This paper deals with several aspects of the assessment of hazard and risk of landsliding. In recent years the interest in this topic has increased greatly and there are many technical papers dealing with this subject in the literature. This article presents a summary review and a classification of the main approaches that have been developed world-wide. The first step is the subdivision between qualitative and quantitative methods. The first group is mainly based on the site-specific experience of experts with the susceptibility/hazard determined directly in the field or by combining different index maps. The approaches of the second group are formally more rigorous. It is possible to distinguish between statistical analyses (bivariate or multivariate) and deterministic methods that involve the analysis of specific sites or slopes based on geo-engineering models. Such analyses can be deterministic or probabilistic. Among the quantitative methods discussed is the Neural Networks approach which has only recently been applied to engineering geology problems. Finally several considerations concerning the concept of acceptable risk and risk management are presented.

Landslide hazard assessment: summary review and new perspectives

https://www.eoas.ubc.ca/personal/erik/e-papers/06EE_EngGeol-Modelling.pdf

Developments in the characterization of complex rock slope deformation and failure using numerical modelling techniques

By modeling soils as spatially random media, estimates of the reliability of foundations against serviceability limit state failure, in the form of excessive differential settlements, can be made. The soil's property of primary interest is its elastic modulus, E, which is represented here using a lognormal distribution and an isotropic correlation structure. Prediction of settlement below a foundation is then obtained using the finite element method. By generating and analyzing multiple realizations, the statistics and density functions of total and differential settlements are estimated. In this paper probabilistic measures of total settlement under a single spread footing and of differential settlement under a pair of spread footings using a two-dimensional model combined with Monte Carlo simulations are presented. For the cases considered, total settlement is found to be represented well by a lognormal distribution. Probabilities associated with differential settlement are conservatively estimated through the use of a normal distribution with parameters derived from the statistics of local averages of the elastic modulus field under each footing.

Probabilistic Foundation Settlement on Spatially Random Soil

By merging elasto-plastic finite element analysis with random field theory, an investigation has been performed into the bearing capacity of undrained clays with spatially varying shear strength. The object of the investigation is to determine the extent to which variance and spatial correlation of the soil's undrained shear strength impact on the statistics of the bearing capacity. Throughout this study, bearing capacity results are expressed in terms of the bearing capacity factor, Nc, in relation to the mean undrained strength. For low coefficients of variation of shear strength, the expected value of the bearing capacity factor tends to the Prandtl solution of Nc = 5·14. For higher values of the coefficient of variation, however, the expected value of the bearing capacity factor falls quite steeply. The spatial correlation length is also shown to be an important parameter that cannot be ignored. The results of Monte Carlo simulations on this non-linear problem are presented in the form of histograms, ...

Bearing capacity of spatially random soil: the undrained clay Prandtl problem revisited

A probabilistic study on the bearing capacity of a rough rigid strip footing on a weightless cohesive soil is carried out to assess the influence of randomly distributed undrained shear strength. Nonlinear finite element analysis is merged with random field theory in conjunction with a Monte Carlo method. In a parametric study, the mean shear strength is held constant while the coefficient of variation and spatial correlation length of cohesion are varied systematically. The influence of the spatial variation of cohesion on the mean bearing capacity is discussed. The results are also presented in a probabilistic context to determine the probability of failure. A comparison between rough and smooth footing conditions is also made.

Bearing Capacity of Rough Rigid Strip Footing on Cohesive Soil: Probabilistic Study

The objective of this study is to provide a simple yet accurate procedure for the description of the spatial variability of the undrained shear strength S u of soft clays. This is achieved on the basis of experimental findings and field observations of the depth-dependent nature of S u . The main features of the method are a linear with depth variation of the mean value and standard deviation of S u and a smooth exponential function that describes the correlation between values received by S u at different vertical locations. The developed procedure is illustrated in a case study involving actual strength data. Two sites are selected from the general area investigated in connection with the West Side Highway in New York City. Each site is characterized by the values of S u obtained along two boreholes using field vane shear tests. The results of the applied analysis verify previous findings on the vertical variability of S u and demonstrates the applicability of the present procedure in the commonly encountered situations with limited data.

Spatial Variability of the Undrained Strength of Clays

A probabilistic model for the progression of failure in a soil slope is presented. Failure progression is defined as a spatial and continuous extension of the failure zone along a potential slip surface in a statistically homogeneous medium. The local safety margin of any segment of the slip surface is assumed to follow a normal distribution; cohesive and frictional parameters of shear strength being considered as independent random variables. The joint distribution of the safety margin of any two adjacent segments of the slip surface is assumed to be bivariate normal. After defining the model and outlining the rules of transition, expressions for the probability of failure progression are derived. The model and its formulation are illustrated by a worked example and the significance of the proposed model is discussed. The suggested approach to the study of progressive failure gives insight into the interdependence of the stability of adjacent elements or sections of a soil mass. Consequently, it is potentially valuable in clarifying the real behavior of soil masses and expecially slopes.

Probabilistic Model of Progressive Failure of Slopes

A simplified procedure permitting the determination of the probability of failure of natural or man-built slopes under static and seismic conditions is presented. Limit equilibrium is expressed as a function of the soil strength parameters (random variables), the numerical values of which are obtained from strength tests under drained conditions. Seismic load is introduced in terms of the maximum horizontal acceleration expected to occur at the site of the slope. The procedure is applied in a case study to predict the probability of failure of a slope during an earthquake. The seismic load is determined in two different ways, namely, (a) from the seismic map of the region (deterministic), and (b) from an engineering analysis of the seismic history of the site of the slope (probabilistic). The results are presented and discussed. (Author)

Dimitri A-Grivas

Papers

Spatial Variability of the Undrained Strength of Clays

Probabilistic Model of Progressive Failure of Slopes

Slope safety prediction under static and seismic loads