Precipitation is essential for hydrological streamflow simulation, but data scarcity in some regions limits ground-based observations. High-resolution satellite-based precipitation products (SPPs) and reanalysis precipitation products (RPs) provide alternative data sources. In this study, the accuracy of eight SPPs and RPs, is evaluated to simulate streamflow using HBV and SWAT hydrological models in two semi-arid river basins in southeastern Iran. The study compared these SPPs and RPs to rain gauge datasets using statistical and contingency indices. ERA5 and NOAA CPC perform best in capturing daily precipitation for both river basins, with higher correlations, lower root mean square error (RMSE), and better ability to identify rain events. GPM and CHIRPS have the best total mean error (ME) and PBIAS scores for both basins. At the monthly scale, ERA5 and GPM show the best agreement with the rain gauge dataset in the two basins. The ability of RPs to accurately capture daily streamflow demonstrates their potential as a source of precipitation for feeding hydrological models. The best efficiency for the streamflow simulation is obtained when the ERA5 reanalysis and the HBV model were combined. However, CMORPH performed poorly, producing an unsatisfactory streamflow simulation due to high PBIAS and low NSE. Bias correction of satellite precipitation inputs improved the accuracy of streamflow simulations, but even with this correction, satellite precipitation inputs still resulted in lower accuracy than rain gauge data inputs. Results will benefit developers, users, and the hydrological modeling community in data-poor regions.
کلید واژگان :Reanalysis precipitation products · Satellite-based precipitation products · Hydrological modeling2
ارزش ریالی : 500000 ریال
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