The Upper Blue Nile River Basin is confronted by land degradation problems, insufficient agricultural production, and limited number of developed energy sources. Process-based hydrological models provide useful tools to better understand such complex systems and improve water resources and land management practices. In this study, SWAT was used to model the hydrological processes in the Upper Blue Nile River Basin. The calibration was done in such a way that the parameterization had a realistic representation of the interaction of land cover and soils properties. Comparisons between a Climate Forecast System Reanalysis (CFSR) and a ground weather dataset were done under two subbasin discretizations (30 and 87 subbasins) to create an integrated dataset to improve the spatial and temporal limitations of both datsets. A SWAT Error Index (SEI) was also proposed to compare the reliability of the models under different discretization levels and weather datasets. This index offers an assessment of the model quality based on precipitation and evapotranspiration. SEI demonstrates to be a reliable and useful method to measure the level of error of SWAT and develop better models. The results showed the discrepancies of using different weather datasets with different levels of subbasin discretization. Datasets under 30 subbasins achieved Nash-Sutcliff (NS) values of 0.15, 0.68 and 0.82; while models under 87 subbasins achieved values of 0.05, 0.61, and 0.84, for the CFSR, ground and integrated datasets, respectively. Based on the parameterization, the integrated dataset provided more reliable results and a more realistic representation of the land use and soil conditions of this region.