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An improved bi-level programming model for water resources allocation under multiple uncertainties.

Chongfeng Ren1, Yashi Wang1, Linghui Yu1

  • 1School of Water and Environment, Chang'an University, Xi'an, PR China; Key Laboratory of Eco-hydrology and Water Security in Arid and Semi-arid Regions of Ministry of Water Resources, Chang'an University, Xi'an, PR China; Key Laboratory of subsurface hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, PR China.

Journal of Environmental Management
|September 6, 2023
PubMed
Summary
This summary is machine-generated.

Water scarcity drives competition. A new fuzzy bi-level programming model optimizes water allocation under uncertainty, balancing economic benefits and fairness, crucial for decision-making in water resource management.

Keywords:
Bi-level programmingMulti-objective programmingMultiple uncertaintiesWater resources optimal allocation

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Area of Science:

  • Water Resource Management
  • Operations Research
  • Environmental Economics

Background:

  • Increasing global water scarcity intensifies competition among various sectors and levels.
  • Uncertainties inherent in water resource systems complicate optimal allocation and conflict resolution.
  • Existing models often struggle to address multi-objective, multi-level water conflicts under uncertainty.

Purpose of the Study:

  • To develop a robust model for optimizing water resource allocation amidst scarcity and uncertainty.
  • To address water conflicts at different levels and between sectors.
  • To balance competing objectives such as agricultural economic benefits and water distribution fairness.

Main Methods:

  • A fuzzy max-min decision bi-level multi-objective interval programming model was formulated.
  • The model was applied to a case study in Wuwei City, Gansu Province, China.
  • Analysis considered different representative hydrological years (wet to dry) and their impact on objectives.

Main Results:

  • Decreasing water availability (wet to dry years) led to reduced agricultural economic benefits and fairness (increased Gini coefficient).
  • The model demonstrated that water distribution fairness is higher in upper-bound allocation schemes compared to lower-bound schemes.
  • The bi-level programming model effectively resolved conflicts by providing solutions between individual upper and lower level objectives.

Conclusions:

  • The proposed fuzzy bi-level programming model successfully optimizes water allocation under uncertainty and multi-objective conflicts.
  • It provides decision-makers with reasonable schemes for managing complex water resource challenges.
  • The model highlights the trade-offs between economic benefits and water distribution fairness in water-scarce regions.