무한방향흐름기법을 이용한 산사태 위험도 평가

Estimation of Landslide Risk based on Infinity Flow Direction

Abstract

본 연구에서는 경상북도 전체를 대상으로 공간분포형 습윤지수와 뿌리보강무한사면안정해석 이론을 활용한 광역적인 산사태 분석을 실시하였다. 해석을 수행하기 위해 수치지도와 정밀토양도, 임상도 등을 이용하여 지형 지질학적 매개변수를 추출하고 $10m{\times}10m$ 해상도의 공간분포형 데이터베이스를 구축하였으며, 공간분포형 습윤지수를 생성하기 위한 비 집수면적은 무한방향흐름기법을 적용하였다. 광역적인 산사태 위험도 평가를 위한 안전율은 4개 등급으로 구분하여 도시하였다. 위험도 평가결과, 산사태 위험지역은 봉화와 김천 등 실제 최근의 산사태 발생지역과 유사성을 갖는 것으로 나타났으며 특히 산지와 인접한 지역에 unstable 지역이 집중적으로 분포되어 있는 것으로 분석되었다. 또한 산사태 기록과 비교해본 결과, 본 해석모형이 합리적인 매개변수의 축적을 통해 광역적인 산사태 위험성을 평가하는 유효한 방법임을 확인할 수 있다.

In this study, it was conducted a broad-area landslide analysis for the entire area of Kyungsangbuk-do Province based on spatially-distributed wetness index and root reinforcement infinity slope stability theory. Specifically, digital map, soil map and forest map were used to extract topological and geological parameters, and to build spatially-distributed database at $10m{\times}10m$ resolution. Infinity flow direction method was used for rain catchment area to produce spatially-distributed wetness index. The safety level that indicates risk of a broad-area landslide was classified into four groups. The result showed that areas with a high estimated risk of a landslide coincided with areas that recently went through an actual landslide, including Bonghwa and Gimcheon, and unstable areas were clustered around mountainous areas. A comparison between the estimation result and the records of actual landslide showed that the analysis model is effective for estimating a risk of a broad-area landslide based on accumulation of reasonable parameters.

Fig. 1. Comparison of flow direction methods for contributing area calculation

Fig. 2. Infinity flow direction algorithm

Fig. 3. Hydrologic unit map of study area

Fig. 4. Slope of the sub-catchments (unit: ^°)

Fig. 5. Hydraulic conductivity distribution

Fig. 6. Effective soil depth distribution

Fig. 7. Soil unit weight distribution

Fig. 8. Soil cohesion distribution

Fig. 9. Soil friction angle distribution

Fig. 10. Root cohesion distribution

Fig. 11. Spacial distribution of maximum rainfall with year

Fig. 12. Spacial distribution of hazard grade classification in steep slope with year

Fig. 13. Spacial distribution of average landslide hazard grade

Fig. 14. Spacial distribution of average landslide hazard gradewith administration area

Table 1. Resently landslide occurrence with year (e-나라지표, 2018)

Table 2. Facet elevation and factors for slope and angle calculations (Tarboton, 1997)

Table 3. Roots tensile strength with major species (MPa)

Table 4. Roots cohension with forest types (MPa)

Table 5. Root cohesion based on the administrative units (MPa)

Table 6. The number by causes of landslide occurrence in Joseon dynasty (Lee et al., 2013)

Table 7. Current state of landslide with administration area