최대 엔트로피 모형을 활용한 기후변화 시나리오 기반 산사태 취약성평가

Climate change has a significant impact on the occurrence of landslides, and as it intensifies, abnormal weather such as cold waves, heavy snowfall, torrential rains, and typhoons will become more frequent, leading to an increase in disasters. This study constructed a maximum entropy (MaxEnt) model using geospatial information and meteorological factors (using representative concentration pathways (RCP) 8.5 and RCP 4.5 scenarios) from landslide occurrence locations from 2010 to 2020 and simulated the national probability of landslide occurrence per year from 2021 to 2085. A vulnerability assessment was performed considering the government’s policy and budget, and the possible damage caused by landslides was quantitatively evaluated. The results of the impact assessment showed that the probability of landslide occurrence based on the RCP 8.5 scenario was 1.8 times higher in the 2030s, 1.7 times higher in the 2050s, and 7.2 times higher in the 2080s than that based on the RCP 4.5 scenario. In addition, passive and active mitigation, assuming a constant increasing rate of policy budget, showed a difference in reduction of landslide risk. Applying passive mitigation in the impact and vulnerability assessments reduced the risk of landslides by a minimum of 47.7% to a maximum of 52.6%. Active mitigation reduced the risk of landslide occurrence from a minimum of 63.6% to a maximum of 68.4%. The results of this study provide basic data for local governments to determine the priorities of landslide prevention projects. However, future research should consider landslide damage intensity and the physical limitations in spatialization of the adaptive capacity considered in the vulnerability evaluation.