Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria) [post]

Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, Alexander Brenning
2022 unpublished
Abstract. The assessment of uncertainties in landslide susceptibility modelling in a changing environment is an important, yet often neglected task. In an Austrian case study, we investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In June 2009, extreme events of heavy thunderstorms occurred in the Styrian basin, triggering thousands of landslides. Using a storyline approach, we discovered a
more » ... lly lower landslide susceptibility for pre-industrial climate, while for future climate (2071–2100) a potential increase of 35 % in highly susceptible areas (storyline of much heavier rain) may be compensated by much drier soils (-45 % areas highly susceptible to landsliding). However, the estimated uncertainties in predictions were generally high. While uncertainties related to within-event internal climate model variability were substantially lower than parametric uncertainties of the landslide susceptibility model (ratio of around 0.25), parametric uncertainties were of the same order as the climate scenario uncertainty for the higher warming levels (+3 K and +4 K). We suggest that in future uncertainty assessments, an improved availability of event-based landslide inventories and high-resolution soil and precipitation data will help to reduce parametric uncertainties of landslide susceptibility models used to assess the impacts of climate change on landslide hazard and risk.
doi:10.5194/nhess-2022-154 fatcat:pgyf4bda4rbexiyl7xewyiytxi