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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.

Current assessments of slope stability rely on point sensors, the results of which are often difficult to interpret, have relatively high costs and do not provide large-area coverage. A new system is under development, based on integrated geophysical-geotechnical sensors to monitor groundwater conditions via electrical resistivity tomography. So that this system can provide end users with reliable information, it is essential that the relationships between resistivity, shear strength, suction and water content are fully resolved, particularly where soils undergo significant cycles of drying and wetting, with associated soil fabric changes. This paper presents a study to establish these relationships for a remoulded clay taken from a test site in Northumberland, UK. A rigorous testing programme has been undertaken, integrating the results of multi-scalar laboratory and field experiments, comparing two-point and four-point resistivity testing methods. Shear strength and water content were investigated using standard methods, whilst a soil water retention curve was derived using a WP4 dewpoint potentiometer. To simulate seasonal effects, drying and wetting cycles were imposed on prepared soil specimens. Results indicated an inverse power relationship between resistivity and water content with limited hysteresis between drying and wetting cycles. Soil resistivity at lower water contents was, however, observed to increase with ongoing seasonal cycling. Linear hysteretic relationships were established between undrained shear strength and water content, principally affected by two mechanisms: soil fabric deterioration and soil suction loss between drying and wetting events. These trends were supported by images obtained from scanning electron microscopy.

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.

Rainfall-triggered landslides are increasing in the humid tropics, and Small Island Developing States are disproportionately affected. Frequent shallow slides in hillside cuttings along roads and in communities hinder sustainable development. Larger, less frequent storms cause hundreds of landslides that block lifeline roads, impede disaster response and reverse economic growth. Top-down Disaster Risk Reduction (DRR) policies and approaches aiming to transfer conventional landslide assessment science and engineering practices are not always suitable in these data-and resourcelimited contexts. This paper recognises the emergence of co-production approaches as part of the resilience paradigm response to DRR science-policy-practice gaps. We present a case study from Saint Lucia, Eastern Caribbean, in which government engineers and policymakers have partnered with the authors to co-produce landslide hazard assessment data and prototype decision support tools to strengthen landslide hazard management along lifeline roads.

Rainfall-triggered landslides are an 'everyday risk' to Small Island States, such as Saint Lucia in the Caribbean, and have the potential to destroy or damage buildings and disrupt lifelines such as roads and pipelines. To better evaluate these landslide hazards, efforts have been made to develop decisionsupport tools linking rainfall scenarios to stability for different types of road cut slope. Many thousands of stochastic simulations can be performed using a combined hydrology and slope stability model (CHASM) which requires inputs of slope cross-sectional geometry, soil and hydrological parameters which allows representative rainfall-triggered landslide scenarios to be produced. To use CHASM for this purpose the statistical variation of the relevant geotechnical properties such as friction angle needs to be assessed. This paper presents the analysis of an updated database for Saint Lucian soils that has been compiled using data supplied by the Government of Saint Lucia Ministry of Infrastructure, Port Services and Transport. The Coefficient of Variation values of the key soil mechanics parameters are reported and previously developed transformation models for estimating effective friction angle are updated. The Weibull statistical distribution is shown to be the best fit to the friction angle data.

Abstract. Geotechnical asset owners need to know which parts of their asset network are vulnerable to climate change induced failure in order to optimise future investment. Protecting these vulnerable slopes requires monitoring systems capable of identifying and alerting to asset operators changes in the internal conditions that precede failure. Current monitoring systems are heavily reliant on point sensors which can be difficult to interpret across slope scale. This paper presents challenges to producing such a system and research being carried out to address some of these using electrical resistance tomography (ERT). Experimental results show that whilst it is possible to measure soil water content indirectly via resistivity the relationship between resistivity and water content will change over time for a given slope. If geotechnical parameters such as pore water pressure are to be estimated using this method then ERT systems will require integrating with more conventional geotechnical instrumentation to ensure correct representative information is provided. The paper also presents examples of how such data can be processed and communicated to asset owners for the purposes of asset management.