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

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

Sci Total Environ

Department of Civil and Environmental Engineering, University of Strathclyde Glasgow 75 Montrose St, Glasgow G1 1XJ, United Kingdom of Great Britain and Northern Ireland. Electronic address:

Published: February 2019

AI Article Synopsis

Article 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.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2018.10.063DOI Listing

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