<p dir="ltr">Reservoirs play a vital role in water resource management, serving essential functions such as flood mitigation, water supply, power generation, and environmental conservation. In the U.S., many of these structures were constructed in the 1900s, and were primarily designed as single purpose facilities for flood risk reduction. Facing increasing threats of water shortages and groundwater depletion, the transition of these reservoirs to multi-purpose operations has never been more imperative. Operational modifications and optimizations emerge as a promising solution, offering cost-effectiveness, swift implementation, and minimal ecological disruption.</p><p dir="ltr">This dissertation advances the theory and framework of modification and optimization of reservoir operations to facilitate their transition from single to multi-purpose use. This dissertation begins with targeted optimization of static operations and progressively advances to dynamic strategies across complex multi-reservoir-river systems. This dissertation sets three primary objectives: (1) To develop a comprehensive framework for assessing the conversion potential of single-purpose reservoirs and optimizing static operation strategies for enhanced multi-purpose functionality. (2) To devise dynamic control strategies that bolster reservoir performance during extreme events through the implementation of inflow-based pre-release operations. (3) To employ a Multi-Objective Simulation-Optimization (MOSO) framework that integrates large-scale datasets and advanced optimization algorithms, optimizing multi-purpose, multi-reservoir operations in complex systems and enhancing decision-making through Multi-Criteria Decision-Making (MCDM) methods.</p><p dir="ltr">In the first objective, a robust framework is developed to evaluate and facilitate the conversion of single-purpose reservoirs into multi-purpose systems. Leveraging historical data, the proposed framework establishes Maximum Safe Water Levels (MSWLs) to optimize flood control while enhancing water supply capabilities. The methodology incorporates numerical reservoir simulation models alongside historical inflow data analysis of 15 reservoirs operated by the U.S. Army Corps of Engineers, Louisville District, all originally designed exclusively for single-purpose flood control. The findings reveal opportunities for some reservoirs to significantly increase their water supply without compromising flood management efficiency.</p><p dir="ltr">The second objective delves into dynamic control strategies for reservoir operation, with a focus on pre-release mechanisms. This objective utilizes inflow-based forecasting models to assess the impacts of different pre-release timings on flood mitigation. This study focuses on 11 of the reservoirs identified in the first objective as having potential for transition to multi-purpose use, exploring dynamic operational adjustments necessary for enhanced performance. The results show that a 72-hour pre-release lead time markedly enhanced flood control effectiveness, whereas a 24-hour lead time provides a practical compromise, achieving substantial flood mitigation with minimal adverse impacts.</p><p dir="ltr">The third objective involves developing an advanced framework utilizing the Multi-Objective Simulation-Optimization (MOSO) model and extensive datasets to optimize pre-release operations in multi-purpose reservoirs. Implementing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Criteria Decision-Making (MCDM) methods, the framework integrates reservoir simulation models and flow routing to refine operations based on projected flood forecasts. Applied to the Green River watershed in Kentucky, this method produces Pareto-optimal solutions, elucidating the trade-offs between flood control, water supply reliability, and downstream channel performance. The results underscore the framework’s potential to significantly refine operational strategies, bolstered by sensitivity analyses that explore the effects of varying storage levels and inflow conditions, thus fostering adaptive, data-driven management for sustainable water resource optimization.</p><p dir="ltr">This dissertation contributes to the field of water resource management by demonstrating and developing innovative strategies and frameworks for the transition of single purpose reservoirs to multi-purpose systems, modifying flood control and enhancing water supply capabilities. This dissertation provides practical solutions with available data, simulation models, and optimization tools, which enable effective decision-making and operational adjustments under varying conditions. Overall, this dissertation presents a foundation for more resilient, reliable, and adaptive water management practices for reservoirs, that can meet diverse demands in a changing environmental landscape.</p>