Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Abstract

Abstract. Landslides have large negative economic and societal impacts, including loss of life and damage to infrastructure. Slope stability assessment is a vital tool for landslide risk management, but high levels of uncertainty often challenge its usefulness. Uncertainties are associated with the numerical model used to assess slope stability and its parameters, with the data characterizing the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g. rainfall). Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socio-economic changes, such as increased urbanization and resultant land use change. In this study, we illustrate how numerical models can be used to explore the uncertain factors that influence potential future landslide hazard using a bottom-up strategy. Specifically, we link the Combined Hydrology And Stability Model (CHASM) with sensitivity analysis and Classification And Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope failure. We apply our approach to a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates, steep slopes, and highly weathered residual soils. For this particular slope, we find that uncertainties regarding some slope properties (namely thickness and effective cohesion of topsoil) are as important as the uncertainties related to future rainfall conditions. Furthermore, we show that 89 % of the expected behaviour of the studied slope can be characterized based on only two variables -the ratio of topsoil thickness to cohesion and the ratio of rainfall intensity to duration.

Earthquake‐Induced Chains of Geologic Hazards: Patterns, Mechanisms, and Impacts

“…Reviews of Geophysics Montgomery & Dietrich, 1994;Olivares & Damiano, 2007;Wieczorek et al, 2000). Yet we can still learn much about the variability and scaling of meteorological and hydrological factors and processes controlling slope failure (Almeida et al, 2017;Beven & Germann, 2013;Corominas et al, 2013;Crosta & Frattini, 2001;von Ruette et al, 2014). Technical advances now permit very detailed measurements of hydromechanical changes within a landslide body (Kogure & Okuda, 2018).…”

Quantifying the Sensitivity of Progressive Landslide Movements to Failure Geometry, Undercutting Processes and Hydrological Changes

“…The three primary controls on the modeled movements from our proposed approach are toe erosion, fluctuation of pore pressure, and shear strength. Assessing the sensitivity and uncertainty of these governing model parameters is useful to understand their influence on the modeled movements (Almeida et al, 2017;Pianosi et al, 2016). In order to characterize the unique interdependence and influence of these parameters, a comprehensive sensitivity analysis was performed ( Figure 9).…”

Landslide risk management through spatial analysis and stochastic prediction for territorial resilience evaluation

“…Worldwide in the last decade, a new vision and collective sensitivity have been affirmed on disaster risk reduction particularly on stability phenomena [1], thanks to institutions and administrations action in territorial planning in which scientific community and research institutes have been providing fundamental support.…”