Articles | Volume 20, issue 3
https://doi.org/10.5194/nhess-20-815-2020
© Author(s) 2020. 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-20-815-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Mar 2020
Research article |
| 24 Mar 2020
| 24 Mar 2020
Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model
Johnnatan Palacio Cordoba
CORRESPONDING AUTHOR
Departamento de Ingeniería Civil, Facultad de Minas, Universidad Nacional de Colombia sede Medellín, Medellín, Colombia
Martin Mergili
Geomorphological Systems and Risk Research, Department of Geography
and Regional Research, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria
Institute of Applied Geology, University of Natural Resources and
Life Sciences (BOKU), Peter-Jordan-Straße 82, 1190 Vienna, Austria
Edier Aristizábal
Departamento de Geociencias y Medio Ambiente, Facultad de Minas,
Universidad Nacional de Colombia sede Medellín, Medellín, Colombia
Related authors
No articles found.
Martin Mergili, Hanna Pfeffer, Andreas Kellerer-Pirklbauer, Christian Zangerl, and Shiva Prasad Pudasaini
EGUsphere, https://doi.org/10.5194/egusphere-2025-213, https://doi.org/10.5194/egusphere-2025-213, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We present a new version of the landslide model r.avaflow. It includes a model where different materials move on top of each other instead of mixing; a model supporting the entire range from block sliding to flowing; a model for slow-moving processes; and an interface for virtual reality visualization. Based on the results for four case studies we conclude that, at the moment, our enhancements are very useful for visualization of landslides for awareness building and environmental education.
Johannes Jakob Fürst, David Farías-Barahona, Thomas Bruckner, Lucia Scaff, Martin Mergili, Santiago Montserrat, and Humberto Peña
EGUsphere, https://doi.org/10.5194/egusphere-2024-3103, https://doi.org/10.5194/egusphere-2024-3103, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
The 1987 Parraguirre ice-rock avalanche developed into a devastating debris-flow causing loss of many lives and inflicting severe damage near Santiago, Chile. Here, we revise this event combining various observational records with modelling techniques. In this year, important snow cover coincided with warm days in spring. We further quantify the total solid volume, and forward important upward corrections for the trigger and flood volumes. Finally, river damming was key for high flow mobility.
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.
Adam Emmer, Simon K. Allen, Mark Carey, Holger Frey, Christian Huggel, Oliver Korup, Martin Mergili, Ashim Sattar, Georg Veh, Thomas Y. Chen, Simon J. Cook, Mariana Correas-Gonzalez, Soumik Das, Alejandro Diaz Moreno, Fabian Drenkhan, Melanie Fischer, Walter W. Immerzeel, Eñaut Izagirre, Ramesh Chandra Joshi, Ioannis Kougkoulos, Riamsara Kuyakanon Knapp, Dongfeng Li, Ulfat Majeed, Stephanie Matti, Holly Moulton, Faezeh Nick, Valentine Piroton, Irfan Rashid, Masoom Reza, Anderson Ribeiro de Figueiredo, Christian Riveros, Finu Shrestha, Milan Shrestha, Jakob Steiner, Noah Walker-Crawford, Joanne L. Wood, and Jacob C. Yde
Nat. Hazards Earth Syst. Sci., 22, 3041–3061, https://doi.org/10.5194/nhess-22-3041-2022, https://doi.org/10.5194/nhess-22-3041-2022, 2022
Short summary
Short summary
Glacial lake outburst floods (GLOFs) have attracted increased research attention recently. In this work, we review GLOF research papers published between 2017 and 2021 and complement the analysis with research community insights gained from the 2021 GLOF conference we organized. The transdisciplinary character of the conference together with broad geographical coverage allowed us to identify progress, trends and challenges in GLOF research and outline future research needs and directions.
Christian Zangerl, Annemarie Schneeberger, Georg Steiner, and Martin Mergili
Nat. Hazards Earth Syst. Sci., 21, 2461–2483, https://doi.org/10.5194/nhess-21-2461-2021, https://doi.org/10.5194/nhess-21-2461-2021, 2021
Short summary
Short summary
The Köfels rockslide in the Ötztal Valley (Austria) represents the largest known extremely rapid rockslide in metamorphic rock masses in the Alps and was formed in the early Holocene. Although many hypotheses for the conditioning and triggering factors were discussed in the past, until now no scientifically accepted explanatory model has been found. This study provides new data and numerical modelling results to better understand the cause and triggering factors of this gigantic natural event.
Guoxiong Zheng, Martin Mergili, Adam Emmer, Simon Allen, Anming Bao, Hao Guo, and Markus Stoffel
The Cryosphere, 15, 3159–3180, https://doi.org/10.5194/tc-15-3159-2021, https://doi.org/10.5194/tc-15-3159-2021, 2021
Short summary
Short summary
This paper reports on a recent glacial lake outburst flood (GLOF) event that occurred on 26 June 2020 in Tibet, China. We find that this event was triggered by a debris landslide from a steep lateral moraine. As the relationship between the long-term evolution of the lake and its likely landslide trigger revealed by a time series of satellite images, this case provides strong evidence that it can be plausibly linked to anthropogenic climate change.
Martin Mergili, Michel Jaboyedoff, José Pullarello, and Shiva P. Pudasaini
Nat. Hazards Earth Syst. Sci., 20, 505–520, https://doi.org/10.5194/nhess-20-505-2020, https://doi.org/10.5194/nhess-20-505-2020, 2020
Short summary
Short summary
Computer simulations of complex landslide processes in mountain areas are important for informing risk management but are at the same time challenging in terms of parameterization and physical and numerical model implementation. Using the tool r.avaflow, we highlight the progress and the challenges with regard to such simulations on the example of the Piz Cengalo–Bondo landslide cascade in Switzerland, which started as an initial rockslide–rockfall and finally evolved into a debris flow.
Martin Mergili, Shiva P. Pudasaini, Adam Emmer, Jan-Thomas Fischer, Alejo Cochachin, and Holger Frey
Hydrol. Earth Syst. Sci., 24, 93–114, https://doi.org/10.5194/hess-24-93-2020, https://doi.org/10.5194/hess-24-93-2020, 2020
Short summary
Short summary
In 1941, the glacial lagoon Lake Palcacocha in the Cordillera Blanca (Peru) drained suddenly. The resulting outburst flood/debris flow consumed another lake and had a disastrous impact on the town of Huaraz 23 km downstream. We reconstuct this event through a numerical model to learn about the possibility of prediction of similar processes in the future. Remaining challenges consist of the complex process interactions and the lack of experience due to the rare occurrence of such process chains.
Ekrem Canli, Martin Mergili, Benni Thiebes, and Thomas Glade
Nat. Hazards Earth Syst. Sci., 18, 2183–2202, https://doi.org/10.5194/nhess-18-2183-2018, https://doi.org/10.5194/nhess-18-2183-2018, 2018
Short summary
Short summary
Regional-scale landslide forecasting traditionally strongly relies on empirical approaches and landslide-triggering rainfall thresholds. Today, probabilistic methods utilizing ensemble predictions are frequently used for flood forecasting. In our study, we specify how such an approach could also be applied for landslide forecasts and for operational landslide forecasting and early warning systems. To this end, we implemented a physically based landslide model in a probabilistic framework.
Martin Mergili, Jan-Thomas Fischer, Julia Krenn, and Shiva P. Pudasaini
Geosci. Model Dev., 10, 553–569, https://doi.org/10.5194/gmd-10-553-2017, https://doi.org/10.5194/gmd-10-553-2017, 2017
Short summary
Short summary
r.avaflow represents a GIS-based, multi-functional open-source tool for the simulation of debris flows, rock avalanches, snow avalanches, or two-phase (solid and fluid) process chains. It further facilitates parameter studies and validation of the simulation results against observed patterns. r.avaflow shall inform strategies to reduce the risks related to the interaction of mass flow processes with society.
M. Mergili, J. Krenn, and H.-J. Chu
Geosci. Model Dev., 8, 4027–4043, https://doi.org/10.5194/gmd-8-4027-2015, https://doi.org/10.5194/gmd-8-4027-2015, 2015
Short summary
Short summary
r.randomwalk is a flexible and multi-functional open-source GIS tool for simulating the propagation of mass movements. Mass points are routed from given release pixels through a digital elevation model until a defined break criterion is reached. In contrast to existing tools, r.randomwalk includes functionalities to account for parameter uncertainties, and it offers built-in functions for validation and visualization. We show the key functionalities of r.randomwalk for three test areas.
M. Mergili and H.-J. Chu
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-5677-2015, https://doi.org/10.5194/nhessd-3-5677-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
We propose a procedure to compute an integrated spatial landslide probability, combining release and propagation. The zonal release probability is introduced to correct the pixel-based release probability for the size of the release zone relevant for a pixel. For a test area in Taiwan we observe that the model performs moderately well in predicting the observed landslides and that the size of the release zone influences the result to a much higher degree than the pixel-based release probability.
M. Mergili, I. Marchesini, M. Alvioli, M. Metz, B. Schneider-Muntau, M. Rossi, and F. Guzzetti
Geosci. Model Dev., 7, 2969–2982, https://doi.org/10.5194/gmd-7-2969-2014, https://doi.org/10.5194/gmd-7-2969-2014, 2014
Short summary
Short summary
The article deals with strategies to (i) reduce computation time and to (ii) appropriately account for uncertain input parameters when applying an open source GIS sliding surface model to estimate landslide susceptibility for a 90km² study area in central Italy. For (i), the area is split into a large number of tiles, enabling the exploitation of multi-processor computing environments. For (ii), the model is run with various parameter combinations to compute the slope failure probability.
F. E. Gruber and M. Mergili
Nat. Hazards Earth Syst. Sci., 13, 2779–2796, https://doi.org/10.5194/nhess-13-2779-2013, https://doi.org/10.5194/nhess-13-2779-2013, 2013
Related subject area
Landslides and Debris Flows Hazards
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
Brief communication: Visualizing uncertainties in landslide susceptibility modeling using bivariate mapping
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
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
Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico
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
From rockfall source areas identification to susceptibility zonation: a proposed workflow tested in El Hierro (Canary Islands, Spain)
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
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
Characterizing the scale of regional landslide triggering from storm hydrometeorology
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
A new analytical method for stability analysis of rock blocks with basal erosion in sub-horizontal strata by considering the eccentricity effect
Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
Characteristics of debris flows recorded in the Shenmu area of central Taiwan between 2004 and 2021
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
The role of thermokarst evolution in debris flow initiation (Hüttekar Rock Glacier, Austrian Alps)
Accounting for the effect of forest and fragmentation in probabilistic rockfall hazard
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.
Matthias Schlögl, Anita Graser, Raphael Spiekermann, Jasmin Lampert, and Stefan Steger
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-213, https://doi.org/10.5194/nhess-2024-213, 2024
Revised manuscript accepted for NHESS
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.
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.
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.
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-141, https://doi.org/10.5194/nhess-2024-141, 2024
Revised manuscript accepted for NHESS
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. We develop methods to identify potential runout zones from landslides. We apply our methods to create susceptibility maps for three study areas in Puerto Rico and assess the success of our methods based on mapped landslides from Hurricane Maria.
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.
Roberto Sarro, Mauro Rossi, Paola Reichenbach, and Rosa María Mateos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-85, https://doi.org/10.5194/nhess-2024-85, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study proposes a novel workflow to precisely model rockfalls. It compares three methods for defining source areas to enhance model accuracy. Identified areas are inputted into a runout model to identify vulnerable zones. A new approach generates probabilistic susceptibility maps using ECDFs. Validation strategies employing various inventory types are included. Comparing six susceptibility maps highlights the impact of source area definition on model precision.
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.
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.
Jonathan P. Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
EGUsphere, https://doi.org/10.5194/egusphere-2024-873, https://doi.org/10.5194/egusphere-2024-873, 2024
Short summary
Short summary
Landslides are a global issue that results in deaths and economic losses annually. However, it is not clear how storm severity relates to landslide severity across large regions. Here we develop a method to estimate the footprint of landslide area and compare this to meteorologic estimates of storm severity. We find that total storm strength does not clearly relate to landslide area. Rather, landslide area depends on soil wetness and smaller storm structures that can produce intense rainfall.
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.
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.
Yi-Min Huang
Nat. Hazards Earth Syst. Sci., 23, 2649–2662, https://doi.org/10.5194/nhess-23-2649-2023, https://doi.org/10.5194/nhess-23-2649-2023, 2023
Short summary
Short summary
Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
Short summary
Short summary
We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
Simon Seelig, Thomas Wagner, Karl Krainer, Michael Avian, Marc Olefs, Klaus Haslinger, and Gerfried Winkler
Nat. Hazards Earth Syst. Sci., 23, 2547–2568, https://doi.org/10.5194/nhess-23-2547-2023, https://doi.org/10.5194/nhess-23-2547-2023, 2023
Short summary
Short summary
A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.
Camilla Lanfranconi, Paolo Frattini, Gianluca Sala, Giuseppe Dattola, Davide Bertolo, Juanjuan Sun, and Giovanni Battista Crosta
Nat. Hazards Earth Syst. Sci., 23, 2349–2363, https://doi.org/10.5194/nhess-23-2349-2023, https://doi.org/10.5194/nhess-23-2349-2023, 2023
Short summary
Short summary
This paper presents a study on rockfall dynamics and hazard, examining the impact of the presence of trees along slope and block fragmentation. We compared rockfall simulations that explicitly model the presence of trees and fragmentation with a classical approach that accounts for these phenomena in model parameters (both the hazard and the kinetic energy change). We also used a non-parametric probabilistic rockfall hazard analysis method for hazard mapping.
Cited articles
Ameratunga, J., Sivakugan, N., and Das, B. M.: Correlations for Laboratory Test Parameters, in: Correlations of Soil and Rock Properties in Geotechnical Engineering, Springer, New Delhi, https://doi.org/10.1007/978-81-322-2629-1_3, 51–86, 2016.
Anderson, S. A. and Sitar, N.: Analysis of Rainfall-Induced Debris Flows, J. Geotech. Eng., 121, 544–552, https://doi.org/10.1061/(ASCE)0733-9410(1995)121:7(544), 1995.
Aristizábal, E. and Gómez, J.: Inventario De Emergencias Y Desastres En El Valle De Aburrá. Originados Por Fenómenos Naturales Y Antropicos En El Periodo 1880-2007, Gestión y Ambiente, 10, 17–30, 2007.
Aristizábal, E., Roser, B., and Yokota, S.: Tropical chemical weathering
of hillslope deposits and bedrock source in the Aburrá Valley, northern
Colombian Andes, Eng. Geol., 81, 389–406, https://doi.org/10.1016/j.enggeo.2005.08.001, 2005.
Aristizábal, E.: SHIA_Landslide: Developing a physically based model to predict shallow landslides triggered by rainfall in tropical environments, Universidad Nacional de Colombia, 2013.
Aristizábal, E., García, E., and Martínez, H.: Susceptibility
assessment of shallow landslides triggered by rainfall in tropical basins
and mountainous terrains, Nat. Hazards, 78, 621–634, https://doi.org/10.1007/s11069-015-1736-4, 2015.
Aristizábal, E., Vélez, J. I., Martínez, H. E., and Jaboyedoff,
M.: SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins, Landslides, 13, 497–517, https://doi.org/10.1007/s10346-015-0580-7, 2016.
Aristizábal, E., García, E., and Martínez, H.: Modelling Shallow Landslides Triggered by Rainfall in Tropical and Mountainous Basins, in: Advancing Culture of Living with Landslides, WLF 2017, edited by: Mikoš, M., Casagli, N., Yin, Y., and Sassa, K., Springer, Cham, https://doi.org/10.1007/978-3-319-53485-5_23, 207–212, 2017.
Baligh, M. M. and Azzouz, A. S.: End Effects of Stability of Cohesive Slopes, Geotech. Eng. Div.-ASCE, 101, 1105–1117, 1975.
Baum, R. L., Godt, J. W., and Savage, W. Z.: Estimating the timing and location of shallow rainfall-induced landslides using a model for
transient, unsaturated infiltration, J. Geophys. Res., 115, F03013,
https://doi.org/10.1029/2009JF001321, 2010.
Bishop, A. W.: The use of the Slip Circle in the Stability Analysis of
Slopes, Géotechnique, 5, 7–17, https://doi.org/10.1680/geot.1955.5.1.7, 1954.
Bout, B., Lombardo, L., van Westen, C. J., and Jetten, V. G.: Integration of two-phase solid fluid equations in a catchment model for flashfloods, debris flows and shallow slope failures, Environ. Model. Softw., 105, 1–16,
https://doi.org/10.1016/j.envsoft.2018.03.017, 2018.
Canli, E., Loigge, B., and Glade, T.: Spatially distributed rainfall information and its potential for regional landslide early warning systems,
Nat. Hazards, 91, 103–127, https://doi.org/10.1007/s11069-017-2953-9, 2017.
Carrara, A.: Multivariate models for landslide hazard evaluation, J. Int. Assoc. Math. Geol., 15, 403–426, https://doi.org/10.1007/BF01031290, 1983.
Carrara, A., and Pike, R. J.: GIS technology and models for assessing
landslide hazard and risk, Geomorphology, 94, 257–260,
https://doi.org/10.1016/j.geomorph.2006.07.042, 2008.
Carson, M. and Kirkby, M.: Hillslope Form and Process, Cambridge University,
Cambridge, https://doi.org/10.1017/S0016756800000546, 1972.
Catani, F., Segoni, S., and Falorni, G.: An empirical geomorphology-based
approach to the spatial prediction of soil thickness at catchment scale,
Water Resour. Res., 46, 1–15, https://doi.org/10.1029/2008WR007450, 2010.
Cervi, F., Berti, M., Borgatti, L., Ronchetti, F., Manenti, F., and Corsini, A.: Comparing predictive capability of statistical and deterministic methods for landslide susceptibility mapping: A case study in the northern Apennines (Reggio Emilia Province, Italy), Landslides, 7, 433–444, https://doi.org/10.1007/s10346-010-0207-y, 2010.
Chen, R. H. and Chameau, J.: Three-dimensional limit equilibrium analysis of slopes, Géotechnique, 33, 31–40, https://doi.org/10.1680/geot.1983.33.1.31, 1983.
Chowdhury, R., Flentje, P., and Bhattacharya, G.: Geotechnical Slope Analysis, CRC Press, London, https://doi.org/10.1201/9780203864203, 2009.
Christian, J. T., and Baecher, G. B.: Discussion of “Factors of Safety and
Reliability in Geotechnical Engineering”, J. Geotech. Geoenviron. Eng., 127,
700–721, https://doi.org/10.1061/(ASCE)1090-0241(2001)127:8(700), 2001.
Corominas, J., Van Westen, C. J., Frattini, P., Cascini, L., Malet, J.-P., Fotopoulou, S., Catani, F., Van Den 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, Bull. Eng. Geol. Environ., 73, 209–263,
https://doi.org/10.1007/s10064-013-0538-8, 2014.
Crosta, G.: Regionalization of rainfall thresholds: an aid to landslide
hazard evaluation, Environ. Geol., 35, 131–145, https://doi.org/10.1007/s002540050300, 1998.
Crozier, M.: Landslides: Causes, Consequences And Environment, Helm, London, p. 252, https://doi.org/10.1111/j.1745-7939.1989.tb01143.x, 1986.
Dennhardt, M. and Forster, W.: Problems of Three Dimensional Slope Stability, in: The 11th International Conference in Soil Mechanics and Foundation Engineering, Part 2, San Francisco, 427–431, 1985.
Dietrich, W. E. and Montgomery, D. R.: SHALSTAB: a digital terrain model for mapping shallow landslide potential,Berkeley Geomorphology Group, 26 pp., 1998.
Dilley, M., Chen, R. S., Deichmann, U., Lener-Lam, A. L., and Arnold, M.: Natural Disaster Hotspots A Global Risk Analysis, World Bank Hazard Management Unit, Washington, D.C., https://doi.org/10.1596/0-8213-5930-4, 2005.
Duncan, J. M. and Wright, S. G.: Soil Strength and Slope Stability, John Wiley & Sons, New York, 2005.
EM-DAT – The International Disaster Database: The OFDA/CRED International Disaster Database, available at: https://www.emdat.be/ (last access: 17 August 2018), 2011.
Fawcett, T.: An introduction to ROC analysis, Pattern Recognit. Lett., 27, 861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Fellenius, W.: Erdstatische Berechnungen mit Reibung und Kohäsion (Adhäsion) und unter Annahme kreiszylindrischer Gleitflächen, Ernst and Sohn, Berlin, 1927.
Fenton, G. A. and Griffiths, D. V.: Review of Probability Theory, in: Risk Assessment in Geotechnical Engineering, John Wiley & Sons, Inc., Hoboken, New Jersey, 1–69, https://doi.org/10.1002/9780470284704.ch1, 2008.
Fressard, M., Olivier, M., Thiery, Y., Davidson, R., and Lissak, C.:
Multi-method characterisation of an active landslide: Case study in the Pays
d'Auge plateau (Normandy, France), Geomorphology, 270, 22–39, https://doi.org/10.1016/j.geomorph.2016.07.001, 2016.
Garcia, G.: Daños Ocurridos en la central hidroelectrica de Calderas por
la avalancha en la quebrada La Arenosa, I Taller Latinoamericano Reducción de Los Efectos de Los Desastres Naturales En Infraestructura Energetica, San José, Costa Rica, 13 pp., 1995.
Geotechdata: GeoParameter, available at:
http://www.geotechdata.info/parameter/parameter.html (last access: 9 May 2018), 2013.
Gorsevski, P. V., Gessler, P., and Foltz, R. B.: Spatial Prediction of Landslide Hazard Using Discriminant Analysis and GIS, in: 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Problems, Prospects and Research Needs, 2–8 September 2000, Banff, Alberta, 10 pp., 2000.
GRASS Team: GRASS Development Team 2011, Geographic Resources Analysis Support System (GRASS) Software, Open Source Geospatial Foundation Project,
available at: http://grass.osgeo.org (last access: 7 November 2018), 2019.
Griffiths, D. V., Huang, J., and Fenton, G. A.: Risk assessment in geotechnical engineering: Stability analysis of highly variable soils, Geotech. Spec. Publ., 226, 78–101, https://doi.org/10.1061/9780784412138.0004, 2012.
Guzzetti, F.: Forecasting natural hazards, performance of scientists, ethics, and the need for transparency, Toxicol. Environ. Chem., 98, 1043–1059, https://doi.org/10.1080/02772248.2015.1030664, 2016.
Hermelin, M., Mejía, O., and Velásquez, E.: Erosional and depositional features produced by a convulsive event, San Carlos, Colombia,
September 21, 1990, Bull. Int. Assoc. Eng. Geol., 45, 89–95, https://doi.org/10.1007/BF02594908, 1992.
Hovland, H. J.: Three-dimensional slope stability analysis method, Geotech. Eng. Div.-ASCE, 103, 971–986, 1997.
Hungr, O.: CLARA: Slope Stability Analysis in Two or Three Dimensions, O. Hungr Geotechnical Research, Inc., Vancouver, BC, 1988.
Hungr, O., Leroueil, S., and Picarelli, L.: The Varnes classification of landslide types, an update, Landslides, 11, 167–194, https://doi.org/10.1007/s10346-013-0436-y, 2014.
IDEAM: Climagramas Antioquia, available at:
http://atlas.ideam.gov.co/basefiles/antioquia_graf.pdf (last access: 26 September 2018), 2010.
IGAC: Estudio general de suelos y zonificación de tierras del departamento de Antioquia, Instituto Geográfico Agustín Codazzi, Bogotá, p. 207, 2007.
INTEGRAL: Informe sobre daños en la central de calderas por la avalancha ocurrida en l quebrada La Arenosa el 21 de septiembre de 1990 y su reparación, Internal Report, Interconexión eléctrica S.A. ISA, 1990.
Kalatehjari, R. and Ali, N.: A review of three-dimensional slope stability
analyses based on limit equilibrium method, Elect. J. Geotech. Eng., 18, 119–134, 2013.
Keefer, D. K., Wilson, R. C., Mark, R. K., Brabb, E. E., William, M., Ellen, S. D., Harp, E. L., Wieczorek, G. F., Alger, C. S., Robert, S., Brown III, W., and Zatkin, R. S.: Real-Time During Warning Landslide Rainfall Heavy, Science, 238, 921–925, 1987.
Kellogg, J. N., Vega, V., Stailings, T. C., and Aiken, C. L. V.: Tectonic development of Panama, Costa Rica, and the Colombian Andes Constraints from Global Positioning System geodetic studies and gravity, in: Geologic and Tectonic Development of the Caribbean Plate Boundary in Southern Central America, Geological Society Special Papers, Boulder, Colorado, 75–90,
https://doi.org/10.1130/SPE295-p75, 1995.
King, G. J. W.: Revision of effective-stress method of slices, Géotechnique, 39, 497–502, 1989.
Kirschbaum, D., Stanley, T., and Zhou, Y.: Spatial and temporal analysis of a global landslide catalog, Geomorphology, 249, 4–15,
https://doi.org/10.1016/j.geomorph.2015.03.016, 2015.
Kirsten, H. A. D.: Significance of the Probability of Failure in Slope Engineering, Civ. Eng. S. Afr. – S. Afr. Inst. Civ. Eng., 25, 17–27, 1983.
Kjekstad, O. and Highland, L.: Economic and Social Impacts of Landslides, in: Landslides – Disaster Risk Reduction, edited by: Sassa, K. and Canut, P., Springer, Berlin, Heidelberg, Germany, 573–587, https://doi.org/10.1007/978-3-540-69970-5, 2009.
Lam, L. and Fredlund, D. G.: A general limit equilibrium model for
three-dimensional slope stability analysis, Can. Geotech. J., 30, 905–919,
https://doi.org/10.1139/t93-089, 1993.
Lee, S.: Application and cross-validation of spatial logistic multiple regression for landslide susceptibility analysis, Geosci. J., 9, 63–71, 2005.
Lee, S. and Pradhan, B.: Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models, Landslides, 4, 33–41,
https://doi.org/10.1007/s10346-006-0047-y, 2007.
Medina-cetina, Z. and Cepeda, J.: Probabilistic classification of local rainfall-thresholds for landslide triggering, in: EGU General Assembly 2010, 2–7 May 2010, Vienna, Austria, 2010.
Mergili, M.: r.slope.stability – The open source GIS slope stability model,
available at: https://www.slopestability.org/ (last access: 20 January 2020), 2017.
Mergili, M., Marchesini, I., Alvioli, M., Metz, M., Schneider-muntau, B.,
Rossi, M., and Guzzetti, F.: A strategy for GIS-based 3-D slope stability
modelling over large areas, Geosci. Model Dev., 7, 2969–2982,
https://doi.org/10.5194/gmd-7-2969-2014, 2014a.
Mergili, M., Marchesini, I., Rossi, M., Guzzetti, F., and Fellin, W.: Spatially distributed three-dimensional slope stability modelling in a
raster GIS, Geomorphology, 206, 178–195, https://doi.org/10.1016/j.geomorph.2013.10.008, 2014b.
Mergili, M., Santiago, C., and Moreiras, S.: Causas, características e
impacto de losprocesos de remoción en masa, en áreascontrastantes de
la región Andina, Revista Colombiana De Geofrafía, 24, 113–131, 2015.
Mergili, M., Fischer, J. T., Krenn, J., and Pudasaini, S. P.: r.avaflow v1, an advanced open-source computational framework for the propagation and
interaction of two-phase mass flows, Geosci. Model Dev., 10, 553–569,
https://doi.org/10.5194/gmd-10-553-2017, 2017.
Montgomery, D. R. and Dietrich, W. E.: A physically based model for the
topographic control on shallow landsliding, Water Resour. Res., 30, 1153–1171, https://doi.org/10.1029/93WR02979, 1994.
O'Loughlin, E. M.: Prediction of Surface Saturation Zones in Natural Catchments by Topographic Analysis, Water Resour. Res., 22, 794–804,
https://doi.org/10.1029/WR022i005p00794, 1986.
Petley, D.: The global occurrence of fatal landslides in 2007, in: EGU General Assembly 2008, 13–18 April 2008, Vienna, Austria, 2008.
Petley, D.: Global patterns of loss of life from landslides, Geology, 40,
927–930, https://doi.org/10.1130/G33217.1, 2012.
Poveda, G., Vélez, J. I., Mesa, O. J., Cuartas, A., Barco, J., Mantilla, R., Mejía, J. F., Hoyos, C., Ramírez, J., Ceballos, L., Zuluaga, M., Arias, P., Botero, B., Montoya, M., Giraldo, J., and Quevedo, D.: Linking long-term water balances and statistical scaling to estimate river flows along the drainage network of Colombia, Hydrol. Eng., 12, 4–13, https://doi.org/10.1061/(ASCE)1084-0699(2007)12:1(4), 2007.
Pyke, R.: TSLOPE3: Users Guide, Taga Engineering Systems and Software, Lafeyette, CA, 1991.
Qiu, C., Xie, M., and Esaki, T.: Application of GIS Technique in Three-Dimensional Slope Stability Analysis, Comput. Mech., 3, 703–712,
https://doi.org/10.1007/978-3-540-75999-7_116, 2007.
Sanchez, O. and Aristizábal, E.: Spatial and temporal patterns and
socioeconomic impact of landslides in Colombia, in: Vol. 20, EGU General Assembly 2018, European Geosciences Union, Vienna, Austria, 2018.
Schuster, R. L. and Highland, L. M.: Socioeconomic Impacts of Landslides in the Western Hemisphere, US Geological Survey, Denver, Co, https://doi.org/10.3133/ofr01276, 2001.
Sepúlveda, S. A. and Petley, D. N.: Regional trends and controlling factors of fatal landslides in Latin America and the Caribbean, Nat. Hazards Earth Syst. Sci., 15, 1821–1833, https://doi.org/10.5194/nhess-15-1821-2015, 2015.
Stark, T. D. and Eid, H. T.: Performance of Three-Dimensional Slope Stability Methods in Geotechnical Practice, J. Geotech. Geoenviron. Eng., 124, 1049–1060, https://doi.org/10.1061/(ASCE)1090-0241(1998)124:11(1049), 1998.
Suarez, J.: Deslizamientos Y Estabilidad De Taludes En Zonas Tropicales, Instituto de Investigaciones sobre Erosión y Deslizamientos, Bucaramanga, Colombia, Universidad Industrial de Santander, Santander, 1998.
Süzen, M. L. and Doyuran, V.: Data driven bivariate landslide susceptibility assessment using geographical information systems: a method
and application to Asarsuyu catchment, Turkey, Eng. Geol., 71, 303–321,
https://doi.org/10.1016/S0013-7952(03)00143-1, 2004.
Taboada, A., Rivera, L. A., Fuenzalida, A., and Cisternas, A.: Geodynamics of the northern Andes: Subductions and intracontinental deformation (Colombia), Tectonics, 19, 787–813, https://doi.org/10.1029/2000TC900004, 2000.
Terlien, M. T. J.: The determination of statistical and deterministic hydrological landslide-triggering thresholds, Environ. Geol., 35, 124–130,
https://doi.org/10.1007/s002540050299, 1998.
Thiery, Y., Reninger, P.-A., Lacquement, F., Raingeard, A., Lombard, M., and Nachbaur, A.: Analysis of Slope Sensitivity to Landslides by a Transdisciplinary Approach in the Framework of Future Development: The Case
of La Trinité in Martinique (French West Indies), Geosciences, 7, 135, https://doi.org/10.3390/geosciences7040135, 2017.
Thiery, Y., Lacquement, F., and Marcot, N.: Landslides triggered in weathered crystalline rocks of moderate latitudes: A case study in Mediterranean environment (The Maures Massif, France), Eng. Geol., 248, 164–184, 2019.
Thomaz, J. E.: A General Method for Three Dimensional Slope Stability Analysis: Informational Report, Joint Highway Research Project, West Lafayette, IN, https://doi.org/10.5703/1288284314113, 1986.
Trenkamp, R., Kellogg, J. N., Freymueller, J. T., and Mora, H. P.: Wide plate margin deformation, southern Central America and northwestern South America, CASA GPS observations, J. S. Am. Earth Sci., 15, 157–171, https://doi.org/10.1016/S0895-9811(02)00018-4, 2002.
Van Westen, C. J. and Terlien, M. T. J.: An Approach Towards Deterministic
Landslide Hazard Analysis in GIS, a Case Study from Manizales (colombia), Earth Surf. Proc. Land., 21, 853–868, https://doi.org/10.1002/(SICI)1096-9837(199609)21:9<853::AID-ESP676>3.0.CO;2-C, 1996.
Van Westen, C. J., Soeters, R., and Sijmons, K.: Digital geomorphological landslide hazard mapping of the Alpago area, Italy, Int. J. Appl. Earth Obs. Geoinform., 2, 51–60, https://doi.org/10.1016/S0303-2434(00)85026-6, 2000.
Van Westen, C. J., van Asch, T. W. J., and Soeters, R.: Landslide hazard and
risk zonation – Why is it still so difficult?, Bull. Eng. Geol. Environ., 65, 167–184, https://doi.org/10.1007/s10064-005-0023-0, 2006.
Van Westen, C. J., Castellanos, E., and Kuriakose, S. L.: Spatial data for
landslide susceptibility, hazard, and vulnerability assessment: An overview,
Eng. Geol., 102, 112–131, https://doi.org/10.1016/j.enggeo.2008.03.010, 2008.
Varnes, D. J.: Slope Movement Types and Processes, Transportation Research Board Special Report 176, Landslides: Analysis and Control, Transportation Research Board, Washington, D.C., 11–33, 1978.
Velásquez, M. E. and Mejía, R.: Procesos y depósitos asociados al aguacero de septiembre 21 de 1990 en el Área de San Carlos (Antioquia), undergraduate thesis, Universidad Nacional de Colombia, Medellín, 1991.
Wang, G. and Sassa, K.: Pore-pressure generation and movement of rainfall-induced landslides: Effects of grain size and fine-particle content, Eng. Geol., 69, 109–125, https://doi.org/10.1016/S0013-7952(02)00268-5, 2003.
Xie, M., Esaki, T., Zhou, G., and Mitani, Y.: Geographic Information
Systems-Based Three-Dimensional Critical Slope Stability Analysis and
Landslide Hazard Assessment, J. Geotech. Geoenviron. Eng., 129, 1109–1118,
https://doi.org/10.1061/(ASCE)1090-0241(2003)129:12(1109), 2003.
Zizioli, D., Meisina, C., Valentino, R., and Montrasio, L.: Comparison
between different approaches to modeling shallow landslide susceptibility: A
case history in Oltrepo Pavese, Northern Italy, Nat. Hazards Earth Syst. Sci., 13, 559–573, https://doi.org/10.5194/nhess-13-559-2013, 2013.
Short summary
Landslides triggered by rainfall are very common phenomena in complex tropical environments such as the Colombian Andes. In this work, we perform probabilistic analyses with r.slope.stability for landslide susceptibility analysis. We test the model in the La Arenosa catchment, northern Colombian Andes. The results are compared to those yielded with the corresponding deterministic analyses and with other physically based models applied in the same catchment.
Landslides triggered by rainfall are very common phenomena in complex tropical environments such...
Altmetrics
Final-revised paper
Preprint