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An efficient irrigation water allocation model under uncertainty

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  • Li, Mo
  • Guo, Ping
  • Singh, Vijay P.

Abstract

An interval linear fractional irrigation water allocation (ILFIWA) model is developed in response to the complexity of errors in estimating crop yields, fluctuating hydrological elements as well as varying economic profits in an irrigation system. The model is capable of quantitatively solving multi-objective problems, i.e. to obtain the maximum system net benefit and the minimum irrigation water use. Particularly, it can handle multi-objective functions expressed as ratios, such as irrigation water productivity. Moreover, it can reflect the uncertainties of the variables/parameters and functions involved. The potential of the developed model is shown by applying to a case study in northwest China. Results of the model can help make irrigation water allocation decisions for different time periods under varying flow levels. Comparison between ILFIWA model and ordinary interval linear programming model shows that the developed model is conducive to improving irrigation water productivity and saving irrigation water, and helping decision makers formulate desired irrigation water resources management policies under uncertainty.

Suggested Citation

  • Li, Mo & Guo, Ping & Singh, Vijay P., 2016. "An efficient irrigation water allocation model under uncertainty," Agricultural Systems, Elsevier, vol. 144(C), pages 46-57.
    • Handle: RePEc:eee:agisys:v:144:y:2016:i:c:p:46-57
    DOI: 10.1016/j.agsy.2016.02.003
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    Cited by:

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    13. Chongfeng Ren & Jiantao Yang & Hongbo Zhang, 2019. "An inexact fractional programming model for irrigation water resources optimal allocation under multiple uncertainties," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    14. Xike Guan & Zengchuan Dong & Yun Luo & Dunyu Zhong, 2021. "Multi-Objective Optimal Allocation of River Basin Water Resources under Full Probability Scenarios Considering Wet–Dry Encounters: A Case Study of Yellow River Basin," IJERPH, MDPI, vol. 18(21), pages 1-19, November.
    15. Tang, Yikuan & Zhang, Fan & Wang, Sufen & Zhang, Xiaodong & Guo, Shanshan & Guo, Ping, 2019. "A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area," Agricultural Water Management, Elsevier, vol. 220(C), pages 13-26.
    16. Guo, Daxin & Olesen, Jørgen Eivind & Manevski, Kiril & Ma, Xiaoyi, 2021. "Optimizing irrigation schedule in a large agricultural region under different hydrologic scenarios," Agricultural Water Management, Elsevier, vol. 245(C).
    17. Zhang, Chenglong & Li, Xuemin & Guo, Ping & Huo, Zailin, 2020. "An improved interval-based fuzzy credibility-constrained programming approach for supporting optimal irrigation water management under uncertainty," Agricultural Water Management, Elsevier, vol. 238(C).
    18. Zhang, Chenglong & Yang, Gaiqiang & Wang, Chaozi & Huo, Zailin, 2023. "Linking agricultural water-food-environment nexus with crop area planning: A fuzzy credibility-based multi-objective linear fractional programming approach," Agricultural Water Management, Elsevier, vol. 277(C).

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