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

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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.

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Abbreviations

WUA:

Weighted useable area

NHL:

Normalized habitat loss

MCM:

Million cubic meters

NPL:

Normalized project loss

GA:

The genetic algorithm

ISV:

Instream volume

TV:

Total volume

OSV:

Optimized offstream volume

MAF:

Mean annual flow

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Authors and Affiliations

  1. College of Science and Engineering, James Cook University, Townsville, Australia

    Mahdi Sedighkia & Bithin Datta

  2. Environmental Science Research Institute, Velenjak sbu, Tehran, Iran

    Asghar Abdoli

Authors
  1. Mahdi Sedighkia
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  2. Asghar Abdoli
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  3. Bithin Datta
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Correspondence to Mahdi Sedighkia.

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Sedighkia, M., Abdoli, A. & Datta, B. Optimizing monthly ecological flow regime by a coupled fuzzy physical habitat simulation–genetic algorithm method. Environ Syst Decis 41, 425–436 (2021). https://doi.org/10.1007/s10669-021-09809-z

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  • DOI: https://doi.org/10.1007/s10669-021-09809-z

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