Rainfall-runoff modeling is a tool for flood prediction, and risk minimization. In this study, the Soil and Water Assessment Tool (SWAT) model was used to determine the factors affecting runoff. For this purpose, spatial data including Digital Elevation Model (DEM), land use, and soil were obtained from reliable sources and finalized in ArcGIS software. Then, climatic data including precipitation, maximum and minimum temperature, relative humidity, wind speed, evapotranspiration, and solar radiation were obtained from various meteorological stations. The model calibrated using the SUFI2 algorithm and then the model validation and sensitivity analysis were carried out. The model performance was evaluated using statistical evaluation criteria including RMSE, R2 and NSE. The results of the model sensitivity analysis showed that the model is sensitive to 16 of the 23 parameters. Also, the model simulation during the calibration and validation period with RMSE values ​​of 18.01 and 53.93 and R2 values ​​of 0.85 and 0.91 and NSE coefficients of 0.72 and 0.36 indicate the model performance in the rainfall-runoff simulation in the studied basin. Given the arid and semi-arid climate of Iran and the limited water resources, there is a need to identify the most important components in the process of converting precipitation into runoff. Therefore, the SWAT model can be considered a useful tool in determining these components and can be used in rainfall-runoff simulation for water resources planning and management.