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.
Research article
| 
18 Jan 2023
Research article |
| 18 Jan 2023
| 18 Jan 2023
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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Impacts from extreme weather events are becoming increasingly severe under global warming, in particular when events occur simultaneously or successively. While these complex event combinations are often difficult to analyse as impact data, early warning schemes or modelling frameworks might not be fit for purpose. In this perspective we reflect on the usability of compound event research to bridge the gap between academic research and real-world applications, by formulating a set of guidelines.
Alexander Brenning, Guillermo F. Azócar, Pablo Iribarren Anacona, Kenji Yoshikawa, Gino Casassa, Pedro Straub-Bustamante, Duilio Fonseca-Gallardo, and Jorge Huenante
EGUsphere, https://doi.org/10.5194/egusphere-2025-5090, https://doi.org/10.5194/egusphere-2025-5090, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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We created the first high-resolution map of mountain permafrost distribution in mainland Chile. Using field evidence from rock glaciers and boreholes with climate and terrain data, we found that more than 8,000 km2, mainly in the dry Andes of northern and central Chile, offer suitable conditions. Permafrost affects water resources, slope stability, and infrastructure, and our model provides a baseline for planning and future research under climate change.
Matthias Schlögl, Laura Waltersdorfer, Peter Regner, Andrea Siposova, and Alexander Brenning
EGUsphere, https://doi.org/10.5194/egusphere-2025-5210, https://doi.org/10.5194/egusphere-2025-5210, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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Reproducibility is essential for reliable scientific research, yet it remains challenging in (geo-)scientific practice. This perspective explores how to improve reproducibility in geospatial analyses by identifying key barriers and proposing actionable solutions. By encouraging both a cultural shift and offering strategies tailored to the unique needs of the field, our aim is to provide clear implementation strategies that foster transparent and reproducible geospatial research.
Armin Schaffer, Tobias Lichtenegger, Albert Ossó, and Douglas Maraun
EGUsphere, https://doi.org/10.5194/egusphere-2025-4235, https://doi.org/10.5194/egusphere-2025-4235, 2025
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Extreme rainfall in Europe is often linked to weather fronts. To understand how these events may change in the future, we first need to evaluate how well climate models represent them. We found that all models show substantial biases, particularly for cold fronts, while higher-resolution models improve their simulation. Warm fronts also show biases, though they are generally better represented than cold fronts. This highlights the importance of high-resolution models for reliable projections.
Daniel Viviroli, Martin Jury, Maria Staudinger, Martina Kauzlaric, Heimo Truhez, and Douglas Maraun
EGUsphere, https://doi.org/10.5194/egusphere-2025-1920, https://doi.org/10.5194/egusphere-2025-1920, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Estimating the frequency and magnitude of floods is challenging due to the limited length of streamflow records. Here, we explore whether an extensive archive of meteorological forecasts run over past dates can assist in this context. After processing and concatenating these data for use as input to a hydrological model, we derive flood statistics from simulated streamflow. Results are promising for the larger catchments studied, providing a valuable complementary perspective on rare floods.
Colin Manning, Martin Widmann, Douglas Maraun, Anne F. Van Loon, and Emanuele Bevacqua
Weather Clim. Dynam., 4, 309–329, https://doi.org/10.5194/wcd-4-309-2023, https://doi.org/10.5194/wcd-4-309-2023, 2023
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Climate models differ in their representation of dry spells and high temperatures, linked to errors in the simulation of persistent large-scale anticyclones. Models that simulate more persistent anticyclones simulate longer and hotter dry spells, and vice versa. This information is important to consider when assessing the likelihood of such events in current and future climate simulations so that we can assess the plausibility of their future projections.
Yi Yang, Douglas Maraun, Albert Ossó, and Jianping Tang
Nat. Hazards Earth Syst. Sci., 23, 693–709, https://doi.org/10.5194/nhess-23-693-2023, https://doi.org/10.5194/nhess-23-693-2023, 2023
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This study quantifies the spatiotemporal variation and characteristics of compound long-duration dry and hot events in China over the 1961–2014 period. The results show that over the past few decades, there has been a substantial increase in the frequency of these compound events across most parts of China, which is dominated by rising temperatures. We detect a strong increase in the spatially contiguous areas experiencing concurrent dry and hot conditions.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022, https://doi.org/10.5194/esd-13-1451-2022, 2022
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Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
Marco Hofmann, Claudia Volosciuk, Martin Dubrovský, Douglas Maraun, and Hans R. Schultz
Earth Syst. Dynam., 13, 911–934, https://doi.org/10.5194/esd-13-911-2022, https://doi.org/10.5194/esd-13-911-2022, 2022
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We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.
Jason Goetz, Robin Kohrs, Eric Parra Hormazábal, Manuel Bustos Morales, María Belén Araneda Riquelme, Cristián Henríquez, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 21, 2543–2562, https://doi.org/10.5194/nhess-21-2543-2021, https://doi.org/10.5194/nhess-21-2543-2021, 2021
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Debris flows are fast-moving landslides that can cause incredible destruction to lives and property. Using the Andes of Santiago as an example, we developed tools to finetune and validate models predicting likely runout paths over large regions. We anticipate that our automated approach that links the open-source R software with SAGA-GIS will make debris-flow runout simulation more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
Milan Flach, Alexander Brenning, Fabian Gans, Markus Reichstein, Sebastian Sippel, and Miguel D. Mahecha
Biogeosciences, 18, 39–53, https://doi.org/10.5194/bg-18-39-2021, https://doi.org/10.5194/bg-18-39-2021, 2021
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Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. We study the impact of droughts and heatwaves on the uptake of CO2 of different vegetation types at the global scale. We find that agricultural areas are generally strongly affected. Forests instead are not particularly sensitive to the events under scrutiny. This implies different water management strategies of forests but also a lack of sensitivity to remote-sensing-derived vegetation activity.
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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...
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