Automated sub-zoning of water distribution systems

Lina Sela Perelman, Michael Allen, Ami Preis, Mudasser Iqbal, Andrew J. Whittle

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    64 Citations (Scopus)


    Water distribution systems (WDS) are complex pipe networks with looped and branching topologies that often comprise thousands to tens of thousands of links and nodes. This work presents a generic framework for improved analysis and management of WDS by partitioning the system into smaller (almost) independent sub-systems with balanced loads and minimal number of interconnections. This paper compares the performance of three classes of unsupervised learning algorithms from graph theory for practical sub-zoning of WDS: (1) Global clustering – a bottom-up algorithm for clustering n objects with respect to a similarity function, (2) Community structure – a bottom-up algorithm based on the property of network modularity, which is a measure of the quality of network partition to clusters versus randomly generated graph with respect to the same nodal degree, and (3) Graph partitioning – a flat partitioning algorithm for dividing a network with n nodes into k clusters, such that the total weight of edges crossing between clusters is minimized and the loads of all the clusters are balanced. The algorithms are adapted to WDS to provide a practical decision support tool for water utilities. Visual qualitative and quantitative measures are proposed to evaluate models' performance. The three methods are applied for two large-scale water distribution systems serving heavily populated areas in Singapore.
    Original languageEnglish
    Pages (from-to)1-14
    JournalEnvironmental Modelling & Software
    Issue numberMarch 2015
    Publication statusPublished - Mar 2015

    Bibliographical note

    This paper is not yet available on the repository


    National Research Council through the Singapore-MIT Alliance for Research and Technology (SMART)


    • Water distribution systems
    • Community structure
    • Graph clustering and partitioning


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