Articles | Volume 23, issue 10
https://doi.org/10.5194/nhess-23-3261-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-23-3261-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Oct 2023
Research article |
| 18 Oct 2023
| 18 Oct 2023
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Annette I. Patton
CORRESPONDING AUTHOR
Sitka Sound Science Center, Sitka, Alaska, USA
Department of Earth Sciences, University of Oregon, Eugene, Oregon, USA
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Institute of Geosciences, University of Potsdam, Potsdam, Germany
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Joshua J. Roering
Department of Earth Sciences, University of Oregon, Eugene, Oregon, USA
Aaron Jacobs
NOAA National Weather Service Forecast Office Juneau, Juneau, Alaska, USA
Oliver Korup
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Institute of Geosciences, University of Potsdam, Potsdam, Germany
Benjamin B. Mirus
Geologic Hazards Science Center, US Geological Survey, Golden, Colorado, USA
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Greg Balco, Alan J. Hidy, William T. Struble, and Joshua J. Roering
Geochronology, 6, 71–76, https://doi.org/10.5194/gchron-6-71-2024, https://doi.org/10.5194/gchron-6-71-2024, 2024
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We describe a new method of reconstructing the long-term, pre-observational frequency and/or intensity of wildfires in forested landscapes using trace concentrations of the noble gases helium and neon that are formed in soil mineral grains by cosmic-ray bombardment of the Earth's surface.
Amalie Skålevåg, Oliver Korup, and Axel Bronstert
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-300, https://doi.org/10.5194/hess-2023-300, 2024
Revised manuscript under review for HESS
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We present a cluster-based approach for inferring sediment discharge event types from suspended sediment concentration and streamflow. Applying it to a glacierised catchment, we find event magnitude and shape complexity to be key characteristics separating event types, while hysteresis is less important. The four event types are attributed to compound rainfall-melt extremes, high snow- and glacier melt, freezethaw modulated snow-melt and precipitation, and late season glacier melt.
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.
Adam Emmer, Simon K. Allen, Mark Carey, Holger Frey, Christian Huggel, Oliver Korup, Martin Mergili, Ashim Sattar, Georg Veh, Thomas Y. Chen, Simon J. Cook, Mariana Correas-Gonzalez, Soumik Das, Alejandro Diaz Moreno, Fabian Drenkhan, Melanie Fischer, Walter W. Immerzeel, Eñaut Izagirre, Ramesh Chandra Joshi, Ioannis Kougkoulos, Riamsara Kuyakanon Knapp, Dongfeng Li, Ulfat Majeed, Stephanie Matti, Holly Moulton, Faezeh Nick, Valentine Piroton, Irfan Rashid, Masoom Reza, Anderson Ribeiro de Figueiredo, Christian Riveros, Finu Shrestha, Milan Shrestha, Jakob Steiner, Noah Walker-Crawford, Joanne L. Wood, and Jacob C. Yde
Nat. Hazards Earth Syst. Sci., 22, 3041–3061, https://doi.org/10.5194/nhess-22-3041-2022, https://doi.org/10.5194/nhess-22-3041-2022, 2022
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Glacial lake outburst floods (GLOFs) have attracted increased research attention recently. In this work, we review GLOF research papers published between 2017 and 2021 and complement the analysis with research community insights gained from the 2021 GLOF conference we organized. The transdisciplinary character of the conference together with broad geographical coverage allowed us to identify progress, trends and challenges in GLOF research and outline future research needs and directions.
William T. Struble and Joshua J. Roering
Earth Surf. Dynam., 9, 1279–1300, https://doi.org/10.5194/esurf-9-1279-2021, https://doi.org/10.5194/esurf-9-1279-2021, 2021
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We used a mathematical technique known as a wavelet transform to calculate the curvature of hilltops in western Oregon, which we used to estimate erosion rate. We find that this technique operates over 1000 times faster than other techniques and produces accurate erosion rates. We additionally built artificial hillslopes to test the accuracy of curvature measurement methods. We find that at fast erosion rates, curvature is underestimated, raising questions of measurement accuracy elsewhere.
David Jon Furbish, Joshua J. Roering, Tyler H. Doane, Danica L. Roth, Sarah G. W. Williams, and Angel M. Abbott
Earth Surf. Dynam., 9, 539–576, https://doi.org/10.5194/esurf-9-539-2021, https://doi.org/10.5194/esurf-9-539-2021, 2021
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Sediment particles skitter down steep hillslopes on Earth and Mars. Particles gain speed in going downhill but are slowed down and sometimes stop due to collisions with the rough surface. The likelihood of stopping depends on the energetics of speeding up (heating) versus slowing down (cooling). Statistical physics predicts that particle travel distances are described by a generalized Pareto distribution whose form varies with the Kirkby number – the ratio of heating to cooling.
David Jon Furbish, Sarah G. W. Williams, Danica L. Roth, Tyler H. Doane, and Joshua J. Roering
Earth Surf. Dynam., 9, 577–613, https://doi.org/10.5194/esurf-9-577-2021, https://doi.org/10.5194/esurf-9-577-2021, 2021
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The generalized Pareto distribution of particle travel distances on steep hillslopes, as described in a companion paper (Furbish et al., 2021a), is entirely consistent with measurements of travel distances obtained from laboratory and field-based experiments, supplemented with high-speed imaging and audio recordings that highlight the effects of bumpety-bump particle motions. Particle size and shape, in concert with surface roughness, strongly influence particle energetics and deposition.
Susan L. Brantley, David M. Eissenstat, Jill A. Marshall, Sarah E. Godsey, Zsuzsanna Balogh-Brunstad, Diana L. Karwan, Shirley A. Papuga, Joshua Roering, Todd E. Dawson, Jaivime Evaristo, Oliver Chadwick, Jeffrey J. McDonnell, and Kathleen C. Weathers
Biogeosciences, 14, 5115–5142, https://doi.org/10.5194/bg-14-5115-2017, https://doi.org/10.5194/bg-14-5115-2017, 2017
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This review represents the outcome from an invigorating workshop discussion that involved tree physiologists, geomorphologists, ecologists, geochemists, and hydrologists and developed nine hypotheses that could be tested. We argue these hypotheses point to the essence of issues we must explore if we are to understand how the natural system of the earth surface evolves, and how humans will affect its evolution. This paper will create discussion and interest both before and after publication.
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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
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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)
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Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
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We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
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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
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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.
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
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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
Akaike, H.: Information Theory and an Extension of the Maximum Likelihood Principle, in: Breakthroughs in Statistics: Foundations and Basic Theory, edited by: Kotz, S. and Johnson, N. L., Springer, New York, NY, 610–624, https://doi.org/10.1007/978-1-4612-0919-5_38, 1992
Ashok, S. P. and Pekkat, S.: A systematic quantitative review on the performance of some of the recent short-term rainfall forecasting techniques, J. Water Clim. Change, 13, 3004–3029, https://doi.org/10.2166/wcc.2022.302, 2022.
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.
BeVille, S. H., Mirus, B. B., Ebel, B. A., Mader, G. G., and Loague, K.: Using simulated hydrologic response to revisit the 1973 Lerida Court landslide, Environ. Earth Sci., 61, 1249–1257, https://doi.org/10.1007/s12665-010-0448-z, 2010.
Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, 2018.
Booth, A. M., Sifford, C., Vascik, B., Siebert, C., and Buma, B.: Large wood inhibits debris flow runout in forested southeast Alaska, Earth Surface Processes and Landforms, 45, 1555–1568, https://doi.org/10.1002/esp.4830, 2020.
Bozzolan, E., Holcombe, E., Pianosi, F., and Wagener, T.: Including informal housing in slope stability analysis – an application to a data-scarce location in the humid tropics, Nat. Hazards Earth Syst. Sci., 20, 3161–3177, https://doi.org/10.5194/nhess-20-3161-2020, 2020.
Brier, G. W.: Monthly weather review, Mon. Weather Rev., 78, 1–3, 1950.
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.
Bürkner, P.-C.: brms: An R Package for Bayesian Multilevel Models Using Stan, J. Stat. Softw., 80, 1–28, https://doi.org/10.18637/jss.v080.i01, 2017.
Busch, L., O'Connell, V., Prussian, K., Foss, J., Landwehr, D. J., Hoffman, J., Becker, M., Gould, A., Wolken, G., Stevens, D. A., Whorton, E., Jacobs, A., Curtis, J., Holloway, E., Fielding, E., Buma, B., and Carter, B.: August 2015 Sitka Landslides, Sitka Geotask Force Summaries, 1, 1–32, 2016.
Busch, L., Lempert, R., Izenberg, M., and Patton, A.: Run Uphill for a Tsunami, Downhill for a Landslide, Issues Sci. Technol., 38, 40–46, 2021.
Chae, B.-G., Park, J.-J., Catani, F., Simoni, A., and Berti, M.: Landslide prediction, monitoring and early warning: a concise review of state-of-the-art, Geosci. J., 21, 1033–1070, 2017.
Chleborad, B. A. F., Baum, R. L., Godt, J. W., and Report, U. S. G. S. O.: Rainfall Thresholds for Forecasting Landslides in the Seattle, Washington, Area – Exceedance and Probability: USGS Open-File Report 2006-1064, 1–31, https://doi.org/10.3133/ofr20061064, 2006.
Chu, M., Patton, A., Roering, J., Siebert, C., Selker, J., Walter, C., and Udell, C.: SitkaNet: A low-cost, distributed sensor network for landslide monitoring and study, HardwareX, 9, e00191, https://doi.org/10.1016/j.ohx.2021.e00191, 2021.
Collins, B. D., Oakley, N. S., Perkins, J. P., East, A. E., Corbett, S. C., and Hatchett, B. J.: Linking Mesoscale Meteorology With Extreme Landscape Response: Effects of Narrow Cold Frontal Rainbands (NCFR), J. Geophys. Res.-Earth, 125, e2020JF005675, https://doi.org/10.1029/2020JF005675, 2020.
Cordeira, J. M., Stock, J., Dettinger, M. D., Young, A. M., Kalansky, J. F., and Ralph, F. M.: A 142-year climatology of northern California landslides and atmospheric rivers, B. Am. Meteorol. Soc., 100, 1499–1509, https://doi.org/10.1175/BAMS-D-18-0158.1, 2019.
Cutter, S. L. and Finch, C.: Temporal and spatial changes in social vulnerability to natural hazards, P. Natl. Acad. Sci. USA, 105, 2301–2306, https://doi.org/10.1073/pnas.0710375105, 2008.
Darrow, M. M., Nelson, V. A., Grilliot, M., Wartman, J., Jacobs, A., Baichtal, J. F., and Buxton, C.: Geomorphology and initiation mechanisms of the 2020 Haines, Alaska landslide, Landslides, 19, 2177–2188, https://doi.org/10.1007/s10346-022-01899-3, 2022.
Diamond, H. J., Karl, T. R., Palecki, M. A., Baker, C. B., Bell, J. E., Leeper, R. D., Easterling, D. R., Lawrimore, J. H., Meyers, T. P., Helfert, M. R., Goodge, G., and Thorne, P. W.: U.S. Climate Reference Network after One Decade of Operations: Status and Assessment, B. Am. Meteorol. Soc., 94, 485–498, https://doi.org/10.1175/BAMS-D-12-00170.1, 2013.
Elliott, J. and Freymueller, J. T.: A Block Model of Present-Day Kinematics of Alaska and Western Canada, J. Geophys. Res.-Sol. Ea., 125, 1–30, https://doi.org/10.1029/2019JB018378, 2020.
Fabry, F. and Seed, A. W.: Quantifying and predicting the accuracy of radar-based quantitative precipitation forecasts, Adv. Water Resour., 32, 1043–1049, https://doi.org/10.1016/j.advwatres.2008.10.001, 2009.
Gariano, S. L., Melillo, M., Peruccacci, S., and Brunetti, M. T.: How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering?, Nat. Hazards, 100, 655–670, https://doi.org/10.1007/s11069-019-03830-x, 2020.
Gelman, A., Jakulin, A., Grazia Pittau, M., and Su, Y.-S.: A weakly informative default prior distribution for logistic and other regression models, Ann. Appl. Stat., 2, 1360–1383, https://doi.org/10.1214/08-AOAS191, 2008.
Giannecchini, R., Galanti, Y., Amato, G. D., and Barsanti, M.: Geomorphology Probabilistic rainfall thresholds for triggering debris flows in a human-modified landscape, Geomorphology, 257, 94–107, https://doi.org/10.1016/j.geomorph.2015.12.012, 2016.
Guzzetti, F.: Invited perspectives: Landslide populations – can they be predicted?, Nat. Hazards Earth Syst. Sci., 21, 1467–1471, https://doi.org/10.5194/nhess-21-1467-2021, 2021.
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.
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., Marchesini, I., Rossi, M., and Melillo, M.: Geographical landslide early warning systems, Earth-Sci. Rev., 200, 102973, https://doi.org/10.1016/j.earscirev.2019.102973, 2020.
Hamilton, T. D.: Correlation of quaternary glacial deposits in Alaska, Quaternary Sci. Rev., 5, 171–180, 1986.
Hennon, A., Paul, E., Amore, D., David, V., Dustin, T., and Melinda, B.: Influence of Forest Canopy and Snow on Microclimate in a Declining Yellow-Cedar Forest of Southeast Alaska, Northwest Sci., 84, 73–87, https://doi.org/10.3955/046.084.0108, 2010.
Izenberg, M., Brown, R., Siebert, C., Heinz, R., Rahmattalabi, A., and Vayanos, P.: A Community-Partnered Approach to Social Network Data Collection for a Large and Partial Network, Field Method., 35, 1–7, https://doi.org/10.1177/1525822X221074769, 2022.
Jacobs, A., Holloway, E., and Dixon, A.: Atmospheric Rivers in Alaska – Yes they do exist, and are usually tied to the biggest and most damaging rain-generated floods in Alaska, International Atmospheric Rivers Conference, La Jolla, CA, USA, 8–11 August 2016, http://cw3e.ucsd.edu/ARconf2016/Posters/Jacobs_IARC2016.pdf (last access: 11 October 2023), 2016.
Jakob, M., Holm, K., Lange, O., and Schwab, J. W.: Hydrometeorological thresholds for landslide initiation and forest operation shutdowns on the north coast of British Columbia, Landslides, 3, 228–238, https://doi.org/10.1007/s10346-006-0044-1, 2006.
Jakob, M., Owen, T., and Simpson, T.: A regional real-time debris-flow warning system for the District of North Vancouver, Canada, Landslides, 9, 165–178, https://doi.org/10.1007/s10346-011-0282-8, 2012.
Johnson, A. C., Swanston, D. N., and Mcgee, K. E.: Landslide Initiation, Runout, and Deposition within Clearcuts and Old-Growth Forests of Alaska, J. Am. Water Resour. As., 36, 17–30, 2000.
Johnson, G. L. and Hanson, C. L.: Topographic and Atmospheric Influences on Precipitation Variability over a Mountainous Watershed, J. Appl. Meteorol., 34, 68–87, 1994.
Johnston, E. C., Davenport, F. V., Wang, L., Caers, J. K., Muthukrishnan, S., Burke, M., and Diffenbaugh, N. S.: Quantifying the Effect of Precipitation on Landslide Hazard in Urbanized and Non-Urbanized Areas, Geophys. Res. Lett., 48, e2021GL094038, https://doi.org/10.1029/2021GL094038, 2021.
Khan, S., Kirschbaum, D. B., and Stanley, T.: Investigating the potential of a global precipitation forecast to inform landslide prediction, Weather Clim. Extrem., 33, 100364, https://doi.org/10.1016/j.wace.2021.100364, 2021.
King, G. and Zeng, L.: Explaining Rare Events in International Relations, Int. Organ., 55, 693–715, 2003.
Kirschbaum, D. and Stanley, T.: Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness, Earth's Future, 6, 505–523, https://doi.org/10.1002/2017EF000715, 2018.
Kristensen, L., Czekirda, J., Penna, I., Etzelmüller, B., Nicolet, P., Pullarello, J. S., Blikra, L. H., Skrede, I., Oldani, S., and Abellan, A.: Movements, failure and climatic control of the Veslemannen rockslide, Western Norway, Landslides, 1963–1980, https://doi.org/10.1007/s10346-020-01609-x, 2021.
Kuha, J.: AIC and BIC: Comparisons of assumptions and performance, Sociol. Method. Res., 33, 188–229, https://doi.org/10.1177/0049124103262065, 2004.
Lee, S., Won, J. S., Jeon, S. W., Park, I., and Lee, M. J.: Spatial Landslide Hazard Prediction Using Rainfall Probability and a Logistic Regression Model, Math. Geosci., 47, 565–589, https://doi.org/10.1007/s11004-014-9560-z, 2015.
Leonarduzzi, E., Molnar, P., and McArdell, B.: Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data, J. Am. Water Resour. As., 5, 6612–6625, https://doi.org/10.1111/j.1752-1688.1969.tb04897.x, 2017.
Lesnek, A. J., Briner, J. P., Lindqvist, C., Baichtal, J. F., and Heaton, T. H.: Deglaciation of the Pacific coastal corridor directly preceded the human colonization of the Americas, Science Advances, 4, eaar5040, https://doi.org/10.1126/sciadv.aar5040, 2018.
Mann, D. H.: Wisconsin and Holocene Glaciation of Southeast Alaska, Glaciat. Alaska Geol. Rec., 64, 237–265, https://doi.org/10.4018/978-1-60566-198-8.ch103, 1986.
Marino, P., Peres, D. J., Cancelliere, A., Greco, R., and Bogaard, T. A.: Soil moisture information can improve shallow landslide forecasting using the hydrometeorological threshold approach, Landslides, 17, 2041–2054, https://doi.org/10.1007/s10346-020-01420-8, 2020.
McCullagh, P. and Nelder, J. A.: Generalized Linear Models, 2nd ed., Chapman and Hall, London New York, 532 pp., https://doi.org/10.2307/2347392, 1989.
McElreath, R.: Statistical Rethinking: A Bayesian Course with Exampels in R and STAN, Second Edn., Chapman and Hall/CRC, ISBN 978-0-367-13991-9, 2020.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., Roccati, A., and Guzzetti, F.: A tool for the automatic calculation of rainfall thresholds for landslide occurrence, Environ. Modell. Softw., 105, 230–243, https://doi.org/10.1016/j.envsoft.2018.03.024, 2018.
University of Utah, Department of Atmospheric Sciences: MesoWest, https://mesowest.utah.edu, last access: 12 October 2023.
Miller, D.: Modeling Susceptibility to Landslides and Debris Flows in Southeast Alaska, https://terrainworks.sharefile.com/share/view/s8532031dfcf44ab0a87bc8a83b2b3b1c (last access: 12 October 2023), 2019.
Mirus, B. B., Morphew, M. D., and Smith, J. B.: Developing Hydro-Meteorological Thresholds for Shallow Landslide Initiation and Early Warning, Water, 10, 1–19, https://doi.org/10.3390/w10091274, 2018a.
Mirus, B. B., Becker, R. E., Baum, R. L., and Smith, J. B.: Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning, Landslides, 15, 1909–1919, https://doi.org/10.1007/s10346-018-0995-z, 2018b.
Napoli, A., Crespi, A., Ragone, F., Maugeri, M., and Pasquero, C.: Variability of orographic enhancement of precipitation in the Alpine region, Sci. Rep., 9, 1–8, https://doi.org/10.1038/s41598-019-49974-5, 2019.
Patton, A. and Luna, L.: pattonai/sitka-lews: sitka-lews repository for manuscript submission 20210105, Zenodo [data set] and [code], https://doi.org/10.5281/zenodo.7508537, 2023.
Oakley, N. S., Lancaster, J. T., Kaplan, M. L., and Ralph, F. M.: Synoptic conditions associated with cool season post-fire debris flows in the Transverse Ranges of southern California, Nat. Hazards, 88, 327–354, https://doi.org/10.1007/s11069-017-2867-6, 2017.
Osanai, N., Shimizu, T., Kuramoto, K., Kojima, S., and Noro, T.: Japanese early-warning for debris flows and slope failures using rainfall indices with Radial Basis Function Network, Landslides, 7, 325–338, https://doi.org/10.1007/s10346-010-0229-5, 2010.
Patton, A. I., Roering, J. J., and Orland, E.: Debris flow initiation in postglacial terrain: Insights from shallow landslide initiation models and geomorphic mapping in Southeast Alaska, Earth Surf. Proc. Landf., 47, 1583–1598, https://doi.org/10.1002/esp.5336, 2022.
Peres, D. J. and Cancelliere, A.: Comparing methods for determining landslide early warning thresholds: potential use of non-triggering rainfall for locations with scarce landslide data availability, Landslides, 18, 3135–3147, https://doi.org/10.1007/s10346-021-01704-7, 2021.
Perica, S., Kane, D., Dietz, S., Maitaria, K., Martin, D., Pavlovic, S., Roy, I., Stuefer, S., Tidwell, A., Trypaluk, C., Unruh, D., Yekta, M., Betts, E., Bonnin, G., Heim, S., Hiner, L., Lilly, E., Narayanan, J., Yan, F., and Zhao, T.: NOAA Atlas 14 Precipitation-Frequency Atlas of the United States, US Department of Commerce, National Oceanic and Atmospheric Administraion, National Weather Service, and University of Fairbanks, Silver Spring, Maryland, v7-2.0, https://www.weather.gov/media/owp/oh/hdsc/docs/Atlas14_Volume7.pdf (last access: 13 October 2023), 2012.
Peruccacci, S., Brunetti, M. T., Gariano, S. L., Melillo, M., Rossi, M., and Guzzetti, F.: Rainfall thresholds for possible landslide occurrence in Italy, Geomorphology, 290, 39–57, https://doi.org/10.1016/j.geomorph.2017.03.031, 2017.
Piciullo, L., Gariano, S. L., Melillo, M., Brunetti, M. T., Peruccacci, S., Guzzetti, F., and Calvello, M.: Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides, Landslides, 14, 995–1008, https://doi.org/10.1007/s10346-016-0750-2, 2017.
Piciullo, L., Calvello, M., and Cepeda, J. M.: Territorial early warning systems for rainfall-induced landslides, Earth-Sci. Rev., 179, 228–247, https://doi.org/10.1016/j.earscirev.2018.02.013, 2018.
R Core Team: R: A languge and environment for statistical computing, https://www.r-project.org/ (last access: 10 October 2023), 2019.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., and Guzzetti, F.: A review of statistically-based landslide susceptibility models, Earth-Sci. Rev., 180, 60–91, https://doi.org/10.1016/j.earscirev.2018.03.001, 2018.
Riehle, J. R., Champion, D. E., Brew, D. A., and Lanphere, M. A.: Pyroclastic deposits of the Mount Edgecumbe volcanic field, southeast Alaska: eruptions of a stratified magma chamber, J. Volcanol. Geoth. Res., 53, 117–143, https://doi.org/10.1016/0377-0273(92)90078-R, 1992a.
Riehle, J. R., Mann, D. H., Peteet, D. M., Engstrom, D. R., Brew, D. A., and Meyer, C. E.: The Mount Edgecumbe tephra deposits, a marker horizon in southeastern Alaska near the Pleistocene-Holocene boundary, Quaternary Res., 37, 183–202, https://doi.org/10.1016/0033-5894(92)90081-S, 1992b.
Roth, A., Hock, R., Schuler, T. V., Bieniek, P. A., Pelto, M., and Aschwanden, A.: Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation, Front. Earth Sci., 6, 1–19, https://doi.org/10.3389/feart.2018.00020, 2018.
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.
Saito, T. and Rehmsmeier, M.: The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets, PLOS ONE, 10, e0118432, https://doi.org/10.1371/journal.pone.0118432, 2015.
Sandberg, E.: A History of Alaska Population Settlement, Alaska Dep. Labor Work. Dev., 19, https://live.laborstats.alaska.gov/pop/estimates/pub/pophistory.pdf (last accessed: 10 October 2023), 2013.
Scheevel, C. R., Baum, R. L., Mirus, B. B., and Smith, J. B.: Precipitation thresholds for landslide occurrence near Seattle, Mukilteo, and Everett, Washington: U.S. Geological Survey Open-File Report 2017–1039, USGS Open-File Rep. 2017-1039, 51, https://doi.org/10.3133/ofr20171039, 2017.
Schwarz, G.: Estimating the Dimenson of a Model, Ann. Stat., 6, 461–464, 1978.
Segoni, S., Piciullo, L., and Gariano, S. L.: A review of the recent literature on rainfall thresholds for landslide occurrence, Landslides, 15, 1483–1501, https://doi.org/10.1007/s10346-018-0966-4, 2018.
Shanley, C. S., Pyare, S., Goldstein, M. I., Alaback, P. B., Albert, D. M., Beier, C. M., Brinkman, T. J., Edwards, R. T., Hood, E., MacKinnon, A., McPhee, M. V., Patterson, T. M., Suring, L. H., Tallmon, D. A., and Wipfli, M. S.: Climate change implications in the northern coastal temperate rainforest of North America, Climatic Change, 130, 155–170, https://doi.org/10.1007/s10584-015-1355-9, 2015.
Sharma, A. R. and Déry, S. J.: Variability and trends of landfalling atmospheric rivers along the Pacific Coast of northwestern North America, Int. J. Climatol., 40, 544–558, https://doi.org/10.1002/joc.6227, 2019.
Sharma, A. R. and Déry, S. J.: Contribution of atmospheric rivers to annual, seasonal, and extreme precipitation across British Columbia and southeastern Alaska, J. Geophys. Res.-Atmos., 125, e2019JD031823, https://doi.org/10.1029/2019jd031823, 2020.
Sidle, R. C.: Shallow groundwater fluctuations in unstable hillslopes of coastal Alaska, Zeitschrift für Gletscherkd. und Glazialgeol., 20, 79–95, 1984.
Sidle, R. C. and Swanston, D. N.: Analysis of a small debris slide in coastal Alaska, Can. Geotech. J., 19, 167–174, https://doi.org/10.1139/t82-018, 1981.
Staley, D. M., Negri, J. A., Kean, J. W., Laber, J. L., Tillery, A. C., and Youberg, A. M.: Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States, Geomorphology, 278, 149–162, https://doi.org/10.1016/j.geomorph.2016.10.019, 2017.
Stan Development Team: Stan User's Guide 2.28, 1–9, https://www.mc-stan.org (last access: 10 February 2022), 2022.
Stanley, T. and Kirschbaum, D. B.: A heuristic approach to global landslide susceptibility mapping, Nat. Hazards, 87, 145–164, https://doi.org/10.1007/s11069-017-2757-y, 2017.
Swanston, D. N.: Mechanics of Debris Avalanching in Shallow Till Soils of Southeast Alaska, USDA Forest Service Research Paper PNW-103, Juneau, Alaska, https://doi.org/10.5962/bhl.title.87969, 1970.
Swanston, D. N. and Marion, D. A.: Landslide response to timber harvest in Southeast Alaska, in: Proceedings of the 5th Fed. Interag. Sediment. Conf., Las Vegas, NV, USA, 18–21 March 1991, 10, 49–56, https://pubs.usgs.gov/misc/FISC_1947-2006/pdf/1st-7thFISCs-CD/5thFISC/5Fisc-V2/5Fsc2-10.PDF (last access: 11 October 2023), 1991.
Synoptic: PASI Station Data Download, Synoptic [data set], https://download.synopticdata.com/#a/PASI, 2023.
Thomas, M. A., Mirus, B. B., Collins, B. D., Lu, N., and Godt, J. W.: Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria, Landslides, 15, 1265–1277, https://doi.org/10.1007/s10346-018-0950-z, 2018.
Tufano, R., Cesarano, M., Fusco, F., and Vita, P. De: Probabilistic approaches for assessing rainfall thresholds triggering shallow landslides. The study case of the peri-vesuvian area (Southern Italy), Ital. J. Eng. Geol. Environ., 2019, 105–110, https://doi.org/10.4408/IJEGE.2019-01.S-17, 2019.
Tullos, D., Byron, E., Galloway, G., Obeysekera, J., Prakash, O., and Sun, Y. H.: Review of challenges of and practices for sustainable management of mountain flood hazards, Nat. Hazards, 83, 1763–1797, https://doi.org/10.1007/s11069-016-2400-3, 2016.
US Census Bureau: QuickFacts for the Sitka city and borough, Alaska, https://www.census.gov/quickfacts/sitkacityandboroughalaska (last access: 12 October 2023), 2022.
US Forest Service: Tongass National Forest Landslide Areas, State of Alaska Open Data Portal, https://gis.data.alaska.gov/datasets/usfs::tongass-national-forest-landslide-areas/about (last access: 12 October 2023), 2019.
Vascik, B. A., Booth, A. M., Buma, B., and Berti, M.: Estimated Amounts and Rates of Carbon Mobilized by Landsliding in Old-Growth Temperate Forests of SE Alaska, J. Geophys. Res.-Biogeo., 126, 1–21, https://doi.org/10.1029/2021JG006321, 2021.
Vehtari, A., Gelman, A., and Gabry, J.: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC, Stat. Comput., 27, 1413–1432, https://doi.org/10.1007/s11222-016-9696-4, 2017.
Wendler, G., Galloway, K., and Stuefer, M.: On the climate and climate change of Sitka, Southeast Alaska, Theor. Appl. Climatol., 126, 27–34, https://doi.org/10.1007/s00704-015-1542-7, 2016.
White, C., Gehrels, G. E., Pecha, M., Giesler, D., Yokelson, I., McClelland, W. C., and Butler, R. F.: U-Pb and Hf isotope analysis of detrital zircons from Paleozoic strata of the southern Alexander terrane (Southeast Alaska), Lithosphere, 8, 83–96, https://doi.org/10.1130/L475.1, 2016.
Wicki, A., Lehmann, P., Hauck, C., Seneviratne, S. I., Waldner, P., and Stähli, M.: Assessing the potential of soil moisture measurements for regional landslide early warning, Landslides, 17, 1881–1896, https://doi.org/10.1007/s10346-020-01400-y, 2020.
Wilks, D. S.: Forecast Verification, Int. Geophys., 100, 301–394, https://doi.org/10.1016/B978-0-12-385022-5.00008-7, 2011.
Short summary
Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Landslide warning systems often use statistical models to predict landslides based on rainfall....
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