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Enhancing Knowledge in Water Distribution Networks via Data Assimilation

Author

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  • Cristiana Bragalli

    (University of Bologna)

  • Matteo Fortini

    (University of Bologna)

  • Ezio Todini

    (University of Bologna)

Abstract

This paper deals with uncertainty estimation and knowledge enhancement in water distribution networks (WDNs). A new three steps data assimilation approach is introduced, which in combination with multi-objective optimization, allows selecting effective and affordable monitoring networks. An innovative cascade of Ensemble Kalman Filters is used to assimilate the information deriving from sensors measuring pressure heads, flow in pipes and demands, with the objective of increasing knowledge while preserving at the same time the structural relationships among state variables. Selection of the most appropriate and economically affordable measurement network, is then based on the derivation of a Pareto front using the NSGA-II algorithm in conjunction with the data assimilation approach. The front is obtained by compromising between the overall sensors cost and the uncertainty reduction (or knowledge enhancement), which is expressed as a function of the Total Variance of state variables. The operational use of the proposed data assimilation approach as well as the effectiveness of the chosen observation network is also demonstrated by showing the reduction of uncertainty deriving from successive assimilations of real-time observations.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:11:d:10.1007_s11269-016-1372-0
    DOI: 10.1007/s11269-016-1372-0
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    Cited by:

    1. Emilio Ruiz & Sarai Díaz & Javier González, 2022. "State Variable Implications on Hydraulic State Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2549-2569, June.
    2. 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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