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A Hybrid Dynamic Dual Interval Programming for Irrigation Water Allocation under Uncertainty

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  • Lei Jin
  • Guohe Huang
  • Yurui Fan
  • Xianghui Nie
  • Guanhui Cheng

Abstract

Along with the economic development in Canada, the shortage of irrigation water has become a serious concern (Bouwer 1993 ; Hennessy 1993 ). In this study, a model of Dynamic Dual Interval Programming (DDIP) is developed and applied to the irrigation water allocation systems with uncertainty. DDIP method improves the existing dynamics interval programming by explicitly addressing the system uncertainties with a dual interval that had higher system reliability. The solution of DDIP is computationally effective, and its decision variables are incorporated into the solutions for final decision. In order to obtain the optimal allocation schemes in a dynamic process, the developed DDIP was applied to an irrigation water system. The results from this case study revealed that optimal solution can be obtained through the DDIP approach from the agriculture water management activities for feasible decisions. These decisions reflect the high uncertainty of the information in the boundaries of dual intervals. The solution presents a maximum benefit under limited yearly uncertain natural resources. Furthermore, the information obtained though this model may help the authority to make optimal decisions and to reduce the risk for uncertain situations. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • Lei Jin & Guohe Huang & Yurui Fan & Xianghui Nie & Guanhui Cheng, 2012. "A Hybrid Dynamic Dual Interval Programming for Irrigation Water Allocation under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(5), pages 1183-1200, March.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:5:p:1183-1200
    DOI: 10.1007/s11269-011-9953-4
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    References listed on IDEAS

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    1. Galioto, Francesco & Battilani, Adriano, 2021. "Agro-economic simulation for day by day irrigation scheduling optimisation," Agricultural Water Management, Elsevier, vol. 248(C).
    2. Javier Alarcón & Alberto Garrido & Luis Juana, 2014. "Managing Irrigation Water Shortage: a Comparison Between Five Allocation Rules Based on Crop Benefit Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2315-2329, June.
    3. Yeonjoo Kim & Eun-Sung Chung & Sang-Mook Jun, 2015. "Iterative Framework for Robust Reclaimed Wastewater Allocation in a Changing Environment Using Multi-Criteria Decision Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(2), pages 295-311, January.
    4. Kun Cheng & Qiang Fu & Xi Chen & Tianxiao Li & Qiuxiang Jiang & Xiaosong Ma & Ke Zhao, 2015. "Adaptive Allocation Modeling for a Complex System of Regional Water and Land Resources Based on Information Entropy and its Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 4977-4993, November.
    5. Mehran Homayounfar & Sai Lai & Mehdi Zommorodian & Amin Oroji & Arman Ganji & Sara Kaviani, 2015. "Developing a Non-Discrete Dynamic Game Model and Corresponding Monthly Collocation Solution Considering Variability in Reservoir Inflow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2599-2618, June.
    6. Jingjing Wu & Jian Chen & Yu Han & Tongshu Li, 2020. "Study on Unsteady Flow Based on Optimized Water Distribution Model in Irrigation District," Sustainability, MDPI, vol. 12(4), pages 1-13, February.
    7. Shiang-Jen Wu & Jie-Sen Mai & Yi-Hong Lin & Keh-Chia Yeh, 2022. "Modeling Probabilistic-Based Reliability Analysis for Irrigation Water Supply Due to Uncertainties in Hydrological and Irrigation Factors," Sustainability, MDPI, vol. 14(19), pages 1-25, October.
    8. Elleuch, Mohamed Ali & Anane, Makram & Euchi, Jalel & Frikha, Ahmed, 2019. "Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case," Agricultural Systems, Elsevier, vol. 176(C).
    9. Gaiqiang Yang & Ping Guo & Mo Li & Shiqi Fang & Liudong Zhang, 2016. "An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 701-729, January.
    10. Wen, Yeqiang & Shang, Songhao & Yang, Jian, 2017. "Optimization of irrigation scheduling for spring wheat with mulching and limited irrigation water in an arid climate," Agricultural Water Management, Elsevier, vol. 192(C), pages 33-44.
    11. Gaiqiang Yang & Ping Guo & Mo Li & Shiqi Fang & Liudong Zhang, 2016. "An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 701-729, January.
    12. Jin, L. & Huang, G.H. & Fan, Y.R. & Wang, L. & Wu, T., 2015. "A pseudo-optimal inexact stochastic interval T2 fuzzy sets approach for energy and environmental systems planning under uncertainty: A case study for Xiamen City of China," Applied Energy, Elsevier, vol. 138(C), pages 71-90.

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