Identification of failure thresholds and critical uncertainties associated with slope stability often requires the specification of geotechnical parameter values for input into a physically-based model. The variation of these parameters (including mechanical soil properties such as effective friction angle and cohesion) can have a significant impact on the computed factor of safety. These uncertainties arise from natural variations in soils, measurement techniques, and lack of reliable information. Researchers may use statistical analysis coupled with numerical simulation to determine possible ranges of slope factors of safety and the relative influence of geotechnical and other parameters, such as topsoil depth and rainfall. This study investigates the variation of geotechnical parameters observed on the island of Saint Lucia in the Eastern Caribbean. A database of particle size distributions, in-situ moisture contents, Atterberg and direct shear box test results is compiled from 91 samples of tropical soils in Saint Lucia. A study of various probability distributions shows that the Weibull distribution may be favoured for the effective friction angle of the Saint Lucian soils considered based on the Akaike information criterion, employed as an estimator of the relative quality of statistical models dealing with the trade-off between goodness-of-fit and simplicity of the model.
Geotechnical designers and modellers must capture and quantify the variability of key soil properties to make engineering decisions. There is a long history in geotechnical engineering of assembling large databases of past soil tests. This paper shows the use of geotechnical databases in two contexts: (a) slope stability modelling in the Eastern Caribbean and (b) settlement response of bored piles in London Clay.
Prediction of the conditions under which landslides may occur is essential for designing sustainable risk-mitigation measures and cost-effective geotechnical structures. Slope stability analyses typically account for slope geometry, soil mechanical properties and groundwater conditions to determine the performance of a slope with respect to a specified factor of safety. These properties vary both spatially and over time; geotechnical design codes require the use of factored design parameter values to account for possible worst-case conditions. Furthermore, standard geotechnical analyses typically exclude the dynamic hydrological processes of rainfall infiltration and loss of matric suction that often trigger landslides. Slope stability assessment is particularly challenging in developing countries with limited resources for acquiring slope data, meeting conservative design standards and mitigating landslide risk. This study applied a combined slope hydrology and stability model to address these issues for a residual soil slope in the tropics. This paper presents a method for maximising stability information from limited data, disaggregating the effects of three different design parameter sets and factor of safety threshold choices, as well as diagnosing the dominant geotechnical and dynamic landslide-triggering factors. This modelling approach provides a more transparent basis for sustainable slope-management decisions.
For assessment of slope stability in data-scarce regions prone to natural hazards, modelling relies, to a large degree, on estimates of the effective friction angle. Using a database, comprising soil data from Saint Lucia in the Eastern Caribbean, both simple regression and multiple linear regression analysis were performed. These analyses correlate various basic soil parameters with the effective friction angle measurements contained in the database. The developed statistical relationships are then employed for the estimation of the effective friction angle for use in a slope stability simulation scenario. These analyses show the narrowing of the expected range of results for the slope factor of safety when more soil parameters are used in the estimation of effective friction angle.
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