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Integrated Decision Support System for Prognostic and Diagnostic Analyses of Water Distribution System Failures

Author

Listed:
  • M. Shafiqul Islam

    (Massachusetts Institute of Technology)

  • Rehan Sadiq

    (University of British Columbia)

  • Manuel J. Rodriguez

    (Université Laval)

  • Homayoun Najjaran

    (University of British Columbia)

  • Mina Hoorfar

    (University of British Columbia)

Abstract

This paper presents an innovative decision support system (DSS) for prognostic and diagnostic analyses of water distribution system (WDS) failures. The framework of the DSS is based on four novel models developed and published by the authors of this paper. The four models include reliability assessment model, leakage potential model, leakage detection model, and water quality failure potential model. Information obtained from these models together with external information such as customer complaints, lab test results (if any), and historical information are integrated using Dempster-Shafer (D-S) theory to evaluate prognostic and diagnostic capabilities of the DSS. The prognostic capabilities of the DSS provide hydraulic and water quality states of a WDS whereas the diagnostic capabilities of the DSS help to identify the failure location with minimal time after the occurrence and will help to reduce false positive and false negative predictions. The framework has ‘unique’ capacity to bring the modeling information (hydraulic and Quality), consumer complaints, historical failure data, and laboratory test information under a single platform to perform a prognostic and diagnostic investigation of WDS failures (hydraulic and Quality). The proof of concept of the DSS has been demonstrated using data used in published four articles. The outcomes of this research widely addressed the uncertainties associated with WDS which improves the efficiency and effectiveness of diagnosis and prognosis analyses of WDS. It is expected that the developed integrated framework will help municipalities to make informed decisions to increase the safety, reliability and the security of public health.

Suggested Citation

  • M. Shafiqul Islam & Rehan Sadiq & Manuel J. Rodriguez & Homayoun Najjaran & Mina Hoorfar, 2016. "Integrated Decision Support System for Prognostic and Diagnostic Analyses of Water Distribution System Failures," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2831-2850, June.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:8:d:10.1007_s11269-016-1326-6
    DOI: 10.1007/s11269-016-1326-6
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    References listed on IDEAS

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    1. Beynon, Malcolm J., 2005. "A novel technique of object ranking and classification under ignorance: An application to the corporate failure risk problem," European Journal of Operational Research, Elsevier, vol. 167(2), pages 493-517, December.
    2. M. Islam & Rehan Sadiq & Manuel Rodriguez & Homayoun Najjaran & Alex Francisque & Mina Hoorfar, 2013. "Evaluating Water Quality Failure Potential in Water Distribution Systems: A Fuzzy-TOPSIS-OWA-based Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2195-2216, May.
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    Cited by:

    1. Zaid Tashman & Christoph Gorder & Sonali Parthasarathy & Mohamad M. Nasr-Azadani & Rachel Webre, 2020. "Anomaly Detection System for Water Networks in Northern Ethiopia Using Bayesian Inference," Sustainability, MDPI, vol. 12(7), pages 1-16, April.

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