Improving the accuracy of multimodel short-to-medium-range precipitation and streamflow forecasts over the Upper Bhima river basin, India

Abstract

Accurate precipitation forecasting with sufficient lead time is a prerequisite for developing a robust flood warning system (FWS), which is very challenging, particularly in developing countries like India. This study evaluates the utility of the TIGGE multimodel ensemble meteorological forecasts over the Upper Bhima river basin and investigated the hydrological utility of the TIGGE forecasts through a calibrated hydrological (VIC-RAPID) model followed by the postprocessing of streamflow through Bayesian model average (BMA) approach. Results show that the quality of the meteorological forecasts of precipitation, and simulated streamflow deteriorated with increasing lead time, which can be ameliorated with a suitable bias-correction technique. The BMA-based postprocessing further improved the streamflow simulations, especially in case of extreme events, which highlighted its efficacy in flood forecasting. From the results of the study, it is recommended that a compound system of improved precipitation prediction, calibrated VIC-RAPID model and postprocessing of streamflows in an integrated manner would facilitate a reliable FWS for operational purposes.