A Hybrid Model-Based Adaptive Framework for the Analysis of Climate Change Impact on Reservoir Performance

Climate change and population growth have influenced social and physical water scarcity in many regions. Accordingly, the future performance of water storage reservoirs, as one of the fundamental elements in the water resource management, are anticipated to be affected by climate change. This study reports on a framework that can model Reliability-Resiliency-Vulnerability (RRV) measures of water reservoirs in the context of climate change. The framework first develops a hydrological model of a reservoir system using its historical data. The model is then optimised to minimise the water deficit and flooding around the catchment area of the reservoir. The resulting optimal policies are simulated back to the model considering the GCMs. Finally, RRV indices are calculated. RRV indices are effective measures for defining the performance of reservoir systems. Reliability is defined as the probability of the failure of the system, Resiliency is defined as the time needed for the system to go back to its satisfactory state once it entered the failure state, and Vulnerability is defined as the "magnitude of the failure" of a system. The proposed framework has been applied to a reservoir system located in the south-west of Iran on the Dez river. The results show climate change may increase the reliability and resiliency of the system under study while increasing its vulnerability. Therefore, the output of this framework can also provide supplementary information to authorities and decision-makers to inform future water management and planning policies.