An optimization approach for managing environmental impacts of generating hydropower on fish biodiversity

Sedighkia, Mahdi, and Abdoli, Asghar (2023) An optimization approach for managing environmental impacts of generating hydropower on fish biodiversity. Renewable Energy, 218. 119283.

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Abstract

The present study proposes an applicable framework to mitigate the impacts of generating hydropower on the fish biodiversity in the large reservoirs considering water quality and hydraulic factors. Moreover, several data driven models were utilized for simulating effective parameters. Finally, a multivariate linear regression model was used to estimate the fish biodiversity index in which two combined hydraulic and water quality indices were the inputs of the model and the fish biodiversity index was the output of the model. Then, all the simulators were applied in the structure of the hydropower plant operation optimization for different hydrological conditions (i.e. dry years, normal years and wet years) in which two purposes were defined: 1- minimizing the fish biodiversity loss 2- minimizing the loss of generating hydropower. Based on the results in the case study, all the simulators are reliable to model the physical flow, water quality parameters and the fish biodiversity index. The optimization model is able to minimize the impacts on the fish biodiversity properly. The reliability of generating hydropower in the dry years is 30%, while it is 53% in the wet years. High computational complexities might be a limitation for the model.

Item ID: 80506
Item Type: Article (Research - C1)
ISSN: 1879-0682
Keywords: Ecological management, Evolutionary optimization, Fish biodiversity, Hydropower, Reservoir operation
Copyright Information: © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Date Deposited: 06 Feb 2024 03:22
FoR Codes: 40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering @ 100%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280111 Expanding knowledge in the environmental sciences @ 100%
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