To overcome the limitations of existing research in effectively addressing the high-dimensional and nonlinear hydraulic processes in open-channel sections of water transfer projects under water diversion disturbances during the icing period， and the high reliance on manual experience in actual operations， this study takes the Wangnou-ruwugou section of the Jiaodong Water Transfer Project as a case study to investigate real-time intelligent hydraulic regulation of gate-pump groups in open channels. Through one-dimensional hydrodynamic simulations of gate-pump groups， step disturbances were applied to the diversion flows of canal pools to reveal the coupling mechanism between hydraulic processes in open channels and the operational responses of gate-pump groups under various diversion disturbances， and thus determine safety thresholds for water diversion disturbances during the icing period. On this basis， a real-time intelligent regulation model for gate-pump groups in open channels was developed by coupling a hydraulic model with a deep reinforcement learning algorithm， which excels at handling nonlinear， high-dimensional problems and requires minimal modeling data. The robustness of the proposed model was validated under various operational conditions. Application results demonstrate that the derived scheduling strategy effectively raises and stabilizes the water level at control sections to the target ice-period regulation level while ensuring operational safety and reducing the gate adjustment frequency.