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Coupling mode-destination accessibility with seismic risk assessment to identify at-risk communities

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  • Miller, Mahalia
  • Baker, Jack W.

Abstract

In this paper, we develop a framework for coupling mode-destination accessibility with quantitative seismic risk assessment to identify communities at high risk for travel disruptions after an earthquake. Mode-destination accessibility measures the ability of people to reach destinations they desire. We use a probabilistic seismic risk assessment procedure, including a stochastic set of earthquake events, ground-motion intensity maps, damage maps, and realizations of traffic and accessibility impacts. For a case study of the San Francisco Bay Area, we couple our seismic risk framework with a practical activity-based traffic model. As a result, we quantify accessibility risk probabilistically by community and household type. We find that accessibility varies more strongly as a function of travelers׳ geographic location than as a function of their income class, and we identify particularly at-risk communities. We also observe that communities more conducive to local trips by foot or bike are predicted to be less impacted by losses in accessibility. This work shows the potential to link quantitative risk assessment methodologies with high-resolution travel models used by transportation planners. Quantitative risk metrics of this type should have great utility for planners working to reduce risk to a region׳s infrastructure systems.

Suggested Citation

  • Miller, Mahalia & Baker, Jack W., 2016. "Coupling mode-destination accessibility with seismic risk assessment to identify at-risk communities," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 60-71.
    • Handle: RePEc:eee:reensy:v:147:y:2016:i:c:p:60-71
    DOI: 10.1016/j.ress.2015.10.018
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    References listed on IDEAS

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    1. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-130, January.
    2. World Bank & United Nations, 2010. "Natural Hazards, UnNatural Disasters : The Economics of Effective Prevention," World Bank Publications - Books, The World Bank Group, number 2512.
    3. R Cervero & K-L Wu, 1997. "Polycentrism, Commuting, and Residential Location in the San Francisco Bay Area," Environment and Planning A, , vol. 29(5), pages 865-886, May.
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    Cited by:

    1. Boakye, Jessica & Guidotti, Roberto & Gardoni, Paolo & Murphy, Colleen, 2022. "The role of transportation infrastructure on the impact of natural hazards on communities," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    2. Gangwal, Utkarsh & Dong, Shangjia, 2022. "Critical facility accessibility rapid failure early-warning detection and redundancy mapping in urban flooding," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    3. Liu, Qiang & Tang, Aiping & Huang, Delong & Huang, Ziyuan & Zhang, Bin & Xu, Xiuchen, 2022. "Total probabilistic measure for the potential risk of regional roads exposed to landslides," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    4. Ming Fang & Yi Zhang & Mengjue Zhu & Shaopei Chen, 2022. "Cause Mechanism of Metro Collapse Accident Based on Risk Coupling," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
    5. Silva-Lopez, Rodrigo & Bhattacharjee, Gitanjali & Poulos, Alan & Baker, Jack W., 2022. "Commuter welfare-based probabilistic seismic risk assessment of regional road networks," Reliability Engineering and System Safety, Elsevier, vol. 227(C).

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