Water outage predictions for natural hazards using synthetic water distribution systems

Hazards can impact water systems, leading to water outages that result in economic, environmental, and societal losses. Modeling a system's behavior helps develop short-term restoration strategies and long-term resilience planning. However, data on the topology and operational characteristics of real water systems are often unavailable outside of the utility operating the system, limiting the ability of others depending on the system to understand its vulnerability and resilience. We address this limitation by developing an algorithm that generates a synthetic water distribution system using only publicly available data. Our approach provides hydraulic information at the building level to support infrastructure resilience assessments. We validated our model by comparing the network topologic and hydraulic properties with data from the real water system of Ann Arbor, Michigan. Our synthetic model results indicate that 95% of the simulated building-level pressures were within <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo> <mml:mspace></mml:mspace> <mml:mn>25</mml:mn></mml:mrow> <mml:annotation>$ \pm \;25$</mml:annotation></mml:semantics> </mml:math> PSI of the hydraulic model data from the existing system. To demonstrate an application of our model, we simulated water outages at the building level using hazard loading and fragility functions corresponding to an earthquake scenario.

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Publication Details

Journal
Risk Analysis
Published
2025-02-21
DOI
https://doi.org/10.1111/risa.70004
Citations
2
Primary Topic
Water Systems and Optimization
Type
article
Field-Weighted Citation Impact
1.91
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article

Water outage predictions for natural hazards using synthetic water distribution systems

Theodore Hu, Keith Smith, Seth David Guikema, Zaira Pagan‐Cajigas et al.
2 citations
Risk Analysis
Water Systems and Optimization
1.91
article

Water outage predictions for natural hazards using synthetic water distribution systems

Theodore Hu, Keith Smith, Seth David Guikema, Zaira Pagan‐Cajigas, Thomas Chen, Rosalia Otaduy‐Ramirez, Vanessa Woolley
article en
2 citations

Abstract

Hazards can impact water systems, leading to water outages that result in economic, environmental, and societal losses. Modeling a system's behavior helps develop short-term restoration strategies and long-term resilience planning. However, data on the topology and operational characteristics of real water systems are often unavailable outside of the utility operating the system, limiting the ability of others depending on the system to understand its vulnerability and resilience. We address this limitation by developing an algorithm that generates a synthetic water distribution system using only publicly available data. Our approach provides hydraulic information at the building level to support infrastructure resilience assessments. We validated our model by comparing the network topologic and hydraulic properties with data from the real water system of Ann Arbor, Michigan. Our synthetic model results indicate that 95% of the simulated building-level pressures were within <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo> <mml:mspace></mml:mspace> <mml:mn>25</mml:mn></mml:mrow> <mml:annotation>$ \pm \;25$</mml:annotation></mml:semantics> </mml:math> PSI of the hydraulic model data from the existing system. To demonstrate an application of our model, we simulated water outages at the building level using hazard loading and fragility functions corresponding to an earthquake scenario.

Risk AnalysisVol. 45(8)
Cornell University (US), University of Michigan (US), Knoxville College (US), Stantec (United States) (US), Xylem (United States) (US)
Openalex Percentile: Top 17%
Water Systems and Optimization
1.91
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Water outage predictions for natural hazards using synthetic water distribution systems — Theodore Hu, Keith Smith, et al. · Risk Analysis (2025) | TGRS Research Map | TGRS