Articles | Volume 7, issue 4
https://doi.org/10.5194/esurf-7-989-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-7-989-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
25 Oct 2019
Research article | Highlight paper |
| 25 Oct 2019
| 25 Oct 2019
Seismic location and tracking of snow avalanches and slush flows on Mt. Fuji, Japan
Cristina Pérez-Guillén
CORRESPONDING AUTHOR
Graduate School of Environmental Studies, Nagoya University,
Nagoya, Aichi, Japan
RISKNAT Natural Hazards Research Group, Geomodels Research Institute, Faculty of Earth Sciences, University of Barcelona, Barcelona, Spain
Kae Tsunematsu
Mount Fuji Research Institute, Yamanashi Prefectural Government, Fujiyoshida, Yamanashi, Japan
Faculty of Science, Yamagata University, Yamagata, Japan
Kouichi Nishimura
Graduate School of Environmental Studies, Nagoya University,
Nagoya, Aichi, Japan
Dieter Issler
Norwegian Geotechnical Institute, Oslo, Norway
Related authors
Cristina Pérez-Guillén, Frank Techel, Michele Volpi, and Alec van Herwijnen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2374, https://doi.org/10.5194/egusphere-2024-2374, 2024
Short summary
Short summary
This study assesses the performance and explainability of a random forest classifier for predicting dry-snow avalanche danger levels during initial live-testing. The model achieved ∼70 % agreement with human forecasts, performing equally well in nowcast and forecast modes, while capturing the temporal dynamics of avalanche forecasting. The explainability approach enhances the transparency of the model's decision-making process, providing a valuable tool for operational avalanche forecasting.
Andri Simeon, Cristina Pérez-Guillén, Michele Volpi, Christine Seupel, and Alec van Herwijnen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-76, https://doi.org/10.5194/gmd-2024-76, 2024
Revised manuscript under review for GMD
Short summary
Short summary
Avalanche seismic detection systems are key for forecasting, but distinguishing avalanches from other seismic sources remains challenging. We propose novel autoencoder models to automatically extract features and compare them with standard seismic attributes. These features are then used to classify avalanches and noise events. The autoencoder feature classifiers have the highest sensitivity to detect avalanches, while the standard seismic classifier performs better overall.
Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, https://doi.org/10.5194/nhess-22-2031-2022, 2022
Short summary
Short summary
A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
Frank Techel, Stephanie Mayer, Cristina Pérez-Guillén, Günter Schmudlach, and Kurt Winkler
Nat. Hazards Earth Syst. Sci., 22, 1911–1930, https://doi.org/10.5194/nhess-22-1911-2022, https://doi.org/10.5194/nhess-22-1911-2022, 2022
Short summary
Short summary
Can the resolution of forecasts of avalanche danger be increased by using a combination of absolute and comparative judgments? Using 5 years of Swiss avalanche forecasts, we show that, on average, sub-levels assigned to a danger level reflect the expected increase in the number of locations with poor snow stability and in the number and size of avalanches with increasing forecast sub-level.
Kouichi Nishimura, Masaki Nemoto, Yoichi Ito, Satoru Omiya, Kou Shimoyama, and Hirofumi Niiya
The Cryosphere, 18, 4775–4786, https://doi.org/10.5194/tc-18-4775-2024, https://doi.org/10.5194/tc-18-4775-2024, 2024
Short summary
Short summary
It is crucial to consider organized structures such as turbulence sweeps and ejections when discussing the onset and development of snow transport. This study aims to systematically measure blowing and drifting snow to investigate their spatiotemporal structures. To achieve this goal, we have deployed 15 snow particle counters (SPCs) in designated test areas and are conducting measurements using an equal number of ultrasonic anemometers, providing high-temporal-resolution data.
Cristina Pérez-Guillén, Frank Techel, Michele Volpi, and Alec van Herwijnen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2374, https://doi.org/10.5194/egusphere-2024-2374, 2024
Short summary
Short summary
This study assesses the performance and explainability of a random forest classifier for predicting dry-snow avalanche danger levels during initial live-testing. The model achieved ∼70 % agreement with human forecasts, performing equally well in nowcast and forecast modes, while capturing the temporal dynamics of avalanche forecasting. The explainability approach enhances the transparency of the model's decision-making process, providing a valuable tool for operational avalanche forecasting.
Andri Simeon, Cristina Pérez-Guillén, Michele Volpi, Christine Seupel, and Alec van Herwijnen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-76, https://doi.org/10.5194/gmd-2024-76, 2024
Revised manuscript under review for GMD
Short summary
Short summary
Avalanche seismic detection systems are key for forecasting, but distinguishing avalanches from other seismic sources remains challenging. We propose novel autoencoder models to automatically extract features and compare them with standard seismic attributes. These features are then used to classify avalanches and noise events. The autoencoder feature classifiers have the highest sensitivity to detect avalanches, while the standard seismic classifier performs better overall.
Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, https://doi.org/10.5194/nhess-22-2031-2022, 2022
Short summary
Short summary
A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
Frank Techel, Stephanie Mayer, Cristina Pérez-Guillén, Günter Schmudlach, and Kurt Winkler
Nat. Hazards Earth Syst. Sci., 22, 1911–1930, https://doi.org/10.5194/nhess-22-1911-2022, https://doi.org/10.5194/nhess-22-1911-2022, 2022
Short summary
Short summary
Can the resolution of forecasts of avalanche danger be increased by using a combination of absolute and comparative judgments? Using 5 years of Swiss avalanche forecasts, we show that, on average, sub-levels assigned to a danger level reflect the expected increase in the number of locations with poor snow stability and in the number and size of avalanches with increasing forecast sub-level.
Markus M. Frey, Sarah J. Norris, Ian M. Brooks, Philip S. Anderson, Kouichi Nishimura, Xin Yang, Anna E. Jones, Michelle G. Nerentorp Mastromonaco, David H. Jones, and Eric W. Wolff
Atmos. Chem. Phys., 20, 2549–2578, https://doi.org/10.5194/acp-20-2549-2020, https://doi.org/10.5194/acp-20-2549-2020, 2020
Short summary
Short summary
A winter sea ice expedition to Antarctica provided the first direct observations of sea salt aerosol (SSA) production during snow storms above sea ice, thereby validating a model hypothesis to account for winter time SSA maxima in Antarctica not explained otherwise. Defining SSA sources is important given the critical roles that aerosol plays for climate, for air quality and as a potential ice core proxy for sea ice conditions in the past.
Xin Yang, Markus M. Frey, Rachael H. Rhodes, Sarah J. Norris, Ian M. Brooks, Philip S. Anderson, Kouichi Nishimura, Anna E. Jones, and Eric W. Wolff
Atmos. Chem. Phys., 19, 8407–8424, https://doi.org/10.5194/acp-19-8407-2019, https://doi.org/10.5194/acp-19-8407-2019, 2019
Short summary
Short summary
This is a comprehensive model–data comparison aiming to evaluate the proposed mechanism of sea salt aerosol (SSA) production from blowing snow on sea ice. Some key parameters such as snow salinity and blowing-snow size distribution were constrained by data collected in the Weddell Sea. The good agreement between modelled SSA and the cruise data strongly indicates that sea ice surface is a large SSA source in polar regions, a process which has not been considered in current climate models.
Gilbert Guyomarc'h, Hervé Bellot, Vincent Vionnet, Florence Naaim-Bouvet, Yannick Déliot, Firmin Fontaine, Philippe Puglièse, Kouichi Nishimura, Yves Durand, and Mohamed Naaim
Earth Syst. Sci. Data, 11, 57–69, https://doi.org/10.5194/essd-11-57-2019, https://doi.org/10.5194/essd-11-57-2019, 2019
Short summary
Short summary
The paper introduces a meteorological and blowing snow data set from Col du Lac Blanc (2720 m a.s.l., French Alps) allowing physical parameterizations and numerical models of blowing snow to be developed and evaluated. In situ winter season data consist of wind, snow depth, air temperature measurements and a database of blowing snow occurrence (2000–2016) complemented by measurements of blowing snow fluxes (2010–2016). Atmospheric data from a meteorological reanalysis and a DEM are also provided.
Koji Fujita, Hiroshi Inoue, Takeki Izumi, Satoru Yamaguchi, Ayako Sadakane, Sojiro Sunako, Kouichi Nishimura, Walter W. Immerzeel, Joseph M. Shea, Rijan B. Kayastha, Takanobu Sawagaki, David F. Breashears, Hiroshi Yagi, and Akiko Sakai
Nat. Hazards Earth Syst. Sci., 17, 749–764, https://doi.org/10.5194/nhess-17-749-2017, https://doi.org/10.5194/nhess-17-749-2017, 2017
Short summary
Short summary
We create multiple DEMs from photographs taken by helicopter and UAV and reveal the deposit volumes over the Langtang village, which was destroyed by avalanches induced by the Gorkha earthquake. Estimated snow depth in the source area is consistent with anomalously large snow depths observed at a neighboring glacier. Comparing with a long-term observational data, we conclude that this anomalous winter snow amplified the disaster induced by the 2015 Gorkha earthquake in Nepal.
J. T. M. Lenaerts, C. J. P. P. Smeets, K. Nishimura, M. Eijkelboom, W. Boot, M. R. van den Broeke, and W. J. van de Berg
The Cryosphere, 8, 801–814, https://doi.org/10.5194/tc-8-801-2014, https://doi.org/10.5194/tc-8-801-2014, 2014
Related subject area
Physical: Geophysics
3D shear wave velocity imaging of the subsurface structure of granite rocks in the arid climate of Pan de Azúcar, Chile, revealed by Bayesian inversion of HVSR curves
Machine learning prediction of the mass and the velocity of controlled single-block rockfalls from the seismic waves they generate
Subaerial and subglacial seismic characteristics of the largest measured jökulhlaup from the eastern Skaftá cauldron, Iceland
Short communication: Potential of Sentinel-1 interferometric synthetic aperture radar (InSAR) and offset tracking in monitoring post-cyclonic landslide activities on Réunion
Automated classification of seismic signals recorded on the Åknes rock slope, Western Norway, using a convolutional neural network
Short communication: A tool for determining multiscale bedform characteristics from bed elevation data
Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series
Vibration of natural rock arches and towers excited by helicopter-sourced infrasound
An update on techniques to assess normal-mode behavior of rock arches by ambient vibrations
Precise water level measurements using low-cost GNSS antenna arrays
Locating rock slope failures along highways and understanding their physical processes using seismic signals
Reconstructing the dynamics of the highly similar May 2016 and June 2019 Iliamna Volcano (Alaska) ice–rock avalanches from seismoacoustic data
Seismo-acoustic energy partitioning of a powder snow avalanche
Comment on “Dynamics of the Askja caldera July 2014 landslide, Iceland, from seismic signal analysis: precursor, motion and aftermath” by Schöpa et al. (2018)
Acoustic wave propagation in rivers: an experimental study
Automatic detection of avalanches combining array classification and localization
Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: a case study in Svalbard
Short Communication: Monitoring rockfalls with the Raspberry Shake
Towards a standard typology of endogenous landslide seismic sources
Seismic detection of rockslides at regional scale: examples from the Eastern Alps and feasibility of kurtosis-based event location
Characterizing the complexity of microseismic signals at slow-moving clay-rich debris slides: the Super-Sauze (southeastern France) and Pechgraben (Upper Austria) case studies
Glacial isostatic adjustment modelling: historical perspectives, recent advances, and future directions
Single-block rockfall dynamics inferred from seismic signal analysis
Rahmantara Trichandi, Klaus Bauer, Trond Ryberg, Benjamin Heit, Jaime Araya Vargas, Friedhelm von Blanckenburg, and Charlotte M. Krawczyk
Earth Surf. Dynam., 12, 747–763, https://doi.org/10.5194/esurf-12-747-2024, https://doi.org/10.5194/esurf-12-747-2024, 2024
Short summary
Short summary
This study investigates subsurface weathering zones, revealing their structure through shear wave velocity variations. The research focuses on the arid climate of Pan de Azúcar National Park, Chile, using seismic ambient noise recordings to construct pseudo-3D models. The resulting models show the subsurface structure, including granite gradients and mafic dike intrusions. Comparison with other sites emphasizes the intricate relationship between climate, geology, and weathering depth.
Clément Hibert, François Noël, David Toe, Miloud Talib, Mathilde Desrues, Emmanuel Wyser, Ombeline Brenguier, Franck Bourrier, Renaud Toussaint, Jean-Philippe Malet, and Michel Jaboyedoff
Earth Surf. Dynam., 12, 641–656, https://doi.org/10.5194/esurf-12-641-2024, https://doi.org/10.5194/esurf-12-641-2024, 2024
Short summary
Short summary
Natural disasters such as landslides and rockfalls are mostly difficult to study because of the impossibility of making in situ measurements due to their destructive nature and spontaneous occurrence. Seismology is able to record the occurrence of such events from a distance and in real time. In this study, we show that, by using a machine learning approach, the mass and velocity of rockfalls can be estimated from the seismic signal they generate.
Eva P. S. Eibl, Kristin S. Vogfjörd, Benedikt G. Ófeigsson, Matthew J. Roberts, Christopher J. Bean, Morgan T. Jones, Bergur H. Bergsson, Sebastian Heimann, and Thoralf Dietrich
Earth Surf. Dynam., 11, 933–959, https://doi.org/10.5194/esurf-11-933-2023, https://doi.org/10.5194/esurf-11-933-2023, 2023
Short summary
Short summary
Floods draining beneath an ice cap are hazardous events that generate six different short- or long-lasting types of seismic signals. We use these signals to see the collapse of the ice once the water has left the lake, the propagation of the flood front to the terminus, hydrothermal explosions and boiling in the bedrock beneath the drained lake, and increased water flow at rapids in the glacial river. We can thus track the flood and assess the associated hazards better in future flooding events.
Marcello de Michele, Daniel Raucoules, Claire Rault, Bertrand Aunay, and Michael Foumelis
Earth Surf. Dynam., 11, 451–460, https://doi.org/10.5194/esurf-11-451-2023, https://doi.org/10.5194/esurf-11-451-2023, 2023
Short summary
Short summary
Landslide processes are causes of major concern to population and infrastructures on Réunion. In this study, we used data from the Copernicus Sentinel-1 satellite to map ground motion in Cirque de Salazie. We concentrate on the cyclonic season 2017–2018. Our results show ground motion in the Hell-Bourg, Ilet à Vidot,
Grand-Ilet, Camp Pierrot, and Le Bélier landslides. Moreover, we show an unknown pattern of ground motion situated in a non-instrumented, uninhabited area on the ground.
Nadège Langet and Fred Marcus John Silverberg
Earth Surf. Dynam., 11, 89–115, https://doi.org/10.5194/esurf-11-89-2023, https://doi.org/10.5194/esurf-11-89-2023, 2023
Short summary
Short summary
Microseismic events recorded on the Åknes rock slope in Norway during the past 15 years are automatically divided into eight classes. The results are analysed and compared to meteorological data, showing a strong increase in the microseismic activity in spring mainly due to freezing and thawing processes.
Judith Y. Zomer, Suleyman Naqshband, and Antonius J. F. Hoitink
Earth Surf. Dynam., 10, 865–874, https://doi.org/10.5194/esurf-10-865-2022, https://doi.org/10.5194/esurf-10-865-2022, 2022
Short summary
Short summary
Riverbeds are often composed of different scales of dunes, whose sizes and shapes are highly variable over time and space. Characterization of these dunes is important in many research studies focused on fluvial processes. A tool is presented here that aims to identify different scales of dunes from riverbed elevation maps. A first step is to separate two scales of bedforms without smoothing steep slopes of the larger dunes. In a second step, dunes are identified and properties are computed.
Carlotta Brunetti, John Lamb, Stijn Wielandt, Sebastian Uhlemann, Ian Shirley, Patrick McClure, and Baptiste Dafflon
Earth Surf. Dynam., 10, 687–704, https://doi.org/10.5194/esurf-10-687-2022, https://doi.org/10.5194/esurf-10-687-2022, 2022
Short summary
Short summary
This paper proposes a method to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution from soil temperature time series. We validate and apply this method to synthetic and field case studies. The improved quantification of soil thermal properties is a cornerstone for advancing the indirect estimation of the fraction of soil components needed to predict subsurface storage and fluxes of water, carbon, and nutrients.
Riley Finnegan, Jeffrey R. Moore, and Paul R. Geimer
Earth Surf. Dynam., 9, 1459–1479, https://doi.org/10.5194/esurf-9-1459-2021, https://doi.org/10.5194/esurf-9-1459-2021, 2021
Short summary
Short summary
We performed controlled helicopter flights near seven rock arches and towers in Utah, USA, and recorded how their natural vibrations changed as the helicopter performed different maneuvers. We found that arches and towers vibrate up to 1000 times faster during these flights compared to time periods just before the helicopter's approach. Our study provides data that can be used to predict long-term damage to culturally significant rock features from sustained helicopter flights over time.
Mauro Häusler, Paul Richmond Geimer, Riley Finnegan, Donat Fäh, and Jeffrey Ralston Moore
Earth Surf. Dynam., 9, 1441–1457, https://doi.org/10.5194/esurf-9-1441-2021, https://doi.org/10.5194/esurf-9-1441-2021, 2021
Short summary
Short summary
Natural rock arches are valued landmarks worldwide. As ongoing erosion can lead to rockfall and collapse, it is important to monitor the structural integrity of these landforms. One suitable technique involves measurements of resonance, produced when mainly natural sources, such as wind, vibrate the spans. Here we explore the use of two advanced processing techniques to accurately measure the resonant frequencies, damping ratios, and deflection patterns of several rock arches in Utah, USA.
David J. Purnell, Natalya Gomez, William Minarik, David Porter, and Gregory Langston
Earth Surf. Dynam., 9, 673–685, https://doi.org/10.5194/esurf-9-673-2021, https://doi.org/10.5194/esurf-9-673-2021, 2021
Short summary
Short summary
We present a new technique for precisely monitoring water levels (e.g. sea level, rivers or lakes) using low-cost equipment (approximately USD 100–200) that is simple to build and install. The technique builds on previous work using antennas that were designed for navigation purposes. Multiple antennas in the same location are used to obtain more precise measurements than those obtained when using a single antenna. Software for analysis is provided with the article.
Jui-Ming Chang, Wei-An Chao, Hongey Chen, Yu-Ting Kuo, and Che-Ming Yang
Earth Surf. Dynam., 9, 505–517, https://doi.org/10.5194/esurf-9-505-2021, https://doi.org/10.5194/esurf-9-505-2021, 2021
Short summary
Short summary
Seismic techniques applied in rock slope failure research do not provide rapid notifications, as for earthquakes, due to the lack of connections between seismic signals and events. We studied 10 known events in Taiwan and developed a GeoLoc scheme to locate rock slope failures, estimate the event volume, and understand their physical process using available videos. With real-time seismic data transmission, a rapid report can be created for the public within several minutes of the event.
Liam Toney, David Fee, Kate E. Allstadt, Matthew M. Haney, and Robin S. Matoza
Earth Surf. Dynam., 9, 271–293, https://doi.org/10.5194/esurf-9-271-2021, https://doi.org/10.5194/esurf-9-271-2021, 2021
Short summary
Short summary
Large avalanches composed of ice and rock are a serious hazard to mountain communities and backcountry travellers. These processes shake the Earth and disturb the atmosphere, generating seismic waves and sound waves which can travel for hundreds of kilometers. In this study, we use the seismic waves and sound waves produced by two massive avalanches on a volcano in Alaska to reconstruct how the avalanches failed. Our method may assist with rapid emergency response to these global hazards.
Emanuele Marchetti, Alec van Herwijnen, Marc Christen, Maria Cristina Silengo, and Giulia Barfucci
Earth Surf. Dynam., 8, 399–411, https://doi.org/10.5194/esurf-8-399-2020, https://doi.org/10.5194/esurf-8-399-2020, 2020
Short summary
Short summary
We present infrasonic and seismic array data of a powder snow avalanche, that was released on 5 February 2016, in the Dischma valley nearby Davos, Switzerland. Combining information derived from both arrays, we show how infrasound and seismic energy are radiated from different sources acting along the path. Moreover, infrasound transmits to the ground and affects the recorded seismic signal. Results highlight the benefits of combined seismo-acoustic array analyses for monitoring and research.
Tómas Jóhannesson, Jón Kristinn Helgason, and Sigríður Sif Gylfadóttir
Earth Surf. Dynam., 8, 173–175, https://doi.org/10.5194/esurf-8-173-2020, https://doi.org/10.5194/esurf-8-173-2020, 2020
Thomas Geay, Ludovic Michel, Sébastien Zanker, and James Robert Rigby
Earth Surf. Dynam., 7, 537–548, https://doi.org/10.5194/esurf-7-537-2019, https://doi.org/10.5194/esurf-7-537-2019, 2019
Short summary
Short summary
This research has been conducted to develop the use of passive acoustic monitoring (PAM) for bedload monitoring in rivers. Monitored bedload acoustic signals depend on bedload characteristics (e.g., grain size distribution, fluxes) but are also affected by the environment in which the acoustic waves are propagated. This study focuses on the determination of propagation effects in rivers. An experimental approach has been conducted in several streams to estimate acoustic propagation laws.
Matthias Heck, Alec van Herwijnen, Conny Hammer, Manuel Hobiger, Jürg Schweizer, and Donat Fäh
Earth Surf. Dynam., 7, 491–503, https://doi.org/10.5194/esurf-7-491-2019, https://doi.org/10.5194/esurf-7-491-2019, 2019
Short summary
Short summary
We used continuous seismic data from two small aperture geophone arrays deployed in the region above Davos in the eastern Swiss Alps to develop a machine learning workflow to automatically identify signals generated by snow avalanches. Our results suggest that the method presented could be used to identify major avalanche periods and highlight the importance of array processing techniques for the automatic classification of avalanches in seismic data.
Andreas Köhler and Christian Weidle
Earth Surf. Dynam., 7, 1–16, https://doi.org/10.5194/esurf-7-1-2019, https://doi.org/10.5194/esurf-7-1-2019, 2019
Short summary
Short summary
The uppermost part of permanently frozen ground can thaw during summer and refreeze during winter. We use a method based on naturally generated seismic waves to continuously monitor these changes close to the research settlement of Ny-Ålesund in Svalbard between April and August 2016. Our results reveal some potential pitfalls when interpreting temporal variations in the data. However, we show that a careful data analysis makes this method a very useful tool for long-term permafrost monitoring.
Andrea Manconi, Velio Coviello, Maud Galletti, and Reto Seifert
Earth Surf. Dynam., 6, 1219–1227, https://doi.org/10.5194/esurf-6-1219-2018, https://doi.org/10.5194/esurf-6-1219-2018, 2018
Short summary
Short summary
We evaluated the performance of the low-cost seismic Raspberry Shake (RS) sensors to identify and monitor rockfall activity in alpine environments. The sensors have been tested for a 1-year period in a high alpine environment, recording numerous rock failure events as well as local and distant earthquakes. This study demonstrates that the RS instruments provide a good option to build low seismic monitoring networks to monitor different kinds of geophysical phenomena.
Floriane Provost, Jean-Philippe Malet, Clément Hibert, Agnès Helmstetter, Mathilde Radiguet, David Amitrano, Nadège Langet, Eric Larose, Clàudia Abancó, Marcel Hürlimann, Thomas Lebourg, Clara Levy, Gaëlle Le Roy, Patrice Ulrich, Maurin Vidal, and Benjamin Vial
Earth Surf. Dynam., 6, 1059–1088, https://doi.org/10.5194/esurf-6-1059-2018, https://doi.org/10.5194/esurf-6-1059-2018, 2018
Short summary
Short summary
Seismic sources generated by the deformation of unstable slopes are diverse in terms of signal properties and mechanisms. Standardized catalogues of landslide endogenous seismicity can help understanding the physical processes controlling slope dynamics. We propose a generic typology of seismic sources based on the analysis of signals recorded at various instrumented slopes. We demonstrate that the seismic signals present similar features at different sites and discuss their mechanical sources.
Florian Fuchs, Wolfgang Lenhardt, Götz Bokelmann, and the AlpArray Working Group
Earth Surf. Dynam., 6, 955–970, https://doi.org/10.5194/esurf-6-955-2018, https://doi.org/10.5194/esurf-6-955-2018, 2018
Short summary
Short summary
The work demonstrates how seismic networks installed in the Alps can be used for country-wide real-time monitoring of rockslide activity. We suggest simple methods that allow us to detect, locate, and characterize rockslides using the seismic signals they generate. We developed an automatic procedure to locate rockslides with kilometer accuracy over hundreds of kilometers of distance. Our findings highlight how seismic networks can help us to understand the triggering of rockslides.
Naomi Vouillamoz, Sabrina Rothmund, and Manfred Joswig
Earth Surf. Dynam., 6, 525–550, https://doi.org/10.5194/esurf-6-525-2018, https://doi.org/10.5194/esurf-6-525-2018, 2018
Short summary
Short summary
Seismic monitoring of active landslides enables the detection of microseismic signals generated by slope activity. We propose a classification of
microseismic signals observed at two active clay-rich debris slides and a simple method to constrain their source origin and their size
based on their signal amplitudes. A better understanding of landslide-induced microseismicity is crucial for the development of early warning systems
based on landslide-induced microseismic signal precursors.
Pippa L. Whitehouse
Earth Surf. Dynam., 6, 401–429, https://doi.org/10.5194/esurf-6-401-2018, https://doi.org/10.5194/esurf-6-401-2018, 2018
Short summary
Short summary
This article is a contribution to a special issue on
Two centuries of modelling across scales. It describes the historical observations, evolving hypotheses, and early calculations that led to the development of the field of glacial isostatic sdjustment (GIA) modelling, which seeks to understand feedbacks between ice-sheet change, sea-level change, and solid Earth deformation. Recent and future advances are discussed. Future progress will likely involve an interdisciplinary approach.
Clément Hibert, Jean-Philippe Malet, Franck Bourrier, Floriane Provost, Frédéric Berger, Pierrick Bornemann, Pascal Tardif, and Eric Mermin
Earth Surf. Dynam., 5, 283–292, https://doi.org/10.5194/esurf-5-283-2017, https://doi.org/10.5194/esurf-5-283-2017, 2017
Cited articles
Aki, K. and Chouet, B.: Origin of coda waves: source, attenuation, and
scattering effects, J. Geophys. Res., 80, 3322–3342, https://doi.org/10.1029/JB080i023p03322, 1975. a
Almendros, J., Ibáñez, J. M., Alguacil, G., and Del Pezzo, E.: Array
analysis using circular-wave-front geometry: an application to locate the
nearby seismo-volcanic source, Geophys. J. Int., 136, 159–170,
https://doi.org/10.1046/j.1365-246X.1999.00699.x, 1999. a
Anma, S: Lahars and slush lahars on the slopes of Fuji volcano, in: Fuji Volcano, edited by: Aramaki, S., Fujii, T., Nakada, S., and Miyaji, N., Yamanashi Institute of Environmental Science, Fujiyoshida, 285–301, 2007 (in Japanese with English summary). a
Arattano, M. and Moia, F.: Monitoring the propagation of a debris flow along a torrent, Hydrolog. Sci. J., 44, 811–823, https://doi.org/10.1080/02626669909492275, 1999. a
Battaglia, J. and Aki, K.: Location of seismic events and eruptive fissures on the Piton de la Fournaise volcano using seismic amplitudes, J. Geophys. Res.-Solid Ea., 108, 2364, https://doi.org/10.1029/2002JB002193, 2003. a
Bessason, B., Eiríksson, G., Thórarinsson,Ó., Thórarinsson,
A., and Einarsson, S.: Automatic detection of avalanches and debris flows by
seismic methods, J. Glaciol., 53, 461–472, https://doi.org/10.3189/002214307783258468, 2007. a
Biescas, B., Dufour, F., Furdada, G., Khazaradze, G., and Suriñach, E.:
Frequency content evolution of snow avalanche seismic signals, Surv. Geophys., 24, 447–464, https://doi.org/10.1023/B:GEOP.0000006076.38174.31, 2003. a, b, c
Cole, S., Cronin, S., Sherburn, S., and Manville, V.: Seismic signals of
snow-slurry lahars in motion: 25 September 2007, Mt Ruapehu, New Zealand,
Geophys. Res. Lett., 36, L09405, https://doi.org/10.1029/2009GL038030, 2009. a
Coviello, V., Arattano, M., Comiti, F., Macconi, P., and Marchi, L.: Seismic
characterization of debris flows: insights into energy radiation and
implications for warning, J. Geophys. Res.-Ea. Surf., 124, 1440–1463, https://doi.org/10.1029/2018JF004683, 2019. a, b
Favreau, P., Mangeney, A., Lucas, A., Crosta, G., and Bouchut, F.: Numerical
modeling of landquakes, Geophys. Res. Lett., 37, 1–5,
https://doi.org/10.1029/2010GL043512, 2010. a
Gauer, P., Issler, D., Lied, K., Kristensen, K., Iwe, H., Lied, E., Rammer, L., and Schreiber, H.: On full-scale avalanche measurements at the Ryggfonn test site, Norway, Cold Reg. Sci. Technol., 49, 39–53,
https://doi.org/10.1016/j.coldregions.2006.09.010, 2007a. a, b
Gauer, P., Kern, M., Kristensen, K., Lied, K., Rammer, L., and Schreiber, H.:
On pulsed Doppler radar measurements of avalanches and their implication to
avalanche dynamics, Cold Reg. Sci. Technol., 50, 55–71,
https://doi.org/10.1016/j.coldregions.2007.03.009, 2007b. a
Guinau, M., Tapia, M., Pérez-Guillén, C., Suriñach, E., Roig, P.,
Khazaradze, G., Torné, M., Royán, M. J., and Echeverria, A.: Remote
sensing and seismic data integration for the characterization of a rock slide
and an artificially triggered rock fall, Eng. Geol., 257, 105113,
https://doi.org/10.1016/j.enggeo.2019.04.010, 2019. a
Hammer, C., Fäh, D., and Ohrnberger, M.: Automatic detection of wet-snow
avalanche seismic signals, Nat. Hazards, 86, 601–618, https://doi.org/10.1007/s11069-016-2707-0, 2017. a, b, c
Heck, M., Hammer, C., Van Herwijnen, A., Schweizer, J., and Fäh, D.:
Automatic detection of snow avalanches in continuous seismic data using
hidden Markov models, Nat. Hazards Earth Syst. Sci., 18, 383–396,
https://doi.org/10.5194/nhess-18-383-2018, 2018a. a, b, c
Heck, M., Hobiger, M., van Herwijnen, A., Schweizer, J., and Fäh, D.:
Localization of seismic events produced by avalanches using multiple signal
classification, Geophys. J. Int., 216, 201–217, https://doi.org/10.1093/gji/ggy394, 2018b. a, b
Heck, M., van Herwijnen, A., Hammer, C., Hobiger, M., Schweizer, J., and Fäh, D.: Automatic detection of avalanches combining array classification and localization, Earth Surf. Dynam., 7, 491–503, https://doi.org/10.5194/esurf-7-491-2019, 2019. a, b
Hibert, C., Mangeney, A., Grandjean, G., and Shapiro, N. M.: Slope
instabilities in Dolomieu crater, Réunion Island: From seismic signals
to rockfall characteristics, J. Geophys. Res., 116, F04032,
https://doi.org/10.1029/2011JF002038, 2011. a, b, c, d
Köhler, A., McElwaine, J., Sovilla, B., Ash, M., and Brennan, P.: The
dynamics of surges in the 3 February 2015 avalanches in Vallée de la
Sionne, J. Geophys. Res.-Ea. Surf., 121, 2192–2210, https://doi.org/10.1002/2016JF003887, 2016. a
Köhler, A., Fischer, J.-T., Scandroglio, R., Bavay, M., McElwaine, J., and Sovilla, B.: Cold-to-warm flow regime transition in snow avalanches, The
Cryosphere, 12, 3759–3774, https://doi.org/10.5194/tc-12-3759-2018, 2018a. a
Köhler, A., McElwaine, J., and Sovilla, B.: GEODAR Data and the flow
regimes of snow avalanches, J. Geophys. Res.-Ea. Surf., 123, 1272–1294, https://doi.org/10.1002/2017JF004375, 2018b. a
Kumagai, H., Nakano, M., Maeda, T., Yepes, H., Palacios, P., Ruiz, M., Arrais, S., Vaca, M., Molina, I., and Yamashima, T.: Broadband seismic monitoring of active volcanoes using deterministic and stochastic approaches, J. Geophys. Res.-Solid Ea., 115, 1–21, https://doi.org/10.1029/2009JB006889, 2010. a, b, c, d, e, f
Kumagai, H., Lacson, R., Maeda, Y., Figueroa, M. S., Yamashina, T., Ruiz, M.,
Palacios, P., Ortiz, H., and Yepes, H.: Source amplitudes of volcano-seismic
signals determined by the amplitude source location method as a quantitative
measure of event size, J. Volcanol. Geoth. Res., 257, 57–71,
https://doi.org/10.1016/j.jvolgeores.2013.03.002, 2013. a, b, c, d
Kumagai, H., Mothes, P., Ruiz, M., and Maeda, Y.: An approach to source
characterization of tremor signals associated with eruptions and lahars,
Earth Planets Space, 67, 178, https://doi.org/10.1186/s40623-015-0349-1, 2015. a, b
Kumagai, H., Londoño, J. M., Maeda, Y., López Velez, C. M., and
Lacson Jr., R.: Envelope widths of volcano-seismic events and seismic
scattering characteristics beneath volcanoes, J. Geophys. Res.-Solid Ea.,
123, 9764–9777, https://doi.org/10.1029/2018JB015557, 2018. a
Lacroix, P., Grasso, J. R., Roulle, J., Giraud, G., Goetz, D., Morin, S., and
Helmstetter, A.: Monitoring of snow avalanches using a seismic array: Location, speed estimation, and relationships to meteorological variables,
J. Geophys. Res.-Ea. Surf., 117, 1–15, https://doi.org/10.1029/2011JF002106, 2012. a, b, c, d, e, f, g
Leprettre, B. J., Navarre, J.-P., and Taillefer, A.: First results from a
pre-operational system for automatic detection and recognition of seismic
signals associated with avalanches, J. Glaciol., 42, 352–363,
https://doi.org/10.3189/s0022143000004202, 1996. a, b
Levy, C., Mangeney, A., Bonilla, F., Hibert, C., Calder, E. S., and Smith,
P. J.: Friction weakening in granular flows deduced from seismic records at
the Soufrière Hills Volcano, Montserrat, J. Geophys. Res.-Solid Ea., 120, 7536–7557, https://doi.org/10.1002/2015JB012151, 2015. a, b
Morioka, H., Kumagai, H., and Maeda, T.: Theoretical basis of the amplitude
source location method for volcano-seismic signals, J. Geophys. Res.-Solid
Ea., 122, 6538–6551, https://doi.org/10.1002/2017JB013997, 2017. a
Nishimura, K. and Izumi, K.: Seismic signals induced by snow avalanche flow,
Nat. Hazards, 15, 89–100, https://doi.org/10.1023/A:1007934815584, 1997. a, b
Ogiso, M. and Yomogida, K.: Estimation of locations and migration of debris
flows on Izu-Oshima Island, Japan, on 16 October 2013 by the distribution of
high frequency seismic amplitudes, J. Volcanol. Geoth. Res., 298, 15–26,
https://doi.org/10.1016/j.jvolgeores.2015.03.015, 2015. a, b, c, d, e, f, g, h, i
Patra, A. K., Bauer, A. C., Nichita, C. C., Pitman, E. B., Sheridan, M. F., Bursik, M., Rupp, B., Webber, A., Stinton, A. J., Namikawa, L. M., and Renschler, C. S.: Parallel adaptive numerical simulation of dry avalanches over natural terrain, J. Volcanol. Geoth. Res., 139, 1–21,
https://doi.org/10.1016/j.jvolgeores.2004.06.014, 2005. a
Phillips, W. S. and Aki, K.: Site amplification of coda waves from local
earthquakes in central California, Bull. Seismol. Soc. Am., 76, 627–648, 1986. a
Schneider, D., Bartelt, P., Caplan-Auerbach, J., Christen, M., Huggel, C., and McArdell, B. W.: Insights into rock-ice avalanche dynamics by combined
analysis of seismic recordings and a numerical avalanche model, J. Geophys.
Res., 115, F04026, https://doi.org/10.1029/2010JF001734, 2010. a
Suriñach, E., Furdada, G., Sabot, F., Biescas, B., and Vilaplana, J.: On
the characterization of seismic signals generated by snow avalanches for
monitoring purposes, Ann. Glaciol., 32, 268–274, https://doi.org/10.3189/172756401781819634, 2001. a, b, c
Suriñach, E., Vilajosana, I., Khazaradze, G., Biescas, B., Furdada, G., and Vilaplana, J.: Seismic detection and characterization of landslides and other mass movements, Nat. Hazards Earth Syst. Sci., 5, 791–798,
https://doi.org/10.5194/nhess-5-791-2005, 2005. a, b
Takeuchi, Y., Nishimura, K., and Patra, A.: Observations and numerical
simulations of the braking effect of forests on large-scale avalanches, Ann.
Glaciol., 59, 50–58, https://doi.org/10.1017/aog.2018.22, 2018. a, b
Tanaka, A., Yamamura, Y., and Nakano, T.: Effects of forest-floor avalanche
disturbance on the structure and dynamics of a subalpine forest near the
forest limit on Mt. Fuji, Ecol. Res., 23, 71–81, https://doi.org/10.1007/s11284-007-0340-9, 2008.
a
van Herwijnen, A. and Schweizer, J.: Monitoring avalanche activity using a
seismic sensor, Cold Reg. Sci. Technol., 69, 165–176,
https://doi.org/10.1016/j.coldregions.2011.06.008, 2011. a
Vilajosana, I., Khazaradze, G., Suriñach, E., Lied, E., and Kristensen,
K.: Snow avalanche speed determination using seismic methods, Cold Reg. Sci. Technol., 49, 2–10, https://doi.org/10.1016/j.coldregions.2006.09.007, 2007a. a, b, c, d
Vilajosana, I., Suriñach, E., Abellán, A., Khazaradze, G., Garcia, D., and Llosa, J.: Rockfall induced seismic signals: case study in Montserrat, Catalonia, Nat. Hazards Earth Syst. Sci., 8, 805–812,
https://doi.org/10.5194/nhess-8-805-2008, 2008. a
Walsh, B., Jolly, A., and Procter, J.: Seismic analysis of the 13 October 2012 Te Maari, New Zealand, lake breakout lahar: Insights into flow dynamics and the implications on mass flow monitoring, J. Volcanol.
Geoth. Res., 324, 144–155, https://doi.org/10.1016/j.jvolgeores.2016.06.004, 2016. a
Yamamoto, M. and Sato, H.: Multiple scattering and mode conversion revealed by an active seismic experiment at Asama volcano, Japan, J. Geophys. Res.-Solid Ea., 115, B07304, https://doi.org/10.1029/2009JB007109, 2010. a, b, c
Short summary
Avalanches and slush flows from Mt. Fuji are a major natural hazard as they may attain run-out distances of up to 4 km and destroy parts of the forest and infrastructure. We located and tracked them for the first time using seismic data. Numerical simulations were conducted to assess the precision of the seismic tracking. We also inferred dynamical properties characterizing these hazardous mass movements. This information is indispensable for assessing avalanche risk in the Mt. Fuji region.
Avalanches and slush flows from Mt. Fuji are a major natural hazard as they may attain run-out...
