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Probabilistic decision-support framework for community resilience: Incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network

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  • Kameshwar, Sabarethinam
  • Cox, Daniel T.
  • Barbosa, Andre R.
  • Farokhnia, Karim
  • Park, Hyoungsu
  • Alam, Mohammad S.
  • van de Lindt, John W.

Abstract

A probabilistic decision support framework is developed in this study for community resilience planning under multiple hazards using performance goals based guidelines such as the Oregon Resilience Plan and the National Institute of Standards and Technology Community Resilience Planning Guide. Herein, resilience of community infrastructure systems is defined as the joint probability of achieving robustness and rapidity based performance goals, which is quantified using Bayesian networks. The framework assesses the effects of decision support options such as selection of hazards, resilience goals, and mitigation (ex-ante) and response (ex-post) strategies to identify measures that can improve infrastructure performance to meet community defined resilience goals. This framework is applied for resilience assessment of building, transportation, water, and electric power infrastructure systems in Seaside, Oregon, under combined earthquake ground shaking and tsunami inundation hazards corresponding to different return periods. Uncertainties in damage, restoration, and economic losses are explicitly considered and propagated in the framework using Monte Carlo simulation (MCS). The MCS results are then used to inform the Bayesian network, which evaluates the joint resilience of infrastructure systems in Seaside. Results highlight the impact of considering different performance goals, introduction of ex-ante and ex-post measures, and interdependencies between various infrastructure systems on infrastructure resilience.

Suggested Citation

  • Kameshwar, Sabarethinam & Cox, Daniel T. & Barbosa, Andre R. & Farokhnia, Karim & Park, Hyoungsu & Alam, Mohammad S. & van de Lindt, John W., 2019. "Probabilistic decision-support framework for community resilience: Incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:reensy:v:191:y:2019:i:c:s0951832018315163
    DOI: 10.1016/j.ress.2019.106568
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    References listed on IDEAS

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    3. Ghazanfar Ali Anwar & Mudasir Hussain & Muhammad Zeshan Akber & Mustesin Ali Khan & Aatif Ali Khan, 2023. "Sustainability-Oriented Optimization and Decision Making of Community Buildings under Seismic Hazard," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
    4. Pawel Gromek & Grzegorz Sobolewski, 2020. "Risk-Based Approach for Informing Sustainable Infrastructure Resilience Enhancement and Potential Resilience Implication in Terms of Emergency Service Perspective," Sustainability, MDPI, vol. 12(11), pages 1-30, June.
    5. Hoang Long Nguyen & Rajendra Akerkar, 2020. "Modelling, Measuring, and Visualising Community Resilience: A Systematic Review," Sustainability, MDPI, vol. 12(19), pages 1-26, September.
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    7. Di Maio, F. & Belotti, M. & Volpe, M. & Selva, J. & Zio, E., 2022. "Parallel density scanned adaptive Kriging to improve local tsunami hazard assessment for coastal infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Xu, Zizhen & Chopra, Shauhrat S., 2022. "Network-based Assessment of Metro Infrastructure with a Spatial–temporal Resilience Cycle Framework," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    9. Stefan Greiving & Mark Fleischhauer & Christian D. León & Leonie Schödl & Gisela Wachinger & Iris Katherine Quintana Miralles & Benjamín Prado Larraín, 2021. "Participatory Assessment of Multi Risks in Urban Regions—The Case of Critical Infrastructures in Metropolitan Lima," Sustainability, MDPI, vol. 13(5), pages 1-21, March.
    10. Goerlandt, Floris & Islam, Samsul, 2021. "A Bayesian Network risk model for estimating coastal maritime transportation delays following an earthquake in British Columbia," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    11. Mujjuni, F. & Betts, T. & To, L.S. & Blanchard, R.E., 2021. "Resilience a means to development: A resilience assessment framework and a catalogue of indicators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    12. Dylan Sanderson & Sabarethinam Kameshwar & Nathanael Rosenheim & Daniel Cox, 2021. "Deaggregation of multi-hazard damages, losses, risks, and connectivity: an application to the joint seismic-tsunami hazard at Seaside, Oregon," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(2), pages 1821-1847, November.
    13. Du, Ao & Wang, Xiaowei & Xie, Yazhou & Dong, You, 2023. "Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective," Reliability Engineering and System Safety, Elsevier, vol. 233(C).

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