The present work is in the framework of water resource control and optimization. Specifically, an advanced process control system was designed and implemented in a hydroelectric power plant for water management. Two reservoirs (connected through a regulation gate) and a set of turbines for energy production constitute the main elements of the process. In-depth data analysis was carried out to determine the control variables and the major issues related to the previous conduction of the plant. A tailored modelization process was conducted, and satisfactory fitting performances were obtained with linear models. In particular, first-principles equations were combined with data-based techniques. The achievement of a reliable model of the plant and the availability of reliable forecasts of the measured disturbance variables—e.g., the hydroelectric power production plan—motivated the choice of a control approach based on model predictive control techniques. A tailored methodology was proposed to account for model uncertainties, and an ad hoc model mismatch compensation strategy was designed. Virtual environment simulations based on meaningful scenarios confirmed the validity of the proposed approach for reducing water waste while meeting the water demand for electric energy production. The control system was commissioned for the real plant, obtaining significant performance and a remarkable service factor.