Trade-Offs in the Water-Energy-Ecosystem Nexus for Cascade Hydropower Systems: A Case Study of the Yalong River, China - Wu, Xiufeng; Yu, Lei; Wu, Shiqiang; Jia, Benyou; Dai, Jiangyu; Zhang, Yu; Yang, Qianqian; Zhou, Zehui (Frontiers in Environmental Science, 2022)
The hydropower system's water-energy-ecosystem nexus (WEEN) has gained particular focus in the last years. The water-use trade-offs between hydropower and ecosystem maintenance are complex and variable for cascade hydropower systems, leading to challenges in water resources management and sustainable development of hydropower. To understand the trade-off in the WEEN of cascade hydropower systems and their changes, a WEEN model using the multi-objective optimization approach is developed in this study, including maximizing cascade power generation, minimizing reservoir water footprint, and minimizing amended annual proportional flow deviation. These optimization objectives characterize the nexus's water, energy, and ecosystem sectors. And the Pareto non-inferiority solutions are obtained by the third edition of the Non-dominated Sorting Genetic Algorithm. Also, we novelly propose an evaluation index called the Multi-objective Trade-off Index (MTI), a quantitative method with clear physical meaning to explore the trade-offs as revealed between different objectives by the solutions. A case study of the Yalong River, China, has shown that: a) the larger the incoming water is, the more beneficial to the power generation and ecological benefits of the hydropower system; and b) the trade-off degrees of the water sector with respect to energy-ecosystem and energy sector with respect to water-ecosystem decreases when the hydrological condition changes from wet to dry, while the degree of ecosystem sector with respect to water-energy increases. In general, the proposed MTI that quantifies trade-offs in the WEEN of cascade hydropower systems is efficient and feasible. Meanwhile, the MTI is also generic and can be applied to other multi-objective optimization problems.