EGU21-15606, updated on 09 Jan 2024
EGU General Assembly 2021
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Combining static and dynamic environmental factors at various scales to predict shallow landsliding in South Tyrol, Italy – The Proslide project

Robin Kohrs1,  Lotte de Vugt2, Thomas Zieher2,3, Alice Crespi1, Mattia Rossi1, Felix Greifeneder1, Barbara Schneider-Muntau4, Bartolomeo Ventura1, Martin Rutzinger2, and Stefan Steger1
Robin Kohrs et al.
  • 1Eurac Research, Institute for Earth Observation, Bolzano, Italy (
  • 2Institute of Geography, University of Innsbruck, Austria
  • 3Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Austria
  • 4Institute of Infrastructure, University of Innsbruck, Austria

Shallow landslides in alpine environments can constitute a serious threat to the exposed elements. The spatio-temporal occurrence of such slope movements is controlled by a combination of predisposing factors (e.g. topography), preparatory factors (e.g. wet periods, snow melting) and landslide triggers (e.g. heavy precipitation events).  

For large study areas, landslide assessments frequently focus either on the static predisposing factors to estimate landslide susceptibility using data-driven procedures, or exclusively on the triggering events to derive empirical rainfall thresholds. For smaller areas, dynamic physical models can reasonably be parameterized to simultaneously account for static and dynamic landslide controls.  

The recently accepted Proslide project aims to develop and test methods with the potential to improve the predictability of landslides for the Italian province of South Tyrol. It is envisaged to account for a variety of innovative input data at multiple spatio-temporal scales. In this context, we seek to exploit remote sensing data for the spatio-temporal description of landslide controlling factors (e.g. precipitation RADAR; satellite soil moisture) and to develop models that allow an integration of heterogeneous model inputs using both, data-driven approaches (regional scale) and physically-based models (catchment scale). This contribution presents the core ideas and methodical framework behind the Proslide project and its very first results (e.g. relationships between landslide observations and gridded daily precipitation data at regional scale). 

How to cite: Kohrs, R., de Vugt,  ., Zieher, T., Crespi, A., Rossi, M., Greifeneder, F., Schneider-Muntau, B., Ventura, B., Rutzinger, M., and Steger, S.: Combining static and dynamic environmental factors at various scales to predict shallow landsliding in South Tyrol, Italy – The Proslide project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15606,, 2021.