• Geotechnical Engineering
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• 제8권2호
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• pp.5-20
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• 1992

The physical-based and lumped-parameter hydrologic groundwater flow model for predicting the rainfall-triggered rise of groundwater levels in hillside slopes is developed in this paper to assess the risk of landslides. The developed model consists of a vertical infiltration model for unsaturated zone linked to a linear storage reservoir model(LSRM) for saturated zone. The groundwater flow model has uncertain constants like soil depttL slope angle, saturated permeability, and potential evapotranspiration and four free model parameters like a, b, c, and K. The free model parameters could be estimated from known input-output records. The BARD algorithm is uses as the parameter estimation technique which is based on a linearization of the proposed model by Gauss -Newton method and Taylor series expansion. The application to examine the capacity of prediction shows that the developed model has a potential of use in forecast systems of predicting landslides and that the optimal estimate of potential 'a' in infiltration model is the most important in the global optimum analysis because small variation of it results in the large change of the objective function, the sum of squares of deviations of the observed and computed groundwater levels. 본 논문에서는 가파른 산사면에서 산사태의 발생을 예측하기 위한 수문학적 인 지하수 흐름 모델을 개발하였다. 이 모델은 물리적인 개념에 기본하였으며, Lumped-parameter를 이용하였다. 개발된 지하수 흐름 모델은 두 모델을 조합하여 구성되어 있으며, 비포화대 흐름을 위해서는 수정된 abcd 모델을, 포화대 흐름에 대해서는 시간 지체 효과를 고려할 수 있는 선형 저수지 모델을 이용하였다. 지하수 흐름 모델은 토층의 두께, 산사면의 경사각, 포화투수계수, 잠재 증발산 량과 같은 불확실한 상수들과 a, b, c, 그리고 K와 같은 자유모델변수들을 가진다. 자유모델변수들은 유입-유출 자료들로부터 평가할 수 있으며, 이를 위해서 본 논문에서는 Gauss-Newton 방법을 이용한 Bard 알고리즘을 사용하였다. 서울 구로구 시흥동 산사태 발생 지역의 산사면에 대하여 개발된 모델을 적용하여 예제 해석을 수행함으로써, 지하수 흐름 모델이 산사태 발생 예측을 위하여 이용할 수 있음을 입증하였다. 또한, 매개변수분석 연구를 통하여, 변수 a값은 작은 변화에 대하여 목적함수값에 큰 변화를 일으키므로 a의 값에 대한 최적값을 구하는 것이 가장 중요한 요소라는 결론을 얻었다.

• Journal of Environmental Policy
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• 제12권3호
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.

• Journal of the Korean Geotechnical Society
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• 제29권7호
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• pp.75-89
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• 2013

This paper describes a GIS-based geohydrologic methodology, called YSGWF (YonSei GroundWater Flow) for predicting the rainfall infiltration-groundwater flow of slopes. This physical-based model was developed by the combination of modified Green-Ampt model that considers the unsaturated soil parameters and GIS-based raster model using Darcy's law that reflects the groundwater flow. In the model, raster data are used to simulate the three dimensional inclination of bedrock surface as actual topographic data, and the groundwater flow is governed by the slope. Also, soil profile is ideally subdivided into three zones, i.e., the wetting band zone, partially saturated zone, and fully saturated zone. In the wetting band and partially saturated zones the vertical infiltration of water (rainfall) from surface into ground is modeled. When the infiltrated water recharges into the fully saturated zone, the horizontal flow of groundwater is introduced. A comparison between the numerical calculation and real landslide data shows a reasonable agreement, which indicate that the model can be used to simulate real rainfall infiltration-groundwater flow.

• Journal of Korean Society for Geospatial Information Science
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• 제16권4호
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• pp.33-39
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• 2008

Typhoon Lusa in 2002 and Typhoon Maemi in 2003 caused the worst damage of landslide and debris flow to Gangwon-do. This damage includes severe damage in riverside road. The damage register indicates that this damage is concentrated on mountain areas in Gangwon-do. In recent years, the studies on GIS application to predicting landslide and debris flow have been progressing actively. Landslide risk map managed by The Forest Service is the representative one. In this study, we generated landslide and debris flow hazard maps using statistical analysis and deterministic analysis in Gangnung area where Typhoons caused severe damage to riverside roads. We built damage point GIS DB from damage registers of National Road Maintenance Agency and field survey, and verified accuracy of landslide and debris flow hazard maps using GIS methods.

• Economic and Environmental Geology
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• 제47권1호
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• pp.49-59
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• 2014

Rainfall-induced landslides are caused by reduction of effective stress and shear strength due to rainfall infiltration. In order to analyze the susceptibility of landslides, the statistical analysis approach has been used widely but this approach has the limitation which cannot take into account of landslide triggering mechanism. Therefore, the physically based model which can consider the process of landslide occurrence was proposed and commonly used. However, the most previous physically based model analyses evaluate and consider the strength characteristics for saturated soil only in the susceptibility analysis. But the strength parameters for unsaturated soil such as matric suction should be considered with the strength parameters for saturated soil since the shear strength in unsaturated soil also plays important role in the stability of slope. Consequently this study suggested the modified physically based slope model which can evaluate strength characteristics for both of saturated and unsaturated soils. In addition, this study evaluated the thickness of saturated part in slope with rainfall intensity and hydraulic characteristics of slope on the basis of physically based model. In order to evaluate the feasibility, the proposed model was applied to practical example in Jinbu area, Gangwon-do, which was experienced large amount of landslides in July 2006. The ROC graph analysis was used to evaluate the validation of the model, and the analysis results were compared with the results of the previous analysis approach.

• Journal of Climate Change Research
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• 제3권1호
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• pp.39-50
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• 2012

KMA(Korea Meteorological Administration) projected that annual mean temperatures of South Korea will rise $3.8^{\circ}C$ and the annual total precipitation will increase by 17 percent by 2100. Rainfall is concentrated during the summer in South Korea. Thus the risk of landslide by heavy rain is expected to increase. After the landslide of Mt. Umyeon occurred in July 2011, disaster of forest sector is highlighted. Therefore vulnerability assessment of landslide is urgent. However, vulnerability assessment based on local governments was not done yet. In this study, we assess vulnerability of landslide by heavy rain for local governments. We used several scenarios to consider uncertainty of climate change. Through this study, local governments can use the results to establish adaptation plans. Also, the results could be used to decrease vulnerability of landslide.

• Journal of the Society of Disaster Information
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• 제16권3호
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• pp.440-448
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• 2020

Purpose: Most of the studies in the country on earthquake-induced landslide predict the displacement of the slope. Until now, no studies have been conducted on the occurrence of landslides and damage characteristics by earthquakes. Therefore, this study was conducted to obtain basic data of landslides caused by earthquakes. Method: In order to analyze the characteristics of earthquake-causing landslides, we have collected data reported in the media over the past decade. Landslides in foreign countries were analyzed separately by cause of occurrences such as rainfall and earthquake. Landslides from abroad were analyzed according to the cause of the occurrence, and landslides caused by earthquakes were further analyzed as follows: the magnitude of an earthquake, year of occurrence, number of occurrences by continent, damage status, etc. Result: In the past 10 years, a total of 608 landslides have been reported from overseas, and the cause is the highest with 340 landslides due to rainfall. There were 70 cases of landslides caused by earthquakes, and it was analyzed as the second cause of landslides. The average magnitude for earthquakes that caused landslides was 6.5, and the minimum and maximum magnitude were 4.4 and 8.2 respectively. The earthquake-induced landslides were the most occurrence in 2011yr and 2012yr, and the continent was the most common in Asia. Also, It was analyzed that if an earthquake caused landslides, the number of casualties increased and the size of the damage increased. Conclusion: Currently, earthquakes are steadily increasing in Korea, and the possibility of strong earthquakes is also increasing. Earthquake-induced landslides are beyond human control due to natural disasters but can minimize damage through active prevention and response. It is expected that the results of this study will be used as basic data in establishing measures for earthquake landslides to reduce property and human damage in the future.

• Journal of the Society of Disaster Information
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• 제17권4호
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• pp.694-709
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• 2021

Purpose: In this study, earthquake-induced landslide risk assessment was conducted to provide basic data for efficient and preemptive damage prevention by selecting the erosion control work before the earthquake and the prediction and restoration priorities of the damaged area after the earthquake. Method: The study analyzed the previous studies abroad to examine the evaluation methodology and to derive the evaluation factors, and examine the utilization of the landslide hazard map currently used in Korea. In addition, the earthquake-induced landslide hazard map was also established on a pilot basis based on the fault zone and epicenter of Pohang using seismic attenuation. Result: The earthquake-induced landslide risk assessment study showed that China ranked 44%, Italy 16%, the U.S. 15%, Japan 10%, and Taiwan 8%. As for the evaluation method, the statistical model was the most common at 59%, and the physical model was found at 23%. The factors frequently used in the statistical model were altitude, distance from the fault, gradient, slope aspect, country rock, and topographic curvature. Since Korea's landslide hazard map reflects topography, geology, and forest floor conditions, it has been shown that it is reasonable to evaluate the risk of earthquake-induced landslides using it. As a result of evaluating the risk of landslides based on the fault zone and epicenter in the Pohang area, the risk grade was changed to reflect the impact of the earthquake. Conclusion: It is effective to use the landslide hazard map to evaluate the risk of earthquake-induced landslides at the regional scale. The risk map based on the fault zone is effective when used in the selection of a target site for preventive erosion control work to prevent damage from earthquake-induced landslides. In addition, the risk map based on the epicenter can be used for efficient follow-up management in order to prioritize damage prevention measures, such as to investigate the current status of landslide damage after an earthquake, or to restore the damaged area.

• Journal of Korea Society of Industrial Information Systems
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• 제14권5호
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• pp.281-288
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• 2009

The purpose of this paper is to provide the statistical models for landslide prediction through quantification and AHP methods. Quantification method is a statistical method of providing quantity to qualitative variables by analyzing the observed data. In this paper, we suggest the quantification process based on the results of cannonical correlation analysis. In contrast with the quantification method which is based on given data the AHP(Analytic Hierarchy Process) technique is a kind of method based on questionaire data which is usually taken from professionals. We analyze both the real data(provided from KIGAM) and questionaire data collected from professionals of various related area. We developed two kinds of evaluation table which provide the scores of land slide possibility and the logistic model providing the probability of occurring landslide. Finally we compare the performance and evaluate the stability of the suggested two models.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제30권3호
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• pp.313-321
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• 2012

Korea has been continuously affected by landslides, as 70% of the land is covered by mountains and most of annual rainfall concentrates between June and September. Recently, abrupt climate change affects the increase of landslide occurrence. Gangwon region is especially suffered by landslide damages, because the most of the part is mountainous, steep, and having shallow soil. In this study, a landslide risk assessment model was developed by applying logistic regression to the various data of Duksan-ri, Inje-eup, Inje-gun, Gangwon-do, which has suffered massive landslide triggered by heavy rain in July 2006. The information collected from field investigation and aerial photos right after the landslide of study area were stored in GIS DB for analysis. Slope gradient entered in two ways-as categorical variable and as linear variable. Error matrix for each case was made, and developed model showed the classification accuracy of 81.4% and 81.9%, respectively.