Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-205-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-205-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)
Raphael Knevels
CORRESPONDING AUTHOR
Department of Geography, Friedrich Schiller University Jena, 07743 Jena, Germany
Helene Petschko
Department of Geography, Friedrich Schiller University Jena, 07743 Jena, Germany
Herwig Proske
Remote Sensing and Geoinformation Department, JOANNEUM RESEARCH Forschungsgesellschaft mbH, Graz, 8010, Austria
Philip Leopold
Center for Low-Emission Transport, AIT Austrian Institute of Technology GmbH, Vienna, 1210, Austria
Aditya N. Mishra
Wegener Center for Climate and Global Change, Karl-Franzens-Universität Graz, Graz, 8010, Austria
Douglas Maraun
Wegener Center for Climate and Global Change, Karl-Franzens-Universität Graz, Graz, 8010, Austria
Alexander Brenning
Department of Geography, Friedrich Schiller University Jena, 07743 Jena, Germany
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Cited
11 citations as recorded by crossref.
- From spatio-temporal landslide susceptibility to landslide risk forecast T. Wang et al. 10.1016/j.gsf.2023.101765
- How will the projected climate change influence rainfall-induced landslides in Europe? A review of modelling approaches S. Gariano & G. Rianna 10.1007/s10346-025-02550-7
- Shallow mass movement susceptibility mapping through remote sensing using AHP, WLC, and soil moisture index analysis H. Shabbir et al. 10.1016/j.asr.2025.07.002
- Climate change amplified the 2009 extreme landslide event in Austria A. Mishra et al. 10.1007/s10584-023-03593-2
- Climate change increases the number of landslides at the juncture of the Alpine, Pannonian and Mediterranean regions M. Jemec Auflič et al. 10.1038/s41598-023-50314-x
- Statistical landslide susceptibility assessment using Bayesian logistic regression and Markov Chain Monte Carlo (MCMC) simulation with consideration of model class selection T. Zhao et al. 10.1080/17499518.2023.2288600
- Enhancing landslide susceptibility predictions with XGBoost and SHAP: a data-driven explainable AI method D. Khan et al. 10.1080/10106049.2025.2514725
- Assessing the impact of climate change on rainfall-triggered landslides: a case study in California S. Semnani et al. 10.1007/s10346-024-02428-0
- Brief communication: Visualizing uncertainties in landslide susceptibility modelling using bivariate mapping M. Schlögl et al. 10.5194/nhess-25-1425-2025
- Potential impacts of climate change on ecosystem services in Austria U. Schirpke & E. Tasser 10.1016/j.ecoser.2024.101641
- Towards a holistic assessment of landslide susceptibility models: insights from the Central Eastern Alps M. Schlögl et al. 10.1007/s12665-024-12041-y
11 citations as recorded by crossref.
- From spatio-temporal landslide susceptibility to landslide risk forecast T. Wang et al. 10.1016/j.gsf.2023.101765
- How will the projected climate change influence rainfall-induced landslides in Europe? A review of modelling approaches S. Gariano & G. Rianna 10.1007/s10346-025-02550-7
- Shallow mass movement susceptibility mapping through remote sensing using AHP, WLC, and soil moisture index analysis H. Shabbir et al. 10.1016/j.asr.2025.07.002
- Climate change amplified the 2009 extreme landslide event in Austria A. Mishra et al. 10.1007/s10584-023-03593-2
- Climate change increases the number of landslides at the juncture of the Alpine, Pannonian and Mediterranean regions M. Jemec Auflič et al. 10.1038/s41598-023-50314-x
- Statistical landslide susceptibility assessment using Bayesian logistic regression and Markov Chain Monte Carlo (MCMC) simulation with consideration of model class selection T. Zhao et al. 10.1080/17499518.2023.2288600
- Enhancing landslide susceptibility predictions with XGBoost and SHAP: a data-driven explainable AI method D. Khan et al. 10.1080/10106049.2025.2514725
- Assessing the impact of climate change on rainfall-triggered landslides: a case study in California S. Semnani et al. 10.1007/s10346-024-02428-0
- Brief communication: Visualizing uncertainties in landslide susceptibility modelling using bivariate mapping M. Schlögl et al. 10.5194/nhess-25-1425-2025
- Potential impacts of climate change on ecosystem services in Austria U. Schirpke & E. Tasser 10.1016/j.ecoser.2024.101641
- Towards a holistic assessment of landslide susceptibility models: insights from the Central Eastern Alps M. Schlögl et al. 10.1007/s12665-024-12041-y
Latest update: 24 Jul 2025
Short summary
In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering thousands of landslides. Landslide storylines help to show potential future changes under changing environmental conditions. The often neglected uncertainty quantification was the aim of this study. We found uncertainty arising from the landslide model to be of the same order as climate scenario uncertainty. Understanding the dimensions of uncertainty is crucial for allowing informed decision-making.
In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering...