Response to Reviewer 1

Abstract

deep uncertainties in landslide modelling for disaster risk reduction under climate change. Natural Hazards and Earth System Sciences Discussions. 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 characterising the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g., rainfall). 10Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socioeconomic changes, such as increased urbanisation 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 ClassificationAnd Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope 15 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 top soil) 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 characterised based on only two variablesthe ratio of top soil thickness to cohesion and the ratio of rainfall 20 intensity to duration.