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

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2 Citations (Scopus)

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.

LanguageEnglish
Pages1877-1891
Number of pages15
JournalScience of the Total Environment
Volume651
Issue numberPart 2
Early online date6 Oct 2018
DOIs
Publication statusPublished - 15 Feb 2019

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Catchments
Rivers
river basin
Computational efficiency
Water resources
Water supply
basin management
Land use
Ecosystems
Agriculture
Water quality
inflow
Economics
water supply
water resource
Water
agriculture
water quality
land use
decision

Keywords

  • environmental flows regime
  • water resources management
  • Borg MOEA
  • ε-DSEA
  • auto-adaptive constraints
  • Diyala River basin

Cite this

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title = "Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm",
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.",
keywords = "environmental flows regime, water resources management, Borg MOEA, ε-DSEA, auto-adaptive constraints, Diyala River basin",
author = "Al-Jawad, {Jafar Y.} and Alsaffar, {Hassan M} and Douglas Bertram and Kalin, {Robert M.}",
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AU - Al-Jawad, Jafar Y.

AU - Alsaffar, Hassan M

AU - Bertram, Douglas

AU - Kalin, Robert M.

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PY - 2019/2/15

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N2 - 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.

AB - 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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KW - water resources management

KW - Borg MOEA

KW - ε-DSEA

KW - auto-adaptive constraints

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