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지역산림환경을 기반으로 한 산사태 발생 위험성의 예측 및 평가

Prediction and Evaluation of Landslide Hazard Based on Regional Forest Environment

  • 마호섭 (경상대학교 산림환경자원학과(농업생명과학연구원)) ;
  • 강원석 (경상대학교 산림환경자원학과(농업생명과학연구원)) ;
  • 이성재 (서울대학교 학술림)
  • Ma, Ho-Seop (Department of Forest Environmental Resources, Gyeongsang National University (Institute of Agriculture Life Science)) ;
  • Kang, Won-Seok (Department of Forest Environmental Resources, Gyeongsang National University (Institute of Agriculture Life Science)) ;
  • Lee, Sung-Jae (University Forest, Seoul National University)
  • 투고 : 2013.11.06
  • 심사 : 2014.05.08
  • 발행 : 2014.06.30

초록

본 연구는 지역산림지역을 중심으로 수량화이론을 이용하여 산사태 발생면적에 영향을 미치는 인자를 도출하여 각 인자의 기여도 분석을 통해 산사태 발생 위험성에 대한 예측기준을 마련하고, 그 기준을 평가하였다. 산사태 발생지 붕괴면적에 영향을 미치는 인자는 모암(화성암), 횡단사면(복합), 침엽수림(임상), 사면경사($21{\sim}30^{\circ}$ 이상)이었다. 각 인자의 Range를 추정한 결과, 횡단사면 (0.2922)이 가장 높게 나타났고, 다음으로는 모암(0.2691), 임상(0.2631), 사면경사(0.2312)순으로 나타났다. 산사태 발생 위험도 판정표를 기준으로 4개 인자의 category별 점수를 계산한 추정치 범위는 0 점에서 1.0556 점 사이에 분포하고 있으며, 중앙값은 0.5278 점이었다. I 등급의 점수는 0.7818 이상, II 등급은 0.5279~7917, III 등급은 0.2694~0.5278, IV 등급은 0.2693 이하로 나타났다. 1 등급 및 2 등급에서 산사태 발생 비율이 72%로서 비교적 높은 적중률을 보였다. 따라서 본 판정표는 산사태 위험도 판정에 활용 가능한 것으로 판단된다.

This study was carried out to propose the criteria for the prediction of landslide occurrence through analysis the influence of each factor by using the quantification theory. The results obtained from this study are summarized as follows. From a stepwise regression analysis between the landslide area($m^2$) and environmental factors, the factors strongly affecting the landslide sediment($m^2$) were the Parents rock (igneous), cross slope(complex), coniferous forests (forest type) and slope gradient ($21{\sim}30^{\circ}$). According to the range, it was shown in order of Cross slope (0.2922), Parents rock (0.2691), Forest type (0.2631) and Slope gradient (0.2312). The range of prediction score of landslide occurrence has been distributed between score 0 and score 1.0556, the median value was score 0.5278. The prediction for class I was over 0.7818, for class II was 0.5279 to 0.7917, for class III 0.2694 to 0.5278 and for class IV was below 0.2693. The prediction on landslide occurrence appeared relatively high accuracy rate as 72% for class I and II. Therefore, this score table for landslide will be very useful for judgement of dangerous slope.

키워드

참고문헌

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피인용 문헌

  1. Prediction of Debris Flow Hazard in High Mountain Areas vol.49, pp.5, 2015, https://doi.org/10.14397/jals.2015.49.5.13
  2. Development of Prediction Technique of Landslide Using Forest Environmental Factors vol.52, pp.4, 2018, https://doi.org/10.14397/jals.2018.52.4.63
  3. Analysis of Landslide Characteristics of the Central Regions in Korea vol.53, pp.1, 2014, https://doi.org/10.14397/jals.2019.53.1.61
  4. Development of Prediction Technique of Landslide Hazard of Central Regions in Korea vol.53, pp.3, 2014, https://doi.org/10.14397/jals.2019.53.3.7
  5. 산악형 국립공원지역의 산사태 발생과 취약지역 특성 분석 vol.108, pp.4, 2014, https://doi.org/10.14578/jkfs.2019.108.4.552
  6. Development of Prediction Technique of Debris Flow Hazard Areas at Rugged Mountain Range of the Jeollabuk-do, Korea vol.54, pp.5, 2020, https://doi.org/10.14397/jals.2020.54.5.73
  7. 산림소유역 토사유출량에 의한 사방댐 시공적지 예측기법 개발 vol.109, pp.4, 2020, https://doi.org/10.14578/jkfs.2020.109.4.438
  8. 설악산 국립공원 지역 토석류 발생가능성 평가 기법의 개발 vol.110, pp.1, 2014, https://doi.org/10.14578/jkfs.2021.110.1.64