• Title/Summary/Keyword: 산사태 예측 모델

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Prediction of potential Landslide Sites Using GIS (지리정보시스템에 기반한 산지재해 예측)

  • Cha, Kyung Seob;Kim, Tae Hoon;Kim, Young Jin
    • Journal of Korean Society of societal Security
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    • v.1 no.4
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    • pp.57-64
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    • 2008
  • Korea has been suffered from serious damages of lives and properties, due to landslides that are triggered by heavy rains in every monsoon season. This study developed the physically based landslide prediction model which consists of 3 parts, such as slope stability analysis model, groundwater flow model and soil depth model. To evaluate its applicability to the prediction of landslides, the data of actual landslides were plotted on the areas predicted on the GIS map. The matching rate of this model to the actual data was 84.8%. The relation between hydrological and landform factors and potential landslide were analyzed.

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Porewater Pressure Predictions on Hillside Slopes for Assessing Landslide Risks(I) -Comparative Study of Groundwater Recharge- (산사태 위험도 추정을 위한 간극수압 예측에 관한 연구(I) -지하수 유입량의 비교 연구-)

  • Lee, In-Mo;Park, Gyeong-Ho;Im, Chung-Mo
    • Geotechnical Engineering
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    • v.8 no.1
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    • pp.81-102
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    • 1992
  • Landslides on hillside slopes with shallow soil cover over a sloping bedrock are frequently caused by increases in porewater pressures following of heavy rainfall and it is one of the most important factors of assessing the risk of landslide to predict the groundwater level fluctuations in hillslopes. This paper presents the comparative study of three unsaturated flow models developed by Sloan et al., Reddi, L.N., and Thomas, H.A., Jr., respectively, which are used to predict the increase of groundwater levels in hillside slopes. The parametric study for each of models is also presented. The Kinematic Storage Model(KSM) developed by Sloan et at. is utilized to predict the saturated groundwater flow. They are applied to the two sites in Korea so as to examine the possibility of use in the groundwater flow model. The results show that two unsaturated models developed by Sloan et al. and Reddi, L. N. are largely affected by the uncertain parameters like saturated permeability and saturated water content : the abed model has the potential of use in unsaturated flow model with the optimal estimates of model parameters utilizing available optimization techniques. And it is also found that the KSM must be modified to account for the time delay effect in the saturated zone. The results of this paper are able to be utilized in developing the predictive model of groan dwater level fluctuations in a hillslope.

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소규모 개발지역의 토사재해예측에 관한 연구

  • Park, Ki-Bum;Park, Eun-Yeong;Cha, Sang-Hwa;Kim, Sung-Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.512-515
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    • 2012
  • 최근의 재해 발생은 하천에 의한 범람, 제방의 붕괴 등에 의한 피해발생보다는 일정지역에 국한적으로 내수배제 불량, 토사유출, 산사태 등으로 인한 피해의 발생이 증가하고 있다. 특히나 도시지역과 신규개발지역을 중심으로 집중호우로 인한 토사유출 등으로 인한 배수로 막힘, 산사태등의 2차적인 피해가 증가하고 있는 추세이다. 2011년의 서울의 우면산 산사태 등과 같은 도시중심에서의 피해와 강원도 등의 신규개발지역에서의 토사로 인해 2차, 3차 피해는 국지적이고 예측이 불가능한 곳에서 발생되고 있다. 이러한 토사유출, 산사태에 의한 예측기법은 최근의 정보기술의 발달로 인해 보다 다양한 방법의 접근들이 시도되고 있으며, 이에 대한 정량적인 평가기법들이 개발되고 적용되고 있다. 본 연구에서는 산지지형의 소규모 개발지의 토사재해의 위험성을 평가하기 위하여 GIS 기술을 이용한 사면의 안정성과 산사태 위험성을 평가하는 대표적인 방법으로 Pack et al. (1998)이 제안한 수리적 무한사면 안정모델과 결합하여 사면안정분석을 위해 개발된 SINMAP을 이용하여 소규모 개발지역의 토석류 해석과 사면의 안정성 검토 그리고 범용토양공식을 이용하여 토사유출량을 산정하여 개발지역내 사면 및 토사재해의 위험성을 평가하였다. GIS를 이용한 지형적 특성에 따른 사면의 위험성과 토사유출량 해석 결과를 이용하여 소규모 개발지역의 토사재해의 위험성을 정량적이고 다각적으로 평가하여 재해발생에 따른 위험성을 노출하고 이에 대한 대책 수립에 도움이 될 것으로 판단된다.

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Application of GIS-based Probabilistic Empirical and Parametric Models for Landslide Susceptibility Analysis (산사태 취약성 분석을 위한 GIS 기반 확률론적 추정 모델과 모수적 모델의 적용)

  • Park, No-Wook;Chi, Kwang-Hoon;Chung, Chang-Jo F.;Kwon, Byung-Doo
    • Economic and Environmental Geology
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    • v.38 no.1
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    • pp.45-55
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    • 2005
  • Traditional GIS-based probabilistic spatial data integration models for landslide susceptibility analysis have failed to provide the theoretical backgrounds and effective methods for integration of different types of spatial data such as categorical and continuous data. This paper applies two spatial data integration models including non-parametric empirical estimation and parametric predictive discriminant analysis models that can directly use the original continuous data within a likelihood ratio framework. Similarity rates and a prediction rate curve are computed to quantitatively compare those two models. To illustrate the proposed models, two case studies from the Jangheung and Boeun areas were carried out and analyzed. As a result of the Jangheung case study, two models showed similar prediction capabilities. On the other hand, in the Boeun area, the parametric predictive discriminant analysis model showed the better prediction capability than that from the non-parametric empirical estimation model. In conclusion, the proposed models could effectively integrate the continuous data for landslide susceptibility analysis and more case studies should be carried out to support the results from the case studies, since each model has a distinctive feature in continuous data representation.

Analysis of the Effect of Soil Depth on Landslide Risk Assessment (산사태 조사를 통한 토층심도가 산사태 발생 위험성에 미치는 영향 분석)

  • Kim, Man-Il;Kim, Namgyun;Kwak, Jaehwan;Lee, Seung-Jae
    • The Journal of Engineering Geology
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    • v.32 no.3
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    • pp.327-338
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    • 2022
  • This study aims to empirically and statistically predict soil depths across areas affected by landslides. Using soil depth measurements from a landslide area in Korea, two sets of soil depths are calculated using a Z-model based on terrain elevation and a probabilistic statistical model. Both sets of calculation results are applied to derive landslide risk using the saturated infiltration depth ratio of the soil layer. This facilitates analysis of the infiltration of rainfall into soil layers for a rainfall event. In comparison with the probabilistic statistical model, the Z-model yields soil depths that are closer to measured values in the study area. Landslide risk assessment in the study area based on soil depth predictions from the two models shows that the percentage of first-grade landslide risk assessed using soil depths from the probabilistic statistical model is 2.5 times that calculated using soil depths from the Z-model. This shows that soil depths directly affect landslide risk assessment; therefore, the acquisition and application of local soil depth data are crucial to landslide risk analysis.

A Study on Development of the Monitoring System Model Based on USN for Landslide Detection (산사태 감지를 위한 USN 모니터링 시스템 모델 개발에 관한 연구)

  • Cheon, Dong-Jn;Kim, Jeong-Sub;Lee, Seung-Ho;Kwak, Dong-Kurl;Coi, Shin-Hyung;Lee, Bong-Sub;Jung, Do-Young
    • Proceedings of the KAIS Fall Conference
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    • 2012.05b
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    • pp.812-816
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    • 2012
  • 본 논문은 산사태 감지 및 붕괴예측을 위한 현장에 USN(Ubiquitous Sensor Network)을 적용한 실시간 모니터링 시스템 모델을 개발하였다. 이 시스템의 성능을 검증하기 위해 USN기반의 상시모니터링시스템모델을 제작하고 실험적 평가를 수행하였다. 성능평가는 지표변위 센서모듈 동작특성 실험적 평가, USN은 Data 수집 전송 효율성 실험적 평가, 개발한 상시감시모니터링 프로그램 동작성능 실험적 평가 등을 수행하였다. 성능평가 결과 지표변위 측정센서모듈은 변위각도에 일치성을 확인하고, USN은 지표변위 센서모듈로부터 측정된 Data를 상시모니터링시스템에 오류 없이 전송되는지를 확인하였으며, 개발한 상시모니터링 프로그램 동작기능은 실시간 모니터링 그래프, 임계동작 알고리즘, 위험성 통보 문자서비스(SMS)기능, 알람서비스기능, 현장 감시카메라 등 동작기능의 우수성을 실험으로 증명하였다. 따라서 본 연구에서 개발된 산사태 감지 예측을 위한 USN기반 실시간 모니터링 시스템 모델은 산사태위험성노출 지역에 원격 실시간 모니터링 시스템으로 널리 사용될 것으로 사료된다.

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Assessment of Landslide Susceptibility using a Coupled Infinite Slope Model and Hydrologic Model in Jinbu Area, Gangwon-Do (무한사면모델과 수리학적 모델의 결합을 통한 강원도 진부지역의 산사태 취약성 분석)

  • Lee, Jung Hyun;Park, Hyuck Jin
    • Economic and Environmental Geology
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    • v.45 no.6
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    • pp.697-707
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    • 2012
  • The quantitative landslide susceptibility assessment methods can be divided into statistical approaches and geomechanical approaches based on the consideration of the triggering factors and landslide models. The geomechanical approach is considered as one of the most effective approaches since this approach proposes physical slope model and considers geomorphological and geomechanical properties of slope materials. Therefore, the geomechanical approaches has been used widely in landslide susceptibility analysis using the infinite slope model as physical slope model. However, the previous studies assumed constant groundwater level for broad study area without the consideration of rainfall intensity and hydraulic properties of soil materials. Therefore, in this study, landslide susceptibility assessment was implemented using the coupled infinite slope model with hydrologic model. For the analysis, geomechanical and hydrualic properties of slope materials and rainfall intensity were measured from the soil samples which were obtained from field investigation. For the practical application, the proposed approach was applied to Jinbu area, Gangwon-Do which was experienced large amount of landslides in July 2006. In order to compare to the proposed approach, the previous approach was used to analyze the landslide susceptibility using randomly selected groundwater level. Comparison of the results shows that the accuracy of the proposed method was improved with the consideration of the hydrologic model.

GIS Landslide Hazard Mapping Using Root Strength Reinforcement Model (GIS 기반의 뿌리보강모델을 활용한 산사태 위험도 작성방법 연구)

  • Kim, Min-Gu;Yoon, Young-Jin;Chang, Hoon
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.1 s.31
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    • pp.45-53
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    • 2005
  • Korea is formed a mountainous district at 70% of country. Damages are occurred by landslide. It is increased annually by industrial development and extension of urban area. Serious damages occurred in Kangreng area of Gangwondo by typoon Rusa in August, 2002. Landslide hazard mapping needs to forecast and to manage landslide hazard area. GIS fits landslide hazard mapping, to reduce of time, manpower and costs, to investigate a board area, to do a spatial forecast model in study site. Variety of methods is for landslide hazard mapping. A study use root strength reinforcement model. This model use factors such as topography of slope, soil depth, soil properties, and vegetation of slope. Landslide hazard map is made by this model.

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The Prediction of Hazard Area Using Raster Model (Raster 모델을 이용한 재해위험지 예측기법)

  • Kang, In-Joon;Choi, Chul-Ung;Cheong, Chang-Sik
    • Journal of Korean Society for Geospatial Information Science
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    • v.2 no.2 s.4
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    • pp.43-53
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    • 1994
  • GSIS(geo-spatial information system), particularly when utilized in hazard management decision, is one of hazard analysis tool. Data of GSIS input from digitizing or scanning of map or aerial photos. This paper focuses upon the hazard prediction in GSIS and RS analysis to assess map, aerialphotos, satellite imagery and soil map. This study found computation of hazard area analysis. the results is formed as raster data model of quadtree. Authors knew more accurate results of overlay. This paper shows building up integrated data base as well as search of hazard area in aerial photographs.

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Porewater Pressure Predictions on Hillside Slopes for Assessing Landslide Risks (II) Development of Groundwater Flow Model (산사태 위험도 추정을 위한 간극수압 예측에 관한 연구(II) -산사면에서의 지하수위 예측 모델의 개발-)

  • Lee, In-Mo;Park, Gyeong-Ho;Im, Chung-Mo
    • Geotechnical Engineering
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    • v.8 no.2
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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.

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