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The frequency of snowmelt-induced soil slope instabilities is increasing in some seasonally cold regions because of climate change. Reliable hazard assessment and risk mitigation of snowmelt-induced landslides require physically-based prediction models. However, existing models either apply only at the slope scale or assume precipitation as the sole landslide trigger. In doing so, they neglect the complexity and coupled nature of the thermo-hydro-mechanical processes leading to slope instability in seasonally cold regions (such as snow accumulation and melting, infiltration and surface runoff, soil saturation, pore water pressure buildup and dissipation). Here, we present a spatially distributed and sequentially coupled numerical model to simulate snowmelt-induced slope instabilities at the catchment scale. The model accounts for temperature-dependent changes in the soil hydraulic behavior related to changes in water state by means of a routine implemented in a geographic information system. We verified the performance of the model using a case study of spring snowmelt-induced soil slope failures that occurred after the 2004 Mid-Niigata earthquake in Japan. Considering limitations and simplifications, the model was able to predict the triggering condition, magnitude, and spatial distribution of the snowmelt-induced landslides with a satisfactory degree of accuracy. We believe that the robustness and simplicity of our numerical approach make it suitable for implementation in early warning systems.Plain Language Summary Climate change is responsible for an increasing number of natural disasters in seasonally cold regions, where heavier snowfalls and sudden snowmelts can cause destructive landslides on hill slopes. These landslides are not easy to study because the mechanisms that trigger them are different from those of shallow landslides occurring in response to rainfall. Moreover, advanced models that incorporate the complex relations among rain, snow, temperature, soil freezing, melting, and slope stability at a detailed scale are still cumbersome and very demanding in terms of computational power. For these reasons, evaluating the risk to people and assets in seasonally cold regions is not straightforward, and existing models tend to underestimate it. In this paper, we propose a novel modeling strategy to study the stability of soil slopes under the influence of both snowmelt and rainfall at a regional scale. First, we explain the governing mechanisms of snowmelt-induced landslides; then, we present our strategy along with detailed explanations of the equations we use. We test our model by predicting a known case study (the snowmelt-induced landslides of 2005 in Niigata, Japan) and obtain a reasonably good result. This simple strategy could be applied in an early warning system for snowmelt-induced landslides.

Abstract. Only two months after a huge forest fire occurred in the upper part of a valley located in central Portugal, several debris flows were triggered by intense rainfall. The event caused infrastructural and economic damage, although no lives were lost. The present research aims to simulate the run-out of two debris flows that occurred during the event as well as to calculate via back-analysis the rheological parameters and the excess rain involved. Thus, a dynamic model was used, which integrates surface runoff, concentrated erosion along the channels, propagation and deposition of flow material. Afterwards, the model was validated using 32 debris flows triggered during the same event that were not considered for calibration. The rheological and entrainment parameters obtained for the most accurate simulation were then used to perform three scenarios of debris flow run-out on the basin scale. The results were confronted with the existing buildings exposed in the study area and the worst-case scenario showed a potential inundation that may affect 345 buildings. In addition, six streams where debris flow occurred in the past and caused material damage and loss of lives were identified.

Background: Landslides hazard analyses entail a scale-dependent approach in order to mitigate accordingly the damages and other negative consequences at the respective scales of occurrence. Medium or large scale landslide run-out modelling for many possible landslide initiation areas has been a very difficult task in the past. This arises from the inability of the run-out models to compute the displacement with a large amount of individual initiation areas as it turns out to be computationally strenuous. Most of the existing physically based run-out models have difficulties in handling such situations. For this reason, empirical methods have been used as a practical mean to predict landslides mobility at a medium scale (1: 10,000 to 1: 50,000). They are the most widely used techniques to estimate the maximum run-out distance and affected zones not only locally but also regionally. In this context, a medium scale numerical model for flow-like mass movements in urban and mountainous areas was developed.