Multi-Objective Model for Efficient, Equitable, and Sustainable Water Allocation Under Uncertainty: A Case Study of Namhan River Basin, South Korea

Water allocation under uncertainty remains a critical challenge in water-scarce regions. This study presents an integrated water allocation model that explicitly incorporates uncertainty through stochastic streamflow simulations and addresses multiple objectives—efficiency, equity, and sustainability—within a unified framework. The model uses historical inflow data, future demand projections, and a multi-objective optimization approach based on the NSGA-II to generate trade-off solutions. To support decision-making, TOPSIS is applied to identify the most balanced allocation strategies from the Pareto-optimal sets. The model is applied to the Namhan River Basin in South Korea, with two key applications: (1) developing adaptive water allocation strategies under dry, normal, and wet hydrological conditions, and (2) proposing targeted infrastructure enhancements—including new dams, transmission lines, and intake points—to address vulnerabilities in dry years. The results demonstrate that the proposed model improves supply reliability, economic efficiency, equity across regions, and sustainability through river maintenance and reservoir storage compliance. This study provides a generalizable and practical decision-support tool for long-term water planning under climate and demand uncertainties, offering actionable insights for water-deficient basins.

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Publication Details

Journal
Water
Published
2025-04-20
DOI
https://doi.org/10.3390/w17081230
Citations
1
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
1.15

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article

Multi-Objective Model for Efficient, Equitable, and Sustainable Water Allocation Under Uncertainty: A Case Study of Namhan River Basin, South Korea

Flavia D. Frederick, Doosun Kang
1 citations
Water
Water resources management and optimization
1.15
article

Multi-Objective Model for Efficient, Equitable, and Sustainable Water Allocation Under Uncertainty: A Case Study of Namhan River Basin, South Korea

Flavia D. Frederick, Doosun Kang
article en
1 citations

Abstract

Water allocation under uncertainty remains a critical challenge in water-scarce regions. This study presents an integrated water allocation model that explicitly incorporates uncertainty through stochastic streamflow simulations and addresses multiple objectives—efficiency, equity, and sustainability—within a unified framework. The model uses historical inflow data, future demand projections, and a multi-objective optimization approach based on the NSGA-II to generate trade-off solutions. To support decision-making, TOPSIS is applied to identify the most balanced allocation strategies from the Pareto-optimal sets. The model is applied to the Namhan River Basin in South Korea, with two key applications: (1) developing adaptive water allocation strategies under dry, normal, and wet hydrological conditions, and (2) proposing targeted infrastructure enhancements—including new dams, transmission lines, and intake points—to address vulnerabilities in dry years. The results demonstrate that the proposed model improves supply reliability, economic efficiency, equity across regions, and sustainability through river maintenance and reservoir storage compliance. This study provides a generalizable and practical decision-support tool for long-term water planning under climate and demand uncertainties, offering actionable insights for water-deficient basins.

WaterVol. 17(8)
Kyung Hee University (KR)
Ministry of Trade, Industry and Energy, Ministry of Environment, Ministry of Education, India, Korea Environmental Industry and Technology Institute, Korea Institute of Energy Technology Evaluation and Planning
Openalex Percentile: Top 24%
Water resources management and optimization
1.15
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Multi-Objective Model for Efficient, Equitable, and Sustainable Water Allocation Under Uncertainty: A Case Study of Namhan River Basin, South Korea — Flavia D. Frederick, Doosun Kang · Water (2025) | TGRS Research Map | TGRS