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

Sedighkia, Mahdi, Datta, Bithin, Abdoli, Asghar, and Moradian, Zahra (2021) An ecohydraulic-based expert system for optimal management of environmental flow at the downstream of reservoirs. Journal of Hydroinformatics, 23 (6). pp. 1343-1367.

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View at Publisher Website: https://doi.org/10.2166/hydro.2021.112
 
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Abstract

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.

Item ID: 72132
Item Type: Article (Research - C1)
ISSN: 1465-1734
Keywords: environmental flow,habitat suitability,knowledge-based system,metaheuristic optimization,reservoir operation
Copyright Information: This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/)
Date Deposited: 09 Feb 2022 09:06
FoR Codes: 40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering @ 100%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180399 Fresh, ground and surface water systems and management not elsewhere classified @ 100%
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