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Multi-scale modeling for irrigation water and cropland resources allocation considering uncertainties in water supply and demand

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Listed:
  • Li, Mo
  • Sun, Hao
  • Liu, Dong
  • Singh, Vijay P.
  • Fu, Qiang

Abstract

Irrigated agriculture is the dominant user of world’s fresh water which feeds the world’s growing population. Conflicts between stakeholders; incompatibility of economic, social, and environmental development; and uncertainties in water supply and demand restrict the sustainable development of irrigated agriculture. This study developed a multi-scale multi-objective programming model for simultaneous optimal allocation of irrigation water and cropland to balance conflicts between farmers’ income and sustainable development of irrigation districts (reflected in economic, social, and environmental aspects). Consideration of the joint uncertainties of water supply and demand helps provide practical and indicative schemes for agricultural water and land allocation. The developed model was applied to a real case study in an irrigation district in northeast China. Farmers’ income, net economic benefit, resources allocation equity, and global warming potential were coordinated by optimally allocating limited water and cropland resources to different crops in different subareas under different combinational scenarios of water supply and demand. The performance of the model was evaluated, based on the concept of “adaptability” which can help realize the degree of ability of the irrigated agricultural system to adapt to changing environment. The developed model can help plan irrigation water and cropland resources in a sustainable way, and can be a reference for similar irrigation systems worldwide.

Suggested Citation

  • Li, Mo & Sun, Hao & Liu, Dong & Singh, Vijay P. & Fu, Qiang, 2021. "Multi-scale modeling for irrigation water and cropland resources allocation considering uncertainties in water supply and demand," Agricultural Water Management, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:agiwat:v:246:y:2021:i:c:s0378377420322319
    DOI: 10.1016/j.agwat.2020.106687
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    4. Jain, Sonal & Ramesh, Dharavath & Trivedi, Munesh C. & Edla, Damodar Reddy, 2023. "Evaluation of metaheuristic optimization algorithms for optimal allocation of surface water and groundwater resources for crop production," Agricultural Water Management, Elsevier, vol. 279(C).

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