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An efficient supply management in water flow network using graph spectral techniques

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Abstract

An efficient way of distributing water in urban cities is one of the major global challenges of our time. A Water Distribution Network (WDN) is a vital infrastructure, intended to provide fresh water to households within a city or designated boundary. Given the WDN’s complexity, effective numerical techniques are required to aid in the development of an ideal monitoring system. Flow meters and gate valves should be placed in low-connected areas of the WDN with water flow reaching several regions of the network. This study proposes a general strategy for assisting water utilities in making decisions for effective water supply. The aim of the research is to use weighted spectral clustering algorithms to outline water districts while addressing hydraulic restrictions via weighted adjacency and Laplacian matrices of the weighted network. This work aims to identify influenced nodes in the network based on Eigen centrality and effectively distribute water across those nodes. This project also looks at how to measure the network’s connection strength to avoid water leaks. The best clusters are found using Eigenvalues and Eigenvectors of weighted adjacency matrices and Laplacian matrices of the water network in the proposed graph spectral framework. In order to establish the optimum water network division approach, topological and graph metrics were used to compare multiple spectral clustering techniques. The proposed graph spectral approach is tested using a genuine water distribution network serving an urban area of Coimbatore city in India and offering a method for partitioning complex networks that employ the spectral graph partitioning algorithm.

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Availability of data and material

All data generated or analyzed during this study are included in this article (and its supplementary information files)

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Abbreviations

WDN:

Water Distribution Network

DMA:

District Meter Area

WNC:

Water Network Clustering

GST:

Graph Spectral Techniques

EPA:

Environmental Protection Agency

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    Authors and Affiliations

    1. Department of Mathematics, PSG College of Technology, Coimbatore, 641004, Tamil Nadu, India

      Tamilselvi Gopalsamy & Vasanthi Thankappan

    2. Department of Computer Applications, PSG College of Technology, Coimbatore, 641004, Tamil Nadu, India

      Sundar Chandramohan

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    1. Tamilselvi Gopalsamy
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    2. Vasanthi Thankappan
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    3. Sundar Chandramohan
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    Contributions

    Tamilselvi, G: writing original draft. Vasanthi, T: review and supervision. Sundar, C: review and editing.

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    Correspondence to Tamilselvi Gopalsamy.

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    Responsible Editor: Arshian Sharif

    Vasanthi Thankappan and Sundar Chandramohan contributed equally to this work.

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    Gopalsamy, T., Thankappan, V. & Chandramohan, S. An efficient supply management in water flow network using graph spectral techniques. Environ Sci Pollut Res 30, 2530–2543 (2023). https://doi.org/10.1007/s11356-022-22335-y

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