Reservoir systems across the United States and globally face mounting pressure from non-stationary hydrology, shifting demands, aging infrastructure, and expanding multi-objective mandates spanning flood risk management, water supply, hydropower, ecological flows, recreation, and navigation. Meeting these challenges requires tighter integration between hydrologic science, engineering practice, and operational decision-making. This session invites contributions that advance the science and practice of water management and reservoir operations. We welcome work on a wide range of topics including but not limited to forecast-informed operations, ensemble streamflow prediction, machine learning informed decision support, digital twins, large-sample and continental-scale modeling, multi-objective optimization under deep uncertainty, and emerging AI technologies. We are particularly interested in studies that bridge research and operations, including case studies from private, federal, state, and local water management organizations and agencies.  In addition, we are also interested in methodological advances that can be translated into open operational tools and platforms.