Articles | Volume 22, issue 3
https://doi.org/10.5194/nhess-22-1129-2022
© Author(s) 2022. 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-22-1129-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories
Robert Emberson
CORRESPONDING AUTHOR
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research II, Greenbelt, MD, USA
University of Maryland, Baltimore County, 1000 Hilltop Cir, Baltimore, MD, USA
Dalia B. Kirschbaum
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Pukar Amatya
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research II, Greenbelt, MD, USA
University of Maryland, Baltimore County, 1000 Hilltop Cir, Baltimore, MD, USA
Hakan Tanyas
ITC, University of Twente, Twente, the Netherlands
Odin Marc
Géosciences Environnement Toulouse (GET), UMR 5563,
CNRS/IRD/CNES/UPS, Observatoire Midi-Pyrénées, Toulouse, France
Related authors
Robert A. Emberson
Hydrol. Earth Syst. Sci., 27, 3547–3563, https://doi.org/10.5194/hess-27-3547-2023, https://doi.org/10.5194/hess-27-3547-2023, 2023
Short summary
Short summary
Soil can be eroded by rainfall, and this is a major threat to agricultural sustainability. Estimating the erosivity of rainfall is essential as a first step to determine how much soil might be lost. Until recently, satellite data have not been used to estimate rainfall erosivity, but the data quality is now sufficient to do so. In this study, I test several methods to calculate rainfall erosivity using satellite rainfall data and contrast this with ground-based estimates.
Robert Emberson, Dalia Kirschbaum, and Thomas Stanley
Nat. Hazards Earth Syst. Sci., 20, 3413–3424, https://doi.org/10.5194/nhess-20-3413-2020, https://doi.org/10.5194/nhess-20-3413-2020, 2020
Short summary
Short summary
Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every year, but different inventories of landslide events can have widely diverging completeness. This can lead to spatial biases in our understanding of the impacts. Here we use a globally homogeneous model of landslide hazard and exposure to provide consistent estimates of where landslides are most likely to cause damage to people, roads and other critical infrastructure at 1 km resolution.
Philip J. Ward, Veit Blauhut, Nadia Bloemendaal, James E. Daniell, Marleen C. de Ruiter, Melanie J. Duncan, Robert Emberson, Susanna F. Jenkins, Dalia Kirschbaum, Michael Kunz, Susanna Mohr, Sanne Muis, Graeme A. Riddell, Andreas Schäfer, Thomas Stanley, Ted I. E. Veldkamp, and Hessel C. Winsemius
Nat. Hazards Earth Syst. Sci., 20, 1069–1096, https://doi.org/10.5194/nhess-20-1069-2020, https://doi.org/10.5194/nhess-20-1069-2020, 2020
Short summary
Short summary
We review the scientific literature on natural hazard risk assessments at the global scale. In doing so, we examine similarities and differences between the approaches taken across the different hazards and identify potential ways in which different hazard communities can learn from each other. Finally, we discuss opportunities for learning from methods and approaches being developed and applied to assess natural hazard risks at more continental or regional scales.
Luke A. McGuire, Scott W. McCoy, Odin Marc, William Struble, and Katherine R. Barnhart
Earth Surf. Dynam., 11, 1117–1143, https://doi.org/10.5194/esurf-11-1117-2023, https://doi.org/10.5194/esurf-11-1117-2023, 2023
Short summary
Short summary
Debris flows are mixtures of mud and rocks that can travel at high speeds across steep landscapes. Here, we propose a new model to describe how landscapes are shaped by debris flow erosion over long timescales. Model results demonstrate that the shapes of channel profiles are sensitive to uplift rate, meaning that it may be possible to use topographic data from steep channel networks to infer how erosion rates vary across a landscape.
Robert A. Emberson
Hydrol. Earth Syst. Sci., 27, 3547–3563, https://doi.org/10.5194/hess-27-3547-2023, https://doi.org/10.5194/hess-27-3547-2023, 2023
Short summary
Short summary
Soil can be eroded by rainfall, and this is a major threat to agricultural sustainability. Estimating the erosivity of rainfall is essential as a first step to determine how much soil might be lost. Until recently, satellite data have not been used to estimate rainfall erosivity, but the data quality is now sufficient to do so. In this study, I test several methods to calculate rainfall erosivity using satellite rainfall data and contrast this with ground-based estimates.
Gregory Ruetenik, Ken Ferrier, and Odin Marc
EGUsphere, https://doi.org/10.5194/egusphere-2023-1278, https://doi.org/10.5194/egusphere-2023-1278, 2023
Short summary
Short summary
Fluvial sediment fluxes increased dramatically in Taiwan during Typhoon Morakot in 2009, which produced some of the heaviest landsliding on record. We analyzed fluvial discharge and suspended sediment concentration data at 87 gauging stations across Taiwan to quantify fluvial sediment responses since Morakot. In basins heavily impacted by landsliding, rating curve coefficients sharply increased during Morakot and then declined exponentially with a characteristic decay time of <10 years.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
EGUsphere, https://doi.org/10.31223/X5B075, https://doi.org/10.31223/X5B075, 2023
Short summary
Short summary
We propose a modelling 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 both in space and in time via an Ensemble Neural Network architecture.
Ionut Cristi Nicu, Letizia Elia, Lena Rubensdotter, Hakan Tanyaş, and Luigi Lombardo
Earth Syst. Sci. Data, 15, 447–464, https://doi.org/10.5194/essd-15-447-2023, https://doi.org/10.5194/essd-15-447-2023, 2023
Short summary
Short summary
Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.
Katy Burrows, Odin Marc, and Dominique Remy
Nat. Hazards Earth Syst. Sci., 22, 2637–2653, https://doi.org/10.5194/nhess-22-2637-2022, https://doi.org/10.5194/nhess-22-2637-2022, 2022
Short summary
Short summary
The locations of triggered landslides following a rainfall event can be identified in optical satellite images. However cloud cover associated with the rainfall means that these images cannot be used to identify landslide timing. Timings of landslides triggered during long rainfall events are often unknown. Here we present methods of using Sentinel-1 satellite radar data, acquired every 12 d globally in all weather conditions, to better constrain the timings of rainfall-triggered landslides.
Alexander L. Handwerger, Mong-Han Huang, Shannan Y. Jones, Pukar Amatya, Hannah R. Kerner, and Dalia B. Kirschbaum
Nat. Hazards Earth Syst. Sci., 22, 753–773, https://doi.org/10.5194/nhess-22-753-2022, https://doi.org/10.5194/nhess-22-753-2022, 2022
Short summary
Short summary
Rapid detection of landslides is critical for emergency response and disaster mitigation. Here we develop a global landslide detection tool in Google Earth Engine that uses satellite radar data to measure changes in the ground surface properties. We find that we can detect areas with high landslide density within days of a triggering event. Our approach allows the broader hazard community to utilize these state-of-the-art data for improved situational awareness of landslide hazards.
Odin Marc, Jens M. Turowski, and Patrick Meunier
Earth Surf. Dynam., 9, 995–1011, https://doi.org/10.5194/esurf-9-995-2021, https://doi.org/10.5194/esurf-9-995-2021, 2021
Short summary
Short summary
The size of grains delivered to rivers is an essential parameter for understanding erosion and sediment transport and their related hazards. In mountains, landslides deliver these rock fragments, but few studies have analyzed the landslide properties that control the resulting sizes. We present measurements on 17 landslides from Taiwan and show that their grain sizes depend on rock strength, landslide depth and drop height, thereby validating and updating a previous theory on fragmentation.
Robert Emberson, Dalia Kirschbaum, and Thomas Stanley
Nat. Hazards Earth Syst. Sci., 20, 3413–3424, https://doi.org/10.5194/nhess-20-3413-2020, https://doi.org/10.5194/nhess-20-3413-2020, 2020
Short summary
Short summary
Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every year, but different inventories of landslide events can have widely diverging completeness. This can lead to spatial biases in our understanding of the impacts. Here we use a globally homogeneous model of landslide hazard and exposure to provide consistent estimates of where landslides are most likely to cause damage to people, roads and other critical infrastructure at 1 km resolution.
Alexander L. Handwerger, Shannan Y. Jones, Mong-Han Huang, Pukar Amatya, Hannah R. Kerner, and Dalia B. Kirschbaum
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-315, https://doi.org/10.5194/nhess-2020-315, 2020
Manuscript not accepted for further review
Short summary
Short summary
The rapid and accurate mapping of landslides is critical for emergency response, disaster mitigation, and understanding landslide processes. Here we present a new approach to detect landslides anywhere in the world using freely available synthetic aperture radar data and open source tools in Google Earth Engine. Importantly, our methods do not require specialized processing software or training, which allows the broader hazards community to utilize these state-of-the-art remote sensing tools.
Philip J. Ward, Veit Blauhut, Nadia Bloemendaal, James E. Daniell, Marleen C. de Ruiter, Melanie J. Duncan, Robert Emberson, Susanna F. Jenkins, Dalia Kirschbaum, Michael Kunz, Susanna Mohr, Sanne Muis, Graeme A. Riddell, Andreas Schäfer, Thomas Stanley, Ted I. E. Veldkamp, and Hessel C. Winsemius
Nat. Hazards Earth Syst. Sci., 20, 1069–1096, https://doi.org/10.5194/nhess-20-1069-2020, https://doi.org/10.5194/nhess-20-1069-2020, 2020
Short summary
Short summary
We review the scientific literature on natural hazard risk assessments at the global scale. In doing so, we examine similarities and differences between the approaches taken across the different hazards and identify potential ways in which different hazard communities can learn from each other. Finally, we discuss opportunities for learning from methods and approaches being developed and applied to assess natural hazard risks at more continental or regional scales.
Claire Rault, Alexandra Robert, Odin Marc, Niels Hovius, and Patrick Meunier
Earth Surf. Dynam., 7, 829–839, https://doi.org/10.5194/esurf-7-829-2019, https://doi.org/10.5194/esurf-7-829-2019, 2019
Short summary
Short summary
Large earthquakes trigger thousands of landslides in the area of their epicentre. For three earthquake cases, we have determined the position of these landslides along hillslopes. These co-seismic landslides tend to cluster at ridge crests and slope toes. We show that crest clustering is specific to seismic triggering. But although co-seismic landslides locate higher in the landscape than rainfall-induced landslides, geological features strongly modulate their position along the hillslopes.
Jianqiang Zhang, Cees J. van Westen, Hakan Tanyas, Olga Mavrouli, Yonggang Ge, Samjwal Bajrachary, Deo Raj Gurung, Megh Raj Dhital, and Narendral Raj Khanal
Nat. Hazards Earth Syst. Sci., 19, 1789–1805, https://doi.org/10.5194/nhess-19-1789-2019, https://doi.org/10.5194/nhess-19-1789-2019, 2019
Short summary
Short summary
The aim of this study is to investigate the differences in the mappable characteristics of earthquake-triggered and rainfall triggered landslides in terms of their frequency–area relationships, spatial distributions and relation with causal factors, as well as to evaluate whether separate susceptibility maps generated for specific landslide size and triggering mechanism are better than a generic landslide susceptibility assessment including all landslide sizes and triggers.
Odin Marc, Robert Behling, Christoff Andermann, Jens M. Turowski, Luc Illien, Sigrid Roessner, and Niels Hovius
Earth Surf. Dynam., 7, 107–128, https://doi.org/10.5194/esurf-7-107-2019, https://doi.org/10.5194/esurf-7-107-2019, 2019
Short summary
Short summary
We mapped eight monsoon-related (> 100 m2) and large (> 0.1 km2) landslides in the Nepal Himalayas since 1970. Adding inventories of Holocene landslides, giant landslides (> 1 km3), and landslides from the 2015 Gorkha earthquake, we constrain the size–frequency distribution of monsoon- and earthquake-induced landslides. Both contribute ~50 % to a long-term (> 10 kyr) total erosion of ~2 mm yr-1, matching the long-term exhumation rate. Large landslides rarer than 10Be sampling time drive erosion.
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.
Odin Marc, Patrick Meunier, and Niels Hovius
Nat. Hazards Earth Syst. Sci., 17, 1159–1175, https://doi.org/10.5194/nhess-17-1159-2017, https://doi.org/10.5194/nhess-17-1159-2017, 2017
Short summary
Short summary
We present an analytical expression for the surface area of the region within which landslides induced by a given earthquake are distributed. The expression is based on seismological scaling laws. Without calibration the model predicts, within a factor of 2, up to 49 out of 83 cases reported in the literature and agrees with the smallest region around the fault containing 95 % of the total landslide area. This model may be used for hazard assessment based on early earthquake detection parameters.
Chenxiao Tang, Cees J. Van Westen, Hakan Tanyas, and Victor G. Jetten
Nat. Hazards Earth Syst. Sci., 16, 2641–2655, https://doi.org/10.5194/nhess-16-2641-2016, https://doi.org/10.5194/nhess-16-2641-2016, 2016
Short summary
Short summary
Post-seismic landslides highlighted the need for more research to provide critical information for reconstruction. By mapping detailed landslide inventories, our work shows that most of the landslide activities were concentrated within the first 3 years after the earthquake, and they are majorly determined by vegetation regrowth, available volumes of loose materials, and extreme rainfall events. The landslide activity will continue to decay, but it may be halted if extreme rainfall occurs.
Robert Emberson, Niels Hovius, Albert Galy, and Odin Marc
Earth Surf. Dynam., 4, 727–742, https://doi.org/10.5194/esurf-4-727-2016, https://doi.org/10.5194/esurf-4-727-2016, 2016
Short summary
Short summary
Rapid dissolution of bedrock and regolith mobilised by landslides can be an important control on rates of overall chemical weathering in mountain ranges. In this study we analysed a number of landslides and rivers in Taiwan to better understand why this occurs. We find that sulfuric acid resulting from rapid oxidation of highly reactive sulfides in landslide deposits drives the intense weathering and can set catchment-scale solute budgets. This could be a CO2 source in fast-eroding mountains.
O. Marc and N. Hovius
Nat. Hazards Earth Syst. Sci., 15, 723–733, https://doi.org/10.5194/nhess-15-723-2015, https://doi.org/10.5194/nhess-15-723-2015, 2015
Short summary
Short summary
We present how amalgamation (i.e. the mapping of several adjacent landslides as a single polygon) can distort results derived from landslide mapping. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and DEM analysis, for automatic identification of amalgamated polygons, allowing one to check and correct landslide inventories faster.
Related subject area
Landslides and Debris Flows Hazards
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
Comprehensive landslide susceptibility map of Central Asia
The influence of large woody debris on post-wildfire debris flow sediment storage
Statistical modeling of sediment supply in torrent catchments of the northern French Alps
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide susceptibility modeling
A data-driven evaluation of post-fire landslide susceptibility
Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models
Brief communication: The northwest Himalaya towns slipping towards potential disaster
Dynamic response and breakage of trees subject to a landslide-induced air blast
Debris-flow surges of a very active alpine torrent: a field database
Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data
Instantaneous limit equilibrium back analyses of major rockslides triggered during the 2016–2017 central Italy seismic sequence
Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines
Antecedent rainfall as a critical factor for the triggering of debris flows in arid regions
Sensitivity analysis of a built environment exposed to the synthetic monophasic viscous debris flow impacts with 3-D numerical simulations
Simulation analysis of 3D stability of a landslide with a locking segment: A case study of Tizicao landslide in Maoxian County, Southwest China
Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo)
Spatio-temporal analysis of slope-type debris flow activity in Horlachtal, Austria, based on orthophotos and lidar data since 1947
Assessing the relationship between weather conditions and rockfall using terrestrial laser scanning to improve risk management
Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data
Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)
Brief communication: An autonomous UAV for catchment-wide monitoring of a debris flow torrent
How volcanic stratigraphy constrains headscarp collapse scenarios: the Samperre cliff case study (Martinique island, Lesser Antilles)
Landslide susceptibility assessment in the rocky coast subsystem of Essaouira, Morocco
Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides
Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments
Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda
Earthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influences
Pre-collapse motion of the February 2021 Chamoli rock–ice avalanche, Indian Himalaya
Physically based modeling of co-seismic landslide, debris flow, and flood cascade
Finite-hillslope analysis of landslides triggered by excess pore water pressure: the roles of atmospheric pressure and rainfall infiltration during typhoons
Estimating global landslide susceptibility and its uncertainty through ensemble modeling
Terrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India)
Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding
Introducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situations
Augmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scars
What drives landslide risk? Disaggregating risk analyses, an example from the Franz Josef Glacier and Fox Glacier valleys, New Zealand
Geographic information system models with fuzzy logic for susceptibility maps of debris flow using multiple types of parameters: a case study in Pinggu District of Beijing, China
Spatial assessment of probable recharge areas – investigating the hydrogeological controls of an active deep-seated gravitational slope deformation
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.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
Short summary
Short summary
This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
Short summary
Short summary
Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
Short summary
Short summary
In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
EGUsphere, https://doi.org/10.5194/egusphere-2023-869, https://doi.org/10.5194/egusphere-2023-869, 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 least amount of missed and false alarms. The ensemble approach moreover allowed to estimate the associated prediction uncertainty.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-70, https://doi.org/10.5194/nhess-2023-70, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
Dividing landscapes into representative hillslopes greatly improves predictions of landslide potential across landscapes but requires vast computing power. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units. The results of this work will allow an improved understanding of landslide potential across different landscapes and can ultimately help reduce the impacts of landslides worldwide.
Elsa S. Culler, Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo
Nat. Hazards Earth Syst. Sci., 23, 1631–1652, https://doi.org/10.5194/nhess-23-1631-2023, https://doi.org/10.5194/nhess-23-1631-2023, 2023
Short summary
Short summary
Landslides have often been observed in the aftermath of wildfires. This study explores regional patterns in the rainfall that caused landslides both after fires and in unburned locations. In general, landslides that occur after fires are triggered by less rainfall, confirming that fire helps to set the stage for landslides. However, there are regional differences in the ways in which fire impacts landslides, such as the size and direction of shifts in the seasonality of landslides after fires.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
Short summary
Short summary
We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Yaspal Sundriyal, Vipin Kumar, Neha Chauhan, Sameeksha Kaushik, Rahul Ranjan, and Mohit Kumar Punia
Nat. Hazards Earth Syst. Sci., 23, 1425–1431, https://doi.org/10.5194/nhess-23-1425-2023, https://doi.org/10.5194/nhess-23-1425-2023, 2023
Short summary
Short summary
The NW Himalaya has been one of the most affected terrains of the Himalaya, subject to disastrous landslides. This article focuses on two towns (Joshimath and Bhatwari) of the NW Himalaya, which have been witnessing subsidence for decades. We used a slope stability simulation to determine the response of the hillslopes accommodating these towns under various loading conditions. We found that the maximum displacement in these hillslopes might reach up to 20–25 m.
Yu Zhuang, Aiguo Xing, Perry Bartelt, Muhammad Bilal, and Zhaowei Ding
Nat. Hazards Earth Syst. Sci., 23, 1257–1266, https://doi.org/10.5194/nhess-23-1257-2023, https://doi.org/10.5194/nhess-23-1257-2023, 2023
Short summary
Short summary
Tree destruction is often used to back calculate the air blast impact region and to estimate the air blast power. Here we established a novel model to assess air blast power using tree destruction information. We find that the dynamic magnification effect makes the trees easier to damage by a landslide-induced air blast, but the large tree deformation would weaken the effect. Bending and overturning are two likely failure modes, which depend heavily on the properties of trees.
Suzanne Lapillonne, Firmin Fontaine, Frédéric Liebault, Vincent Richefeu, and Guillaume Piton
Nat. Hazards Earth Syst. Sci., 23, 1241–1256, https://doi.org/10.5194/nhess-23-1241-2023, https://doi.org/10.5194/nhess-23-1241-2023, 2023
Short summary
Short summary
Debris flows are fast flows most often found in torrential watersheds. They are composed of two phases: a liquid phase which can be mud-like and a granular phase, including large boulders, transported along with the flow. Due to their destructive nature, accessing features of the flow, such as velocity and flow height, is difficult. We present a protocol to analyse debris flow data and results of the Réal torrent in France. These results will help experts in designing models.
Carlos Millán-Arancibia and Waldo Lavado-Casimiro
Nat. Hazards Earth Syst. Sci., 23, 1191–1206, https://doi.org/10.5194/nhess-23-1191-2023, https://doi.org/10.5194/nhess-23-1191-2023, 2023
Short summary
Short summary
This study is the first approximation of regional rainfall thresholds for shallow landslide occurrence in Peru. This research was generated from a gridded precipitation data and landslide inventory. The analysis showed that the threshold based on the combination of mean daily intensity–duration variables gives the best results for separating rainfall events that generate landslides. Through this work the potential of thresholds for landslide monitoring at the regional scale is demonstrated.
Luca Verrucci, Giovanni Forte, Melania De Falco, Paolo Tommasi, Giuseppe Lanzo, Kevin W. Franke, and Antonio Santo
Nat. Hazards Earth Syst. Sci., 23, 1177–1190, https://doi.org/10.5194/nhess-23-1177-2023, https://doi.org/10.5194/nhess-23-1177-2023, 2023
Short summary
Short summary
Stability analyses in static and seismic conditions were performed on four rockslides that occurred during the main shocks of the 2016–2017 central Italy seismic sequence. These results also indicate that specific structural features of the slope must carefully be accounted for in evaluating potential hazards on transportation infrastructures in mountainous regions.
Enner Alcântara, José A. Marengo, José Mantovani, Luciana R. Londe, Rachel Lau Yu San, Edward Park, Yunung Nina Lin, Jingyu Wang, Tatiana Mendes, Ana Paula Cunha, Luana Pampuch, Marcelo Seluchi, Silvio Simões, Luz Adriana Cuartas, Demerval Goncalves, Klécia Massi, Regina Alvalá, Osvaldo Moraes, Carlos Souza Filho, Rodolfo Mendes, and Carlos Nobre
Nat. Hazards Earth Syst. Sci., 23, 1157–1175, https://doi.org/10.5194/nhess-23-1157-2023, https://doi.org/10.5194/nhess-23-1157-2023, 2023
Short summary
Short summary
The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
Joshua N. Jones, Georgina L. Bennett, Claudia Abancó, Mark A. M. Matera, and Fibor J. Tan
Nat. Hazards Earth Syst. Sci., 23, 1095–1115, https://doi.org/10.5194/nhess-23-1095-2023, https://doi.org/10.5194/nhess-23-1095-2023, 2023
Short summary
Short summary
We modelled where landslides occur in the Philippines using landslide data from three typhoon events in 2009, 2018, and 2019. These models show where landslides occurred within the landscape. By comparing the different models, we found that the 2019 landslides were occurring all across the landscape, whereas the 2009 and 2018 landslides were mostly occurring at specific slope angles and aspects. This shows that landslide susceptibility must be considered variable through space and time.
Shalev Siman-Tov and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1079–1093, https://doi.org/10.5194/nhess-23-1079-2023, https://doi.org/10.5194/nhess-23-1079-2023, 2023
Short summary
Short summary
Debris flows represent a threat to infrastructure and the population. In arid areas, they are observed when heavy rainfall hits steep slopes with sediments. Here, we use digital surface models and radar rainfall data to detect and characterize the triggering and non-triggering rainfall conditions. We find that rainfall intensity alone is insufficient to explain the triggering. We suggest that antecedent rainfall could represent a critical factor for debris flow triggering in arid regions.
Xun Huang, Zhijian Zhang, and Guoping Xiang
Nat. Hazards Earth Syst. Sci., 23, 871–889, https://doi.org/10.5194/nhess-23-871-2023, https://doi.org/10.5194/nhess-23-871-2023, 2023
Short summary
Short summary
A sensitivity analysis on the building impact force resulting from the representative built environment parameters is executed through the FLOW-3D model. The surrounding buildings' properties, especially the azimuthal angle, have been confirmed to play significant roles in determining the peak impact forces. The single and combined effects of built environments are analyzed in detail. This will improve understanding of vulnerability assessment and migration design against debris flow hazards.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
EGUsphere, https://doi.org/10.5194/egusphere-2023-28, https://doi.org/10.5194/egusphere-2023-28, 2023
Short summary
Short summary
We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide. We found that the CSM-HSP combines the advantages of the IRMM model in simulating the actual deformation of slopes with rock bridges and the modeling advantage of the JM model. The research results are helpful to choose an appropriate rock bridge model to simulate the 3D landslide stability and to reveal the influence laws of rock bridges on the 3D stability of landslides.
Jean-Claude Maki Mateso, Charles L. Bielders, Elise Monsieurs, Arthur Depicker, Benoît Smets, Théophile Tambala, Luc Bagalwa Mateso, and Olivier Dewitte
Nat. Hazards Earth Syst. Sci., 23, 643–666, https://doi.org/10.5194/nhess-23-643-2023, https://doi.org/10.5194/nhess-23-643-2023, 2023
Short summary
Short summary
This research highlights the importance of human activities on the occurrence of landslides and the need to consider this context when studying hillslope instability patterns in regions under anthropogenic pressure. Also, this study highlights the importance of considering the timing of landslides and hence the added value of using historical information for compiling an inventory.
Jakob Rom, Florian Haas, Tobias Heckmann, Moritz Altmann, Fabian Fleischer, Camillo Ressl, Sarah Betz-Nutz, and Michael Becht
Nat. Hazards Earth Syst. Sci., 23, 601–622, https://doi.org/10.5194/nhess-23-601-2023, https://doi.org/10.5194/nhess-23-601-2023, 2023
Short summary
Short summary
In this study, an area-wide slope-type debris flow record has been established for Horlachtal, Austria, since 1947 based on historical and recent remote sensing data. Spatial and temporal analyses show variations in debris flow activity in space and time in a high-alpine region. The results can contribute to a better understanding of past slope-type debris flow dynamics in the context of extreme precipitation events and their possible future development.
Tom Birien and Francis Gauthier
Nat. Hazards Earth Syst. Sci., 23, 343–360, https://doi.org/10.5194/nhess-23-343-2023, https://doi.org/10.5194/nhess-23-343-2023, 2023
Short summary
Short summary
On highly fractured rockwalls such as those found in northern Gaspésie, most rockfalls are triggered by weather conditions. This study highlights that in winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0 °C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a mainly dry period. This knowledge could be used to implement a risk management strategy.
Nunziarita Palazzolo, David J. Peres, Enrico Creaco, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci., 23, 279–291, https://doi.org/10.5194/nhess-23-279-2023, https://doi.org/10.5194/nhess-23-279-2023, 2023
Short summary
Short summary
We propose an approach exploiting PCA to derive hydrometeorological landslide-triggering thresholds using multi-layered soil moisture data from ERA5-Land reanalysis. Comparison of thresholds based on single- and multi-layered soil moisture information provides a means to identify the significance of multi-layered data for landslide triggering in a region. In Sicily, the proposed approach yields thresholds with a higher performance than traditional precipitation-based ones (TSS = 0.71 vs. 0.50).
Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 23, 205–229, https://doi.org/10.5194/nhess-23-205-2023, https://doi.org/10.5194/nhess-23-205-2023, 2023
Short summary
Short summary
In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering thousands of landslides. Landslide storylines help to show potential future changes under changing environmental conditions. The often neglected uncertainty quantification was the aim of this study. We found uncertainty arising from the landslide model to be of the same order as climate scenario uncertainty. Understanding the dimensions of uncertainty is crucial for allowing informed decision-making.
Fabian Walter, Elias Hodel, Erik S. Mannerfelt, Kristen Cook, Michael Dietze, Livia Estermann, Michaela Wenner, Daniel Farinotti, Martin Fengler, Lukas Hammerschmidt, Flavia Hänsli, Jacob Hirschberg, Brian McArdell, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 22, 4011–4018, https://doi.org/10.5194/nhess-22-4011-2022, https://doi.org/10.5194/nhess-22-4011-2022, 2022
Short summary
Short summary
Debris flows are dangerous sediment–water mixtures in steep terrain. Their formation takes place in poorly accessible terrain where instrumentation cannot be installed. Here we propose to monitor such source terrain with an autonomous drone for mapping sediments which were left behind by debris flows or may contribute to future events. Short flight intervals elucidate changes of such sediments, providing important information for landscape evolution and the likelihood of future debris flows.
Marc Peruzzetto, Yoann Legendre, Aude Nachbaur, Thomas J. B. Dewez, Yannick Thiery, Clara Levy, and Benoit Vittecoq
Nat. Hazards Earth Syst. Sci., 22, 3973–3992, https://doi.org/10.5194/nhess-22-3973-2022, https://doi.org/10.5194/nhess-22-3973-2022, 2022
Short summary
Short summary
Volcanic edifices result from successive construction and dismantling phases. Thus, the geological units forming volcanoes display complex geometries. We show that such geometries can be reconstructed thanks to aerial views, topographic surveys and photogrammetric models. In our case study of the Samperre cliff (Martinique, Lesser Antilles), it allows us to link destabilizations from a rocky cliff to the existence of a filled paleo-valley and estimate a potentially unstable volume.
Abdellah Khouz, Jorge Trindade, Sérgio C. Oliveira, Fatima El Bchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud
Nat. Hazards Earth Syst. Sci., 22, 3793–3814, https://doi.org/10.5194/nhess-22-3793-2022, https://doi.org/10.5194/nhess-22-3793-2022, 2022
Short summary
Short summary
The aim of this study was to assess the landslide susceptibility of the rocky coast of Essaouira using the information value model. The resulting susceptibility maps could be used for both environmental protection and general planning of future development activities.
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764, https://doi.org/10.5194/nhess-22-3751-2022, https://doi.org/10.5194/nhess-22-3751-2022, 2022
Short summary
Short summary
The landslide hazard models assist in mitigating losses due to landslides. However, these models depend on landslide databases, which often have missing triggering information, rendering these databases unusable for landslide hazard models. In this work, we developed a Python library, Landsifier, consisting of three different methods to identify the triggers of landslides. These methods can classify landslide triggers with high accuracy using only a landslide polygon shapefile as an input.
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700, https://doi.org/10.5194/nhess-22-3679-2022, https://doi.org/10.5194/nhess-22-3679-2022, 2022
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.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022, https://doi.org/10.5194/nhess-22-3641-2022, 2022
Short summary
Short summary
This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci., 22, 3361–3384, https://doi.org/10.5194/nhess-22-3361-2022, https://doi.org/10.5194/nhess-22-3361-2022, 2022
Short summary
Short summary
We present a new landslide inventory for the 2021, M 7.2, Haiti, earthquake. We compare characteristics of this inventory with those of the 2010 seismically induced landslides, highlighting the much larger total area of 2021 landslides. This fact could be related to the larger earthquake magnitude in 2021, to the more central location of the fault segment ruptured in 2021 with respect to coastal zones, and/or to possible climatic preconditioning of slope failures in the 2021 affected area.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022, https://doi.org/10.5194/nhess-22-3309-2022, 2022
Short summary
Short summary
On 7 February 2021, a large rock–ice avalanche occurred in Chamoli, Indian Himalaya. The resulting debris flow swept down the nearby valley, leaving over 200 people dead or missing. We use a range of satellite datasets to investigate how the collapse area changed prior to collapse. We show that signs of instability were visible as early 5 years prior to collapse. However, it would likely not have been possible to predict the timing of the event from current satellite datasets.
Bastian van den Bout, Chenxiao Tang, Cees van Westen, and Victor Jetten
Nat. Hazards Earth Syst. Sci., 22, 3183–3209, https://doi.org/10.5194/nhess-22-3183-2022, https://doi.org/10.5194/nhess-22-3183-2022, 2022
Short summary
Short summary
Natural hazards such as earthquakes, landslides, and flooding do not always occur as stand-alone events. After the 2008 Wenchuan earthquake, a co-seismic landslide blocked a stream in Hongchun. Two years later, a debris flow breached the material, blocked the Min River, and resulted in flooding of a small town. We developed a multi-process model that captures the full cascade. Despite input and process uncertainties, probability of flooding was high due to topography and trigger intensities.
Lucas Pelascini, Philippe Steer, Maxime Mouyen, and Laurent Longuevergne
Nat. Hazards Earth Syst. Sci., 22, 3125–3141, https://doi.org/10.5194/nhess-22-3125-2022, https://doi.org/10.5194/nhess-22-3125-2022, 2022
Short summary
Short summary
Landslides represent a major natural hazard and are often triggered by typhoons. We present a new 2D model computing the respective role of rainfall infiltration, atmospheric depression and groundwater in slope stability during typhoons. The results show rainfall is the strongest factor of destabilisation. However, if the slope is fully saturated, near the toe of the slope or during the wet season, rainfall infiltration is limited and atmospheric pressure change can become the dominant factor.
Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 22, 3063–3082, https://doi.org/10.5194/nhess-22-3063-2022, https://doi.org/10.5194/nhess-22-3063-2022, 2022
Short summary
Short summary
In this study we assessed global landslide susceptibility at the coarse 36 km spatial resolution of global satellite soil moisture observations to prepare for a subsequent combination of the two. Specifically, we focus therefore on the susceptibility of hydrologically triggered landslides. We introduce ensemble techniques, common in, for example, meteorology but not yet in the landslide community, to retrieve reliable estimates of the total prediction uncertainty.
Txomin Bornaetxea, Ivan Marchesini, Sumit Kumar, Rabisankar Karmakar, and Alessandro Mondini
Nat. Hazards Earth Syst. Sci., 22, 2929–2941, https://doi.org/10.5194/nhess-22-2929-2022, https://doi.org/10.5194/nhess-22-2929-2022, 2022
Short summary
Short summary
One cannot know if there is a landslide or not in an area that one has not observed. This is an obvious statement, but when landslide inventories are obtained by field observation, this fact is seldom taken into account. Since fieldwork campaigns are often done following the roads, we present a methodology to estimate the visibility of the terrain from the roads, and we demonstrate that fieldwork-based inventories are underestimating landslide density in less visible areas.
Katy Burrows, Odin Marc, and Dominique Remy
Nat. Hazards Earth Syst. Sci., 22, 2637–2653, https://doi.org/10.5194/nhess-22-2637-2022, https://doi.org/10.5194/nhess-22-2637-2022, 2022
Short summary
Short summary
The locations of triggered landslides following a rainfall event can be identified in optical satellite images. However cloud cover associated with the rainfall means that these images cannot be used to identify landslide timing. Timings of landslides triggered during long rainfall events are often unknown. Here we present methods of using Sentinel-1 satellite radar data, acquired every 12 d globally in all weather conditions, to better constrain the timings of rainfall-triggered landslides.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635, https://doi.org/10.5194/nhess-22-2611-2022, https://doi.org/10.5194/nhess-22-2611-2022, 2022
Short summary
Short summary
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Chuxuan Li, Alexander L. Handwerger, Jiali Wang, Wei Yu, Xiang Li, Noah J. Finnegan, Yingying Xie, Giuseppe Buscarnera, and Daniel E. Horton
Nat. Hazards Earth Syst. Sci., 22, 2317–2345, https://doi.org/10.5194/nhess-22-2317-2022, https://doi.org/10.5194/nhess-22-2317-2022, 2022
Short summary
Short summary
In January 2021 a storm triggered numerous debris flows in a wildfire burn scar in California. We use a hydrologic model to assess debris flow susceptibility in pre-fire and postfire scenarios. Compared to pre-fire conditions, postfire conditions yield dramatic increases in peak water discharge, substantially increasing debris flow susceptibility. Our work highlights the hydrologic model's utility in investigating and potentially forecasting postfire debris flows at regional scales.
Saskia de Vilder, Chris Massey, Biljana Lukovic, Tony Taig, and Regine Morgenstern
Nat. Hazards Earth Syst. Sci., 22, 2289–2316, https://doi.org/10.5194/nhess-22-2289-2022, https://doi.org/10.5194/nhess-22-2289-2022, 2022
Short summary
Short summary
This study calculates the fatality risk posed by landslides while visiting Franz Josef Glacier and Fox Glacier valleys, New Zealand, for nine different scenarios, where the variables of the risk equation were adjusted to determine the range in risk values and associated uncertainty. The results show that it is important to consider variable inputs that change through time, such as the increasing probability of an earthquake and the impact of climate change on landslide characteristics.
Yiwei Zhang, Jianping Chen, Qing Wang, Chun Tan, Yongchao Li, Xiaohui Sun, and Yang Li
Nat. Hazards Earth Syst. Sci., 22, 2239–2255, https://doi.org/10.5194/nhess-22-2239-2022, https://doi.org/10.5194/nhess-22-2239-2022, 2022
Short summary
Short summary
The disaster prevention and mitigation of debris flow is a very important scientific problem. Our model is based on geographic information system (GIS), combined with grey relational, data-driven and fuzzy logic methods. Through our results, we believe that the streamlining of factors and scientific classification should attract attention from other researchers to optimize a model. We also propose a good perspective to make better use of the watershed feature parameters.
Jan Pfeiffer, Thomas Zieher, Jan Schmieder, Thom Bogaard, Martin Rutzinger, and Christoph Spötl
Nat. Hazards Earth Syst. Sci., 22, 2219–2237, https://doi.org/10.5194/nhess-22-2219-2022, https://doi.org/10.5194/nhess-22-2219-2022, 2022
Short summary
Short summary
The activity of slow-moving deep-seated landslides is commonly governed by pore pressure variations within the shear zone. Groundwater recharge as a consequence of precipitation therefore is a process regulating the activity of landslides. In this context, we present a highly automated geo-statistical approach to spatially assess groundwater recharge controlling the velocity of a deep-seated landslide in Tyrol, Austria.
Cited articles
Adriano, B., Yokoya, N., Miura, H., Matsuoka, M., and Koshimura, S.: A semiautomatic pixel-object method for detecting landslides using multitemporal ALOS-2 intensity images, Remote Sens., 12, 561, https://doi.org/10.3390/rs12030561, 2020.
Amatya, P., Kirschbaum, D., and Stanley, T.: Use of very high-resolution optical data for landslide mapping and susceptibility analysis along the
Karnali highway, Nepal, Remote Sens., 11, 2284, https://doi.org/10.3390/rs11192284, 2019.
Amatya, P., Kirschbaum, D., Stanley, T., and Tanyas, H.: Landslide mapping
using object-based image analysis and open source tools, Eng. Geol., 282, 106000, https://doi.org/10.1016/j.enggeo.2021.106000, 2021.
Badoux, A., Andres, N., and Turowski, J. M.: Damage costs due to bedload
transport processes in Switzerland, Nat. Hazards Earth Syst. Sci., 14, 279–294, https://doi.org/10.5194/nhess-14-279-2014, 2014.
Behling, R., Roessner, S., Segl, K., Kleinschmit, B., and Kaufmann, H.: Robust automated image co-registration of optical multi-sensor time series data: Database generation for multi-temporal landslide detection, Remote Sens., 6, 2572–2600, https://doi.org/10.3390/rs6032572, 2014.
Bekaert, D. P., Handwerger, A. L., Agram, P., and Kirschbaum, D. B.: InSAR-based detection method for mapping and monitoring slow-moving landslides in remote regions with steep and mountainous terrain: An application to Nepal, Remote Sens. Environ., 249, 111983,
https://doi.org/10.1016/j.rse.2020.111983, 2020.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant, Hydrolog. Sci. J., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Bogaard, T. A. and Greco, R.: Landslide hydrology: from hydrology to pore
pressure, Wiley Interdisciplin. Rev.: Water, 3, 439–459, https://doi.org/10.1002/wat2.1126, 2016.
Bookhagen, B. and Strecker, M. R.: Spatiotemporal trends in erosion rates
across a pronounced rainfall gradient: Examples from the southern Central
Andes, Earth Planet. Sc. Lett., 327–328, 97–110, https://doi.org/10.1016/j.epsl.2012.02.005, 2012.
Broeckx, J., Maertens, M., Isabirye, M., Vanmaercke, M., Namazzi, B., Deckers, J., Tamale, J., Jacobs, L., Thiery, W., Kervyn, M., Vranken, L., and Poesen, J.: Landslide susceptibility and mobilization rates in the Mount Elgon region, Uganda, (October 2018), Landslides, 16, 571–584, https://doi.org/10.1007/s10346-018-1085-y, 2019.
Budimir, M. E. A., Atkinson, P. M., and Lewis, H. G.: A systematic review of
landslide probability mapping using logistic regression, Landslides, 12, 419–436, https://doi.org/10.1007/s10346-014-0550-5, 2015.
Burrows, K., Walters, R. J., Milledge, D., and Densmore, A. L.: A systematic
exploration of satellite radar coherence methods for rapid landslide
detection, Nat. Hazards Earth Syst. Sci., 20, 3197–3214, https://doi.org/10.5194/nhess-20-3197-2020, 2020.
Camilo, D. C., Lombardo, L., Mai, P. M., Dou, J., and Huser, R.: Environmental Modelling & Software Handling high predictor dimensionality
in slope-unit-based landslide susceptibility models through LASSO-penalized
Generalized Linear Model, Environ. Model. Softw., 97, 145–156, https://doi.org/10.1016/j.envsoft.2017.08.003, 2017.
Casagli, N., Frodella, W., Morelli, S., Tofani, V., Ciampalini, A., Interieri, C., Raspini, F., Rossi, G., Tanteri, L., and Lu, P.: Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning, Geoenviron. Disast., 4, 1–23, https://doi.org/10.1186/s40677-017-0073-1, 2017.
Chang, K., Chiang, S., Chen, Y., and Mondini, A. C.: Modeling the spatial occurrence of shallow landslides triggered by typhoons, Geomorphology, 208,
137–148, https://doi.org/10.1016/j.geomorph.2013.11.020, 2014.
Chen, Y., Chang, K., Chiu, Y., Lau, S., Lee, H., and County, T.: Quantifying
rainfall controls on catchment-scale landslide erosion in Taiwan, Earth Surf. Proc. Land., 382, 372–382, https://doi.org/10.1002/esp.3284, 2013.
Conrad, J. L., Morphew, M. D., Baum, R. L., and Mirus, B. B.: HydroMet: A New Code for Automated Objective Optimization of Hydrometeorological Thresholds for Landslide Initiation, Water, 13, 1752, https://doi.org/10.3390/w13131752, 2021.
Costanzo, D., Rotigliano, E., Irigaray, C., Jiménez-Perálvarez, J. D., and Chacón, J.: Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: Application to the
river Beiro basin (Spain), Nat. Hazards Earth Syst. Sci., 12, 327–340, https://doi.org/10.5194/nhess-12-327-2012, 2012.
Densmore, A. L. and Hovius, N.: Topographic fingerprints of bedrock landslides, Geology, 28, 371–374, https://doi.org/10.1130/0091-7613(2000)28<371:TFOBL>2.0.CO;2, 2000.
Dietrich, W. E., Reiss, R., Hsu, M. L., and Montgomery, D. R.: A process-based model for colluvial soil depth and shallow landsliding using digital elevation data, Hydrol. Process., 9, 383–400, https://doi.org/10.1002/hyp.3360090311, 1995.
Domej, G., Bourdeau, C., Lenti, L., Martino, S., and Piuta, K.: Mean landslide geometries inferred from a global database of earthquake-and non-earthquake-triggered landslides, Ital. J. Eng. Geol. Environ., 17, 87–107, https://doi.org/10.4408/IJEGE.2017-02.O-05, 2017.
Emberson, R., Kirschbaum, D., and Stanley, T.: New global characterisation of landslide exposure, Nat. Hazards Earth Syst. Sci., 20, 3413–3424,
https://doi.org/10.5194/nhess-20-3413-2020, 2020.
Emberson, R. A., Kirschbaum, D. B., and Stanley, T.: Landslide hazard and exposure modelling in data-poor regions: the example of the Rohingya refugee camps in Bangladesh, Earth's Future, 9, e2020EF001666, https://doi.org/10.1029/2020EF001666, 2021.
Friedman, J., Hastie, T., Tibshirani, R., Narasimhan, B., Tay, K., Simon, N., and Qian, J.: Lasso and Elastic-Net Regularized Generalized Linear Models, CRAN, https://doi.org/10.18637/jss.v033.i01, 2021.
Froude, M. J. and Petley, D. N.: Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
García-Rodríguez, M. J., Malpica, J. A., Benito, B., and Díaz, M.: Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression, Geomorphology, 95, 172–191,
https://doi.org/10.1016/j.geomorph.2007.06.001, 2008.
Geiger, R.: Klassifikation der Klimate nach W. Köppen, in: Landolt-Börnstein – Zahlenwerte und Funktionen aus Physik, Chemie,
Astronomie, Geophysik und Technik, alte Serie, Springer, Berlin, 603–607,
1954.
Goetz, J. N., Brenning, A., Petschko, H., and Leopold, P.: Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling, Comput. Geosci., 81, 1–11, https://doi.org/10.1016/j.cageo.2015.04.007, 2015.
Guzzetti, F., Cardinali, M., and Reichenbach, P.: The Influence of Structural Setting and Lithology on Landslide Type and Pattern, Environ. Eng. Geosci., II, 531–555, https://doi.org/10.2113/gseegeosci.II.4.531, 1996.
Guzzetti, F., Cesare, A., Cardinali, M., Fiorucci, F., Santangelo, M., and
Chang, K.: Landslide inventory maps: New tools for an old problem, Earth Sci. Rev., 112, 42–66, https://doi.org/10.1016/j.earscirev.2012.02.001, 2012.
Handwerger, A. L., Fielding, E. J., Huang, M., Bennett, G., Liang, C., and
Schulz, W. H.: Widespread Initiation, Reactivation , and Acceleration of
Landslides in the Northern California Coast Ranges due to Extreme Rainfall, J. Geophys. Res.-Earth, 124, 1782–1797, https://doi.org/10.1029/2019JF005035, 2019.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., and Townshend, J. R. G.: High-Resolution Global Maps of 21st-Century Forest Cover Change, Science, 342, 850–853, https://doi.org/10.1126/science.1244693, 2013.
Harp, B. E. L., Reid, M. E., and Michael, J. A.: Hazard Analysis of Landslides Triggered by Typhoon Chata'an on July 2, 2002, in Chuuk State, Federated States of Micronesia, USGS Open-File Report 2004-1348, USGS, https://doi.org/10.3133/ofr20041348, 2004.
Harp, E. L., Keefer, D. K., Sato, H. P., and Yagi, H.: Landslide inventories: The essential part of seismic landslide hazard analyses, Eng. Geol., 122, 9–21, https://doi.org/10.1016/j.enggeo.2010.06.013, 2011.
Hartmann, J. and Moosdorf, N.: The new global lithological map database GLiM: A representation of rock properties at the Earth surface, Geochem. Geophy. Geosy., 13, 1–37, https://doi.org/10.1029/2012GC004370, 2012.
Hencher, S. R.: Preferential flow paths through soil and rock and their
association with landslides, Hydrol. Process., 24, 1610–1630, https://doi.org/10.1002/hyp.7721, 2010.
Hosmer, D. and Lemeshow, S: Applied Logistic Regression, 2nd Edn., Wiley, New York, ISBN 978-0-470-58247-3, 2000.
Hu, X., Bürgmann, R., Lu, Z., Handwerger, A. L., Wang, T., and Miao, R.:
Mobility, Thickness, and Hydraulic Diffusivity of the Slow – Moving Monroe
Landslide in California Revealed by L – Band Satellite Radar Interferometry
J. Geophys. Res.-Solid, 124, 7504–7518, https://doi.org/10.1029/2019JB017560, 2019.
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K.-L., Joyce, R. J., Kidd, C., Nelkin, E. J., Sorooshian, S., Stocker, E. F., Tan, J., Wolff, D. B., and Xie, P.: Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement (GPM) Mission (IMERG), in: Advances in Global Change Research, Springer, 343–353, https://doi.org/10.1007/978-3-030-24568-9_19, 2020.
Iida, T.: A stochastic hydro-geomorphological model for shallow landsliding
due to rainstorm, Catena, 34, 293–313, https://doi.org/10.1016/S0341-8162(98)00093-9, 1999.
Iida, T.: Theoretical research on the relationship between return period of
rainfall and shallow landslides, Hydrol. Process., 18, 739–756, https://doi.org/10.1002/hyp.1264, 2004.
Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897–1910, https://doi.org/10.1029/2000WR900090, 2000.
Jibson, R. W., Harp, E. L., and Michael, J. A.: A method for producing digital probabilistic seismic landslide hazard maps, Eng. Geol., 58, 271–289, https://doi.org/10.1016/S0013-7952(00)00039-9, 2000.
Jung, J. and Yun, S. H.: Evaluation of coherent and incoherent landslide detection methods based on synthetic aperture radar for rapid response: A case study for the 2018 Hokkaido landslides, Remote Sens., 12, 265,
https://doi.org/10.3390/rs12020265, 2020.
Kirschbaum, D. B. and Stanley, T.: Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness, Earth's
Future, 6, 505–523, https://doi.org/10.1002/2017EF000715, 2018.
Kirschbaum, D. B., 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.
Korup, O., Görüm, T., and Hayakawa, Y.: Without power? Landslide
inventories in the face of climate change, Earth Surf. Proc. Land., 37, 92–99, https://doi.org/10.1002/esp.2248, 2012.
Larsen, I. J., Montgomery, D. R., and Korup, O.: Landslide erosion controlled by hillslope material, Nat. Geosci., 3, 247–251, https://doi.org/10.1038/ngeo776, 2010.
Liang, W. and Chan, M.: Spatial and temporal variations in the effects of soil depth and topographic wetness index of bedrock topography on subsurface saturation generation in a steep natural forested headwater catchment, J. Hydrol., 546, 405–418, https://doi.org/10.1016/j.jhydrol.2017.01.033, 2017.
Lin, C.-W., Chang, W.-S., Liu, S.-H., Tsai, T.-T., Lee, S.-P., Tsang, Y.-C., Shieh, C.-L., and Tseng, C.-M.: Landslides triggered by the 7 August 2009 Typhoon Morakot in southern Taiwan, Eng. Geol., 123, 3–12, https://doi.org/10.1016/j.enggeo.2011.06.007, 2011.
Lombardo, L. and Tanyas, H.: Chrono-validation of near-real-time landslide
susceptibility models via plug-in statistical simulations, Eng. Geol., 278,
105818, https://doi.org/10.1016/j.enggeo.2020.105818, 2020.
Lombardo, L., Optiz, T., and Huser, R.: Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster, Stoch. Environ. Res. Risk Assess., 32, 2179–2198, https://doi.org/10.1007/s00477-018-1518-0, 2018.
Malamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P.: Landslide inventories and their statistical properties, Earth Surf. Proc. Land., 29, 687–711, https://doi.org/10.1002/esp.1064, 2004.
Marc, O. and Hovius, N.: Amalgamation in landslide maps: effects and automatic detection, Nat. Hazards Earth Syst. Sci., 15, 723–733,
https://doi.org/10.5194/nhess-15-723-2015, 2015.
Marc, O., Hovius, N., Meunier, P., Gorum, T., and Uchida, T.: A seismologically consistent expression for the total area and volume of
earthquake-triggered landsliding, J. Geophys. Res.-Earth, 121, 640–663, https://doi.org/10.1002/2015JF003732, 2016.
Marc, O., Meunier, P., and Hovius, N.: Prediction of the area affected by
earthquake-induced landsliding based on seismological parameters, Nat.
Hazards Earth Syst. Sci., 17, 1159–1175, https://doi.org/10.5194/nhess-17-1159-2017, 2017.
Marc, O., Stumpf, A., Malet, J.-P., Gosset, M., Uchida, T., and Chiang, S.-H.: Initial insights from a global database of rainfall-induced landslide inventories: the weak influence of slope and strong influence of total storm rainfall, Earth Surf. Dynam., 6, 903–922, https://doi.org/10.5194/esurf-6-903-2018, 2018.
Marc, O., Gosset, M., Saito, H., Uchida, T., and Malet, J.-P.: Spatial Patterns of Storm-Induced Landslides and Their Relation to Rainfall Anomaly
Maps, Geophys. Res. Lett., 46, 11167–11177, https://doi.org/10.1029/2019GL083173, 2019.
Martha, T. R., Kerle, N., Van Westen, C. J., Jetten, V., and Kumar, K. V.:
Object-oriented analysis of multi-temporal panchromatic images for creation
of historical landslide inventories, ISPRS J. Photogram. Remote Sens., 67, 105–119, https://doi.org/10.1016/j.isprsjprs.2011.11.004, 2012.
Meunier, P., Hovius, N., and Haines, J. A.: Topographic site effects and the
location of earthquake induced landslides, Earth Planet. Sc. Lett., 275, 221–232, https://doi.org/10.1016/j.epsl.2008.07.020, 2008.
Milledge, D. G., Densmore, A. L., Bellugi, D., Rosser, N. J., Watt, J., Li,
G., and Oven, K. J.: Simple rules to minimise exposure to coseismic landslide hazard, Nat. Hazards Earth Syst. Sci., 19, 837–856, https://doi.org/10.5194/nhess-19-837-2019, 2019.
Milliman, J. and Syvitski, J. P. M.: Geomorphic Tectonic Control of Sediment Discharge to Ocean – The Importance of Small Mountainous Rivers Geomorphic/Tectonic Control of Sediment Discharge to the Ocean: The Importance of Small, J. Geol., 100, 525–544, https://doi.org/10.1086/629606, 1991.
Mirus, B., Jones, E. S., Baum, R. L., Godt, J. W., Slaughter, S., Crawford, M. M., Lancaster, J., Stanley, T., Kirschbaum, D. B., Burns, W. J., Schmitt, R. G., Lindsey, K. O., and McCoy, K. M.: Landslides across the USA: occurrence, susceptibility, and data limitations, Landslides, 17, 2271–2285, 2020.
Mondini, A. C., Santangelo, M., Rocchetti, M., Rossetto, E., Manconi, A., and Monserrat, O.: Sentinel-1 SAR amplitude imagery for rapid landslide detection, Remote Sens., 11, 760, https://doi.org/10.3390/rs11070760, 2019.
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.
Montgomery, D. R., Schmidt, K. M., Dietrich, W. E., and McKean, J.: Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability, J. Geophys. Res.-Earth, 114, F01031, https://doi.org/10.1029/2008JF001078, 2009.
Nowicki Jessee, M. A., Hamburger, M. W., Allstadt, K., Wald, D. J., Robeson, S. M., Tanyas, H., Hearne, M., and Thompson, E. M.: A Global Empirical Model for Near-Real-Time Assessment of Seismically Induced Landslides, J. Geophys. Res.-Earth, 123, 1835–1859, https://doi.org/10.1029/2017JF004494, 2018.
Pawluszek, K., Borkowski, A., and Tarolli, P.: Sensitivity analysis of automatic landslide mapping: numerical experiments towards the best solution, Landslides, 15, 1851–1865, https://doi.org/10.1007/s10346-018-0986-0, 2018.
Petley, D. Global patterns of loss of life from landslides, Geology, 40,
927–930, https://doi.org/10.1130/G33217.1, 2012.
Planet Team: Planet Application Program Interface: In Space for Life on Earth, Planet Team, San Francisco, CA, https://api.planet.com (last access: 31 March 2022), 2017.
Prancevic, J. P., Lamb, M. P., McArdell, B. W., Rickli, C., and Kirchner, J. W.: Decreasing landslide erosion on steeper slopes in soil-mantled landscapes, Geophys. Res. Lett., 47, e2020GL087505, https://doi.org/10.1029/2020GL087505, 2020.
Rault, C., Robert, A., Marc, O., Hovius, N., and Meunier, P.: Seismic and
geologic controls on spatial clustering of landslides in three large earthquakes, Earth Surf. Dynam., 7, 829–839, https://doi.org/10.5194/esurf-7-829-2019, 2019.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 31 March 2022), 2018.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., and Guzzetti, F.: A
review of statistically-based landslide susceptibility models, Earth-Sci.
Rev., 180, 60–91, https://doi.org/10.1016/j.earscirev.2018.03.001, 2018.
Riley, S. J., DeGloria, S. D., and Elliot, R.: A Terrain Ruggedness Index that Quantifies Topographic Heterogeneity, Intermount. J. Sci., 5, 23–27, 1999.
Roering, J. J., Kirchner, J. W., Sklar, L. S., and Dietrich, W. E.: Hillslope evolution by nonlinear creep and landsliding: An experimental study, Geology, 29, 143–146, https://doi.org/10.1130/0091-7613(2001)029<0143:HEBNCA>2.0.CO;2, 2001.
Rossi, G., Tanteri, L., Tofani, V., Vannocci, P., Moretti, S., and Casagli,
N.: Multitemporal UAV surveys for landslide mapping and characterization,
Landslides, 15, 1045–1052, https://doi.org/10.1007/s10346-018-0978-0, 2018.
Santangelo, M., Marchesini, I., Cardinali, M., Fiorucci, F., Rossi, M., Bucci, F., and Guzzetti, F.: A method for the assessment of the influence of
bedding on landslide abundance and types, Landslides, 12, 295–309,
https://doi.org/10.1007/s10346-014-0485-x, 2015.
Schmitt, R. G., Tanyas, H., Nowicki Jessee, M. A., Zhu, J., Biegel, K. M.,
Allstadt, K. E., Jibson, R. W., Thompson, E. M., van Westen, C. J., Sato, H. P., Wald, D. J., Godt, J. W., Gorum, T., Xu, C., Rathje, E. M., and Knudsen, K. L.: An open repository of earthquake-triggered ground-failure inventories, Data Series, USGS, Reston, VA, https://doi.org/10.3133/ds1064, 2017.
Selby, M. J.: Controls on the Stability and Inclinations of Hillslopes formed
on hard rock, Earth Surf. Proc. Land., 7, 449–467, https://doi.org/10.1002/esp.3290070506, 1982.
Sörensen, R., Zinko, U., and Seibert, J.: On the calculation of the topographic wetness index: evaluation of different methods based on field observations, Hydrol. Earth Syst. Sci., 10, 101–112, https://doi.org/10.5194/hess-10-101-2006, 2006.
Stanley, T. A. and Kirschbaum, D. B.: A heuristic approach to global landslide susceptibility mapping, Nat. Hazards, 87, 145–164, https://doi.org/10.1007/s11069-017-2757-y, 2017.
Tanyaş, H. and Lombardo, L.: Variation in landslide-affected area under
the control of ground motion and topography, Eng. Geol., 260, 105229, https://doi.org/10.1016/j.enggeo.2019.105229, 2019.
Tanyaş, H., van Westen, C. J., Allstadt, K. E., Nowicki Jessee, M. A., Gorum, T., Jibson, R. W., Godt, J. W., Sato, H. P., Schmitt, R. G., Marc, O., and Hovius, N.: Presentation and Analysis of Earthquake-Induced Landslide Inventories, J. Geophys. Res.-Earth, 122, 1991–2015, https://doi.org/10.1002/2017JF004236, 2017.
Tanyaş, H., Rossi, M., Alvioli, M., van Westen, C. J., and Marchesini, I.: A global slope unit-based method for the near real-time prediction of earthquake-induced landslides, Geomorphology, 327, 126–146, https://doi.org/10.1016/j.geomorph.2018.10.022, 2019.
The Association of Japanese Geographers: The 2018 July Heavy rain in West
Japan, http://ajg-disaster.blogspot.com/2018/07/3077.html, last access: 1 November 2019.
Tibshirani, R.: Regression Shrinkage and Selection via the Lasso, J. Roy. Stat. Soc. Ser. B, 58, 267–288, https://doi.org/10.1111/j.2517-6161.1996.tb02080.x, 1996.
Van Den Eeckhaut, M. and Hervás, J.: Geomorphology State of the art of
national landslide databases in Europe and their potential for assessing
landslide susceptibility, Hazard Risk, 140, 545–558, https://doi.org/10.1016/j.geomorph.2011.12.006, 2012.
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, https://doi.org/10.1007/s10346-011-0299-z, 2012.
van Westen, C. J. and Zhang, J.: Landslides and floods triggered by Hurricane Maria (18 September, 2017) in Dominica, Digital or Visual Products, UNITAR-UNOSAT, http://www.unitar.org/unosat/node/44/2762 (last access: 31 March 2022), 2018.
van Westen, C., Jetten, V., and Alkema, D.: Validating national landslide susceptibility and hazard maps for Caribbean island countries: the case of Dominica and tropical storm Erika, in: EGU General Assembly Conference Abstracts, April 2016, EPSC2016-4334, 2016.
Wasowski, J., Keefer, D. K., and Lee, C. T.: Toward the next generation of research on earthquake-induced landslides: current issues and future challenges, Eng. Geol., 122, 1–8, https://doi.org/10.1016/j.enggeo.2011.06.001, 2011.
Weiss, A.: Topographic Position and Landforms Analysis, in: ESRI User Conference, San Diego, CA, http://www.jennessent.com/downloads/TPI-poster-TNC_18x22.pdf (last access: 31 March 2022), 2001.
Williams, J. G., Rosser, N. J., Kincey, M. E., Benjamin, J., Oven, K. J.,
Densmore, A. L., Milledge, D. G., Robinson, T. R., Jordan, C. A., and Dijkstra, T. A.: Satellite-based emergency mapping using optical imagery:
experience and reflections from the 2015 Nepal earthquakes, Nat. Hazards
Earth Syst. Sci., 18, 185–205, https://doi.org/10.5194/nhess-18-185-2018, 2018.
Xu, C., Dai, F., Xu, X., and Hsi, Y.: GIS-based support vector machine modeling of earthquake-triggered landslide susceptibility in the Jianjiang
River watershed, China, Geomorphology, 145–146, 70–80, https://doi.org/10.1016/j.geomorph.2011.12.040, 2012.
Short summary
Understanding where landslides occur in mountainous areas is critical to support hazard analysis as well as understand landscape evolution. In this study, we present a large compilation of inventories of landslides triggered by rainfall, including several that are described here for the first time. We analyze the topographic characteristics of the landslides, finding consistent relationships for landslide source and deposition areas, despite differences in the inventories' locations.
Understanding where landslides occur in mountainous areas is critical to support hazard analysis...
Altmetrics
Final-revised paper
Preprint