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Research Article | Open Access

Decision models enhancing environmental flow sustainability: A strategic approach to water resource management

Seiran Haghgoo1Jamil Amanollahi1( )Barzan Bahrami Kamangar2Shahryar Sorooshian3( )
Department of Environmental Sciences, Faculty of Natural Resources, University of Kurdistan, Iran
Department of Fisheries, Faculty of Natural Resources, University of Kurdistan, Iran
Department of Business Administration, University of Gothenburg, Sweden
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Abstract

Proper water resource management is essential for maintaining a sustainable supply chain and meeting water demand. The urgent need to preserve river ecosystems by sustaining environmental flow (EF) in the realm of environmental management has been highlighted by the drastic changes to river ecosystems and upstream flow dynamics brought about by careless river exploitation in the last few decades. To optimize EF in river basin management, we present an integrated modeling approach. We focused on the Pir Khezran River basin. Our objective was to estimate EF and generalize the findings to adjacent rivers using modeling techniques, thus providing valuable insights for environmental management applications. The assessment and optimization of EF under uncertain conditions was achieved by combining physical habitat simulation (PHABSIM) modeling with advanced techniques like Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Multilayer Perceptron (MLP) neural networks. This integrated modeling approach contributes to sustainable solutions for river basin management and environmental conservation by effectively optimizing EF, as demonstrated by the results. This research, therefore, makes valuable contributions to environmental management in various areas such as ecological preservation, modeling and optimizing environmental systems, and policy considerations.

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AIMS Environmental Science
Pages 900-917

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Cite this article:
Haghgoo S, Amanollahi J, Kamangar BB, et al. Decision models enhancing environmental flow sustainability: A strategic approach to water resource management. AIMS Environmental Science, 2024, 11(6): 900-917. https://doi.org/10.3934/environsci.2024045

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Received: 27 May 2024
Revised: 26 July 2024
Accepted: 10 October 2024
Published: 16 October 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)