Multi-variate and single-variable flood fragility and loss approaches for buildings
Omar M. Nofal,
John W. van de Lindt and
Trung Q. Do
Reliability Engineering and System Safety, 2020, vol. 202, issue C
Propagating uncertainties in flood damage models is a critical step towards a risk-informed decision methodology that is based on quantitative assessment. Flood-related data scarcity and the use of deterministic models present challenges when seeking to include uncertainties in flood damage modeling. In this paper, a single-variable and multi-variate component-based flood fragility method is proposed. The method uses expert-based data derived from online sources that are applied within a Monte Carlo framework to divide the building into independent components and then assigns these components to five predefined damage states that describe the building damage as a whole. Using a series of Monte Carlo simulations, uncertainties in flood depth and flood duration that result in each damage level for each component were propagated. Their damage is then characterized using component fragility functions to be used to develop total building fragility and loss functions. The resulting fragilities can be used as a probabilistic vulnerability function to be assigned to a real community based on building archetype and occupancy. The ability to develop flood fragility curves for buildings without the need for empirical field data is the primary contribution of this work.
Keywords: Resilience; Flood loss, Flood vulnerability, Fragility function, Loss function (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:202:y:2020:i:c:s0951832019313262
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