Distribution, Characteristics, and Deformation Tendency of Cracks in Landslide: a Case Study of Baishuihe Landslide, Puge County, Sichuan Province, China

( Kun He ),( Xiewen Hu ),( Guotao Ma ),( Bo Liu ) 대한지질공학회 2019 대한지질공학회 학술발표회논문집 Vol.2019 No.2

Deformed cracks are widely spread in landslide area, which have significant effects on geometry as well as motion patterns of landslides. A typical landslide named Baishuihe Landslide was selected here for giving a comprehensive analysis for deeply understanding about distribution, characteristics, and deformation tendency of landslide cracks. The landslide, with complicated deformation behaviors, activated in 2012 and reactivated in 2015 and 2016, respectively. Through detailed investigation, geological mapping, as well as unmanned aerial vehicle (UAV) photos interpretation, in-situ monitoring, the cracks data as well as landslide patterns were deeply studied here. It suggests that the cracks types are highly related to slope failure motion patterns. According to the penetrating depth and geometry of the cracks, it can be divided into two types: shallow cracks and deep cracks. The shallow cracks would become the margins of local failures, while the deep ones could be the foundation for further slope instability. More importantly, the potential landslide with creeping slide state is determined by both shallow and deep cracks simultaneously, which contribute to the ongoing slope deformation. Moreover, cracks change soil stress distribution and make it be limit equilibrium state, resulting in landslides under small water infiltration, and also, that can aggregate surface water and increase the probability of rainfall-induced landslides. The research work, with the perspective of cracks, can give new insight for landslide risk assessments and mitigation countermeasures for potential failure.

Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling

Pradhan, B.,Lee, S. Elsevier Science 2010 Environmental modelling & software Vol.25 No.6

Data collection for landslide susceptibility modeling is often an inhibitive activity. This is one reason why for quite some time landslides have been described and modelled on the basis of spatially distributed values of landslide-related attributes. This paper presents landslide susceptibility analysis in the Klang Valley area, Malaysia, using back-propagation artificial neural network model. A landslide inventory map with a total of 398 landslide locations was constructed using the data from various sources. Out of 398 landslide locations, 318 (80%) of the data taken before the year 2004 was used for training the neural network model and the remaining 80 (20%) locations (post-2004 events) were used for the accuracy assessment purpose. Topographical, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Eleven landslide occurrence related factors were selected as: slope angle, slope aspect, curvature, altitude, distance to roads, distance to rivers, lithology, distance to faults, soil type, landcover and the normalized difference vegetation index value. For calculating the weight of the relative importance of each factor to the landslide occurrence, an artificial neural network method was developed. Each thematic layer's weight was determined by the back-propagation training method and landslide susceptibility indices (LSI) were calculated using the trained back-propagation weights. To assess the factor effects, the weights were calculated three times, using all 11 factors in the first case, then recalculating after removal of those 4 factors that had the smallest weights, and thirdly after removal of the remaining 3 least influential factors. The effect of weights in landslide susceptibility was verified using the landslide location data. It is revealed that all factors have relatively positive effects on the landslide susceptibility maps in the study. The validation results showed sufficient agreement between the computed susceptibility maps and the existing data on landslide areas. The distribution of landslide susceptibility zones derived from ANN shows similar trends as those obtained by applying in GIS-based susceptibility procedures by the same authors (using the frequency ratio and logistic regression method) and indicates that ANN results are better than the earlier method. Among the three cases, the best accuracy (94%) was obtained in the case of the 7 factors weight, whereas 11 factors based weight showed the worst accuracy (91%).

질량비 변화에 따른 산사태 모형으로 인해 발생하는 충격파 특성분석

조한울(Han Woll Cho),이호진(Ho Jin Lee),김성덕(Sung Duk Kim) 한국산학기술학회 2023 한국산학기술학회논문지 Vol.24 No.5

산사태로 인해 유발되는 충격파는 일반적으로 산사태 충격파(Landslide-impulse wave)라고 부른다. 산사태 충격파는 댐, 저수지, 호수, 화산섬 및 피오르드(fjord) 등 특정 지역에 국한되지 않고 발생하며, 수역인근에서 발생하는 산사태 충격파의 경우는 주변의 인명과 기반시설에 심각한 피해를 끼칠 수 있다. 특히 산악지대에서는 급경사의 계곡과 상당수의 댐과 같은 수공 구조물 등이 위치하고 있는 경우가 많아 작은 규모의 지진만으로도 위력적인 산사태 충격파가 발생할 수 있다. 한 가지 예시로 산사태 충격파로 인해 1963년 이탈리아 바이온트(Vaiont)에서는 수천 명의 사망자가 발생하였다. 최근에는 전 세계적으로 이상기후의 영향 때문에 국지성 집중호우가 빈번하게 발생하고 있으며, 이로 인해 국내에서 발생하는 지진과 산사태의 발생빈도와 발생규모 모두 증가하고 있다. 우리나라도 더 이상 산사태 충격파로부터 안전하지 않고, 산사태 충격파로부터의 위험을 줄이기 위해서는 충격파 특성들에 대한 더 나은 이해능력은 필수적이다. 따라서 본 연구에서는 산사태 충격파의 특성들을 알아보고자 산사태 모형실험을 수행하였다. 산사태 모형으로는 블록형태 산사태 모형과 입상형태 산사태 모형을 이용하였으며, 산사태 모형으로부터 유발되는 충격파의 특성 중 진폭을 중점으로 분석하였다. A impulse wave generated by a landslide is commonly referred to as a landslide-impulse wave. Landslide-impulse waves are not limited to specific areas such as dams, reservoirs, lakes, volcanic islands, and fjords. Landslide-impulse waves generated near water bodies can cause serious damage to human life and infrastructure. Steep valleys and many water structures such as dams are often located in mountainous areas, so even a small-scale earthquake can generate a powerful landslide-impulse wave. One example is a landslide-impulse wave that killed thousands in Vaiont, Italy, in 1963. Recently, due to the influence of abnormal weather around the world, localized torrential rains have frequently occurred, and as a result, both the frequency and scale of earthquakes and landslides occurring in Korea are increasing. Korea is no longer safe from landslide-impulse waves, and a better understanding of their characteristics is essential to reduce the risk. Thus, in this study, an experiment was conducted with a landslide model to find out the characteristics of a landslide-impulse wave. Block-type landslide models and granular-type landslide models were used, and the amplitude was observed and analyzed.

Landslide prediction, monitoring and early warning: a concise review of state-of-the-art

채병곤,박혁진,Filippo Catani,Alessandro Simoni,Matteo Berti 한국지질과학협의회 2017 Geosciences Journal Vol.21 No.6

Landslide is one of the repeated geological hazards during rainy season, which causes fatalities, damage to property and economic losses in Korea. Landslides are responsible for at least 17% of all fatalities from natural hazards worldwide, and nearly 25% of annual casualties caused by natural hazards in Korea. Due to global climate change, the frequency of landslide occurrence has been increased and subsequently, the losses and damages associated with landslides also have been increased. Therefore, accurate prediction of landslide occurrence, and monitoring and early warning for ground movements are very important tasks to reduce the damages and losses caused by landslides. Various studies on landslide prediction and reduction in landslide damage have been performed and consequently, much of the recent progress has been in these areas. In particular, the application of information and geospatial technologies such as remote sensing and geographic information systems (GIS) has greatly contributed to landslide hazard assessment studies over recent years. In this paper, the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed. Especially, this paper focused on the evaluation of the landslide susceptibility using probabilistic approach and physically based method, runout evaluation using volume based model and dynamic model, in situ ground based monitoring techniques, remote sensing techniques for landslide monitoring, and landslide early warning using rainfall and physical thresholds.

Mapping Landslide Susceptibility Based on Spatial Prediction Modeling Approach and Quality Assessment

Al-Mamun,Park, Hyun-Su,JANG, Dong-Ho 한국지형학회 2019 한국지형학회지 Vol.26 No.3

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

산사태예측도에 의한 석조문화재 주변의 산사태재해 가능성 분석

김경수 ( Kyeong Su Kim ),이춘오 ( Choon Oh Lee ),송영석 ( Young Suk Song ),조용찬 ( Yong Chan Cho ),김만일 ( Man Il Kim ),채병곤 ( Byung Gon Chae ) 대한지질공학회 2007 지질공학 Vol.17 No.3

산사태가 일어날 지점을 예측한다든지 사태물질로 인한 피해 예상지역을 알아내는 것은 쉬운 일이 아니다. 이는 산사태를 발생시키는 요인들이 여러가지가 있고 개개의 요인들이 산사태를 발생시키는데 기여하는 중요도도 서로 다르기 때문이다. 그러나 많은 산사태자료에 대한 분석을 바탕으로 발생 메커니즘 규명과 통계적 해석기법을 통해 산사태 발생가능성의 예측과 위험지역의 분류가 가능해졌다. 석조문화재가 산사면 또는 그 직하부에 인접해 있는 경우는 산사태가 발생되면 재해에 무방비로 노출되어 있다. 이 연구에서는 여름철의 집중호우 등에 의해 석조문화재 및 그 주변지역에 산사태가 발생할 가능성을 사전에 예측함으로써 그로 인한 석조문화재의 피해가능성을 분석하고자 하였다. 이러한 목적을 위해 2002년 8월 산사태재해로 인해 피해가 발생된 바 있으며 중요 석조문화재가 위치해 있는 실상사 백장암지역을 연구대상지역으로 선정하여 산사태예측도를 작성하였다. 그리고 산사태재해 가능성을 발생확률로 표현하여 등급별로 구분함으로써 석조문화재 및 그 주변지역이 산사태에 취약한지의 여부를 평가하였다. 또한, 이러한 조사 및 해석기법을 앞으로 석조문화재 주변의 산사태재해 예측 및 평가를 위해 실용적으로 활용할 수 있는 토대를 마련하였다. It is a very difficult thing to estimate an occurrence possibility location and hazard expectation area by landslide. The prediction difficulty of landslide occurrence has relativity in factor of various geological physical factors and contributions. However, estimation of landslide occurrence possibility and classification of hazard area became available correlation mechanism through analysis of landslide occurrence through landslide data analysis and statistical analysis. This study analyzed a damage possibility of a cultual heritage area due to landslide occurrence by a heavy rainfall. We make a landslide prediction map and tried to analysis of landslide occurrence possibility for the cultural heritage site. The study area chooses a temple of Silsang-Sa Baekjang-Am site and made a landslide prediction map. In landslide prediction map, landslide hazard possibility area expressed by occurrence probability and divided by each of probability degrees. This degree used to evaluate occurrence possibility for existence and nonexistence of landslide in the study site. For the prediction and evaluation of landslide hazard for the cultural heritage site, investigation and analysis technique which is introduced in this study may contribute an efficient management and investigation in the cultural heritage site, Korea.

Comparative Analysis of Future Landslide Susceptible Areas Based on Climate Change Scenario Applications

김준우,정휘철,김호걸 인간식물환경학회 2023 인간식물환경학회지 Vol.26 No.5

Background and objective: Landslides have inflicted significant damage to human lives and property for many years, leadingto substantial socio-economic costs and environmental degradation. With the advent of climate change, the increase andintensification of rainfall exacerbate the risk of landslides. Considering this scenario, understanding the priorities inlandslide response becomes crucial. This study aims to compare methods of predicting future landslide-prone areas,explore accurate forecasting techniques, and determine the landslide response priorities at the municipal level in the studyMethods: (1) Collection and development of the landslide inventory map and landslide conditioning factors. (2) Constructingthe landslide susceptibility model (LSM) using the landslide inventory map and conditioning factors. (3) Projecting rainfalldata from periods B and C onto the LSM of past period A. (4) Comparing and analyzing landslide-prone areas for eachscenario and year. (5) Identifying areas vulnerable to landslides based on the scenario with the most frequent occurrenceof landslide-prone areas during the rainy seasons in periods B and C. Results: From the LSM, the landslide susceptible area (LSA) for period A was identified as 31,902 ㎢. All Supply-sideplatform(SSP) scenarios displayed an increasing trend in landslide-prone areas, with the SSP5-8.5 scenario displaying themost significant increase. Taking this into consideration, landslide response priorities were established, with GoseongCounty in South Gyeongsang ranking first with an LSA ratio of 88.4%. This suggests that this area should be prioritized forfuture landslide risk mitigation. Conclusion: The study provides a foundational model for future landslide response strategies which consider environmentalchanges. limitations of the study were challenges in considering landslide conditioning factors other than rainfall whenanalyzing future landslide susceptibility. Future studies will aim to provide more reliable information through higherresolution analysis and damage scale predictions and to discern response priorities.

GIS를 이용한 땅밀림지 특성 분석: 산지경사 및 산사태위험등급을 중심으로

박재현,서정일,이창우 한국산림과학회 2019 한국산림과학회지 Vol.108 No.3

This study was carried out to establish basic data for the development of slow-moving landslide hazard classes. Mountain slopes in slow-moving landslide areas ranged from 11.8° to 37.0° with a mean slope of 23.8°. However, the slope inclination of microtopography in slow-moving landslide areas was slightly different, with a mean slope of 23.5° (10.7°~41.5°) compared with the mountain slope. There was a significant difference (p < 0.05) between the contour intervals of microtopography and the contour intervals of the slow-moving landslide areas. Among all the slow-moving landslide areas examined, 14 plots (approximately 38.0%) were classified into landslide hazard class I, 6 plots (approximately 16.0%) into landslide hazard class II, 5 plots (approximately 14.0%) into landslide hazard class III and IV, and 16 plots (approximately 43.0%) into landslide hazard class V, whereas 9 plots (approximately 24.0%) fit the no landslide hazard class. 이 연구는 땅밀림위험등급을 구축하기 위하여 수행되었다. 땅밀림지의 평균산지경사는 23.8°(11.8°~37.0°), 땅밀림지 내에서 미세지형지의 평균사면경사는 23.5° (10.7°~41.5°)로 미소한 차이가 있는 것으로 분석되었다. 땅밀림지 및 땅밀림 재발생지에서 땅밀림지 내 등고선 간격과 땅밀림지 내 미세지형지의 등고선 간격은 5% 수준에서 유의한 결과를 나타내었다. 산사태위험등급에 포함되지 않는 땅밀림지는 전체 땅밀림지 중 1등급이 14개소(약 38.0%), 2등급이 6개소(약16.0%), 3등급과 4등급이 각각 5개소(약 14.0%), 5등급이 16개소(약 43.0%), 산사태위험지등급 외 지역이 9개소(약24.0%)이었다. 땅밀림지 중 산사태위험 1~5등급으로 지정되지 않은 면적 비율이 50.0% 이상인 지역은 8개소(약 22.0%), 20.0%~50.0% 이상인 지역은 18개소(약 49.0%), 20.0% 이상인 지역은 26개소(약 70.0%)이었다.

Assessment and Applicability Analysis of Dynamic Landslide Hazard Using Matrix Approach

Ki Dae Kim,Min Jeng Kang,Chang Woo Lee,Choong Shik Woo,Jun Pyo Seo 위기관리 이론과 실천 2020 Crisisonomy Vol.16 No.9

산사태 발생시점 및 지점을 예측하기 위한 연구는 서로 다른 목적과 범위로 구성되었지만 상호보완적인 역할을 한다. 따라서 이 연구에서는 산림청에서 구축한 산사태 예보체계와 산사태위험지도의 활용성을 높이고자 정적 산사태위험도를 동적 산사태위험도로 변환하고, 이를 평가하기 위해 시공간적 위험도의 매트릭스 결합을 수행하였다. 2017년 산사태 발생지인 충청남도 천안시의 시나리오 및 실제 산사태 발생시점을 대상으로 다양한 매트릭스 평가모형을 적용한 결과, 간단한 행렬 조합만으로 동적 산사태위험도의 정량적 평가를 가능케 하였으며, 정확도 또한 기존의 산사태위험지도에 비해 높게 나타났다. 또한 산림청에서 제공하는 1시간 이후의 산사태 예측정보와 결합을 통해 단기적인 미래의 동적 산사태위험도를 평가할 수 있는 점에 의의가 있다. 이 연구결과는 기구축된 국가산사태 예보체계와 산사태위험지도의 활용성을 극대화함과 동시에 우기 시의 산사태위험지 관리효율성 향상에 기여할 수 있을 것이다. The models to predict when and where a landslide occurs were constructed with different purposes and scopes, but tended to be complementary to each other. The objective of this study was to convert the static landslide hazard into the dynamic landslide hazard and combine a spatiotemporal hazard matrix to assess it, in order to enhance the usability of the early warning system for landslide and the landslide hazard map developed by the Korea Forest Service. We applied various matrix evaluation models to develop scenarios and assess the 2017 landslide occurred in Cheonan, Korea. The results of this study showed that a simple combination of matrices facilitated quantitative evaluation of the dynamic landslide hazard and its accuracy was higher than the static landslide hazard map. In addition, the dynamic landslide hazard can be assessed for the near future by integrating the 1-hour prediction data provided by the Korea Forest Service. The results of this study can help maximize the utilization of the existing national landslide forecast system and landslide hazard map, which should enhance the efficiency of managing landslide-prone zones during the rainy season.

산사태지역 토층사면의 지질조건별 토질특성

김경수 ( Kyeong Su Kim ) 대한지질공학회 2006 지질공학 Vol.16 No.4

이 연구는 산사태가 발생한 편마암류, 화강암류 및 제3기퇴적암류지역 자연사면의 토층을 대상으로 여러 토질시험을 실시하여 산사태에 영향을 미치는 토층사면의 토질특성을 고찰하였다. 이를 위하여 같은 시기에 집중호우로 인해 많은 산사태들이 발생되었던 지역으로 편마암류인 장흥지역, 화강암류인 상주지역 및 제3기퇴적암류인 포항지역의 산사태현장 및 그와 대비되는 곳의 토층으로부터 채취한 시료에 대해 물성 및 공학시험을 실시하였다. 산사태자료와 시험결과를 토대로 산사태지역의 토질특성을 파악하고 발생지역과 미발생지역간의 차별성을 분석하였다. 지질별로 다소의 차이는 있으나 산사태발생지역의 토층은 미발생지역에 비해 균등계수와 곡률계수가 더 크고 세립자의 함유비율이 더 높다. 액성한계는 거의 유사한 경향성을 보이나 소성한계는 다른 두 지질에 비해서 편마암이 상대적으로 더 크게 나타났으며, 산사태발생지역의 토층이 더 낮은 연경도를 갖는다. 함수비는 다른 두 지질에 비해서 제3기퇴적암류가 훨씬 큰데, 이는 모암의 광물조성과 토층의 구조 및 풍화양상 등 다양한 토질요소에 영향을 받는다. 3개 지질조건 모두에서 산사태발생지역의 토층이 미발생지역에 비해서 대체로 큰 간극율과 작은 밀도특성을 갖는데, 이는 산사태발생지역의 토층이 미발생지역에 비해 더 불량한 입도분포와 느슨한 지반상태에 있음을 보여주는 것으로, 간극율이 크고 밀도가 작은 토층에서 산사태가 더 쉽게 발생될 수 있음을 의미한다. 그리고 동일한 지질조건인 경우 투수성이 양호한 토층이 산사태에 더 취약한데, 투수성은 입도분포, 간극크기, 흙입자의 거칠기 및 구조 등의 토질특성과 풍화나 퇴적환경 등 지질성인에 영향을 받는다. 한편, 전단특성은 지질조건에 따라 다소의 차이는 있으나 특별하게 구분되지는 않는다. 그러나 모든 지질조건에서 산사태발생지역의 토층이 미발생지역에 비해 전단저항각이 더 작은 것으로 나타남으로써 동일한 지질조건인 경우 전단저항각이 큰 토층은 작은 토층에 비해 산사태에 더 안정한 지반으로 분류된다. In this study, the soil characteristics are analyzed using the result of various soil tests as an object of the soil layer of natural slopes in landslides areas composed with gneiss, granite, and the tertiary sedimentary rock. To investigate the soil characteristics according to landslide and non landslide areas, soils are sampled from Jangheung, Sangju and Pohang. The landslides at three areas are occurred due to heavy rainfall in same time. The geology of Jangheung area, Sangju area and Pohang area is gneiss, granite, and the tertiary sedimentary rock, respectively. On the basis of the landslide data and the result of soil test, the soil characteristics at the landslide area and the differentiation between landslide area and non landslide area are analyzed. However soil characteristics have a little differentiation to geological condition, the uniformity coefficient and the coefficient of gradation of soils at the landslide area is larger than those of soils at the non landslide area. Also, the proportion of fine particle of soils at the landslide area is higher. The plastic limit of soils sampled from the granite and the sedimentary rock regions is larger than that sampled from the gneiss region. However the liquid limit is irrelevant to the geological condition. Also, the consistency of soils at the landslide area is smaller. The natural moisture content of soils in the sedimentary rock regions is larger than that of the granite and gneiss. It is mainly influenced by mineral compo- sition, soil layer structure, weathering condition, and so on. The soils sampled from landslide area have higher porosity and lower density than those from non landslide area. It means that the soils of landslide area have poor particle size distribution and loose density. Therefore, the terrain slope with poor distribution and loose density is vulnerable to occur in landslides. Also, landslides are occurred in the terrain slope with high permeability. The permeability is mainly influenced by the soil characteristics such as particle size distribution, porosity, particle structure, and the geological origins such as weathering, sedimentary environment. Meanwhile, the shear strength of soils is little difference according to the geological condition. But, the internal friction angle of soils sampled from the landslide area is lower than that of soils from the non landslide area. Therefore, the terrain slope with low internal friction angle is more vulnerable to the landslide.