Abstract

A method to use a distributed hydrologic model in conjunction with threshold frequencies (DHM-TF) is proposed to improve the accuracy of flash flood forecasts at ungauged locations. The model produces high-resolution grids of peak flow forecast frequencies during rainfall events. Forecasters can compare these grids to locally derived threshold frequency (TF) grids to aid in warning decisions. TF grids may be derived from several sources of information such as known flood frequencies at selected river locations and local hydraulic engineering design standards. The proposed model characterizes flood severity at ungauged locations, and provides an inherent bias correction to reduce systematic errors in model predicted peaks. The distributed model basis for the approach offers advantages over current lumped model-based national weather service (NWS) flash flood guidance (FFG) procedures because it makes hydrologic calculations at spatial and temporal scales that are more commensurate with flash flooding. In this study, simulation results for 10 basins (eight nested) in Oklahoma and Arkansas, USA, were analyzed to (1) improve our understanding of distributed hydrologic model accuracy in small, interior basins, when forced by operational quality radar-based precipitation data, (2) validate that a distributed model can improve upon the lumped model-based NWS FFG, and (3) validate that the DHM-TF method can provide an inherent bias correction using available operational data archives to develop statistical parameters. We analyzed eight years of continuous hourly stream flow simulations and peak flows from 247 individual events. Both uncalibrated and calibrated distributed model results improved upon lumped model-based FFG at interior points. The DHM-TF method provided an average inherent bias correction for both uncalibrated and calibrated models in most basins examined. These positive results suggest that further development and testing of this technique should proceed.

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