Triggering of shallow landslides and soil-hydrological processes

Shallow landslides triggered by rainfall events pose a serious threat to people and infrastructure. Previous research has shown that considering both soil moisture conditions and precipitation events helps to effectively predict periods of increased landslide risk. Here in this project, soil moisture measurement data from monitoring stations across Switzerland, precipitation information and landslide observations will lead to even better regional early warnings of landslides with the help of machine learning and physics-based modeling. 

In a second step, we will investigate why landslides occur at certain locations and not at others, even though, from an objective point of view (based on GIS-based susceptibility maps), they should occur with equal probability at both locations. To this end, field surveys of the subsoil will be carried out in summer 2025 using various methods (e.g., electrical resistance measurement). The field sites are located in St. Anthönien and Sachseln, where widespread landslides occurred in 2005 and 1997, respectively.

Finally, the impact of climate change on the occurrence of such landslide events will be investigated. We will use future hydrological scenarios that show how heavy precipitation events, soil moisture, and snowmelt will change in different regions of Switzerland as a result of climate change.

Publications:

Halter T., Lehmann P., Wicki A., Aaron J., Stähli M. (2024) Optimising landslide initiation modelling with high-resolution saturation prediction based on soil moisture monitoring data. Landslides. doi:10.1007/s10346-024-02304-x

Halter, T., Lehmann, P., Bast, A., Aaron, J., & Stähli, M. (2025). In situ soil moisture data improve precipitation-based shallow landslide early warning through innovative machine learning methods. Landslides. https://doi.org/10.1007/s10346-025-02599-4

Conference contributions:

Stähli M., Halter T., Walter F., Wicki A., Lehmann P. (2023) A pilot study in the Napf-Region (Central Switzerland) for an upcoming national landslide early warning system In V. Capobianco, L. Rødvand, F. Nadim, H. Heyerdahl, & S. Lacasse (Eds.), Proceedings of the 3rd JTC1 workshop. Impact of global changes on landslide hazard and risk. Oslo: Norwegian Geotechnical Institute (NGI). 121-124. Institutional Repository DORA

Stähli M., Halter T., Walter F., Wicki A., Lehmann P. (2023) Towards a national Landslide Early Warning System for Switzerland: a pilot study to assess the use of soil wetness information and physically-based modelling, World Landslide Forum 6, Florence, Italy, 13-17 November, 2023, oral presentation (slides).

Halter T., Lehmann P., Bast A., Stähli M. (2023) Combining climate and soil moisture information in statistical modelling for landslide early warning. 21st Swiss Geoscience Meeting, Mendrisio, 18 November, 2023, abstract.