Comparative Assessment of Optimal Reservoir Rule Curves Under Future Hydrological Conditions in Thailand and Lao PDR

Reservoir rule curves are important tools for guiding water storage and release, especially under changing hydrological conditions. In this study, the future optimal rule curves and hydropower performance of two reservoirs are compared based on their different physical and operational characteristics: the Nam Khan 2 Reservoir in Lao PDR and the Ubolrat Reservoir in Thailand. A reservoir simulation model was linked with the Genetic Algorithm (GA) and Bat Algorithm (BA) to derive optimal rule curves under historical and future inflow conditions. Future inflows were evaluated for a 30-year period from 2026 to 2055, with the objective of maximizing hydropower generation. The results show that the GA and BA produced similar seasonal rule curve patterns for each reservoir, although differences from the existing curves were observed in response to future inflow and reservoir characteristics. Under the future scenario, Nam Khan 2 achieved an average hydropower generation per unit inflow of 284,082 ± 62,691 kWh/MCM with the GA and 273,471 ± 61,790 kWh/MCM with the BA compared with 36,476 ± 6064 and 35,999 ± 5466 kWh/MCM, respectively, for Ubolrat. The results also show substantial differences in hydropower generation per unit storage between the two reservoirs. These differences indicate that reservoir size, inflow characteristics, water release, storage level, and hydraulic head influence hydropower performance. Overall, both optimization methods provide comparable operating patterns, while the different responses of the two reservoirs demonstrate the importance of developing rule curves according to reservoir-specific physical and hydrological conditions. The proposed comparative framework can support more adaptive and efficient reservoir operation under future hydrological change.