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

Mohammad Ehteram, Amr H. El-Shafie, Lai Sai Hin, Faridah Othman, Suhana Koting, Hojat Karami, Sayed Farhad Mousavi, Saeed Farzin, Mohd Hafiz Bins Zawawi, Md Shabbir Hossain, Nuruol Syuhadaa Mohd, Haitham Abdulmohsin Afan, Ahmed El-Shafie, Ali Najah Ahmed

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number3960
JournalApplied Sciences (Switzerland)
Volume9
Issue number19
DOIs
Publication statusPublished - 01 Oct 2019

Fingerprint

sharks
irrigation
climate change
Irrigation
Climate change
dams
Dams
Runoff
Water
water
drainage
Water supply
water runoff
Iran
Precipitation (meteorology)
Rain
trends
Temperature
optimization
temperature

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

Cite this

Ehteram, Mohammad ; El-Shafie, Amr H. ; Hin, Lai Sai ; Othman, Faridah ; Koting, Suhana ; Karami, Hojat ; Mousavi, Sayed Farhad ; Farzin, Saeed ; Zawawi, Mohd Hafiz Bins ; Hossain, Md Shabbir ; Mohd, Nuruol Syuhadaa ; Afan, Haitham Abdulmohsin ; El-Shafie, Ahmed ; Ahmed, Ali Najah. / Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model. In: Applied Sciences (Switzerland). 2019 ; Vol. 9, No. 19.
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Ehteram, M, El-Shafie, AH, Hin, LS, Othman, F, Koting, S, Karami, H, Mousavi, SF, Farzin, S, Zawawi, MHB, Hossain, MS, Mohd, NS, Afan, HA, El-Shafie, A & Ahmed, AN 2019, 'Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model', Applied Sciences (Switzerland), vol. 9, no. 19, 3960. https://doi.org/10.3390/app9193960

Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model. / Ehteram, Mohammad; El-Shafie, Amr H.; Hin, Lai Sai; Othman, Faridah; Koting, Suhana; Karami, Hojat; Mousavi, Sayed Farhad; Farzin, Saeed; Zawawi, Mohd Hafiz Bins; Hossain, Md Shabbir; Mohd, Nuruol Syuhadaa; Afan, Haitham Abdulmohsin; El-Shafie, Ahmed; Ahmed, Ali Najah.

In: Applied Sciences (Switzerland), Vol. 9, No. 19, 3960, 01.10.2019.

Research output: Contribution to journalArticle

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AU - Ehteram, Mohammad

AU - El-Shafie, Amr H.

AU - Hin, Lai Sai

AU - Othman, Faridah

AU - Koting, Suhana

AU - Karami, Hojat

AU - Mousavi, Sayed Farhad

AU - Farzin, Saeed

AU - Zawawi, Mohd Hafiz Bins

AU - Hossain, Md Shabbir

AU - Mohd, Nuruol Syuhadaa

AU - Afan, Haitham Abdulmohsin

AU - El-Shafie, Ahmed

AU - Ahmed, Ali Najah

PY - 2019/10/1

Y1 - 2019/10/1

N2 - 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.

AB - 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.

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