Citation

Contento A, Xu H, Gardoni P. Struct. Infrastruct. Eng. 2020; 16(4): 547-566.

Copyright

(Copyright © 2020, Informa - Taylor and Francis Group)

DOI

10.1080/15732479.2020.1721543

PMID

unavailable

Abstract

The impact of several devastating hurricanes revealed the vulnerability of large areas of the U.S.A. to this catastrophic natural hazard. Therefore, especially considering the uncertainties in future climate and demographic conditions, exposure and vulnerability, there is a strong need to include storm surge predictions in hurricane risk analyses. In general, the models used for storm surge are unsuited for probabilistic studies that require a large number of simulations. This article presents a probabilistic formulation for storm surge predictions that are developed using the combination of a logistic model and a non-stationary random field. The proposed fully probabilistic formulation (i) provides the probability that a location is being flooded, (ii) considers the spatial correlation among the storm surge at different locations and (iii) predicts storm surge at locations that are different from those of the observations used for the model calibration and are not restricted to be alongshore. Such formulation can include the effects of climate change by calibrating the models with high-fidelity simulations that account for the effect of climate change performed using a realistic set of hurricanes. The proposed formulation is used to predict the storm surge in a specific geographic region near the Pamlico River in North Carolina.

Language: en

Keywords

floods; Hurricanes; predictions; probabilistic models; simulation models