Articles | Volume 21, issue 9
https://doi.org/10.5194/nhess-21-2773-2021
© Author(s) 2021. 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-21-2773-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Sep 2021
Research article |
| 10 Sep 2021
| 10 Sep 2021
Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment
Mountain Hydrology and Mass Movements, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
Alexandre Badoux
Mountain Hydrology and Mass Movements, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
Brian W. McArdell
Mountain Hydrology and Mass Movements, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
Elena Leonarduzzi
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
Mountain Hydrology and Mass Movements, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
Peter Molnar
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
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Virginia Ruiz-Villanueva, Alexandre Badoux, Dieter Rickenmann, Martin Böckli, Salome Schläfli, Nicolas Steeb, Markus Stoffel, and Christian Rickli
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Anna Costa, Peter Molnar, Laura Stutenbecker, Maarten Bakker, Tiago A. Silva, Fritz Schlunegger, Stuart N. Lane, Jean-Luc Loizeau, and Stéphanie Girardclos
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Albrecht von Boetticher, Jens M. Turowski, Brian W. McArdell, Dieter Rickenmann, Marcel Hürlimann, Christian Scheidl, and James W. Kirchner
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Anna Costa, Daniela Anghileri, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-419, https://doi.org/10.5194/hess-2017-419, 2017
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Fabian Walter, Arnaud Burtin, Brian W. McArdell, Niels Hovius, Bianca Weder, and Jens M. Turowski
Nat. Hazards Earth Syst. Sci., 17, 939–955, https://doi.org/10.5194/nhess-17-939-2017, https://doi.org/10.5194/nhess-17-939-2017, 2017
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Florian Frank, Brian W. McArdell, Nicole Oggier, Patrick Baer, Marc Christen, and Andreas Vieli
Nat. Hazards Earth Syst. Sci., 17, 801–815, https://doi.org/10.5194/nhess-17-801-2017, https://doi.org/10.5194/nhess-17-801-2017, 2017
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Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
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Hydrol. Earth Syst. Sci., 21, 1359–1380, https://doi.org/10.5194/hess-21-1359-2017, https://doi.org/10.5194/hess-21-1359-2017, 2017
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Alexandre Badoux, Norina Andres, Frank Techel, and Christoph Hegg
Nat. Hazards Earth Syst. Sci., 16, 2747–2768, https://doi.org/10.5194/nhess-16-2747-2016, https://doi.org/10.5194/nhess-16-2747-2016, 2016
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A database of fatalities caused by natural hazards in Switzerland was compiled for the period from 1946 to 2015: in 70 years, 635 events occurred causing 1023 fatalities. The most common causes of death were snow avalanches (37 %), followed by lightning (16 %), floods (12 %), windstorms (10 %), rockfalls (8 %) and landslides (7 %). The annual number of victims showed a distinct decrease over time. In comparison to other countries, the natural hazard mortality rate in Switzerland is quite low.
Claudio I. Meier, Jorge Sebastián Moraga, Geri Pranzini, and Peter Molnar
Hydrol. Earth Syst. Sci., 20, 4177–4190, https://doi.org/10.5194/hess-20-4177-2016, https://doi.org/10.5194/hess-20-4177-2016, 2016
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We show that the derived distribution approach is able to characterize the interannual variability of precipitation much better than fitting a probabilistic model to annual rainfall totals, as long as continuously gauged data are available. The method is a useful tool for describing temporal changes in the distribution of annual rainfall, as it works for records as short as 5 years, and therefore does not require any stationarity assumption over long periods.
Bahareh Kianfar, Simone Fatichi, Athansios Paschalis, Max Maurer, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-536, https://doi.org/10.5194/hess-2016-536, 2016
Revised manuscript has not been submitted
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Raingauge observations show a large variability in extreme rainfall depths in the current climate. Climate model predictions of extreme rainfall in the future have to be compared with this natural variability. Our work shows that predictions of future extreme rainfall often lie within the range of natural variability of present-day climate, and therefore predictions of change are highly uncertain. We demonstrate this by using stochastic rainfall models and 10-min rainfall data in Switzerland.
Albrecht von Boetticher, Jens M. Turowski, Brian W. McArdell, Dieter Rickenmann, and James W. Kirchner
Geosci. Model Dev., 9, 2909–2923, https://doi.org/10.5194/gmd-9-2909-2016, https://doi.org/10.5194/gmd-9-2909-2016, 2016
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Debris flows are characterized by unsteady flows of water with different content of clay, silt, sand, gravel, and large particles, resulting in a dense moving mixture mass. Here we present a three-dimensional fluid dynamic solver that simulates the flow as a mixture of a pressure-dependent rheology model of the gravel mixed with a Herschel–Bulkley rheology of the fine material suspension. We link rheological parameters to the material composition. The user must specify two free model parameters.
Matteo Saletti, Peter Molnar, Marwan A. Hassan, and Paolo Burlando
Earth Surf. Dynam., 4, 549–566, https://doi.org/10.5194/esurf-4-549-2016, https://doi.org/10.5194/esurf-4-549-2016, 2016
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This study presents a new reduced-complexity model with few parameters linked to basic physical processes, which aims to reproduce the transport of sediment as bed load and the formation and stability of channel morphology in steep mountain streams. The model is able to simulate the formation and stability of steps, bed structures commonly encountered in steep channels, by assuming that their formation is due to intense sediment transport during high flows causing jamming of particles.
F. Frank, B. W. McArdell, C. Huggel, and A. Vieli
Nat. Hazards Earth Syst. Sci., 15, 2569–2583, https://doi.org/10.5194/nhess-15-2569-2015, https://doi.org/10.5194/nhess-15-2569-2015, 2015
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The sudden onset of large and erosive debris flows has been observed recently in different catchments in Switzerland, implicating the importance of erosion for debris flow modelling. Therefore, an erosion model was established based on field data (relationship between maximum shear stress and erosion depth and rate) of several debris flows measured at the Illgraben. Erosion model tests at the Spreitgraben showed considerable improvements in runout pattern as well as hydrograph propagation.
J. C. Peña, L. Schulte, A. Badoux, M. Barriendos, and A. Barrera-Escoda
Hydrol. Earth Syst. Sci., 19, 3807–3827, https://doi.org/10.5194/hess-19-3807-2015, https://doi.org/10.5194/hess-19-3807-2015, 2015
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A. von Boetticher, J. M. Turowski, B. W. McArdell, D. Rickenmann, M. Hürlimann, C. Scheidl, and J. W. Kirchner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-6379-2015, https://doi.org/10.5194/gmdd-8-6379-2015, 2015
Preprint withdrawn
M. Jochner, J. M. Turowski, A. Badoux, M. Stoffel, and C. Rickli
Earth Surf. Dynam., 3, 311–320, https://doi.org/10.5194/esurf-3-311-2015, https://doi.org/10.5194/esurf-3-311-2015, 2015
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The export of coarse particulate organic matter (CPOM) from mountain catchments seems to be strongly linked to rising discharge, but the mechanism leading to this is unclear. We show that log jams in a steep headwater stream are an effective barrier for CPOM export. Exceptional discharge events play a dual role: First, they destroy existing jams, releasing stored material. Second, they intensify channel--hillslope coupling, thereby recruiting logs to the channel, around which new jams can form.
K. Schraml, B. Thomschitz, B. W. McArdell, C. Graf, and R. Kaitna
Nat. Hazards Earth Syst. Sci., 15, 1483–1492, https://doi.org/10.5194/nhess-15-1483-2015, https://doi.org/10.5194/nhess-15-1483-2015, 2015
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In this paper we used two different numerical simulation models to replicate two debris-flow events in Austria and compare the range and sensitivity of the model input parameters. We expect that our results contribute to a better application of simulation models for hazard and risk assessment in alpine regions.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
M. Stähli, M. Sättele, C. Huggel, B. W. McArdell, P. Lehmann, A. Van Herwijnen, A. Berne, M. Schleiss, A. Ferrari, A. Kos, D. Or, and S. M. Springman
Nat. Hazards Earth Syst. Sci., 15, 905–917, https://doi.org/10.5194/nhess-15-905-2015, https://doi.org/10.5194/nhess-15-905-2015, 2015
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This review paper describes the state of the art in monitoring and predicting rapid mass movements for early warning. It further presents recent innovations in observation technologies and modelling to be used in future early warning systems (EWS). Finally, the paper proposes avenues towards successful implementation of next-generation EWS.
P. Molnar, S. Fatichi, L. Gaál, J. Szolgay, and P. Burlando
Hydrol. Earth Syst. Sci., 19, 1753–1766, https://doi.org/10.5194/hess-19-1753-2015, https://doi.org/10.5194/hess-19-1753-2015, 2015
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We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.
K. Džubáková, P. Molnar, K. Schindler, and M. Trizna
Hydrol. Earth Syst. Sci., 19, 195–208, https://doi.org/10.5194/hess-19-195-2015, https://doi.org/10.5194/hess-19-195-2015, 2015
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We use a high-resolution ground-based camera system with near-infrared sensitivity to quantify the response of riparian vegetation in an Alpine river to floods with the use of vegetation indices. The vegetation showed both damage and enhancement within 1 week following floods, with a selective impact determined by pre-flood vegetation vigour, morphological setting and intensity of flood forcing. The tested vegetation indices differed in the direction of predicted change in the range 0.7-35.8%.
F. U. M. Heimann, D. Rickenmann, M. Böckli, A. Badoux, J. M. Turowski, and J. W. Kirchner
Earth Surf. Dynam., 3, 35–54, https://doi.org/10.5194/esurf-3-35-2015, https://doi.org/10.5194/esurf-3-35-2015, 2015
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
L. Gaál, P. Molnar, and J. Szolgay
Hydrol. Earth Syst. Sci., 18, 1561–1573, https://doi.org/10.5194/hess-18-1561-2014, https://doi.org/10.5194/hess-18-1561-2014, 2014
A. Badoux, N. Andres, and J. M. Turowski
Nat. Hazards Earth Syst. Sci., 14, 279–294, https://doi.org/10.5194/nhess-14-279-2014, https://doi.org/10.5194/nhess-14-279-2014, 2014
A. Burtin, N. Hovius, B. W. McArdell, J. M. Turowski, and J. Vergne
Earth Surf. Dynam., 2, 21–33, https://doi.org/10.5194/esurf-2-21-2014, https://doi.org/10.5194/esurf-2-21-2014, 2014
J. M. Turowski, A. Badoux, K. Bunte, C. Rickli, N. Federspiel, and M. Jochner
Earth Surf. Dynam., 1, 1–11, https://doi.org/10.5194/esurf-1-1-2013, https://doi.org/10.5194/esurf-1-1-2013, 2013
Related subject area
Landslides and Debris Flows Hazards
Brief communication: Weak correlation between building damage and loss of life from landslides
Comparative analysis of μ(I) and Voellmy-type grain flow rheologies in geophysical mass flows: insights from theoretical and real case studies
Exploring implications of input parameter uncertainties in glacial lake outburst flood (GLOF) modelling results using the modelling code r.avaflow
From rockfall source area identification to susceptibility zonation: a proposed workflow tested on El Hierro (Canary Islands, Spain)
Brief communication: Visualizing uncertainties in landslide susceptibility modelling using bivariate mapping
Topographic controls on landslide mobility: modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico
Characterizing the scale of regional landslide triggering from storm hydrometeorology
A participatory approach to determine the use of road cut slope design guidelines in Nepal to lessen landslides
An integrated method for assessing vulnerability of buildings caused by debris flows in mountainous areas
Identifying unrecognised risks to life from debris flows
Predicting the thickness of shallow landslides in Switzerland using machine learning
Unraveling landslide failure mechanisms with seismic signal analysis for enhanced pre-survey understanding
The Parraguirre ice-rock avalanche 1987, semi-arid Andes, Chile – A holistic revision
Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models
Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
Limit analysis of earthquake-induced landslides considering two strength envelopes
The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China
Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area
Is higher resolution always better? Open-access DEM comparison for Slope Units delineation and regional landslide prediction
Brief communication: Monitoring impending slope failure with very high-resolution spaceborne synthetic aperture radar
Size scaling of large landslides from incomplete inventories
InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)
Brief Communication: AI-driven rapid landslides mapping following the 2024 Hualien City Earthquake in Taiwan
A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence
More than one landslide per road kilometer – surveying and modeling mass movements along the Rishikesh–Joshimath (NH-7) highway, Uttarakhand, India
Transformations in Exposure to Debris Flows in Post-Earthquake Sichuan, China
Large-scale assessment of rainfall-induced landslide hazard based on hydrometeorological information: application to Partenio Massif (Italy)
Temporal clustering of precipitation for detection of potential landslides
Shallow-landslide stability evaluation in loess areas according to the Revised Infinite Slope Model: a case study of the 7.25 Tianshui sliding-flow landslide events of 2013 in the southwest of the Loess Plateau, China
Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall
Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
Addressing class imbalance in soil movement predictions
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
A regional analysis of paraglacial landslide activation in southern coastal Alaska
Analysis of three-dimensional slope stability combined with rainfall and earthquake
Assessing landslide damming susceptibility in Central Asia
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
Evaluation of debris-flow building damage forecasts
Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA
Morphological characteristics and conditions of drainage basins contributing to the formation of debris flow fans: an examination of regions with different rock strength using decision tree analysis
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
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)
Maximillian Van Wyk de Vries, Alexandre Dunant, Amy L. Johnson, Erin L. Harvey, Sihan Li, Katherine Arrell, Jeevan Baniya, Dipak Basnet, Gopi K. Basyal, Nyima Dorjee Bhotia, Simon J. Dadson, Alexander L. Densmore, Tek Bahadur Dong, Mark E. Kincey, Katie Oven, Anuradha Puri, and Nick J. Rosser
Nat. Hazards Earth Syst. Sci., 25, 1937–1942, https://doi.org/10.5194/nhess-25-1937-2025, https://doi.org/10.5194/nhess-25-1937-2025, 2025
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Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. In this study, we show that there is a poor correlation between building damage and deaths from landslides, such that the deadliest landslides do not always destroy the most buildings and vice versa. This has important implications for our management of landslide risk.
Yu Zhuang, Brian W. McArdell, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 25, 1901–1912, https://doi.org/10.5194/nhess-25-1901-2025, https://doi.org/10.5194/nhess-25-1901-2025, 2025
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The experimentally based μ(I) rheology, widely used for gravitational mass flows, is reinterpreted as a Voellmy-type relationship to highlight its link to grain flow theory. Through block modeling and case studies, we establish its equivalence to μ(R) rheology. μ(I) models shear thinning but fails to capture acceleration and deceleration processes and deposit structure. Incorporating fluctuation energy in μ(R) improves accuracy, refining mass flow modeling and revealing practical challenges.
Sonam Rinzin, Stuart Dunning, Rachel Joanne Carr, Ashim Sattar, and Martin Mergili
Nat. Hazards Earth Syst. Sci., 25, 1841–1864, https://doi.org/10.5194/nhess-25-1841-2025, https://doi.org/10.5194/nhess-25-1841-2025, 2025
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We modelled multiple glacial lake outburst flood (GLOF) scenarios (84 simulations) and tested the effect of nine key input parameters on the modelling results using r.avaflow. Our results highlight that GLOF modelling results are subject to uncertainty from the multiple input parameters. The variation in the volume of mass movement entering the lake causes the highest uncertainty in the modelled GLOF, followed by the DEM dataset and the origin of mass movement.
Roberto Sarro, Mauro Rossi, Paola Reichenbach, and Rosa María Mateos
Nat. Hazards Earth Syst. Sci., 25, 1459–1479, https://doi.org/10.5194/nhess-25-1459-2025, https://doi.org/10.5194/nhess-25-1459-2025, 2025
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This study proposes a novel systematic workflow that integrates source area identification, deterministic runout modelling, the classification of runout outputs to derive susceptibility zonation, and robust procedures for validation and comparison. The proposed approach enables the integration and comparison of different modelling, introducing a robust and consistent workflow/methodology that allows us to derive and verify rockfall susceptibility zonation, considering different steps.
Matthias Schlögl, Anita Graser, Raphael Spiekermann, Jasmin Lampert, and Stefan Steger
Nat. Hazards Earth Syst. Sci., 25, 1425–1437, https://doi.org/10.5194/nhess-25-1425-2025, https://doi.org/10.5194/nhess-25-1425-2025, 2025
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Communicating uncertainties is a crucial yet challenging aspect of spatial modelling – especially in applied research, where results inform decisions. In disaster risk reduction, susceptibility maps for natural hazards guide planning and risk assessment, yet their uncertainties are often overlooked. We present a new type of landslide susceptibility map that visualizes both susceptibility and associated uncertainty alongside guidelines for creating such maps using free and open-source software.
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci., 25, 1229–1253, https://doi.org/10.5194/nhess-25-1229-2025, https://doi.org/10.5194/nhess-25-1229-2025, 2025
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Landslide runout zones are the areas downslope or downstream of landslide initiation. People often live and work in these areas, leading to property damage and deaths. Landslide runout may occur on hillslopes or in channels, requiring different modeling approaches. We develop methods to identify potential runout zones and apply these methods to identify susceptible areas for three municipalities in Puerto Rico.
Jonathan Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
Nat. Hazards Earth Syst. Sci., 25, 1037–1056, https://doi.org/10.5194/nhess-25-1037-2025, https://doi.org/10.5194/nhess-25-1037-2025, 2025
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Rainfall-induced landslides result in deaths and economic losses annually across the globe. However, it is unclear how storm severity relates to landslide severity across large regions. Here we develop a method to dynamically map landslide-affected areas, and we compare this to meteorological estimates of storm severity. We find that preconditioning by earlier storms and the location of rainfall bursts, rather than atmospheric storm strength, dictate landslide magnitude and pattern.
Ellen B. Robson, Bhim Kumar Dahal, and David G. Toll
Nat. Hazards Earth Syst. Sci., 25, 949–973, https://doi.org/10.5194/nhess-25-949-2025, https://doi.org/10.5194/nhess-25-949-2025, 2025
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Slopes excavated alongside roads in Nepal frequently fail (a landslide), resulting in substantial losses. Our participatory approach study with road engineers aimed to assess how road slope design guidelines in Nepal can be improved. Our study revealed inconsistent guideline adherence due to a lack of user-friendliness and inadequate training. We present general recommendations to enhance road slope management, as well as technical recommendations to improve the guidelines.
Chenchen Qiu and Xueyu Geng
Nat. Hazards Earth Syst. Sci., 25, 709–726, https://doi.org/10.5194/nhess-25-709-2025, https://doi.org/10.5194/nhess-25-709-2025, 2025
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We propose an integrated method using a combination of a physical vulnerability matrix and a machine learning model to estimate the potential physical damage and associated economic loss caused by future debris flows based on collected historical data on the Qinghai–Tibet Plateau region.
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
Nat. Hazards Earth Syst. Sci., 25, 647–656, https://doi.org/10.5194/nhess-25-647-2025, https://doi.org/10.5194/nhess-25-647-2025, 2025
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Debris flows occur infrequently, with average recurrence intervals (ARIs) ranging from decades to millennia. Consequently, they pose an underappreciated hazard. We describe how to make a preliminary identification of debris-flow-susceptible catchments, estimate threshold ARIs for debris flows that pose an unacceptable risk to life, and identify the “window of non-recognition” where debris flows are infrequent enough that their hazard is unrecognised yet frequent enough to pose a risk to life.
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci., 25, 467–491, https://doi.org/10.5194/nhess-25-467-2025, https://doi.org/10.5194/nhess-25-467-2025, 2025
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We developed a machine-learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables, including metrics on terrain, geomorphology, vegetation height, and lithology, and used data from two Swiss field inventories to calibrate and test the models. The best-performing machine learning model consistently reduced the mean average error by at least 20 % compared to previous models.
Jui-Ming Chang, Che-Ming Yang, Wei-An Chao, Chin-Shang Ku, Ming-Wan Huang, Tung-Chou Hsieh, and Chi-Yao Hung
Nat. Hazards Earth Syst. Sci., 25, 451–466, https://doi.org/10.5194/nhess-25-451-2025, https://doi.org/10.5194/nhess-25-451-2025, 2025
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The study on the Cilan landslide (CL) demonstrates the utilization of seismic analysis results as preliminary data for geologists during field surveys. Spectrograms revealed that the first event of CL consisted of four sliding failures accompanied by a gradual reduction in landslide volume. The second and third events were minor toppling and rockfalls. Then combining the seismological-based knowledge and field survey results, the spatiotemporal variation in landslide evolution is proposed.
Johannes Jakob Fürst, David Farías-Barahona, Thomas Bruckner, Lucia Scaff, Martin Mergili, Santiago Montserrat, and Humberto Peña
EGUsphere, https://doi.org/10.5194/egusphere-2024-3103, https://doi.org/10.5194/egusphere-2024-3103, 2025
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The 1987 Parraguirre ice-rock avalanche developed into a devastating debris-flow causing loss of many lives and inflicting severe damage near Santiago, Chile. Here, we revise this event combining various observational records with modelling techniques. In this year, important snow cover coincided with warm days in spring. We further quantify the total solid volume, and forward important upward corrections for the trigger and flood volumes. Finally, river damming was key for high flow mobility.
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025, https://doi.org/10.5194/nhess-25-183-2025, 2025
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The paper focuses on classifying continuous landslide conditioning factors for susceptibility modelling, which resulted in 54 landslide susceptibility models that tested 11 classification criteria in combination with 5 statistical methods. The novelty of the research is that using stretched landslide conditioning factor values results in models with higher accuracy and that certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others.
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025, https://doi.org/10.5194/nhess-25-169-2025, 2025
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Early warning of increased landslide potential provides situational awareness to reduce landslide-related losses from major storm events. For decades, landslide forecasts relied on rainfall data alone, but recent research points to the value of hydrologic information for improving predictions. In this paper, we provide our perspectives on the value and limitations of integrating subsurface hillslope hydrologic monitoring data and mathematical modeling for more accurate landslide forecasts.
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci., 25, 119–146, https://doi.org/10.5194/nhess-25-119-2025, https://doi.org/10.5194/nhess-25-119-2025, 2025
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This study enhances landslide prediction using advanced machine learning, including new algorithms inspired by historical explorations. The research accurately forecasts landslide movements by analyzing 8 years of data from Taiwan's Lushan, improving early warning and potentially saving lives and infrastructure. This integration marks a significant advancement in environmental risk management.
Di Wu, Yuke Wang, and Xin Chen
Nat. Hazards Earth Syst. Sci., 24, 4617–4630, https://doi.org/10.5194/nhess-24-4617-2024, https://doi.org/10.5194/nhess-24-4617-2024, 2024
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This paper proposes a 3D limit analysis for seismic stability of soil slopes to address the influence of earthquakes on slope stabilities with nonlinear and linear criteria. Comparison results illustrate that the use of a linear envelope leads to the non-negligible overestimation of steep-slope stability, and this overestimation will be significant with increasing earthquakes. Earthquakes have a smaller influence on slope slip surfaces with a nonlinear envelope than those with a linear envelope.
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024, https://doi.org/10.5194/nhess-24-4179-2024, 2024
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The damage patterns of the buildings were classified into three types: (I) buried by primary debris flow, (II) inundated by secondary dam-burst flood, and (III) sequentially buried by debris flow and inundated by dam-burst flood. The threshold of the impact pressures in Zones (II) and (III) where vulnerability is equal to 1 is 84 kPa and 116 kPa, respectively. Heavy damage occurs at an impact pressure greater than 50 kPa, while slight damage occurs below 30 kPa.
Bo Peng and Xueling Wu
Nat. Hazards Earth Syst. Sci., 24, 3991–4013, https://doi.org/10.5194/nhess-24-3991-2024, https://doi.org/10.5194/nhess-24-3991-2024, 2024
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Our research enhances landslide prevention using advanced machine learning to forecast heavy-rainfall-triggered landslides. By analyzing regions and employing various models, we identified optimal ways to predict high-risk rainfall events. Integrating multiple factors and models, including a neural network, significantly improves landslide predictions. Real data validation confirms our approach's reliability, aiding communities in mitigating landslide impacts and safeguarding lives and property.
Mahnoor Ahmed, Giacomo Titti, Sebastiano Trevisani, Lisa Borgatti, and Mirko Francioni
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-211, https://doi.org/10.5194/nhess-2024-211, 2024
Revised manuscript accepted for NHESS
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Elevation models are compared with a true dataset for terrain characteristics which selects a better ranking model to test with different parameters for partitioning the terrain. The partitioning of the terrain is measured by how well a partitioned unit can support the mapped landslide area and number of landslides. The effect of this relationship is reflected with different metrics in the susceptibility maps.
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
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Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
Oliver Korup, Lisa V. Luna, and Joaquin V. Ferrer
Nat. Hazards Earth Syst. Sci., 24, 3815–3832, https://doi.org/10.5194/nhess-24-3815-2024, https://doi.org/10.5194/nhess-24-3815-2024, 2024
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Catalogues of mapped landslides are useful for learning and forecasting how frequently they occur in relation to their size. Yet, rare and large landslides remain mostly uncertain in statistical summaries of these catalogues. We propose a single, consistent method of comparing across different data sources and find that landslide statistics disclose more about subjective mapping choices than trigger types or environmental settings.
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024, https://doi.org/10.5194/nhess-24-3651-2024, 2024
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This work examines the use of interferometric synthetic-aperture radar (InSAR) alongside in situ borehole measurements to assess the stability of deep-seated landslides for the case study of El Forn (Andorra). Comparing InSAR with borehole data suggests a key trade-off between accuracy and precision for various InSAR resolutions. Spatial interpolation with InSAR informed how many remote observations are necessary to lower error in a remote sensing re-creation of ground motion over the landslide.
Lorenzo Nava, Alessandro Novellino, Chengyong Fang, Kushanav Bhuyan, Kathryn Leeming, Itahisa Gonzalez Alvarez, Claire Dashwood, Sophie Doward, Rahul Chahel, Emma McAllister, Sansar Raj Meena, and Filippo Catani
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-146, https://doi.org/10.5194/nhess-2024-146, 2024
Revised manuscript accepted for NHESS
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On April 2, 2024, a Mw 7.4 earthquake hit Taiwan’s eastern coast, causing extensive landslides and damage. We used automated methods combining Earth Observation (EO) data with Artificial Intelligence (AI) to quickly inventory the landslides. This approach identified 7,090 landslides over 75 km2 within 3 hours of acquiring the EO imagery. The study highlights AI’s role in improving landslide detection and understanding earthquake-landslide interactions for better hazard mitigation.
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024, https://doi.org/10.5194/nhess-24-3357-2024, 2024
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The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
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The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Isabelle Utley, Tristram Hales, Ekbal Hussain, and Xuanmei Fan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2277, https://doi.org/10.5194/egusphere-2024-2277, 2024
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We analysed debris flows in Sichuan, China, using satellite data and simulations to assess check dam efficacy. Our study found whilst check dams can mitigate smaller flows, they may increase exposure to extreme events, with up to 40 % of structures in some areas affected. Urban development and reliance on check dams can create a false sense of security, raising exposure during large debris flows and highlights the need for risk management and infrastructure planning in hazard-prone areas.
Daniel Camilo Roman Quintero, Pasquale Marino, Abdullah Abdullah, Giovanni Francesco Santonastaso, and Roberto Greco
EGUsphere, https://doi.org/10.5194/egusphere-2024-2329, https://doi.org/10.5194/egusphere-2024-2329, 2024
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Local thresholds for landslide forecasting, combining hydrologic predisposing factors and rainfall features, are developed from a physically based model of a slope. To extend their application to a wide area, uncertainty due to spatial variability of geomorphological and hydrologic variables is introduced. The obtained hydrometeorological thresholds, integrating root zone soil moisture and aquifer water level with rainfall depth, outperform thresholds based on rain intensity and duration.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
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Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
Jianqi Zhuang, Jianbing Peng, Chenhui Du, Yi Zhu, and Jiaxu Kong
Nat. Hazards Earth Syst. Sci., 24, 2615–2631, https://doi.org/10.5194/nhess-24-2615-2024, https://doi.org/10.5194/nhess-24-2615-2024, 2024
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The Revised Infinite Slope Model (RISM) is proposed using the equal differential unit method and correcting the deficiency of the safety factor increasing with the slope increasing when the slope is larger than 40°, as calculated using the Taylor slope infinite model. The intensity–duration (I–D) prediction curve of the rainfall-induced shallow loess landslides with different slopes was constructed and can be used in forecasting regional shallow loess landslides.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
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Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 h) needed for decision-making. This work takes an initial step toward a near-real-time postfire debris-flow inundation hazard assessment product.
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
Nat. Hazards Earth Syst. Sci., 24, 2093–2114, https://doi.org/10.5194/nhess-24-2093-2024, https://doi.org/10.5194/nhess-24-2093-2024, 2024
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Every year the U.S. Geological Survey produces 50–100 postfire debris-flow hazard assessments using models for debris-flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris-flow response, and debris-flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a 2-year period. We also proposed ways to improve these models.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024, https://doi.org/10.5194/nhess-24-1913-2024, 2024
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Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-means SMOTE (synthetic minority oversampling technique) achieves high precision, high recall, and a high F1 score. Our findings highlight the potential of these models with oversampling techniques to improve soil movement predictions in landslide-prone areas.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
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In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Jane Walden, Mylène Jacquemart, Bretwood Higman, Romain Hugonnet, Andrea Manconi, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1086, https://doi.org/10.5194/egusphere-2024-1086, 2024
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In a study of eight landslides adjacent to glaciers in Alaska, we found that landslide movement increased as the glacier retreated past the landslide at four sites. Movement at other sites coincided with heavy precipitation or increased glacier thinning, and two sites showed little-to-no motion. We suggest that landslides next to water-terminating glaciers may be especially vulnerable to acceleration, which we guess is due to faster retreat rates and water replacing ice at the landslide edge.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
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With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
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Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
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We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
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Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
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Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
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Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
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We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
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We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
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Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. 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 (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
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.
Cited articles
Abancó, C., Hürlimann, M., Moya, J., and Berenguer, M.: Critical
rainfall conditions for the initiation of torrential flows. Results from the
Rebaixader catchment (Central Pyrenees), J. Hydrol., 541,
218–229, https://doi.org/10.1016/j.jhydrol.2016.01.019, 2016. a, b, c
Badoux, A., Graf, C., Rhyner, J., Kuntner, R., and McArdell, B. W.: A
debris-flow alarm system for the Alpine Illgraben catchment: Design and
performance, Nat. Hazards, 49, 517–539, https://doi.org/10.1007/s11069-008-9303-x,
2009. a, b, c, d
Badoux, A., Turowski, J. M., Mao, L., Mathys, N., and Rickenmann, D.: Rainfall intensity–duration thresholds for bedload transport initiation in small Alpine watersheds, Nat. Hazards Earth Syst. Sci., 12, 3091–3108, https://doi.org/10.5194/nhess-12-3091-2012, 2012. a, b
Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747–2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016. a
Bennett, G. L., Molnar, P., Eisenbeiss, H., and Mcardell, B. W.: Erosional
power in the Swiss Alps: Characterization of slope failure in the Illgraben,
Earth Surf. Proc. Land., 37, 1627–1640,
https://doi.org/10.1002/esp.3263, 2012. a
Bennett, G. L., Molnar, P., McArdell, B. W., and Burlando, P.: A probabilistic
sediment cascade model of sediment transfer in the Illgraben, Water
Resour. Res., 50, 1225–1244, https://doi.org/10.1002/2013WR013806, 2014. a
Berger, C., McArdell, B. W., and Schlunegger, F.: Sediment transfer patterns
at the Illgraben catchment, Switzerland: Implications for the time scales of
debris flow activities, Geomorphology, 125, 421–432,
https://doi.org/10.1016/j.geomorph.2010.10.019, 2011. a, b
Berti, M. and Simoni, A.: Experimental evidences and numerical modelling of
debris flow initiated by channel runoff, Landslides, 2, 171–182,
https://doi.org/10.1007/s10346-005-0062-4, 2005. a
Berti, M., Bernard, M., Simoni, A., and Gregoretti, C.: Physical
interpretation of rainfall thresholds for runoff-generated debris flows,
J. Geophys. Res.-Earth, 125, 1–25,
https://doi.org/10.1029/2019JF005513, 2020. 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
Breiman, L.: Random forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324, 2001. a, b, c
Brunetti, M. T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., and Guzzetti, F.: Rainfall thresholds for the possible occurrence of landslides in Italy, Nat. Hazards Earth Syst. Sci., 10, 447–458, https://doi.org/10.5194/nhess-10-447-2010, 2010. a, b
Caine, N.: The Rainfall Intensity -Duration Control of Shallow Landslides and
Debris Flows, Geogr. Ann. A, 62, 23–27,
https://doi.org/10.1080/04353676.1980.11879996, 1980. a, b, c
Cannon, S. H., Gartner, J. E., Rupert, M. G., Michael, J. A., Rea, A. H., and
Parrett, C.: Predicting the probability and volume of postwildfire debris
flows in the intermountain western United States, Bull. Geol.
Soc. Am., 122, 127–144, https://doi.org/10.1130/B26459.1, 2010. a, b
Chmiel, M., Walter, F., Wenner, M., Zhang, Z., McArdell, B. W., and Hibert, C.:
Machine Learning Improves Debris Flow Warning, Geophys. Res.
Lett., 48, e2020GL090874, https://doi.org/10.1029/2020GL090874, 2021. a
Coe, J. A., Kinner, D. A., and Godt, J. W.: Initiation conditions for debris
flows generated by runoff at Chalk Cliffs, central Colorado, Geomorphology,
96, 270–297, https://doi.org/10.1016/j.geomorph.2007.03.017, 2008. a, b, c
de Haas, T., Nijland, W., de Jong, S. M., and Mcardell, B. W.: How memory
effects, check dams, and channel geometry control erosion and deposition by
debris flows, Sci. Rep.-UK, 10, 1–8,
https://doi.org/10.1038/s41598-020-71016-8, 2020. a
Domènech, G., Fan, X., Scaringi, G., van Asch, T. W., Xu, Q., Huang, R.,
and Hales, T. C.: Modelling the role of material depletion, grain coarsening
and revegetation in debris flow occurrences after the 2008 Wenchuan
earthquake, Eng. Geol., 250, 34–44,
https://doi.org/10.1016/j.enggeo.2019.01.010, 2019. a
Dowling, C. A. and Santi, P. M.: Debris flows and their toll on human life: A
global analysis of debris-flow fatalities from 1950 to 2011, Nat.
Hazards, 71, 203–227, https://doi.org/10.1007/s11069-013-0907-4, 2014. a
Dunkerley, D.: Identifying individual rain events from pluviograph records: A
review with analysis of data from an Australian dryland site, Hydrol.
Process., 22, 5024–5036, https://doi.org/10.1002/hyp.7122, 2008. a
Fawcett, T.: An introduction to ROC analysis, Pattern Recogn. Lett.,
27, 861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006. a
Frei, C. and Schär, C.: A precipitation climatology of the Alps from
high-resolution rain-gauge observations, Int. J.
Climatol., 18, 873–900,
https://doi.org/10.1002/(SICI)1097-0088(19980630)18:8<873::AID-JOC255>3.0.CO;2-9, 1998. a
Fryxwell, F. M. and Horberg, L.: Alpine mudflows in Grand Teton National Park,
Wyoming, GSA Bulletin, 54, 457–472, https://doi.org/10.1130/GSAB-54-457, 1943. a
Gaál, L., Molnar, P., and Szolgay, J.: Selection of intense rainfall events based on intensity thresholds and lightning data in Switzerland, Hydrol. Earth Syst. Sci., 18, 1561–1573, https://doi.org/10.5194/hess-18-1561-2014, 2014. a, b, c
Gariano, S. L., Brunetti, M. T., Iovine, G., Melillo, M., Peruccacci, S.,
Terranova, O., Vennari, C., and Guzzetti, F.: Calibration and validation of
rainfall thresholds for shallow landslide forecasting in Sicily, southern
Italy, Geomorphology, 228, 653–665, https://doi.org/10.1016/j.geomorph.2014.10.019,
2015. a
Gariano, S. L., Melillo, M., Peruccacci, S., and Brunetti, M. T.: How much
does the rainfall temporal resolution affect rainfall thresholds for
landslide triggering?, Nat. Hazards, 100, 655–670,
https://doi.org/10.1007/s11069-019-03830-x, 2020. a
Gregoretti, C.: The initiation of debris flow at high slopes: Experimental
results, J. Hydraul. Res., 38, 83–88,
https://doi.org/10.1080/00221680009498343, 2000. a
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds
for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007. a
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., Marchesini, I.,
Rossi, M., and Melillo, M.: Geographical landslide early warning systems,
Earth-Sci. Rev., 200, 102973, https://doi.org/10.1016/j.earscirev.2019.102973,
2020. a
Hanssen, A. W. and Kuipers, W. J. A.: On the relationship between the frequency of rain and various meteorological parameters, Meded. Verh, 81, 2–15, 1965. a
Hilker, N., Badoux, A., and Hegg, C.: The Swiss flood and landslide damage database 1972–2007, Nat. Hazards Earth Syst. Sci., 9, 913–925, https://doi.org/10.5194/nhess-9-913-2009, 2009. a, b
Hirschberg, J.: Source code for: Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment, EnviDat [code], https://doi.org/10.16904/envidat.240, 2021. a
Hirschberg, J., McArdell, B. W., Badoux, A., and Molnar, P.: Analysis of
rainfall and runoff for debris flows at the Illgraben catchment,
Switzerland, in: Debris-Flow Hazards Mitigation: Mechanics, Monitoring,
Modeling, and Assessment – Proceedings of the 7th International Conference on
Debris-Flow Hazards Mitigation, 693–700, 2019. a, b
Hirschberg, J., Fatichi, S., Bennett, G. L., McArdell, B. W., Peleg, N., Lane,
S. N., Schlunegger, F., and Molnar, P.: Climate Change Impacts on Sediment
Yield and Debris-Flow Activity in an Alpine Catchment, J.
Geophys. Res.-Earth, 126, e2020JF005739, https://doi.org/10.1029/2020JF005739, 2021. a, b, c, d
Hungr, O., Leroueil, S., and Picarelli, L.: The Varnes classification of
landslide types, an update, Landslides, 11, 167–194,
https://doi.org/10.1007/s10346-013-0436-y, 2014. a
Hürlimann, M., Rickenmann, D., and Graf, C.: Field and monitoring data
of debris-flow events in the Swiss Alps, Can. Geotech. J., 40,
161–175, https://doi.org/10.1139/t02-087, 2003. a, b, c
Hydrological Atlas of Switzerland: Mean Precipitation, [data set], available at:
https://hydrologicalatlas.ch (last access: 4 September 2020-09-), 2015. a
Iverson, R. M.: The Physics of Debris Flows, Rev. Geophys., 35,
245–296, https://doi.org/10.1029/97RG00426, 1997. a
Iverson, R. M., Reid, M. E., Logan, M., LaHusen, R. G., Godt, J. W., and
Griswold, J. P.: Positive feedback and momentum growth during debris-flow
entrainment of wet bed sediment, Nat. Geosci., 4, 116–121,
https://doi.org/10.1038/ngeo1040, 2011. a
James, G., Witten, D., Hastie, T., and Tibshirani, R.: Resampling Methods,
Springer New York, New York, NY, 175–201,
https://doi.org/10.1007/978-1-4614-7138-7_5, 2013a. a
James, G., Witten, D., Hastie, T., and Tibshirani, R.: Tree-Based Methods,
Springer New York, New York, NY, 303–335,
https://doi.org/10.1007/978-1-4614-7138-7_8, 2013b. a
Johnson, A. M. and Rodine, J. D.: Debris flow, in: Slope instability, edited
by: Brunsden, D. and Prior, D., Wiley and Sons, Chichester, England, 1984. a
Kern, A. N., Addison, P., Oommen, T., Salazar, S. E., and Coffman, R. A.:
Machine Learning Based Predictive Modeling of Debris Flow Probability
Following Wildfire in the Intermountain Western United States, Math.
Geosci., 49, 717–735, https://doi.org/10.1007/s11004-017-9681-2, 2017. a, b
Lichtenhahn, C.: Zwei Betonmauern: die Geschieberückhaltesperre am Illgraben [Wallis] und die Staumauer des Hochwasserschutzbeckens an der Orlegna im Bergell [Graubünden], Internationales Symposium Interpraevent, Villach, Austria: F.f.v. Hochwasserbekämpfung, 451–456, 1971. a
Marra, F.: Rainfall thresholds for landslide occurrence: systematic
underestimation using coarse temporal resolution data, Nat. Hazards,
95, 889–890, https://doi.org/10.1007/s11069-018-3508-4, 2019. a
Marra, F., Nikolopoulos, E. I., Creutin, J. D., and Borga, M.: Space–time
organization of debris flows-triggering rainfall and its effect on the
identification of the rainfall threshold relationship, J. Hydrol.,
541, 246–255, https://doi.org/10.1016/j.jhydrol.2015.10.010, 2016. a, b, c
McArdell, B. W.: Field Measurements of Forces in Debris Flows at the
Illgraben: Implications for Channel-Bed Erosion, International Journal of
Erosion Control Engineering, 9, 194–198, https://doi.org/10.13101/ijece.9.194, 2016. a
McArdell, B. W. and Badoux, A.: Influence of rainfall on the initiation of
debris flows at the Illgraben catchment, canton of Valais, Switzerland, in:
Geophysical Research Abstracts, 9, 8804, 2007. a
McArdell, B. W. and Hirschberg, J.: Debris-flow volumes at the Illgraben
2000–2017, EnviDat [data set], https://doi.org/10.16904/envidat.173, 2020. a, b, c
McArdell, B. W. and Sartori, M.: The Illgraben Torrent System, 367–378,
Springer International Publishing, Cham, https://doi.org/10.1007/978-3-030-43203-4_25,
2021. a
McArdell, B. W., Bartelt, P., and Kowalski, J.: Field observations of basal
forces and fluid pore pressure in a debris flow, Geophys. Res.
Lett., 34, 2–5, https://doi.org/10.1029/2006GL029183, 2007. a
McCoy, S. W., Kean, J. W., Coe, J. A., Tucker, G. E., Staley, D. M., and
Wasklewicz, T. A.: Sediment entrainment by debris flows: In situ
measurements from the headwaters of a steep catchment, J.
Geophys. Res.-Earth, 117, F03016, https://doi.org/10.1029/2011JF002278, 2012. a
Mirus, B., Morphew, M., and Smith, J.: Developing Hydro-Meteorological
Thresholds for Shallow Landslide Initiation and Early Warning, Water, 10,
1274, https://doi.org/10.3390/w10091274, 2018. a, b
Mostbauer, K., Kaitna, R., Prenner, D., and Hrachowitz, M.: The temporally varying roles of rainfall, snowmelt and soil moisture for debris flow initiation in a snow-dominated system, Hydrol. Earth Syst. Sci., 22, 3493–3513, https://doi.org/10.5194/hess-22-3493-2018, 2018. a
Nikolopoulos, E. I., Destro, E., Bhuiyan, M. A. E., Borga, M., and Anagnostou, E. N.: Evaluation of predictive models for post-fire debris flow occurrence in the western United States, Nat. Hazards Earth Syst. Sci., 18, 2331–2343, https://doi.org/10.5194/nhess-18-2331-2018, 2018. a, b, c, d
Nikolopoulos, E. I., Crema, S., Marchi, L., Marra, F., Guzzetti, F., and Borga,
M.: Impact of uncertainty in rainfall estimation on the identification of
rainfall thresholds for debris flow occurrence, Geomorphology, 221,
286–297, https://doi.org/10.1016/j.geomorph.2014.06.015, 2014. a, b
Papa, M. N., Medina, V., Ciervo, F., and Bateman, A.: Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems, Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, 2013. a
Pastorello, R., Hürlimann, M., and D'Agostino, V.: Correlation between
the rainfall, sediment recharge, and triggering of torrential flows in the
Rebaixader catchment (Pyrenees, Spain), Landslides, 15, 1921–1934,
https://doi.org/10.1007/s10346-018-1000-6, 2018. a
Pedregosa, F., Michel, V., Varoquaux, G., Thirion, B., Dubourg, V., Passos, A.,
Perrot, M., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Vanderplas,
J., Cournapeau, D., Pedregosa, F., Varoquaux, G., Gramfort, A., Thirion, B.,
Grisel, O., Dubourg, V., Passos, A., Brucher, M., Perrot andÉdouardand,
M., and Duchesnay, É.: Scikit-learn: Machine Learning in Python,
J. Machine Learn. Res., 12, 2825–2830,
2011. a
Peirce, C. S.: The numerical measure of the success of predictions, Science,
4, 453–454, https://doi.org/10.1126/science.ns-4.93.453-a, 1884. a
Peruccacci, S., Brunetti, M. T., Luciani, S., Vennari, C., and Guzzetti, F.:
Lithological and seasonal control on rainfall thresholds for the possible
initiation of landslides in central Italy, Geomorphology, 139–140, 79–90,
https://doi.org/10.1016/j.geomorph.2011.10.005, 2012. a
Peruccacci, S., Brunetti, M. T., Gariano, S. L., Melillo, M., Rossi, M., and
Guzzetti, F.: Rainfall thresholds for possible landslide occurrence in
Italy, Geomorphology, 290, 39–57, https://doi.org/10.1016/j.geomorph.2017.03.031,
2017. a
Postance, B., Hillier, J., Dijkstra, T., and Dixon, N.: Comparing threshold
definition techniques for rainfall-induced landslides: A national assessment
using radar rainfall, Earth Surf. Proc. Land., 43, 553–560,
https://doi.org/10.1002/esp.4202, 2018. a
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J.,
Carvalhais, N., and Prabhat: Deep learning and process understanding for
data-driven Earth system science, Nature, 566, 195–204,
https://doi.org/10.1038/s41586-019-0912-1, 2019. a
Rickenmann, D., Hürlimann, M., Graf, C., Näf, D., and Weber, D.:
Murgang-Beobachtungsstationen in der Schweiz, in: Wasser Energie Luft,
93, 1–8, 2001. a
Schlunegger, F., Badoux, A., McArdell, B. W., Gwerder, C., Schnydrig, D.,
Rieke-Zapp, D., and Molnar, P.: Limits of sediment transfer in an alpine
debris-flow catchment, Illgraben, Switzerland, Quaternary Sci. Rev.,
28, 1097–1105, https://doi.org/10.1016/j.quascirev.2008.10.025, 2009. a, b
Schneuwly-Bollschweiler, M. and Stoffel, M.: Hydrometeorological triggers of
periglacial debris flows in the Zermatt valley (Switzerland) since 1864,
J. Geophys. Res.-Earth, 117, 1–12,
https://doi.org/10.1029/2011JF002262, 2012. a
Segoni, S., Piciullo, L., and Gariano, S. L.: A review of the recent
literature on rainfall thresholds for landslide occurrence, Landslides, 15,
1483–1501, https://doi.org/10.1007/s10346-018-0966-4, 2018. a, b, c
Stähli, M., Sättele, M., Huggel, C., McArdell, B. W., Lehmann, P., Van Herwijnen, A., Berne, A., Schleiss, M., Ferrari, A., Kos, A., Or, D., and Springman, S. M.: Monitoring and prediction in early warning systems for rapid mass movements, Nat. Hazards Earth Syst. Sci., 15, 905–917, https://doi.org/10.5194/nhess-15-905-2015, 2015. a
Staley, D. M., Kean, J. W., Cannon, S. H., Schmidt, K. M., and Laber, J. L.:
Objective definition of rainfall intensity-duration thresholds for the
initiation of post-fire debris flows in southern California, Landslides, 10,
547–562, https://doi.org/10.1007/s10346-012-0341-9, 2013. a, b, c, d
Staley, D. M., Negri, J. A., Kean, J. W., Laber, J. L., Tillery, A. C., and
Youberg, A. M.: Prediction of spatially explicit rainfall
intensity–duration thresholds for post-fire debris-flow generation in the
western United States, Geomorphology, 278, 149–162,
https://doi.org/10.1016/j.geomorph.2016.10.019, 2017. a, b
Takahashi, T.: Mechanical Characteristics of Debris Flow, J. Hydr. Eng. Div.-ASCE, 104, 1153–1169, 1978. a
Takahashi, T.: Debris Flow, Annu. Rev. Fluid Mech., 13,
57–77, https://doi.org/10.1146/annurev.fl.13.010181.000421, 1981. a
Tang, H., McGuire, L. A., Rengers, F. K., Kean, J. W., Staley, D. M., and
Smith, J. B.: Developing and Testing Physically Based Triggering Thresholds
for Runoff-Generated Debris Flows, Geophys. Res. Lett., 46,
8830–8839, https://doi.org/10.1029/2019GL083623, 2019. a
Tognacca, C.: Beitrag zur Untersuchung der Entstehungsmechanismen von
Murgangen, Phd thesis, ETH Zürich, Zürich, https://doi.org/10.3929/ethz-a-010025751,
1999. a
Wenner, M., Hibert, C., van Herwijnen, A., Meier, L., and Walter, F.: Near-real-time automated classification of seismic signals of slope failures with continuous random forests, Nat. Hazards Earth Syst. Sci., 21, 339–361, https://doi.org/10.5194/nhess-21-339-2021, 2021. a
Wicki, A., Lehmann, P., Hauck, C., Seneviratne, S. I., Waldner, P., and
Stähli, M.: Assessing the potential of soil moisture measurements for
regional landslide early warning, Landslides, 17, 1881–1896,
https://doi.org/10.1007/s10346-020-01400-y, 2020.
a
Youden, W. J.: Index for rating diagnostic tests, Cancer, 3, 32–35,
https://doi.org/10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3, 1950. a
Short summary
Debris-flow prediction is often based on rainfall thresholds, but uncertainty assessments are rare. We established rainfall thresholds using two approaches and find that 25 debris flows are needed for uncertainties to converge in an Alpine basin and that the suitable method differs for regional compared to local thresholds. Finally, we demonstrate the potential of a statistical learning algorithm to improve threshold performance. These findings are helpful for early warning system development.
Debris-flow prediction is often based on rainfall thresholds, but uncertainty assessments are...
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