Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm
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 defi...
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| Format: | Article |
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MDPI
2018
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| author | Ehteram, Mohammad P. Singh, Vijay Karami, Hojat Hosseini, Khosrow Dianatikhah, Mojgan Hossain, Md. Ming Fai, Chow El-Shafie, Ahmed |
| author_facet | Ehteram, Mohammad P. Singh, Vijay Karami, Hojat Hosseini, Khosrow Dianatikhah, Mojgan Hossain, Md. Ming Fai, Chow El-Shafie, Ahmed |
| author_sort | Ehteram, Mohammad |
| collection | UM |
| description | 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. |
| first_indexed | 2024-03-06T05:56:04Z |
| format | Article |
| id | um.eprints-22113 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:56:04Z |
| publishDate | 2018 |
| publisher | MDPI |
| record_format | dspace |
| spelling | um.eprints-221132019-08-30T00:44:34Z http://eprints.um.edu.my/22113/ Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm Ehteram, Mohammad P. Singh, Vijay Karami, Hojat Hosseini, Khosrow Dianatikhah, Mojgan Hossain, Md. Ming Fai, Chow El-Shafie, Ahmed TA Engineering (General). Civil engineering (General) 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. MDPI 2018 Article PeerReviewed Ehteram, Mohammad and P. Singh, Vijay and Karami, Hojat and Hosseini, Khosrow and Dianatikhah, Mojgan and Hossain, Md. and Ming Fai, Chow and El-Shafie, Ahmed (2018) Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm. Water, 10 (9). p. 1267. ISSN 2073-4441, DOI https://doi.org/10.3390/w10091267 <https://doi.org/10.3390/w10091267>. https://doi.org/10.3390/w10091267 doi:10.3390/w10091267 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Ehteram, Mohammad P. Singh, Vijay Karami, Hojat Hosseini, Khosrow Dianatikhah, Mojgan Hossain, Md. Ming Fai, Chow El-Shafie, Ahmed Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm |
| title | Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm |
| title_full | Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm |
| title_fullStr | Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm |
| title_full_unstemmed | Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm |
| title_short | Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm |
| title_sort | irrigation management based on reservoir operation with an improved weed algorithm |
| topic | TA Engineering (General). Civil engineering (General) |
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