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A New Method for Simultaneous Calibration of Demand Pattern and Hazen-Williams Coefficients in Water Distribution Systems

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  • Mehdi Dini
  • Massoud Tabesh

Abstract

Water distribution systems, where flow in some pipes is not measured or storage tanks are connected together, calculation of demand pattern coefficients of the network is difficult. Since, Hazen-Williams coefficients of the network are also unknown; the problem is becoming unintelligible further. The present study proposes a new method for simultaneous calibration of demand pattern and Hazen-Williams coefficients that uses the Ant Colony Optimization (ACO) algorithms coupled with the hydraulic simulator (EPANET2) in a MATLAB code. In this paper demand pattern and Hazen-Williams coefficients are the calibration parameters and measured data consist of nodal pressure heads and pipe flows. The defined objective function minimizes the difference between the measured and simulated values. The new proposed method was tested on a two-loop test example and a real water distribution network. The results show that the new calibration model is able to calibrate demand pattern and Hazen-Williams coefficients simultaneously with high precision and accuracy. Copyright The Author(s) 2014

Suggested Citation

  • Mehdi Dini & Massoud Tabesh, 2014. "A New Method for Simultaneous Calibration of Demand Pattern and Hazen-Williams Coefficients in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 2021-2034, May.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:7:p:2021-2034
    DOI: 10.1007/s11269-014-0592-4
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    References listed on IDEAS

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    1. Shanmugam Kumar & Shankar Narasimhan & S. Murty Bhallamudi, 2010. "Parameter Estimation in Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(6), pages 1251-1272, April.
    2. Zheng Wu & Christopher Clark, 2009. "Evolving Effective Hydraulic Model for Municipal Water Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(1), pages 117-136, January.
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    Cited by:

    1. Mehdi Dini & Asghar Asadi, 2020. "Optimal Operational Scheduling of Available Partially Closed Valves for Pressure Management in Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2571-2583, June.
    2. Erfan Hajibandeh & Sara Nazif, 2018. "Pressure Zoning Approach for Leak Detection in Water Distribution Systems Based on a Multi Objective Ant Colony Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2287-2300, May.
    3. Chia-Cheng Shiu & Chih-Chung Chung & Tzuping Chiang, 2024. "Enhancing the EPANET Hydraulic Model through Genetic Algorithm Optimization of Pipe Roughness Coefficients," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(1), pages 323-341, January.
    4. Shipeng Chu & Tuqiao Zhang & Chengna Xu & Tingchao Yu & Yu Shao, 2021. "Dealing with Data Missing and Outlier to Calibrate Nodal Water Demands in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2863-2878, July.
    5. Gustavo Meirelles & Daniel Manzi & Bruno Brentan & Thaisa Goulart & Edevar Luvizotto, 2017. "Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(13), pages 4339-4351, October.
    6. Cristiana Bragalli & Matteo Fortini & Ezio Todini, 2016. "Enhancing Knowledge in Water Distribution Networks via Data Assimilation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 3689-3706, September.
    7. Jian Wang & Bangwu Deng & Shuai Jiang & Zhuozhi Deng & Wei Wang & Guowei Chen & Li Liu, 2024. "Optimizing Control of Secondary Water Supply Tanks for Demand Peak Staggering," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(11), pages 4123-4136, September.
    8. Zheng, Xuejing & Shi, Zhiyuan & Wang, Yaran & Zhang, Huan & Tang, Zhiyun, 2024. "Digital twin modeling for district heating network based on hydraulic resistance identification and heat load prediction," Energy, Elsevier, vol. 288(C).
    9. Alemtsehay G. Seyoum & Tiku T. Tanyimboh, 2016. "Investigation into the Pressure-Driven Extension of the EPANET Hydraulic Simulation Model for Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5351-5367, November.

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