기후변화 취약성 평가지표의 개발 및 도입방안

Abstract

Abstract Development and application of a climate change vulnerability index Vulnerability assessment plays a vital role in setting up climate change adaptation policies. The concept of vulnerability, however, is difficult to functionally define due to the fact that vulnerability itself includes many aspects (biophysical, socioeconomic, etc.) in various sectors. As such, much research on vulnerability has used indicators which are useful for standardization and aggregation. Although there are a few studies on sectoral vulnerability assessment in Korea, we have very few studies to develop and apply cross-sectoral climate change vulnerability indicators. The objective of this study is to develop an index to assess the climate change vulnerability of each local government (Si, Do) in Korea. Identification of local vulnerabilities and analysis of the components comprising the vulnerability would help local governments develop appropriate and sound adaptation policy frameworks. As the climate change vulnerability index by Moss et al.(2001) was not applicable to assess local vulnerabilities in Korea, we decided to develop a modified index adjusted for the Korean context. The conceptual framework of climate change vulnerability was defined as a function of climate exposure, sensitivity, and adaptive capacity. Then, we collected statistical data on 33 variables assumed to comprise climate change vulnerability by 16 local governments (Si, Do). The time spans of the variables are from 1986 to 2006. After collecting statistical data, data was standardized using the dimension index suggested by UNDP (2006). A Vulnerability-Resilience Indicator (VRI) was calculated using Moss et al. (2001)'s method. Please note that high VRI indicates low vulnerability because our VRI combines negative values of climate exposure and sensitivity and positive values of adaptive capacity at the same time. The local governments (Si, Do) of lower VRI (highly vulnerable) are generally located in island and coastal areas, whereas regions of higher VRI (moderately or low vulnerable) are generally concentrated in urban areas. Low vulnerability in urban area was mostly explained by high economic capacity. To verify the VRI suggested in this study, data on casualty due to extreme weather by NEMA (National Emergency Management Agency) and VRI were compared and the Pearson Correlation Coefficient was calculated. The output showed that the correlation coefficient between casualty due to extreme weather events (NEMA data) and VRI was 0.62. This suggests that the indicator developed was verified as a useful tool to explain local variances of climate change vulnerability. To identify the major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted (MatLab, 2006). The result of PCA showed that the first 5 principal components (PC 1~PC 5) explained approximately 72% of the total variance. The PC 1 was correlated with variables of infrastructure, GDP, and the variables of human health. The PC 2 and PC 3 were closely related to climate exposure data (precipitation and temperature), forest areas, and human health. This study provided the information on regional vulnerability to climate change in Korea. This study would support the need to set up regionally- adjusted adaptation policies and provide the quartitative backgrounds for policy prioritization. Future studies should focus on further application of VRI to prepare regionally-adjusted guidelines for setting up adaptation strategies. Projections of future vulnerabilities for each local government would also help set up medium- to long-term adaptation policies.