Multi-Objective Two-Layer Robust Optimisation Model for Water Resource Allocation in the Basin: A Case Study of Yellow River Basin, China

The continuous growth of the social economy and the accelerated urbanisation process have led to a rising increase in the demand for water resources in river basins. The uneven temporal and spatial distribution of water resources has further exacerbated the contradiction between supply and demand. T...

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Published in:Water (Basel) Vol. 17; no. 20; p. 3009
Main Authors: Di, Danyang, Hu, Hao, Duan, Shikun, Shi, Qi, Wang, Huiliang, Xiao, Lizhong
Format: Journal Article
Language:English
Published: Basel MDPI AG 20.10.2025
Subjects:
Ecology
Environmental aspects
Equilibrium
Fuzzy sets
Genetic algorithms
Linear programming
Management
Mathematical optimization
Methods
Metropolitan areas
Pareto optimum
Quantitative analysis
Sustainable development
Water
Water quality
Water resources management
Watersheds
China
Yellow River
ISSN:2073-4441, 2073-4441
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Abstract The continuous growth of the social economy and the accelerated urbanisation process have led to a rising increase in the demand for water resources in river basins. The uneven temporal and spatial distribution of water resources has further exacerbated the contradiction between supply and demand. The traditional extensive water resource allocation model is no longer suitable for the diverse demands of sustainable development in river basins. Therefore, there is an urgent demand to determine how to reconcile the supply and demand of water resources in river basins to achieve a rational allocation. Taking the Yellow River Basin as an example, an optimal water allocation framework based on multi-objective robust optimisation method was proposed in this study. A robust constraint boundary conditions for the industrial, agricultural, construction and service, ecological, and social water demand were selected from the perspective of the economy–society–ecology nexus. Then, Latin hypercube sampling was adopted to modify the Monte Carlo method to improve the dispersion of sampling values for quantifying the uncertainty of water allocation parameters. Furthermore, a multi-dimensional spatial equilibrium optimal allocation combining adjustable robust optimisation and multi-objective optimisation was established. Finally, a multi-objective particle swarm optimisation algorithm based on a crossover operator was constructed to obtain the Pareto-optimal solution for multi-dimensional spatial equilibrium optimal allocation. The primary findings were as follows: (1) Parameter uncertainty had a significant effect on the provincial/regional revenues of water resources but has no obvious effect on basin revenue. (2) The uncertainty in runoff and parameters had a significant influence on decisions for optimal water allocation. The optimal volume of water purchased by different provinces (regions) varied greatly under different scenarios.
AbstractList The continuous growth of the social economy and the accelerated urbanisation process have led to a rising increase in the demand for water resources in river basins. The uneven temporal and spatial distribution of water resources has further exacerbated the contradiction between supply and demand. The traditional extensive water resource allocation model is no longer suitable for the diverse demands of sustainable development in river basins. Therefore, there is an urgent demand to determine how to reconcile the supply and demand of water resources in river basins to achieve a rational allocation. Taking the Yellow River Basin as an example, an optimal water allocation framework based on multi-objective robust optimisation method was proposed in this study. A robust constraint boundary conditions for the industrial, agricultural, construction and service, ecological, and social water demand were selected from the perspective of the economy–society–ecology nexus. Then, Latin hypercube sampling was adopted to modify the Monte Carlo method to improve the dispersion of sampling values for quantifying the uncertainty of water allocation parameters. Furthermore, a multi-dimensional spatial equilibrium optimal allocation combining adjustable robust optimisation and multi-objective optimisation was established. Finally, a multi-objective particle swarm optimisation algorithm based on a crossover operator was constructed to obtain the Pareto-optimal solution for multi-dimensional spatial equilibrium optimal allocation. The primary findings were as follows: (1) Parameter uncertainty had a significant effect on the provincial/regional revenues of water resources but has no obvious effect on basin revenue. (2) The uncertainty in runoff and parameters had a significant influence on decisions for optimal water allocation. The optimal volume of water purchased by different provinces (regions) varied greatly under different scenarios.
Audience Academic
Author Wang, Huiliang
Shi, Qi
Di, Danyang
Duan, Shikun
Xiao, Lizhong
Hu, Hao
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SubjectTerms Ecology
Environmental aspects
Equilibrium
Fuzzy sets
Genetic algorithms
Linear programming
Management
Mathematical optimization
Methods
Metropolitan areas
Pareto optimum
Quantitative analysis
Sustainable development
Water
Water quality
Water resources management
Watersheds
Title Multi-Objective Two-Layer Robust Optimisation Model for Water Resource Allocation in the Basin: A Case Study of Yellow River Basin, China
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