The state of the art for optimal water reservoir operations is rapidly evolving, driven by emerging societal challenges. Changing values for balancing environmental resources, multisectoral human system pressures, and more frequent climate extremes are increasing the complexity of operational decision making. Today, reservoir operations benefit from technological advances, including improved monitoring and forecasting systems as well as increasing computational power. Past research in this area has largely focused on improving solution algorithms within the limits of the available computational power, using simplified problem formulations that can misrepresent important systemic complexities and intersectoral interactions. In this study, we review the recent literature focusing on how the operation design problem is formulated, rather than solved, to address existing challenges and take advantage of new opportunities. This paper contributes a comprehensive classification of over 300 studies published over the last years into distinctive categories depending on the adopted problem formulation, which clarifies consolidated methodological approaches and emerging trends. Our analysis also suggests that control policy design methods may benefit from broadening the types of information that is used to condition operational decisions, and from using emulation modeling to identify low‐order, computationally efficient surrogate models capturing realistic representations of river basin systems' complexity in order to isolate key decision‐relevant processes. These advances in reservoir operations hold significant promise for better addressing the challenges of conflicting human pressures and a changing world, which is particularly important, given the renewed interest in dam construction globally. Key Points We review the evolution of water reservoir operation studies driven by emerging societal challenges Simulation‐based control methods facilitate realistic problem formulations that are able to handle system uncertainties Research opportunities remain to combine policy design with more information sources and emulation modeling