Landslide susceptibility maps are helpful tools to identify areas potentially prone to future landslide occurrence. As more and more national and provincial authorities demand for these maps to be computed and implemented in spatial planning strategies, several aspects of the quality of the landslide susceptibility model and the resulting classified map are of high interest. In this study of landslides in Lower Austria, we focus on the model form uncertainty to assess the quality of a flexible statistical modelling technique, the generalized additive model (GAM). The study area (15 850 km2) is divided into 16 modelling domains based on lithology classes. A model representing the entire study area is constructed by combining these models. The performances of the models are assessed using repeated k-fold cross-validation with spatial and random subsampling. This reflects the variability of performance estimates arising from sampling variation. Measures of spatial transferability and thematic consistency are applied to empirically assess model quality. We also analyse and visualize the implications of spatially varying prediction uncertainties regarding the susceptibility map classes by taking into account the confidence intervals of model predictions. The 95% confidence limits fall within the same susceptibility class in 85% of the study area. Overall, this study contributes to advancing open communication and assessment of model quality related to statistical landslide susceptibility models.

Landslides are a major natural hazard, but uncertainties about their occurrence in a warmer climate are substantial. The relative role of rainfall, soil moisture, and land-use changes and the importance of climate change mitigation are not well understood. Here, we develop an event storyline approach to address these issues, considering an observed event in Austria with some 3000 landslides as a showcase. We simulate the event using a convection permitting regional climate model and a statistical landslide model at present and a range of plausible future climate and land use conditions. Depending on the changes of rainfall and soil moisture, the area affected during a 2009-type event could grow by 45% at 4 K global warming, although a slight reduction is also possible. Such growth could be reduced to less than 10% by limiting global warming according to the Paris agreement. Anticipated land-use changes towards a climate-resilient forest would fully compensate for such a limited increase in hazard.