Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model

• Main Authors: Ehteram, M., El-Shafie, A.H., Hin, L.S., Othman, F., Koting, S., Karami, H., Mousavi, S.-F., Farzin, S., Ahmed, A.N., Zawawi, M.H.B., Hossain, M.S., Mohd, N.S., Afan, H.A., El-Shafie, A.
• Format: Article
• Language: English
• Published: 2020

Climate change is one of the most effectual variables on the dam operations and reservoir water system. This is due to the fact that climate change has a direct effect on the rainfall-runoff process that is influencing the water inflow to the reservoir. This study examines future trends in climate change in terms of temperature and precipitation as an important predictor to minimize the gap between water supply and demand. In this study, temperature and precipitation were predicted for the period between 2046 and 2065, in the context of climate change, based on the A1B scenario and the HAD-CM3 model. Runoff volume was then predicted with the IHACRES model. A new, nature-inspired optimization algorithm, named the shark algorithm, was examined. Climate change model results were utilized by the shark algorithm to generate an optimal operation rule for dam and reservoir water systems to minimize the gap between water supply and demand for irrigation purposes. The proposed model was applied for the Aydoughmoush Dam in Iran. Results showed that, due to the decrease in water runoff to the reservoir and the increase in irrigation demand, serious irrigation deficits could occur downstream of the Aydoughmoush Dam. © 2019 by the authors.