The performance evaluation of the different SWAT-ANN hybrid models for predicting daily streamflow at the training and testing phase is given in Table 7. According to Moriasi et al. (2007) criteria, GPM, PERSIANN, and CHIRPS SWAT-ANN hybrid models demonstrated very good competence in computing streamflows. As a result of the training and testing period, the performance indices R², NSE, PBIAS, and RSR for GPM, PERSIANN, and CHIRPS SWAT-ANN hybrid models ranged from 0.86 to 0.90 and 0.82 to 0.89, 0.86 to 0.90 and 0.81 to 0.89, −0.53 to −0.02% and −0.4 to 5.16%, and 0.31 to 0.37 and 0.34 to 0.44, respectively. Furthermore, the performance of the CMORPH SWAT-ANN model was improved from satisfactory to good when compared with the calibrated SWAT-CUP model in predicting streamflow. The outcomes (Tables 6 and 7) revealed that the SWAT-ANN hybrid models are much better than the calibrated SWAT-CUP model.