<p>Precipitation is the most critical input for hydrological models. This study proposes an integrated framework for utilizing GPM-IMERG satellite precipitation data through re-gridding to improve runoff simulation in data-scarce basin. The HEC-HMS hydrological model was applied to the Eydanak catchment in southwestern Iran, focusing on four selected flood events. Two main factors were evaluated: the grid resolution (5000, 7500, 12,500, 15,000, and 17,500&#xa0;m) and the statistical re-gridding methods (Bilinear, Nearest, and Cubic). After calibrating the model and applying re-gridding, 16 precipitation datasets for each flood event were used for the rainfall-runoff simulation. The simulations were assessed based on hydrograph characteristics, including peak discharge difference and time-to-peak deviation, along with performance metrics, such as NSE, R², NRMSE, PBias, and rPFD. Results revealed that changes in grid resolution had a more significant impact on simulation accuracy than the choice of re-gridding method. Coarser grid resolutions than the original (10,000&#xa0;m) improved accuracy on average as follows: NRMSE (27.9%), NSE (44.3%) and rPFD (59.8%). The Cubic method exhibited superior performance compared to other re-gridding methods, yielding more accurate simulated discharges. These findings demonstrate the potential of re-gridding and advanced statistical methods to enhance hydrological modeling in low-data basins.</p>