Articles | Volume 22, issue 5
https://doi.org/10.5194/nhess-22-1541-2022
© Author(s) 2022. 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-22-1541-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Brief communication
| 
06 May 2022
Brief communication |
| 06 May 2022
| 06 May 2022
Brief communication: Seismological analysis of flood dynamics and hydrologically triggered earthquake swarms associated with Storm Alex
Małgorzata Chmiel
CORRESPONDING AUTHOR
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
Laboratory of Hydraulics, Hydrology and Glaciology, ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
Maxime Godano
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
Marco Piantini
Institute for Geosciences and Environmental Research (IGE), CNRS/INSU, IRD, Université Grenoble Alpes and Grenoble INP, 38 058 Grenoble, France
Pierre Brigode
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
INRAE, UR HYCAR, Université Paris-Saclay, 1 Rue Pierre-Gilles de Gennes, 92160 Antony, France
Florent Gimbert
Institute for Geosciences and Environmental Research (IGE), CNRS/INSU, IRD, Université Grenoble Alpes and Grenoble INP, 38 058 Grenoble, France
Maarten Bakker
Institute for Geosciences and Environmental Research (IGE), CNRS/INSU, IRD, Université Grenoble Alpes and Grenoble INP, 38 058 Grenoble, France
Françoise Courboulex
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
Jean-Paul Ampuero
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
Diane Rivet
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
Anthony Sladen
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
David Ambrois
Géoazur, Observatoire de la Côte d'Azur, CNRS, IRD, Université Côte d'Azur, 06905 Sophia Antipolis, France
Margot Chapuis
ESPACE, CNRS, Université Côte d'Azur, bd Edouard Herriot, 06204 Nice, France
Related authors
No articles found.
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data, 17, 1461–1479, https://doi.org/10.5194/essd-17-1461-2025, https://doi.org/10.5194/essd-17-1461-2025, 2025
Short summary
Short summary
This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyze hydrological behavior and perform model assessments.
Juan-Pedro Roldán-Blasco, Adrien Gilbert, Luc Piard, Florent Gimbert, Christian Vincent, Olivier Gagliardini, Anuar Togaibekov, Andrea Walpersdorf, and Nathan Maier
The Cryosphere, 19, 267–282, https://doi.org/10.5194/tc-19-267-2025, https://doi.org/10.5194/tc-19-267-2025, 2025
Short summary
Short summary
The flow of glaciers and ice sheets results from ice deformation and basal sliding driven by gravitational forces. Quantifying the rate at which ice deforms under its own weight is critical for assessing glacier evolution. This study uses borehole instrumentation in an Alpine glacier to quantify ice deformation and constrain ice viscosity in a natural setting. Our results show that the viscosity of ice at 0 °C is largely influenced by interstitial liquid water, which enhances ice deformation.
Pierre Brigode and Ludovic Oudin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-336, https://doi.org/10.5194/hess-2024-336, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
We analyzed how well two global climate datasets can simulate river flows across Europe over the last 150 years. Our results show good performance overall, revealing important long-term changes in water availability and extreme events, like floods, in different regions. This research helps us better understand past and future water trends, providing insights to manage resources and address the challenges posed by climate change.
Carlo Mologni, Marie Revel, Eric Chaumillon, Emmanuel Malet, Thibault Coulombier, Pierre Sabatier, Pierre Brigode, Gwenael Hervé, Anne-Lise Develle, Laure Schenini, Medhi Messous, Gourguen Davtian, Alain Carré, Delphine Bosch, Natacha Volto, Clément Ménard, Lamya Khalidi, and Fabien Arnaud
Clim. Past, 20, 1837–1860, https://doi.org/10.5194/cp-20-1837-2024, https://doi.org/10.5194/cp-20-1837-2024, 2024
Short summary
Short summary
The reactivity of local to regional hydrosystems to global changes remains understated in East African climate models. By reconstructing a chronicle of seasonal floods and droughts from a lacustrine sedimentary core, this paper highlights the impact of El Niño anomalies in the Awash River valley (Ethiopia). Studying regional hydrosystem feedbacks to global atmospheric anomalies is essential for better comprehending and mitigating the effects of global warming in extreme environments.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
Short summary
Short summary
The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023, https://doi.org/10.5194/hess-27-3375-2023, 2023
Short summary
Short summary
We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.
Olivier Delaigue, Pierre Brigode, Guillaume Thirel, and Laurent Coron
Hydrol. Earth Syst. Sci., 27, 3293–3327, https://doi.org/10.5194/hess-27-3293-2023, https://doi.org/10.5194/hess-27-3293-2023, 2023
Short summary
Short summary
Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, https://doi.org/10.5194/hess-26-5793-2022, 2022
Short summary
Short summary
Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
Marco Piantini, Florent Gimbert, Hervé Bellot, and Alain Recking
Earth Surf. Dynam., 9, 1423–1439, https://doi.org/10.5194/esurf-9-1423-2021, https://doi.org/10.5194/esurf-9-1423-2021, 2021
Short summary
Short summary
We carry out laboratory experiments to investigate the formation and propagation dynamics of exogenous sediment pulses in mountain rivers. We show that the ability of a self-formed deposit to destabilize and generate sediment pulses depends on the sand content of the mixture, while each pulse turns out to be formed by a front, a body, and a tail. Seismic measurements reveal a complex and non-unique dependency between seismic power and sediment pulse transport characteristics.
Itzhak Lior, Anthony Sladen, Diego Mercerat, Jean-Paul Ampuero, Diane Rivet, and Serge Sambolian
Solid Earth, 12, 1421–1442, https://doi.org/10.5194/se-12-1421-2021, https://doi.org/10.5194/se-12-1421-2021, 2021
Short summary
Short summary
The increasing use of distributed acoustic sensing (DAS) inhibits the transformation of optical fibers into dense arrays of seismo-acoustic sensors. Here, DAS strain records are converted to ground motions using the waves' apparent velocity. An algorithm for velocity determination is presented, accounting for velocity variations between different seismic waves. The conversion allows for robust determination of fundamental source parameters, earthquake magnitude and stress drop.
Martijn P. A. van den Ende and Jean-Paul Ampuero
Solid Earth, 12, 915–934, https://doi.org/10.5194/se-12-915-2021, https://doi.org/10.5194/se-12-915-2021, 2021
Short summary
Short summary
Distributed acoustic sensing (DAS) is an emerging technology that measures stretching of an optical-fibre cable. This technology can be used to record the ground shaking of earthquakes, which offers a cost-efficient alternative to conventional seismometers. Since DAS is relatively new, we need to verify that existing seismological methods can be applied to this new data type. In this study, we reveal several issues by comparing DAS with conventional seismometer data for earthquake localisation.
Nathan Maier, Florent Gimbert, Fabien Gillet-Chaulet, and Adrien Gilbert
The Cryosphere, 15, 1435–1451, https://doi.org/10.5194/tc-15-1435-2021, https://doi.org/10.5194/tc-15-1435-2021, 2021
Short summary
Short summary
In Greenland, ice motion and the surface geometry depend on the friction at the bed. We use satellite measurements and modeling to determine how ice speeds and friction are related across the ice sheet. The relationships indicate that ice flowing over bed bumps sets the friction across most of the ice sheet's on-land regions. This result helps simplify and improve our understanding of how ice motion will change in the future.
Christian Vincent, Diego Cusicanqui, Bruno Jourdain, Olivier Laarman, Delphine Six, Adrien Gilbert, Andrea Walpersdorf, Antoine Rabatel, Luc Piard, Florent Gimbert, Olivier Gagliardini, Vincent Peyaud, Laurent Arnaud, Emmanuel Thibert, Fanny Brun, and Ugo Nanni
The Cryosphere, 15, 1259–1276, https://doi.org/10.5194/tc-15-1259-2021, https://doi.org/10.5194/tc-15-1259-2021, 2021
Short summary
Short summary
In situ glacier point mass balance data are crucial to assess climate change in different regions of the world. Unfortunately, these data are rare because huge efforts are required to conduct in situ measurements on glaciers. Here, we propose a new approach from remote sensing observations. The method has been tested on the Argentière and Mer de Glace glaciers (France). It should be possible to apply this method to high-spatial-resolution satellite images and on numerous glaciers in the world.
Martijn P. A. van den Ende, Marco M. Scuderi, Frédéric Cappa, and Jean-Paul Ampuero
Solid Earth, 11, 2245–2256, https://doi.org/10.5194/se-11-2245-2020, https://doi.org/10.5194/se-11-2245-2020, 2020
Short summary
Short summary
The injection of fluids (like wastewater or CO2) into the subsurface could cause earthquakes when existing geological faults inside the reservoir are (re-)activated. To assess the hazard associated with this, previous studies have conducted experiments in which fluids have been injected into centimetre- and decimetre-scale faults. In this work, we analyse and model these experiments. To this end, we propose a new approach through which we extract the model parameters that govern slip on faults.
Cited articles
Aki, K. and Richards, P. G.: Quantitative Seismology, University Science Books, 2nd Edn., 704 pp., ISBN 0-935702-96-2, 2002. a
Bakker, M., Gimbert, F., Geay, T., Misset, C., Zanker, S., and Recking, A.:
Field Application and Validation of a Seismic Bedload Transport Model, J. Geophys. Res.-Earth, 125, e2019JF005416, https://doi.org/10.1029/2019JF005416, 2020. a, b
Borga, M., Boscolo, P., Zanon, F., and Sangati, M.: Hydrometeorological Analysis of the 29 August 2003 Flash Flood in the Eastern Italian Alps, J. Hydrometeorol., 8, 1049–1067, https://doi.org/10.1175/JHM593.1, 2007. a
Borga, M., Comiti, F., Ruin, I., and Marra, F.: Forensic analysis of flash
flood response, WIREs Water, 6, e1338, https://doi.org/10.1002/wat2.1338, 2019. a
Brenguier, F., Campillo, M., Hadziioannou, C., Shapiro, N. M., Nadeau, R. M.,
and Larose, É.: Postseismic Relaxation Along the San Andreas Fault at
Parkfield from Continuous Seismological Observations, Science, 321, 1478–1481, 2008. a
Brigode, P., Vigoureux, S., Delestre, O., Nicolle, P., Payrastre, O., Dreyfus, R., Nomis, S., and Salvan, L.: Inondations sur la Côte d'Azur: bilan hydro-météorologique des épisodes de 2015 et 2019, La Houille Blanche, 107, 1–14, https://doi.org/10.1080/27678490.2021.1976600, 2021. a, b
Burtin, A., Cattin, R., Bollinger, L., Vergne, J., Steer, P., Robert, A.,
Findling, N., and Tiberi, C.: Towards the hydrologic and bed load monitoring
from high-frequency seismic noise in a braided river: The “torrent de
St Pierre”, French Alps, J. Hydrol., 408, 43–53, https://doi.org/10.1016/j.jhydrol.2011.07.014, 2011. a
Burtin, A., Hovius, N., and Turowski, J. M.: Seismic monitoring of torrential
and fluvial processes, Earth Surf. Dynam., 4, 285–307,
https://doi.org/10.5194/esurf-4-285-2016, 2016. a, b
Carrega, P. and Michelot, N.: Une catastrophe hors norme d'origine
météorologique le 2 octobre 2020 dans les montagnes des Alpes-Maritimes, Physio-Géo, 16, 1–70, https://doi.org/10.4000/physio-geo.12370, 2021. a, b, c
Chen, X. and Shearer, P. M.: Comprehensive analysis of earthquake source
spectra and swarms in the Salton Trough, California, J. Geophys. Res., 116, B04301, https://doi.org/10.1029/2011JB008263, 2011. a
Chen, X., Shearer, P. M., and Abercrombie, R. E.: Spatial migration of
earthquakes within seismic clusters in Southern California: Evidence for
fluid diffusion, J. Geophys. Res.-Solid, 117, B04301, https://doi.org/10.1029/2011JB008973, 2012. a, b
Chmiel, M., Walter, F., Wenner, M., Zhang, Z., McArdell, B. W., and Hibert, C.: Machine Learning Improves Debris Flow Warning, Geophys. Res. Lett., 48, e2020GL090874, https://doi.org/10.1029/2020GL090874, 2021. a
Cook, K. L., Andermann, C., Gimbert, F., Adhikari, B. R., and Hovius, N.:
Glacial lake outburst floods as drivers of fluvial erosion in the Himalaya,
Science, 362, 53–57, https://doi.org/10.1126/science.aat4981, 2018. a, b, c, d
Cook, K. L., Rekapalli, R., Dietze, M., Pilz, M., Cesca, S., Rao, N. P.,
Srinagesh, D., Paul, H., Metz, M., Mandal, P., Suresh, G., Cotton, F., Tiwari, V. M., and Hovius, N.: Detection and potential early warning of
catastrophic flow events with regional seismic networks, Science, 374, 87–92, https://doi.org/10.1126/science.abj1227, 2021.
a
Costain, J. K. and Bollinger, G. A.: Review: Research results in hydroseismicity from 1987 to 2009, Bull. Seismol. Soc. Am., 100, 1841–1858, https://doi.org/10.1785/0120090288, 2010. a
D'Agostino, N., Silverii, F., Amoroso, O., Convertito, V., Fiorillo, F.,
Ventafridda, G., and Zollo, A.: Crustal Deformation and Seismicity Modulated
by Groundwater Recharge of Karst Aquifers, Geophys. Res. Lett., 45, 12253–12262, https://doi.org/10.1029/2018GL079794, 2018. a, b
de Barros, L., Cappa, F., Deschamps, A., and Dublanchet, P.: Imbricated
Aseismic Slip and Fluid Diffusion Drive a Seismic Swarm in the Corinth Gulf,
Greece, Geophys. Res. Lett., 47, e2020GL087142, https://doi.org/10.1029/2020GL087142, 2020. a
Eibl, E. P. S., Bean, C. J., Einarsson, B., Pàlsson, F., and Vogfjörd, K. S.:
Seismic ground vibrations give advanced early-warning of subglacial floods,
Nat. Commun., 11, 2504, https://doi.org/10.1038/s41467-020-15744-5, 2020. a
Gibbons, S. J. and Ringdal, F.: The detection of low magnitude seismic events
using array-based waveform correlation, Geophys. J. Int., 165, 149–166, https://doi.org/10.1111/j.1365-246X.2006.02865.x, 2006. a, b
Gimbert, F., Tsai, V., and Lamb, M.: A physical model for seismic noise
generation by turbulent flow in rivers, J. Geophys. Res.-Earth, 119, 2209–2238, https://doi.org/10.1002/2014JF003201, 2014. a, b, c
Gimbert, F., Fuller, B. M., Lamb, M. P., Tsai, V. C., and Johnson, J. P. L.:
Particle transport mechanics and induced seismic noise in steep flume
experiments with accelerometer-embedded tracers, Earth Surf. Proc. Land., 44, 219–241, https://doi.org/10.1002/esp.4495, 2019. a
Goodling, P. J., Lekic, V., and Prestegaard, K.: Seismic signature of
turbulence during the 2017 Oroville Dam spillway erosion crisis, Earth
Surf. Dynam., 6, 351–367, https://doi.org/10.5194/esurf-6-351-2018, 2018. a, b, c, d
Hainzl, S., Kraft, T., Wassermann, J., Igel, H., and Schmedes, E.: Evidence for rainfall-triggered earthquake activity, Geophys. Res. Lett., 33, L19303, https://doi.org/10.1029/2006GL027642, 2006. a
Hanka, W., Saul, J., Weber, B., Becker, J., Harjadi, P., Fauzi, and Group, G. S.: Real-time earthquake monitoring for tsunami warning in the Indian Ocean and beyond, Nat. Hazards Earth Syst. Sci., 10, 2611–2622,
https://doi.org/10.5194/nhess-10-2611-2010, 2010. a
Hatch, R. L., Abercrombie, R. E., Ruhl, C. J., and Smith, K. D.: Evidence of
Aseismic and Fluid‐Driven Processes in a Small Complex Seismic Swarm Near
Virginia City, Nevada, Geophys. Res. Lett., 47, e2019GL085477, https://doi.org/10.1029/2019GL085477, 2020. a, b
Hsu, Y.-J., Kao, H., Bürgmann, R., Lee, Y.-T., Huang, H.-H., Hsu, Y.-F., Wu, Y.-M., and Zhuang, J.: Synchronized and asynchronous modulation of seismicity by hydrological loading: A case study in Taiwan, Sci. Advances, 7,
eabf7282, https://doi.org/10.1126/sciadv.abf7282, 2021. a
Husen, S., Bachmann, C., and Giardini, D.: Locally triggered seismicity in the central Swiss Alps following the large rainfall event of August 2005,
Geophys. J. Int., 171, 1126–1134, https://doi.org/10.1111/j.1365-246X.2007.03561.x, 2007. a
Illien, L., Sens‐Schönfelder, C., Andermann, C., Marc, O., Cook, K. L.,
Adhikari, L. B., and Hovius, N.: Seismic velocity recovery in the subsurface:
transient damage and groundwater drainage following the 2015 Gorkha earthquake, Nepal, J. Geophys. Res.-Solid, 127, e2021JB023402, https://doi.org/10.1029/2021JB023402, 2022. a
IPCC: Summary for Policymakers, Cambridge University Press, Cambridge, UK and New York, NY, USA,
https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_SPM_final.pdf, last access: 12 April 2022, in press, 2022. a
Johnson, C. W., Fu, Y., and BÃŒrgmann, R.: Seasonal water storage, stress
modulation, and California seismicity, Science, 356, 1161–1164,
https://doi.org/10.1126/science.aak9547, 2017. a
Khajehei, S., Ahmadalipour, A., Shao, W., and Moradkhani, H.: A Place-based
Assessment of Flash Flood Hazard and Vulnerability in the Contiguous United States, Scient. Reports, 10, 448, https://doi.org/10.1038/s41598-019-57349-z, 2020. a
Koper, K. D. and Hawley, V. L.: Frequency dependent polarization analysis of
ambient seismic noise recorded at a broadband seismometer in the central
United States, Earthq. Sci., 23, 439–447, https://doi.org/10.1007/s11589-010-0743-5, 2010. a
Kraft, T., Wassermann, J., Schmedes, E., and Igel, H.: Meteorological
triggering of earthquake swarms at Mt. Hochstaufen, SE-Germany, Tectonophysics, 424, 245–258, https://doi.org/10.1016/j.tecto.2006.03.044, 2006. a, b, c
Krischer, L., Megies, T., Barsch, R., Beyreuther, M., Lecocq, T., Caudron, C., and Wassermann, J.: ObsPy: a bridge for seismology into the scientific Python ecosystem, Comput. Sci. Discov., 8, 014003, https://doi.org/10.1088/1749-4699/8/1/014003, 2015. a
Kundu, B., Vissa, N. K., Panda, D., Jha, B., Asaithambi, R., Tyagi, B., and
Mukherjee, S.: Influence of a meteorological cycle in mid-crustal seismicity
of the Nepal Himalaya, J. Asian Earth Sci., 146, 317–325, https://doi.org/10.1016/j.jseaes.2017.06.003, 2017. a
Lagarde, S., Dietze, M., Gimbert, F., Laronne, J. B., Turowski, J. M., and
Halfi, E.: Grain-Size Distribution and Propagation Effects on Seismic Signals
Generated by Bedload Transport, Water Resour. Rese., 57, e2020WR028700, https://doi.org/10.1029/2020WR028700, 2021. a
Lai, V. H., Tsai, V. C., Lamb, M. P., Ulizio, T. P., and Beer, A. R.: The
Seismic Signature of Debris Flows: Flow Mechanics and Early Warning at Montecito, California, Geophys. Res. Lett., 45, 5528–5535, https://doi.org/10.1029/2018GL077683, 2018. a, b
Laurantin, O.: ANTILOPE: Hourly rainfall analysis merging radar and rain gauge data, in: Proceedings of the International Symposium on Weather Radar and Hydrology, 10–12 March 2008, Grenoble, 2–8, http://www.wrah-2008.com/ (last access: 8 November 2020), 2008. a
Lohman, R. B. and McGuire, J. J.: Earthquake swarms driven by aseismic creep in the Salton Trough, California, J. Geophys. Res., 112, B04405, https://doi.org/10.1029/2006JB004596, 2007. a
Maurer, J. M., Schaefer, J. M., Russell, J. B., Rupper, S., Wangdi, N., Putnam, A. E., and Young, N.: Seismic observations, numerical modeling, and
geomorphic analysis of a glacier lake outburst flood in the Himalayas, Sci. Adv., 6, eaba3645, https://doi.org/10.1126/sciadv.aba3645, 2020. a, b
Meng, H. and Ben-Zion, Y.: Detection of small earthquakes with dense array
data: example from the San Jacinto fault zone, southern California, Geophys. J. Int., 212, 442–457, https://doi.org/10.1093/gji/ggx404, 2017. a
Miller, S. A.: Note on rain-triggered earthquakes and their dependence on
karst geology, Geophys. J. Int., 173, 334–338, https://doi.org/10.1111/j.1365-246X.2008.03735.x, 2008. a, b
Montgomery-Brown, E. K., Shelly, D. R., and Hsieh, P. A.: Snowmelt-Triggered
Earthquake Swarms at the Margin of Long Valley Caldera, California, Geophys. Res. Lett., 46, 3698–3705, https://doi.org/10.1029/2019GL082254, 2019. a, b
Park, C. B., Miller, R. D., and Xia, J.: Imaging dispersion curves of surface
waves on multi-channel record, Society of Exploration Geophysicists, 1377–1380, https://doi.org/10.1190/1.1820161, 2005. a
Piantini, M., Gimbert, F., Bellot, H., and Recking, A.: Triggering and
propagation of exogenous sediment pulses in mountain channels: insights from
flume experiments with seismic monitoring, Earth Surf. Dynam., 9, 1423–1439, https://doi.org/10.5194/esurf-9-1423-2021, 2021. a
Raynaud, D., Thielen, J., Salamon, P., Burek, P., Anquetin, S., and Alfieri,
L.: A dynamic runoff co-efficient to improve flash flood early warning in
Europe: evaluation on the 2013 central European floods in Germany, Meteorol. Appl., 22, 410–418, https://doi.org/10.1002/met.1469, 2015. a
RESIF: RESIF-RLBP French Broad-band network. RESIF-RAP strong motion network and other seismic stations in metropolitan France, RESIF – Réseau Sismologique et géodésique Français [data set],
https://doi.org/10.15778/resif.fr, 1995a. a
RESIF: RESIF-RAP French Accelerometric Network, RESIF – Réseau Sismologique et géodésique Français [data set],
https://doi.org/10.15778/resif.ra, 1995b. a
RESIF: Résif Seismological Data Portal, RESIF – Réseau Sismologique et géodésique Français, https://doi.org/10.17616/R37Q06, 1995c. a
Ribes, A., Thao, S., Vautard, R., Dubuisson, B., Somot, S., Colin, J., Planton, S., and Soubeyroux, J.-M.: Observed increase in extreme daily rainfall in the French Mediterranean, Clim. Dynam., 52, 1095–1114,
https://doi.org/10.1007/s00382-018-4179-2, 2019. a
Rigo, A., Béthoux, N., Masson, F., and Ritz, J.-F.: Seismicity rate and
wave-velocity variations as consequences of rainfall: The case of the
catastrophic storm of September 2002 in the Nîmes Fault region (Gard, France), Geophys. J. Int., 173, 473–482, https://doi.org/10.1111/j.1365-246X.2008.03718.x, 2008. a, b, c, d
Roland, E. and McGuire, J. J.: Earthquake swarms on transform faults, Geophys. J. Int., 178, 1677–1690, 2009. a
Roth, D. L., Brodsky, E. E., Finnegan, N. J., Rickenmann, D., Turowski, J. M., and Badoux, A.: Bed load sediment transport inferred from seismic signals
near a river, J. Geophys. Res.-Earth, 121, 725–747, https://doi.org/10.1002/2015JF003782, 2016. a, b
Roth, D. L., Finnegan, N. J., Brodsky, E. E., Rickenmann, D., Turowski, J. M., Badoux, A., and Gimbert, F.: Bed load transport and boundary roughness
changes as competing causes of hysteresis in the relationship between river
discharge and seismic amplitude recorded near a steep mountain stream, J. Geophys. Res.-Earth, 122, 1182–1200, https://doi.org/10.1002/2016JF004062, 2017.
a
Roth, P., Pavoni, N., and Deichmann, N.: Seismotectonics of the eastern Swiss
Alps and evidence for precipitation-induced variations of seismic activity,
Tectonophysics, 207, 183–197, https://doi.org/10.1016/0040-1951(92)90477-N, 1992. a
Saar, M. O. and Manga, M.: Seismicity induced by seasonal groundwater recharge at Mt. Hood, Oregon, Earth Planet. Sc. Lett., 214, 605–618,
https://doi.org/10.1016/S0012-821X(03)00418-7, 2003. a, b, c
Schmandt, B., Aster, R. C., Scherler, D., Tsai, V. C., and Karlstrom, K.:
Multiple fluvial processes detected by riverside seismic and infrasound
monitoring of a controlled flood in the Grand Canyon, Geophys. Res. Lett., 40, 4858–4863, https://doi.org/10.1002/grl.50953, 2013. a, b, c, d
Schmandt, B., Gaeuman, D., Stewart, R., Hansen, S., Tsai, V., and Smith, J.:
Seismic array constraints on reach-scale bedload transport, Geology, 45,
299–302, https://doi.org/10.1130/G38639.1, 2017. a
Shapiro, S. A., Huenges, E., and Borm, G.: Estimating the crust permeability
from fluid-injection-induced seismic emission at the KTB site, Geophys. J. Int., 131, F15–F18, https://doi.org/10.1111/j.1365-246X.1997.tb01215.x, 1997. a
Solomon, J.: PSD computations using Welch's method. [Power Spectral Density (PSD)], Tech. Rep. SAND-91-1533, Sandia National Labs., Albuquerque, NM, USA, https://doi.org/10.2172/5688766, 1991. a, b
Stoffel, M. and Huggel, C.: Effects of climate change on mass movements in
mountain environments, Prog. Phys. Geogr., 36, 421–439, https://doi.org/10.1177/0309133312441010, 2012. a
Tabary, P., Dupuy, P., L'HEenaff, G., Gueguen, C., Moulin, L., Laurantin, O.,
Merlier, C., and J.-M., S.: A 10-year (1997–2006) reanalysis of Quantitative Precipitation Estimation over France: methodology and first results, in: Weather Radar and Hydrology, vol. 351, International Association of Hydrological Sciences, Wallingford, UK, 255–260, 2022http://www.meteo.fr/cic/meetings/2012/ERAD/extended_abs/QPE_199_ext_abs.pdf (last access: 3 May 2022), 2012. a
Tramblay, Y. and Somot, S.: Future evolution of extreme precipitation in the
Mediterranean, Climatic Change, 151, 289–302, https://doi.org/10.1007/s10584-018-2300-5, 2018. a
Tsai, V. C., Minchew, B., Lamb, M. P., and Ampuero, J.-P.: A physical model for seismic noise generation from sediment transport in rivers, Geophys. Res. Lett., 39, L02404, https://doi.org/10.1029/2011GL050255, 2012. a, b
Ueda, T. and Kato, A.: Seasonal Variations in Crustal Seismicity in San-in
District, Southwest Japan, Geophys. Res. Lett., 46, 3172–3179,
https://doi.org/10.1029/2018GL081789, 2019. a
Zhang, Z., Walter, F., McArdell, B. W., Wenner, M., Chmiel, M., de Haas, T.,
and He, S.: Insights From the Particle Impact Model Into the High-Frequency
Seismic Signature of Debris Flows, Geophys. Res. Lett., 48, e2020GL088994, https://doi.org/10.1029/2020GL088994, 2021. a
Short summary
On 2 October 2020, the French Maritime Alps were struck by an extreme rainfall event caused by Storm Alex. Here, we show that seismic data provide the timing and velocity of the propagation of flash-flood waves along the Vésubie River. We also detect 114 small local earthquakes triggered by the rainwater weight and/or its infiltration into the ground. This study paves the way for future works that can reveal further details of the impact of Storm Alex on the Earth’s surface and subsurface.
On 2 October 2020, the French Maritime Alps were struck by an extreme rainfall event caused by...
Altmetrics
Final-revised paper
Preprint