Based on the criteria suggested by Moriasi et al. (2007), the accuracy of SWAT-CUP models was evaluated by different statistical parameters, such as R², NSE, PBIAS, RMSE, and RSR. A comparison of the calibration and validation results of the different SWAT-CUP models are shown in Table 6. In both calibration and validation phases, CHIRPS, PERSIANN, and GPM models showed satisfactory to good competence in computing streamflows with R², NSE, PBIAS, and RSR varying from 0.68 to 0.70 and 0.75 to 0.78, 0.62 to 0.67 and 0.73 to 0.76, −19.0 to −8.20% and −10.50 to +7.0%, and 0.57 to 0.62 and 0.49 to 0.52, respectively. Furthermore, the performance of the CMORPH model was poor, especially in its calibration phase, as the lowest R² was 0.45 and NSE was 0.36, and highly underestimated streamflow prediction with PBIAS −22.6%. Based on Figure 6 and Table 6, the GPM model performed slightly better than the CHIRPS and PERSIANN models with a higher R² and NSE, acceptable PBIAS and minimum RMSE and RSR. Previous studies by Popovych & Dunaieva (2021), Saddique et al. (2022), and Tang et al. (2020) have shown similar results.