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산사태 모니터링 오탐지율 개선을 위한 토양수분자료 활용에 관한 연구

A study of applying soil moisture for improving false alarm rates in monitoring landslides

  • 오승철 (성균관대학교 건설환경시스템공학과) ;
  • 정재환 (성균관대학교 건설환경연구소) ;
  • 최민하 (성균관대학교 수자원학과) ;
  • 윤홍식 (성균관대학교 건설환경시스템공학과)
  • Oh, Seungcheol (Civil, Architectural and Environmental System Engineering, Sungkyunkwan University) ;
  • Jeong, Jaehwan (Center for Built Environment, Sungkyunkwan University) ;
  • Choi, Minha (Department of Water Resources, Sungkyunkwan University) ;
  • Yoon, Hongsik (Civil, Architectural and Environmental System Engineering, Sungkyunkwan University)
  • 투고 : 2021.09.24
  • 심사 : 2021.10.08
  • 발행 : 2021.12.31

초록

강수는 공극수압의 상승에 관여해 토양 강도 및 응력의 변동을 발생시켜 산사태의 주요 원인 인자 중 하나로 지목된다. 따라서 강수는 산사태 발생 임계값 산정에 빈번히 사용되나, 지반 안정성을 직접적으로 산정하고 예측하기에는 무리가 있어 오탐지 사건에 대한 분석에는 한계가 있다. 한편 토양수분은 공극수압의 변동에 보다 직접적인 연관성을 지니므로, 다수의 연구에서 지반 안정성의 정량적인 평가에 활용된 바 있다. 이에 본 연구에서는 산사태 발생에 대한 임계값 산정에 있어 토양수분 인자 활용의 적정성을 평가하고자 하였다. 먼저 두 수문 인자의 거동 분석을 통해 강수에 대한 토양 포화도의 반응성을 파악하고, 선행 강수지수(Antecedent Precipitation Index)를 활용해 산사태 발생 임계값을 산정하였다. 이후 토양 포화도를 활용하여 산사태 발생 임계값을 산정했으며, 분할표를 활용해 두 임계값을 정성적으로 평가하였다. 그 결과, 일 강수량(Pdaily)을 단일 인자로 사용해 결정된 산사태 발생 임계값 대비 괴산읍에서는 각각 75% (API), 42% (SM)의 향상을 보였고 창수면에서는 각각 33% (API), 44% (SM)의 향상을 보였다. 따라서 토양수분과 선행 강수지수 모두 임계성공지수(Critical Success Index)를 효과적으로 향상시켰으며 오탐지율을 감소시켰다. 추후 토양 포화도를 통해 산사태 발생에 요구되는 강우 강도를 산정하는 연구와 토양 포화도 수준에 따른 강우 저항성을 산정하는 연구 등 토양수분 자료를 다각적으로 접목한 연구가 수행된다면 산사태 예측 정확성을 향상시키는 데 기여할 수 있을 것으로 보인다.

Precipitation is one of a major causes of landslides by rising of pore water pressure, which leads to fluctuations of soil strength and stress. For this reason, precipitation is the most frequently used to determine the landslide thresholds. However, using only precipitation has limitations in predicting and estimating slope stability quantitatively for reducing false alarm events. On the other hand, Soil Moisture (SM) has been used for calculating slope stability in many studies since it is directly related to pore water pressure than precipitation. Therefore, this study attempted to evaluate the appropriateness of applying soil moisture in determining the landslide threshold. First, the reactivity of soil saturation level to precipitation was identified through time-series analysis. The precipitation threshold was calculated using daily precipitation (Pdaily) and the Antecedent Precipitation Index (API), and the hydrological threshold was calculated using daily precipitation and soil saturation level. Using a contingency table, these two thresholds were assessed qualitatively. In results, compared to Pdaily only threshold, Goesan showed an improvement of 75% (Pdaily + API) and 42% (Pdaily + SM) and Changsu showed an improvement of 33% (Pdaily + API) and 44% (Pdaily + SM), respectively. Both API and SM effectively enhanced the Critical Success Index (CSI) and reduced the False Alarm Rate (FAR). In the future, studies such as calculating rainfall intensity required to cause/trigger landslides through soil saturation level or estimating rainfall resistance according to the soil saturation level are expected to contribute to improving landslide prediction accuracy.

키워드

과제정보

이 논문은 교육부 및 한국연구재단의 4단계 두뇌한국21 사업(4단계 BK21 사업)으로 지원된 연구임. 이 논문은 행정안전부 '자연재난 정책연계형 기술개발사업'의 지원을 받아 수행된 연구임(2021-MOIS35-003). 이 논문은 2021년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(NRF-2021R1A6A3A01087645).

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