This study develops a robust modeling and stabilization framework for an interconnected lake-aquifer system in the field of hydrology. The conventional lake-aquifer dynamics are transformed into a multi-input multi-output linear time-invariant model with a bounded uncertainty. The robust performance of the system is obtained through an H-infinity controller to address a bounded model uncertainty, satisfactory reference input tracking and disturbance rejection behaviour, and maximum profitability of the water extraction process. The robust optimization design results demonstrate that the designed robust controller maintains the desired aquifer level under a bounded model uncertainty and an exogenous input excitation while maximizing the corresponding environmental utility. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for policy makers during efficient water management policy decisions, maximizing economical benefits while ensuring sustainable social, biological and environmental activities.