Climate change results in reservoir management challenges, especially in areas with a high risk of drought and flooding. Traditional reservoir rule curves are insufficient for addressing variations in reservoir inflow. This study presents a framework combining GCMs from CMIP6 (ACCESS-CM2, MIROC6, and MPI-ESM1-2-LR) under SSP2-4.5 and SSP5-8.5 scenarios and WEAP, the accuracy of which has been validated for reservoir inflow and storage capacity. This framework is integrated with Hippopotamus Optimization (HO) to develop a resilience reservoir rule curve (RRRC) for the Ubolrat Reservoir for 2024–2055, employing a dual-objective function that emphasizes reducing water shortages and water excess. The results indicate that the RRRC developed via HO is more efficient and suitable than Honeybee Mating Optimization (HBMO) and existing rule curves. When tested with historical inflow data, HO reduced the average water shortage by 50% and the maximum shortage period by 79% compared to the existing rule curve. Under future climate scenarios (SSP2-4.5 and SSP5-8.5), efficiency improved significantly, achieving a water shortage reduction of 95–98% and a shortage period reduction of 83–88%. Additionally, HO demonstrated outstanding efficiency in water excess management, with a 7–11% reduction in average excess water. This potential reflects its adaptability in the context of future variations in hydrological conditions. This crucial finding illustrates that the integrated framework can develop resilient rule curves even under uncertainty. HO integrated with various models can be implemented as an optimal framework with high potential for reservoir operation planning under climate change. The developed methodology can be implemented in other reservoirs to investigate additional factors for the sustainable promotion of water resource resilience.
Prasanchum et al. (Thu,) studied this question.