Efficient and equitable irrigation management: A fuzzy multi-objective optimization model integrating water movement processes

  • 0Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China; State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing, 100083, China.

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Summary

This summary is machine-generated.

This study developed a multi-objective model for optimizing irrigation water allocation, balancing economic benefits, water equity, and efficiency under uncertainty. The model provides optimal solutions for sustainable irrigated agriculture.

Area Of Science

  • Agricultural Water Management
  • Optimization Modeling
  • Environmental Science

Background

  • Irrigation decisions face conflicts between economic benefits, water equity, and efficiency, especially under uncertainty.
  • Managing water resources sustainably requires balancing competing objectives in irrigation.
  • The Hetao Irrigation District exemplifies challenges in irrigation water supply and demand conflicts.

Purpose Of The Study

  • To develop a robust multi-objective model for optimizing irrigation water allocation.
  • To balance economic benefits, water equity, and irrigation efficiency under uncertainty.
  • To address conflicts in irrigation water supply and demand.

Main Methods

  • Utilized water balance simulation to model daily water movement (irrigation, soil, groundwater, drainage).
  • Employed interval multi-objective programming and fuzzy-boundary interval programming to manage objective conflicts under uncertainty.
  • Applied interactive algorithms to align constraint feasibility with objective satisfaction for optimal solutions.

Main Results

  • Optimal water allocation solutions were derived for different feasibility levels (0.5-1.0) across subareas and crops.
  • Decision satisfaction peaked at a feasibility level of 0.9, balancing feasibility and objective satisfaction.
  • At 0.9 feasibility, economic benefits were [3.62, 13.60] × 10^9 Yuan, with a reduced Gini coefficient compared to 1.0 feasibility.

Conclusions

  • The developed model facilitates decision-making for irrigation optimization under multiple conflicting objectives and uncertainties.
  • Achieving optimal irrigation water allocation promotes sustainable irrigated agriculture across economic, social, and resource dimensions.
  • Balancing feasibility and objective satisfaction is crucial for aligning model outcomes with decision-maker expectations.

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