Comparative Analysis of Future Landslide Susceptible Areas Based on Climate Change Scenario Applications

Abstract

Background and objective: Landslides have inflicted significant damage to human lives and property for many years, leading to substantial socio-economic costs and environmental degradation. With the advent of climate change, the increase and intensification of rainfall exacerbate the risk of landslides. Considering this scenario, understanding the priorities in landslide response becomes crucial. This study aims to compare methods of predicting future landslide-prone areas, explore accurate forecasting techniques, and determine the landslide response priorities at the municipal level in the study Methods: (1) Collection and development of the landslide inventory map and landslide conditioning factors. (2) Constructing the landslide susceptibility model (LSM) using the landslide inventory map and conditioning factors. (3) Projecting rainfall data from periods B and C onto the LSM of past period A. (4) Comparing and analyzing landslide-prone areas for each scenario and year. (5) Identifying areas vulnerable to landslides based on the scenario with the most frequent occurrence of landslide-prone areas during the rainy seasons in periods B and C.Results: From the LSM, the landslide susceptible area (LSA) for period A was identified as 31,902 ㎢. All Supply-side platform(SSP) scenarios displayed an increasing trend in landslide-prone areas, with the SSP5-8.5 scenario displaying the most significant increase. Taking this into consideration, landslide response priorities were established, with Goseong County in South Gyeongsang ranking first with an LSA ratio of 88.4%. This suggests that this area should be prioritized for future landslide risk mitigation.Conclusion: The study provides a foundational model for future landslide response strategies which consider environmental changes. limitations of the study were challenges in considering landslide conditioning factors other than rainfall when analyzing future landslide susceptibility. Future studies will aim to provide more reliable information through higher resolution analysis and damage scale predictions and to discern response priorities.