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Decision Support System Based on Queuing Theory to Optimize Canal Management

Author

Listed:
  • Gaiqiang Yang

    (Taiyuan University of Science and Technology)

  • Mo Li

    (Northeast Agricultural University)

  • Lijuan Huo

    (Taiyuan University of Science and Technology)

Abstract

Uncertainties of groundwater utilization are usually neglected in decision support systems for irrigation system management. In this study, an irrigation water allocation model based on queuing theory was developed and an IOMSD (Irrigation Optimization Management for Shijin irrigation district Decision Support System) was designed. As the core of the system, the model adopts minimum water transportation time as the primary goal, and minimum loss of irrigation as the secondary goal. The developed IOMSD includes four layers: interaction, database, program, and model. Decision makers can obtain a detailed water allocation scheme by operating the IOMSD. To illustrate its application, the Shijin irrigation district was used. An optimal scheme was obtained using the IOMSD, which showed that the system utilization rate was particularly low between day 37 and day 54, and only trunk canal b5 was irrigated independently. To simplify the operation of trunk canals and decrease the whole irrigation period, a hierarchical cluster analysis was adopted. The improved optimal schemes were more concise, and the utilization rates of trunk canals were higher. The asymmetrical coefficient of the main channel decreased to 1.375, and the irrigation system was more stable and more efficient.

Suggested Citation

  • Gaiqiang Yang & Mo Li & Lijuan Huo, 2019. "Decision Support System Based on Queuing Theory to Optimize Canal Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4367-4384, September.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:12:d:10.1007_s11269-019-02372-y
    DOI: 10.1007/s11269-019-02372-y
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    References listed on IDEAS

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    1. Michel Le Page & B. Berjamy & Y. Fakir & F. Bourgin & L. Jarlan & A. Abourida & M. Benrhanem & G. Jacob & M. Huber & F. Sghrer & V. Simonneaux & G. Chehbouni, 2012. "An Integrated DSS for Groundwater Management Based on Remote Sensing. The Case of a Semi-arid Aquifer in Morocco," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3209-3230, September.
    2. Wu, Xin & Zheng, Yi & Wu, Bin & Tian, Yong & Han, Feng & Zheng, Chunmiao, 2016. "Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach," Agricultural Water Management, Elsevier, vol. 163(C), pages 380-392.
    3. Mahmoud Mohammad Rezapour Tabari & Mohsen Mazak Mari, 2016. "The Integrated Approach of Simulation and Optimization in Determining the Optimum Dimensions of Canal for Seepage Control," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1271-1292, February.
    4. Yang, Gaiqiang & Liu, Lei & Guo, Ping & Li, Mo, 2017. "A flexible decision support system for irrigation scheduling in an irrigation district in China," Agricultural Water Management, Elsevier, vol. 179(C), pages 378-389.
    5. Murat Kilic & Suer Anac, 2010. "Multi-Objective Planning Model for Large Scale Irrigation Systems: Method and Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(12), pages 3173-3194, September.
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