Articles | Volume 23, issue 4
https://doi.org/10.5194/nhess-23-1241-2023
© 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-23-1241-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Apr 2023
Research article |
| 03 Apr 2023
| 03 Apr 2023
Debris-flow surges of a very active alpine torrent: a field database
Suzanne Lapillonne
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
Firmin Fontaine
Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
Frédéric Liebault
Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
Vincent Richefeu
Univ. Grenoble Alpes, 3SR, Gières, France
Guillaume Piton
Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
Related authors
Suzanne Lapillonne, Georgios Fourtakas, Vincent Richefeu, Guillaume Piton, and Guillaume Chambon
EGUsphere, https://doi.org/10.22541/au.170628457.73131740/v2, https://doi.org/10.22541/au.170628457.73131740/v2, 2024
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Debris flows are fast flowing flows saturated with granular material. They naturally occur in steep creeks and are a threat to local communities. Scientists turn to numerical models to better understand how they behave. We investigate the accuracy of a numerical model which relies on modelling the debris flow as a mixture of a granular phase and a fluid phase. We focus on a demonstration of the capacity of the model to reliably represent the behaviour of the flow at different scales.
Miao Huo, Stéphane Lambert, Firmin Fontaine, and Guillaume Piton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3575, https://doi.org/10.5194/egusphere-2024-3575, 2024
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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The presented study mainly describes the loading on a flexible barrier at rest in order that the static component of the force exerted by the dead zone received limited attention up to now. Four interaction modes are identified from a gentle flow stopping to high granular jump and/or overtopping. Interestingly, overflow resulted in a significant increase in the residual load and were almost twice that observed in the absence of overflow.
Loïs Ribet, Frédéric Liébault, Laurent Borgniet, Michaël Deschâtres, and Gabriel Melun
EGUsphere, https://doi.org/10.5194/egusphere-2024-3697, https://doi.org/10.5194/egusphere-2024-3697, 2024
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This work presents a protocol and a model to get the size of the pebbles in mountain rivers from Unmanned Aerial Vehicle images. A set of 12 rivers located in south-eastern France were photographed to build the model. The results show that the model has little error and should be usable for similar rivers. Grain-size of mountain rivers is an important parameter for environmental diagnostics by mapping the aquatic habitats and for flood management by estimating the pebbles fluxes during floods.
Suzanne Lapillonne, Georgios Fourtakas, Vincent Richefeu, Guillaume Piton, and Guillaume Chambon
EGUsphere, https://doi.org/10.22541/au.170628457.73131740/v2, https://doi.org/10.22541/au.170628457.73131740/v2, 2024
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Debris flows are fast flowing flows saturated with granular material. They naturally occur in steep creeks and are a threat to local communities. Scientists turn to numerical models to better understand how they behave. We investigate the accuracy of a numerical model which relies on modelling the debris flow as a mixture of a granular phase and a fluid phase. We focus on a demonstration of the capacity of the model to reliably represent the behaviour of the flow at different scales.
Sebastien Klotz, Caroline Le Bouteiller, Nicolle Mathys, Firmin Fontaine, Xavier Ravanat, Jean-Emmanuel Olivier, Frédéric Liébault, Hugo Jantzi, Patrick Coulmeau, Didier Richard, Jean-Pierre Cambon, and Maurice Meunier
Earth Syst. Sci. Data, 15, 4371–4388, https://doi.org/10.5194/essd-15-4371-2023, https://doi.org/10.5194/essd-15-4371-2023, 2023
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Mountain badlands are places of intense erosion. They deliver large amounts of sediment to river systems, with consequences for hydropower sustainability, habitat quality and biodiversity, and flood hazard and river management. Draix-Bleone Observatory was created in 1983 to understand and quantify sediment delivery from such badland areas. Our paper describes how water and sediment fluxes have been monitored for almost 40 years in the small mountain catchments of this observatory.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
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.
Guillaume Piton, Toshiyuki Horiguchi, Lise Marchal, and Stéphane Lambert
Nat. Hazards Earth Syst. Sci., 20, 3293–3314, https://doi.org/10.5194/nhess-20-3293-2020, https://doi.org/10.5194/nhess-20-3293-2020, 2020
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Open check dams are flood protection structures trapping sediment and large wood. Large wood obstructs openings of dams, thus increasing flow levels. If flow levels become higher than the dam crest, the trapped large wood may overtop the structure and be suddenly released downstream, which may also eventually obstruct downstream bridges. This paper is based on experiments on small-scale models. It shows how to compute the increase in flow level and conditions leading to sudden overtopping.
Alexandre Loye, Michel Jaboyedoff, Joshua Isaac Theule, and Frédéric Liébault
Earth Surf. Dynam., 4, 489–513, https://doi.org/10.5194/esurf-4-489-2016, https://doi.org/10.5194/esurf-4-489-2016, 2016
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The sediment supply and storage changes from major channels of the Manival catchment (French Alps) were surveyed periodically for 16 months to study the coupling between sediment dynamics and torrent responses in terms of debris flow events. The spatial and seasonal variability of sediment delivery is displayed and analysed. This study shows that monitoring the changes within a torrent’s in-channel storage and its debris supply can improve knowledge on recharge thresholds leading to debris flow.
P. Bottelin, D. Jongmans, D. Daudon, A. Mathy, A. Helmstetter, V. Bonilla-Sierra, H. Cadet, D. Amitrano, V. Richefeu, L. Lorier, L. Baillet, P. Villard, and F. Donzé
Nat. Hazards Earth Syst. Sci., 14, 3175–3193, https://doi.org/10.5194/nhess-14-3175-2014, https://doi.org/10.5194/nhess-14-3175-2014, 2014
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Two mid-size rockfalls (~2,000 m3 each) occurred at the same place in 2011. While the first event was natural, the second one was artificially triggered and recorded by video cameras and seismic sensors. The measurements showed propagation velocities ranging from 12 to 30 m/s over the successive event phases. The most seismogenic phases were related to ground impact after free-fall and individual block impacts into a protective barrier. DEM reproduced the key features of the rockfall dynamics.
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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.
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Ellen B. Robson, Bhim Kumar Dahal, and David G. Toll
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Chenchen Qiu and Xueyu Geng
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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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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.
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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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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.
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.
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.
Yu Zhuang, Brian W. McArdell, and Perry Bartelt
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-87, https://doi.org/10.5194/nhess-2024-87, 2024
Revised manuscript accepted for NHESS
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This study reformulates the μ(I) rheology into a Voellmy-type relationship to elucidate its physical implications. The μ(I) rheology, incorporating a dimensionless inertial number, mimics granular temperature effects, reflecting shear thinning behavior of mass flows. However, its constant Coulomb friction coefficient limits accuracy in modeling deposition. Comparing μ(I) with Voellmy-type rheologies reveals strengths and limitations, enhancing mass flow modeling and engineering applications.
Sonam Rinzin, Stuart Dunning, Rachel Carr, Ashim Sattar, and Martin Mergili
EGUsphere, https://doi.org/10.5194/egusphere-2024-1819, https://doi.org/10.5194/egusphere-2024-1819, 2024
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We evaluated the sensitivity of model outputs to input parameter uncertainties by performing multiple GLOF simulations using the r.avaflow model. We found out that GLOF modelling outputs are highly sensitive to six parameters: volume of mass movements entering lakes, DEM datasets, origin of mass movements, mesh size, basal frictional angle, and entrainment coefficient. Future modelling should carefully consider the output uncertainty from these sensitive parameters.
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.
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. Discuss., https://doi.org/10.5194/nhess-2024-40, https://doi.org/10.5194/nhess-2024-40, 2024
Revised manuscript accepted for NHESS
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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 on landslide risk.
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.
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.
Cited articles
Abancó, C., Hürlimann, M., Fritschi, B., Graf, C., and Moya, J.: Transformation of Ground Vibration Signal for Debris-Flow Monitoring and Detection in Alarm Systems, Sensors, 12, 4870–4891, https://doi.org/10.3390/s120404870, 2012. a
Albaba, A., Lambert, S., Nicot, F., and Chareyre, B.: Modeling the Impact of Granular Flow against an Obstacle, in: Recent Advances in Modeling Landslides and Debris Flows, edited by: Wu, W., Springer International Publishing, 95–105, https://doi.org/10.1007/978-3-319-11053-0_9, 2015. a
Arattano, M., Abancó, C., Coviello, V., and Hürlimann, M.: Processing the ground vibration signal produced by debris flows: the methods of amplitude and impulses compared, Comput. Geosci., 73, 17–27, https://doi.org/10.1016/j.cageo.2014.08.005, 2014. a
Bardou, E., Ancey, C., Bonnard, C., and Vulliet, L.: Classification of debris-flow deposits for hazard assessment in alpine areas, in: 3th International Conference on Debris-Flow hazards mitigation: mechanics, prediction, and assessment, Davos, Switzerland, Millpress, 799–808, 2003. a
Ceccato, F., Redaelli, I., di Prisco, C., and Simonini, P.: Impact forces of granular flows on rigid structures: Comparison between discontinuous (DEM) and continuous (MPM) numerical approaches, Comput. Geotech., 103, 201–217, 2018. a
Chen, J., Wang, D., Zhao, W., Chen, H., Wang, T., Nepal, N., and Chen, X.: Laboratory study on the characteristics of large wood and debris flow processes at slit-check dams, Landslides, 17, 1703–1711, https://doi.org/10.1007/s10346-020-01409-3, 2020. a
Chmiel, M., Godano, M., Piantini, M., Brigode, P., Gimbert, F., Bakker, M., Courboulex, F., Ampuero, J.-P., Rivet, D., Sladen, A., Ambrois, D., and Chapuis, M.: Brief communication: Seismological analysis of flood dynamics and hydrologically triggered earthquake swarms associated with Storm Alex, Nat. Hazards Earth Syst. Sci., 22, 1541–1558, https://doi.org/10.5194/nhess-22-1541-2022, 2022. a
Cucchiaro, S., Cavalli, M., Vericat, D., Crema, S., Llena, M., Beinat, A., Marchi, L., and Cazorzi, F.: Monitoring topographic changes through 4D-structure-from-motion photogrammetry: application to a debris-flow channel, Environ. Earth Sci., 77, 632, https://doi.org/10.1007/s12665-018-7817-4, 2018. a
Cucchiaro, S., Cavalli, M., Vericat, D., Crema, S., Llena, M., Beinat, A., Marchi, L., and Cazorzi, F.: Geomorphic effectiveness of check dams in a debris-flow catchment using multi-temporal topographic surveys, CATENA, 174, 73–83, https://doi.org/10.1016/j.catena.2018.11.004, 2019a. a
Cucchiaro, S., Cazorzi, F., Marchi, L., Crema, S., Beinat, A., and Cavalli, M.: Multi-temporal analysis of the role of check dams in a debris-flow channel: Linking structural and functional connectivity, Geomorphology, 345, 106844, https://doi.org/10.1016/j.geomorph.2019.106844, 2019b. a
de Haas, T., McArdell, B. W., Nijland, W., Åberg, A. S., Hirschberg, J., and Huguenin, P.: Flow and Bed Conditions Jointly Control Debris-Flow Erosion and Bulking, Geophys. Res. Lett., 49, e2021GL097611, https://doi.org/10.1029/2021GL097611, 2022. a, b, c
Faug, T., Caccamo, P., and Chanut, B.: A scaling law for impact force of a granular avalanche flowing past a wall, Geophys. Res. Lett., 39, L23401, https://doi.org/10.1029/2012gl054112, 2012. a
Fontaine, F., Bel, C., Bellot, H., Piton, G., Liebault, F., Juppet, M., and Royer, K.: Suivi automatisé des crues à fort transport solide dans les torrents: stratégie de mesure et potentiel des données collectées, in: Collection EDYTEM, Monitoring en milieux naturels – Retours d'expériences en terrains difficiles, 19, 213–220, https://hal.archives-ouvertes.fr/hal-01656535 (last access: 17 March 2023), 2017. a, b
Goodwin, G. R. and Choi, C. E.: A depth-averaged SPH study on spreading mechanisms of geophysical flows in debris basins: Implications for terminal barrier design requirements, Comput. Geotech., 141, 104503, https://doi.org/10.1016/j.compgeo.2021.104503, 2022. a
Guo, X., Li, Y., Cui, P., Yan, H., and Zhuang, J.: Intermittent viscous debris flow formation in Jiangjia Gully from the perspectives of hydrological processes and material supply, J. Hydrol., 589, 125184, https://doi.org/10.1016/j.jhydrol.2020.125184, 2020. a, b, c, d
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
Hürlimann, M., Coviello, V., Bel, C., Guo, X., Berti, M., Graf, C., Hübl, J., Miyata, S., Smith, J. B., and Yin, H.-Y.: Debris-flow monitoring and warning: Review and examples, Earth-Sci. Rev., 199, 102981, https://doi.org/10.1016/j.earscirev.2019.102981, 2019. a, b, c
Jacquemart, M., Meier, L., Graf, C., and Morsdorf, F.: 3D dynamics of debris flows quantified at sub-second intervals from laser profiles, Nat. Hazards, 89, 785–800, https://doi.org/10.1007/s11069-017-2993-1, 2017. a
Jakob, M. and Hungr, O.: Debris-flow Hazards and Related Phenomena, Springer Praxis Books, Springer Berlin Heidelberg, IBSN: 978-3-540-27129-1, 2005. a
Kaitna, R. and Hübl, J.: Monitoring debris-flow surges and triggering rainfall at the Lattenbach creek, Austria, Environ. Eng. Geosci., 27, 213–220, 2021. a
Laigle, D. and Labbe, M.: SPH-Based Numerical Study of the Impact of Mudflows on Obstacles, International Journal of Erosion Control Engineering, 10, 56–66, 2017. a
Marchi, L., Cazorzi, F., Arattano, M., Cucchiaro, S., Cavalli, M., and Crema, S.: Debris flows recorded in the Moscardo catchment (Italian Alps) between 1990 and 2019, Nat. Hazards Earth Syst. Sci., 21, 87–97, https://doi.org/10.5194/nhess-21-87-2021, 2021. 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
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., 117, F03016, https://doi.org/10.1029/2011JF002278, 2012. a, b, c
Mitchell, A., Zubrycky, S., McDougall, S., Aaron, J., Jacquemart, M., Hübl, J., Kaitna, R., and Graf, C.: Variable hydrograph inputs for a numerical debris-flow runout model, Nat. Hazards Earth Syst. Sci., 22, 1627–1654, https://doi.org/10.5194/nhess-22-1627-2022, 2022. a
Nagl, G., Hübl, J., and Kaitna, R.: Stress anisotropy in natural debris flows during impacting a monitoring structure, Landslides, 19, 211–220, 2022. a
Navratil, O., Liébault, F., Bellot, H., Theule, J., Ravanat, X., Ousset, F., Laigle, D., Segel, V., and Fiquet, M.: Installation d'un suivi en continu des crues et laves torrentielles dans les Alpes françaises, Journée de Rencontre sur les Dangers Naturels, Institut de Géomatique et d'Analyse du Risque, 8 pp., https://hal.science/hal-00615484 (last access: 17 March 2023), 2011. a
Ng, C. W. W., Liu, H., Choi, C. E., Kwan, J. S. H., and Pun, W. K.: Impact dynamics of boulder-enriched debris flow on a rigid barrier, J. Geotech. Geoenviron., 147, 04021004, https://doi.org/10.1061/(ASCE)GT.1943-5606.0002485, 2020. a, b
Piton, G., Berthet, J., Bel, C., Fontaine, F., Bellot, H., Malet, E., Astrade, L., Recking, A., Liebault, F., Astier, G., Juppet, M., and Royer, K.: Dynamique géomorphologique des torrents: intérêt de l’emploi des appareils photographiques automatiques, Collection EDYTEM,
in: Monitoring en milieux naturels – Retours d'expériences en terrains difficiles, Collection EDYTEM. Cahiers de géographie, 19, 205–212, https://hal.archives-ouvertes.fr/hal-01635571, 2017. a
Simoni, A., Bernard, M., Berti, M., Boreggio, M., Lanzoni, S., Stancanelli, L. M., and Gregoretti, C.: Runoff-generated debris flows: Observation of initiation conditions and erosion–deposition dynamics along the channel at Cancia (eastern Italian Alps), Earth Surf. Proc. Land., 45, 3556–3571, https://doi.org/10.1002/esp.4981, 2020.
a, b
Suwa, H., Okano, K., and Kanno, T.: Forty years of debris flow monitoring at Kamikamihorizawa Creek, Mount Yakedake, Japan, in: 5th international conference on debris-flow hazards mitigation: mechanics, prediction and assessment, Casa Editrice UniversitaLa Sapienza, Roma, 605–613, https://doi.org/10.4408/IJEGE.2011-03.B-066, 2011. a
Takahashi, T.: Debris flow: mechanics, prediction and countermeasures, 2nd edn. CRC Press, ISBN 978-1138000070, 2014. a
Theule, J. I., Liébault, F., Loye, A., Laigle, D., and Jaboyedoff, M.: Sediment budget monitoring of debris-flow and bedload transport in the Manival Torrent, SE France, Nat. Hazards Earth Syst. Sci., 12, 731–749, https://doi.org/10.5194/nhess-12-731-2012, 2012. a
Theule, J. I., Liébault, F., Laigle, D., Loye, A., and Jaboyedoff, M.: Channel scour and fill by debris flows and bedload transport, Geomorphology, 243, 92–105, https://doi.org/10.1016/j.geomorph.2015.05.003, 2015. a, b
Short summary
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.
Debris flows are fast flows most often found in torrential watersheds. They are composed of two...
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