EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Historical Relationship between Snow Depth and Damaged Area in South Korea

Gunhui Chung1 and Heeseong Park2
Gunhui Chung and Heeseong Park
  • 1Hoseo University, Civil Engineering, Chungcheongnam-do, Korea, Republic of (
  • 2Corresponding Author, Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Gyeonggi-do, Korea, Republic of (

Recently, snow disasters have been increased in South Korea due to the unexpected heavy snow in a region where winter gives little snow. For instance, 10 people were dead by the collapsed roof due to the unusual heavy snow. Many local governments do not have enough snow removal equipment because of little snow in winter season. Therefore, it has been important to estimate the amount of snow damage to prepare heavy snow disaster. There are not many researches to estimate damage of snow disaster in South Korea. In this study, historical snow damage data from 1994~2018 recorded in National Disaster Report were used to predict the future snow disaster damage using a statistical equation. However, it was not easy to predict the amount of snow damage when the heavy snow is happened in the area where no snow during the winter in history. Therefore, the relationship between the snow depth and damaged area were analyzed using the historical damage data. Principal multiple regression method was applied to develop the snow damage estimation function using the damaged area. The developed model could be applied to plan the budget for the snow removal equipment or snow damage reduction.



This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Intelligent Management Program for Urban Water Resources Project, funded by Korea Ministry of Environment(MOE) (2019002950002).


How to cite: Chung, G. and Park, H.: Historical Relationship between Snow Depth and Damaged Area in South Korea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19549,, 2020