A Multi-Objective Optimization and Evaluation Framework for Sustainable Cascade Reservoir Operation: Evidence from the Lower Jinsha River

Abstract

Climate variability and growing competition for limited water resources have made the operation of cascade reservoirs increasingly complex. This study develops a comprehensive system-based multi-objective optimization and evaluation framework that simultaneously integrates five goals: power generation, water supply, ecological protection, navigation reliability, and flood control as a constraint. The framework employs the NSGA-III evolutionary algorithm to address the high-dimensional optimization problem and combines Analytic Hierarchy Process (AHP), Entropy Weight Method, and TOPSIS to integrate subjective expertise with objective data in the evaluation of alternatives. Applied to the lower Jinsha River cascade under wet, normal, and dry hydrological scenarios, the model reveals distinct conflicts between hydropower and ecological or navigational requirements, partial synergies between hydropower and water supply, and tension between ecological and supply demands. Hydrological variability alters these relationships, with wet years intensifying conflicts and dry years heightening supply and ecological pressures. Functional differentiation among reservoirs is also evident, with Baihetan and Xiluodu showing pronounced power–ecology tensions, while Xiangjiaba primarily supports supply and navigation. The study not only advances the theory of multi-objective decision-making in water resources systems but also offers actionable guidance for sustainable reservoir governance and regional development.