Evaluation, bias correction and application of satellite precipitation product TRMM_3B42_V7 for extreme event-based hydrologic model in context of semi-arid region, Rajasthan, India

The understanding and identification of peak streamflow events are important for flood risk and water resources management. Precipitation products based on the radar and satellite are an alternative or supplementary product to the areas where ground-based rain gauge station is unavailable, limited in number or sparsely located. The objectives of this study are to (1) assess the performance of TRMM_3B42 product for selected seven flood events by use of statistical and categorical matrices, and identification of elevation-related trends in them and (2) drive the HEC-HMS model by use of bias-corrected TRMM_3B42 data to reproduce the flood hydrograph in Banas River Basin, semi-arid region, Rajasthan, India. The bias-corrected TRMM_3B42 data have improved the overall accuracy of hydrologic simulation as compared to ground-based rain gauge station data. The HEC-HMS results revealed that bias-corrected TRMM_3B42 data can simulate the streamflow with less than 30% deviation in the prediction of peak discharge and flood volume and show an NSE and R² value of 0.90 and 0.95, respectively. The bias-corrected TRMM_3B42 data are found to be excellent to reproduce the flood hydrograph at a daily temporal scale.