空间三维滑坡敏感性分区工具及其应用

对于滑坡敏感性分区目前有三种方法:定性法、统计法和基于岩土定量模型的确定性方法。定性法基于对滑坡敏感性或灾害评估的人为判断;统计法用一个来源于结合了权重因子的预测函数或指标;而确定性法,或者说是物理定量模型法以质量、能量和动量守恒定律为基础。二维确定性模型广泛用于土木工程设计,而无限边坡模型(一维)也用于滑坡灾害分区的确定性模型。文中提出了一个新的基于GIS(地理信息系统)的滑坡敏感性分区系统,这个系统可用于从复杂地形中确认可能的危险三维(3-D)滑坡体。所有与滑坡相关的空间数据(矢量或栅格数据)都被集成到这个系统中。通过把研究区域划分为边坡单元并假定初始滑动面是椭球的下半部分,并使用Monte Carlo随机搜索法,三维滑坡稳定性分析中的三维最危险滑面是三维安全系数最小的地方。使用近似方法假定有效凝聚力、有效摩擦角和三维安全系数服从正态分布,可以计算出滑坡失稳概率。3DSlopeGIS是一个计算机程序,它内嵌了GIS Developer kit(ArcObjects of ESRI)来实现GIS空间分析功能和有效的数据管理。应用此工具可以解决所有的三维边坡空间数据解问题。通过使用空间分析、数据管理和GIS的可视化功能来处理复杂的边坡数据,三维边坡稳定性问题很容易用一个友好的可视化图形界面来解决。将3DSlopeGIS系统应用到3个滑坡敏感性分区的实例中:第一个是一个城市规划项目,第二个是预测以往滑坡灾害对临近区域可能的影响,第三个则是沿着国家主干道的滑坡分区。基于足够次数的Monte Carlo模拟法,可以确认可能的最危险滑坡体。这在以往的传统边坡稳定性分析中是不可能的。     

A Reliability Based Expert System for Assessment and Mitigation of Landslides Hazard Under Seismic Loading

Different models were developed for evaluating the probabilistic three-dimensional (3-D) stability analysis of earth slopes and embankments under earthquake loading using both the safety factor and the displacement criteria of slope failure.The probabilistic models evaluate the probability of failure under seismic loading considering the different sources of uncertainties involved in the problem. The models also take into consideration the spatial variabilities and correlations of soil properties. The developed models are incorporated in a computer program PTDDSSA.These analysis/design procedures are incorporated within a code named SARETL developed in this study for stability analysis and remediation of earthquake triggered landslides. In addition to the dynamic inertia forces, the system takes into consideration local site effects.The code is capable of assessing the landslide hazard affecting major transportation routes in the event of earthquakes and preparing earthquake induced landslide hazard maps (i.e., maps showing expected displacements and probability of slope/embankments failure) for different earthquake magnitudes and environmental conditions. It can also beused for proposing a mitigation strategy against landslides.     

A time-space based approach for mapping rainfall-induced shallow landslide hazard

A rainfall-induced shallow landslide is a major hazard in mountainous terrain, but a time-space based approach is still an unsettled issue for mapping rainfall-induced shallow landslide hazards. Rain induces a rise of the groundwater level and an increase in pore water pressure that results in slope failures. In this study, an integrated infinite slope analysis model has been developed to evaluate the influence of infiltration on surficial stability of slopes by the limit equilibrium method. Based on this new integrated infinite slope analysis model, a time-space based approach has been implemented to map the distributed landslide hazard in a GIS (Geographic Information Systems) and to evaluate the shallow slope failure induced by a particular rainfall event that accounts for the rainfall intensity and duration. The case study results in a comprehensive time-space landslide hazard map that illustrates the change of the safety factor and the depth of the wetting front over time.     

Seismic reliability analysis of earth slopes under short term stability conditions

Different models were developed for evaluating the probabilistic three-dimensional (3-D) stability analysis of earth slopes and embankments under earthquake loading. The 3-D slope stability model assumed is that of a simple cylindrical failure surface. The probabilistic models evaluate the probability of failure under seismic loading considering the randomness of earthquake occurrence, and earthquake induced acceleration and uncertainties stemming from the discrepancies between laboratory-measured and in-situ values of shear strength parameters. The models also takes into consideration the spatial variabilities and correlations of soil properties. The probabilistic analysis and design approach is capable of obtaining the 2-D and 3-D static and dynamic safety factors, the probability of slope failure, the earthquake induced acceleration coefficient, the yield acceleration coefficient, the earthquake induced displacement, and the probability of allowable displacement exceedance taking into account the local site effect. The approach is applied to a well known landslide case: Congress Street Landslide in Chicago. A sensitivity analysis was conducted on the different parameters involved in the models by applying those models to the Congress Street landslide considering different levels of seismic hazard. Also, a sensitivity analysis was carried out to study the sensitivity of computed results to input parameters of undrained shear strength, and corrective factors. A comparison was made between the different models of failure. The parametric study revealed that the hypocentral distance and earthquake magnitude have major influence on the earthquake induced displacement, probability of failure and dynamic 2-D and 3-D safety factors.     

公路沿线花岗岩风化区滑坡危险度评价--以日本49号国道合户地区为例

对公路沿线边坡进行稳定性评价及滑坡灾害分析，对于由滑坡、泥石流等引起的公路灾害的防治具有重要指导意义。为了评价处于花岗岩风化区的日本福岛县合户地区49号国道沿线边坡的滑坡危险程度，在调查和分析了该地区的表层破坏模式、并通过简易探测方法摸清了风化土层的厚度分布后，将研究区域划分为边坡单元(Slopeunit)，使用椭球体下半部模拟滑动面的形状，通过随机试算法确定各边坡单元危险滑动面的位置及空间形状；采用一种基于GIS的边坡稳定性三维分析模型计算各边坡单元最小安全系数以及滑坡发生概率，定量评价滑坡灾害危险程度。所有的计算过程及结果显示均在一个基于GIS平台的系统中完成，为如何利用GIS技术更好地为滑坡灾害防治工作服务拓宽了思路。     

SARETL: an expert system for probabilistic displacement-based dynamic 3-D slope stability analysis and remediation of earthquake triggered landslides

 Different models were developed for evaluating the probabilistic three-dimensional (3-D) stability analysis of earth slopes and embankments under earthquake loading using both the safety factor and the displacement criteria of slope failure. In the 3-D analysis, the critical and total slope widths become two new and important parameters. The probabilistic models evaluate the probability of failure under seismic loading and consider the different sources of uncertainties involved in the problem, i.e. uncertainties stemming from the discrepancies between laboratory-measured and in situ values of shear strength parameters, randomness of earthquake occurrence, and earthquake-induced acceleration. The models also take into consideration the spatial variabilities and correlations of soil properties. The developed models are incorporated in a computer program, PTDDSSA (probabilistic three-dimensional dynamic slope stability analysis). These developed analysis/design procedures are incorporated within a code named SARETL (stability analysis and remediation of earthquake-triggered landslides) that was developed in this study for stability analysis and remediation of earthquake-triggered landslides. In addition to the dynamic inertia forces; the developed system takes into consideration the local site effects. The code is capable of: 1. Prediction of permanent deformations that result from landslides under seismic loading using both probabilistic and deterministic approaches. 2. The assessment of landslide hazard that affects major transportation routes in the event of earthquakes, and the preparation of earthquake-induced landslide hazard maps (i.e. maps that show expected displacements and probability of slope/embankments failure) for different earthquakes magnitudes and environmental conditions. 3. Proposing a mitigation strategy against landslides and suggesting guidelines for remedial measures. The developed expert system is applied to a major highway case study. Design maps are developed for the highway under seismic loading. Received: 18 March 1999 · Accepted: 11 October 1999     

基于边坡单元的公路沿线滑坡危险度概率分析

公路沿线发生的滑坡、泥石流等自然灾害是造成交通停滞的主要原因。对公路沿线边坡进行稳定性评价及滑坡灾害分析对于公路管理和灾害防治具有重要意义。为了能对大范围边坡应用三维力学模型进行稳定性评价,研究中将较大研究区域划分为多个边坡单元（slope unit）,并介绍了边坡单元划分方法。对每个边坡单元,采用随机生成许多假想滑动面并通过一个基于GIS的边坡稳定性三维分析模型计算其安全系数的方法,找出具有最小安全系数的危险滑动面,同时求出在试算过程中安全系数小于某临界值（通常设为1.0）的结果出现的比率,作为该边坡单元的滑坡发生概率,以此作为指标对研究区域进行危险度评价。通过对日本49号国道沿线边坡中的应用对该方法的实用性进行了验证。     

Landslide susceptibility zonation mapping and its validation in part of Garhwal Lesser Himalaya, India, using binary logistic regression analysis and receiver operating characteristic curve method

A landslide susceptibility zonation (LSZ) map helps to understand the spatial distribution of slope failure probability in an area and hence it is useful for effective landslide hazard mitigation measures. Such maps can be generated using qualitative or quantitative approaches. The present study is an attempt to utilise a multivariate statistical method called binary logistic regression (BLR) analysis for LSZ mapping in part of the Garhwal Lesser Himalaya, India, lying close to the Main Boundary Thrust (MBT). This method gives the freedom to use categorical and continuous predictor variables together in a regression analysis. Geographic Information System has been used for preparing the database on causal factors of slope instability and landslide locations as well as for carrying out the spatial modelling of landslide susceptibility. A forward stepwise logistic regression analysis using maximum likelihood estimation method has been used in the regression. The constant and the coefficients of the predictor variables retained by the regression model have been used to calculate the probability of slope failure for the entire study area. The predictive logistic regression model has been validated by receiver operating characteristic curve analysis, which has given 91.7% accuracy for the developed BLR model.     

考虑优势流作用的降雨入渗边坡可靠度分析

降雨诱发滑坡是世界上最普遍的地质灾害,而关于降雨入渗对边坡的可靠度分析,优势入渗的影响被长期忽视。使用Comsol Multiphysics对降雨条件下优势入渗做数值求解,利用无限边坡模型计算边坡安全系数;并应用改进Cholesky分解法生成空间相关随机场,使用蒙特卡洛方法分析降雨过程中边坡的可靠度。结合确定性与可靠度计算对比均质入渗与优势入渗在降雨过程中边坡安全性变化：（1）降雨强度较低时,优势入渗安全性较好,而降雨强度较高时,均质入渗更稳定;（2）均质入渗中参数空间变异性是边坡失稳破坏的关键因素,而优势入渗的边坡失稳则由湿润峰快速推进所导致;（3）针对优势入渗模型研究,发现基质域与优势域水力交换强度较大时边坡有更大概率失稳,而较小的水力交换强度可能影响边坡底部的失稳破坏。     

Physically-based landslide susceptibility analysis using Monte Carlo simulation in a tropical mountain basin

ABSTRACT

Physically-based distributed models are implemented for landslide susceptibility and hazard assessment around the world. Probabilistic methodologies are considered appropriate to study and quantify the uncertainties derived from the input parameters of these models. In this paper, three sets of Monte Carlo simulations, each one with 10,000 iterations, were applied for a slope stability analysis in a small basin of Envigado (Colombia), using the TRIGRS model, to characterise the uncertainty in the landslide assessment. Different parameters to determine the minimum number of realizations required to ensure a small variation in the failure probability were proposed and analyzed. The quality of the landslide susceptibility assessment was studied. Unexpected and probably erroneous results that may be common in the maps generated using this and other similar methodologies were identified and explained. Additionally, the distribution of the factor of safety was calculated for different grid cells of the basin, showing that the probability density function with the best adjustment to the frequency histogram of the factor of safety can vary between grid cells. The assumption of a normal distribution for the factor of safety would be inappropriate and would lead to miscalculations in this case study.     

降雨型滑坡时间概率的逻辑回归拟合及连续概率滑坡危险性建模

提高降雨型滑坡危险性预警精度和空间辨识度具有重要意义.以江西宁都县1980—2001年156个降雨型滑坡为例,首先基于传统的EE-D（early effective rainfall-rainfall duration）阈值法计算不同降雨诱发滑坡的时间概率级别;然后以各级别临界降雨阈值曲线对应的时间概率为因变量,并以对应的前期有效降雨量（early effective rainfall,EE）和降雨历时（D）为自变量,采用逻辑回归拟合出上述因变量与自变量之间的非线性关系,得到降雨诱发滑坡的连续概率值;之后对比C5.0决策树和多层感知器的滑坡易发性预测性能;最后利用降雨诱发滑坡的连续概率值与易发性图相耦合以实现连续概率滑坡危险性预警.结果显示:（1）宁都降雨型滑坡连续概率值的逻辑回归方程为1/P=1+e4.062+0.747 4×D-0.079 44×EE,其拟合优度为0.983;（2）2002—2003年的20处用于连续概率阈值测试的降雨型滑坡大都落在连续概率值大于0.7的区域,只有4处落在小于0.7的区域;（3）C5.0决策树预测滑坡易发性的精度显著高于多层感知器;（4）近5年的4次降雨型滑坡的连续概率危险性值都在0.8以上,且高和极高预警区的面积较传统滑坡危险性分区更小.可见连续概率滑坡危险性预警法相较于传统危险性分区法具有更高的预警精度和空间辨识度,且通过叠加滑坡易发性图及其临界降雨阈值可开展实时滑坡危险性预警制图.      

Mapping susceptibility of rainfall-triggered shallow landslides using a probabilistic approach

To prepare a landslide susceptibility map is essential to identify hazardous regions, construct appropriate mitigation facilities, and plan emergency measures for a region prone to landslides triggered by rainfall. The conventional mapping methods require much information about past landslides records and contributing terrace and rainfall. They also rely heavily on the quantity and quality of accessible information and subjectively of the map builder. This paper contributes to a systematic and quantitative assessment of mapping landslide hazards over a region. Geographical Information System is implemented to retrieve relevant parameters from data layers, including the spatial distribution of transient fluid pressures, which is estimated using the TRIGRS program. The factor of safety of each pixel in the study region is calculated analytically. Monte Carlo simulation of random variables is conducted to process the estimation of fluid pressure and factor of safety for multiple times. The failure probability of each pixel is thus estimated. These procedures of mapping landslide potential are demonstrated in a case history. The analysis results reveal a positive correlation between landslide probability and accumulated rainfall. This approach gives simulation results compared to field records. The location and size of actual landslide are well predicted. An explanation for some of the inconsistencies is also provided to emphasize the importance of site information on the accuracy of mapping results.     

A method for producing digital probabilistic seismic landslide hazard maps

The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include: (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24 000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10 m grid spacing using ARC/INFO GIS software on a UNIX computer. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure.     

Deterministic Landslide Risk Assessment at a Past Landslide Site

The slope failure and landslide hazard will possess the same properties within a range including the same engineering geological conditions. To assess the landslide risk of a mountainous area, the study of landslides previously having occurred is very important to evaluate the landslide risk around the area in which they took place. Based on the study of the mechanism of a previous landslide recorded in Kumamoto, Japan, this study initially proposes mechanical parameters for evaluating the landslide hazard using a 3D slope stability method. For each slope unit in the study area, the critical slip surface, which reveals the minimum safety factor of a slope, can be obtained. The affected streams and range of possible landslide masses are analyzed based on the debris flow simulation. This is initially applied to simulate the past landslide event and the result shows the landslide-deduced debris flow effectively re-displayed. Overlayered with layers of infrastructure in Geographic Information Systems (GIS), this risk map indicates which houses and road sections remain in dangerous areas.     

基于三维GIS的滑坡灾害监测预警系统及应用

为了减少或消除地质灾害的影响,基于地质勘察与监测资料,利用先进的计算机技术和三维可视化技术建立地质灾害监测预警系统显得十分的必要。在研究利用TIN方法建立地质体模型的基础上,将自动获取的监测数据通过北斗卫星的传输和三维地质体模型有机结合,进一步利用基于时间序列的方法,对监测数据进行预测分析,形成了一套完整的三维滑坡灾害预警系统,并提供剖面分析等实用GIS分析工具,从而提高滑坡灾害预警的快速性和直观性。基于四川雅安滑坡的工程实例,验证了系统的有效性。     

三峡库区巴东复杂斜坡系统变形机理数值模拟与稳定性研究

三峡库区巴东斜坡系统复杂,其变形机理与稳定性研究对移民迁建和地质灾害防治具有重要意义。本文采用FLAC3D数值计算方法,对巴东复杂斜坡系统变形机理进行研究,为“重力成因论”提供了支持和佐证。从整个斜坡系统的角度,联合使用数值计算方法(FLAC3D)和极限平衡法(Sarma法),系统研究了巴东复杂斜坡系统在不同蓄水状态下不同层次的稳定性问题,结果表明斜坡系统不存在整体深层滑动的可能性;斜坡系统沿岩层界面或软弱层发生失稳的可能性较小,但赵树岭滑体和黄土坡滑体在表层滑体发生较大变形或失稳的条件下,可能导致滑坡整体复活;在水库调蓄过程中,部分滑坡表层堆积体产生变形破坏的可能性较大。另外,斜坡的表层改造可能会引起斜坡中层稳定性的恶化。     

Probabilistic landslide hazard assessment using homogeneous susceptible units (HSU) along a national highway corridor in the northern Himalayas, India

The increased socio-economic significance of landslides has resulted in the application of statistical methods to assess their hazard, particularly at medium scales. These models evaluate where, when and what size landslides are expected. The method presented in this study evaluates the landslide hazard on the basis of homogenous susceptible units (HSU). HSU are derived from a landslide susceptibility map that is a combination of landslide occurrences and geo-environmental factors, using an automated segmentation procedure. To divide the landslide susceptibility map into HSU, we apply a region-growing segmentation algorithm that results in segments with statistically independent spatial probability values. Independence is tested using Moran’s I and a weighted variance method. For each HSU, we obtain the landslide frequency from the multi-temporal data. Temporal and size probabilities are calculated using a Poisson model and an inverse-gamma model, respectively. The methodology is tested in a landslide-prone national highway corridor in the northern Himalayas, India. Our study demonstrates that HSU can replace the commonly used terrain mapping units for combining three probabilities for landslide hazard assessment. A quantitative estimate of landslide hazard is obtained as a joint probability of landslide size, of landslide temporal occurrence for each HSU for different time periods and for different sizes.     

Modeling uncertainty in stability analysis for design of embankment dams on difficult foundations

A probabilistic 3-D slope stability analysis model (PTDSSAM) is developed to evaluate the stability of embankment dams and their foundations under conditions of staged construction taking into consideration uncertainty, spatial variabilities and correlations of shear strength parameters, as well as the uncertainties in pore water pressure. The model has the following capabilities: (1) conducting undrained shear strength analysis (USA) and effective stress analysis (ESA) slope stability analysis of staged construction, (2) incorporation of field monitored data of pore water pressure, and (3) incorporation of increase of undrained shear strength with depth, effective stress, and pore water pressure dissipation. The PTDSSAM model is incorporated in a computer program that can analyze slopes located in multilayered deposits, considering the total slope width.

The main outputs of the program are the geometric parameters of the most critical sliding surface (i.e., center of rotation/radius of rotation and critical width of failure), mean 2-D safety factor, mean 3-D safety factor, squared coefficient of variation of resisting moment, and the probability of slope failure. The program is applied to a case study, Karameh dam in Jordan. Monitored data of induced pore water pressure in the dam embankment and soft foundation were gathered during dam construction.

The stability of Karameh dam embankment and foundation was evaluated during staged construction using deterministic and probabilistic analysis. Foundation stability was evaluated based on the monitored data of pore water pressure.

The study showed that the mean values of the corrective factors which account for the discrepancies between the in situ and laboratory-measured values of soil properties and for the modeling errors have significant influence on the 2-D safety factor, 3-D safety factor, slope probability of failure, and on the expected failure width.

The degree of spatial correlation associated with shear strength parameters within a soil deposit also influences the probability of slope failure and the expected failure width. This correlation is quantified by scale of fluctuation. It is found that a larger scale of fluctuation gives an increase in the probability of slope failure and a reduction in the critical failure width.     

Landslide hazard mapping along national highway-154A in Himachal Pradesh,India using information value and frequency ratio

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “slope, aspect, relative relief, soil, curvature, Land Use and Land Cover (LULC), lithology, drainage density, and lineament density” were selected for landslide hazard mapping based on landslide inventory. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard.” The results from these two methods have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.     

A probabilistic model for rainfall—induced shallow landslide prediction at the regional scale

This paper presents a new probabilistic physically-based computational model (called PG_TRIGRS) for the probabilistic analysis of rainfall-induced landslide hazard at a regional scale. The model is based on the deterministic approach implemented in the original TRIGRS code, developed by Baum et al. (USGS Open File Report 02–424, 2002) and Baum et al. (USGS Open File Report 08–1159, 2008). Its key innovative features are: (a) the application of Ordinary Kriging for the estimation of the spatial distributions of the first two statistical moments of the probability density functions of the relevant soil properties over the entire area, based on limited available information gathered from available information from limited site investigation campaigns, and (b) the use of Rosenblueth’s Point Estimate method as a more efficient alternative to the classical Monte Carlo method for the reliability analysis performed at the single-cell level to obtain the probability of failure associated to a given rainfall event. The application of the PG_TRIGRS code to a selected study area located in the Umbria Region for different idealized but realistic rainfall scenarios has demonstrated the computational efficiency and the accuracy of the proposed methodology, assessed by comparing predicted landslide densities with available field observations reported by the IFFI project. In particular, while the model might fail to identify all individual landslide events, its predictions are remarkably good in identifying the areas of higher landslide density.