Articles | Volume 24, issue 5
https://doi.org/10.5194/nhess-24-1579-2024
© Author(s) 2024. 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-24-1579-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 May 2024
Research article |
| 06 May 2024
| 06 May 2024
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
U.S. Geological Survey, Golden, Colorado 80401, USA
Dianne L. Brien
U.S. Geological Survey, Moffett Field, California 94035, USA
Mark E. Reid
U.S. Geological Survey, Moffett Field, California 94035, USA
William H. Schulz
U.S. Geological Survey, Golden, Colorado 80401, USA
Matthew J. Tello
U.S. Geological Survey, Golden, Colorado 80401, USA
currently at: Colorado Department of Transportation, Denver, Colorado 80204, USA
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Landslides and Debris Flows Hazards
Evaluation of debris-flow building damage forecasts
Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA
Morphological characteristics and conditions of drainage basins contributing to the formation of debris flow fans: an examination of regions with different rock strength using decision tree analysis
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
Analysis of three-dimensional slope stability combined with rainfall and earthquake
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
Evaluating Post-Wildfire Debris Flow Rainfall Thresholds and Volume Models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
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
Addressing Class Imbalance in Soil Movement Predictions
Assessing Landslide Damming susceptibility in Central Asia
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
Assessing the impact of climate change to landslides using public data, a case study from Vejle, Denmark
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
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
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
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
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Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
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Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
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Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
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We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
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We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
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Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-181, https://doi.org/10.5194/nhess-2023-181, 2023
Revised manuscript accepted for NHESS
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By a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, we derive the calculation of the seepage force. A global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquake. The reliability of the proposed method is also verified with two examples combining software calculations and previous results.
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.
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
EGUsphere, https://doi.org/10.5194/egusphere-2023-2063, https://doi.org/10.5194/egusphere-2023-2063, 2023
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Every year the U.S. Geological Survey produces 50–100 postfire debris flow hazard assessments using models for debris flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris flow response, and debris flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a two year period. We also proposed ways to improve these models.
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.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
EGUsphere, https://doi.org/10.5194/egusphere-2023-1417, https://doi.org/10.5194/egusphere-2023-1417, 2023
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Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-Means SMOTE achieves high accuracy (99.68 %), precision, recall, and F1-score, followed by RF with K-Means SMOTE. Our findings highlight the potential of these models to improve soil movement predictions in landslide-prone areas.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umuralievd, and Veronica Tofani
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-140, https://doi.org/10.5194/nhess-2023-140, 2023
Revised manuscript accepted for NHESS
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Central Asia regions are characterized by active tectonics, high mountains with glaciers and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of potential damming scenarios which endanger the population. To prevent this, a semi-automated GIS-based mapping method, centred on a bivariate correlation of morphometric parameters, was applied to spatially assess the rivers obstruction in Central Asia.
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.
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.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-68, https://doi.org/10.5194/nhess-2023-68, 2023
Revised manuscript accepted for NHESS
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In this study, we examine how future climate change may affect activity in landslides in Denmark using publicly available data. Our findings show that climate change will increase groundwater table depth, which will lead to increased landslide activity. During past events of extremely wet winters in this region, landslides caused damage to buildings and infrastructure.
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.
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.
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.
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.
Cited articles
Aaron, J., McDougall, S., Moore, J. R., Coe, J. A., and Hungr, O.: The role of initial coherence and path materials in the dynamics of three rock avalanche case histories, Geoenvironmental Disasters, 4, 5, https://doi.org/10.1186/s40677-017-0070-4, 2017.
Alvioli, M. and Baum, R. L.: Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface, Environ. Modell. Softw., 81, 122–135, https://doi.org/10.1016/j.envsoft.2016.04.002, 2016a.
Alvioli, M. and Baum, R. L.: Serial and parallel versions of the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS, version 2.1), U.S. Geol. Surv. software release [code], https://doi.org/10.5066/F7M044QS, 2016b.
Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., and Guzzetti, F.: Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling, Geosci. Model Dev., 9, 3975–3991, https://doi.org/10.5194/gmd-9-3975-2016, 2016.
Arnone, E., Noto, L., Lepore, C., and Bras, R.: Physically-based and distributed approach to analyze rainfall-triggered landslides at watershed scale, Geomorphology, 133, 121–131, https://doi.org/10.1016/j.geomorph.2011.03.019, 2011.
ASTM International: D2487-17e1, Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System), https://doi.org/10.1520/D2487-17E01, 2020.
Baum, R. L.: Rapid sensitivity analysis for reducing uncertainty in landslide hazard assessments, in: Understanding and Reducing Landslide Disaster Risk, edited by: Guzzetti, F., Mihalić Arbanas, S., Reichenbach, P., Sassa, K., Bobrowsky, P. T., and Takara, K., Springer, Cham, Switzerland, 329–335, https://doi.org/10.1007/978-3-030-60227-7_37, 2021.
Baum, R. L.: Slabs3D – A Fortran 95 program for analyzing potential shallow landslides in a digital landscape, U.S. Geol. Surv. software release [code], https://doi.org/10.5066/P9G4I8IU, 2023.
Baum, R. L. and Lewis, A. C.: Engineering soil classification and geotechnical measurements in Lares, Naranjito, and Utuado, Puerto Rico: U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9UXTQ4B, 2023.
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.-Earth, 115, F03013, https://doi.org/10.1029/2009JF001321, 2010.
Baum, R. L., Godt, J. W., Coe, J. A., and Reid, M. E.: Assessment of shallow landslide potential using 1D and 3D slope stability analysis, in: Landslides and Engineered Slopes: Protecting Society through Improved Understanding, edited by: Eberhardt, E., Froese, C., Turner, A. K., and Leroueil, S., Taylor & Francis Group, London, 1667–1672, ISBN 978-0-415-62123-6, 2012.
Baum, R. L., Schulz, W. H., Brien, D. L., Burns, W. L., Reid, M. E., and Godt, J. W.: Progress in regional landslide hazard assessment – Examples from the USA, in: Landslide Science for a Safer Geoenvironment, edited by: Sassa, K., Canuti, P., and Yin, Y., Springer, Cham, Switzerland, 21–36, https://doi.org/10.1007/978-3-319-04999-1_2, 2014.
Baum, R. L., Cerovski-Darriau, C., Schulz, W. H., Bessette-Kirton, E., Coe, J. A., Smith, J. B., and Smoczyk, G. M.: Variability of hurricane María debris-flow source areas in Puerto Rico – Implications for hazard assessment, AGU Fall Meeting, Washington, DC 2018, NH14A-02, https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/412740 (last access: 10 August 2023), 2018.
Baum, R. L., Scheevel, C. R., and Jones, E. S.: Constraining parameter uncertainty in modeling debris-flow initiation during the September 2013 Colorado Front Range storm, in: Debris-flow Hazards Mitigation: Mechanics, Monitoring, Modeling, and Assessment, edited by: Kean, J. W., Coe, J. A., Santi, P. M., and Guillen, B. K., Association of Environmental and Engineering, Brunswick, Ohio, 249–256, https://doi.org/10.25676/11124/173212, 2019.
Baum, R. L., Bedinger, E. C., and Tello, M. J.: REGOLITH – A Fortran 95 program for estimating soil mantle thickness in a digital landscape for landslide and debris-flow hazard assessment, U.S. Geol. Surv. software release [code], https://doi.org/10.5066/P9U2RDWJ, 2021.
Baum, R. L., Brien, D. L., Reid, M. E., Schulz, W. H., Tello, M. J., and Bedinger, E. C.: Model input and output data covering Lares Municipio, Utuado Municipio, and Naranjito Municipio, Puerto Rico, for landslide initiation susceptibility assessment after Hurricane Maria, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9C1U0LP, 2023.
Bawiec, W. J.: Geologic terranes of Puerto Rico, in: Geology, geochemistry, geophysics, mineral occurrences, and mineral resource assessment for the commonwealth of Puerto Rico, edited by: Bawiec, W. J., U.S. Geol. Surv. Open-File Rep. 98–38, https://doi.org/10.3133/ofr9838, 1998.
Baxstrom, K. W., Einbund, M. M., and Schulz, W. H.: Map data from landslides triggered by Hurricane María in a section of Naranjito, Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9GBGA4I, 2021a.
Baxstrom, K. W., Einbund, M. M., and Schulz, W. H.: Map data from landslides triggered by Hurricane María in the greater karst region of northwest Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9YYU7W1, 2021b.
Begueria, S.: Validation and evaluation of predictive models in hazard assessment and risk management, Nat. Hazards, 37, 315–329, https://doi.org/10.1007/s11069-005-5182-6, 2006.
Benda, L., Miller, D., Andras, K., Bigelow, P., Reeves, G., and Michael, D.: NetMap: A new tool in support of watershed science and resource management, Forest Sci., 53, 206–219, https://doi.org/10.1093/forestscience/53.2.206, 2007.
Bessette-Kirton, E. K., Coe, J. A., Godt, J. W., Kean, J. W., Rengers, F. K., Schulz, W. H., Baum, R. L., Jones, E. S., and Staley, D. M.: Map data showing concentration of landslides caused by hurricane María in Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/F7JD4VRF, 2017.
Bessette-Kirton, E. K., Cerovski-Darriau, C., Schulz, W. H., Coe, J. A., Kean, J. W., Godt, J. W., Thomas, M. A., and Hughes, K. S.: Landslides triggered by Hurricane María: Assessment of an extreme event in Puerto Rico, GSA Today, 29, 4–10, https://doi.org/10.1130/GSATG383A.1, 2019a.
Bessette-Kirton, E. K., Kean, J. W., Coe, J. A., Rengers, F. K., and Staley, D. M.: An evaluation of debris-flow runout model accuracy and complexity in Montecito, California: Towards a framework for regional inundation-hazard forecasting, in: Debris-flow Hazards Mitigation: Mechanics, Monitoring, Modeling, and Assessment, edited by: Kean, J. W., Coe, J. A., Santi, P. M., and Guillen, B. K., Association of Environmental and Engineering Geologists, Brunswick, Ohio, 257–264, https://doi.org/10.25676/11124/173211, 2019b.
Bessette-Kirton, E. K., Coe, J. A., Kelly, M. A., Cerovski-Darriau, C., and Schulz, W. H.: Map data from landslides triggered by Hurricane María in four study areas of Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9OW4SLX, 2019c.
Bessette-Kirton, E. K., Coe, J. A., Schulz, W. H., Cerovski-Darriau, C., and Einbund, M. M.: Mobility characteristics of debris slides and flows triggered by Hurricane María in Puerto Rico, Landslides, 17, 2795–2809, https://doi.org/10.1007/s10346-020-01445-z, 2020.
Brien, D. L., Reid, M. E., Cronkite-Ratcliff, C., and Perkins, J. P.: Portraying runout and inundation from hurricane-induced landslides in Puerto Rico, Geological Society of America Abstracts with Programs, 53, 85-4, https://doi.org/10.1130/abs/2021AM-368632, 2021.
Catani, F., Segoni, S., and Falorni, G.: An empirical geomorphology-based approach to the spatial prediction of soil thickness at catchment scale, Water Resour. Res., 46, W05508, https://doi.org/10.1029/2008WR007450, 2010.
Canli, E., Mergili, M., Thiebes, B., and Glade, T.: Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology, Nat. Hazards Earth Syst. Sci., 18, 2183–2202, https://doi.org/10.5194/nhess-18-2183-2018, 2018.
Carrara, A., Guzzetti, F., Cardinali, M., and Reichenbach, P.: Use of GIS technology in the prediction and monitoring of landslide hazard, Nat. Hazards, 20, 117–135, https://doi.org/10.1023/A:1008097111310, 1999.
Chung, C. F. and Fabbri, A. G.: Validation of spatial prediction models for landslide hazard mapping, Nat. Hazards, 30, 451–472, https://doi.org/10.1023/B:NHAZ.0000007172.62651.2b, 2003.
DeRose, R. C., Trustrum, N. A., and Blaschke, P. M.: Geomorphic change implied by regolith-slope relationships on steepland hillslopes, Taranaki, New Zealand, Catena, 18, 489–514, https://doi.org/10.1016/0341-8162(91)90051-X, 1991.
Einbund, M. M., Baxstrom, K. S., and Schulz, W. H.: Map data from landslides triggered by Hurricane María in four study areas in the Utuado municipality, Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9ZNUR1P, 2021a.
Einbund, M. M., Baxstrom, K. S., and Schulz, W. H.: Map data from landslides triggered by Hurricane María in four study areas in the Lares municipality, Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9EASZZ7, 2021b.
Ellen, S. D., Mark, R. K., Cannon, S. H., and Knifong, D. L.: Map of debris-flow hazard in the Honolulu District of Oahu, Hawaii, U.S. Geol. Surv. Open-File Rep. 93-213, 28 pp., https://doi.org/10.3133/ofr93213, 1993.
Fan, L., Lehmann, P., McArdell, B., and Or, D.: Linking rainfall-induced landslides with debris flows runout patterns towards catchment scale hazard assessment, Geomorphology, 280, 1–15, https://doi.org/10.1016/j.geomorph.2016.10.007, 2017.
Fawcett, T.: An introduction to ROC analysis, Pattern Recogn. Lett., 27, 861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Formetta, G., Capparelli, G., and Versace, P.: Evaluating performance of simplified physically based models for shallow landslide susceptibility, Hydrol. Earth Syst. Sci., 20, 4585–4603, https://doi.org/10.5194/hess-20-4585-2016, 2016.
George, D. L. and Iverson, R. M.: A depth-averaged debris-flow model that includes the effects of evolving dilatancy: 2. Numerical predictions and experimental tests, P. Roy. Soc. A-Math. Phy., 470, 20130820, https://doi.org/10.1098/rspa.2013.0820, 2014.
Godt, J. W., Schulz, W. H., Baum, R. L., and Savage, W. Z.: Modeling rainfall conditions for shallow landsliding in Seattle, Washington, in: Landslides and Engineering Geology of the Seattle, Washington, Area, edited by: Baum, R. L., Godt, J. W., and Highland, L. M., Geological Society of America, Boulder, Colorado, 137–152, https://doi.org/10.1130/2008.4020(08), 2008a.
Godt, J. W., Baum, R. L., Savage, W. Z., Salciarini, D., Schulz, W. H., and Harp, E. L.: Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework, Eng. Geol., 102, 214–226, https://doi.org/10.1016/j.enggeo.2008.03.019, 2008b.
Gomes, G. J. C., Vrugt, J. A., and Vargas Jr., E. A.: Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom-up control hypothesis using high-resolution topographic data, Water Resour. Res., 52, 3085–3112, https://doi.org/10.1002/2015WR018147, 2016.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modeling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Heidemann, H. K.: Lidar base specification (ver. 1.3, February 2018), U.S. Geological Survey Techniques and Methods, 11, 102 pp., https://doi.org/10.3133/tm11b4, 2018.
Ho, J.-Y., Lee, K. T., Chang, T.-C., Wang, Z.-Y., and Liao, Y.-H.: Influences of spatial distribution of soil thickness on shallow landslide prediction, Eng. Geol., 124, 38–46, https://doi.org/10.1016/j.enggeo.2011.09.013, 2012.
Hovland, H. J.: Three-dimensional slope stability analysis method, J. Geotech. Eng.-ASCE, 103, 971–986, https://doi.org/10.1061/AJGEB6.0000493, 1977.
Hsu, Y. C. and Liu, K. F.: Combining TRIGRS and DEBRIS-2D models for the simulation of a rainfall infiltration induced shallow landslide and subsequent debris flow, Water, 11, 890, https://doi.org/10.3390/w11050890, 2019.
Hughes, K. S. and Schulz, W. H.: Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico, U.S. Geol. Surv. Open-File Rep. 2020–1022, 91 pp., https://doi.org/10.3133/ofr20201022, 2020a.
Hughes, K. S. and Schulz, W. H.: Results from frequency-ratio analyses of soil classification and land use related to landslide locations in Puerto Rico following Hurricane María, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9VK2FAL, 2020b.
Hughes, K. S., Bayouth-García, D., Martínez-Milian, G. O., Schulz, W. H., and Baum, R. L.: Map of slope-failure locations in Puerto Rico after Hurricane María, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9BVMD74, 2019.
Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897–1910, https://doi.org/10.1029/2000WR900090, 2000.
Jibson, R. W.: Debris flows in southern Puerto Rico, in: Landslide processes of the eastern United States and Puerto Rico, edited by: Schultz, A. P. and Jibson, R. W., Geol. Soc. Am. Spec. Pap., 236, 29–55, https://doi.org/10.1130/SPE236-p29, 1989.
Jolly, W. T., Lidiak, E. G., Dickin, A. P., and Wu, T.-W.: Geochemical diversity of Mesozoic island arc tectonic blocks in eastern Puerto Rico, in: Tectonics and Geochemistry of the Northeastern Caribbean, edited by: Likiak, E. G. and Larue, D. K., Geol. Soc. Am. Spec Pap., 322, 67–98, https://doi.org/10.1130/0-8137-2322-1.67, 1998.
Larsen, M. C.: Landslides and sediment budgets in four watersheds in eastern Puerto Rico, in: Water Quality and Landscape Processes of Four Watersheds in Eastern Puerto Rico, edited by: Murphy, S. F. and Stallard, R. F., U.S. Geol. Surv. Prof. Paper 1789, 153–178, https://doi.org/10.3133/pp1789, 2012.
Larsen, M. C. and Parks, J. E.: Map showing landslide susceptibility in the Comerio municipality, Puerto Rico, U.S. Geol. Surv. Open-File Rep. 98-566, https://doi.org/10.3133/ofr98566, 1998.
Larsen, M. C. and Simon, A.: A rainfall intensity-duration threshold for landslides in a humid-tropical environment, Puerto Rico, Geogr. Ann. A, 75, 13–23, https://doi.org/10.1080/04353676.1993.11880379, 1993.
Larsen, M. C. and Torres-Sanchez, A. J.: Landslides triggered by hurricane Hugo in eastern Puerto Rico, September 1989, Caribb. J. Sci., 28, 113–125, 1992.
Larsen, M. C. and Torres-Sanchez, A. J.: The frequency and distribution of recent landslides in three montane tropical regions of Puerto Rico, Geomorphology, 24, 309–331, https://doi.org/10.1016/S0169-555X(98)00023-3, 1998.
Larsen, M. C., Santiago, M., Jibson, R., and Questell, E.: Map showing susceptibility to rainfall-triggered landslides in the municipality of Ponce, Puerto Rico, U.S. Geol. Surv. Scientific Investigations Map 2818, https://doi.org/10.3133/sim2818, 2004.
Lee, S., Ryu, J.-H., Min, K., and Won, J.-S.: Landslide susceptibility analysis using GIS and artificial neural network, Earth Surf. Proc. Land., 28, 1361–1376, https://doi.org/10.1002/esp.593, 2003.
Lepore, C., Kamal, S. A., Shanahan, P., and Bras, R. L.: Rainfall-induced landslide susceptibility zonation of Puerto Rico, Environ. Earth Sci., 66, 1667–1681, https://doi.org/10.1007/s12665-011-0976-1, 2012.
Lepore, C., Arnone, E., Noto, L. V., Sivandran, G., and Bras, R. L.: Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico, Hydrol. Earth Syst. Sci., 17, 3371–3387, https://doi.org/10.5194/hess-17-3371-2013, 2013.
Likos, W. J., Wayllace, A., Godt, J., and Lu, N.: Modified direct shear apparatus for unsaturated sands at low suction and stress, Geotech. Test. J., 33, 286–298, https://doi.org/10.1520/GTJ102927, 2010.
Medina, V., Hürlimann, M., Guo, Z., Lloret, A., and Vaunat, J.: Fast physically based model for rainfall-induced landslide susceptibility assessment at regional scale, Catena, 201, 105213, https://doi.org/10.1016/j.catena.2021.105213, 2021.
Mergili, M., Marchesini, I., Rossi, M., Guzzetti, F., and Fellin, W.: Spatially distributed three-dimensional slope stability modelling in a raster GIS, Geomorphology, 206, 178–195, https://doi.org/10.1016/j.geomorph.2013.10.008, 2014a.
Mergili, M., Marchesini, I., Alvioli, M., Metz, M., Schneider-Muntau, B., Rossi, M., and Guzzetti, F.: A strategy for GIS-based 3-D slope stability modelling over large areas, Geosci. Model Dev., 7, 2969–2982, https://doi.org/10.5194/gmd-7-2969-2014, 2014b.
Mergili, M., Schwarz, L., and Kociu, A.: Combining release and runout in statistical landslide susceptibility modeling, Landslides, 16, 2151–2165, https://doi.org/10.1007/s10346-019-01222-7, 2019.
Metz, C. E.: Basic principles of ROC analysis, Semin. Nucl. Med., 8, 283–298, https://doi.org/10.1016/S0001-2998(78)80014-2, 1978.
Milledge, D. G., Bellugi, D., McKean, J. A., Densmore, A. L., and Dietrich, W. E.: A multi-dimensional stability model for predicting shallow landslide size and shape across landscapes, J. Geophys. Res.-Earth, 119, 2481–2504, https://doi.org/10.1002/2014JF003135, 2015.
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.
Murphy, S. F., Stallard, R. F., Larsen, M. C., and Gould, W. A.: Physiography, geology, and land cover of four watersheds in eastern Puerto Rico, U.S. Geol. Surv. Prof. Paper 1789-A, 24 pp., https://doi.org/10.3133/pp1789A, 2012.
Monroe, W. H.: The karst landforms of Puerto Rico, U.S. Geol. Surv. Prof. Paper 899, 69 pp., https://doi.org/10.3133/pp899, 1976.
Nicótina, L., Tarboton, D. G., Tesfa, T. K., and Rinaldo, A.: Hydrologic controls on equilibrium soil depths, Water Resour. Res., 47, W04517, https://doi.org/10.1029/2010WR009538, 2011.
Pack, R. T., Tarboton, D. G., and Goodwin, C. N.: The SINMAP approach to terrain stability mapping, in: International Congress of the International Association of Engineering Geology and the Environment Proceedings, 8 September 21–25 1998, Vancouver, British Columbia, Canada, A. A. Balkema, Rotterdam, Netherlands, 2, 1157–1165, https://digitalcommons.usu.edu/cee_facpub/2583/ (last access: 13 March 2024), 1998.
Palacio Cordoba, J., Mergili, M., and Aristizábal, E.: Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model, Nat. Hazards Earth Syst. Sci., 20, 815–829, https://doi.org/10.5194/nhess-20-815-2020, 2020.
Pando, M. A., Ruiz, M. E., and Larsen, M. C.: Rainfall-induced landslides in Puerto Rico: An overview, in: Slopes and Retaining Structures Under Seismic and Static Conditions, edited by: Gabr, M. A., Bowders, J. J., Elton, D., and Zornberg, J. G., ASCE Geotech. SP., 140, 2911–2925, https://doi.org/10.1061/40787(166)25, 2005.
Patton, N. R., Lohse, K. A., Godsey, S. E., Crosby, B. T., and Seyfried, M. S.: Predicting soil thickness on soil mantled hillslopes, Nat. Commun., 9, 3329, https://doi.org/10.1038/s41467-018-05743-y, 2018.
Pelletier, J. D. and Rasmussen, C.: Geomorphically based predictive mapping of soil thickness in upland watersheds, Water Resour. Res., 45, W09417, https://doi.org/10.1029/2008WR007319, 2009.
Perkins, J. P., Baxstrom, K. W., Einbund, M. M., and Schulz, W. H.: Modified basal contact of the Tertiary Lares Limestone in the vicinity of Utuado, Puerto Rico, USA, derived from USGS Open-File Report 98-038, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9NL9EZG, 2022.
Raia, S., Alvioli, M., Rossi, M., Baum, R. L., Godt, J. W., and Guzzetti, F.: Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach, Geosci. Model Dev., 7, 495–514, https://doi.org/10.5194/gmd-7-495-2014, 2014.
Ramos-Scharrón, C. E., Arima, E. Y., Guidry, A., Ruffe, D., and Vest, B.: Sediment mobilization by hurricane-driven shallow landsliding in a wet subtropical watershed, J. Geophys. Res.-Earth, 126, e2020JF006054, https://doi.org/10.1029/2020JF006054, 2021.
Reid, M. E., Christian, S. B., Brien, D. L., and Henderson, S. T.: Scoops3D – Software to analyze 3D slope stability throughout a digital landscape, U.S. Geol. Surv. Techniques and Methods 14-A1 [code], 218 pp. https://doi.org/10.3133/tm14A1, 2015.
Reid, M. E., Coe, J. A., and Brien, D. L.: Forecasting inundation from debris flows that grow volumetrically during travel, with application to the Oregon coast range, USA, Geomorphology, 273, 396–411, https://doi.org/10.1016/j.geomorph.2016.07.039, 2016.
Roering, J. J.: How well can hillslope evolution models “explain” topography?, Geol. Soc. Am. Bull., 120, 1248–1262, https://doi.org/10.1130/B26283.1, 2008.
Rossi, G., Catani, F., Leoni, L., Segoni, S., and Tofani, V.: HIRESSS: a physically based slope stability simulator for HPC applications, Nat. Hazards Earth Syst. Sci., 13, 151–166, https://doi.org/10.5194/nhess-13-151-2013, 2013.
Schulz, W. H., Jensen, E. K., Cerovski-Darriau, C. R., Baum, R. L., Thomas, M. A., and Coe, J. A.: Field observations of landslides and related materials following Hurricane Maria, Puerto Rico, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9T9KZ6T, 2023.
Segoni, S., Leoni, L., Benedetti, A. I., Catani, F., Righini, G., Falorni, G., Gabellani, S., Rudari, R., Silvestro, F., and Rebora, N.: Towards a definition of a real-time forecasting network for rainfall induced shallow landslides, Nat. Hazards Earth Syst. Sci., 9, 2119–2133, https://doi.org/10.5194/nhess-9-2119-2009, 2009.
Simon, A., Larsen, M. C., and Hupp, C. R.: The role of soil processes in determining mechanisms of slope failure and hillslope development in a humid-tropical forest eastern Puerto Rico, Geomorphology, 3, 263–286, https://doi.org/10.1016/0169-555X(90)90007-D, 1990.
Simoni, S., Zanotti, F., Bertoldi, G., and Rigon, R.: Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS, Hydrol. Process., 22, 532–545, https://doi.org/10.1002/hyp.6886, 2008.
Smith, J. B., Thomas, M. A., Ashland, F., Michel, A. R., Wayllace, A., and Mirus, B. B.: Hillslope hydrologic monitoring data following Hurricane María in 2017, Puerto Rico, July 2018 to June 2020, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9548YK2, 2020.
Soil Survey Staff: Soil Survey Geographic (SSURGO) Database for Puerto Rico, all regions, U.S. Department of Agriculture Natural Resources Conservation Service, https://www.nrcs.usda.gov/resources/data-and-reports/web-soil-survey (last access: 10 August 2023), 2018.
Sowers, G. F.: Landslides in weathered volcanics in Puerto Rico, in: Proceedings of the Fourth Pan-American Conference on Soil Mechanics and Foundation Engineering, American Society of Civil Engineers, New York, 105–115, 1971.
Taggart, B. E. and Joyce, J.: Radiometrically dated marine terraces on northwestern Puerto Rico, in: Transactions of the 12th Caribbean Geological Conference, St. Croix, U.S. Virgin Islands, 7–11 August 1989, Miami Geological Society, South Miami, Florida, 248–258, 1991.
Taylor, D. W.: Fundamentals of Soil Mechanics, John Wiley & Sons, New York, 700 pp., 1948.
Thomas, M. A. and Cerovski-Darriau, C.: Infiltration data collected post-Hurricane María across landslide source area materials, Puerto Rico, USA, U.S. Geol. Surv. data release [data set], https://doi.org/10.5066/P9SCGVF7, 2019.
Tello, M.: Optimization of landslide susceptibility modeling: A Puerto Rico case study, Master of Science Thesis, Colorado School of Mines, Golden, Colorado, https://hdl.handle.net/11124/174137 (last access: 10 August 2023), 2020.
Terzaghi, K., Peck, R. B., and Mesri, G.: Soil Mechanics in Engineering Practice, 3rd edn., John Wiley & Sons: New York, 549 pp., ISBN 978-0-471-08658-1, 1996.
Tofani, V., Bicocchi, G., Rossi, G., Segoni, S., D'Ambrosio, M., Casagli, N., and Catani, F.: Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy), Landslides, 14, 755–770, https://doi.org/10.1007/s10346-017-0809-8, 2017.
U.S. Geological Survey: 2015–2016 USGS Puerto Rico LiDAR (project PR_PuertoRico_2015) [data set], https://apps.nationalmap.gov/lidar-explorer/#/ (last access: 10 August 2023), 2018.
U.S. Geological Survey: 2018 USGS Puerto Rico – Virgin Islands LiDAR (project PR_PRVI_A_2018), https://apps.nationalmap.gov/lidar-explorer/#/ (last access: 10 August 2023), 2020a.
U.S. Geological Survey: 2018 USGS Puerto Rico – Virgin Islands LiDAR (project PR_PRVI_D_2018), https://apps.nationalmap.gov/lidar-explorer/#/ (last access: 10 August 2023), 2020b.
U.S. Geological Survey: 2018 USGS Puerto Rico – Virgin Islands LiDAR (project PR_PRVI_H_2018), https://apps.nationalmap.gov/lidar-explorer/#/ (last access: 10 August 2023), 2020c.
von Ruette, J., Lehmann, P., and Or, D.: Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization, Water Resour. Res., 49, 6266–6285, https://doi.org/10.1002/wrcr.20418, 2013.
Wang, S., Zhang K., van Beek, L. P. H., Tian, X., and Bogaard, T. A.: Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment, Environ. Modell. Softw., 124, 104607, https://doi.org/10.1016/j.envsoft.2019.104607, 2020.
Woodard, J. B., Mirus, B. B., Wood, N. J., Allstadt, K. E., Leshchinsky, B. A., and Crawford, M. M.: Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling, Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, 2024.
Wu, W. and Sidle, R. C.: A distributed slope stability model for steep forested hillslopes, Water Resour. Res., 31, 2097–2110, https://doi.org/10.1029/95WR01136, 1995.
Xiao, T., Segoni, S., Liang, X., Yin, K., and Casagli, N.: Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County, Three Gorges Reservoir, Geosci. Front., 14, 101514, https://doi.org/10.1016/j.gsf.2022.101514, 2023.
Yan, Q., Wainwright, H., Dafflon, B., Uhlemann, S., Steefel, C. I., Falco, N., Kwang, J., and Hubbard, S. S.: A hybrid data–model approach to map soil thickness in mountain hillslopes, Earth Surf. Dynam., 9, 1347–1361, https://doi.org/10.5194/esurf-9-1347-2021, 2021.
Zieher, T., Rutzinger, M., Schneider-Muntau, B., Perzl, F., Leidinger, D., Formayer, H., and Geitner, C.: Sensitivity analysis and calibration of a dynamic physically based slope stability model, Nat. Hazards Earth Syst. Sci., 17, 971–992, https://doi.org/10.5194/nhess-17-971-2017, 2017.
Short summary
We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
We mapped potential for heavy rainfall to cause landslides in part of the central mountains of...
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