Open AccessInfrastructure failure propagations and recovery strategies from an Alpine Fault earthquake scenario
Author(s) -
Alistair J. Davies,
Conrad Zorn,
Thomas Wilson,
Liam Wotherspoon,
Sarah Beavan,
Tim Davies,
Matthew W. Hughes
Publication year - 2021
Publication title -
bulletin of the new zealand society for earthquake engineering/nzsee quarterly bulletin
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.917
H-Index - 36
eISSN - 2324-1543
pISSN - 1174-9857
DOI - 10.5459/bnzsee.54.2.82-96
Subject(s) - interdependence , resilience (materials science) , risk analysis (engineering) , critical infrastructure , computer science , community resilience , vulnerability (computing) , asset (computer security) , government (linguistics) , business , process management , environmental resource management , computer security , resource (disambiguation) , environmental science , computer network , linguistics , philosophy , physics , political science , law , thermodynamics
While it is well established that community members should participate in resilience planning, participation with genuine decision-making power remains rare. We detail an end-to-end disaster impact reduction modelling framework for infrastructure networks, embedded within a scenario-based participatory approach. Utilising the AF8+ earthquake scenario, we simulate hazard exposure, asset failure and recovery of interdependent critical infrastructure networks. Quantifying service levels temporally offers insights into possible interdependent network performance and community disconnection from national networks, not apparent when studying each infrastructure in isolation. Sequencing participation enables feedbacks between integrated modelling and participants’ impact assessments. Shared ownership of modelling outputs advances stakeholders’ understanding of resilience measures, allowing real-time implementation, increasing community resilience. Readily understood by central government, this format may increase support and resourcing, if nationally significant. Finally, this method tested integrated modelling and impacts assessments, identifying and enabling improvements for both.