In this study, we use multiple linear regression to develop a function for predicting damage caused by typhoons. The number of explanatory independent variables constituting the damage prediction function is large and varied because typhoon damage is attributed to a combination of factors such as heavy rain, strong wind, and waves. However, existing data of typhoon damage are insufficient for developing a damage prediction function. To resolve this problem, a model for prediction power only was developed, and the leave-one-out-cross-validation (LOOCV)-forward selection method was applied to select the variables. In addition, the power transformation of Tukey's Ladder of Powers was adopted to create linearity in the dependent and independent variables. The typhoon damage prediction function was developed for 22 districts with more than 16 datasets. The transformation factor λ, representing these 22 districts, was shown to vary according to the regional characteristics of each city and district. The best results occurred when λ = 0.2 and λ = 0.3 for the normalized root-mean-square error (NRMSE) and coefficient of determination ( ) standards, respectively.

Typhoon cause damage through simultaneous flooding, strong winds, and storms; they have been one of the most damaging disasters of the last decade. In this study, we develop a typhoon risk index (TRI) based on records of typhoon damage that occurred in 229 municipalities across South Korea since 1994. The TRI employs a pressure-state-response (PSR) framework system. For the pressure index (PI), we use ten indicators that represent hydro-meteorological, regional, and socioeconomic characteristics. The state index (SI) includes three indicators related to typhoons and the response index (RI) comprises six indicators including financial status and disaster mitigation-related projects and facilities. The weighting of each indicator for the TRI was calculated using an entropy method. The PIs are higher in the Seoul metropolitan and southern coast areas of the Korean peninsula. The SIs are higher for the southern and eastern coastal areas. It is not easy to determine a regional trend for the RIs. The TRI is higher for the southern and eastern coasts and the Jirisan and Deogyusan areas. These regions are consistent with the areas where typhoons have frequently caused damage. The TRI developed in this research will contribute to decision-making about the priority of disaster prevention projects to mitigate typhoon damage.