Articles | Volume 15, issue 10
https://doi.org/10.5194/nhess-15-2257-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/nhess-15-2257-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A dynamic landslide hazard assessment system for Central America and Hispaniola
D. B. Kirschbaum
CORRESPONDING AUTHOR
Hydrological Sciences Laboratory, Goddard Space Flight Center, Greenbelt, Maryland, USA
T. Stanley
Hydrological Sciences Laboratory, Goddard Space Flight Center, Greenbelt, Maryland, USA
Universities Space Research Association, Columbia, Maryland, USA
J. Simmons
Columbia University, New York, USA
Related authors
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
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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.
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
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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
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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.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
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.
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
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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.
Related subject area
Landslides and Debris Flows Hazards
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
Optimization strategy for flexible barrier structures: Investigation and back analysis of a rockfall disaster case in southwestern China
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
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
Space-time landslide hazard modeling via Ensemble Neural Networks
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)
Numerical model derived intensity-duration thresholds for early warning of rainfall-induced debris flows in the Himalayas
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
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
Short summary
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
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A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 2023
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Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here, we present new results from a Doppler radar rockfall alarm system, which has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 2023
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Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
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The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
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Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
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Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
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
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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.
Li-Ru Luo, Zhi-Xiang Yu, Qi Wang, Li-Jun Zhang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-136, https://doi.org/10.5194/nhess-2023-136, 2023
Revised manuscript accepted for NHESS
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Field investigations were done on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was presumed from UAV survey. A FEM model, including the barrier and rocks, was created to reproduce the damage evolution. It was found that the impact kinetic energy was below the design protection energy. The improper member connections prevent the barrier from producing significant deformation to absorb energy. Damages are avoided by improving the nets’ and ropes’ ability to slide.
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
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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
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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
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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
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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
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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
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In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
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
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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
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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
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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.
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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Srikrishnan Siva Subramanian, Piyush Srivastava, Ali Pulpadan Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-297, https://doi.org/10.5194/nhess-2022-297, 2023
Revised manuscript accepted for NHESS
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Rainfall intensity-duration (ID) thresholds can aid in the prediction of natural disasters. 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 model (WRF) with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Cited articles
Aleotti, P.: A warning system for rainfall-induced shallow failures, Eng. Geol., 73, 247–265, https://doi.org/10.1016/j.enggeo.2004.01.007, 2004.
Alpert, L.: The areal distribution of mean annual rainfall over the Island of Hispaniola, Mon. Weather Rev., 69, 201–204, 1941.
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.
Berti, M., Martina, M. L. V, Franceschini, S., Pignone, S., Simoni, A., and Pizziolo, M.: Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach, J. Geophys. Res.-Earth, 117, F04006, https://doi.org/10.1029/2012JF002367, 2012.
Brunetti, M. T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., and Guzzetti, F.: Rainfall thresholds for the possible occurrence of landslides in Italy, Nat. Hazards Earth Syst. Sci., 10, 447–458, https://doi.org/10.5194/nhess-10-447-2010, 2010.
Bucknam, R. C., Coe, J. A., Chavarria, M. M., Godt, J. W., Tarr, A. C., Bradley, L., Rafferty, S., Hancock, D., Dart, R. L. and Johnson, M. L.: Landslides triggered by Hurricane Mitch in Guatemala – Inventory and Discussion, US Geol. Surv. Open-File Rep. 01-443, US Geological Survey, Denver, Colorado, 1–40, 2001.
Caine, N.: The Rainfall Intensity: Duration Control of Shallow Landslides and Debris Flows, Geogr. Ann. Phys. Geogr., 62, 23–27, 1980.
Cannon, S. H., Haller, K. M., Ekstrom, I., Schweig III, E. S., Devoli, G., Moore, D. W., Rafferty, S. A. and Tarr, A. C.: Landslide Response to Hurricane Mitch Rainfall in Seven Study Areas in Nicaragua, Open-File Report 01-412-A, US Geological Survey, available from: http://pubs.usgs.gov/of/2001/ofr-01-0412-a/OFR01-412-A.access.pdf (last access: 14 April 2013), 1–17, 2001.
Cepeda, J., Hoeg, K., and Nadim, F.: Landslide-triggering rainfall thresholds: a conceptual framework, Q. J. Eng. Geol. Hydrogeol., 43, 69–84, 2009.
Cepeda, J., Chávez, J. A., and Cruz Martínez, C.: Procedure for the selection of runout model parameters from landslide back-analyses: application to the Metropolitan Area of San Salvador, El Salvador, Landslides, 7, 105–116, https://doi.org/10.1007/s10346-010-0197-9, 2010a.
Cepeda, J., Díaz, M. R., Nadim, F., Høeg, K., and Elverhøi, A.: Generalised form of a power law threshold function for rainfall-induced landslides, in: EGU General Assembly, p. 8256, Vienna, Austria, 2010b.
Chleborad, A. F.: Temperature, Snowmelt, and the Onset of Spring Season Landslides in the Central Rocky Mountains, Open-File Report 97-27, US Geological Survey, Denver, Colorado, 1997.
Chleborad, A. F., Baum, R. L., and Godt, J. W.: Rainfall Thresholds for Forecasting Landslides in the Seattle, Washington, Area – Exceedance and Probability, US Geol. Surv. Open-File Rep. 2006-1064, US Geological Survey, Reston, VA, 2006.
CIESIN and ITOS – Center for International Earth Science Information Network (CIESIN)/Columbia University and Georgia, I. T. O. S. (ITOS)/University of: Global Roads Open Access Data Set, Version 1 (gROADSv1), available at: http://sedac.ciesin.columbia.edu/data/set/groads-global-roads-open-access-v1 (last access: 14 February 2015), 2013.
Crone, A. J., Baum, R. L., Lidke, D. J., Sather, D. N., Bradley, L.-A., and Tarr, A. C.: Landslides induced by Hurricane Mitch in El Salvador – an inventory and descriptions of selected features, Open-File Report 01-444, US Geological Survey, Denver, Colorado, 2001.
Dahal, R. K. and Hasegawa, S.: Representative rainfall thresholds for landslides in the Nepal Himalaya, Geomorphology, 100, 429–443, https://doi.org/10.1016/j.geomorph.2008.01.014, 2008.
Devoli, G., Morales, A., and Hoeg, K.: Historical landslides in Nicaragua – collection and analysis of data, Landslides, 4, 5–18, https://doi.org/10.1007/s10346-006-0048-x, 2006.
Devoli, G., Strauch, W., Chavez, G., and Hoeg, K.: A landslide database for Nicaragua: a tool for landslide-hazard management, Landslides, 4, 163–176, https://doi.org/10.1007/s10346-006-0074-8, 2007.
Devoli, G., De Blasio, F. V., Elverhoi, A., and Hoeg, K.: Statistical Analysis of Landslide Events in Central America and their Run-out Distance, Geotech. Geol. Eng., 27, 23–42, https://doi.org/10.1007/s10706-008-9209-0, 2008.
Do Amaral Vargas Jr., E., Velloso, R., Chávez, L., Gusmão, L., and do Amaral, C.: On the Effect of Thermally Induced Stresses in Failures of Some Rock Slopes in Rio de Janeiro, Brazil, Rock Mech. Rock Eng., 46, 123–134, https://doi.org/10.1007/s00603-012-0247-9, 2013.
FAO/IIASA/ISRIC/ISSCAS/JRC: Harmonized World Soil Database, Version 1.2, available from: http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/ (last access: 6 July 2014), 2012.
Farahmand, A. and AghaKouchak, A.: A satellite-based global landslide model, Nat. Hazards Earth Syst. Sci., 13, 1259–1267, https://doi.org/10.5194/nhess-13-1259-2013, 2013.
Fawcett, T.: An introduction to ROC analysis, Pattern Recog. Lett., 27, 861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Frattini, P., Crosta, G., and Sosio, R.: Approaches for defining thresholds and return periods for rainfall-triggered shallow landslides, Hydrol. Process., 1460, 1444–1460, 2009.
French, C. D. and Schenk, C. J.: Map Showing Geology, Oil and Gas Fields, and Geologic Provinces of the Caribbean Region, Open File Report 97-470-K, US Geological Survey, Denver, CO., 2004.
Gerencia de Geología: Landslide inventory of El Salvador, El Salvador, available at: http://www.marn.gob.sv/ (last access: 5 March 2013), 2012.
Godt, J. W., Baum, R. L., and Chleborad, A. F.: Rainfall characteristics for shallow landsliding in Seattle, Washington, USA, Earth Surf. Proc. Land, 31, 97–110, https://doi.org/10.1002/esp.1237, 2006.
Guha-Sapir, D., Below, R., and Hoyois, P.: EM-DAT: International Disaster Database, Univ. Cathol. Louvain–Brussels–Belgium, available at: http://www.em-dat.net, last access: 20 March 2014.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, 2007.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: The rainfall intensity–duration control of shallow landslides and debris flows: an update, Landslides, 5, 3–17, https://doi.org/10.1007/s10346-007-0112-1, 2008.
Harp, 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, Open-File Report 2004-1348, US Geological Survey, Denver, CO, 1–24. 2004.
Heroku: Heroku Cloud Application Platform, available from: https://aws.amazon.com/marketplace/pp/B008DJG1TY/ref=sp_mpgproduct_title/178-1902068-2217163?ie=UTF8&sr=0-2, last access: 8 March 2015.
Hijmans, R. and van Etten, J.: raster: raster: Geographic data analysis and modeling, R Packag. version 2, available at: https://cran.r-project.org/web/packages/raster/raster.pdf (last access: November 2014), update 8 September 2015, 2014.
Hong, Y., Adler, R., and Huffman, G.: Evaluation of the potential of NASA multi-satellite precipitation analysis in global landslide hazard assessment, Geophys. Res. Lett., 33, L22402, https://doi.org/10.1029/2006GL028010, 2006.
Hong, Y., Adler, R., and Huffman, G.: Use of satellite remote sensing data in the mapping of global landslide susceptibility, Nat. Hazards, 43, 245–256, https://doi.org/10.1007/s11069-006-9104-z, 2007.
Hromadka II, T. V., Hromadka III, T. V., and Phillips, M.: Use of Rainfall Statistical Return Periods to Determine Threshold for Mass Wasting Events, Environ. Eng. Geosci., XVI, 343–356, 2010.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., and Wolff, D. B.: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales, J. Hydrometeorol., 8, 38–55, https://doi.org/10.1175/JHM560.1, 2007.
Huffman, G. J., Adler, R. F., Bolvin, D. T., and Nelkin, E. J.: The TRMM Multi-satellite Precipitation Analysis (TMPA), in Satellite Rainfall Applications for Surface Hydrology, edited by: Hossain, F. and Gebremichael, M., Springer Verlag, Dordrecht, 3–22, 2010.
INETER: Localización de deslizamientos en las comunidades Cerro Azul y La Gongolona, municipo El Ayote, Nicaragua, 2014.
IPCC: Climate Change 2007: Working Group I: The Physical Science Basis, IPCC Fourt., edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge and New York, 2007.
Jackson, T. J. and Schmugge, T. J.: Vegetation effects on the microwave emission of soils, Remote Sens. Environ., 36, 203–212, https://doi.org/10.1016/0034-4257(91)90057-D, 1991.
Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., and Lerner-Lam, A.: A global landslide catalog for hazard applications: method, results, and limitations, Nat. Hazards, 52, 561–575, https://doi.org/10.1007/s11069-009-9401-4, 2010.
Kirschbaum, D. B., Adler, R., Adler, D., Peters-Lidard, C., and Huffman, G.: Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years, J. Hydrometeorol., 13, 1536–1551, https://doi.org/10.1175/JHM-D-12-02.1, 2012a.
Kirschbaum, D. B., Adler, R., Hong, Y., Kumar, S., Peters-Lidard, C., and Lerner-Lam, A.: Advances in landslide nowcasting: evaluation of a global and regional modeling approach, Environ. Earth Sci., 66, 1683–1696, https://doi.org/10.1007/s12665-011-0990-3, 2012b.
Kirschbaum, D. B., Stanley, T., and Yatheendradas, S.: Modeling Landslide Susceptibility over Large Regions with Fuzzy Overlay, Landslides, https://doi.org/10.1007/s10346-015-0577-2, in press, 2015a.
Kirschbaum, D. B., Stanley, T., and Zhou, Y.: Spatial and Temporal Analysis of a Global Landslide Catalog, Geomorphology, https://doi.org/10.1016/j.geomorph.2015.03.016, in press, 2015b.
Kohler, M. and Linsley, R.: Predicting the runoff from storm rainfall, Weather Bur. Res. Pap. No. 34, 1951.
Lagomarsino, D., Segoni, S., Fanti, R., and Catani, F.: Updating and tuning a regional-scale landslide early warning system, Landslides, 10, 91–97, https://doi.org/10.1007/s10346-012-0376-y, 2013.
Larsen, M. C. and Simon, A.: A Rainfall Intensity-Duration Threshold for Landslides in a Humid-Tropical Environment, Puerto Rico, Geogr. Ann. Phys. Geogr., 75, 13–23, 1993.
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.
Li, C., Ma, T., Zhu, X., and Li, W.: The power–law relationship between landslide occurrence and rainfall level, Geomorphology, 130, 221–229, https://doi.org/10.1016/j.geomorph.2011.03.018, 2011.
Li, T., Li, P., and Wang, H.: Forming Mechanisms of Landslides in the Seasonal Frozen Loess Region in China, in: Landslides in Cold Regions in the Context of Climate Change, edited by: Shan, W., Guo, Y., Wang, F., Marui, H., and Strom, A., Springer, Switzerland, 41–52, 2013.
Liao, Z., Hong, Y., Kirschbaum, D., and Liu, C.: Assessment of shallow landslides from Hurricane Mitch in central America using a physically based model, Environ. Earth Sci., 66, 1697–1705, https://doi.org/10.1007/s12665-011-0997-9, 2012.
Martelloni, G., Segoni, S., Fanti, R., and Catani, F.: Rainfall thresholds for the forecasting of landslide occurrence at regional scale, Landslides, 9, 485–495, https://doi.org/10.1007/s10346-011-0308-2, 2012.
Mathew, J., Babu, D. G., Kundu, S., Kumar, K. V., and Pant, C. C.: Integrating intensity–duration-based rainfall threshold and antecedent rainfall-based probability estimate towards generating early warning for rainfall-induced landslides in parts of the Garhwal Himalaya, India, Landslides, 11, 575–588, https://doi.org/10.1007/s10346-013-0408-2, 2014.
Montgomery, D. R. and Dietrich, W. E.: A physically based model for the topographic control on shallow landsliding, Water Resour. Res., 30, 1153, https://doi.org/10.1029/93WR02979, 1994.
Montrasio, L., Valentino, R., and Losi, G. L.: Towards a real-time susceptibility assessment of rainfall-induced shallow landslides on a regional scale, Nat. Hazards Earth Syst. Sci., 11, 1927–1947, https://doi.org/10.5194/nhess-11-1927-2011, 2011.
Mora, S. C.: Extent and Socio-Economic Significance of Slope-Instability on the Island of Hispaniola (Haiti and Dominican Republic), in: Energy and Mineral Potential of Central America-Caribbean Regions, edited by: Miller, R. L., Escalante, G., Reinemund, J. A., and Bergin, M. J., Springer-Verlag, Berlin, Heidelberg, 1995.
Mora, S. C. and Vahrson, W.-G.: Macrozonation Methodology for Landslide Hazard Determination, Bull. Assoc. Eng. Geol., XXXI, 49–58, 1994.
Nadim, F., Kjekstad, O., Peduzzi, P., Herold, C., and Jaedicke, C.: Global landslide and avalanche hotspots, Landslides, 3, 159–173, https://doi.org/10.1007/s10346-006-0036-1, 2006.
Nadim, F., Cepeda, J., Sandersen, F., Jaedicke, C., and Heyerdahl, H.: Prediction of Rainfall-Induced Landslides through Empirical and Numerical Models, in: Rainfall-Induced Landslides: mechanisms, monitoring techniques and nowcasting models for early-warning systems, First Italian Workshop on Landslides, Naples, 1–10, 2009.
Njoku, E. G., Jackson, T. J., Lakshmi, V., Chan, T. K., and Nghiem, S. V: Soil moisture retrieval from AMSR-E, IEEE T. Geosci. Remote, 41, 215–229, 2003.
Pradhan, B. and Lee, S.: Landslide susceptiblity assessment and factor effect analysis: backpropagation artifical neural networks and their comparison with frequency ratio and bivariate logistic regression modelling, Environ. Model. Softw., 25, 747–759, https://doi.org/10.1016/j.envsoft.2009.10.016, 2010.
R Core Team: R: A language and environment for statistical computing, R Found. Stat. Comput., Version 3.0.1, available at: http://www.r-project.org/, last access: 16 May 2013.
Ray, R. L. and Jacobs, J. M.: Relationships among remotely sensed soil moisture, precipitation and landslide events, Nat. Hazards, 43, 211–222, https://doi.org/10.1007/s11069-006-9095-9, 2007.
Rossi, M., Kirschbaum, D., Luciani, S., and Guzzetti, F.: Comparison of TRMM satellite rainfall estimates with rain gauge data and landslide empirical rainfall thresholds under different morphological and climatological conditions in Italy, in: EGU General Assembly, 22–27 April 2012, Vienna, Austria, p. 9354, 2012.
Saito, H., Nakayama, D. and Matsuyama, H.: Relationship between the initiation of a shallow landslide and rainfall intensity–duration thresholds in Japan, Geomorphology, 118, 167–175, https://doi.org/10.1016/j.geomorph.2009.12.016, 2010.
Segoni, S., Lagomarsino, D., Fanti, R., Moretti, S., and Casagli, N.: Integration of rainfall thresholds and susceptibility maps in the Emilia Romagna (Italy) regional-scale landslide warning system, Landslides, 12, 773–785 https://doi.org/10.1007/s10346-014-0502-0, 2014.
Swenson, S., Famiglietti, J., Basara, J., and Wahr, J.: Estimating profile soil moisture and groundwater variations using GRACE and Oklahoma Mesonet soil moisture data, Water Resour. Res., 44, W01413, https://doi.org/10.1029/2007WR006057, 2008.
Tatard, L., Grasso, J. R., Helmstetter, A., and Garambois, S.: Characterization and comparison of landslide triggering in different tectonic and climatic settings, J. Geophys. Res., 115, F04040, https://doi.org/10.1029/2009JF001624, 2010.
Terlien, M. T. J.: The determination of statistical and deterministic hydrological landslide-triggering thresholds, Environ. Geol., 35, 124–130, 1998.
Tiranti, D. and Rabuffetti, D.: Estimation of rainfall thresholds triggering shallow landslides for an operational warning system implementation, Landslides, 7, 471–481, https://doi.org/10.1007/s10346-010-0198-8, 2010.
Van Den Eeckhaut, M., Reichenbach, P., Guzzetti, F., Rossi, M., and Poesen, J.: Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium, Nat. Hazards Earth Syst. Sci., 9, 507–521, https://doi.org/10.5194/nhess-9-507-2009, 2009.
Verdin, K. L., Godt, J., Funk, C., Pedreros, D., Worstell, B., and Verdin, J.: Development of a Global Slope Dataset for Estimation of Landslide Occurrence Resulting from Earthquakes, US Geol. Surv. Open-File 1-29, US Geological Survey, Reston, Virginia, 2007.
Wieczorek, G. F.: Effect of rainfall intensity and duration on debris flows in central Santa Cruz Mountains, in: Debris Flows/Avalanches: Process, Recognition, and Mitigation, Reviews in Engineering Geology, vol. 7, edited by: Costa, J. E. and Wieczorek, G. F., Geological Society of America, Boulder, CO., 93–104, 1987.
Short summary
This research presents a new framework for evaluating potential landslide activity in near real time. This system was implemented in Central America and the Caribbean by integrating a regional susceptibility map and satellite-based rainfall estimates into a binary decision tree, considering both daily and antecedent rainfall. The model demonstrates the capability to use free, globally available satellite products for near real-time regional landslide hazard assessment and situational awareness.
This research presents a new framework for evaluating potential landslide activity in near real...
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