Abstract

Climate change can affect the amount of rain intensity and inflow discharge into reservoirs. The Statistical Downscaling Model (SDSM) method is used to predict future rainfall data using GCM CanESM5 data under three greenhouse gas scenarios, namely SSP2.6, SSP4.5, and SSP8.5. Future rainfall projections show increasing values in the SSP4.5 and SSP8.5 scenarios in the 2030s and 2060s. The flow of inflow discharge into the reservoir can influence the value of annual cropping intensity and rule curve. Reservoir water availability was calculated by converting rainfall variations into discharge data using the F.J. Mock model. Inflow discharge for wet, dry, and normal years was then created using the Weibull method. Simulation discharge using the F.J. Mock method is compared with the measured discharge data. The results show good agreement with correlation values of 0.956. The highest total cropping intensity values for each discharge scenario in dry, normal, and wet years were 278%, 300%, and 300%. The success of optimizing reservoir operations can be seen from the k-factor value for irrigation water needs and domestic water, which meets the minimum limit requirements, namely 0.70 and 0.85, and the reliability of the reservoir in serving these water needs reaches 100%.

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