AbstractThis paper evaluates several efficiency indexes of hydropower energy generation in Iran’s Karkheh Basin water reservoir system (i.e., Seymareh and Karkheh Rivers) under climate change based on the system dynamics approach. The climate change effects are investigated with simulations of surface temperature and rainfall driven by downscaled climate projections from atmosphere–ocean circulation models in the current literature, and the models with the highest correlation and lowest error for rainfall and temperature in the 1976–2005 baseline period are identified. Rainfall and temperature are projected over two future periods, 2040–2069 and 2070–2099, and are downscaled to basin scale. Results project that the basin temperature over future periods will be higher than in the baseline period. Downscaled results under climate change indicate that rainfall will not follow a specific pattern. An artificial neural network applied to predict runoff indicates that the runoff and flood peak will decrease. Software is implemented to simulate the operation of hydropower reservoirs in baseline and future periods. Five reservoir operation states are considered, with simulation results of energy production showing that runoff and energy production have a complex pattern. Seven indexes of hydropower reservoir efficiency are also calculated for the five operation states corresponding to targets of energy production.

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