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Applying uncertain programming model to improve regional farming economic benefits and water productivity

Author

Listed:
  • Li, Xiaojuan
  • Kang, Shaozhong
  • Niu, Jun
  • Du, Taisheng
  • Tong, Ling
  • Li, Sien
  • Ding, Risheng

Abstract

The development of optimum crop area planning is valuable for agricultural water management in the arid and semiarid regions. However, the uncertain information existing in the crop area planning system is inevitable, and it cannot be tackled through the traditional multi-objective linear programming model (MOLP). In this study, an inexact multi-objective fuzzy programming model (IMOFP) was developed, considering the multi-objective characteristics, the vagueness associated with the objective functions and constraints, and the interval uncertainty in the parameters. Three objectives were considered including maximizing benefits, minimizing evapotranspiration (ET) and maximizing water productivity (WP). The IMOFP model was applied to solve the problem of crop area planning in Wuwei city of Gansu province in China, and the optimal results under different scenarios of water-saving levels and satisfactory degrees of the decision maker (DM) for available resources were obtained. Different scenarios were also considered to make in-depth analysis of interaction among weight coefficients, economic benefit and water conservation requirement. Moreover, violation variables were introduced to analyze the relationship among system satisfaction, risk level and benefit. Results indicate that using the IMOFP model made the economic benefit, water productivity and water production efficiency of planting in the region increased by 7.05–16.65%, 25.68–33.15% and 39.22–47.59% respectively, and the ET reduced by 20.96–23.10%. Compared to MOLP model, the proposed IMOFP model has advantages in effectively reflecting uncertainties expressed as discrete intervals and fuzzy sets, and can provide reasonable solutions and more stable decision alternatives.

Suggested Citation

  • Li, Xiaojuan & Kang, Shaozhong & Niu, Jun & Du, Taisheng & Tong, Ling & Li, Sien & Ding, Risheng, 2017. "Applying uncertain programming model to improve regional farming economic benefits and water productivity," Agricultural Water Management, Elsevier, vol. 179(C), pages 352-365.
    • Handle: RePEc:eee:agiwat:v:179:y:2017:i:c:p:352-365
    DOI: 10.1016/j.agwat.2016.06.030
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    Cited by:

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    2. Wu, Hui & Li, Xiaojuan & Lu, Hongna & Tong, Ling & Kang, Shaozhong, 2023. "Crop acreage planning for economy- resource- efficiency coordination: Grey information entropy based uncertain model," Agricultural Water Management, Elsevier, vol. 289(C).
    3. Behnam Sadeghi & Mahmoud Ahmadpour Borazjani & Mostafa Mardani & Saman Ziaee & Hamid Mohammadi, 2023. "Systemic Management of Water Resources with Environmental and Climate Change Considerations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2543-2574, May.
    4. Zhang, Fan & Guo, Ping & Engel, Bernard A. & Guo, Shanshan & Zhang, Chenglong & Tang, Yikuan, 2019. "Planning seasonal irrigation water allocation based on an interval multiobjective multi-stage stochastic programming approach," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    5. Vijendra Kumar & S. M. Yadav, 2019. "Optimization of Cropping Patterns Using Elitist-Jaya and Elitist-TLBO Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(5), pages 1817-1833, March.

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