Current flood vulnerability analyses rely on deterministic methods (e.g., stage–damage functions) to quantify resulting damage and losses to the built environment. While such approaches have been used extensively by communities, they do not enable the propagation of uncertainty into a risk- or resilience-informed decision process. In this paper, a method that allows the development of building fragility and building loss functions is articulated and applied to develop an archetype portfolio that can be used to model buildings in a typical community. The typical single-variable flood vulnerability function, normally based on flood depth, is extended to a multi-variate flood vulnerability function, which is a function of both flood depth and flood duration, thereby creating fragility surfaces. The portfolio presented herein consists of 15 building archetypes that can serve to populate a community-level model to predict damage and resulting functionality from a scenario flood event. The prediction of damage and functionality of buildings within a community is the first step in developing risk-informed mitigation decisions to improve community resilience.
Propagation of uncertainty in physicochemical data to force field predictions