## 3 Data and Processes
### Proxy Variable Selection  
For feasible and reasonable outcomes in vulnerability assessments, the proxy variables should be carefully selected for each assessment component relevant to the objective of the vulnerability assessment. This study employed the three constituent components such as exposure, sensitivity, and adaptability in the conceptual framework by the IPCC [1] as primary assessment components. Exposure is defined as \"the nature and degree to which a system is exposed to significant climatic variations\" in the IPCC [1], and also described as \"degree, duration, and/or extent in which the system is in contact with, or subject to, the perturbation\" by [PERSON] [11]. Sensitivity is defined as \"the degree to which a system is affected, either adversely or beneficially, by climate-related stimuli\" in the IPCC [1], and also described as \"the elements exposed within the system (e.g., people, property, infrastructure, etc. ), which influence the probabilities of being harmed at times of hazardous floods\" by [PERSON] and [PERSON] [44]. Adaptability is defined as \"the ability of a system to adjust to climate change, to moderate potential damages, to take advantage of opportunities, or to cope with the consequences\" in the IPCC [1], and also described as \"the collective capacity of the human actors in the system to manage resilience\" by [PERSON] et al. [45]. The possible available efforts are required to reduce the controversy and difficulties in selecting proxy variables for the vulnerability assessments. Thus, two proxy variables, which are deemed relevant to human and properties are identified based on the IPCC's widely referred assessment components. A comprehensive review was carried out for previously published flood vulnerability assessment articles [13; 14; 15; 16; 17; 19; 20; 21; 23; 30; 31; 32; 34; 35] to select each proxy variable for the study site, as presented in Table 1. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
\begin{tabular}{c} **Primary** \\ **Components** \\ \end{tabular} & \multicolumn{2}{c}{**Intermediate Components**} & \multicolumn{1}{c}{**Proxy Variables**} & \multicolumn{1}{c}{**Units**} \\ \hline \multirow{2}{*}{Exposure} & Potential & \multirow{2}{*}{-} & \multirow{2}{*}{Lvelihood} & Heavy rainy days & Days \\  & Impact & & Vulnerability & Flooded area ratio & km\({}^{2}\)/km\({}^{2}\) \\ \hline \multirow{3}{*}{Sensitivity} & Potential & Internal & \multirow{2}{*}{-} & Children and elderly & \\  & Impact & Factor & & population density & \\ \cline{4-5}  & & & & Major facilities and & \\ \cline{4-5}  & & & & infrastructure density & \\ \hline \multirow{2}{*}{Adaptability} & \multirow{2}{*}{-} & Internal & \multirow{2}{*}{Lvelihood} & Emergency service density & number/km\({}^{2}\) \\  & & Factor & Vulnerability & Drainage system capacity & m\({}^{3}\)/min \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The proxy variables selected for the flood vulnerability assessment in the three primary components, exposure, sensitivity, and adaptability, based on the concept of the IPCC [1]. Figure 1: The location map of the study site with administrative districts in the Republic of Korea. To represent the duration and extent to which the study site is influenced by flood events, the proxy variables for the exposure component comprised of days of heavy rainfall greater than 80 mm per day [52] and ratio of flooded area to each administrative district area. The heavy rainy days were temporally averaged for the past decade during 2008 to 2017 years and then computed by Thiessen polygons method [53] as the mean areal values for the 231 administrative districts from the 50 gauge stations managed by the Korea Meteorological Administration [49]. The flooded area ratio data were constructed as the annual average of the past decade data during 2008 to 2017 years for the 231 administrative districts from the flood damage data by the National Disaster Information Center [54].