Fragility and Vulnerability Models for Buildings Impacted by Hurricane Surge and Waves

This paper presents a vulnerability assessment and fragility analysis using 3,408 buildings impacted by Hurricane Ian (2022) in Fort Myers Beach, Florida. The vulnerability assessment was conducted to identify key parameters affecting performance of buildings under surge and wave loadings. The correlation analysis was conducted to evaluate the linear relationship between parameters and to inform the selection of predictor variables for vulnerability models. Multivariable vulnerability functions were developed for wood-frame and masonry/concrete buildings based on several damage state groups and predictor variables: distance from shoreline; effective year-built; flood zone; and total water elevation above the first-floor elevation or lowest horizontal structural member. The results indicate that the distance from shoreline is a significant predictor variable, which is highly correlated with shielding effects of nearshore structures and the attenuation of waves. Further, there is a moderate correlation between the distance from shoreline and flood zone. Comparisons of observed and predicted damage states showed overall good agreement, particularly with the gradation of higher structural damage near the shoreline and decreasing damage further inland. The accuracy of vulnerability models strongly depends on the damage state group. For wood-framed buildings, merging the damage states increases the accuracy of vulnerability models, with the average cross-classification rates (CCR) ranging from 44% to 85%. A similar trend is observed for masonry/concrete buildings with CCR ranging from 36% to 80%. Replacing the distance from shoreline with the flood zone as a predictor variable reduces the accuracy of models by an average of 12%, but it can enhance the model applicability to other regions vulnerable to coastal flooding.