Significant climate variations have decreased the stability of water resource systems, leading to multiple uncertainties in streamflow response, reservoir operation optimization, decision-making, and adaptive adjustments for water resource scheduling. Understanding the impact of climate change on reginal streamflow is necessary and crucial to identifying reservoir operation strategies and decision-making responses. In this study, we created an integrated systematic “uncertain streamflow responses”– “reservoir operation”– “optimization”– “decision-making risk analysis” chain. Three bias-corrected and downscaled general circulation models (GCMs) were used to analyze the inter-model uncertainties under three representative concentration pathways (RCPs). The streamflow responses and uncertainty in the future were determined using a distributed hydrological model and the fuzzy extension principle under predefined scenarios and uncertainty levels. Then, a stochastic simulation model and modified stochastic multi-criteria decision-making model were applied to identify the effects of climate change projections and streamflow responses on reservoir multi-objective operation and decision-making. Moreover, risk quantification indices were used to determine the uncertainty propagation and potential risks accumulated in the chain. We applied this framework to cascade reservoirs in the Qing River Basin. The results indicate that the mean annual streamflow projected using selected GCMs will increase, enhancing the hydropower response and weakening the ecological benefit response. The Pareto non-dominated solutions optimized based on the streamflow projections obtained using the GCMs (under the same RCP) and hydrological model are more distinct than those based on different RCPs and the same GCM. Moreover, a high emission scenario may increase the uncertainty of the streamflow projections and reservoir operation responses, which is consistent with the finding that the decision-making process becomes more variable and sensitive with increasing streamflow uncertainty. Finally, we identified the preferred solutions for reservoir operation under different uncertainties, the respective expected values, and the 95% confidence interval bands to enhance the adaptability of future reservoir operation.
Bibliographical noteFunding Information:
This work is supported by the National Natural Science Foundation of China (Grant No. 52109034), Chinese Universities Scientific Fund (Grant Nos. 2452021085, 2452021086), Shaanxi Province Department of Science and Technology (Grant No. 2023-JC-QN-0572), Cyrus Tang Foundation, State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University (Grant No. SKHL2112), and Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province (Grant No. GORS202101). The authors appreciated for the insightful comments and suggestions from editors and anonymous reviewers.
© 2023 Elsevier B.V.
- Adaptive reservoir operation
- Climate change
- Risk analysis
- Stochastic decision-making
- Uncertain streamflow responses
ASJC Scopus subject areas
- Water Science and Technology