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A Pipe Ranking Method for Water Distribution Network Resilience Assessment Based on Graph-Theory Metrics Aggregated Through Bayesian Belief Networks

Author

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  • Alessandro Pagano

    (Istituto di Ricerca Sulle Acque del Consiglio Nazionale delle Ricerche (IRSA-CNR), U.O.S. di Bari)

  • Raffaele Giordano

    (Istituto di Ricerca Sulle Acque del Consiglio Nazionale delle Ricerche (IRSA-CNR), U.O.S. di Bari)

  • Ivan Portoghese

    (Istituto di Ricerca Sulle Acque del Consiglio Nazionale delle Ricerche (IRSA-CNR), U.O.S. di Bari)

Abstract

The resilience assessment is crucial for many infrastructures, including water supply and distribution networks. In particular, the identification of the ‘critical’ components (nodes or pipes) whose failure may negatively affect network performances and system resilience is a key issue, with a direct relevance for decision-makers involved in planning, management and improvement activities. Among the multiple methods and tools available, the use of graph-theory metrics is a cutting-edge research topic, as the analysis of topological properties may provide simple yet reliable information on the performance of complex networks. In the present work, we aim to overcome the limit associated to the use of individual graph-theory metrics, identifying a subset of relevant metrics that are directly connected to network resilience properties, using them to perform a ‘network degradation analysis’ in case of single pipe failure and finally proposing an aggregation of the results using a Bayesian Belief Network. Ultimately, the proposed methodology provides a ranking of the most critical pipes, i.e. those that contribute most to system resilience. A real water distribution network in Italy is used for model development and validation.

Suggested Citation

  • Alessandro Pagano & Raffaele Giordano & Ivan Portoghese, 2022. "A Pipe Ranking Method for Water Distribution Network Resilience Assessment Based on Graph-Theory Metrics Aggregated Through Bayesian Belief Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5091-5106, October.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:13:d:10.1007_s11269-022-03293-z
    DOI: 10.1007/s11269-022-03293-z
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    References listed on IDEAS

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    1. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    2. Manuel Herrera & Edo Abraham & Ivan Stoianov, 2016. "A Graph-Theoretic Framework for Assessing the Resilience of Sectorised Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1685-1699, March.
    3. A. Simone & C. Di Cristo & O. Giustolisi, 2022. "Analysis of the isolation valve system in water distribution networks using the segment graph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3561-3574, August.
    4. Alessandro Pagano & Chris Sweetapple & Raziyeh Farmani & Raffaele Giordano & David Butler, 2019. "Water Distribution Networks Resilience Analysis: a Comparison between Graph Theory-Based Approaches and Global Resilience Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2925-2940, June.
    5. Agathoklis Agathokleous & Chrystalleni Christodoulou & Symeon E. Christodoulou, 2017. "Topological Robustness and Vulnerability Assessment of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 4007-4021, September.
    6. Manuel Herrera & Edo Abraham & Ivan Stoianov, 2016. "A Graph-Theoretic Framework for Assessing the Resilience of Sectorised Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1685-1699, March.
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    Cited by:

    1. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.

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