기후변화 적응을 위한 격자기반의 풍해 위험도 평가

Assessment of a Grid-Based Wind Disaster Risk for Climate Change Adaptation

본 연구에서는 기후변화에 관한 정부간 협의체에서 정립한 기후변화 적응을 위한 위험도의 개념을 적용하여 풍해 위험도 평가모형을 개발하고 대구광역시, 울산광역시, 경상북도, 강원도를 대상으로 위험도를 평가하였다. 네 개의 대리변수인 위해성, 노출도, 취약성, 적응역량 자료를 구축하였고 대리변수간의 연산을 통해 위험지도를 작성하였다. 행정구역별 위험도 평균 분석 결과, 전체 54개 행정구역 중 13.0%인 7개 행정구역의 위험도 등급이 ‘매우위험’, 1.9%인 1개 행정구역이 ‘위험’, 14.8%인 8개 행정구역이 ‘약간위험’ 등급으로 평가되었다. 이 지역들의 대리변수 평균 등급은 위해성 ‘매우높음’, 노출도 ‘낮음’, 취약성 ‘약간높음’, 적응역량 ‘보통’ 등급으로 위해성과 취약성이 위험도 증가에 큰 영향을 미치는 것으로 나타났다. 한편, 위험도 등급이 ‘약간낮음’ 등급 이하인 행정구역은 31.5%인 17개로 분석 되었다. 이 지역들의 대리변수 평균 등급은 위해성 ‘약간낮음’, 노출도 ‘매우낮음’, 취약성 ‘약간높음’, 적응역량 ‘약간낮음’ 등급으로 위해성과 노출도가 위험도 감소에 큰 영향을 미치는 것으로 분석 되었다.

In this study, a wind disaster risk assessment model applying the concept of risk for adaptation to climate change, established by the Intergovernmental Panel on Climate Change, was developed, and a risk assessment was conducted for Daegu City, Ulsan City, Gyeongsangbuk Province, and Gangwon Province. Four proxy variables, including hazard, exposure, vulnerability, and adaptive capacity, were developed, and the risks were mapped through analysis of the proxy variables. The results from the analysis of average risk across administrative districts showed that the risk severity of the seven administrative districts, which makes up 13.0% of the total 54 administrative districts, is ‘very high’. One administrative district that is 1.9% of the total administrative districts shows a ‘high’ risk severity, and eight administrative districts that make up 14.8% of the total administrative districts were rated as ‘moderately high’. The mean of the proxy variables in these regions was calculated to be “very high” for hazard, “low” for exposure, “moderately high” for vulnerability, and “moderate” for adaptive capacity. Therefore, the increase in risk in these regions was found to be highly influenced by hazard and vulnerability. On the other hand, the number of administrative districts whose risk level is rated below ‘low’ risk severity was 17, which is about 31.5% of the total administrative districts. The mean of the proxy variables in these regions was estimated to be “moderately low” for hazard, “very low” for exposure, “moderately high” for vulnerability, and “moderately low” for adaptive capacity. Therefore, the decrease in risk in these regions was found to be highly influenced by hazard and exposure.