Determining the most effective flow rising process to stimulate fish spawning via reservoir operation

Various studies have shown that stream flow regimes play a significant role in fish spawning stimuli. Stream flows have been altered by reservoir operations around the world, especially in arid and semi-arid regions. In this study, the flow rising processes most effective for fish spawning stimuli are identified, and their quantitative characteristics are then represented by a set of hydrological indices. Based on a quantitative ecological scoring method describing the statistical similarity between the reservoir release and the natural flow regime, a multi-objective optimization model considering hydropower generation and fish habitat protection is proposed and then solved by the Non-dominated Sorting Genetic Algorithm (NSGA-II). The proposed methodology is applied to a large-scale reservoir on the upper reaches of the Yellow River in China. The statistics of these indices verify the regulations on the flow rising processes in fish spawning seasons via reservoir operation in different hydrological years. The Pareto Front derived from the multi-objective optimization indicates that it is possible to both improve the local ecology and increase hydropower generation profits using the method proposed herein on the basis of proper understanding of the effective flow process required by fish.