Articles | Volume 15, issue 10
https://doi.org/10.5194/nhess-15-2369-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-2369-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Oct 2015
Research article |
| 22 Oct 2015
Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study
R. Schlögel
Institut de Physique du Globe de Strasbourg, UMR7516, Université de Strasbourg/EOST, CNRS, 5 rue René Descartes, 67084 Strasbourg, CEDEX, France
now at: Institute for Applied Remote Sensing, EURAC, Viale Druso 1, 39100 Bolzano, Italy
J.-P. Malet
Institut de Physique du Globe de Strasbourg, UMR7516, Université de Strasbourg/EOST, CNRS, 5 rue René Descartes, 67084 Strasbourg, CEDEX, France
P. Reichenbach
CNR-IRPI, via Madonna Alta 126, 06128 Perugia, Italy
A. Remaître
Institut de Physique du Globe de Strasbourg, UMR7516, Université de Strasbourg/EOST, CNRS, 5 rue René Descartes, 67084 Strasbourg, CEDEX, France
C. Doubre
Institut de Physique du Globe de Strasbourg, UMR7516, Université de Strasbourg/EOST, CNRS, 5 rue René Descartes, 67084 Strasbourg, CEDEX, France
Related authors
No articles found.
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
Short summary
Short summary
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.
Floriane Provost, Dimitri Zigone, Emmanuel Le Meur, Jean-Philippe Malet, and Clément Hibert
The Cryosphere, 18, 3067–3079, https://doi.org/10.5194/tc-18-3067-2024, https://doi.org/10.5194/tc-18-3067-2024, 2024
Short summary
Short summary
The recent calving of Astrolabe Glacier in November 2021 presents an opportunity to better understand the processes leading to ice fracturing. Optical-satellite imagery is used to retrieve the calving cycle of the glacier ice tongue and to measure the ice velocity and strain rates in order to document fracture evolution. We observed that the presence of sea ice for consecutive years has favoured the glacier extension but failed to inhibit the growth of fractures that accelerated in June 2021.
Clément Hibert, François Noël, David Toe, Miloud Talib, Mathilde Desrues, Emmanuel Wyser, Ombeline Brenguier, Franck Bourrier, Renaud Toussaint, Jean-Philippe Malet, and Michel Jaboyedoff
Earth Surf. Dynam., 12, 641–656, https://doi.org/10.5194/esurf-12-641-2024, https://doi.org/10.5194/esurf-12-641-2024, 2024
Short summary
Short summary
Natural disasters such as landslides and rockfalls are mostly difficult to study because of the impossibility of making in situ measurements due to their destructive nature and spontaneous occurrence. Seismology is able to record the occurrence of such events from a distance and in real time. In this study, we show that, by using a machine learning approach, the mass and velocity of rockfalls can be estimated from the seismic signal they generate.
Luca Schilirò, Mauro Rossi, Federica Polpetta, Federica Fiorucci, Carolina Fortunato, and Paola Reichenbach
Nat. Hazards Earth Syst. Sci., 23, 1789–1804, https://doi.org/10.5194/nhess-23-1789-2023, https://doi.org/10.5194/nhess-23-1789-2023, 2023
Short summary
Short summary
We present a database of the main scientific articles published on earthquake-triggered landslides in the last 4 decades. To enhance data viewing, the articles were catalogued into a web-based GIS, which was specifically designed to show different types of information, such as bibliometric information, the relevant topic and sub-topic category (or categories), and earthquake(s) addressed. Such information can be useful to obtain a general overview of the topic, especially for a broad readership.
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700, https://doi.org/10.5194/nhess-22-3679-2022, https://doi.org/10.5194/nhess-22-3679-2022, 2022
Short summary
Short summary
Landslides and flash floods are rainfall-induced processes that often co-occur and interact, generally very quickly. In mountainous cloud-covered environments, determining when these processes occur remains challenging. We propose a regional methodology using open-access satellite radar images that allow for the timing of landslide and flash floods events, in the contrasting landscapes of tropical Africa, with an accuracy of up to a few days. The methodology shows potential for transferability.
François Noël, Michel Jaboyedoff, Andrin Caviezel, Clément Hibert, Franck Bourrier, and Jean-Philippe Malet
Earth Surf. Dynam., 10, 1141–1164, https://doi.org/10.5194/esurf-10-1141-2022, https://doi.org/10.5194/esurf-10-1141-2022, 2022
Short summary
Short summary
Rockfall simulations are often performed to make sure infrastructure is safe. For that purpose, rockfall trajectory data are needed to calibrate the simulation models. In this paper, an affordable, flexible, and efficient trajectory reconstruction method is proposed. The method is tested by reconstructing trajectories from a full-scale rockfall experiment involving 2670 kg rocks and a flexible barrier. The results highlight improvements in precision and accuracy of the proposed method.
Mauro Rossi, Txomin Bornaetxea, and Paola Reichenbach
Geosci. Model Dev., 15, 5651–5666, https://doi.org/10.5194/gmd-15-5651-2022, https://doi.org/10.5194/gmd-15-5651-2022, 2022
Short summary
Short summary
LAND-SUITE is a software package designed to support landslide susceptibility zonation. The software integrates, extends, and completes LAND-SE (Rossi et al., 2010; Rossi and Reichenbach, 2016). The software is implemented in R, a free software environment for statistical computing and graphics, and gives expert users the possibility to perform easier, more flexible, and more informed statistically based landslide susceptibility applications and zonations.
Giuseppe Esposito, Ivan Marchesini, Alessandro Cesare Mondini, Paola Reichenbach, Mauro Rossi, and Simone Sterlacchini
Nat. Hazards Earth Syst. Sci., 20, 2379–2395, https://doi.org/10.5194/nhess-20-2379-2020, https://doi.org/10.5194/nhess-20-2379-2020, 2020
Short summary
Short summary
In this article, we present an automatic processing chain aimed to support the detection of landslides that induce sharp land cover changes. The chain exploits free software and spaceborne SAR data, allowing the systematic monitoring of wide mountainous regions exposed to mass movements. In the test site, we verified a general accordance between the spatial distribution of seismically induced landslides and the detected land cover changes, demonstrating its potential use in emergency management.
A. Déprez, A. Puissant, J.-P. Malet, and D. Michéa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 677–683, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-677-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-677-2020, 2020
Michele Santangelo, Massimiliano Alvioli, Marco Baldo, Mauro Cardinali, Daniele Giordan, Fausto Guzzetti, Ivan Marchesini, and Paola Reichenbach
Nat. Hazards Earth Syst. Sci., 19, 325–335, https://doi.org/10.5194/nhess-19-325-2019, https://doi.org/10.5194/nhess-19-325-2019, 2019
Short summary
Short summary
The paper discusses the use of rockfall modelling software and photogrammetry applied to images acquired by RPAS to provide support to civil protection agencies during emergency response. The paper focuses on a procedure that was applied to define the residual rockfall risk for a road that was hit by an earthquake-triggered rockfall that occurred during the seismic sequence that hit central Italy on 24 August 2016. Road reopening conditions were decided based on the results of this study.
Floriane Provost, Jean-Philippe Malet, Clément Hibert, Agnès Helmstetter, Mathilde Radiguet, David Amitrano, Nadège Langet, Eric Larose, Clàudia Abancó, Marcel Hürlimann, Thomas Lebourg, Clara Levy, Gaëlle Le Roy, Patrice Ulrich, Maurin Vidal, and Benjamin Vial
Earth Surf. Dynam., 6, 1059–1088, https://doi.org/10.5194/esurf-6-1059-2018, https://doi.org/10.5194/esurf-6-1059-2018, 2018
Short summary
Short summary
Seismic sources generated by the deformation of unstable slopes are diverse in terms of signal properties and mechanisms. Standardized catalogues of landslide endogenous seismicity can help understanding the physical processes controlling slope dynamics. We propose a generic typology of seismic sources based on the analysis of signals recorded at various instrumented slopes. We demonstrate that the seismic signals present similar features at different sites and discuss their mechanical sources.
Odin Marc, André Stumpf, Jean-Philippe Malet, Marielle Gosset, Taro Uchida, and Shou-Hao Chiang
Earth Surf. Dynam., 6, 903–922, https://doi.org/10.5194/esurf-6-903-2018, https://doi.org/10.5194/esurf-6-903-2018, 2018
Short summary
Short summary
Rainfall-induced landslides cause significant damage and fatality worldwide, but we have few datasets constraining the impact of individual storms. We present and analyze 8 landslide inventories, with >150 to >150 00 landslides, comprehensively representing the landslide population caused by 8 storms from Asia and the Americas. We found that the total storm rainfall is a major control on total landsliding, landslide size, and that storms trigger landslides on less steep slopes than earthquakes.
O. Monserrat, A. Barra, G. Herrera, S. Bianchini, C. Lopez, R. Onori, P. Reichenbach, R. Sarro, R. M. Mateos, L. Solari, S. Ligüérzana, and I. P. Carralero
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 351–355, https://doi.org/10.5194/isprs-archives-XLII-3-W4-351-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W4-351-2018, 2018
Clément Hibert, Jean-Philippe Malet, Franck Bourrier, Floriane Provost, Frédéric Berger, Pierrick Bornemann, Pascal Tardif, and Eric Mermin
Earth Surf. Dynam., 5, 283–292, https://doi.org/10.5194/esurf-5-283-2017, https://doi.org/10.5194/esurf-5-283-2017, 2017
Massimiliano Alvioli, Ivan Marchesini, Paola Reichenbach, Mauro Rossi, Francesca Ardizzone, Federica Fiorucci, and Fausto Guzzetti
Geosci. Model Dev., 9, 3975–3991, https://doi.org/10.5194/gmd-9-3975-2016, https://doi.org/10.5194/gmd-9-3975-2016, 2016
Short summary
Short summary
Slope units are morphological mapping units bounded by drainage and divide lines that maximize within-unit homogeneity and between-unit heterogeneity. We use r.slopeunits, a software for the automatic delination of slope units. We outline an objective procedure to optimize the software input parameters for landslide susceptibility (LS) zonation. Optimization is achieved by maximizing an objective function that simultaneously evaluates terrain aspect segmentation quality and LS model performance.
Mauro Rossi and Paola Reichenbach
Geosci. Model Dev., 9, 3533–3543, https://doi.org/10.5194/gmd-9-3533-2016, https://doi.org/10.5194/gmd-9-3533-2016, 2016
Short summary
Short summary
Landslide susceptibility maps show places where landslides may occur in the future. These maps are prepared using different approaches, information on past landslides distribution and a variety of geo-environmental data. The paper describes LAND-SE (LANDslide Susceptibility Evaluation), an open-source software coded in R for statistically based susceptibility zonation that provides estimates of model performances and uncertainty. A user guide and example data are distributed with the software.
C. Lissak, O. Maquaire, J.-P. Malet, F. Lavigne, C. Virmoux, C. Gomez, and R. Davidson
Nat. Hazards Earth Syst. Sci., 15, 1399–1406, https://doi.org/10.5194/nhess-15-1399-2015, https://doi.org/10.5194/nhess-15-1399-2015, 2015
Short summary
Short summary
The objective of this paper is to demonstrate the applicability of ground-penetrating radar (GPR) for monitoring the displacement of permanent slow-moving landslides affected by seasonal kinematic pattern and acceleration events. GPR data are used here to estimate the vertical movement of two rotational slides, since 1982, in combination with other surveying techniques.
D. M. Krzeminska, T. A. Bogaard, T.-H. Debieche, F. Cervi, V. Marc, and J.-P. Malet
Earth Surf. Dynam., 2, 181–195, https://doi.org/10.5194/esurf-2-181-2014, https://doi.org/10.5194/esurf-2-181-2014, 2014
V. K. Dang, C. Doubre, C. Weber, N. Gourmelen, and F. Masson
Nat. Hazards Earth Syst. Sci., 14, 657–674, https://doi.org/10.5194/nhess-14-657-2014, https://doi.org/10.5194/nhess-14-657-2014, 2014
D. M. Krzeminska, T. A. Bogaard, J.-P. Malet, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 17, 947–959, https://doi.org/10.5194/hess-17-947-2013, https://doi.org/10.5194/hess-17-947-2013, 2013
Related subject area
Landslides and Debris Flows Hazards
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
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)
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
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
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 on GLOF modelling results using the state-of-the-art modelling code, r.avaflow
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
Brief Communication: Weak correlation between building damage and loss of life from landslides
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)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Ardizzone, F., Cardinali, M., Carrara, A., Guzzetti, F., and Reichenbach, P.: Impact of mapping errors on the reliability of landslide hazard maps, Nat. Hazards Earth Syst. Sci., 2, 3–14, https://doi.org/10.5194/nhess-2-3-2002, 2002.
Ardizzone, F., Cardinali, M., Galli, M., Guzzetti, F., and Reichenbach, P.: Identification and mapping of recent rainfall-induced landslides using elevation data collected by airborne Lidar, Nat. Hazards Earth Syst. Sci., 7, 637–650, https://doi.org/10.5194/nhess-7-637-2007, 2007.
Baynes, F. J., Lee, I. K., and Stewart, I. E.: A study of the accuracy and precision of some landslide risk analyses, Aust. Geomech., 37, 149–156, 2002.
Bell, R., Petschko, H., Röhrs, M., and Dix, A.: Assessment of landslide age, landslide persistence and human impact using airborne laser scanning digital terrain models, Geogr. Anna. A, 94, 135–156, 2012.
Brardinoni, F., Slaymaker, O., and Hassan, M. A.: Landslide inventory in a rugged forested watershed: a comparison between air-photo and field survey data, Geomorphology, 54, 179–196, 2003.
Campbell, R. H.: Isopleth map of landslide deposits, Point Dume quadrangle, Los Angeles County, California, an experiment in generalizing and quantifying areal distribution of landslides: U.S. Geological Survey Miscellaneous Field Studies Map MF-535, scale 1 : 24 000, 1973.
Canuti, P., Casagli, N., Ermini, L., Fanti, R. and Farina, P.: Landslide activity as a geoindicator in Italy: significance and new perspectives from remote sensing, Environ. Geol., 45, 907–919, 2004.
Carrara, A., Cardinali, M., and Guzzetti, F.: Uncertainty in assessing landslide hazard and risk, ITC J., 2, 172–183, 1992.
Cascini, L., Fornaro, G., and Peduto, D.: Analysis at medium scale of low-resolution DInSAR data in slow-moving landslide-affected areas, ISPRS J. Photogramm., 64, 598–611, 2009.
Coe, J. A., Michael, J. A., Crovelli, R. A., and Savage, W. Z.: Preliminary map showing landslide densities, mean recurrence intervals, and exceedance probabilities as determined from historic records, Seattle, Washington, USA. USGS Open-File Report 00-0303, 2000.
Colesanti, C. and Wasowski, J.: Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry, Eng. Geol., 88, 173–199, 2006.
Corominas, J.: The angle of reach as a mobility index for small and large landslides, Can. Geotech. J., 33, 260–271, 1996.
Corominas, J., van Westen, C. J., Frattini, P., Cascini, L., Malet, J.-P., Fotopoulou, S., Catani, F., Eeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winter, M. G., Pastor, M., Ferlisi, S., Tofani, V., Hervás, J., and Smith, J. T.: Recommendations for the quantitative analysis of landslide risk, B. Eng. Geol. Environ., 73, 209–263, 2014.
Crovelli, R. A.: Probability models for estimation of number and costs of landslides. U.S. Geological Survey Open File Report 00-249, 2000.
Cruden, D. M. and Varnes, D. J.: Landslide types and processes, in: Landslides-investigations and mitigation, edited by: Turner, R. L. and Schuster, A. K., 36–75, Washington D.C., USA, 1996.
DeGraff, J. V and Canuti, P.: Using isopleth mapping to evaluate landslide activity in relation to agricultural practices, Bull. Int. Assoc. Eng. Geol., 38, 61–71, 1988.
Doin, M.-P., Lodge, F., Guillaso, S., Jolivet, R., Lasserre, C., Ducret, G., Grandin, R., Pathier, E., and Pinel, V.: Presentation of the small baseline processing chain on a case example: the Etna deformation monitoring from 2003 to 2010 using ENVISAT data, in Proc. "Fringe 2011 Workshop", Frascati, Italy, 19–23 September 2011, p. 7., 2011.
Flageollet, J.-C., Maquaire, O., Martin, B., and Weber, D.: Landslides and climatic conditions in the Barcelonnette and Vars basins (Southern French Alps, France), Geomorphology, 30, 65–78, 1999.
Florsheim, J. L. and Nichols, A.: Landslide area probability density function statistics to assess historical landslide magnitude and frequency in coastal California, Catena, 109, 129–138, 2013.
Galli, M., Ardizzone, F., Cardinali, M., Guzzetti, F. and Reichenbach, P.: Comparing landslide inventory maps, Geomorphology, 94, 268–289, 2008.
Günther, A., Reichenbach, P., Malet, J.-P., Eeckhaut, M., Hervás, J., Dashwood, C., and Guzzetti, F.: Tier-based approaches for landslide susceptibility assessment in Europe, Landslides, 10, 529–546, 2013.
Guzzetti, F., Cardinali, M., and Reichenbach, P.: Map of sites historically affected by landslides and floods, The AVI Project, CNR Gruppo Nazionale per la Difesa dalle Catastrofi Idrogeologiche Publication number 1356, scale 1 : 1 200 000, 1996.
Guzzetti, F., Cardinali, M., Reichenbach, P., and Carrara, A.: Comparing landslide maps: a case study in the upper Tiber River Basin, Central Italy, Environ. Manage., 25, 247–363, 2000.
Guzzetti, F., Malamud, B. D., Turcotte, D. L., and Reichenbach, P.: Power-law correlations of landslide areas in central Italy, Earth Planet. Sc. Lett., 195, 169–183, 2002.
Guzzetti, F., Reichenbach, P., Cardinali, M., Ardizzone, F., and Galli, M.: The impact of landslides in the Umbria region, central Italy, Nat. Hazards Earth Syst. Sci., 3, 469–486, https://doi.org/10.5194/nhess-3-469-2003, 2003.
Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F.: Probabilistic landslide hazard assessment at the basin scale, Geomorphology, 72, 272–299, 2005.
Guzzetti, F., Galli, M., Reichenbach, P., Ardizzone, F., and Cardinali, M.: Landslide hazard assessment in the Collazzone area, Umbria, Central Italy, Nat. Hazards Earth Syst. Sci., 6, 115–131, https://doi.org/10.5194/nhess-6-115-2006, 2006.
Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., and Chang, K.-T.: Landslide inventory maps: new tools for an old problem, Earth-Science Rev., 112, 42–66, 2012.
Haneberg, W. C., Cole, W. F., and Kasali, G.: High-resolution lidar-based landslide hazard mapping and modeling, UCSF Parnassus Campus, San Francisco, USA, B. Eng. Geol. Environ., 68, 263–276, 2009.
Hanssen, R. F.: Radar interferometry: data interpretation and error analysis, Kluwer, Academic Publishers, Dordrecht, the Netherlands, 308 pp., 2001.
Jorda, M.: Morphogenèse et évolution des paysages des Alpes de Haute-Provence depuis le Tardiglaciaire. Facteurs naturels et facteurs anthropiques, Bull. de l'Association des Géographes Français, 472, 295–304, 1980.
Lopez-Saez, J., Corona, C., Stöffel, M., Astrade, L., Berger, F., and Malet, J.-P.: Dendrogeomorphic reconstruction of past landslide reactivation with seasonal precision: the Bois Noir landslide, southeast French Alps, Landslides, 9, 189–203, 2011.
Lopez-Saez, J., Corona, C., Stöffel, M., Schoeneich, P., and Berger, F.: Probability maps of landslide reactivation derived from tree-ring records: Pra Bellon landslide, Southern French Alps, Geomorphology, 138, 189–202, 2012.
Lopez-Saez, J., Corona, C., Stöffel, M., and Berger, F.: High-resolution fingerprints of past landsliding and spatially explicit, probabilistic assessment of future reactivations: Aiguettes landslide, southeastern French Alps, Tectonophysics, 602, 355–369, 2013.
Lu, P., Casagli, N., Catani, F., and Tofani, V.: Persistent Scatterers Interferometry Hotspot and Cluster Analysis (PSI-HCA) for detection of extremely slow-moving landslides, Int. J. Remote Sens., 33, 466–489, 2012.
Malamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P.: Landslide inventories and their statistical properties, Earth Surf. Processes, 29, 687–711, 2004.
Malet, J.-P.: Les "glissements de type écoulement" dans les marnes noires des Alpes du Sud. Morphologie, fonctionnement et mode\`ilisation hydro-me\`icanique, PhD Thesis, University Louis Pasteur, Strasbourg, France, 2003.
Malet, J.-P., van Asch, T. W. J., van Beek, R., and Maquaire, O.: Forecasting the behaviour of complex landslides with a spatially distributed hydrological model, Nat. Hazards Earth Syst. Sci., 5, 71–85, https://doi.org/10.5194/nhess-5-71-2005, 2005a.
Malet, J.-P., Laigle, D., Remaître, A., and Maquaire, O.: Triggering conditions and mobility of debris flows associated to complex earthflows, Geomorphology, 66, 215–235, 2005b.
Marchesini, I., Santangelo, M., Fiorucci, F., Cardinali, M., Rossi, M., and Guzzetti, F.: A GIS method for obtaining geologic bedding attitude, in: Landslide Science and Practice, edited by: Margottini, C., Canuti, P., and Sassa, K., Springer, Berlin, Heidelberg, Germany, 243–247, 2013.
Martha, T. R., Kerle, N., Jetten, V., van Westen, C. J., and Kumar, K. V.: Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods, Geomorphology, 116, 24–36, 2010.
Maquaire, O., Malet, J.-P., Remaître, A., Locat, J., Klotz, S., and Guillon, J.: Instability conditions of marly hillslopes: towards landsliding or gullying? The case of the Barcelonnette Basin, South East France, Eng. Geol., 70, 109–130, 2003.
McCalpin, J.: Preliminary age classification of landslides for inventory mapping, Proc. Annu. Symp. Eng. Geol. Soil Eng., 21, 99–111, 1984.
Metternicht, G., Hurni, L., and Gogu, R.: Remote sensing of landslides: an analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments, Remote Sens. Environ., 98, 284–303, 2005.
Razak, K. A., Straatsma, M. W., van Westen, C. J., Malet, J.-P., and de Jong, S. M.: Airborne laser scanning of forested landslides characterization: terrain model quality and visualization, Geomorphology, 126, 186–200, 2011.
Razak, K. A., Santangelo, M., van Westen, C. J., Straatsma, M. W., and de Jong, S. M.: Generating an optimal DTM from airborne laser scanning data for landslide mapping in a tropical forest environment, Geomorphology, 190, 112–125, 2013.
Reichenbach, P., Guzzetti, F., and Cardinali, M.: Map of sites historically affected by landslides and floods in Italy, 2nd edition, CNR GNDCI publication n. 1786, Rome, Italy, scale 1 : 1 200 000, 1998.
Remaître, A., Malet, J., Maquaire, O., Ancey, C., and Locat, J.: Flow behaviour and runout modelling of a complex debris flow in a clay-shale basin, Earth Sci. Rev., 30, 479–488, 2005.
Rosen, P. A., Hensley, S., Peltzer, G., and Simons, M.: Updated repeat orbit interferometry package released, Eos, Trans. Am. Geophys. Union, 85, 47–47, 2004.
Rossi, M., Ardizzone, F., Cardinali, M., Fiorucci, F., Marchesini, I., Mondini, A. C., Santangelo, M., Ghosh, S., Riguer, D. E. L., Lahousse, T., Chang, K. T., and Guzzetti, F.: A tool for the estimation of the distribution of landslide area in R, Geophys. Res. Abstr., 14, EGU2012–9438–1, 2012.
Salomé, A. I. and Beukenkamp, P.: Geomorphological mapping of a high-mountain area in black and white, Z. Geomorphol., 33, 19–23, 1989.
Salvati, P., Guzzetti, F., Reichenbach, P., Cardinali, M., and Stark, C. P.: Map of landslides and floods with human consequences in Italy. CNR GNDCI publication n. 2822, Rome, Italy, scale 1 : 1 200 000, 2003.
Santangelo, M., Marchesini, I., Bucci, F., Cardinali, M., Fiorucci, F., and Guzzetti, F.: An approach to reduce mapping errors in the production of landslide inventory maps, Nat. Hazards Earth Syst. Sci., 15, 2111–2126, https://doi.org/10.5194/nhess-15-2111-2015, 2015.
Schlögel, R., Torgoev, I., De Marneffe, C., and Havenith, H.-B.: Evidence of a changing size-frequency distribution of landslides in the Kyrgyz Tien Shan, Central Asia, Earth Surf. Processes, 36, 1658–1669, 2011.
Schlögel, R., Doubre, C., Malet, J.-P., and Masson, F.: Landslide deformation monitoring with ALOS/PALSAR imagery: a D-InSAR geomorphological interpretation method, Geomorphology, 231, 314–330, 2015.
Shannon, C. E.: Communication in the presence of noise, P. I.R.E., 37, 10–21, 1949.
Singhroy, V. and Molch, K.: Characterizing and monitoring rockslides from SAR techniques, Adv. Space. Res., 33, 290–295, 2004.
Stark, C. P. and Hovius, N.: The characterization of landslide size distributions, Geophys. Res. Lett., 28, 1091–1094, 2001.
Stien, D.: Glissements de terrains et enjeux dans la vallée de l'Ubaye et le pays de Seyne. Rapport ONF-RTM, Division de Barcelonnette, France, 2001.
Thiery, Y.: Susceptibilité du Bassin de Barcelonnette (Alpes du sud, France) aux mouvements de versant?: cartographie morphodynamique, analyse spatiale et modélisation probabiliste, Thèse de Doctorat, Université de Caen Basse-Normandie, France, 2007.
Thiery, Y., Malet, J.-P., Sterlacchini, S., Puissant, A., and Maquaire, O.: Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment, Geomorphology, 92, 38–59, 2007.
Thiery, Y., Maquaire, O., and Fressard, M.: Application of expert rules in indirect approaches for landslide susceptibility assessment, Landslides, 11, 411–424, 2014.
Travelletti, J., Malet, J.-P., and Delacourt, C.: Image-based correlation of Laser Scanning point cloud time series for landslide monitoring, Int. J. Appl. Earth Obs., 32, 1–18, 2014.
van den Eeckhaut, M., Poesen, J., Verstraeten, G., Vanacker, V., Moeyersons, J., Nyssen, J., and van Beek, L. P. H.: The effectiveness of hillshade maps and expert knowledge in mapping old deep-seated landslides, Geomorphology, 67, 351–363, 2005.
van den Eeckhaut, M., Poesen, J., Govers, G., Verstraeten, G., and Demoulin, A.: Characteristics of the size distribution of recent and historical landslides in a populated hilly region, Earth Planet. Sc. Lett., 256, 588–603, 2007.
van den Eeckhaut, M., Hervás, J., Jaedicke, C., Malet, J.-P., Montanarella, L., and Nadim, F.: Statistical modelling of Europe-wide landslide susceptibility using limited landslide inventory data, Landslides, 9, 357–369, 2012.
Varnes, D. J.: Slope movement types and processes, in: Special Report 176: Landslides: Analysis and Control, edited by: Schuster, R. L. and Krizek, R. J., 11–33, Transportation and Road Research Board, National Academy of Science, Washington, D.C., USA, 1978.
Wills, C. J. and McCrink, T. P.: Comparing landslide inventories: the map depends on the method, Environ. Eng. Geosci., 8, 279–293, 2002.
Wolfe, M. D. and Williams, J. W.: Rates of landsliding as impacted by timber management activities in Northwestern California, Discussion Bull. Of Assoc. Eng. Geol., 24, 429–431, 1987.
Wright, R. H., Campbell, R. H. and Nilsen, T. H.: Preparation and use of isopleth maps of landslide deposits, Geology, 483–486, 1974.
ZERMOS: Carte des Zones Exposées à des Risques liés aux MOuvements du Sol et du sous-sol, Barcelonnette, 1/25 000, 1975.
Zhao, C., Lu, Z., Zhang, Q. and de la Fuente, J.: Large-area landslide detection and monitoring with ALOS / PALSAR imagery data over Northern California and Southern Oregon, USA, Remote Sens. Environ., 124, 348–359, 2012.
Short summary
The paper proposes an approach to prepare a multi-date landslide inventory for the Ubaye valley (French Alps), a complex mountainous area affected by several landslide types with different degrees of activity. The inventory covering the period 1956-2010 have been analysed in order to quantify the uncertainties associated to the mapping, to measure the evolution of morphological indicators and to estimate temporal occurrence. Evolution of landslide activity is compared to other inventory sources.
The paper proposes an approach to prepare a multi-date landslide inventory for the Ubaye valley...
Altmetrics
Final-revised paper
Preprint