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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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.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Marco Marcer, Charlie Serrano, Alexander Brenning, Xavier Bodin, Jason Goetz, and Philippe Schoeneich
The Cryosphere, 13, 141–155, https://doi.org/10.5194/tc-13-141-2019, https://doi.org/10.5194/tc-13-141-2019, 2019
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This study aims to assess the occurrence of rock glacier destabilization in the French Alps, a process that causes a landslide-like behaviour of permafrost debris slopes. A significant number of the landforms in the region were found to be experiencing destabilization. Multivariate analysis suggested a link between destabilization occurrence and permafrost thaw induced by climate warming. These results call for a regional characterization of permafrost hazards in the context of climate change.
Milan Flach, Sebastian Sippel, Fabian Gans, Ana Bastos, Alexander Brenning, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 15, 6067–6085, https://doi.org/10.5194/bg-15-6067-2018, https://doi.org/10.5194/bg-15-6067-2018, 2018
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Northern forests enhanced their productivity during and before the 2010 Russian mega heatwave. We scrutinize this issue with a novel type of multivariate extreme event detection approach. Forests compensate for 54 % of the carbon losses in agricultural ecosystems due to vulnerable conditions in spring and better water management in summer. The findings highlight the importance of forests in mitigating climate change, while not alleviating the consequences of extreme events for food security.
Douglas Maraun and Martin Widmann
Hydrol. Earth Syst. Sci., 22, 4867–4873, https://doi.org/10.5194/hess-22-4867-2018, https://doi.org/10.5194/hess-22-4867-2018, 2018
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Cross-validation of free-running bias-corrected climate change simulations against observations is misleading, because it is typically dominated by internal variability. In particular, a sensible bias correction may be rejected and a non-sensible bias correction may be accepted. We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations. Instead, one should evaluate temporal, spatial and
process-based aspects.
Milan Flach, Fabian Gans, Alexander Brenning, Joachim Denzler, Markus Reichstein, Erik Rodner, Sebastian Bathiany, Paul Bodesheim, Yanira Guanche, Sebastian Sippel, and Miguel D. Mahecha
Earth Syst. Dynam., 8, 677–696, https://doi.org/10.5194/esd-8-677-2017, https://doi.org/10.5194/esd-8-677-2017, 2017
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Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community. The Earth system is highly multivariate. We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing. We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches. The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided.
Emanuele Bevacqua, Douglas Maraun, Ingrid Hobæk Haff, Martin Widmann, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, https://doi.org/10.5194/hess-21-2701-2017, 2017
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We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme impacts to society which are driven by statistically dependent climatic variables. Based on this model we study compound floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model includes meteorological predictors which (1) provide insight into the physical processes underlying CEs, as well as into the temporal variability, and (2) allow us to statistically downscale CEs.
Guillermo F. Azócar, Alexander Brenning, and Xavier Bodin
The Cryosphere, 11, 877–890, https://doi.org/10.5194/tc-11-877-2017, https://doi.org/10.5194/tc-11-877-2017, 2017
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We present in this work a new statistical permafrost distribution model that provided a more detailed, locally adjusted insights into mountain permafrost distribution in the semi-arid Chilean Andes. The results indicate conditions favorable for permafrost presence, can be present in up to about 6.8 % of the study area (1051 km2), especially in the Elqui and Huasco watersheds. This kind of methodological approach used in this research can be replicable in another parts of the Andes.
Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann
Hydrol. Earth Syst. Sci., 21, 1693–1719, https://doi.org/10.5194/hess-21-1693-2017, https://doi.org/10.5194/hess-21-1693-2017, 2017
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For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.
Stefan Steger, Alexander Brenning, Rainer Bell, and Thomas Glade
Nat. Hazards Earth Syst. Sci., 16, 2729–2745, https://doi.org/10.5194/nhess-16-2729-2016, https://doi.org/10.5194/nhess-16-2729-2016, 2016
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This study investigates the propagation of landslide inventory-based positional errors into statistical landslide susceptibility models by artificially introducing such spatial inaccuracies. The findings highlight that (i) an increasing positional error is related to increasing distortions of modelling and validation results, (ii) interrelations between inventory-based errors and modelling results are complex, and (iii) inventory-based errors can be counteracted by adapting the study design.
D. Maraun and M. Widmann
Hydrol. Earth Syst. Sci., 19, 3449–3456, https://doi.org/10.5194/hess-19-3449-2015, https://doi.org/10.5194/hess-19-3449-2015, 2015
A. Brenning, M. Schwinn, A. P. Ruiz-Páez, and J. Muenchow
Nat. Hazards Earth Syst. Sci., 15, 45–57, https://doi.org/10.5194/nhess-15-45-2015, https://doi.org/10.5194/nhess-15-45-2015, 2015
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Mountain roads in developing countries often increase landslide occurrence. In this study, landslide initiation frequency along interurban highways was investigated in the Ecuadorian Andes across different climates. Using statistical models, landslides were found to be about 20 times more likely to occur in close proximity to highways compared to areas in 200m distance from highways while accounting for other environmental factors. Road effects appear to be enhanced in some geological units.
Related subject area
Landslides and Debris Flows Hazards
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
A new analytical method for stability analysis of rock blocks with basal erosion in sub-horizontal strata by considering the eccentricity effect
Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
Characteristics of debris flows recorded in the Shenmu area of central Taiwan between 2004 and 2021
Optimization strategy for flexible barrier structures: Investigation and back analysis of a rockfall disaster case in southwestern China
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
The role of thermokarst evolution in debris flow initiation (Hüttekar Rock Glacier, Austrian Alps)
Accounting for the effect of forest and fragmentation in probabilistic rockfall hazard
Comprehensive landslide susceptibility map of Central Asia
The influence of large woody debris on post-wildfire debris flow sediment storage
Statistical modeling of sediment supply in torrent catchments of the northern French Alps
A data-driven evaluation of post-fire landslide susceptibility
Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models
Brief communication: The northwest Himalaya towns slipping towards potential disaster
Dynamic response and breakage of trees subject to a landslide-induced air blast
Debris-flow surges of a very active alpine torrent: a field database
Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data
Instantaneous limit equilibrium back analyses of major rockslides triggered during the 2016–2017 central Italy seismic sequence
Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines
Antecedent rainfall as a critical factor for the triggering of debris flows in arid regions
Sensitivity analysis of a built environment exposed to the synthetic monophasic viscous debris flow impacts with 3-D numerical simulations
Simulation analysis of 3D stability of a landslide with a locking segment: A case study of Tizicao landslide in Maoxian County, Southwest China
Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo)
Spatio-temporal analysis of slope-type debris flow activity in Horlachtal, Austria, based on orthophotos and lidar data since 1947
Assessing the relationship between weather conditions and rockfall using terrestrial laser scanning to improve risk management
Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data
Numerical model derived intensity-duration thresholds for early warning of rainfall-induced debris flows in the Himalayas
Brief communication: An autonomous UAV for catchment-wide monitoring of a debris flow torrent
How volcanic stratigraphy constrains headscarp collapse scenarios: the Samperre cliff case study (Martinique island, Lesser Antilles)
Landslide susceptibility assessment in the rocky coast subsystem of Essaouira, Morocco
Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides
Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments
Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda
Earthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influences
Pre-collapse motion of the February 2021 Chamoli rock–ice avalanche, Indian Himalaya
Physically based modeling of co-seismic landslide, debris flow, and flood cascade
Finite-hillslope analysis of landslides triggered by excess pore water pressure: the roles of atmospheric pressure and rainfall infiltration during typhoons
Estimating global landslide susceptibility and its uncertainty through ensemble modeling
Terrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India)
Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding
Introducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situations
Augmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scars
What drives landslide risk? Disaggregating risk analyses, an example from the Franz Josef Glacier and Fox Glacier valleys, New Zealand
Geographic information system models with fuzzy logic for susceptibility maps of debris flow using multiple types of parameters: a case study in Pinggu District of Beijing, China
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
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A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 2023
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Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here, we present new results from a Doppler radar rockfall alarm system, which has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 2023
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Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
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The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
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Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
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Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
Yi-Min Huang
Nat. Hazards Earth Syst. Sci., 23, 2649–2662, https://doi.org/10.5194/nhess-23-2649-2023, https://doi.org/10.5194/nhess-23-2649-2023, 2023
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Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.
Li-Ru Luo, Zhi-Xiang Yu, Qi Wang, Li-Jun Zhang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-136, https://doi.org/10.5194/nhess-2023-136, 2023
Revised manuscript accepted for NHESS
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Field investigations were done on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was presumed from UAV survey. A FEM model, including the barrier and rocks, was created to reproduce the damage evolution. It was found that the impact kinetic energy was below the design protection energy. The improper member connections prevent the barrier from producing significant deformation to absorb energy. Damages are avoided by improving the nets’ and ropes’ ability to slide.
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
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We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
Simon Seelig, Thomas Wagner, Karl Krainer, Michael Avian, Marc Olefs, Klaus Haslinger, and Gerfried Winkler
Nat. Hazards Earth Syst. Sci., 23, 2547–2568, https://doi.org/10.5194/nhess-23-2547-2023, https://doi.org/10.5194/nhess-23-2547-2023, 2023
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A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.
Camilla Lanfranconi, Paolo Frattini, Gianluca Sala, Giuseppe Dattola, Davide Bertolo, Juanjuan Sun, and Giovanni Battista Crosta
Nat. Hazards Earth Syst. Sci., 23, 2349–2363, https://doi.org/10.5194/nhess-23-2349-2023, https://doi.org/10.5194/nhess-23-2349-2023, 2023
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This paper presents a study on rockfall dynamics and hazard, examining the impact of the presence of trees along slope and block fragmentation. We compared rockfall simulations that explicitly model the presence of trees and fragmentation with a classical approach that accounts for these phenomena in model parameters (both the hazard and the kinetic energy change). We also used a non-parametric probabilistic rockfall hazard analysis method for hazard mapping.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
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This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
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Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
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In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Elsa S. Culler, Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo
Nat. Hazards Earth Syst. Sci., 23, 1631–1652, https://doi.org/10.5194/nhess-23-1631-2023, https://doi.org/10.5194/nhess-23-1631-2023, 2023
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Landslides have often been observed in the aftermath of wildfires. This study explores regional patterns in the rainfall that caused landslides both after fires and in unburned locations. In general, landslides that occur after fires are triggered by less rainfall, confirming that fire helps to set the stage for landslides. However, there are regional differences in the ways in which fire impacts landslides, such as the size and direction of shifts in the seasonality of landslides after fires.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
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We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Yaspal Sundriyal, Vipin Kumar, Neha Chauhan, Sameeksha Kaushik, Rahul Ranjan, and Mohit Kumar Punia
Nat. Hazards Earth Syst. Sci., 23, 1425–1431, https://doi.org/10.5194/nhess-23-1425-2023, https://doi.org/10.5194/nhess-23-1425-2023, 2023
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The NW Himalaya has been one of the most affected terrains of the Himalaya, subject to disastrous landslides. This article focuses on two towns (Joshimath and Bhatwari) of the NW Himalaya, which have been witnessing subsidence for decades. We used a slope stability simulation to determine the response of the hillslopes accommodating these towns under various loading conditions. We found that the maximum displacement in these hillslopes might reach up to 20–25 m.
Yu Zhuang, Aiguo Xing, Perry Bartelt, Muhammad Bilal, and Zhaowei Ding
Nat. Hazards Earth Syst. Sci., 23, 1257–1266, https://doi.org/10.5194/nhess-23-1257-2023, https://doi.org/10.5194/nhess-23-1257-2023, 2023
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Tree destruction is often used to back calculate the air blast impact region and to estimate the air blast power. Here we established a novel model to assess air blast power using tree destruction information. We find that the dynamic magnification effect makes the trees easier to damage by a landslide-induced air blast, but the large tree deformation would weaken the effect. Bending and overturning are two likely failure modes, which depend heavily on the properties of trees.
Suzanne Lapillonne, Firmin Fontaine, Frédéric Liebault, Vincent Richefeu, and Guillaume Piton
Nat. Hazards Earth Syst. Sci., 23, 1241–1256, https://doi.org/10.5194/nhess-23-1241-2023, https://doi.org/10.5194/nhess-23-1241-2023, 2023
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Debris flows are fast flows most often found in torrential watersheds. They are composed of two phases: a liquid phase which can be mud-like and a granular phase, including large boulders, transported along with the flow. Due to their destructive nature, accessing features of the flow, such as velocity and flow height, is difficult. We present a protocol to analyse debris flow data and results of the Réal torrent in France. These results will help experts in designing models.
Carlos Millán-Arancibia and Waldo Lavado-Casimiro
Nat. Hazards Earth Syst. Sci., 23, 1191–1206, https://doi.org/10.5194/nhess-23-1191-2023, https://doi.org/10.5194/nhess-23-1191-2023, 2023
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This study is the first approximation of regional rainfall thresholds for shallow landslide occurrence in Peru. This research was generated from a gridded precipitation data and landslide inventory. The analysis showed that the threshold based on the combination of mean daily intensity–duration variables gives the best results for separating rainfall events that generate landslides. Through this work the potential of thresholds for landslide monitoring at the regional scale is demonstrated.
Luca Verrucci, Giovanni Forte, Melania De Falco, Paolo Tommasi, Giuseppe Lanzo, Kevin W. Franke, and Antonio Santo
Nat. Hazards Earth Syst. Sci., 23, 1177–1190, https://doi.org/10.5194/nhess-23-1177-2023, https://doi.org/10.5194/nhess-23-1177-2023, 2023
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Stability analyses in static and seismic conditions were performed on four rockslides that occurred during the main shocks of the 2016–2017 central Italy seismic sequence. These results also indicate that specific structural features of the slope must carefully be accounted for in evaluating potential hazards on transportation infrastructures in mountainous regions.
Enner Alcântara, José A. Marengo, José Mantovani, Luciana R. Londe, Rachel Lau Yu San, Edward Park, Yunung Nina Lin, Jingyu Wang, Tatiana Mendes, Ana Paula Cunha, Luana Pampuch, Marcelo Seluchi, Silvio Simões, Luz Adriana Cuartas, Demerval Goncalves, Klécia Massi, Regina Alvalá, Osvaldo Moraes, Carlos Souza Filho, Rodolfo Mendes, and Carlos Nobre
Nat. Hazards Earth Syst. Sci., 23, 1157–1175, https://doi.org/10.5194/nhess-23-1157-2023, https://doi.org/10.5194/nhess-23-1157-2023, 2023
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The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
Joshua N. Jones, Georgina L. Bennett, Claudia Abancó, Mark A. M. Matera, and Fibor J. Tan
Nat. Hazards Earth Syst. Sci., 23, 1095–1115, https://doi.org/10.5194/nhess-23-1095-2023, https://doi.org/10.5194/nhess-23-1095-2023, 2023
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We modelled where landslides occur in the Philippines using landslide data from three typhoon events in 2009, 2018, and 2019. These models show where landslides occurred within the landscape. By comparing the different models, we found that the 2019 landslides were occurring all across the landscape, whereas the 2009 and 2018 landslides were mostly occurring at specific slope angles and aspects. This shows that landslide susceptibility must be considered variable through space and time.
Shalev Siman-Tov and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1079–1093, https://doi.org/10.5194/nhess-23-1079-2023, https://doi.org/10.5194/nhess-23-1079-2023, 2023
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Debris flows represent a threat to infrastructure and the population. In arid areas, they are observed when heavy rainfall hits steep slopes with sediments. Here, we use digital surface models and radar rainfall data to detect and characterize the triggering and non-triggering rainfall conditions. We find that rainfall intensity alone is insufficient to explain the triggering. We suggest that antecedent rainfall could represent a critical factor for debris flow triggering in arid regions.
Xun Huang, Zhijian Zhang, and Guoping Xiang
Nat. Hazards Earth Syst. Sci., 23, 871–889, https://doi.org/10.5194/nhess-23-871-2023, https://doi.org/10.5194/nhess-23-871-2023, 2023
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A sensitivity analysis on the building impact force resulting from the representative built environment parameters is executed through the FLOW-3D model. The surrounding buildings' properties, especially the azimuthal angle, have been confirmed to play significant roles in determining the peak impact forces. The single and combined effects of built environments are analyzed in detail. This will improve understanding of vulnerability assessment and migration design against debris flow hazards.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
EGUsphere, https://doi.org/10.5194/egusphere-2023-28, https://doi.org/10.5194/egusphere-2023-28, 2023
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide. We found that the CSM-HSP combines the advantages of the IRMM model in simulating the actual deformation of slopes with rock bridges and the modeling advantage of the JM model. The research results are helpful to choose an appropriate rock bridge model to simulate the 3D landslide stability and to reveal the influence laws of rock bridges on the 3D stability of landslides.
Jean-Claude Maki Mateso, Charles L. Bielders, Elise Monsieurs, Arthur Depicker, Benoît Smets, Théophile Tambala, Luc Bagalwa Mateso, and Olivier Dewitte
Nat. Hazards Earth Syst. Sci., 23, 643–666, https://doi.org/10.5194/nhess-23-643-2023, https://doi.org/10.5194/nhess-23-643-2023, 2023
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This research highlights the importance of human activities on the occurrence of landslides and the need to consider this context when studying hillslope instability patterns in regions under anthropogenic pressure. Also, this study highlights the importance of considering the timing of landslides and hence the added value of using historical information for compiling an inventory.
Jakob Rom, Florian Haas, Tobias Heckmann, Moritz Altmann, Fabian Fleischer, Camillo Ressl, Sarah Betz-Nutz, and Michael Becht
Nat. Hazards Earth Syst. Sci., 23, 601–622, https://doi.org/10.5194/nhess-23-601-2023, https://doi.org/10.5194/nhess-23-601-2023, 2023
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In this study, an area-wide slope-type debris flow record has been established for Horlachtal, Austria, since 1947 based on historical and recent remote sensing data. Spatial and temporal analyses show variations in debris flow activity in space and time in a high-alpine region. The results can contribute to a better understanding of past slope-type debris flow dynamics in the context of extreme precipitation events and their possible future development.
Tom Birien and Francis Gauthier
Nat. Hazards Earth Syst. Sci., 23, 343–360, https://doi.org/10.5194/nhess-23-343-2023, https://doi.org/10.5194/nhess-23-343-2023, 2023
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On highly fractured rockwalls such as those found in northern Gaspésie, most rockfalls are triggered by weather conditions. This study highlights that in winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0 °C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a mainly dry period. This knowledge could be used to implement a risk management strategy.
Nunziarita Palazzolo, David J. Peres, Enrico Creaco, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci., 23, 279–291, https://doi.org/10.5194/nhess-23-279-2023, https://doi.org/10.5194/nhess-23-279-2023, 2023
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We propose an approach exploiting PCA to derive hydrometeorological landslide-triggering thresholds using multi-layered soil moisture data from ERA5-Land reanalysis. Comparison of thresholds based on single- and multi-layered soil moisture information provides a means to identify the significance of multi-layered data for landslide triggering in a region. In Sicily, the proposed approach yields thresholds with a higher performance than traditional precipitation-based ones (TSS = 0.71 vs. 0.50).
Srikrishnan Siva Subramanian, Piyush Srivastava, Ali Pulpadan Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-297, https://doi.org/10.5194/nhess-2022-297, 2023
Revised manuscript accepted for NHESS
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Rainfall intensity-duration (ID) thresholds can aid in the prediction of natural disasters. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the weather research and forecasting model (WRF) with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Fabian Walter, Elias Hodel, Erik S. Mannerfelt, Kristen Cook, Michael Dietze, Livia Estermann, Michaela Wenner, Daniel Farinotti, Martin Fengler, Lukas Hammerschmidt, Flavia Hänsli, Jacob Hirschberg, Brian McArdell, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 22, 4011–4018, https://doi.org/10.5194/nhess-22-4011-2022, https://doi.org/10.5194/nhess-22-4011-2022, 2022
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Debris flows are dangerous sediment–water mixtures in steep terrain. Their formation takes place in poorly accessible terrain where instrumentation cannot be installed. Here we propose to monitor such source terrain with an autonomous drone for mapping sediments which were left behind by debris flows or may contribute to future events. Short flight intervals elucidate changes of such sediments, providing important information for landscape evolution and the likelihood of future debris flows.
Marc Peruzzetto, Yoann Legendre, Aude Nachbaur, Thomas J. B. Dewez, Yannick Thiery, Clara Levy, and Benoit Vittecoq
Nat. Hazards Earth Syst. Sci., 22, 3973–3992, https://doi.org/10.5194/nhess-22-3973-2022, https://doi.org/10.5194/nhess-22-3973-2022, 2022
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Volcanic edifices result from successive construction and dismantling phases. Thus, the geological units forming volcanoes display complex geometries. We show that such geometries can be reconstructed thanks to aerial views, topographic surveys and photogrammetric models. In our case study of the Samperre cliff (Martinique, Lesser Antilles), it allows us to link destabilizations from a rocky cliff to the existence of a filled paleo-valley and estimate a potentially unstable volume.
Abdellah Khouz, Jorge Trindade, Sérgio C. Oliveira, Fatima El Bchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud
Nat. Hazards Earth Syst. Sci., 22, 3793–3814, https://doi.org/10.5194/nhess-22-3793-2022, https://doi.org/10.5194/nhess-22-3793-2022, 2022
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The aim of this study was to assess the landslide susceptibility of the rocky coast of Essaouira using the information value model. The resulting susceptibility maps could be used for both environmental protection and general planning of future development activities.
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764, https://doi.org/10.5194/nhess-22-3751-2022, https://doi.org/10.5194/nhess-22-3751-2022, 2022
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The landslide hazard models assist in mitigating losses due to landslides. However, these models depend on landslide databases, which often have missing triggering information, rendering these databases unusable for landslide hazard models. In this work, we developed a Python library, Landsifier, consisting of three different methods to identify the triggers of landslides. These methods can classify landslide triggers with high accuracy using only a landslide polygon shapefile as an input.
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700, https://doi.org/10.5194/nhess-22-3679-2022, https://doi.org/10.5194/nhess-22-3679-2022, 2022
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Landslides and flash floods are rainfall-induced processes that often co-occur and interact, generally very quickly. In mountainous cloud-covered environments, determining when these processes occur remains challenging. We propose a regional methodology using open-access satellite radar images that allow for the timing of landslide and flash floods events, in the contrasting landscapes of tropical Africa, with an accuracy of up to a few days. The methodology shows potential for transferability.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022, https://doi.org/10.5194/nhess-22-3641-2022, 2022
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This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci., 22, 3361–3384, https://doi.org/10.5194/nhess-22-3361-2022, https://doi.org/10.5194/nhess-22-3361-2022, 2022
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We present a new landslide inventory for the 2021, M 7.2, Haiti, earthquake. We compare characteristics of this inventory with those of the 2010 seismically induced landslides, highlighting the much larger total area of 2021 landslides. This fact could be related to the larger earthquake magnitude in 2021, to the more central location of the fault segment ruptured in 2021 with respect to coastal zones, and/or to possible climatic preconditioning of slope failures in the 2021 affected area.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022, https://doi.org/10.5194/nhess-22-3309-2022, 2022
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On 7 February 2021, a large rock–ice avalanche occurred in Chamoli, Indian Himalaya. The resulting debris flow swept down the nearby valley, leaving over 200 people dead or missing. We use a range of satellite datasets to investigate how the collapse area changed prior to collapse. We show that signs of instability were visible as early 5 years prior to collapse. However, it would likely not have been possible to predict the timing of the event from current satellite datasets.
Bastian van den Bout, Chenxiao Tang, Cees van Westen, and Victor Jetten
Nat. Hazards Earth Syst. Sci., 22, 3183–3209, https://doi.org/10.5194/nhess-22-3183-2022, https://doi.org/10.5194/nhess-22-3183-2022, 2022
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Natural hazards such as earthquakes, landslides, and flooding do not always occur as stand-alone events. After the 2008 Wenchuan earthquake, a co-seismic landslide blocked a stream in Hongchun. Two years later, a debris flow breached the material, blocked the Min River, and resulted in flooding of a small town. We developed a multi-process model that captures the full cascade. Despite input and process uncertainties, probability of flooding was high due to topography and trigger intensities.
Lucas Pelascini, Philippe Steer, Maxime Mouyen, and Laurent Longuevergne
Nat. Hazards Earth Syst. Sci., 22, 3125–3141, https://doi.org/10.5194/nhess-22-3125-2022, https://doi.org/10.5194/nhess-22-3125-2022, 2022
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Landslides represent a major natural hazard and are often triggered by typhoons. We present a new 2D model computing the respective role of rainfall infiltration, atmospheric depression and groundwater in slope stability during typhoons. The results show rainfall is the strongest factor of destabilisation. However, if the slope is fully saturated, near the toe of the slope or during the wet season, rainfall infiltration is limited and atmospheric pressure change can become the dominant factor.
Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 22, 3063–3082, https://doi.org/10.5194/nhess-22-3063-2022, https://doi.org/10.5194/nhess-22-3063-2022, 2022
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In this study we assessed global landslide susceptibility at the coarse 36 km spatial resolution of global satellite soil moisture observations to prepare for a subsequent combination of the two. Specifically, we focus therefore on the susceptibility of hydrologically triggered landslides. We introduce ensemble techniques, common in, for example, meteorology but not yet in the landslide community, to retrieve reliable estimates of the total prediction uncertainty.
Txomin Bornaetxea, Ivan Marchesini, Sumit Kumar, Rabisankar Karmakar, and Alessandro Mondini
Nat. Hazards Earth Syst. Sci., 22, 2929–2941, https://doi.org/10.5194/nhess-22-2929-2022, https://doi.org/10.5194/nhess-22-2929-2022, 2022
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One cannot know if there is a landslide or not in an area that one has not observed. This is an obvious statement, but when landslide inventories are obtained by field observation, this fact is seldom taken into account. Since fieldwork campaigns are often done following the roads, we present a methodology to estimate the visibility of the terrain from the roads, and we demonstrate that fieldwork-based inventories are underestimating landslide density in less visible areas.
Katy Burrows, Odin Marc, and Dominique Remy
Nat. Hazards Earth Syst. Sci., 22, 2637–2653, https://doi.org/10.5194/nhess-22-2637-2022, https://doi.org/10.5194/nhess-22-2637-2022, 2022
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The locations of triggered landslides following a rainfall event can be identified in optical satellite images. However cloud cover associated with the rainfall means that these images cannot be used to identify landslide timing. Timings of landslides triggered during long rainfall events are often unknown. Here we present methods of using Sentinel-1 satellite radar data, acquired every 12 d globally in all weather conditions, to better constrain the timings of rainfall-triggered landslides.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635, https://doi.org/10.5194/nhess-22-2611-2022, https://doi.org/10.5194/nhess-22-2611-2022, 2022
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Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Chuxuan Li, Alexander L. Handwerger, Jiali Wang, Wei Yu, Xiang Li, Noah J. Finnegan, Yingying Xie, Giuseppe Buscarnera, and Daniel E. Horton
Nat. Hazards Earth Syst. Sci., 22, 2317–2345, https://doi.org/10.5194/nhess-22-2317-2022, https://doi.org/10.5194/nhess-22-2317-2022, 2022
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In January 2021 a storm triggered numerous debris flows in a wildfire burn scar in California. We use a hydrologic model to assess debris flow susceptibility in pre-fire and postfire scenarios. Compared to pre-fire conditions, postfire conditions yield dramatic increases in peak water discharge, substantially increasing debris flow susceptibility. Our work highlights the hydrologic model's utility in investigating and potentially forecasting postfire debris flows at regional scales.
Saskia de Vilder, Chris Massey, Biljana Lukovic, Tony Taig, and Regine Morgenstern
Nat. Hazards Earth Syst. Sci., 22, 2289–2316, https://doi.org/10.5194/nhess-22-2289-2022, https://doi.org/10.5194/nhess-22-2289-2022, 2022
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This study calculates the fatality risk posed by landslides while visiting Franz Josef Glacier and Fox Glacier valleys, New Zealand, for nine different scenarios, where the variables of the risk equation were adjusted to determine the range in risk values and associated uncertainty. The results show that it is important to consider variable inputs that change through time, such as the increasing probability of an earthquake and the impact of climate change on landslide characteristics.
Yiwei Zhang, Jianping Chen, Qing Wang, Chun Tan, Yongchao Li, Xiaohui Sun, and Yang Li
Nat. Hazards Earth Syst. Sci., 22, 2239–2255, https://doi.org/10.5194/nhess-22-2239-2022, https://doi.org/10.5194/nhess-22-2239-2022, 2022
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The disaster prevention and mitigation of debris flow is a very important scientific problem. Our model is based on geographic information system (GIS), combined with grey relational, data-driven and fuzzy logic methods. Through our results, we believe that the streamlining of factors and scientific classification should attract attention from other researchers to optimize a model. We also propose a good perspective to make better use of the watershed feature parameters.
Cited articles
Amt der Steiermärkischen Landesregierung: Regionale Bevölkerungsprognose, Steiermark – Bundesland, Bezirke und Gemeindegruppen, Steirische Statistiken, Heft 3, Abteilung 17 Landes- und Regionalentwicklung, Referat Statistik und Geoinformation, Graz, Austria,
https://www.landesentwicklung.steiermark.at/cms/dokumente/12658765_141979497/b6924e0e/Heft%203-2020%20Bev%C3%B6lkerungsprognose%20aktuell.pdf,
(last access: 20 May 2022), 2020. a
Bastola, S., Murphy, C., and Sweeney, J.: The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments, Adv. Water Resour., 34, 562–576, https://doi.org/10.1016/j.advwatres.2011.01.008, 2011. a, b
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales, Q. J. Roy. Meteorol. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008 (data available at: https://www.ecmwf.int/en/forecasts/datasets, last access: 20 May 2022). a, b
BFW: Interim evaluation of the Austrian Forest Inventory 2016/18 – Styria [Zwischenauswertung der ÖWI 2016/18 – Steiermark], Tech. rep., Austrian Reseach Centre for Forests, Vienna, Austria, https://www.bfw.gv.at/wp-content/uploads/Steiermark_OEWI_16_18.pdf (last access: 20 May 2022), 2019. a
Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, 2018. a
Brenning, A., Schwinn, M., Ruiz-Páez, A. P., and Muenchow, J.: Landslide susceptibility near highways is increased by 1 order of magnitude in the Andes of southern Ecuador, Loja province, Nat. Hazards Earth Syst. Sci., 15, 45–57, https://doi.org/10.5194/nhess-15-45-2015, 2015. a
Brock, J., Schratz, P., Petschko, H., Muenchow, J., Micu, M., and Brenning, A.: The Performance of Landslide Susceptibility Models Critically Depends on the Quality of Digital Elevations Models, Geomat. Nat. Haz. Risk, 11, 1075–1092, https://doi.org/10.1080/19475705.2020.1776403, 2020. a
Chen, D., Rojas, M., Samset, B. H., Cobb, K., Diongue-Niang, A., Edwards, P., Emori, S., Faria, S. H., Hawkins, E., Hope, P., Huybrechts, P., Meinshausen, M., Mustafa, S. K., Plattner, G.-K., and Tréguier, A. M.: Framing, context, and methods, in: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, Ö., Yu, R., and Zhou, B., Cambridge University Press, https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter01.pdf (last access: 20 May 2022), 2021. a
Chen, F., Manning, K. W., LeMone, M. A., Trier, S. B., Alfieri, J. G., Roberts, R., Tewari, M., Niyogi, D., Horst, T. W., Oncley, S. P., Basara, J. B., and Blanken, P. D.: Description and Evaluation of the Characteristics of the NCAR High-Resolution Land Data Assimilation System, J. Appl. Meteorol. Clim., 46, 694–713, https://doi.org/10.1175/JAM2463.1, 2007. a
Crozier, M. J.: Deciphering the effect of climate change on landslide activity: A review, Geomorphology, 124, 260–267, https://doi.org/10.1016/j.geomorph.2010.04.009, 2010. a
Cruden, D. M. and Varnes, D. J.: Landslide Types and Processes, in: Landslides investigation and mitigation, edited by: Turner, A. and Schuster, R., Transportation research board, Special Report 247, 36–75, 1996. a
Debele, S. E., Kumar, P., Sahani, J., Marti-Cardona, B., Mickovski, S. B., Leo, L. S., Porcù, F., Bertini, F., Montesi, D., Vojinovic, Z., and Di Sabatino, S.: Nature-based solutions for hydro-meteorological hazards: Revised concepts, classification schemes and databases, Environ. Res., 179,
108799, https://doi.org/10.1016/j.envres.2019.108799, 2019. a, b
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim Reanalysis: Configuration and Performance of the Data
Assimilation System, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Doblas-Reyes, F. J., Sörensson, A. A., Almazroui, M., Dosio, A., Gutowski, W. J., Haarsma, R., Hamdi, R., Hewitson, B., Kwon, W.-T., Lamptey, B. L., Maraun, D., Stephenson, T. S., Takayabu, I., Terray, L., Turner, A., and Zuo,
Z.: Linking global to regional climate change, in: Climate Change 2021:
The Physical Science Basis. Contribution of Working Group I
to the Sixth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by Masson-Delmotte, V., Zhai, P., Pirani, A.,
Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L.,
Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R.,
Maycock, T. K., Waterfield, T., Yelekçi, Ö., Yu, R., and Zhou, B.,
Cambridge University Press, 2021. a, b
EPA, U.: Guidelines for Human Exposure Assessment, EPA/100/B-19/001, Risk Assessment Forum, U.S. Environmental Protection Agency, Washington, DC, USA,
https://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=429103 (last access: 20 May 2022), 2019. a
Fahrmeir, L., Kneib, T., Lang, S., and Marx, B.: Regression: Models, Methods and Applications, Springer-Verlag, Berlin Heidelberg, https://doi.org/10.1007/978-3-642-34333-9, 2013. a
Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., and Savage, W. Z.: Guidelines for landslide susceptibility, hazard and risk zoning for land use planning, Eng. Geol., 102, 85–98, https://doi.org/10.1016/j.enggeo.2008.03.022, 2008. a
Felsberg, A., Poesen, J., Bechtold, M., Vanmaercke, M., and De Lannoy, G. J. M.: Estimating global landslide susceptibility and its uncertainty through ensemble modeling, Nat. Hazards Earth Syst. Sci., 22, 3063–3082, https://doi.org/10.5194/nhess-22-3063-2022, 2022. a
Froude, M. J. and Petley, D. N.: Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018. a
Gariano, S. L. and Guzzetti, F.: Landslides in a changing climate, Earth-Sci. Rev., 162, 227–252, https://doi.org/10.1016/j.earscirev.2016.08.011, 2016. a, b
Gariano, S. L. and Guzzetti, F.: 5.32 – Mass-Movements and Climate Change, in: Treatise on Geomorphology, 2nd edn., edited by: Shroder, J. F., Academic Press, Oxford, 546–558, https://doi.org/10.1016/B978-0-12-818234-5.00043-2, 2022. a, b
Gariano, S. L., Rianna, G., Petrucci, O., and Guzzetti, F.: Assessing future changes in the occurrence of rainfall-induced landslides at a regional scale, Sci. Total Environ., 596–597, 417–426, https://doi.org/10.1016/j.scitotenv.2017.03.103, 2017. a, b, c
Gariano, S. L., Petrucci, O., Rianna, G., Santini, M., and Guzzetti, F.: Impacts of past and future land changes on landslides in southern Italy, Reg. Environ. Change, 18, 437–449, https://doi.org/10.1007/s10113-017-1210-9, 2018. a
Haiden, T.: Meteorologische Analyse des Niederschlags von 22.-25. Juni 2009 [Meteorological analysis of the precipitation from 22 to 25 June 2009], Tech. rep., ZAMG, Vienna, Austria,
http://www.zamg.ac.at/docs/aktuell/2009-06-30_Meteorologische%20Analyse%20HOWA2009.pdf (last access: 20 May 2022), 2009. a
Haiden, T., Kann, A., Wittmann, C., Pistotnik, G., Bica, B., and Gruber, C.:
The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region, Weather Forecast., 26, 166–183, https://doi.org/10.1175/2010WAF2222451.1, 2010 (data available at: https://data.hub.zamg.ac.at, last access: 20 May 2022). a
Haque, U., da Silva, P. F., Devoli, G., Pilz, J., Zhao, B., Khaloua, A., Wilopo, W., Andersen, P., Lu, P., Lee, J., Yamamoto, T., Keellings, D., Wu, J.-H., and Glass, G. E.: The human cost of global warming: Deadly landslides and their triggers (1995–2014), Sci. Total Environ., 682, 673–684, https://doi.org/10.1016/j.scitotenv.2019.03.415, 2019. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 Global Reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020 (data available at: https://www.ecmwf.int/en/forecasts/datasets/browse-reanalysis-datasets, last access: 20 May 2022). a
Holzkämper, A., Klein, T., Seppelt, R., and Fuhrer, J.: Assessing the propagation of uncertainties in multi-objective optimization for agro-ecosystem adaptation to climate change, Environ. Modell. Softw., 66, 27–35, https://doi.org/10.1016/j.envsoft.2014.12.012, 2015. a
Hosmer, D. W., Lemeshow, S., and Sturdivant, R. X.: Applied Logistic Regression, Wiley Series in Probability and Statistics, John Wiley & Sons, Hoboken, NJ, USA, https://doi.org/10.1002/9781118548387, 2013. a
Jaedicke, C., Solheim, A., Blikra, L. H., Stalsberg, K., Sorteberg, A., Aaheim, A., Kronholm, K., Vikhamar-Schuler, D., Isaksen, K., Sletten, K., Kristensen, K., Barstad, I., Melchiorre, C., Høydal, Ø. A., and Mestl, H.: Spatial and temporal variations of Norwegian geohazards in a changing climate, the GeoExtreme Project, Nat. Hazards Earth Syst. Sci., 8, 893–904, https://doi.org/10.5194/nhess-8-893-2008, 2008. a, b
Jaedicke, C., Van Den Eeckhaut, M., Nadim, F., Hervás, J., Kalsnes, B., Vangelsten, B. V., Smith, J. T., Tofani, V., Ciurean, R., Winter, M. G., Sverdrup-Thygeson, K., Syre, E., and Smebye, H.: Identification of Landslide Hazard and Risk 'Hotspots' in Europe, B. Eng. Geol. Environ., 73, 325–339, https://doi.org/10.1007/s10064-013-0541-0, 2014. a
Jandl, R.: Climate-induced challenges of Norway spruce in Northern Austria, Trees, Forests and People, 1, 100008, https://doi.org/10.1016/j.tfp.2020.100008, 2020. a
Jones, J. N., Boulton, S. J., Bennett, G. L., Stokes, M., and Whitworth, M. R. Z.: Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling, J. Geophys. Res.-Earth, 126, e2021JF006067, https://doi.org/10.1029/2021JF006067, 2021. a, b
Kim, H. G., Lee, D. K., Park, C., Ahn, Y., Kil, S.-H., Sung, S., and Biging, G. S.: Estimating landslide susceptibility areas considering the uncertainty inherent in modeling methods, Stoch. Env. Res. Risk A., 32, 2987–3019, https://doi.org/10.1007/s00477-018-1609-y, 2018. a
Kirchner, M., Mitter, H., Schneider, U. A., Sommer, M., Falkner, K., and Schmid, E.: Uncertainty concepts for integrated modeling – Review and application for identifying uncertainties and uncertainty propagation pathways, Environ. Modell. Softw., 135, 104905, https://doi.org/10.1016/j.envsoft.2020.104905, 2021. a, b, c, d, e
Knevels, R., Petschko, H., Proske, H., Leopold, P., Maraun, D., and Brenning, A.: Event-Based Landslide Modeling in the Styrian Basin, Austria: Accounting for Time-Varying Rainfall and Land Cover, Geosciences, 10, 217, https://doi.org/10.3390/geosciences10060217, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t
Knevels, R., Petschko, H., Proske, H., Leopold, P., Maraun, D., and Brenning, A.: Event-based landslide susceptibility models (Styrian Basin, Austria), Version 1.0.0, Zenodo [data set], https://doi.org/10.5281/zenodo.6365228, 2022. a
Kolström, M., Lindner, M., Vilén, T., Maroschek, M., Seidl, R., Lexer, M. J., Netherer, S., Kremer, A., Delzon, S., Barbati, A., Marchetti, M., and Corona,
P.: Reviewing the Science and Implementation of Climate Change Adaptation Measures in European Forestry , Forests, 2, 961–982, https://doi.org/10.3390/f2040961, 2011. a
Landeswarnzentrale Steiermark: Niederschlagswarnung für die Steiermark. Für den Zeitraum: Donnerstag, 11.09.2014 12:00 Uhr MESZ bis Sonntag, 14.09.2014 12:00 Uhr MESZ [Precipitation warning for Styria. For the period: Thursday, 11 September 2014 12:00 CEST to Sunday, 14 September 2014 12:00 CEST], Tech. rep., Fachabteilung Katastrophenschutz und Landesverteidigung, Referat Landeswarnzentrale und Kommunikationstechnik, Graz, Austria, http://www.katastrophenschutz.steiermark.at/cms/beitrag/12083692/5461/ (last access: 20 May 2022), 2014. a
Lee, C.-T.: Landslide trends under extreme climate events, Terr. Atmos. Ocean. Sci., 28, 33–42, https://doi.org/10.3319/TAO.2016.05.28.01(CCA), 2017. a, b, c
Lima, P., Steger, S., and Glade, T.: Counteracting Flawed Landslide Data in Statistically Based Landslide Susceptibility Modelling for Very Large Areas: A National-Scale Assessment for Austria, Landslides, 18, 3531–3546, https://doi.org/10.1007/s10346-021-01693-7, 2021. a
Lombardo, L., Opitz, T., Ardizzone, F., Guzzetti, F., and Huser, R.: Space-time landslide predictive modelling, Earth-Sci. Rev., 209, 103318, https://doi.org/10.1016/j.earscirev.2020.103318, 2020. a
Maraun, D. and Widmann, M.: Statistical Downscaling and Bias Correction for Climate Research, Cambridge University Press, Cambridge, https://doi.org/10.1017/9781107588783, 2018. a
Maraun, D., Shepherd, T. G., Widmann, M., Zappa, G., Walton, D., Gutiérrez, J. M., Hagemann, S., Richter, I., Soares, P. M. M., Hall, A., and Mearns, L. O.: Towards process-informed bias correction of climate change simulations, Nat. Clim. Change, 7, 764–773, https://doi.org/10.1038/nclimate3418, 2017. a
Maraun, D., Knevels, R., Mishra, A. N., Truhetz, H., Bevacqua, E., Proske, H., Zappa, G., Brenning, A., Petschko, H., Schaffer, A., Leopold, P., and Puxley, B. L.: A severe landslide event in the Alpine foreland under possible future climate and land-use changes, Communications Earth & Environment, 3, 1–11, https://doi.org/10.1038/s43247-022-00408-7, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z, aa, ab, ac, ad, ae, af, ag, ah, ai, aj
Marra, G. and Wood, S. N.: Coverage Properties of Confidence Intervals for Generalized Additive Model Components, Scand. J. Stat., 39, 53–74, https://doi.org/10.1111/j.1467-9469.2011.00760.x, 2012. a
Olefs, M., Formayer, H., Gobiet, A., Marke, T., Schöner, W., and Revesz, M.: Past and future changes of the Austrian climate – Importance for tourism, Journal of Outdoor Recreation and Tourism, 34, 100395, https://doi.org/10.1016/j.jort.2021.100395, 2021. a, b
Ozturk, U., Pittore, M., Behling, R., Roessner, S., Andreani, L., and Korup, O.: How Robust Are Landslide Susceptibility Estimates?, Landslides, 18, 681–695, https://doi.org/10.1007/s10346-020-01485-5, 2021. a, b, c
Picarelli, L., Comegna, L., Gariano, S. L., Guzzetti, F., Mercogliano, P., Rianna, G., Santini, M., and Tommasi, P.: Potential climate changes in Italy and consequences for land stability, in: Slope Safety Preparedness for Impact of Climate Change, CRC Press, 47 pp., https://doi.org/10.1201/9781315387789, 2017. a
Pisano, L., Zumpano, V., Malek, Ž., Rosskopf, C. M., and Parise, M.: Variations in the susceptibility to landslides, as a consequence of land cover changes: A look to the past, and another towards the future, Sci. Total Environ., 601–602, 1147–1159, https://doi.org/10.1016/j.scitotenv.2017.05.231, 2017. a
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria,
https://www.R-project.org/ (last access: 20 May 2022), 2021. a
Refsgaard, J., Sonnenborg, T., Butts, M., Christensen, J., Christensen, S., Drews, M., Jensen, K., Jørgensen, F., Jørgensen, L., Larsen, M., Rasmussen, S., Seaby, L., Seifert, D., and Vilhelmsen, T.: Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?, Hydrolog. Sci. J., 61, 2312–2324, https://doi.org/10.1080/02626667.2015.1131899, 2016. a, b, c, d, e
Reichenbach, P., Busca, C., Mondini, A. C., and Rossi, M.: The Influence of Land Use Change on Landslide Susceptibility Zonation: The Briga Catchment Test Site (Messina, Italy), Environ. Manage., 54, 1372–1384, https://doi.org/10.1007/s00267-014-0357-0, 2014. a
Rianna, G., Comegna, L., Mercogliano, P., and Picarelli, L.: Potential effects of climate changes on soil–atmosphere interaction and landslide hazard, Nat. Hazards, 84, 1487–1499, https://doi.org/10.1007/s11069-016-2481-z, 2016. a
Rianna, G., Comegna, L., Gariano, S. L., Guzzetti, F., Mercogliano, P., Picarelli, L., and Tommasi, P.: Potential Effects of Climate Changes on Landslide Activity in Different Geomorphological Contexts, in: Advancing Culture of Living with Landslides, edited by: Mikoš, M., Casagli, N., Yin, Y., and Sassa, K., Springer International Publishing, Cham, 243–249, https://doi.org/10.1007/978-3-319-53485-5_28, 2017. a, b, c
Roberts, D. R., Wood, W. H., and Marshall, S. J.: Assessments of Downscaled Climate Data with a High-Resolution Weather Station Network Reveal Consistent but Predictable Bias, Int. J. Climatol., 39, 3091–3103, https://doi.org/10.1002/joc.6005, 2019. a
Roberts, G. O., Gelman, A., and Gilks, W. R.: Weak convergence and optimal scaling of random walk Metropolis algorithms, Ann. Appl. Probab., 7, 110–120, https://doi.org/10.1214/aoap/1034625254, 1997. a, b
Rockel, B., Will, A., and Hense, A.: The Regional Climate Model COSMO-CLM (CCLM), Meteorol. Z., 17, 347–348, https://doi.org/10.1127/0941-2948/2008/0309, 2008. a
Rougier, J.: Quantifying hazard losses, in: Risk and Uncertainty Assessment
for Natural Hazards, edited by: Rougier, J., Hill, L. J., and Sparks, S., Cambridge University Press, Cambridge, 19–39, https://doi.org/10.1017/CBO9781139047562.003, 2013. a
Rougier, J. and Beven, K.: Model and data limitations: the sources and implications of epistemic uncertainty, in: Risk and Uncertainty Assessment for Natural Hazards, edited by: Rougier, J., Hill, L. J., and Sparks, S., Cambridge University Press, Cambridge, 40–63, https://doi.org/10.1017/CBO9781139047562.004, 2013. a, b
Rougier, J., Sparks, S., and Hill, L. J. (Eds.): Risk and Uncertainty Assessment for Natural Hazards, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781139047562, 2013. a
Roy, C. J. and Oberkampf, W. L.: A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing, Comput. Method. Appl. M., 200, 2131–2144, https://doi.org/10.1016/j.cma.2011.03.016, 2011. a, b, c, d
Ruppert, D., Wand, M. P., and Carroll, R. J.: Semiparametric Regression, Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9780511755453, 2003. a
Samia, J., Temme, A., Bregt, A., Wallinga, J., Guzzetti, F., Ardizzone, F., and Rossi, M.: Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory, Landslides, 14, 547–558, https://doi.org/10.1007/s10346-016-0739-x, 2017. a
Schaffer, A.: Evaluation of the Soil Moisture-Precipitation Feedback in Austria [Beurteilung des Bodenfeuchte-Niederschlag-Feedbacks in Österreich], Master's thesis, Graz University of Technology, Graz, Austria, https://online.tugraz.at/tug_online/wbabs.showThesis?pThesisNr=73261&pOrgNr=37 (last access: 20 May 2022), 2021. a, b
Schlögel, R., Kofler, C., Gariano, S. L., Van Campenhout, J., and Plummer, S.: Changes in climate patterns and their association to natural hazard distribution in South Tyrol (Eastern Italian Alps), Scientific Reports, 10, 5022, https://doi.org/10.1038/s41598-020-61615-w, 2020. a, b
Schweigl, J. and Hervás, J.: Landslide mapping in Austria, JRC Scientific and Technical Reports EUR 23785 EN, European Commission, Joint Research Centre, Luxembourg, https://doi.org/10.2788/85150, 2009. a
Shepherd, T. G.: Atmospheric circulation as a source of uncertainty in climate change projections, Nat. Geosci., 7, 703–708, https://doi.org/10.1038/ngeo2253, 2014. a
Shepherd, T. G., Boyd, E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West, I. M., Fowler, H. J., James, R., Maraun, D., Martius, O., Senior, C. A., Sobel, A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., van den Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., and Zenghelis, D. A.: Storylines: an alternative approach to representing uncertainty in physical aspects of climate change, Clim. Change, 151, 555–571, https://doi.org/10.1007/s10584-018-2317-9, 2018. a, b
Stainforth, D., Allen, M., Tredger, E., and Smith, L.: Confidence, uncertainty and decision-support relevance in climate predictions, Philos. T. Roy. Soc. A, 365, 2145–2161, https://doi.org/10.1098/rsta.2007.2074, 2007. a
Steger, S., Brenning, A., Bell, R., and Glade, T.: The propagation of inventory-based positional errors into statistical landslide susceptibility models, Nat. Hazards Earth Syst. Sci., 16, 2729–2745, https://doi.org/10.5194/nhess-16-2729-2016, 2016. a
Steger, S., Brenning, A., Bell, R., and Glade, T.: The influence of systematically incomplete shallow landslide inventories on statistical susceptibility models and suggestions for improvements, Landslides, 14, 1767–1781, https://doi.org/10.1007/s10346-017-0820-0, 2017. a
Szumilas, M.: Explaining Odds Ratios, Journal of the Canadian Academy of
Child and Adolescent Psychiatry, 19, 227–229,
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2938757/ (last access: 20 May 2022), 2010. a
Tang, A. M., Hughes, P. N., Dijkstra, T. A., Askarinejad, A., Brenčič, M., Cui, Y. J., Diez, J. J., Firgi, T., Gajewska, B., Gentile, F., Grossi, G., Jommi, C., Kehagia, F., Koda, E., ter Maat, H. W., Lenart, S., Lourenco, S., Oliveira, M., Osinski, P., Springman, S. M., Stirling, R., Toll, D. G., and
Van Beek, V.: Atmosphere–vegetation–soil interactions in a climate change context; impact of changing conditions on engineered transport infrastructure slopes in Europe, Q. J. Eng. Geol. Hydroge., 51, 156–168, https://doi.org/10.1144/qjegh2017-103, 2018. a
Torizin, J., Fuchs, M., Kuhn, D., Balzer, D., and Wang, L.: Practical Accounting for Uncertainties in Data-Driven Landslide Susceptibility Models. Examples from the Lanzhou Case Study, in: Understanding and Reducing Landslide Disaster Risk: Volume 2 From Mapping to Hazard and Risk Zonation, edited by: Guzzetti, F., Mihalić Arbanas, S., Reichenbach, P., Sassa, K., Bobrowsky, P. T., and Takara, K., ICL Contribution to Landslide Disaster Risk Reduction, Springer International Publishing, Cham, 249–255, https://doi.org/10.1007/978-3-030-60227-7_27, 2021. a, b
Valeriano, K. L., Lachos, V. H., and Matos, L. A.: StempCens: Spatio-temporal estimation and prediction for censored/missing responses, R Foundation for Statistical Computing, https://CRAN.R-project.org/package=StempCens (last access: 20 May 2022), 2020.
a
Walker, W., Harremoës, P., Rotmans, J., van der Sluijs, J., van Asselt, M., Janssen, P., and Krayer von Krauss, M.: Defining Uncertainty: A Conceptual Basis for Uncertainty Management in Model-Based Decision Support, Integrated Assessment, 4, 5–17, https://doi.org/10.1076/iaij.4.1.5.16466, 2003. a
Wallemacq, P., House, R., and McLean, D.: Economic Losses, Poverty & Disasters: 1998–2017, Tech. rep., Centre for Research on the Epidemiology of Disaster, UN Office for Disaster Risk Reductions, https://www.cred.be/sites/default/files/CRED_Economic_Losses_10oct.pdf (last access: 20 May 2022), 2018. a
Wood, S. N.: Core Statistics, Institute of Mathematical Statistics Textbooks, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781107741973, 2015. a, b, c, d
ZAMG: Meldungen zu Unwetter und Witterungsbedingten Schäden in der Wirtschaft / September 2014 [Reports on severe weather and weather-related losses in the economy / September 2014], ZAMG, Tech. rep., https://www.zamg.ac.at/zamgWeb/klima/klimarueckblick/archive/2014/09/unwetter09-14.pdf (last access: 20 May 2022), 2014. a, b
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D., Maraun, D., Ramos, A. M., Ridder, N. N., Thiery, W., and Vignotto, E.: A typology of compound weather and climate events, Nature Reviews Earth & Environment, 1, 333–347, https://doi.org/10.1038/s43017-020-0060-z, 2020. a, b
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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