• Journal of the Korean GEO-environmental Society
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• v.5 no.4
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• pp.47-56
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• 2004

This research analyzed about various landslide causes and resettled items, which are fit to environment of army facilities, of safe estimating table of Korea Institute of Construction technology through the spot inspection data. Analyzed relation with rainfall and slope failure occurrence for forecast slope failure appearance. Analyzed special quality of rainfall, topography, geological features that become occurrence factor of slope failure that happen in Kang-Won area come up with use of slope failure safety estimating table. Wish to examine closely phenomenon of slope failure and regional special quality that appear in military bases area and consider countermeasure.

• Journal of The Geomorphological Association of Korea
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• v.24 no.2
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• pp.91-101
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• 2017

Quantitative forecasting methods based on spatial data and geographic information system have been used in predicting the landslide location. This study compared the simulated results of logistic, Bayesian, and maximum entropy models to understand the uncertainties of each model and identify the main factors that influence landslide. The study area is Boeun gun where 388 landslides occurred in the year of 1998. The verification results showed that the AUC of the three models was 0.84. However, the landslide susceptibility distribution of Maxent model was different from those of the other two models. With the same landslide occurrence data, the result of high susceptible area in Maxent model is smaller than Logistic or Bayesian. Maxent model, however, proved to be more efficient in predicting landslide than the other two models. In Maxent's simulations, the responsible factors for landslide susceptibility are timber age class, land cover, timber diameter, crown closure, and soil drainage. The results suggest that it is necessary to consider the possibility of overestimation when using Logistic or Bayesian model, and forest management around the study area can be an effective way to minimize landslide possibility.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.192-192
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• 2021

산지 사면에서 발생한 토석류는 지형변화에 큰 영향을 미치는 대표적인 자연재해이다. 특히, 집중호우로 인해 발생하는 산사태의 경우 단시간에 많은 토사가 붕괴되며, 이는 매우 빠른 속도로 유동하는 토석류로 발전할 수 있다. 이러한 토석류가 도심지역에서 발생할 경우 많은 인명 및 재산피해를 야기하며, 이와 같은 피해를 저감하기 위해선 토석류의 유동과 피해규모를 예측할 수 있는 수치모형을 통한 연구가 필수적으로 이루어져야한다. 유동 및 퇴적지역의 피해규모를 크게 증가시킬 수 있는 침식-연행작용에 대한 연구는 최근에 활발히 이루어지고 있다. 수치모형으로 분석된 피해범위와 규모를 정밀하게 산정하기 위해선 침적과정에 대한 구현·해석이 필요하나 국내·외적으로 토석류 침적에 대한 연구는 미비한인 실정이다. 이에 본 연구는 침적을 고려하는 침식-연행작용 모형을 개발하여 토석류의 유동 및 퇴적과정을 자연현상에 가깝게 묘사하고자 하였다. 해당 모형은 2011년 우면산 일대에서 발생한 일련의 토석류를 대상으로 검증하고자하며, 연구지역의 지형 및 붕괴지점 자료는 토석류 발생 전·후 DEMs(Digital Elevation Models)을 이용하여 구축하였다. 현장에서 관측된 피해 범위, 총퇴적량, 특정 지점에서의 최대 피해 높이와 첨두속도 등은 실측자료로 활용하여 모형의 결과와 비교·분석하였으며 이를 통해 모형의 성능을 검증하고자 하였다.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1998.11a
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• pp.303-308
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• 1998

암반을 대상으로 하는 건설공사는 많은 시간과 비용, 설계, 시공, 안전상에 많은 문제점을 일으키고 있다. 이러한 암반들은 흡수, 풍화 등에 기인하여 안정성이 약화되어 낙석, 산사태, 붕괴 등의 위험을 안고 있으며 이러한 현상은 우기, 해빙기에 두드러지게 나타나고 있다 비균질, 비등방성의 역학적 성질을 지닌 암석은 변형 거동을 완벽하게 예측하지는 못하고 있는 실정으로 이러한 거동은 암석의 종류와 구성 광물, 내부 불연속면의 상태, 응력 조건과 온도, 습도의 함수비등과 같은 다양한 요소에 의해 영향을 받으며, 이러한 경향은 퇴적암의 경우 두드러지게 나타나고 있다. (중략)

• Water for future
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• v.54 no.9
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• pp.132-136
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• 2021

2021년 하계방학 동안 농어촌연구원 국제융합수리시험센터에서 현장실습을 하며 경험했던 것, 배운 점, 느낀 점을 후기로 작성하였다. 이번 현장실습동안 진행한 활동들은 크게 수리실험 교육 및 장비조작 실습, 세미나발표 참관, 문헌조사, 안전교육 4가지로 구분된다. 현장실습을 하면서 느낀 점은 수리실험은 다양한 분야에서 활용된다는 것이었다. 수리실험을 통해 산사태를 예측하여 방재계획을 수립하고, 어도를 구축하여 생태계 보호에 기여할 수 있으며, 파력발전을 통해 에너지를 생산할 수 있다는 것을 알게 되었다. 이 때 다양한 환경문제가 발생할 수도 있는 데 향후 환경 계통에 취업을 했을 시 본 현장실습을 통해 얻은 경험이 매우 유용하게 활용 될 수 있을 것이라 기대된다.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.943-953
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• 2021

The propagation of impact wave induced by landslide and debris flow occurred on the slope of lake, reservoir and bays is a three-dimensional natural phenomenon associated with strong interaction of debris flow and water flow in complex geometrical environments. We carried out 3D numerical modeling of such impact wave in a bay using a multiphase turbulence flow model and a rheology model for non-Newtonian debris flow. Numerical results are compared with previous experimental result to evaluate the performance of present numerical approach. The results underscore that the reasonable predictions of both thickness and speed of debris flow head penetrating below the water surface are crucial to accurately reproduce the maximum peak height and free surface profiles of impact wave. Two predictions computed using different initial debris flow thicknesses become different from the instant when the peaks of impact waves fall due to the gravity. Numerical modeling using relatively thick initial debris flow thickness appears to well reproduce the water surface profile of impact wave propagating across the bay as well as wave run-up on the opposite slope. The results show that the maximum run-up height on the opposite slope is not sensitive to the initial thickness of debris flows of same total volume. Meanwhile, appropriate rheology model for debris flow consisting of inviscid particle only should be employed to more accurately reproduce the debris flow propagating along the channel bottom.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.61-89
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• 2020

The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.

• Journal of the Korean Geosynthetics Society
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• v.22 no.2
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• pp.1-12
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• 2023

Research on the causes of landslides and prediction of vulnerable areas is being conducted globally. This study aims to predict the effective soil depth, a critical element in analyzing and forecasting landslide disasters, using topographic information. Topographic data from various institutions were collected and assigned as attribute information to a 100 m × 100 m grid, which was then reduced through data grading. The study predicted effective soil depth for two cases: three depths (shallow, normal, deep) and five depths (very shallow, shallow, normal, deep, very deep). Three classification models, including K-Nearest Neighbor, Random Forest, and Deep Artificial Neural Network, were used, and their performance was evaluated by calculating accuracy, precision, recall, and F1-score. Results showed that the performance was in the high 50% to early 70% range, with the accuracy of the three classification criteria being about 5% higher than the five criteria. Although the grading criteria and classification model's performance presented in this study are still insufficient, the application of the classification model is possible in predicting the effective soil depth. This study suggests the possibility of predicting more reliable values than the current effective soil depth, which assumes a large area uniformly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.515-525
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• 2014

Recently, because of increasing in downpour and typhoon, which are caused by climate changes, those sedimentation disasters, such as landslide and debris flow, have become frequent. Those sedimentation disasters take place in natural slope. In order to predict debris flow damage range within wide area, the response model is more appropriate than numerical analysis. However, to make a prediction using Random Walk Model, the regional parameters is needed to be decided, since the regional environments conditions are not always same. This random Walk Model is a probability model with easy calculation method, and simplified slope factor. The objective of this study is to calculate the optimal parameters of Random Walk Model for Umyeon mountain in Seoul, where the large debris flow has occurred in 2011. Debris flow initiation zones and sedimentation zones were extracted through field survey, aerial photograph and visual reading of debris flow before and after its occurrence via LiDAR DEM.

• Geotechnical Engineering
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• v.10 no.1
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• pp.47-62
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• 1994

It has been well known that the rainfall-triggered rise of groundwater levels is one of the most important factors resulting the instability of the hillside slopes. Thus, the prediction of porewater pressure is an essential step in the evaluation of landslide hazard. This study involves the development and verification of numerical groundwater flow model for the prediction of groundwater flow fluctuations accounting for both of unsatu나toed flow and saturated flow on steep hillside slopes. The first part of this study is to develop a nomerical groundwater flow model. The numerical technique chosen for this study is the finitro element method in combination with the finite difference method. The finite element method is used to transform the space derivatives and the finite difference method is used to discretize the time domain. The second part of this study is to estimate the unknown model parameters used in the proposed numerical model. There were three parameters to be estimated from input -output record $K_e$, $\psi_e$, b. The Maximum -A-Posteriori(MAP) optimization method is utilized for this purpose, . The developed model is applied to a site in Korea where two debris avalanches of large scale and many landslides of small scale were occurred. The results of example analysis show that the numerical groundwater flow model has a capacity of predicting the fluctuation of groundwater levels due to rainfall reasonably well.