Modeling Joint Probability of Wind and Flood Hazards in Boston

Abstract

The Atlantic Coast of the United States is subjected to damage from wind and flooding as a result of coastal storms. This paper seeks to model the joint probability of exceedance for wind speed and flood elevation, two common measures of storm severity, using the storm data provided by the North Atlantic Coast Comprehensive Study. A case study is performed for Boston, Massachusetts. A copula is used to model the dependence between storm severity measures. The Gaussian copula and the Archimedean copulas (i.e., Gumbel, Clayton, and Frank) are examined in this paper. The correlation matrix used to construct the Gaussian copula is estimated empirically, and the parameters of the Archimedean copulas are estimated by a semi-parametric estimation method. The Gumbel copula, which is found to describe the dependence between the severity measures better than other copulas, is used to develop a copula-based joint probability model. The methodology presented in this paper is used to estimate joint hazard curves for wind speed and flood elevation for different mean recurrence intervals. The results can be used to define hazard scenarios in a multihazard study, estimate building performance under coastal storms, and assess community resilience.