Journal of Hydroinformatics (Nov 2021)

An ecohydraulic-based expert system for optimal management of environmental flow at the downstream of reservoirs

  • Mahdi Sedighkia,
  • Bithin Datta,
  • Asghar Abdoli,
  • Zahra Moradian

DOI
https://doi.org/10.2166/hydro.2021.112
Journal volume & issue
Vol. 23, no. 6
pp. 1343 – 1367

Abstract

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Linking ecohydraulic modeling and reservoir operation optimization is a requirement for robust management of the environmental degradations at the downstream of the reservoirs. The present study proposes and evaluates an ecohydraulic-based expert system to optimize environmental flow at the downstream of the reservoirs. Three fuzzy inference systems including physical habitat assessment, water quality assessment and combined suitability assessment were developed based on the expert panel method. Moreover, water temperature and dissolved oxygen were simulated by the coupled particle swarm optimization (PSO)–adaptive neuro-fuzzy inference system. Three evolutionary algorithms including PSO, differential evolution algorithm (DE) and biogeography-based optimization were applied to optimize the environmental flow regime. A fuzzy technique for order of preference by similarity to ideal solution was applied to select the best evolutionary algorithm to assess environmental flow. Based on the results in the case study, the proposed method provides a robust framework for simultaneous management of environmental flow and water supply. DE was selected as the best algorithm to optimize environmental flow. The optimization system was able to balance habitat losses, storage loss and water supply loss that might reduce negotiations between the stakeholders and environmental managers in the reservoir management. HIGHLIGHTS Environmental flow at downstream of dams is critical to protect river habitats.; The present study proposes an ecohydraulic expert system for the reservoir operation.; Optimal environmental flow and water supply are the outputs of the model.; The developed system can minimize physical and water quality habitat losses.; Differential evolution was the best optimization algorithm in the case study.;

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