Adapting reservoir operations to the nexus across water supply, power generation, and environment systems: An explanatory tool for policy makers.

• Reservoir operations are adapted to the nexus across water supply, power generation, and environment systems. • Dynamic weights for multiple objectives are considered for reservoir operations within the framework of the WPE nexus. • Tradeoffs across WPE systems and reservoir operational decisions shift from stage to stage. • The control parameter that dominates the shift in the stable levels of a given variable can be identified. Reservoir operation plays an important role in the coevolution of the nexus across water supply, power generation, and environment (WPE) systems. This paper aims to contribute to the state-of-the-art in how multi-objective reservoir operation can be modeled within the framework of the WPE nexus by incorporating the interactions among reservoirs operation, stakeholders' decision preferences, and WPE systems. Specifically, five ordinary differential equations are used to describe the dynamics of WPE states. These dynamics are driven by a multi-objective optimization model that optimizes reservoir operation decisions. Two novel response linkages that describe how the reservoir operational decisions influence socio-economic variables and how the environmental awareness influences stakeholders' preference for reservoir operation are proposed in this study. The Middle Route of China's South-to-North Water Transfer Project is selected as the case study. The results show that: (1) response linkages are effective in describing the interactions between reservoir operational decisions and WPE systems, (2) tradeoffs across WPE systems and reservoir operational decisions shift from stage to stage because of the changing socio-economic conditions, and (3) the control parameter that dominates the shift in stable levels of a given variable can be identified. These results highlight the importance of re-evaluating involved tradeoff effects and updating of operational policies periodically, and how our modeling approach can be used to detect and guide such adaptions. [ABSTRACT FROM AUTHOR]