Hydrological Modeling in the Chaohu Lake Basin of China—Driven by Open-Access Gridded Meteorological and Remote Sensing Precipitation Products

This study assessed the performance of two well-known gridded meteorological datasets, CFSR (Climate Forecast System Reanalysis) and CMADS (China Meteorological Assimilation Driving Datasets), three satellite-based precipitation TRMM (Tropical Rainfall Measuring Mission), CMORPH Prediction Center morphing technique), CHIRPS Hazards Group InfraRed Precipitation with Station data), in driving SWAT (Soil Water Assessment Tool) model for streamflow simulation Fengle watershed middle–lower Yangtze Plain, China. Eighteen scenarios were generated by forcing different combinations datasets six datasets. Our results showed that (1) (i.e., TRMM, CMORPH, CHIRPS) generally provided more accurate estimates than CMADS. agreed fairly well gauged measurements maximum temperature, minimum relative humidity, but large discrepancies existed solar radiation wind speed. (2) The impact data on simulated was much larger other variables. Satisfactory simulations achieved using daily monthly simulation. suggests can be used optimal at temporal scales.