Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms
Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA) and...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/6474870 |
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| author | Anongrit Kangrang Haris Prasanchum Rattana Hormwichian |
| author_facet | Anongrit Kangrang Haris Prasanchum Rattana Hormwichian |
| author_sort | Anongrit Kangrang |
| collection | DOAJ |
| description | Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. The Ubolrat Reservoir located in the northeast region of Thailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. The future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. The situations of water shortage and excess water were shown in terms of frequency magnitude and duration. The results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. The optimal future rule curves were more suitable for future situations than the other rule curves. |
| format | Article |
| id | doaj-art-0cf344e0b1004aa2a0f0c372f33826e7 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-0cf344e0b1004aa2a0f0c372f33826e72025-02-03T07:24:55ZengWileyAdvances in Civil Engineering1687-80861687-80942018-01-01201810.1155/2018/64748706474870Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search AlgorithmsAnongrit Kangrang0Haris Prasanchum1Rattana Hormwichian2Faculty of Engineering, Mahasarakham University, Kantharawichai, Mahasarakham 44150, ThailandFaculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Muang, Khon Kaen 40000, ThailandFaculty of Engineering, Mahasarakham University, Kantharawichai, Mahasarakham 44150, ThailandOptimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. The Ubolrat Reservoir located in the northeast region of Thailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. The future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. The situations of water shortage and excess water were shown in terms of frequency magnitude and duration. The results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. The optimal future rule curves were more suitable for future situations than the other rule curves.http://dx.doi.org/10.1155/2018/6474870 |
| spellingShingle | Anongrit Kangrang Haris Prasanchum Rattana Hormwichian Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms Advances in Civil Engineering |
| title | Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms |
| title_full | Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms |
| title_fullStr | Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms |
| title_full_unstemmed | Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms |
| title_short | Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms |
| title_sort | development of future rule curves for multipurpose reservoir operation using conditional genetic and tabu search algorithms |
| url | http://dx.doi.org/10.1155/2018/6474870 |
| work_keys_str_mv | AT anongritkangrang developmentoffuturerulecurvesformultipurposereservoiroperationusingconditionalgeneticandtabusearchalgorithms AT harisprasanchum developmentoffuturerulecurvesformultipurposereservoiroperationusingconditionalgeneticandtabusearchalgorithms AT rattanahormwichian developmentoffuturerulecurvesformultipurposereservoiroperationusingconditionalgeneticandtabusearchalgorithms |