Irrigation management based on reservoir operation with an improved weed algorithm

Mohammad Ehteram, Vijay P. Singh, Hojat Karami, Khosrow Hosseini, Mojgan Dianatikhah, Md Shabbir Hossain, Ming Fai Chow, Ahmed El-Shafie

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.

Original languageEnglish
Article number1267
JournalWater (Switzerland)
Volume10
Issue number9
DOIs
Publication statusPublished - 17 Sep 2018

Fingerprint

irrigation
Irrigation
irrigation management
weed
weeds
management
inflow
bat
genetic algorithm
swarms
Particle swarm optimization (PSO)
Genetic algorithms
Chiroptera
water
dams (hydrology)
Aptitude
Dams
Water
dam
Agricultural Irrigation

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Geography, Planning and Development
  • Aquatic Science
  • Water Science and Technology

Cite this

Ehteram, M., Singh, V. P., Karami, H., Hosseini, K., Dianatikhah, M., Hossain, M. S., ... El-Shafie, A. (2018). Irrigation management based on reservoir operation with an improved weed algorithm. Water (Switzerland), 10(9), [1267]. https://doi.org/10.3390/w10091267
Ehteram, Mohammad ; Singh, Vijay P. ; Karami, Hojat ; Hosseini, Khosrow ; Dianatikhah, Mojgan ; Hossain, Md Shabbir ; Chow, Ming Fai ; El-Shafie, Ahmed. / Irrigation management based on reservoir operation with an improved weed algorithm. In: Water (Switzerland). 2018 ; Vol. 10, No. 9.
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Ehteram, M, Singh, VP, Karami, H, Hosseini, K, Dianatikhah, M, Hossain, MS, Chow, MF & El-Shafie, A 2018, 'Irrigation management based on reservoir operation with an improved weed algorithm', Water (Switzerland), vol. 10, no. 9, 1267. https://doi.org/10.3390/w10091267

Irrigation management based on reservoir operation with an improved weed algorithm. / Ehteram, Mohammad; Singh, Vijay P.; Karami, Hojat; Hosseini, Khosrow; Dianatikhah, Mojgan; Hossain, Md Shabbir; Chow, Ming Fai; El-Shafie, Ahmed.

In: Water (Switzerland), Vol. 10, No. 9, 1267, 17.09.2018.

Research output: Contribution to journalArticle

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AU - Ehteram, Mohammad

AU - Singh, Vijay P.

AU - Karami, Hojat

AU - Hosseini, Khosrow

AU - Dianatikhah, Mojgan

AU - Hossain, Md Shabbir

AU - Chow, Ming Fai

AU - El-Shafie, Ahmed

PY - 2018/9/17

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N2 - Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.

AB - Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.

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