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A Study to Define Area of Concern for Potential Soil Loss in Geumgang Watershed by KORSLE-based GIS model

한국형 토양유실공식의 GIS 기반 모형에 의한 금강 유역에 대한 토양유실 우심지역 선정에 관한 연구

  • Kim, Jonggun (Dept of Regional Infrastructure Engineering, Kangwon National University) ;
  • Yang, JaeE (Dept of Biological Environment, Kangwon National University) ;
  • Lim, Kyoung Jae (Dept of Regional Infrastructure Engineering, Kangwon National University) ;
  • Kim, Sung Chul (Bio Environmental Chemistry, Chungnam National University) ;
  • Lee, Giha (Dept of Construction and Disaster Prevention Engineering, Kyungpook National University) ;
  • Hwang, Sangil (Korea Environment Institute) ;
  • Yu, Nayoung (Rural Construction Engineering, Kongju National University) ;
  • Park, Youn Shik (Rural Construction Engineering, Kongju National University)
  • 김종건 (강원대학교 지역건설공학과) ;
  • 양재의 (강원대학교 바이오자원환경학과) ;
  • 임경재 (강원대학교 지역건설공학과) ;
  • 김성철 (충남대학교 생물환경화학과) ;
  • 이기하 (경북대학교 건설방재공학부) ;
  • 황상일 (한국환경정책평가연구원) ;
  • 유나영 (공주대학교 생물산업공학부) ;
  • 박윤식 (공주대학교 생물산업공학부)
  • Received : 2017.11.20
  • Accepted : 2017.12.06
  • Published : 2017.12.31

Abstract

Universal soil loss equation (USLE) has been frequently employed to estimate potential soil loss in land since it was developed based on the statewide data measured and collected in the United States. The equation is an empirical model mainly used for U.S. soil, thus it has been recently modified to reflect Korean soil conditions and named as Korean Soil Loss Equation (KORSLE). The modified equation was implemented in ArcGIS software, and used for estimation of potential soil loss from 2003 to 2016 in the thirty-eight Water Protection Districts. Five out of the thirty-eight districts were identified as the area of potential soil erosion most severly. In those five districts, potential soil erosion were estimated to be more than 50 Mg/ha/year that requires site investigation under supervision of the Korean Ministry of Environment. Distinctive site characteristics were found in the potential soil loss estimation such that the districts of low potential soil loss had low five factors in the aggregate. However, if one of more factors are dominantly large, the potential soil loss significantly increased. This study provides a useful tool to identify the potential areas for soil erosion and the important factors that play an important role in the estimation process.

Keywords

References

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