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Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm

Al-Jawad, Jafar Y. and Alsaffar, Hassan M and Bertram, Douglas and Kalin, Robert M. (2019) Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm. Science of the Total Environment, 651 (Part 2). pp. 1877-1891. ISSN 0048-9697

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Abstract

Water resource system complexity, high-dimension modelling difficulty and computational efficiency challenges often limit decision makers' strategies to combine environmental flow objectives (e.g. water quality, ecosystem) with social flow objectives (e.g. hydropower, water supply and agriculture). Hence, a novel Optimum Social-Environmental Flows (OSEF) with Auto-Adaptive Constraints (AAC) approach introduced as a river basin management decision support tool. The OSEF-AAC approach integrates Socio-Environmental (SE) objectives with convergence booster support to soften any computational challenges. Nine SE objectives and 396 decision variables modelled for Iraq's Diyala river basin. The approach's effectiveness evaluated using two non-environmental models and two inflows' scenarios. The advantage of OSEF-AAC approved, and other decision support alternatives highlighted that could enhance river basin SE sectors' revenues, as river basin economic benefits will improve as well. However, advanced land use and water exploitation policy would need adoption to secure the basin's SE sectors.

Item type: Article
ID code: 65877
Keywords: environmental flows regime, water resources management, Borg MOEA, ε-DSEA, auto-adaptive constraints, Diyala River basin, Engineering (General). Civil engineering (General), Civil and Structural Engineering
Subjects: Technology > Engineering (General). Civil engineering (General)
Department: Faculty of Engineering > Civil and Environmental Engineering
Depositing user: Pure Administrator
Date deposited: 29 Oct 2018 07:55
Last modified: 18 Feb 2019 17:16
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URI: https://strathprints.strath.ac.uk/id/eprint/65877
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