Articles | Volume 21, issue 11
https://doi.org/10.5194/nhess-21-3539-2021
© Author(s) 2021. 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-21-3539-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Nov 2021
Research article |
| 22 Nov 2021
| 22 Nov 2021
Multiscale analysis of surface roughness for the improvement of natural hazard modelling
Alpine Environment and Natural Hazards, WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Department of Environmental Systems Science, Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Flüelastrasse 11, 7260 Davos
Dorf, Switzerland
Tommaso Baggio
Department of Land, Environment, Agriculture and Forestry, University of Padua, Legnaro, Italy
Vincenzo D'Agostino
Department of Land, Environment, Agriculture and Forestry, University of Padua, Legnaro, Italy
Yves Bühler
Alpine Environment and Natural Hazards, WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Flüelastrasse 11, 7260 Davos
Dorf, Switzerland
Peter Bebi
Alpine Environment and Natural Hazards, WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Flüelastrasse 11, 7260 Davos
Dorf, Switzerland
Related authors
Natalie Piazza, Luca Malanchini, Edoardo Nevola, and Giorgio Vacchiano
Nat. Hazards Earth Syst. Sci., 24, 3579–3595, https://doi.org/10.5194/nhess-24-3579-2024, https://doi.org/10.5194/nhess-24-3579-2024, 2024
Short summary
Short summary
Natural disturbances are projected to intensify in the future, threatening our forests and their functions such as wood production, protection against natural hazards, and carbon sequestration. By assessing risks to forests from wind and fire damage, alongside the vulnerability of carbon, it is possible to prioritize forest stands at high risk. In this study, we propose a novel methodological approach to support climate-smart forest management and inform better decision-making.
Julia Glaus, Katreen Wikstrom Jones, Perry Bartelt, Marc Christen, Lukas Stoffel, Johan Gaume, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 2399–2419, https://doi.org/10.5194/nhess-25-2399-2025, https://doi.org/10.5194/nhess-25-2399-2025, 2025
Short summary
Short summary
This study assesses RAMMS::EXTENDED's predictive power in estimating avalanche runout distances critical for mountain road safety. Leveraging meteorological data and sensitivity analyses, it offers meaningful predictions, aiding near real-time hazard assessments and future model refinement for improved decision-making.
Pia Ruttner, Annelies Voordendag, Thierry Hartmann, Julia Glaus, Andreas Wieser, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1315–1330, https://doi.org/10.5194/nhess-25-1315-2025, https://doi.org/10.5194/nhess-25-1315-2025, 2025
Short summary
Short summary
Snow depth variations caused by wind are an important factor in avalanche danger, but detailed and up-to-date information is rarely available. We propose a monitoring system, using lidar and optical sensors, to measure the snow depth distribution at high spatial and temporal resolution. First results show that we can quantify snow depth changes with an accuracy on the low decimeter level, or better, and can identify events such as avalanches or displacement of snow during periods of strong winds.
John Sykes, Pascal Haegeli, Roger Atkins, Patrick Mair, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1255–1292, https://doi.org/10.5194/nhess-25-1255-2025, https://doi.org/10.5194/nhess-25-1255-2025, 2025
Short summary
Short summary
We model the decision-making of professional ski guides and develop decision support tools to assist with determining appropriate terrain based on current conditions. Our approach compares a manually constructed Bayesian network with machine learning classification models. The models accurately capture the real-world decision-making outcomes in 85–93 % of cases. Our conclusions focus on strengths and weaknesses of each model and discuss ramifications for practical applications in ski guiding.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
Short summary
Short summary
In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
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
Short summary
Short summary
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.
Natalie Piazza, Luca Malanchini, Edoardo Nevola, and Giorgio Vacchiano
Nat. Hazards Earth Syst. Sci., 24, 3579–3595, https://doi.org/10.5194/nhess-24-3579-2024, https://doi.org/10.5194/nhess-24-3579-2024, 2024
Short summary
Short summary
Natural disturbances are projected to intensify in the future, threatening our forests and their functions such as wood production, protection against natural hazards, and carbon sequestration. By assessing risks to forests from wind and fire damage, alongside the vulnerability of carbon, it is possible to prioritize forest stands at high risk. In this study, we propose a novel methodological approach to support climate-smart forest management and inform better decision-making.
Jaeyoung Lim, Elisabeth Hafner, Florian Achermann, Rik Girod, David Rohr, Nicholas R. J. Lawrance, Yves Bühler, and Roland Siegwart
EGUsphere, https://doi.org/10.5194/egusphere-2024-2728, https://doi.org/10.5194/egusphere-2024-2728, 2024
Short summary
Short summary
As avalanches occur in remote and potentially dangerous locations, data relevant to avalanche monitoring is difficult to obtain. Uncrewed fixed-wing aerial vehicles are promising platforms for gathering aerial imagery to map avalanche activity over a large area. In this work, we present an unmanned aerial system (UAS) capable of autonomously navigating and mapping avalanches in steep mountainous terrain. We expect our work to enable efficient large-scale autonomous avalanche monitoring.
Elisabeth D. Hafner, Theodora Kontogianni, Rodrigo Caye Daudt, Lucien Oberson, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 18, 3807–3823, https://doi.org/10.5194/tc-18-3807-2024, https://doi.org/10.5194/tc-18-3807-2024, 2024
Short summary
Short summary
For many safety-related applications such as road management, well-documented avalanches are important. To enlarge the information, webcams may be used. We propose supporting the mapping of avalanches from webcams with a machine learning model that interactively works together with the human. Relying on that model, there is a 90% saving of time compared to the "traditional" mapping. This gives a better base for safety-critical decisions and planning in avalanche-prone mountain regions.
Elisabeth D. Hafner, Frank Techel, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 23, 2895–2914, https://doi.org/10.5194/nhess-23-2895-2023, https://doi.org/10.5194/nhess-23-2895-2023, 2023
Short summary
Short summary
Oftentimes when objective measurements are not possible, human estimates are used instead. In our study, we investigate the reproducibility of human judgement for size estimates, the mappings of avalanches from oblique photographs and remotely sensed imagery. The variability that we found in those estimates is worth considering as it may influence results and should be kept in mind for several applications.
Leon J. Bührle, Mauro Marty, Lucie A. Eberhard, Andreas Stoffel, Elisabeth D. Hafner, and Yves Bühler
The Cryosphere, 17, 3383–3408, https://doi.org/10.5194/tc-17-3383-2023, https://doi.org/10.5194/tc-17-3383-2023, 2023
Short summary
Short summary
Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from aeroplane to large (> 100 km2) detailed and accurate snow depth maps around Davos (CH). We use these maps to describe the existing snow depth distribution, other special features and potential applications.
Adrian Ringenbach, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Yves Bühler, Andreas Stoffel, and Andrin Caviezel
Earth Surf. Dynam., 11, 779–801, https://doi.org/10.5194/esurf-11-779-2023, https://doi.org/10.5194/esurf-11-779-2023, 2023
Short summary
Short summary
Swiss researchers carried out repeated rockfall experiments with rocks up to human sizes in a steep mountain forest. This study focuses mainly on the effects of the rock shape and lying deadwood. In forested areas, cubic-shaped rocks showed a longer mean runout distance than platy-shaped rocks. Deadwood especially reduced the runouts of these cubic rocks. The findings enrich standard practices in modern rockfall hazard zoning assessments and strongly urge the incorporation of rock shape effects.
Gregor Ortner, Michael Bründl, Chahan M. Kropf, Thomas Röösli, Yves Bühler, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 23, 2089–2110, https://doi.org/10.5194/nhess-23-2089-2023, https://doi.org/10.5194/nhess-23-2089-2023, 2023
Short summary
Short summary
This paper presents a new approach to assess avalanche risk on a large scale in mountainous regions. It combines a large-scale avalanche modeling method with a state-of-the-art probabilistic risk tool. Over 40 000 individual avalanches were simulated, and a building dataset with over 13 000 single buildings was investigated. With this new method, risk hotspots can be identified and surveyed. This enables current and future risk analysis to assist decision makers in risk reduction and adaptation.
Adrian Ringenbach, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Yves Bühler, Andreas Stoffel, and Andrin Caviezel
Earth Surf. Dynam., 10, 1303–1319, https://doi.org/10.5194/esurf-10-1303-2022, https://doi.org/10.5194/esurf-10-1303-2022, 2022
Short summary
Short summary
The presented automatic deadwood generator (ADG) allows us to consider deadwood in rockfall simulations in unprecedented detail. Besides three-dimensional fresh deadwood cones, we include old woody debris in rockfall simulations based on a higher compaction rate and lower energy absorption thresholds. Simulations including different deadwood states indicate that a 10-year-old deadwood pile has a higher protective capacity than a pre-storm forest stand.
John Sykes, Pascal Haegeli, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 3247–3270, https://doi.org/10.5194/nhess-22-3247-2022, https://doi.org/10.5194/nhess-22-3247-2022, 2022
Short summary
Short summary
Automated snow avalanche terrain mapping provides an efficient method for large-scale assessment of avalanche hazards, which informs risk management decisions for transportation and recreation. This research reduces the cost of developing avalanche terrain maps by using satellite imagery and open-source software as well as improving performance in forested terrain. The research relies on local expertise to evaluate accuracy, so the methods are broadly applicable in mountainous regions worldwide.
Elisabeth D. Hafner, Patrick Barton, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 16, 3517–3530, https://doi.org/10.5194/tc-16-3517-2022, https://doi.org/10.5194/tc-16-3517-2022, 2022
Short summary
Short summary
Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 2673–2701, https://doi.org/10.5194/nhess-22-2673-2022, https://doi.org/10.5194/nhess-22-2673-2022, 2022
Short summary
Short summary
Natural hazard modelers simulate mass movements to better anticipate the risk to people and infrastructure. These simulations require accurate digital elevation models. We test the sensitivity of a well-established snow avalanche model (RAMMS) to the source and spatial resolution of the elevation model. We find key differences in the digital representation of terrain greatly affect the simulated avalanche results, with implications for hazard planning.
Adrian Ringenbach, Elia Stihl, Yves Bühler, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Guang Lu, Andreas Stoffel, Martin Kistler, Sandro Degonda, Kevin Simmler, Daniel Mader, and Andrin Caviezel
Nat. Hazards Earth Syst. Sci., 22, 2433–2443, https://doi.org/10.5194/nhess-22-2433-2022, https://doi.org/10.5194/nhess-22-2433-2022, 2022
Short summary
Short summary
Forests have a recognized braking effect on rockfalls. The impact of lying deadwood, however, is mainly neglected. We conducted 1 : 1-scale rockfall experiments in three different states of a spruce forest to fill this knowledge gap: the original forest, the forest including lying deadwood and the cleared area. The deposition points clearly show that deadwood has a protective effect. We reproduced those experimental results numerically, considering three-dimensional cones to be deadwood.
Yves Bühler, Peter Bebi, Marc Christen, Stefan Margreth, Lukas Stoffel, Andreas Stoffel, Christoph Marty, Gregor Schmucki, Andrin Caviezel, Roderick Kühne, Stephan Wohlwend, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 22, 1825–1843, https://doi.org/10.5194/nhess-22-1825-2022, https://doi.org/10.5194/nhess-22-1825-2022, 2022
Short summary
Short summary
To calculate and visualize the potential avalanche hazard, we develop a method that automatically and efficiently pinpoints avalanche starting zones and simulate their runout for the entire canton of Grisons. The maps produced in this way highlight areas that could be endangered by avalanches and are extremely useful in multiple applications for the cantonal authorities, including the planning of new infrastructure, making alpine regions more safe.
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
Short summary
Short summary
To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
Short summary
Short summary
The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Elisabeth D. Hafner, Frank Techel, Silvan Leinss, and Yves Bühler
The Cryosphere, 15, 983–1004, https://doi.org/10.5194/tc-15-983-2021, https://doi.org/10.5194/tc-15-983-2021, 2021
Short summary
Short summary
Satellites prove to be very valuable for documentation of large-scale avalanche periods. To test reliability and completeness, which has not been satisfactorily verified before, we attempt a full validation of avalanches mapped from two optical sensors and one radar sensor. Our results demonstrate the reliability of high-spatial-resolution optical data for avalanche mapping, the suitability of radar for mapping of larger avalanches and the unsuitability of medium-spatial-resolution optical data.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
Short summary
Short summary
The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Lucie A. Eberhard, Pascal Sirguey, Aubrey Miller, Mauro Marty, Konrad Schindler, Andreas Stoffel, and Yves Bühler
The Cryosphere, 15, 69–94, https://doi.org/10.5194/tc-15-69-2021, https://doi.org/10.5194/tc-15-69-2021, 2021
Short summary
Short summary
In spring 2018 in the alpine Dischma valley (Switzerland), we tested different industrial photogrammetric platforms for snow depth mapping. These platforms were high-resolution satellites, an airplane, unmanned aerial systems and a terrestrial system. Therefore, this study gives a general overview of the accuracy and precision of the different photogrammetric platforms available in space and on earth and their use for snow depth mapping.
Cited articles
Amman, M.: Schutzwirkung abgestorbener Bäume gegen Naturgefahren, PhD thesis, Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft, ETH Zürich, Zurich, Switzerland, 240 pp., 2006.
Baggio, T.: TommBagg/terrain_roughness_GRASS: Roughness calculation in GRASS, v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.5675833, 2021.
Baroni, C., Armiraglio, S., Gentili, R., and Carton, A.: Landform-vegetation
units for investigating the dynamics and geomorphologic evolution of alpine
composite debris cones (Valle dell'Avio, Adamello Group, Italy),
Geomorphology, 84, 59–79, https://doi.org/10.1016/j.geomorph.2006.07.002, 2007.
Bartelt, P., Bühler, Y., Christen, M., Deubelbeiss, Y., Salz, M.,
Schneider, M., and Schumacher, L.: A numerical model for snow avalanches in
research and practice, RAMMS User Manual v. 1.7. 0 Avalanche, WSL Institute for Snow and Avalanche Research SLF, Davos,
104 pp., 2017.
Bebi, P., Kulakowski, D., and Rixen, C.: Snow avalanche disturbances in
forest ecosystems-State of research and implications for management, Forest.
Ecol. Manag., 257, 1883–1892, https://doi.org/10.1016/j.foreco.2009.01.050, 2009.
Bebi, P., Putallaz, J. M., Fankhauser, M., Schmid, U., Schwitter, R., and Gerber, W.: Die Schutzfunktion in Windwurfflächen, Schweizerische
Zeitschrift fur Forstwes., 166, 168–176, https://doi.org/10.3188/szf.2015.0168, 2015.
Bebi, P., Seidl, R., Motta, R., Fuhr, M., Firm, D., Krumm, F., Conedera, M.,
Ginzler, C., Wohlgemuth, T., and Kulakowski, D.: Changes of forest cover and
disturbance regimes in the mountain forests of the Alps, Forest. Ecol. Manag., 388, 43–56, https://doi.org/10.1016/j.foreco.2016.10.028, 2017.
Bigot, C., Dorren, L. K. A., and Berger, F.: Quantifying the protective
function of a forest against rockfall for past, present and future scenarios
using two modelling approaches, Nat. Hazards, 49, 99–111,
https://doi.org/10.1007/s11069-008-9280-0, 2009.
Bourrier, F., Dorren, L., and Berger, F.: Full scale tests on rockfall
impacting trees felled transverse to the slope, in: Interpraevent, Grenoble, pp. 643–650, available at: http://www.interpraevent.at (last access: 3 November 2020), 2012.
Brändli, U. B. and Speich, S.: Swiss NFI glossary and dictionary, Birmensdorf, Swiss Federal Research Institute WSL, available at:
https://www.lfi.ch/glossar/glossar-en.php (last access: 17 November 2020), 2007.
Brožová, N., Fischer, J. T., Bühler, Y., Bartelt, P., and Bebi,
P.: Determining forest parameters for avalanche simulation using remote
sensing data, Cold Reg. Sci. Technol., 172, 102976,
https://doi.org/10.1016/j.coldregions.2019.102976, 2020.
Bühler, Y., Christen, M., Kowalski, J., and Bartelt, P.: Sensitivity of
snow avalanche simulations to digital elevation model quality and
resolution, Ann. Glaciol., 52, 72–80, https://doi.org/10.3189/172756411797252121,
2011.
Bühler, Y., Kumar, S., Veitinger, J., Christen, M., Stoffel, A., and Snehmani: Automated identification of potential snow avalanche release areas based on digital elevation models, Nat. Hazards Earth Syst. Sci., 13, 1321–1335, https://doi.org/10.5194/nhess-13-1321-2013, 2013.
Bühler, Y., von Rickenbach, D., Stoffel, A., Margreth, S., Stoffel, L., and Christen, M.: Automated snow avalanche release area delineation – validation of existing algorithms and proposition of a new object-based approach for large-scale hazard indication mapping, Nat. Hazards Earth Syst. Sci., 18, 3235–3251, https://doi.org/10.5194/nhess-18-3235-2018, 2018.
Busse, A. and Jelly, T. O.: Influence of Surface Anisotropy on Turbulent Flow Over Irregular Roughness, Flow Turbul. Combust., 104, 331–354, https://doi.org/10.1007/s10494-019-00074-4, 2020.
Cavalli, M. and Marchi, L.: Characterisation of the surface morphology of an alpine alluvial fan using airborne LiDAR, Nat. Hazards Earth Syst. Sci., 8, 323–333, https://doi.org/10.5194/nhess-8-323-2008, 2008.
Cavalli, M., Tarolli, P., Marchi, L., and Dalla Fontana, G.: The
effectiveness of airborne LiDAR data in the recognition of channel-bed
morphology, Catena, 73, 249–260, https://doi.org/10.1016/j.catena.2007.11.001, 2008.
Caviezel, A., Demmel, S. E., Ringenbach, A., Bühler, Y., Lu, G., Christen, M., Dinneen, C. E., Eberhard, L. A., von Rickenbach, D., and Bartelt, P.: Reconstruction of four-dimensional rockfall trajectories using remote sensing and rock-based accelerometers and gyroscopes, Earth Surf. Dynam., 7, 199–210, https://doi.org/10.5194/esurf-7-199-2019, 2019.
Christen, M., Kowalski, J., and Bartelt, P.: RAMMS: Numerical simulation of
dense snow avalanches in three-dimensional terrain, Cold Reg. Sci. Technol.,
63, 1–14, https://doi.org/10.1016/j.coldregions.2010.04.005, 2010.
Crosta, G. B. and Agliardi, F.: Parametric evaluation of 3D dispersion of rockfall trajectories, Nat. Hazards Earth Syst. Sci., 4, 583–598, https://doi.org/10.5194/nhess-4-583-2004, 2004.
Dorren, L., Berger, F., Frehner, M., Huber, M., Kühne, K., Métral,
R., Sandri, A., Schwitter, R., Thormann, J.-J., and Wasser, B.: Das neue
NaiS-Anforderungsprofil Steinschlag, Schweizerische Zeitschrift fur
Forstwes., 166, 16–23, https://doi.org/10.3188/szf.2015.0016, 2015.
Dorren, L. K. A., Berger, F., Le Hir, C., Mermin, E., and Tardif, P.:
Mechanisms, effects and management implications of rockfall in forests, For.
Ecol. Manag., 215, 183–195, https://doi.org/10.1016/j.foreco.2005.05.012, 2005.
Durrant, A.: Vectors in physics and engineering, CRC Press, Taylor & Francis Group, Boca Raton, 310 pp., ISBN 978-0-2037-3439-1, 1996.
Elliott, G. P.: Treeline Ecotones, in: International Encyclopedia of
Geography: People, the Earth, Environment and Technology, edited by: Richardson, D., Castree, N., Goodchild, M. F., Kobayashi, A., Liu, W., and Marston, R. A., John
Wiley & Sons, Ltd, Oxford, UK, 10 pp., https://doi.org/10.1002/9781118786352, 2017.
Endo, Y.: Glide Processes of a Snow Cover as a Release Mechanism of an
Avalanche on a Slope Covered with Bamboo Bushes, Low Temp. Sci., 32, 39–68, 1983.
Evans, I.: Correlation Structures and Factor Analysis in the Investigation
of Data dimensionality: Statistical Properties of the Wessex Land Surface,
England, in: Proceeding of the international symposium on spatial data
handling, Zurich, Switzerland, 20–25 August 1984, vol. 2, pp. 98–116., 1984.
FAO: Forest Resources Assessment 2015, Terms and Definitions, Rome, available at: https://www.fao.org/forestry/fra (last access: 30 March 2020), 2015.
Feistl, T., Bebi, P., Dreier, L., Hanewinkel, M., and Bartelt, P.: Quantification of basal friction for technical and silvicultural glide-snow avalanche mitigation measures, Nat. Hazards Earth Syst. Sci., 14, 2921–2931, https://doi.org/10.5194/nhess-14-2921-2014, 2014.
Feistl, T., Bebi, P., Christen, M., Margreth, S., Diefenbach, L., and Bartelt, P.: Forest damage and snow avalanche flow regime, Nat. Hazards Earth Syst. Sci., 15, 1275–1288, https://doi.org/10.5194/nhess-15-1275-2015, 2015.
Fisher, R. A.: Dispersion on a sphere, Proc. R. Soc. London. Ser. A. Math.
Phys. Sci., 217, 295–305, 1953.
Frank, F., McArdell, B. W., Oggier, N., Baer, P., Christen, M., and Vieli, A.: Debris-flow modeling at Meretschibach and Bondasca catchments, Switzerland: sensitivity testing of field-data-based entrainment model, Nat. Hazards Earth Syst. Sci., 17, 801–815, https://doi.org/10.5194/nhess-17-801-2017, 2017.
Franklin, J. F., Spies, T. A., Pelt, R. Van, Carey, A. B., Thornburgh, D.
A., Berg, D. R., Lindenmayer, D. B., Harmon, M. E., Keeton, W. S., Shaw, D.
C., Bible, K., and Chen, J.: Disturbances and structural development of
natural forest ecosystems with silvicultural implications, using Douglas-fir
forests as an example, Forest. Ecol. Manag., 155, 399–423,
https://doi.org/10.1016/S0378-1127(01)00575-8, 2002.
Fuhr, M., Bourrier, F., and Cordonnier, T.: Protection against rockfall along
a maturity gradient in mountain forests, Forest. Ecol. Manag., 354, 224–231,
https://doi.org/10.1016/j.foreco.2015.06.012, 2015.
Gille, S. T., Yale, M. M., and Sandwell, D. T.: Global correlation of
mesoscale ocean variability with seafloor roughness from satellite
altimetry, Geophys. Res. Lett., 27, 1251–1254, https://doi.org/10.1029/1999GL007003, 2000.
Glenn, N. F., Streutker, D. R., Chadwick, D. J., Thackray, G. D., and Dorsch,
S. J.: Analysis of LiDAR-derived topographic information for characterizing
and differentiating landslide morphology and activity, Geomorphology,
73, 131–148, https://doi.org/10.1016/j.geomorph.2005.07.006, 2006.
GRASS Development Team: Geographic Resources Analysis Support System
(GRASS) Software, Version 7.8, available at:
http://grass.osgeo.org (last access: 10 January), 2021.
Grohmann, C. H. and Riccomini, C.: Comparison of roving-window and
search-window techniques for characterising landscape morphometry, Comput.
Geosci., 35, 2164–2169, https://doi.org/10.1016/j.cageo.2008.12.014, 2009.
Grohmann, C. H., Smith, M. J., and Riccomini, C.: Multiscale analysis of
topographic surface roughness in the Midland Valley, Scotland, IEEE Trans.
Geosci. Remote Sens., 49, 1200–1213, https://doi.org/10.1109/TGRS.2010.2053546,
2011.
Guo, J., Yi, S., Yin, Y., Cui, Y., Qin, M., Li, T., and Wang, C.: The effect of topography on landslide kinematics: a case study of the Jichang town landslide in Guizhou, China, Landslides, 17, 959–973, https://doi.org/10.1007/s10346-019-01339-9, 2020.
Haneberg, W. C., Creighton, A. L., Medley, E. W., and Jonas, D. A.: Use of
LiDAR to assess slope hazards at the Lihir gold mine, Papua New Guinea, in:
Proceedings of International Conference on Landslide Risk Management, edited by: Hungr, O., Fell, R., Couture, R., and Eberhard, E., Vancouver, 31 May–3 June 2005, 2005.
Hansen, W. D., Chapin, F. S., Naughton, H. T., Rupp, T. S., and Verbyla, D.:
Forest-landscape structure mediates effects of a spruce bark beetle
(Dendroctonus rufipennis) outbreak on subsequent likelihood of burning in
Alaskan boreal forest, Forest. Ecol. Manag., 369, 38–46,
https://doi.org/10.1016/j.foreco.2016.03.036, 2016.
Harsch, M. A., Hulme, P. E., McGlone, M. S., and Duncan, R. P.: Are treelines
advancing? A global meta-analysis of treeline response to climate warming,
Ecol. Lett., 12, 1040–1049, https://doi.org/10.1111/j.1461-0248.2009.01355.x, 2009.
Hobson, R. D.: FORTRAN IV programs to determine the surface roughness in
topography for the CDC 3400 computer, Comput. Contrib. State Geol. Surv.
Kansas, 14, 1–28, 1967.
Höller, P.: Snow gliding and avalanches in a south-facing, in: Soil-vegetation-atmosphere Transfer Schemes and Large-scale Hydrological Models: Proceedings of an International Symposium (Symposium S5) Held During the Sixth Scientific Assembly of the International Association of Hydrological Sciences (IAHS), Maastricht, the Netherlands, 18–27 July 2001, No. 270, p. 355–358, 2001.
Höller, P.: Snow gliding on a south-facing slope covered with larch
trees, Ann. For. Sci., 71, 81–89, https://doi.org/10.1007/s13595-013-0333-5, 2013.
Horn, B. K. P.: Hill shading and the reflectance map, in Proceeding of the
IEEE, pp. 14–47, available at:
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1456186
(last access: 26 March 2020), 1981.
Huebl, J. and Fiebiger, G.: Debris-flow mitigation measures, in Debris-flow
Hazards and Related Phenomena, Springer, Berlin, 445–487, ISBN 3-540-20726-0, 2007.
Hungr, O. and McDougall, S.: Two numerical models for landslide dynamic
analysis, Comput. Geosci., 35, 978–992, https://doi.org/10.1016/j.cageo.2007.12.003,
2009.
INFC: Inventario nazionale delle foreste e dei serbatoi di carbonio,
available at: https://www.sian.it/inventarioforestale/ (last access: 30 March 2020), 2005.
Insua-Arévalo, J. M., Tsige, M., Sánchez-Roldán, J. L., Rodríguez-Escudero, E., and Martínez-Díaz, J. J.: Influence of the microstructure and roughness of weakness planes on the strength anisotropy of a foliated clay-rich fault gouge, Eng. Geol., 289, 106186, https://doi.org/10.1016/j.enggeo.2021.106186, 2021.
Ishikawa, Y., Mizuhara, K., and Ashida, S.: Effect of density of trees on
drag exerted on trees in river channels, J. For. Res., 5, 271–279,
https://doi.org/10.1007/BF02767121, 2000.
Iverson, R. M., George, D. L., and Logan, M.: Debris flow runup on vertical barriers and adverse slopes, J. Geophys. Res.-Earth, 121, 2333–2357, https://doi.org/10.1002/2016JF003933, 2016.
Jakob, M., Hungr, O., and Jakob, D.: Debris-flow hazards and related
phenomena, edited by: Blonde, P., Springer, Berlin, 795 pp., ISBN 3-540-20726-0, available at:
https://link.springer.com/content/pdf/10.1007/b138657.pdf (last access: 27 November 2018), 2005.
Jonsson, M. J. O.: Energy absorption of trees in a rockfall protection
forest, PhD thesis, Swiss Federal Institute of Technology, Zurich, 209 pp., 2007.
Koponen, P., Nygren, P., Sabatier, D., Rousteau, A., and Saur, E.: Tree
species diversity and forest structure in relation to microtopography in a
tropical freshwater swamp forest in French Guiana, Plant Ecol., 173,
17–32, https://doi.org/10.1023/B:VEGE.0000026328.98628.b8, 2004.
Lehning, M., Grünewald, T., and Schirmer, M.: Mountain snow distribution
governed by an altitudinal gradient and terrain roughness, Geophys. Res.
Lett., 38, 1–5, https://doi.org/10.1029/2011GL048927, 2011.
Leitinger, G., Höller, P., Tasser, E., Walde, J., and Tappeiner, U.:
Development and validation of a spatial snow-glide model, Ecol. Modell., 211, 363–374 https://doi.org/10.1016/j.ecolmodel.2007.09.015, 2008.
Lopez-Saez, J., Corona, C., Eckert, N., Stoffel, M., Bourrier, F., and
Berger, F.: Impacts of land-use and land-cover changes on rockfall
propagation: Insights from the Grenoble conurbation, Sci. Total Environ.,
547, 345–355, https://doi.org/10.1016/j.scitotenv.2015.12.148, 2016.
López-Vicente, M. and Álvarez, S.: Influence of DEM resolution on
modelling hydrological connectivity in a complex agricultural catchment with
woody crops, Earth Surf. Process. Landforms, 43, 1403–1415,
https://doi.org/10.1002/esp.4321, 2018.
May, C. L.: Debris flows through different forest age classes in the central
Oregon Coast Range, J. Am. Water Resour. Assoc., 38, 1097–1113., 2002.
McClung, D. and Schaerer, P.: The avalanche handbook, third edn., edited by: Ummel Hoster, C., in: The mountaineers books, Seattle, WA,
ISBN 0-89886-809-2, available at:
https://books.google.it/books?hl=it&lr=&id=0Bpscs7Gqb8C&oi=fnd&pg=PA6&dq=The+avalanche+handbook&ots=vXt8PraiDb&sig=5rP0r0NvfZK8-IeKckmYAgrkLt8
(last access: 21 September 2020), 2006.
McClung, D. M. M.: Characteristics of terrain, snow supply and forest cover
for avalanche initiation caused by logging, Ann. Glaciol., 32, 223–229, 2001.
McKean, J. and Roering, J.: Objective landslide detection and surface
morphology mapping using high-resolution airborne laser altimetry,
Geomorphology, 57, 331–351, https://doi.org/10.1016/S0169-555X(03)00164-8, 2004.
Mergili, M., Fischer, J.-T., Krenn, J., and Pudasaini, S. P.: r.avaflow v1, an advanced open-source computational framework for the propagation and interaction of two-phase mass flows, Geosci. Model Dev., 10, 553–569, https://doi.org/10.5194/gmd-10-553-2017, 2017.
Michelini, T.: Analisi Sperimentale Delle Scabrezze Di Superficie E Di Fondo
Per La Modellazione Dinamica Dei Flussi Torrentizi E Della Caduta Massi, available at:
http://paduaresearch.cab.unipd.it/9407/1/Tesi_Tamara_Michelini.pdf (last access: 26 February 2021), 2016.
Michelini, T., Bettella, F., and D'Agostino, V.: Field investigations of the
interaction between debris flows and forest vegetation in two Alpine fans,
Geomorphology, 279, 150–164, https://doi.org/10.1016/j.geomorph.2016.09.029, 2017.
Middleton, M., Nevalainen, P., Hyvönen, E., Heikkonen, J., and Sutinen, R.: Pattern recognition of LiDAR data and sediment anisotropy advocate a polygenetic subglacial mass-flow origin for the Kemijärvi hummocky moraine field in northern Finland, Geomorphology, 362, 107212, https://doi.org/10.1016/j.geomorph.2020.107212, 2020.
Mina, M., Bugmann, H., Cordonnier, T., Irauschek, F., Klopcic, M., Pardos,
M., and Cailleret, M.: Future ecosystem services from European mountain
forests under climate change, J. Appl. Ecol., 54, 389–401,
https://doi.org/10.1111/1365-2664.12772, 2017.
Mitasova, H.: Cartographic aspects of computer surface modelling, PhD thesis, Slovak
Technical University, Bratislava, 1985.
Myers-Smith, I. H., Elmendorf, S. C., Beck, P. S. A., Wilmking, M.,
Hallinger, M., Blok, D., Tape, K. D., Rayback, S. A., Macias-Fauria, M.,
Forbes, B. C., Speed, J. D. M., Boulanger-Lapointe, N., Rixen, C.,
Lévesque, E., Schmidt, N. M., Baittinger, C., Trant, A. J., Hermanutz,
L., Collier, L. S., Dawes, M. A., Lantz, T. C., Weijers, S., JØrgensen,
R. H., Buchwal, A., Buras, A., Naito, A. T., Ravolainen, V.,
Schaepman-Strub, G., Wheeler, J. A., Wipf, S., Guay, K. C., Hik, D. S., and
Vellend, M.: Climate sensitivity of shrub growth across the tundra biome,
Nat. Clim. Change., 5, 887–891, https://doi.org/10.1038/nclimate2697, 2015.
Nel, J. L., Le Maitre, D. C., Nel, D. C., Reyers, B., Archibald, S., van
Wilgen, B. W., Forsyth, G. G., Theron, A. K., O'Farrell, P. J., Kahinda,
J.-M. M., Engelbrecht, F. A., Kapangaziwiri, E., van Niekerk, L., and
Barwell, L.: Natural Hazards in a Changing World: A Case for Ecosystem-Based
Management, edited by: Magar, V., PLoS One, 9, e95942,
https://doi.org/10.1371/journal.pone.0095942, 2014.
Nguyen, H. T. and Fenton J. D.: Identification of roughness for flood routing in compound channels, Proc.
31st Congress, Int. Assoc. Hydraulic Engng and Res., Seoul, Korea, 11–16 September 2005, 2005.
O'Brien, J. S., Julien, P. Y., and Fullerton, W. T.: Two-Dimensional Water
Flood and Mudflow Simulation, J. Hydraul. Eng., 119, 244–261,
https://doi.org/10.1061/(asce)0733-9429(1993)119:2(244), 1993.
Palomo, I.: Climate change impacts on ecosystem services in high mountain
areas: A literature review, Mt. Res. Dev., 37, 179–187,
https://doi.org/10.1659/MRD-JOURNAL-D-16-00110.1, 2017.
Pastore, M.: Overlapping: a R package for estimating overlapping in
empirical distributions, J. Open Source Softw., 3, 1023,
https://doi.org/10.21105/joss.01023, 2018.
Pastore, M. and Calcagnì, A.: Measuring distribution similarities
between samples: A distribution-free overlapping index, Front. Psychol.,
10, 1–8, https://doi.org/10.3389/fpsyg.2019.01089, 2019.
Pfeiffer, T. J. and Bowen, T. D.: Computer simulation of rockfalls, Bull.-Assoc. Eng. Geol., 26, 135–146, https://doi.org/10.2113/gseegeosci.xxvi.1.135, 1989.
Philip, G. M. and Watson, D. F.: A method for assessing local variation
among scattered measurements, Math. Geol., 18, 759–764,
https://doi.org/10.1007/BF00899742, 1986.
Pincus, H. J.: Some vector and arithmetic operations on two-dimensional
orientation variates, with applications to geological data, J. Geol., 64,
553–556, https://doi.org/10.1086/626391, 1956.
Pudasaini, S. P.: A general two-phase debris flow model, J. Geophys. Res.-Earth Surf., 117, 1–28, https://doi.org/10.1029/2011JF002186, 2012.
Pudasaini, S. P. and Mergili, M.: A Multi-Phase Mass Flow Model, J. Geophys.
Res.-Earth Surf., 124, 1–23, https://doi.org/10.1029/2019jf005204, 2019.
R Core Team: R: A language and environment for statistical computing, R
Found. Stat. Comput., available at: http://www.r-project.org
(last access: 28 January), 2021.
Riley, S.: Index that quantifies topographic heterogeneity, Intermt. J.
Sci., 5, 23–27, 1999.
Riley, S. J., DeGloria, S. D., and Elliot, R.: A terrain ruggedness index
that quantifies topographic heterogeneity, Intermt. J. Sci., 5,
23–27, 1999.
Ringenbach, A., Caviezel, A., Lu, G., Christen, M., Bebi, P., and Bartelt,
P.: Rockfall experiments in forests: Influence of rock-shape and deadwood,
in Interpraevent, in: 14th Congress INTERPRAEVENT,
Bergen, Norway, 31 May to 2 June 2021, 2021.
Rosatti, G. and Begnudelli, L.: Two-dimensional simulation of debris flows over mobile bed: Enhancing the TRENT2D model by using a well-balanced Generalized Roe-type solver, Comput. Fluids, 71, 179–195, https://doi.org/10.1016/j.compfluid.2012.10.006, 2013.
Roy, S. G., Koons, P. O., Osti, B., Upton, P., and Tucker, G. E.: Multi-scale characterization of topographic anisotropy, Comput. Geosci., 90, 102–116, https://doi.org/10.1016/j.cageo.2015.09.023, 2016.
Sappington, J. M., Longshore, K. M., and Thompson, D. B.: Quantifying
landscape ruggedness for animal habitat analysis: a case study using bighorn
sheep in the Mojave Desert, J. Wildlife Manage., 71, 1419–1426,
https://doi.org/10.2193/2005-723, 2007.
Schneebeli, M. and Bebi, P.: HYDROLOGY | Snow and Avalanche Control,
in: Encyclopedia of Forest Sciences, pp. 397–402, https://doi.org/10.1016/B0-12-145160-7/00271-4, 2004.
Schumann, G., Matgen, P., Hoffmann, L., Hostache, R., Pappenberger, F., and
Pfister, L.: Deriving distributed roughness values from satellite radar data
for flood inundation modelling, J. Hydrol., 344, 96–111,
https://doi.org/10.1016/j.jhydrol.2007.06.024, 2007.
Schweizer, J., Jamieson, J. B. and Schneebeli, M.: Snow avalanche formation,
Rev. Geophys., 41, 1016, https://doi.org/10.1029/2002RG000123, 2003.
Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M.,
Vacchiano, G., Wild, J., Ascoli, D., Petr, M., Honkaniemi, J., Lexer, M. J.,
Trotsiuk, V., Mairota, P., Svoboda, M., Fabrika, M., Nagel, T. A., and O
Reyer, C. P.: Forest disturbances under climate change, Nat. Clim. Change,
7, 395–402, https://doi.org/10.1038/NCLIMATE3303, 2017.
Shepard, M. K., Campbell, B. A., Bulmer, M. H., Farr, T. G., Gaddis, L. R.,
and Plaut, J. J.: The roughness of natural terrain: A planetary and remote
sensing perspective, J. Geophys. Res., 106, 32777–32795,
https://doi.org/10.1029/2000JE001429, 2001.
Smith, M. W.: Roughness in the Earth Sciences, Earth-Science Rev., 136,
202–225, https://doi.org/10.1016/j.earscirev.2014.05.016, 2014.
Sovilla, B., Sonatore, I., Bühler, Y., and Margreth, S.: Wet-snow avalanche interaction with a deflecting dam: field observations and numerical simulations in a case study, Nat. Hazards Earth Syst. Sci., 12, 1407–1423, https://doi.org/10.5194/nhess-12-1407-2012, 2012.
Stambaugh, M. C. and Guyette, R. P.: Predicting spatio-temporal variability
in fire return intervals using a topographic roughness index, Forest. Ecol.
Manag., 254, 463–473, https://doi.org/10.1016/j.foreco.2007.08.029, 2008.
swisstopo: swissALTI3D – Das hoch aufgelöste Terrainmodell der Schweiz,
Swiss Federal Office of Topography, Bern, Switzerland, 2018.
swisstopo: SWISSIMAGE – Das digitale Orthofotomosaik der Schweiz, Swiss
Federal Office of Topography, Bern, Switzerland, 2021.
Takahashi, T.: Initiation and flow of various types of debris-flow, in:
Debris-flow Hazards Mitigation: Mechanics, Prediction, and Assessment, Proceedings 2nd International Debris-flow hazards mitigation Conference, Taipei, Taiwan, 16–18 August 2000, 15–25, 2000.
Tasser, E. and Tappeiner, U.: Impact of land use changes on mountain
vegetation, Appl. Veg. Sci., 5, 173–184,
https://doi.org/10.1111/j.1654-109X.2002.tb00547.x, 2002.
Teich, M., Marty, C., Gollut, C., Grêt-Regamey, A., and Bebi, P.: Snow
and weather conditions associated with avalanche releases in forests: Rare
situations with decreasing trends during the last 41 years, Cold Reg. Sci.
Technol., 83, 77–88, https://doi.org/10.1016/j.coldregions.2012.06.007, 2012a.
Teich, M., Bartelt, P., Grět-Regamey, A., and Bebi, P.: Snow avalanches
in forested terrain: Influence of forest parameters, topography, and
avalanche characteristics on runout distance, Arct, Antarct. Alp. Res.,
44, 509–519, https://doi.org/10.1657/1938-4246-44.4.509, 2012b.
Teich, M., Techel, F., Caviezel, P., and Bebi, P.: Forecasting forest
avalanches: A review of winter 2011/12, Int. Snow Sci. Work., Grenoble Chamonix Mont Blanc, 7–11 October 2013, 324–330, 2013.
Teich, M., Fischer, J.-T., Feistl, T., Bebi, P., Christen, M., and Grêt-Regamey, A.: Computational snow avalanche simulation in forested terrain, Nat. Hazards Earth Syst. Sci., 14, 2233–2248, https://doi.org/10.5194/nhess-14-2233-2014, 2014.
Trevisani, S. and Cavalli, M.: Topography-based flow-directional roughness: potential and challenges, Earth Surf. Dynam., 4, 343–358, https://doi.org/10.5194/esurf-4-343-2016, 2016.
Trevisani, S. and Rocca, M.: MAD: Robust image texture analysis for applications in high resolutiongeomorphometry, Comput. Geosci., 81, 78–92, https://doi.org/10.1016/j.cageo.2015.04.003, 2015.
Veitinger, J. and Sovilla, B.: Linking snow depth to avalanche release area size: measurements from the Vallée de la Sionne field site, Nat. Hazards Earth Syst. Sci., 16, 1953–1965, https://doi.org/10.5194/nhess-16-1953-2016, 2016.
Veitinger, J., Sovilla, B., and Purves, R. S.: Influence of snow depth distribution on surface roughness in alpine terrain: a multi-scale approach, The Cryosphere, 8, 547–569, https://doi.org/10.5194/tc-8-547-2014, 2014.
Vetter, M., Höfle, B., Hollaus, M., Gschöpf, C., Mandlburger, G., Pfeifer, N., and Wagner, W.: Vertical vegetation structure analysis and hydraulic roughness determination using dense ALS point cloud data – a voxel based approach, in: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-5/W12, 2011ISPRS Calgary 2011 Workshop, Calgary, Canada, 29–31 August 2011, 265–270, 2011.
Viero, D. P. and Valipour, M.: Modeling anisotropy in free-surface overland and shallow inundation flows, Adv. Water Resour., 104, 1–14, https://doi.org/10.1016/j.advwatres.2017.03.007, 2017.
Viglietti, D., Letey, S., Motta, R., Maggioni, M., and Freppaz, M.: Snow
avalanche release in forest ecosystems: A case study in the Aosta Valley
Region (NW-Italy), Cold Reg. Sci. Technol., 64, 167–173,
https://doi.org/10.1016/j.coldregions.2010.08.007, 2010.
Waldron, K., Ruel, J. C., and Gauthier, S.: Forest structural attributes
after windthrow and consequences of salvage logging, Forest. Ecol. Manag.,
289, 28–37, https://doi.org/10.1016/j.foreco.2012.10.006, 2013.
Wang, I. T. and Lee, C. Y.: Influence of slope shape and surface roughness
on the moving paths of a single rockfall, World Acad. Sci. Eng. Technol.,
65, 1021–1027, https://doi.org/10.5281/zenodo.1059436, 2010.
Wohlgemuth, T., Schwitter, R., Bebi, P., Sutter, F., and Brang, P.:
Post-windthrow management in protection forests of the Swiss Alps, Eur. J.
Forest. Res., 136, 1029–1040, https://doi.org/10.1007/s10342-017-1031-x, 2017.
Wu, J., Yang, Q., and Li, Y.: Partitioning of terrain features based on
roughness, Remote Sens., 10, 1–21, https://doi.org/10.3390/rs10121985, 2018.
Yang, P., Ames, D. P., Fonseca, A., Anderson, D., Shrestha, R., Glenn, N. F.,
and Cao, Y.: What is the effect of LiDAR-derived DEM resolution on
large-scale watershed model results?, Environ. Model. Softw., 58, 48–57,
https://doi.org/10.1016/j.envsoft.2014.04.005, 2014.
Short summary
Surface roughness plays a great role in natural hazard processes but is not always well implemented in natural hazard modelling. The results of our study show how surface roughness can be useful in representing vegetation and ground structures, which are currently underrated. By including surface roughness in natural hazard modelling, we could better illustrate the processes and thus improve hazard mapping, which is crucial for infrastructure and settlement planning in mountainous areas.
Surface roughness plays a great role in natural hazard processes but is not always well...
Altmetrics
Final-revised paper
Preprint