the bottom of the available alluvial storage. Within two model tests, one separate for the routing component (October 1979) and one for the complete model (October 1991), observed hydrographs and reconstructed peak discharges were successfully simulated. The spatially distributed model output showed that during the October 1991 test, tributaries produced preceding peaks that wetted the channel alluvium before the main flood had arrived and transmission losses lost their significance downstream. Total maximum model uncertainty was estimated including the uncertainty ranges of each model parameter. In general, this study shows that field-based data on generation and losses of runoff may be incorporated into a distributed hydrologic model to overcome calibration with the poor data records of arid high-magnitude events.