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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Lisa V. Luna, Jacob B. Woodard, Janice L. Bytheway, Gina M. Belair, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 25, 3279–3307, https://doi.org/10.5194/nhess-25-3279-2025, https://doi.org/10.5194/nhess-25-3279-2025, 2025
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Landslide frequency (how often landslides occur) is needed to assess landslide hazard and risk but has rarely been quantified at near-continental scales. Here, we used statistical models to estimate landslide frequency across the United States while addressing gaps in landslide reporting. Our results showed strong variations in landslide frequency that followed topography, earthquake probability, and ecological region and highlighted areas with potential for widespread landsliding.
Amalie Skålevåg, Lena Katharina Schmidt, Nele Eggers, Jana Tjeda Brettin, Oliver Korup, and Axel Bronstert
EGUsphere, https://doi.org/10.5194/egusphere-2025-3683, https://doi.org/10.5194/egusphere-2025-3683, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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As glaciers retreat in mountain regions, heavy rainstorms increasingly control how much soil and sediment rivers carry downstream. We analysed rainfall and sediment data over 21 years in the Austrian Alps and found short, intense storms becoming more important for sediment movement, although total annual sediment transport is declining as glaciers shrink. This shift may increase flood hazards, affecting ecosystems and water quality downstream.
Joshua J. Roering, Margaret Darrow, Annette Patton, and Aaron Jacobs
EGUsphere, https://doi.org/10.5194/egusphere-2025-4123, https://doi.org/10.5194/egusphere-2025-4123, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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A deadly landslide struck Wrangell Island, Alaska, in November 2023, traveling over a kilometer and claiming six lives. Our study shows it was likely triggered by moderate rainfall combined with rapid snowmelt and drainage from a ridgetop wetland, which saturated deep soil deposits. The landslide grew unusually large as it entrained abundant soil downslope. Findings highlight the role of storm patterns, geology, and hydrology in driving future landslide hazards in SE Alaska.
Maria Isabel Arango-Carmona, Paul Voit, Marcel Hürlimann, Edier Aristizábal, and Oliver Korup
EGUsphere, https://doi.org/10.5194/egusphere-2025-1698, https://doi.org/10.5194/egusphere-2025-1698, 2025
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We studied 22 cascading landslide and torrential events in tropical mountains to understand how rainfall, slopes, and soil types interact to trigger them. We found that extreme rainfall alone is not always the cause, but long wet periods and sediment type also play a role. Our findings can help improve warning systems and reduce disaster risks in vulnerable regions.
Ian D. Wachino, Joshua J. Roering, Reuben Cash, and Annette I. Patton
EGUsphere, https://doi.org/10.5194/egusphere-2025-1168, https://doi.org/10.5194/egusphere-2025-1168, 2025
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Rockfalls are a common hazard in steep mountain valleys, especially near Skagway, Alaska, where recent events have threatened public safety and infrastructure. This study identifies zones prone to rockfall by analyzing rock formations, past rockfall deposits, and computer models predicting how rocks travel downslope. Our findings highlight high-risk areas and provide insights to improve hazard mitigation, helping protect communities and tourism in the region.
Natalie Lützow, Bretwood Higman, Martin Truffer, Bodo Bookhagen, Friedrich Knuth, Oliver Korup, Katie E. Hughes, Marten Geertsema, John J. Clague, and Georg Veh
The Cryosphere, 19, 1085–1102, https://doi.org/10.5194/tc-19-1085-2025, https://doi.org/10.5194/tc-19-1085-2025, 2025
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As the atmosphere warms, thinning glacier dams impound smaller lakes at their margins. Yet, some lakes deviate from this trend and have instead grown over time, increasing the risk of glacier floods to downstream populations and infrastructure. In this article, we examine the mechanisms behind the growth of an ice-dammed lake in Alaska. We find that the growth in size and outburst volumes is more controlled by glacier front downwaste than by overall mass loss over the entire glacier surface.
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025, https://doi.org/10.5194/nhess-25-169-2025, 2025
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Early warning of increased landslide potential provides situational awareness to reduce landslide-related losses from major storm events. For decades, landslide forecasts relied on rainfall data alone, but recent research points to the value of hydrologic information for improving predictions. In this paper, we provide our perspectives on the value and limitations of integrating subsurface hillslope hydrologic monitoring data and mathematical modeling for more accurate landslide forecasts.
Oliver Korup, Lisa V. Luna, and Joaquin V. Ferrer
Nat. Hazards Earth Syst. Sci., 24, 3815–3832, https://doi.org/10.5194/nhess-24-3815-2024, https://doi.org/10.5194/nhess-24-3815-2024, 2024
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Catalogues of mapped landslides are useful for learning and forecasting how frequently they occur in relation to their size. Yet, rare and large landslides remain mostly uncertain in statistical summaries of these catalogues. We propose a single, consistent method of comparing across different data sources and find that landslide statistics disclose more about subjective mapping choices than trigger types or environmental settings.
Amalie Skålevåg, Oliver Korup, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 4771–4796, https://doi.org/10.5194/hess-28-4771-2024, https://doi.org/10.5194/hess-28-4771-2024, 2024
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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 the key characteristics separating event types, while hysteresis is less important. The four event types are attributed to compound rainfall–melt extremes, high snowmelt and glacier melt, freeze–thaw-modulated snow-melt and precipitation, and late-season glacier melt.
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.
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.
Z. Xiong, D. Stober, M. Krstić, O. Korup, M. I. Arango, H. Li, and M. Werner
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-5-W1-2023, 75–81, https://doi.org/10.5194/isprs-annals-X-5-W1-2023-75-2023, https://doi.org/10.5194/isprs-annals-X-5-W1-2023-75-2023, 2023
Melanie Fischer, Jana Brettin, Sigrid Roessner, Ariane Walz, Monique Fort, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 22, 3105–3123, https://doi.org/10.5194/nhess-22-3105-2022, https://doi.org/10.5194/nhess-22-3105-2022, 2022
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Nepal’s second-largest city has been rapidly growing since the 1970s, although its valley has been affected by rare, catastrophic floods in recent and historic times. We analyse potential impacts of such floods on urban areas and infrastructure by modelling 10 physically plausible flood scenarios along Pokhara’s main river. We find that hydraulic effects would largely affect a number of squatter settlements, which have expanded rapidly towards the river by a factor of up to 20 since 2008.
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.
Melanie Fischer, Oliver Korup, Georg Veh, and Ariane Walz
The Cryosphere, 15, 4145–4163, https://doi.org/10.5194/tc-15-4145-2021, https://doi.org/10.5194/tc-15-4145-2021, 2021
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Glacial lake outburst floods (GLOFs) in the greater Himalayan region threaten local communities and infrastructure. We assess this hazard objectively using fully data-driven models. We find that lake and catchment area, as well as regional glacier-mass balance, credibly raised the susceptibility of a glacial lake in our study area to produce a sudden outburst. However, our models hardly support the widely held notion that rapid lake growth increases GLOF susceptibility.
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.
Guilherme S. Mohor, Annegret H. Thieken, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 21, 1599–1614, https://doi.org/10.5194/nhess-21-1599-2021, https://doi.org/10.5194/nhess-21-1599-2021, 2021
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We explored differences in the damaging process across different flood types, regions within Germany, and six flood events through a numerical model in which the groups can learn from each other. Differences were found mostly across flood types, indicating the importance of identifying them, but there is great overlap across regions and flood events, indicating either that socioeconomic or temporal information was not well represented or that they are in fact less different within our cases.
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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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