Evaluating landslide hazards using RCP 4.5 and 8.5 scenarios

Ho Gul Kim, Dong Kun Lee, Chan Park, Sungho Kil, Yonghoon Son, Jin Han Park

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Recently, extreme meteorological events have occurred frequently owing to climate change and its influence. Impacts of concentrated precipitation events include the damage caused by landslides. Many areas in Gangwondo (Korea) are located at high elevation and have large elevation differences; these areas are thus at high risk of landslides. The purpose of this study was to evaluate the landslide hazard of the province using representative concentration pathways (RCP) scenarios 4.5 and 8.5 and to compare results. This study produced an optimal landslide model for the province through analysis of variables and points of landslide origin. Estimates indicate that the landslide hazard area will increase to 154 km2. The RCP 8.5 scenario showed a larger (by about 59 km2) landslide hazard area than the RCP 4.5 scenario. The uncertainty of climate change scenarios was also explored using statistical values of each scenario period. An overlay analysis (overlay of landslide hazard areas and land cover map) showed that 40.6 % of farmlands would be susceptible to landslides in 2070–2099 (RCP 8.5). Additionally, damage to the alpine agriculture due to landslides was also identified as a critical area. In the RCP 8.5 scenario, the land-use types that occupy more than 20 % of the landslide hazard area are transportation, recreational facilities, and vinyl house for farming. This suggests that casualties from landslides will increase in future. It also highlights a lack of policies to manage development. Therefore, the local government of Gangwondo should consider landslide hazard areas when planning future land uses.

Original languageEnglish
Pages (from-to)1385-1400
Number of pages16
JournalEnvironmental Earth Sciences
Issue number3
StatePublished - Feb 2015


  • Climate change scenario
  • Gangwondo
  • Landslide susceptibility map
  • Maximum entropy model


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