Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty
This study investigated reservoir operation under climate change for a base period (1981-2000) and future period (2011-2030). Different climate change models, based on A2 scenario, were used and the HAD-CM3 model, considering uncertainty, among other climate change models was found to be the best mo...
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| Format: | Article |
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IWA Publishing
2018
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| _version_ | 1825720182291562496 |
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| author | Ehteram, Mohammad Mousavi, Sayed Farhad Karami, Hojat Farzin, Saeed Singh, Vijay P. Chau, Kwok Wing El-Shafie, Ahmed |
| author_facet | Ehteram, Mohammad Mousavi, Sayed Farhad Karami, Hojat Farzin, Saeed Singh, Vijay P. Chau, Kwok Wing El-Shafie, Ahmed |
| author_sort | Ehteram, Mohammad |
| collection | UM |
| description | This study investigated reservoir operation under climate change for a base period (1981-2000) and future period (2011-2030). Different climate change models, based on A2 scenario, were used and the HAD-CM3 model, considering uncertainty, among other climate change models was found to be the best model. For the Dez basin in Iran, considered as a case study, the climate change models predicted increasing temperature from 1.16 to 2.5°C and decreasing precipitation for the future period. Also, runoff volume for the basin would decrease and irrigation demand for the downstream consumption would increase for the future period. A hybrid framework (optimization-climate change) was used for reservoir operation and the bat algorithm was used for minimization of irrigation deficit. A genetic algorithm and a particle swarm algorithm were selected for comparison with the bat algorithm. The reliability, resiliency, and vulnerability indices, based on a multi-criteria model, were used to select the base method for reservoir operation. Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms. |
| first_indexed | 2024-03-06T05:31:08Z |
| format | Article |
| id | um.eprints-12427 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:31:08Z |
| publishDate | 2018 |
| publisher | IWA Publishing |
| record_format | dspace |
| spelling | um.eprints-124272019-12-23T04:34:16Z http://eprints.um.edu.my/12427/ Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty Ehteram, Mohammad Mousavi, Sayed Farhad Karami, Hojat Farzin, Saeed Singh, Vijay P. Chau, Kwok Wing El-Shafie, Ahmed TA Engineering (General). Civil engineering (General) This study investigated reservoir operation under climate change for a base period (1981-2000) and future period (2011-2030). Different climate change models, based on A2 scenario, were used and the HAD-CM3 model, considering uncertainty, among other climate change models was found to be the best model. For the Dez basin in Iran, considered as a case study, the climate change models predicted increasing temperature from 1.16 to 2.5°C and decreasing precipitation for the future period. Also, runoff volume for the basin would decrease and irrigation demand for the downstream consumption would increase for the future period. A hybrid framework (optimization-climate change) was used for reservoir operation and the bat algorithm was used for minimization of irrigation deficit. A genetic algorithm and a particle swarm algorithm were selected for comparison with the bat algorithm. The reliability, resiliency, and vulnerability indices, based on a multi-criteria model, were used to select the base method for reservoir operation. Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms. IWA Publishing 2018 Article PeerReviewed Ehteram, Mohammad and Mousavi, Sayed Farhad and Karami, Hojat and Farzin, Saeed and Singh, Vijay P. and Chau, Kwok Wing and El-Shafie, Ahmed (2018) Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty. Journal of Hydroinformatics, 20 (2). pp. 332-355. ISSN 1464-7141, DOI https://doi.org/10.2166/hydro.2018.094 <https://doi.org/10.2166/hydro.2018.094>. https://doi.org/10.2166/hydro.2018.094 doi:10.2166/hydro.2018.094 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Ehteram, Mohammad Mousavi, Sayed Farhad Karami, Hojat Farzin, Saeed Singh, Vijay P. Chau, Kwok Wing El-Shafie, Ahmed Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty |
| title | Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty |
| title_full | Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty |
| title_fullStr | Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty |
| title_full_unstemmed | Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty |
| title_short | Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty |
| title_sort | reservoir operation based on evolutionary algorithms and multi criteria decision making under climate change and uncertainty |
| topic | TA Engineering (General). Civil engineering (General) |
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