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<p>The Rift Valley Lakes Basin (RVLB) in Ethiopia faces significant challenges in water resource management due to competing demands from economic development, social equity, and environmental sustainability. Rapid population growth, agricultural expansion, industrial activities, and urbanization exert increasing pressure on the region’s limited water resources. Current water allocation practices often prioritize short-term economic gains, leading to over-extraction and inefficient water use, exacerbating social inequities and environmental degradation. This study introduces a multi-objective optimization framework using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to balance economic efficiency, equity, and environmental sustainability in water allocation. Environmental sustainability goals are&#xa0;expressed in terms of preservation of biodiversity, protection of ecosystem services, avoidance of environmental degradation, mitigation of climate change impacts and sustainable water use. The study area, RVLB, is characterized by diverse hydrological and hydrogeological settings, with significant variations in temperature, rainfall, and evapotranspiration. The optimization model aims to achieve maximum economic benefit efficiency and minimize the Gini coefficient to ensure equitable water distribution. The results indicate a trade-off between economic return and equity, highlighting the need for decision-makers to balance these objectives based on public demands and preferences. The study concludes that the optimal Pareto front strategy can effectively manage the conflict between economic efficiency and equity, providing a comprehensive water allocation scheme for the RVLB.</p>

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Multi-objective optimization of water resources allocation in rift valley lakes basin (Ethiopia): tradeoffs between efficiency and equity

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月7日

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  • Mulugeta Mohammed,
  • Belete Birhanu,
  • Fentaw Abegaz

摘要

The Rift Valley Lakes Basin (RVLB) in Ethiopia faces significant challenges in water resource management due to competing demands from economic development, social equity, and environmental sustainability. Rapid population growth, agricultural expansion, industrial activities, and urbanization exert increasing pressure on the region’s limited water resources. Current water allocation practices often prioritize short-term economic gains, leading to over-extraction and inefficient water use, exacerbating social inequities and environmental degradation. This study introduces a multi-objective optimization framework using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to balance economic efficiency, equity, and environmental sustainability in water allocation. Environmental sustainability goals are expressed in terms of preservation of biodiversity, protection of ecosystem services, avoidance of environmental degradation, mitigation of climate change impacts and sustainable water use. The study area, RVLB, is characterized by diverse hydrological and hydrogeological settings, with significant variations in temperature, rainfall, and evapotranspiration. The optimization model aims to achieve maximum economic benefit efficiency and minimize the Gini coefficient to ensure equitable water distribution. The results indicate a trade-off between economic return and equity, highlighting the need for decision-makers to balance these objectives based on public demands and preferences. The study concludes that the optimal Pareto front strategy can effectively manage the conflict between economic efficiency and equity, providing a comprehensive water allocation scheme for the RVLB.