Adaptive reservoir operating rules based on the Dempster-Shafer evidence theory

Since there is no consensus about how to assign weights in Global Circulation Model (GCM) ensemble, this paper uses the Dempster-Shafer (DS) evidence theory to synthesize the following three the basic probability assignment (BPA) methods:the equal probability, the probability for statistic characteristics of the mean annual inflow, and the probability based on the relative monthly inflow variation. Then, DS evidence theory-based Adaptive Operating Rules (DS-AOR) are derived, in order to mitigate the adverse effect of climate change. The objective is to maximize the weighted average annual hydropower generation for all future scenario, and then the Simulation-Based Optimization (SBO) method is implemented to optimize the parameters of DS-AOR. The case study of the Jinxi Reservoir shows that:under uncertain future climate change, DS-AOR is an effective and robust strategy. Compared with Historical Operating Rules (HOR) and adaptive operating rules based on Equal Weights (EW-AOR), DS-AOR results in an increase in hydropower benefits by 0.76×10⁸ kWh and 0.61×10⁸ kWh, and an increase in hydropower reliability by 0.5%-11.17% and 3.50%-9.34%, respectively, and it performs more robustly. It is concluded that DS-AOR facilitates adaptive reservoir management under climate change.