Exploring the stability of shallow landslides through global sensitivity analysis: a proof of concept from western Rwanda

Shallow landslides represent a major hazard in western Rwanda, where steep slopes, deeply weathered materials and intense precipitation frequently interact. This study, carried out in the framework of the WALL project (Grant ID: GCRW-CL001, https://www.wallatrwanda.org/), focuses on a landslide-prone area within the Karongi District and presents a proof-of-concept analysis aimed at investigating the sensitivity of slope stability to key geotechnical and pore pressure–related parameters.Slope stability is analysed using Scoops 3D (Reid et al., 2015), which implements three-dimensional limit-equilibrium methods (LEM) and evaluates slope stability by testing a large number of potential spherical trial failure surfaces. This approach allows for a systematic exploration of potential instability mechanisms while maintaining a computationally efficient framework suitable for regional-scale and data-scarce applications. Due to the limited availability of site-specific geotechnical data, model parameters are defined within plausible ranges derived from published literature and regional information.Under these conditions, a global sensitivity analysis based on Sobol indices (Saltelli and Sobol, 1995) represents a suitable and robust strategy to investigate model behaviour and uncertainty. The Sobol analysis is applied to investigate the influence of key geotechnical parameters, including cohesion, internal friction angle and unit weight, and additional pore pressure accounting for hydrological conditions on slope stability results. Both first-order effects and higher-order interaction terms are analysed, providing insights into the combined mechanical and hydraulic controls on slope stability.The proposed workflow identifies the dominant sources of variability on the output and offers a structured basis for prioritizing the quantification of geotechnical parameters in future data acquisition and model refinement, also in connection with specific triggering factors relevant for the studied area, such as rainfall. REFERENCESReid, M. E., Christian, S. B., Brien, D. L., & Henderson, S. T. (2015). Scoops3D: software to analyze 3D slope stability throughout a digital landscape (No. 14-A1). US Geological Survey.Saltelli, A., Sobol’, I. M. (1995). Sensitivity analysis for nonlinear mathematical models: numerical experience. Matematicheskoe Modelirovanie, 7(11), 16–28.