Optimal reservoir operation for transport timescales using an integrated methodology

Dam construction hinders the transport process of water constituents, resulting in various water quality issues in reservoir areas that impede the sustainable development of hydropower. Conventional reservoir operation optimizations to address these issues face challenges in mathematizing multiple water quality objectives and solving high-dimensional computational problems. Taking a comprehensive perspective, we propose a methodology that incorporates the concept of transport timescales into optimal reservoir operation. Firstly, a specific transport timescale is estimated through numerical tracer experiments using a 3D hydrodynamic model. Subsequently, a surrogate model is developed to approximate the hydrodynamic model for computationally efficient estimation. Finally, we employ a non-dominated ranking genetic algorithm, combined with the surrogate model, to search for a Pareto-optimal solution for multiple objectives. As a case study, we selected flushing time as the representation of transport timescales and applied it to Xiangxi Bay (XXB) in the Three Gorges Reservoir, which has experienced serious water quality problems since dam construction. Our results show that under the optimal operation scheme, the average flushing time for the entire XXB is 23.991 d, which represents a 10.9% reduction compared to the practical operation scheme. The reduction rate of flushing time along XXB shows a monotonically increasing trend towards the reservoir mainstream, with a maximum reduction of 90.9%. The proposed methodology provides a heuristic tool that links optimal reservoir operation and the transport process of holistic water constituents for comprehensive water quality management in reservoirs.