Precipitation data is a primary influencing factor in hydrological modeling. However, the sparse distribution of surface hydrological stations and the lack of available data constrain the development of watershed models and the management and allocation of water resources. This study employs statistical metrics to evaluate discrepancies between observed precipitation data and multi-source precipitation products (CMADS, ERA5, GPM IMERG, and TRMM). It identifies highly sensitive parameters in the SWAT model established using observed hydrological data and quantitatively assesses runoff simulation performance in the Manas River Basin using the coefficient of determination and Nash index. Results indicate the following: (1) CMADS and TRMM exhibit good overall trends within a year. For multi-year monthly precipitation averages, CMADS performs best at monthly and seasonal scales (CC > 0.7), while TRMM performs best at the annual scale (CC > 0.75). (2) At spatial scales, IMERG shows the poorest performance compared to observed stations, and ERA5 exhibits anomalous points. (3) TRMM achieved the best monthly runoff simulation performance in the Manas River Basin, with an average NSE value of 0.73, average R² of 0.80, and average KGE of 0.80. This study provides valuable scientific support for hydrological forecasting in data-scarce regions with complex topography and similar climate variability.