IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v38y2024i4d10.1007_s11269-024-03736-9.html
   My bibliography  Save this article

Pressure Sampling Design for Estimating Nodal Water Demand in Water Distribution Systems

Author

Listed:
  • Yu Shao

    (Zhejiang University, Key Laboratory of Drinking Water Safety and Distribution Technology of Zhejiang Province)

  • Kun Li

    (Zhejiang University, Key Laboratory of Drinking Water Safety and Distribution Technology of Zhejiang Province)

  • Tuqiao Zhang

    (Zhejiang University, Key Laboratory of Drinking Water Safety and Distribution Technology of Zhejiang Province)

  • Weilin Ao

    (SiChuan Communication Surveying & Design Institute Co., LTD)

  • Shipeng Chu

    (Zhejiang University, Key Laboratory of Drinking Water Safety and Distribution Technology of Zhejiang Province)

Abstract

The water distribution system (WDS) hydraulic model is extensively used for design and management of WDS. The nodal water demand is the crucial parameter of the model that requires accurate estimating by the pressure measurements. Proper pressure sampling design is essential for estimating nodal water demand and improving model accuracy. Existing research has emphasized the need to enhance the observability of monitoring systems and mitigate the adverse effects of monitoring noise. However, methods that simultaneously consider both of these factors in sampling design have not been adequately studied. In this study, a novel two-objective sampling design method is developed to improve the system observability and mitigate the adverse effects of monitoring noise. The approach is applied to a realistic network and results demonstrate that the developed approach can effectively improve the observability and robustness of the system especially when considerable measurement noise is considered.

Suggested Citation

  • Yu Shao & Kun Li & Tuqiao Zhang & Weilin Ao & Shipeng Chu, 2024. "Pressure Sampling Design for Estimating Nodal Water Demand 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. 38(4), pages 1511-1527, March.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:4:d:10.1007_s11269-024-03736-9
    DOI: 10.1007/s11269-024-03736-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-024-03736-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-024-03736-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andrea Menapace & Diego Avesani, 2019. "Global Gradient Algorithm Extension to Distributed Pressure Driven Pipe Demand Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(5), pages 1717-1736, March.
    2. Shipeng Chu & Tuqiao Zhang & Xinhong Zhou & Tingchao Yu & Yu Shao, 2022. "An Efficient Approach for Nodal Water Demand Estimation in Large-scale Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 491-505, January.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Kostner, Michael K. & Zanfei, Ariele & Alberizzi, Jacopo C. & Renzi, Massimiliano & Righetti, Maurizio & Menapace, Andrea, 2023. "Micro hydro power generation in water distribution networks through the optimal pumps-as-turbines sizing and control," Applied Energy, Elsevier, vol. 351(C).
    7. Panagiota Galiatsatou & Panagiota Stournara & Ioannis Kavouras & Michail Raouzaios & Christos Anastasiadis & Filippos Iosifidis & Dimitrios Spyrou & Alexandros Mentes, 2025. "Combining Geographic Information Systems and Hydraulic Modeling to Analyze the Hydraulic Response of an Urban Area Under Different Conditions: A Case Study to Assist Engineering Practice," Geographies, MDPI, vol. 5(2), pages 1-25, April.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. Yumin Wang, 2023. "Joint-Probabilistic Double-Sided Random Interval Programming for Booster Optimization in Water Distribution Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 501-520, January.
    13. Dominik Schojda & Jan Scheipers & Jürgen Roes & Harry Hoster, 2025. "Modelling and Transient Simulation of District Heating Networks Based on a Control Theory Approach," Energies, MDPI, vol. 18(3), pages 1-22, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:38:y:2024:i:4:d:10.1007_s11269-024-03736-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.