Articles | Volume 20, issue 11
https://doi.org/10.5194/nhess-20-2905-2020
© Author(s) 2020. 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-20-2905-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Nov 2020
Research article |
| 03 Nov 2020
| 03 Nov 2020
Deriving rainfall thresholds for landsliding at the regional scale: daily and hourly resolutions, normalisation, and antecedent rainfall
Elena Leonarduzzi
CORRESPONDING AUTHOR
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
Peter Molnar
Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
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Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-345, https://doi.org/10.5194/hess-2022-345, 2022
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As the stress on water resources from climate change grows, we need models that represent water processes at the scale of counties, states, and even countries in order to make viable predictions about things will change. While such models are powerful, they can be cumbersome to deal with because they are so large. This research explores a novel way of increasing the efficiency of large-scale hydrologic models using an approach called Simulation-Based Inference.
Elena Leonarduzzi, Brian W. McArdell, and Peter Molnar
Hydrol. Earth Syst. Sci., 25, 5937–5950, https://doi.org/10.5194/hess-25-5937-2021, https://doi.org/10.5194/hess-25-5937-2021, 2021
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Landslides are a dangerous natural hazard affecting alpine regions, calling for effective warning systems. Here we consider different approaches for the prediction of rainfall-induced shallow landslides at the regional scale, based on open-access datasets and operational hydrological forecasting systems. We find antecedent wetness useful to improve upon the classical rainfall thresholds and the resolution of the hydrological model used for its estimate to be a critical aspect.
Jacob Hirschberg, Alexandre Badoux, Brian W. McArdell, Elena Leonarduzzi, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 21, 2773–2789, https://doi.org/10.5194/nhess-21-2773-2021, https://doi.org/10.5194/nhess-21-2773-2021, 2021
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Debris-flow prediction is often based on rainfall thresholds, but uncertainty assessments are rare. We established rainfall thresholds using two approaches and find that 25 debris flows are needed for uncertainties to converge in an Alpine basin and that the suitable method differs for regional compared to local thresholds. Finally, we demonstrate the potential of a statistical learning algorithm to improve threshold performance. These findings are helpful for early warning system development.
Amber van Hamel, Peter Molnar, Joren Janzing, and Manuela Irene Brunner
Hydrol. Earth Syst. Sci., 29, 2975–2995, https://doi.org/10.5194/hess-29-2975-2025, https://doi.org/10.5194/hess-29-2975-2025, 2025
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Suspended sediment is a natural component of rivers, but extreme suspended sediment concentrations (SSCs) can have negative impacts on water use and aquatic ecosystems. We identify the main factors influencing the spatial and temporal variability of annual SSC regimes and extreme SSC events. Our analysis shows that different processes are more important for annual SSC regimes than for extreme events and that compound events driven by glacial melt and high-intensity rainfall led to the highest SSCs.
Mosisa Tujuba Wakjira, Nadav Peleg, Johan Six, and Peter Molnar
Hydrol. Earth Syst. Sci., 29, 863–886, https://doi.org/10.5194/hess-29-863-2025, https://doi.org/10.5194/hess-29-863-2025, 2025
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In this study, we implement a climate, water, and crop interaction model to evaluate current conditions and project future changes in rainwater availability and its yield potential, with the goal of informing adaptation policies and strategies in Ethiopia. Although climate change is likely to increase rainfall in Ethiopia, our findings suggest that water-scarce croplands in Ethiopia are expected to face reduced crop yields during the main growing season due to increases in temperature.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jessica Droujko, Srividya Hariharan Sudha, Gabriel Singer, and Peter Molnar
Earth Surf. Dynam., 11, 881–897, https://doi.org/10.5194/esurf-11-881-2023, https://doi.org/10.5194/esurf-11-881-2023, 2023
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We combined data from satellite images with data measured from a kayak in order to understand the propagation of fine sediment in the Vjosa River. We were able to find some storm-activated and some permanent sources of sediment. We also estimated how much fine sediment is carried into the Adriatic Sea by the Vjosa River: approximately 2.5 Mt per year, which matches previous findings. With our work, we hope to show the potential of open-access satellite images.
Tobias Siegfried, Aziz Ul Haq Mujahid, Beatrice Sabine Marti, Peter Molnar, Dirk Nikolaus Karger, and Andrey Yakovlev
EGUsphere, https://doi.org/10.5194/egusphere-2023-520, https://doi.org/10.5194/egusphere-2023-520, 2023
Preprint archived
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Our study investigates climate change impacts on water resources in Central Asia's high-mountain regions. Using new data and a stochastic soil moisture model, we found increased precipitation and higher temperatures in the future, leading to higher water discharge despite decreasing glacier melt contributions. These findings are crucial for understanding and preparing for climate change effects on Central Asia's water resources, with further research needed on extreme weather event impacts.
Qinggang Gao, Christian Zeman, Jesus Vergara-Temprado, Daniela C. A. Lima, Peter Molnar, and Christoph Schär
Weather Clim. Dynam., 4, 189–211, https://doi.org/10.5194/wcd-4-189-2023, https://doi.org/10.5194/wcd-4-189-2023, 2023
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We developed a vortex identification algorithm for realistic atmospheric simulations. The algorithm enabled us to obtain a climatology of vortex shedding from Madeira Island for a 10-year simulation period. This first objective climatological analysis of vortex streets shows consistency with observed atmospheric conditions. The analysis shows a pronounced annual cycle with an increasing vortex shedding rate from April to August and a sudden decrease in September.
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.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-345, https://doi.org/10.5194/hess-2022-345, 2022
Publication in HESS not foreseen
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As the stress on water resources from climate change grows, we need models that represent water processes at the scale of counties, states, and even countries in order to make viable predictions about things will change. While such models are powerful, they can be cumbersome to deal with because they are so large. This research explores a novel way of increasing the efficiency of large-scale hydrologic models using an approach called Simulation-Based Inference.
Silvan Ragettli, Tabea Donauer, Peter Molnar, Ron Delnoije, and Tobias Siegfried
Earth Surf. Dynam., 10, 797–815, https://doi.org/10.5194/esurf-10-797-2022, https://doi.org/10.5194/esurf-10-797-2022, 2022
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This paper presents a novel methodology to identify and quantitatively analyze deposition and erosion patterns in ephemeral ponds or in perennial lakes with strong water level fluctuations. We apply this method to unravel the water and sediment balance of Lac Wégnia, a designated Ramsar site in Mali. The study can be a showcase for monitoring Sahelian lakes using remote sensing data, as it sheds light on the actual drivers of change in Sahelian lakes.
Elena Leonarduzzi, Brian W. McArdell, and Peter Molnar
Hydrol. Earth Syst. Sci., 25, 5937–5950, https://doi.org/10.5194/hess-25-5937-2021, https://doi.org/10.5194/hess-25-5937-2021, 2021
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Landslides are a dangerous natural hazard affecting alpine regions, calling for effective warning systems. Here we consider different approaches for the prediction of rainfall-induced shallow landslides at the regional scale, based on open-access datasets and operational hydrological forecasting systems. We find antecedent wetness useful to improve upon the classical rainfall thresholds and the resolution of the hydrological model used for its estimate to be a critical aspect.
Jacob Hirschberg, Alexandre Badoux, Brian W. McArdell, Elena Leonarduzzi, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 21, 2773–2789, https://doi.org/10.5194/nhess-21-2773-2021, https://doi.org/10.5194/nhess-21-2773-2021, 2021
Short summary
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Debris-flow prediction is often based on rainfall thresholds, but uncertainty assessments are rare. We established rainfall thresholds using two approaches and find that 25 debris flows are needed for uncertainties to converge in an Alpine basin and that the suitable method differs for regional compared to local thresholds. Finally, we demonstrate the potential of a statistical learning algorithm to improve threshold performance. These findings are helpful for early warning system development.
Marius G. Floriancic, Wouter R. Berghuijs, Tobias Jonas, James W. Kirchner, and Peter Molnar
Hydrol. Earth Syst. Sci., 24, 5423–5438, https://doi.org/10.5194/hess-24-5423-2020, https://doi.org/10.5194/hess-24-5423-2020, 2020
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Low river flows affect societies and ecosystems. Here we study how precipitation and potential evapotranspiration shape low flows across a network of 380 Swiss catchments. Low flows in these rivers typically result from below-average precipitation and above-average potential evapotranspiration. Extreme low flows result from long periods of the combined effects of both drivers.
Giulia Battista, Peter Molnar, and Paolo Burlando
Earth Surf. Dynam., 8, 619–635, https://doi.org/10.5194/esurf-8-619-2020, https://doi.org/10.5194/esurf-8-619-2020, 2020
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Suspended sediment load in rivers is highly uncertain because of spatial and temporal variability. By means of a hydrology and suspended sediment transport model, we investigated the effect of spatial variability in precipitation and surface erodibility on catchment sediment fluxes in a mesoscale river basin.
We found that sediment load depends on the spatial variability in erosion drivers, as this affects erosion rates and the location and connectivity to the channel of the erosion areas.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
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Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Anna Costa, Daniela Anghileri, and Peter Molnar
Hydrol. Earth Syst. Sci., 22, 3421–3434, https://doi.org/10.5194/hess-22-3421-2018, https://doi.org/10.5194/hess-22-3421-2018, 2018
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We analyse the control of hydroclimatic factors – erosive rainfall, ice melt, and snowmelt – on suspended sediment concentration (SSC) of Alpine catchments regulated by hydropower, and we develop a multivariate hydroclimatic–informed rating curve. We show that while erosive rainfall determines the variability of SSC, ice melt generates the highest contribution to SSC per unit of runoff. This approach allows the exploration of climate–driven changes in fine sediment dynamics in Alpine catchments.
Anna Costa, Peter Molnar, Laura Stutenbecker, Maarten Bakker, Tiago A. Silva, Fritz Schlunegger, Stuart N. Lane, Jean-Luc Loizeau, and Stéphanie Girardclos
Hydrol. Earth Syst. Sci., 22, 509–528, https://doi.org/10.5194/hess-22-509-2018, https://doi.org/10.5194/hess-22-509-2018, 2018
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We explore the signal of a warmer climate in the suspended-sediment dynamics of a regulated and human-impacted Alpine catchment. We demonstrate that temperature-driven enhanced melting of glaciers, which occurred in the mid-1980s, played a dominant role in suspended sediment concentration rise, through increased runoff from sediment-rich proglacial areas, increased contribution of sediment-rich meltwater, and increased sediment supply in proglacial areas due to glacier recession.
Anna Costa, Daniela Anghileri, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-419, https://doi.org/10.5194/hess-2017-419, 2017
Manuscript not accepted for further review
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We develop a novel rating curve to simulate suspended sediment concentration (SSC) in Alpine catchments (Process-Based Rating Curve, PBRC). Instead of relating SSC to discharge, as in traditional approaches, we model SSC by differentiating the potential contributions of the main erosional and transport processes of Alpine environments: erosive rainfall, snowmelt, and icemelt. We show that PBRC significantly improves predictions of SSC, especially when analysing climate-induced changes.
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
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We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
Søren Thorndahl, Thomas Einfalt, Patrick Willems, Jesper Ellerbæk Nielsen, Marie-Claire ten Veldhuis, Karsten Arnbjerg-Nielsen, Michael R. Rasmussen, and Peter Molnar
Hydrol. Earth Syst. Sci., 21, 1359–1380, https://doi.org/10.5194/hess-21-1359-2017, https://doi.org/10.5194/hess-21-1359-2017, 2017
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This paper reviews how weather radar data can be used in urban hydrological applications. It focuses on three areas of research: (1) temporal and spatial resolution of rainfall data, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Moreover, the paper provides examples of urban hydrological applications which can benefit from radar rainfall data in comparison to tradition rain gauge measurements of rainfall.
Claudio I. Meier, Jorge Sebastián Moraga, Geri Pranzini, and Peter Molnar
Hydrol. Earth Syst. Sci., 20, 4177–4190, https://doi.org/10.5194/hess-20-4177-2016, https://doi.org/10.5194/hess-20-4177-2016, 2016
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We show that the derived distribution approach is able to characterize the interannual variability of precipitation much better than fitting a probabilistic model to annual rainfall totals, as long as continuously gauged data are available. The method is a useful tool for describing temporal changes in the distribution of annual rainfall, as it works for records as short as 5 years, and therefore does not require any stationarity assumption over long periods.
Bahareh Kianfar, Simone Fatichi, Athansios Paschalis, Max Maurer, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-536, https://doi.org/10.5194/hess-2016-536, 2016
Revised manuscript has not been submitted
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Raingauge observations show a large variability in extreme rainfall depths in the current climate. Climate model predictions of extreme rainfall in the future have to be compared with this natural variability. Our work shows that predictions of future extreme rainfall often lie within the range of natural variability of present-day climate, and therefore predictions of change are highly uncertain. We demonstrate this by using stochastic rainfall models and 10-min rainfall data in Switzerland.
Matteo Saletti, Peter Molnar, Marwan A. Hassan, and Paolo Burlando
Earth Surf. Dynam., 4, 549–566, https://doi.org/10.5194/esurf-4-549-2016, https://doi.org/10.5194/esurf-4-549-2016, 2016
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This study presents a new reduced-complexity model with few parameters linked to basic physical processes, which aims to reproduce the transport of sediment as bed load and the formation and stability of channel morphology in steep mountain streams. The model is able to simulate the formation and stability of steps, bed structures commonly encountered in steep channels, by assuming that their formation is due to intense sediment transport during high flows causing jamming of particles.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
P. Molnar, S. Fatichi, L. Gaál, J. Szolgay, and P. Burlando
Hydrol. Earth Syst. Sci., 19, 1753–1766, https://doi.org/10.5194/hess-19-1753-2015, https://doi.org/10.5194/hess-19-1753-2015, 2015
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We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.
K. Džubáková, P. Molnar, K. Schindler, and M. Trizna
Hydrol. Earth Syst. Sci., 19, 195–208, https://doi.org/10.5194/hess-19-195-2015, https://doi.org/10.5194/hess-19-195-2015, 2015
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We use a high-resolution ground-based camera system with near-infrared sensitivity to quantify the response of riparian vegetation in an Alpine river to floods with the use of vegetation indices. The vegetation showed both damage and enhancement within 1 week following floods, with a selective impact determined by pre-flood vegetation vigour, morphological setting and intensity of flood forcing. The tested vegetation indices differed in the direction of predicted change in the range 0.7-35.8%.
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
L. Gaál, P. Molnar, and J. Szolgay
Hydrol. Earth Syst. Sci., 18, 1561–1573, https://doi.org/10.5194/hess-18-1561-2014, https://doi.org/10.5194/hess-18-1561-2014, 2014
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Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
Addressing class imbalance in soil movement predictions
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
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Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
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Lorenzo Nava, Alessandro Novellino, Chengyong Fang, Kushanav Bhuyan, Kathryn Leeming, Itahisa Gonzalez Alvarez, Claire Dashwood, Sophie Doward, Rahul Chahel, Emma McAllister, Sansar Raj Meena, and Filippo Catani
Nat. Hazards Earth Syst. Sci., 25, 2371–2377, https://doi.org/10.5194/nhess-25-2371-2025, https://doi.org/10.5194/nhess-25-2371-2025, 2025
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On 2 April 2024, a Mw 7.4 earthquake hit Taiwan's eastern coast, causing extensive landslides and damage. We used automated methods combining Earth observation (EO) data with AI to quickly inventory the landslides. This approach identified 7090 landslides over 75 km2 within 3 h of acquiring the EO imagery. The study highlights AI's role in improving landslide detection efforts in disaster response.
Jane Walden, Mylène Jacquemart, Bretwood Higman, Romain Hugonnet, Andrea Manconi, and Daniel Farinotti
Nat. Hazards Earth Syst. Sci., 25, 2045–2073, https://doi.org/10.5194/nhess-25-2045-2025, https://doi.org/10.5194/nhess-25-2045-2025, 2025
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We studied eight glacier-adjacent landslides in Alaska and found that slope movement increased at four sites as the glacier retreated past the landslide area. Movement at other sites may be due to heavy precipitation or increased glacier thinning, and two sites showed little to no motion. We suggest that landslides near waterbodies may be especially vulnerable to acceleration, which we guess is due to faster retreat rates of water-terminating glaciers and changing water flow in the slope.
Maximillian Van Wyk de Vries, Alexandre Dunant, Amy L. Johnson, Erin L. Harvey, Sihan Li, Katherine Arrell, Jeevan Baniya, Dipak Basnet, Gopi K. Basyal, Nyima Dorjee Bhotia, Simon J. Dadson, Alexander L. Densmore, Tek Bahadur Dong, Mark E. Kincey, Katie Oven, Anuradha Puri, and Nick J. Rosser
Nat. Hazards Earth Syst. Sci., 25, 1937–1942, https://doi.org/10.5194/nhess-25-1937-2025, https://doi.org/10.5194/nhess-25-1937-2025, 2025
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Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. In this study, we show that there is a poor correlation between building damage and deaths from landslides, such that the deadliest landslides do not always destroy the most buildings and vice versa. This has important implications for our management of landslide risk.
Yu Zhuang, Brian W. McArdell, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 25, 1901–1912, https://doi.org/10.5194/nhess-25-1901-2025, https://doi.org/10.5194/nhess-25-1901-2025, 2025
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The experimentally based μ(I) rheology, widely used for gravitational mass flows, is reinterpreted as a Voellmy-type relationship to highlight its link to grain flow theory. Through block modeling and case studies, we establish its equivalence to μ(R) rheology. μ(I) models shear thinning but fails to capture acceleration and deceleration processes and deposit structure. Incorporating fluctuation energy in μ(R) improves accuracy, refining mass flow modeling and revealing practical challenges.
Sonam Rinzin, Stuart Dunning, Rachel Joanne Carr, Ashim Sattar, and Martin Mergili
Nat. Hazards Earth Syst. Sci., 25, 1841–1864, https://doi.org/10.5194/nhess-25-1841-2025, https://doi.org/10.5194/nhess-25-1841-2025, 2025
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We modelled multiple glacial lake outburst flood (GLOF) scenarios (84 simulations) and tested the effect of nine key input parameters on the modelling results using r.avaflow. Our results highlight that GLOF modelling results are subject to uncertainty from the multiple input parameters. The variation in the volume of mass movement entering the lake causes the highest uncertainty in the modelled GLOF, followed by the DEM dataset and the origin of mass movement.
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.
Roberto Sarro, Mauro Rossi, Paola Reichenbach, and Rosa María Mateos
Nat. Hazards Earth Syst. Sci., 25, 1459–1479, https://doi.org/10.5194/nhess-25-1459-2025, https://doi.org/10.5194/nhess-25-1459-2025, 2025
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This study proposes a novel systematic workflow that integrates source area identification, deterministic runout modelling, the classification of runout outputs to derive susceptibility zonation, and robust procedures for validation and comparison. The proposed approach enables the integration and comparison of different modelling, introducing a robust and consistent workflow/methodology that allows us to derive and verify rockfall susceptibility zonation, considering different steps.
Matthias Schlögl, Anita Graser, Raphael Spiekermann, Jasmin Lampert, and Stefan Steger
Nat. Hazards Earth Syst. Sci., 25, 1425–1437, https://doi.org/10.5194/nhess-25-1425-2025, https://doi.org/10.5194/nhess-25-1425-2025, 2025
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Communicating uncertainties is a crucial yet challenging aspect of spatial modelling – especially in applied research, where results inform decisions. In disaster risk reduction, susceptibility maps for natural hazards guide planning and risk assessment, yet their uncertainties are often overlooked. We present a new type of landslide susceptibility map that visualizes both susceptibility and associated uncertainty alongside guidelines for creating such maps using free and open-source software.
Lisa V. Luna, Jacob B. Woodard, Janice L. Bytheway, Gina M. Belair, and Benjamin B. Mirus
EGUsphere, https://doi.org/10.5194/egusphere-2025-947, https://doi.org/10.5194/egusphere-2025-947, 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.
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci., 25, 1229–1253, https://doi.org/10.5194/nhess-25-1229-2025, https://doi.org/10.5194/nhess-25-1229-2025, 2025
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Landslide runout zones are the areas downslope or downstream of landslide initiation. People often live and work in these areas, leading to property damage and deaths. Landslide runout may occur on hillslopes or in channels, requiring different modeling approaches. We develop methods to identify potential runout zones and apply these methods to identify susceptible areas for three municipalities in Puerto Rico.
Jonathan Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
Nat. Hazards Earth Syst. Sci., 25, 1037–1056, https://doi.org/10.5194/nhess-25-1037-2025, https://doi.org/10.5194/nhess-25-1037-2025, 2025
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Rainfall-induced landslides result in deaths and economic losses annually across the globe. However, it is unclear how storm severity relates to landslide severity across large regions. Here we develop a method to dynamically map landslide-affected areas, and we compare this to meteorological estimates of storm severity. We find that preconditioning by earlier storms and the location of rainfall bursts, rather than atmospheric storm strength, dictate landslide magnitude and pattern.
Ellen B. Robson, Bhim Kumar Dahal, and David G. Toll
Nat. Hazards Earth Syst. Sci., 25, 949–973, https://doi.org/10.5194/nhess-25-949-2025, https://doi.org/10.5194/nhess-25-949-2025, 2025
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Slopes excavated alongside roads in Nepal frequently fail (a landslide), resulting in substantial losses. Our participatory approach study with road engineers aimed to assess how road slope design guidelines in Nepal can be improved. Our study revealed inconsistent guideline adherence due to a lack of user-friendliness and inadequate training. We present general recommendations to enhance road slope management, as well as technical recommendations to improve the guidelines.
Chenchen Qiu and Xueyu Geng
Nat. Hazards Earth Syst. Sci., 25, 709–726, https://doi.org/10.5194/nhess-25-709-2025, https://doi.org/10.5194/nhess-25-709-2025, 2025
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We propose an integrated method using a combination of a physical vulnerability matrix and a machine learning model to estimate the potential physical damage and associated economic loss caused by future debris flows based on collected historical data on the Qinghai–Tibet Plateau region.
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
Nat. Hazards Earth Syst. Sci., 25, 647–656, https://doi.org/10.5194/nhess-25-647-2025, https://doi.org/10.5194/nhess-25-647-2025, 2025
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Debris flows occur infrequently, with average recurrence intervals (ARIs) ranging from decades to millennia. Consequently, they pose an underappreciated hazard. We describe how to make a preliminary identification of debris-flow-susceptible catchments, estimate threshold ARIs for debris flows that pose an unacceptable risk to life, and identify the “window of non-recognition” where debris flows are infrequent enough that their hazard is unrecognised yet frequent enough to pose a risk to life.
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci., 25, 467–491, https://doi.org/10.5194/nhess-25-467-2025, https://doi.org/10.5194/nhess-25-467-2025, 2025
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We developed a machine-learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables, including metrics on terrain, geomorphology, vegetation height, and lithology, and used data from two Swiss field inventories to calibrate and test the models. The best-performing machine learning model consistently reduced the mean average error by at least 20 % compared to previous models.
Jui-Ming Chang, Che-Ming Yang, Wei-An Chao, Chin-Shang Ku, Ming-Wan Huang, Tung-Chou Hsieh, and Chi-Yao Hung
Nat. Hazards Earth Syst. Sci., 25, 451–466, https://doi.org/10.5194/nhess-25-451-2025, https://doi.org/10.5194/nhess-25-451-2025, 2025
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The study on the Cilan landslide (CL) demonstrates the utilization of seismic analysis results as preliminary data for geologists during field surveys. Spectrograms revealed that the first event of CL consisted of four sliding failures accompanied by a gradual reduction in landslide volume. The second and third events were minor toppling and rockfalls. Then combining the seismological-based knowledge and field survey results, the spatiotemporal variation in landslide evolution is proposed.
Johannes Jakob Fürst, David Farías-Barahona, Thomas Bruckner, Lucia Scaff, Martin Mergili, Santiago Montserrat, and Humberto Peña
EGUsphere, https://doi.org/10.5194/egusphere-2024-3103, https://doi.org/10.5194/egusphere-2024-3103, 2025
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The 1987 Parraguirre ice-rock avalanche developed into a devastating debris-flow causing loss of many lives and inflicting severe damage near Santiago, Chile. Here, we revise this event combining various observational records with modelling techniques. In this year, important snow cover coincided with warm days in spring. We further quantify the total solid volume, and forward important upward corrections for the trigger and flood volumes. Finally, river damming was key for high flow mobility.
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025, https://doi.org/10.5194/nhess-25-183-2025, 2025
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The paper focuses on classifying continuous landslide conditioning factors for susceptibility modelling, which resulted in 54 landslide susceptibility models that tested 11 classification criteria in combination with 5 statistical methods. The novelty of the research is that using stretched landslide conditioning factor values results in models with higher accuracy and that certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others.
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.
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci., 25, 119–146, https://doi.org/10.5194/nhess-25-119-2025, https://doi.org/10.5194/nhess-25-119-2025, 2025
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This study enhances landslide prediction using advanced machine learning, including new algorithms inspired by historical explorations. The research accurately forecasts landslide movements by analyzing 8 years of data from Taiwan's Lushan, improving early warning and potentially saving lives and infrastructure. This integration marks a significant advancement in environmental risk management.
Di Wu, Yuke Wang, and Xin Chen
Nat. Hazards Earth Syst. Sci., 24, 4617–4630, https://doi.org/10.5194/nhess-24-4617-2024, https://doi.org/10.5194/nhess-24-4617-2024, 2024
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This paper proposes a 3D limit analysis for seismic stability of soil slopes to address the influence of earthquakes on slope stabilities with nonlinear and linear criteria. Comparison results illustrate that the use of a linear envelope leads to the non-negligible overestimation of steep-slope stability, and this overestimation will be significant with increasing earthquakes. Earthquakes have a smaller influence on slope slip surfaces with a nonlinear envelope than those with a linear envelope.
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024, https://doi.org/10.5194/nhess-24-4179-2024, 2024
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The damage patterns of the buildings were classified into three types: (I) buried by primary debris flow, (II) inundated by secondary dam-burst flood, and (III) sequentially buried by debris flow and inundated by dam-burst flood. The threshold of the impact pressures in Zones (II) and (III) where vulnerability is equal to 1 is 84 kPa and 116 kPa, respectively. Heavy damage occurs at an impact pressure greater than 50 kPa, while slight damage occurs below 30 kPa.
Bo Peng and Xueling Wu
Nat. Hazards Earth Syst. Sci., 24, 3991–4013, https://doi.org/10.5194/nhess-24-3991-2024, https://doi.org/10.5194/nhess-24-3991-2024, 2024
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Our research enhances landslide prevention using advanced machine learning to forecast heavy-rainfall-triggered landslides. By analyzing regions and employing various models, we identified optimal ways to predict high-risk rainfall events. Integrating multiple factors and models, including a neural network, significantly improves landslide predictions. Real data validation confirms our approach's reliability, aiding communities in mitigating landslide impacts and safeguarding lives and property.
Mahnoor Ahmed, Giacomo Titti, Sebastiano Trevisani, Lisa Borgatti, and Mirko Francioni
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-211, https://doi.org/10.5194/nhess-2024-211, 2024
Revised manuscript accepted for NHESS
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Elevation models are compared with a true dataset for terrain characteristics which selects a better ranking model to test with different parameters for partitioning the terrain. The partitioning of the terrain is measured by how well a partitioned unit can support the mapped landslide area and number of landslides. The effect of this relationship is reflected with different metrics in the susceptibility maps.
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
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Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
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.
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024, https://doi.org/10.5194/nhess-24-3651-2024, 2024
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This work examines the use of interferometric synthetic-aperture radar (InSAR) alongside in situ borehole measurements to assess the stability of deep-seated landslides for the case study of El Forn (Andorra). Comparing InSAR with borehole data suggests a key trade-off between accuracy and precision for various InSAR resolutions. Spatial interpolation with InSAR informed how many remote observations are necessary to lower error in a remote sensing re-creation of ground motion over the landslide.
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024, https://doi.org/10.5194/nhess-24-3357-2024, 2024
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The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
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The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Bart Strijker and Matthijs Kok
EGUsphere, https://doi.org/10.5194/egusphere-2024-1495, https://doi.org/10.5194/egusphere-2024-1495, 2024
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This study examines how hydraulic head levels in canal dikes respond to heavy rainfall, potentially causing instabilities and flooding. Using time series models and simulating long-term head levels, we identified clusters of dikes where head peaks are driven by similar rainfall events. Statistical analyses show that extreme and yearly conditions are close. However, extreme conditions are expected to become more frequent due to climate change, though some dikes will be less affected than others.
Isabelle Utley, Tristram Hales, Ekbal Hussain, and Xuanmei Fan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2277, https://doi.org/10.5194/egusphere-2024-2277, 2024
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We analysed debris flows in Sichuan, China, using satellite data and simulations to assess check dam efficacy. Our study found whilst check dams can mitigate smaller flows, they may increase exposure to extreme events, with up to 40 % of structures in some areas affected. Urban development and reliance on check dams can create a false sense of security, raising exposure during large debris flows and highlights the need for risk management and infrastructure planning in hazard-prone areas.
Daniel Camilo Roman Quintero, Pasquale Marino, Abdullah Abdullah, Giovanni Francesco Santonastaso, and Roberto Greco
EGUsphere, https://doi.org/10.5194/egusphere-2024-2329, https://doi.org/10.5194/egusphere-2024-2329, 2024
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Local thresholds for landslide forecasting, combining hydrologic predisposing factors and rainfall features, are developed from a physically based model of a slope. To extend their application to a wide area, uncertainty due to spatial variability of geomorphological and hydrologic variables is introduced. The obtained hydrometeorological thresholds, integrating root zone soil moisture and aquifer water level with rainfall depth, outperform thresholds based on rain intensity and duration.
Micol Fumagalli, Alberto Previati, Paolo Frattini, and Giovanni B. Crosta
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-140, https://doi.org/10.5194/nhess-2024-140, 2024
Revised manuscript accepted for NHESS
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Shallow landslides are mass movements of limited thickness, mainly triggered by extreme rainfalls, that can pose a serious risk to the population. This study uses statistical methods to analyse and simulate the relationship between shallow landslides and rainfalls, showing that in the studied area shallow landslides are modulated by rainfall but controlled by lithology. A new classification method considering the costs associated with a misclassification of the susceptibility is also proposed.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
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Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
Jianqi Zhuang, Jianbing Peng, Chenhui Du, Yi Zhu, and Jiaxu Kong
Nat. Hazards Earth Syst. Sci., 24, 2615–2631, https://doi.org/10.5194/nhess-24-2615-2024, https://doi.org/10.5194/nhess-24-2615-2024, 2024
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The Revised Infinite Slope Model (RISM) is proposed using the equal differential unit method and correcting the deficiency of the safety factor increasing with the slope increasing when the slope is larger than 40°, as calculated using the Taylor slope infinite model. The intensity–duration (I–D) prediction curve of the rainfall-induced shallow loess landslides with different slopes was constructed and can be used in forecasting regional shallow loess landslides.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
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Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 h) needed for decision-making. This work takes an initial step toward a near-real-time postfire debris-flow inundation hazard assessment product.
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 K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
Nat. Hazards Earth Syst. Sci., 24, 2093–2114, https://doi.org/10.5194/nhess-24-2093-2024, https://doi.org/10.5194/nhess-24-2093-2024, 2024
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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 2-year period. We also proposed ways to improve these models.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024, https://doi.org/10.5194/nhess-24-1913-2024, 2024
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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 (synthetic minority oversampling technique) achieves high precision, high recall, and a high F1 score. Our findings highlight the potential of these models with oversampling techniques to improve soil movement predictions in landslide-prone areas.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
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In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
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With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, 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 earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
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Central Asia regions are marked 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 possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
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
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.
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Short summary
Landslides are a natural hazard that affects alpine regions. Here we focus on rainfall-induced shallow landslides and one of the most widely used approaches for their predictions: rainfall thresholds. We design several comparisons utilizing a landslide database and rainfall records in Switzerland. We find that using daily rather than hourly rainfall might be a better option in some circumstances, and mean annual precipitation and antecedent wetness can improve predictions at the regional scale.
Landslides are a natural hazard that affects alpine regions. Here we focus on rainfall-induced...
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