High spatial and temporal resolution satellite products provide useful rainfall information for dispersed or ungauged large-scale river basins. In the Belles basin, the rainfall stations are scarce and distributed unevenly and the cross-border feature makes it difficult to collect precipitation data, which has inadequate the simulation of hydrological processes. In this study, the daily rainfall data taken from six datasets (gauge observations, Climate Prediction Center Morphing Method (CMORPH), Tropical Rainfall Measuring Mission (TRMM3B42V7) estimates, Climate Forecast System Reanalysis(CFSR) and Precipitation Estimation using Remote sensing information of Artificial Neural Network (PERSIANN) estimates), were applied to drive the Soil and Water Assessment Tool plus (SWAT+) model, and then the capability for hydrological simulation from 6 gauge station in Belles watershed located in Ethiopia was examined, from 2003 to 2011. TRMM3B42V7 and CMORPH data showed good performances on precipitation estimation in the Belles watershed compare with other satellite products within rainfall gauge. The Nash-Sutcliffe efficiency (NSE) values of rain gauge, CMORPH, TRMM3B42V7, CFSR and PERSIANN simulations during the calibration period were 0.88, 0.81, 0.80, 0.79 and 0.78 for monthly flow, respectively, and during validation period were 0.88, 0.87, 0.87,0.66 and 0.69, respectively. Satellite precipitation estimates could be suitable data sources to simulate hydrological processes for large or dispersed river basins, particularly in international river basins for which it is difficult to collect observations on precipitation. For satellite-based precipitation products, differences in frequencies of occurrence and amounts of precipitation with different intensities would affect the results of the simulation of the components of the water balance, which must be considered in an integral way in the estimation and planning of the water resources. The outcomes of the hydrological evaluation recommend that rainfall is a critical source of uncertainty in the SWAT + model and that the changed precipitation values produce uncertainty in the parameters, which is propagated to the forecast and management of uncertainties in water resources. The CMORPH product perform well, while PERSIANN and CFSR show low hydrological performance. Consequently, CMORPH works better than the other three satellite precipitation products in this study area.