Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model
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 c...
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my.uniten.dspace-244302023-05-29T15:23:28Z Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model 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. 57113510800 57207789882 57201523473 36630785100 55839645200 36863982200 7003344568 55315758000 57214837520 39162217600 55579596900 57192892703 56436626600 16068189400 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. Final 2023-05-29T07:23:28Z 2023-05-29T07:23:28Z 2019 Article 10.3390/app9193960 2-s2.0-85073301549 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073301549&doi=10.3390%2fapp9193960&partnerID=40&md5=ce0ccc810c4a83e0ace3dce93e16cce0 https://irepository.uniten.edu.my/handle/123456789/24430 9 19 3960 All Open Access, Gold MDPI AG Scopus |
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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. |
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57113510800 |
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57113510800 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. |
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Article |
author |
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. |
spellingShingle |
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. Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
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Ehteram M. |
title |
Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
title_short |
Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
title_full |
Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
title_fullStr |
Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
title_full_unstemmed |
Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
title_sort |
toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model |
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MDPI AG |
publishDate |
2023 |
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1806427567163441152 |
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13.211869 |