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Risk classification and uncertainty propagation for virtual water distribution systems

Author

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  • Torres, Jacob M.
  • Brumbelow, Kelly
  • Guikema, Seth D.

Abstract

While the secrecy of real water distribution system data is crucial, it poses difficulty for research as results cannot be publicized. This data includes topological layouts of pipe networks, pump operation schedules, and water demands. Therefore, a library of virtual water distribution systems can be an important research tool for comparative development of analytical methods. A virtual city, “Micropolis†, has been developed, including a comprehensive water distribution system, as a first entry into such a library. This virtual city of 5000 residents is fully described in both geographic information systems (GIS) and EPANet hydraulic model frameworks. A risk classification scheme and Monte Carlo analysis are employed for an attempted water supply contamination attack. Model inputs to be considered include uncertainties in: daily water demand, seasonal demand, initial storage tank levels, the time of day a contamination event is initiated, duration of contamination event, and contaminant quantity. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. High uncertainties in exposure patterns lead to greater resources needed for more effective mitigation strategies.

Suggested Citation

  • Torres, Jacob M. & Brumbelow, Kelly & Guikema, Seth D., 2009. "Risk classification and uncertainty propagation for virtual water distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1259-1273.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:8:p:1259-1273
    DOI: 10.1016/j.ress.2009.01.008
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    Cited by:

    1. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2020. "Optimization of time constrained N-version programming service components with competing task execution and version corruption processes," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    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.
    3. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2022. "Co-residence based data theft game in cloud system with virtual machine replication and cancellation," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    4. Atiyeh Bozorgi & Abbas Roozbahani & Seied Mehdy Hashemy Shahdany & Rouzbeh Abbassi, 2021. "Development of Multi-Hazard Risk Assessment Model for Agricultural Water Supply and Distribution Systems Using Bayesian Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3139-3159, August.
    5. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2021. "Minimization of Expected User Losses Considering Co-resident Attacks in Cloud System with Task Replication and Cancellation," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    6. Gregory Levitin & Liudong Xing & Hong‐Zhong Huang, 2019. "Security of Separated Data in Cloud Systems with Competing Attack Detection and Data Theft Processes," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 846-858, April.
    7. Jensen, H.A. & Jerez, D.J., 2018. "A Stochastic Framework for Reliability and Sensitivity Analysis of Large Scale Water Distribution Networks," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 80-92.
    8. Mo, Huadong & Xie, Min & Levitin, Gregory, 2015. "Optimal resource distribution between protection and redundancy considering the time and uncertainties of attacks," European Journal of Operational Research, Elsevier, vol. 243(1), pages 200-210.
    9. Morteza Babaei & Abbas Roozbahani & S. Mehdy Hashemy Shahdany, 2018. "Risk Assessment of Agricultural Water Conveyance and Delivery Systems by Fuzzy Fault Tree Analysis Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 4079-4101, September.

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