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Optimizing monthly ecological flow regime by a coupled fuzzy physical habitat simulation–genetic algorithm method

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  • Mahdi Sedighkia

    (James Cook University)

  • Asghar Abdoli

    (Environmental Science Research Institute)

  • Bithin Datta

    (James Cook University)

Abstract

The present study proposes and evaluates a fuzzy hydraulic habitat simulation–genetic algorithm method to optimize environmental flow regime with focus on diversion dam project. Proposed method develops an objective function that minimizes differences between habitat loss and water demand or project loss. Fuzzy physical habitat simulation was used to develop habitat loss function. Moreover, the genetic algorithm was utilized as optimization method. Based on results, minimum available environmental flow in dry seasons was approximately 15% of mean annual flow. However, its maximum would increase to 40% of mean annual flow in wet seasons. Reliability and vulnerability indices for supply of water demand were 80% and 34%, respectively, in the case study. Results of the proposed framework were compared with the Tennant method to demonstrate abilities for optimizing environmental flow. The most important advantage of proposed method is minimization of conflict between stakeholders and environmental advocators. In other words, the proposed method might be able to minimize negotiations to assess environmental flow regime.

Suggested Citation

  • Mahdi Sedighkia & Asghar Abdoli & Bithin Datta, 2021. "Optimizing monthly ecological flow regime by a coupled fuzzy physical habitat simulation–genetic algorithm method," Environment Systems and Decisions, Springer, vol. 41(3), pages 425-436, September.
    • Handle: RePEc:spr:envsyd:v:41:y:2021:i:3:d:10.1007_s10669-021-09809-z
    DOI: 10.1007/s10669-021-09809-z
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    References listed on IDEAS

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    1. Asmadi Ahmad & Ahmed El-Shafie & Siti Razali & Zawawi Mohamad, 2014. "Reservoir Optimization in Water Resources: a Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3391-3405, September.
    2. Suwal, Naresh & Huang, Xianfeng & Kuriqi, Alban & Chen, Yingqin & Pandey, Kamal Prasad & Bhattarai, Khem Prasad, 2020. "Optimisation of cascade reservoir operation considering environmental flows for different environmental management classes," Renewable Energy, Elsevier, vol. 158(C), pages 453-464.
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    Cited by:

    1. Zachary A. Collier & James H. Lambert & Igor Linkov, 2021. "Integrating data from physical and social science to address emerging societal challenges," Environment Systems and Decisions, Springer, vol. 41(3), pages 331-333, September.
    2. Mahdi Sedighkia & Asghar Abdoli, 2022. "Optimizing environmental flow regime by integrating river and reservoir ecosystems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 2079-2094, April.
    3. Masoud Zanjani & Omid Bozorg-Haddad & Mustafa Zanjani & Ali Arefinia & Masoud Pourgholam-Amiji & Hugo A. Loáiciga, 2024. "Estimating the riverine environmental water demand under climate change with data mining models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(12), pages 11451-11464, September.

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