Seismic techniques are becoming widely used to detect and quantitatively characterise a wide variety of natural processes occurring at the Earth’s surface. These processes include mass movements such as landslides, rock falls, debris flows and lahars; glacial phenomena such as icequakes, glacier calving/serac falls, glacier melt and supra- to sub-glacial hydrology; snow avalanches; water storage and water dynamics phenomena such as water table changes, river flow turbulence and fluvial sediment transport. Where other methods often provide limited spatial and temporal coverage, seismic observations allow recovering sequences of events with high temporal resolution and over large areas. These observational capabilities allow establishing connections with meteorological drivers, and give unprecedented insights on the underlying physics of the various Earth’s surface processes as well as on their interactions (chains of events). These capabilities are also of first interest for real time hazards monitoring and early warning purposes. In particular, seismic monitoring techniques can provide relevant information on the dynamics of flows and unstable slopes, and thus allow for the identification of precursory patterns of hazardous events and timely warning.
This session aims at bringing together scientists who use seismic methods to study Earth surface dynamics. We invite contributions from the field of geomorphology, cryospheric sciences, seismology, natural hazards, volcanology, soil system sciences and hydrology. Theoretical, field based and experimental approaches are highly welcome.
Solicited presenter: Kate Allstadt - USGS Geologic Hazards Science Center, Golden, CO, USA
vPICO presentations: Tue, 27 Apr
Researchers are increasingly incorporating force histories derived from long-period seismic waves into multidisciplinary studies of large, rapid landslides. The force history can provide important information about what happened during failure — information that complements data available from field investigations and remote sensing analyses. It can also provide additional constraints on the dynamics of landslide motion than can be used to validate and/or calibrate numerical landslide models. However, the inversions need to be of high quality and must be interpreted properly. Because this technique is relatively new, we are still discovering how to best conduct inversions to obtain robust results and how to appropriately interpret these results. In this study, we run numerical models of landslides with idealized source and path geometries using two different modeling packages, DAN3D and D-Claw, and we use the model outputs to generate synthetic long-period seismic data. Both models use depth-averaged flow equations over 3D topography, with DAN3D using semi-empirical material rheologies and D-Claw using a two-phase granular and fluid flow approach. To examine the influence of station azimuthal coverage and distance, we synthesize seismic data for a wide range of possible station configurations. We then use these synthetic seismic data to conduct seismic inversions using the recently released open-source Python-based software package, lsforce (https://code.usgs.gov/ghsc/lhp/lsforce). In doing these inversions, we add differing levels and types of noise, vary the inversion options (e.g., frequency range, regularization techniques) and then compare the results to the “known” dynamics of the modeled idealized landslides. We aim to understand common artefacts, limitations, and other potential pitfalls in interpretation, to guide the inversion process in future studies. We repeat this process for idealized landslides of increasing complexity, including multi-part failures, sinuous paths, and gradual versus sudden initiations, to simulate how these characteristics are reflected in the force history and to better understand what level of detail can be constrained from the seismic inversion. This work will help guide researchers to obtain more reliable information about landslide dynamics from seismic inversions in future landslide studies.
How to cite: Allstadt, K., Mitchell, A., Toney, L., George, D., and McDougall, S.: Seismic inversions of large, rapid landslides: what they can and cannot tell us about event dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-954, https://doi.org/10.5194/egusphere-egu21-954, 2021.
In the last decade, the increasing number and spatial density of seismological stations provide unprecedented opportunities for recording various natural and human-related events in continuous records. Diverse methods have been proposed for event detection, classification, and characterization, but few of them are based on the physical properties of the events. In this study, inspired by music information retrieval methods such as audio fingerprinting, we present a time-efficient event detection method based on capturing the physical properties of seismic signatures such as corner frequency, high-frequency fall-off, and complexity of signature. The zero-crossing rate of the recorded signal is used to estimate the corner frequency, which is the dominant frequency in the velocity domain of record. The high-frequency fall-off can be estimated in the time-frequency spectrogram by finding the frequency below which 75% of the energy of the spectrum is produced. The complexity of the spectrum of the recorded signal is finally represented by a second-order polynomial coefficient fitting the spectrum and capturing the slope of the source spectra. Also, we use the spectral flatness to quantify the noise properties. We validate the proposed procedure to synthetic data generated by the stochastic simulation method. We finally apply the method to real data sets to detect the seismic precursors for the Nuugaatsiaq landslide. We separate the earthquake event and precursory signals because of different corner frequencies and show that the precursory signals started for hours before the main landslide.
How to cite: Dokht Dolatabadi Esfahani, R., Scherbaum, F., Cotton, F., and Ohrnberger, M.: An efficient physic-based event detection algorithm inspired by music information retrieval, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13572, https://doi.org/10.5194/egusphere-egu21-13572, 2021.
An understanding of the characteristics of a mass movement descending a slope enables us to obtain a better control through models and also to reduce its associated risks. The seismic signals generated by the mass movement are mainly caused by friction of the moving mass on the ground. Most of the studies of the seismic signals use the spectrograms as a complementary information of the signals. Our study seeks to expand the current applications of the spectrograms using the information contained in them. A spectrogram represents the evolution in time of the frequency content of a time series. It can also be read as a 3D representation of amplitude, frequency and time of the seismic signal. The spectrograms of the seismic signals generated by a mass movement that descend a slope and approach a seismic sensor can be divided into sections: SON (Signal ONset), SOV (Signal Over) and SEN (Signal End), depending on whether the gravitational mass movement is approaching the sensor, is on it or is moving away from it.
The method presented here consist of analyzing the spectrogram as an image, applying image processing techniques as “Hough Transform”. This method allows us to obtain quantitative information from the spectrograms. Our aim is to obtain the parameters of the shape of the spectrograms, focused on SON section, to create indicators linked to the evolution of the mass movement, for example the speed. The method is applied to spectrograms of three types of gravitational mass movements: snow avalanches (7), lahars (4), and debris flows (1). The results indicate similarities in the shape of the spectrograms of the different types of mass movement, prevailing, however, the specific characteristics of each type.
How to cite: Surinach, E. and Flores-Márquez, E. L.: Information on gravitational mass movements obtained from the spectrograms of their seismic signals generated, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12173, https://doi.org/10.5194/egusphere-egu21-12173, 2021.
In volcanoes, topography and shallow morphology can substantially modify seismic signals, tracing anisotropic signatures in the crust's most surficial layers. To better understand the influence of key morphologies, forward modelling of the seismic waveforms is fundamental. Here, we introduce a forward model of the seismic wave equation developed with finite-differences schemes in anisotropic viscoelastic media. The observation of geomorphological features and the surficial geology map of Mount St. Helens are used to reproduce the scattering and anisotropic effects caused by shallow heterogeneity on seismic signals. The main aim is to understand if and to which lengths lateral anisotropic variations in geomorphological features control the generation and propagation of low-frequency seismic signals, focusing especially on the timing of surface-wave enhancement.
The model shows how the geomorphology-derived anisotropy controls the travel times of the horizontally polarized S waves (SH), in particular along with two directions: WNW-ESE, following the trend of a buried fault, and NS, consistent with the main morphological difference between southern (mostly untouched by the 1980 eruption) and northern (collapsed in 1980’s blast) flanks of the volcano. An analysis of the waveforms of a shallow event of 2005 (during the last eruption of Mt. St. Helens), located in the crater, shows how an isotropic model can reproduce the arrival of the SH wave at high frequencies (10 Hz). The introduction of an effective anisotropic medium is necessary to explain the arrivals for stations deployed across the north-northwestern flank of the volcano at lower frequencies (1 Hz and 6 Hz). The heterogeneity in the crater (e.g., the glacier inside the crater covered by a rock-debris layer) can create interfaces made mostly of unconsolidated materials. As also demonstrated by radiative transfer simulation, the crater acts as a primary source of surface waves dominating the seismic signals.
How to cite: De Siena, L., Gabrielli, S., and Spagnolo, M.: Geomorphologically-controlled seismic signals at Mount St. Helens volcano, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3238, https://doi.org/10.5194/egusphere-egu21-3238, 2021.
The coupling between the ocean activity driven by winds and the solid Earth generates seismic signals recorded by seismometers worldwide. The 2-10 s period band, known as secondary microseism, represents the largest background seismic wavefield. While moving over the ocean, tropical cyclones generate particularly strong and localized sources of secondary microseisms that are detected remotely by seismic arrays.
We assess and compare the seismic sources of P, SV, and SH waves associated with typhoon Ioke during its extra-tropical transition. To understand their generation mechanisms, we compare the observed multi-phase sources with theoretical sources computed with a numerical ocean wave model, and we assess the influence of the ocean resonance (or ocean site effect) and coastal reflection of ocean waves. We show how the location and lateral extent of the associated seismic source is period- and phase-dependent. This information is crucial for the use of body waves for ambient noise imaging and gives insights about the sea state, complementary to satellite data.
How to cite: Retailleau, L. and Gualtieri, L.: Multi-phase seismic source imprint of tropical cyclones, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3763, https://doi.org/10.5194/egusphere-egu21-3763, 2021.
Measuring ambient seismic vibration provides a promising tool to monitor unstable rock slopes due to its independence from actual surface deformations. It is generally observed that the seismic wavefield, arising from ambient vibrations, polarizes perpendicular to open fractures and that unstable slopes exhibit strong wavefield amplifications compared to stable reference sites. Rock slope instabilities dominated by deep persistent fracture sets exhibit normal mode behaviour due to standing wave phenomena within individual compartments of the unstable volume. Techniques to assess such behavior are well established in mechanical and civil engineering to assess the dynamic response and possibly the structural integrity of the structure studied.
We performed enhanced frequency domain decomposition modal analysis on ambient vibration data acquired in real-time on an unstable rock site with a volume larger than 150,000 m3 near Preonzo, Switzerland. We tracked the resonance frequency and normal mode polarization of the first two modes over a period of four years. In addition, we show the development of the modal damping ratio of the fundental mode over time, which is a measure of energy dissipation within and out of the system. We found that the dynamic properties of the rock structure experienced annual variations and that they are primarily controlled by temperature and only secondarily by the exension and closure of large-scale fractures. Even though no large slope failure was observed during the monitoring period, the dataset provides a reference model for ongoing slope monitoring, as the resonance frequency and damping ratio is expected to change significantly prior to failure.
How to cite: Häusler, M., Michel, C., Burjánek, J., and Fäh, D.: Monitoring Rock Slope Instabilities Using Frequency Domain Decomposition Modal Analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6390, https://doi.org/10.5194/egusphere-egu21-6390, 2021.
Rockfalls are a substantial geohazard to human life and infrastructure in mountainous regions but we still lack detailed understanding of when and where rockfalls occur, and which environmental conditions lead to rockfall over diurnal, seasonal and annual timescales. This is due to the fact that direct observations in alpine landscapes are difficult to make and long, high-resolution time series of measurements are rare. Using seismic techniques, we can collect near-complete catalogues of geomorphic events and record their distributions in time and space. This allows studying the interaction of process domains, the role of various rockfall triggers, and lead and lag times with unprecedented detail.
We use the unique six-year long seismic dataset of the Reintal rockfall observatory in the German Alps to detect, classify and locate rockfalls in the Reintal catchment. This rockfall catalogue enables us to analyse the spatial and temporal variability of rockfalls spanning several orders of magnitude in size. We test the hypothesis that variations of rockfall in the Reintal catchment are dominated by seasonal patterns. In combination with weather data, we examine boundary conditions, drivers and triggers of rockfalls in this alpine catchment.
How to cite: Schöpa, A., Turowski, J., and Hovius, N.: Spatial and temporal variability, triggers and drivers of seismically detected rockfalls in the Reintal catchment, German Alps , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8793, https://doi.org/10.5194/egusphere-egu21-8793, 2021.
Changes in crustal seismic velocity (dv/v) can be monitored continuously in time by interferometry of seismic ambient noise. This approach has been successfully employed to study temporal perturbations in stress fields, rock fractures, and fluids. Here we go one step further with this monitoring technique, by not only detecting the temporal changes but also imaging the inhomogeneous spatial distributions of dv/v. We implement the spatial imaging by leveraging travel-time shifts at successive lag times and solving inverse problems based on coda-wave sensitivity kernels. We then use these space-time observations of dv/v to investigate the groundwater fluctuations in the Coastal Los Angeles (LA) Basin during 2000-2020. Imaging of dv/v demonstrates the spatial patterns of groundwater variations: Seasonal changes are most pronounced within confined zones in Santa Ana Basin and LA Central Basin, whereas the long-term changes extend to a broader area including the unconfined forebay. We further compare dv/v observations with InSAR measurements and find strongly consistent spatial patterns. Compared with surface deformation measurements, dv/v additionally help to characterize the depths of several aquifers in the study area. This real-data application substantiates the validity of our dv/v imaging protocol, and shows the promise of using spatio-temporal dv/v observations to monitor surficial hydrological processes.
How to cite: Mao, S., Campillo, M., van der Hilst, R., and Lecointre, A.: Mapping Groundwater Fluctuations in the Coastal Los Angeles Basin by Seismic Interferometry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7012, https://doi.org/10.5194/egusphere-egu21-7012, 2021.
Due to their heterogeneity and inaccessibility, karst aquifers are poorly understood along with their functioning, complex structure and behavior in response to flood events. Conventional methods such as piezometers or other underground equipment give only punctual observations that are not very representative of the functioning of the aquifer at the scale of the catchment basin, nor show spatio-temporal variation that occur along the karst network. The objective of this work is to image the flow of water over time from rainfall to the aquifer outlet in a target catchment basin located in the Jura Mountains near Besançon (Eastern France, Fourbanne site of the 'Jurassic Karst' observatory), which hosts a karstic aquifer monitored since 2014 (Cholet et al. 2017). The approach consists in analyzing jointly seismological, hydrogeological and atmospheric data recorded on the aquifer. The instrumentation comprises 2 permanent seismometers, 2 Conductivity Temperature and Pressure (CTD) probes and 1 rain gauge, which will be completed by 65 seismic nodes, 30 rain gauges and 1 additional CTD for an acquisition period of 4 months. We observe that underground hydrological processes occurring in the aquifer, such as water flow or sediment transport, can be precisely monitored using data from one seismometer installed inside the karst conduit. Furthermore, noise cross-correlation analysis will be carried out to detect seismic velocity variations in the medium induced by fluid saturation changes (Froment, 2011). Several studies have demonstrated that these methods can detect changes in saturation in underground aquifers (Lecocq et al. 2017; Voisin et al., 2017). Accordingly, velocity variation will be correlated with flow velocity, soil water content or even permeability, based on measurements of the volume of water entering the basin and circulating in the karstic network obtained from data collected from the CTDs and rain gauges.
FROMENT B., 2011 – Utilisation du bruit sismique ambiant dans le suivi temporel de structures géologiques. [Grenoble]: École doctorale terre, univers, environnement.
LECOCQ, T., LONGUEVERNE, L., PEDERSEN, H.A., 2017 – Monitoring ground water storage at mesoscale using seismic noise: 30 years of continuous observation and thermo-elastic and hydrological modeling. Sci Rep 7, 14241 (2017). https://doi.org/10.1038/s41598-017-14468-9
VOISIN, C., GUZMAN, M., REFLOCH, A., TARUSELLI, M. and GARAMBOIS, S., 2017 – Groundwater Monitoring with Passive Seismic Interferometry. Journal of Water Resource and Protection, 9, 1414-1427. doi: 10.4236/jwarp.2017.912091.
CHOLET, C., CHARLIER, J.-B., MOUSSA, R., STEINMANN, M., DENIMAL, S., 2017 – Assessing lateral flows and solute transport during floods in a conduit-flow-dominated karst system using the inverse problem for the advection–diffusion equation. Hydrology and Earth System Sciences 21, 3635–3653. https://doi.org/10.5194/hess-21-3635-2017
How to cite: Abi Nader, A., Albaric, J., Marchand, A., Gros, M., Steinmann, M., Fores, B., Vanessa, S., Pohl, B., Celle-Jeanton, H., and Sue, C.: Combining Seismology, Hydrogeology and Climatology for Monitoring Karstic Groundwater Reservoirs., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3383, https://doi.org/10.5194/egusphere-egu21-3383, 2021.
On 2-3 October 2020, the Maritime Alps were struck by storm Alex, a violent meteorological event that triggered heavy rainfall in southeast France, more generally referred to as a "Mediterranean Episode". The Mediterranean episode generated cumulative 24-hour rainfall rate locally exceeding yearly averages (>500 mm per 24 hours). The torrential rains triggered hazardous sediment-transporting floods of an intensity never documented in the area causing several casualties, and large infrastructure and economic damage.
Rain and stream gauges’ measurements during the episode are incomplete and highly uncertain due to threshold saturation and destruction of measuring devices, and changes in the stream bed. However, 11 regional seismological stations of the French permanent network recorded continuous ground shaking during and after the episode. Significant ground unrest was generated by the geomorphological phenomena providing additional information on their temporal and spatial dynamics.
Here, we present results of the combined efforts in environmental and crustal seismology to better understand the spatiotemporal dynamics of the sediment-transporting floods and hydrological forcing on the solid Earth during and after the episode. For that, we first analyze seismic power, peak frequency, and dominant noise directions of seismic signals generated by sediment-transporting floods to infer bedload transport dynamics. Moreover, by using template matching we detect 93 small earthquakes that were triggered during the Alex episode exactly in the area where rainfall was maximum. This exceptional seismic swarm is possibly triggered by overpressure due to the water load in karsts, or changes in pore fluid pressure. Our results illustrate that seismological observations allow for better understanding and quantifying of the geomorphological impact of extreme weather phenomena in mountainous settings and the related hydro-geomorphological hazards.
How to cite: Chmiel, M., Godano, M., Piantini, M., Rivet, D., Ampuero, J.-P., Gimbert, F., Bakker, M., Courboulex, F., Sladen, A., Ambrois, D., and Brigode, P.: Geomorphological impact of storm Alex in the Maritime Alps, France: what can we learn from seismological observations?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6253, https://doi.org/10.5194/egusphere-egu21-6253, 2021.
Rainfall-induced landslides may pose a significant risk to communities and infrastructures. Such landslides are substantially impacted by the fluvial systems, therefore the continuous monitoring of the seasonal erosive potentials of these rivers are crucial. However, such environmental conditions the direct in-situ investigation is often a challenging task. Therefore, the present study aims at providing a brief overview of the use of ambient seismic noise for the dynamic monitoring of fluvial systems and a discussion about the preliminary results obtained from a Brazilian case study.
Data were acquired with single short-period (2 Hz) seismometers, REFTEK-130 data-logger and GPS lock, in dry and rainy days installed within a seasonal streams in Ribeirão Contagem watershed of the Federal district of Brazil. The pre-processing of ambient noise records include conversion from REFTEK to mini-seed format and saving data in units of velocity after removing the instrumental response. Then, the frequency content (spectrograms, percentiles), waveform characteristics (envelope) and polarization attributes of changes in ambient noise wave-fields induced by bed-load transport and water flow in dry and flooding days are analyzed.
A prominent increase in mean probabilistic power spectral density (PPSD) values are observed during rainy days within a frequency range of 10 Hz to 100 Hz. The polarization analysis shows that most of the recorded energy arrived from the river side. It is concluded that seismic attributes have their relation with the river generated ambient noise and can be used for the remote monitoring of such fluvial systems. Future studies dedicated to the dense surficial and geodetic surveying (also with UAV) are recommend for the detailed quantification of these seasonal river dynamics.
Keywords: Seismic records; bed-loads; spectrograms; percentile; envelope
How to cite: Havenith, H.-B., Hussain, Y., and Maciel, S.: Fluvial Seismology: Case Study of the Contagem River (Brasilia), Brazil, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12830, https://doi.org/10.5194/egusphere-egu21-12830, 2021.
Bedload transport is the dominant fluvial mechanism shaping canyons and constitutes a significant portion of sediments transported from mountains to oceans. Monitoring of bedload flux in bedrock canyons during large magnitude floods remains an outstanding problem in fluvial geomorphology, due to extreme hydraulic conditions and the risk to equipment and human life. Surrogate monitoring methods include the interpretation of seismic and acoustic signals generated by colliding transported grains. Establishing a reliable relationship between seismic and acoustic signals and bedload flux in such floods has hitherto not been attempted. Here we present seismic and acoustic data from two pairs of adjacent channel reaches in the Liwu river, Taiwan, that differ by the concentration of boulders, but otherwise share similar hydraulic conditions and drainage area (~ 60 km2). In each of the paired locations (Shakadang and Baiyang) we have setup a field experiment where seismic sensors and data loggers with a frequency acquisition resolution of 200 Hz, were deployed aside each of the boulder-bed - boulder-free channels. In Baiyang we have also installed a hydrophone, i.e., a microphone submerged in the water column, recording acoustic signals in frequencies up to 16,000 Hz. Our monitoring system recorded a flood during August 2019 where water stage rose from 1 to 3-4 meters within few hours. In the Baiyang stations, bedload transport onset, peak and cessation were resolved through manual listening to audio files recorded by the hydrophone and counting the number of inferred impacts that occurred during one-minute time intervals. The bedload transport event lasted more than 78 hours, peaked in the recession, thus producing a counterclockwise hysteresis between the power of the acoustic signal and the water depth, not observed in the seismic signals. Signals generated by bedload impacts excited the hydrophone at frequencies of 600 to 3000 Hz, and the seismic sensor at the boulder-free stations at 18 to 30 Hz. In contrast, the highest seismic power at the boulder-bed channels peaked at a frequency band of 50 to 80 Hz, which is commonly not associated with bedload nor with water turbulence. The peak in the high frequency bands suggests that boulder-bed channels may differ in how bedload and turbulence are expressed in terms of the seismic content. We hypothesize that the high frequency content may be a combination of (i) small bedload grains colliding onto boulders, and (ii) the coupled effect of enhanced turbulence with the proximity of the seismic station to the channel.
How to cite: Nativ, R., Turowski, J., Laronne, J., Hovius, N., and Goren, L.: Joint Seismic and Acoustic Signals in a Boulder-Bed Channel along a Bedrock Canyon, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3223, https://doi.org/10.5194/egusphere-egu21-3223, 2021.
Over the last decade, seismic techniques have provided unique observational constraints on Earth surface processes. In particular, dense seismic array monitoring has recently allowed the detailed investigation of noise sources and their spatiotemporal dynamics. Despite their large potential, these approaches have not yet been applied for the monitoring of fluvial processes. In a context where traditional methods often do not provide data with adequate temporal and spatial resolution, the use of dense arrays could allow the identification and tracking of different sources of river-induced seismic ground vibrations (e.g. turbulence and bedload transport), which would provide insight in river functioning and morphological evolution.
Here, we study the potential of dense seismic array monitoring by analysing data from a 4-month long field survey, which we conducted in summer 2019 along a 600-m long braided reach of the Séveraisse river (French Alps). We installed a network of 40 to 80 seismometers on both river banks, predominantly deployed in 4-seismometer subarrays, and we supplement these seismic observations with flow gauging measurements and time-lapse imagery covering the study area. We present a preliminary analysis that focuses on a high-flow event that occurred at the end of the melt season. During this event, we observe impulsive signals that are coherently detected over the array, and which we interpret as being associated with the bedload transport of clusters of coarse grains. Through phase-delay analysis we are able to locate episodes of motion at high temporal resolution and investigate their spatiotemporal dynamics with respect to river morphology and morphological changes observed from the time-lapse images. Our work demonstrates the unique capability of using dense seismic arrays to better understand the fluvial processes that play an important role in storing and transferring sediments in braided rivers.
How to cite: Piantini, M., Gimbert, F., Bakker, M., Recking, A., and Nanni, U.: Applying dense seismic array monitoring to locate fluvial processes during floods in a braided river reach, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8800, https://doi.org/10.5194/egusphere-egu21-8800, 2021.
Seismic measurements are used to study various processes that shape the Alpine landscape, including rock falls, debris flows, bedload transport and turbulent water flow. Here, we focus on the seismic quantification of turbulent flow conditions which is particularly useful for the remote monitoring of channels that are inaccessible (e.g. subglacial conduits) and/or highly dynamic (e.g. actively braiding river reaches). We test a physically-based model (Gimbert et al., 2014) to quantify force spectra generated by turbulent flow in flume experiments performed by Lamb et al. (2017) and subsequently apply the model to estimate river flow depth from continuous seismic measurements in the field.
In the flume, we assess near-bed flow velocity spectra and resulting drag and lift force spectra experienced by particles (D=0.075-0.20 m) on the cobble bed for a wide range of channel gradients (S=0.004-0.3) and submergence levels (h/D50=1-9.6). These measurements are used to test our model, and to quantify wake (interaction) effects and fluid-dynamic admittance on force spectral amplitude. Based on the conservation of turbulent energy in the Kolmogorov inertial subrange, we predict lift and drag force spectra to within ±5 dB rel. N2/Hz (frequency ~10-25 Hz) of the measured values.
We apply the calibrated model to bank-side geophone measurements from an Alpine stream (Séveraisse River, France). Using locally-derived seismic parameters, riverbed particle-size distribution and bed roughness, we can invert for water depth over a range of flow conditions, including flows with bedload transport (bedload transport dominates the seismic signal at higher frequencies). This allows us to monitor changes in flow depth during the course of a high-magnitude flood (October 2019). During the falling limb, the inferred flow depths progressively deviate from independently made water level measurements, indicating local riverbed aggradation of approximately 0.5 m, which is in agreement with post-flood observations. Through insights in near-bed turbulent flow conditions and their seismic signature, we can study flow-bedload transport interactions and the effects of extreme flow events on river morphodynamics.
Gimbert, F., Tsai, V. C. & Lamb, M. P. (2014). A physical model for seismic noise generation by turbulent flow in rivers. Journal of Geophysical Research: Earth Surface, 119(10), 2209-2238. http://dx.doi.org/10.1002/2014JF003201
Lamb, M. P., Brun, F. & Fuller, B. M. (2017). Direct measurements of lift and drag on shallowly submerged cobbles in steep streams: Implications for flow resistance and sediment transport. Water Resources Research, 53(9), 7607-7629. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017WR020883
How to cite: Bakker, M., Gimbert, F., Lamb, M. P., and Recking, A.: Seismic quantification of river flow depth - from the flume to the field, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4322, https://doi.org/10.5194/egusphere-egu21-4322, 2021.
Environmental seismology is the discipline that uses ambient noise to detect and to measure geomorphic processes. The basic principle relies on the unique seismic signal, in terms of excited frequencies and amplitudes, generated by such processes which is then propagated and recorded to sensors (geophones). Recent developments of this technique are interesting for geomorphology because there is evidence that it can be used to study processes that are rare and difficult to measure, such as bedload transport in rivers. This is of particular importance for quantify bedload flux in proglacial streams. This paper focuses on using this method to quantify bedload export from an Alpine valley glacier. At present, there is no time-continuous measurement of bedload export in such settings. This is because objective measurement of bedload flux is a challenge task for both theoretical and practical reasons. Theoretically, the high variability of bedload transport means that measurements need to be continuous to identify when it happens and with which intensity. Practically, in order to know how to sample the signal through time, you need to know its variance a priori, which is commonly unsteady, and therefore needs to be sampled in order to know how to sample it. Direct manual sampling (e.g. with Helley-Smith samplers) have a serious disadvantage in this sense. Existing indirect methods (e.g. hydrophones and plate geophones) allow collection of continuous data but, at the same time, their installation can be difficult and expensive and they need to be carefully calibrated against manual samplings.
In the present study we used seismic data collected by out-of-stream geophones to infer bedload flux along an entire melt season (June - September) at the Glacier d’Otemma proglacial forefield, south-western Swiss Alps. Raw seismic data were inverted into sediment flux following the methodology developed in Dietze et al. (2019), to produce the first continuous dataset of bedload export from an Alpine glacier. The inversion model has been calibrated using statistical (i.e. sensitivity analysis) and direct (i.e. in situ active seismic survey) approaches.
How to cite: Mancini, D., Dietze, M., Jenkin, M., Miesen, F. M., Müller, T., and Lane, S. N.: Bedload export from an Alpine glacier inferred from seismic methods , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4000, https://doi.org/10.5194/egusphere-egu21-4000, 2021.
In mountainous areas, an increasing sediment delivery from glaciers to the channel network has been argued due to the ongoing global warming. However, quantitative estimations of sediment transport in such harsh environments are particularly challenging. A growing number of studies investigate the use of seismic techniques to perform indirect measurements of bedload transport. Seismic methods are attractive, as they can provide continuous recordings without the need of operators. Hydraulic structures equipped with geophone plates are established methods to monitor bedload in mountain rivers, but have the drawback of being expensive to install and to maintain. Seismometers installed along the channel banks have been successfully tested, but they are quite expensive too. Here, we present the application of a low-cost and easy-to-install geophone network to investigate the temporal variability of bedload transport at the snout of an Alpine debris-covered glacier.
Since 2017, we have been monitoring the upper sector of the Sulden/Solda river basin (South Tyrol, Eastern Italian Alps). The upper Sulden basin ranges in elevation between 2225 and 3905 m a.s.l., has a glacier extent of about 7 km² and is characterized by extended glacier forefields feeding the channel network with sediments. During the summer seasons, we deployed three single-component geophones (4.5 Hz) along the proglacial stream draining the Western Sulden glacier, which is heavily debris-covered. The geophones were installed at a distance of few meters from the channel, immediately downstream of the glacier snout. In 2018 and 2019, we performed monthly sampling campaigns of bedload by portable “Bunte” samplers to calibrate the seismic information. Water stage was measured using a submersible pressure transducer and pictures of the monitored area were taken every hour by an automatic camera. Meteorological data were measured at an automatic weather station located at 2825 m a.s.l., operated by the local hydrographic office. All of these complementary data were used to validate the analysis of the seismic signals.
Here, we analyze geophone data collected in the upper Sulden from 2018 to 2020 and we compare the time-frequency seismic information with air temperature and water discharge. Results show how (i) an array of single component geophones installed close to the flow path can detect both daily and longer period bedload fluctuations; (ii) geophone signal mirrors well the daily melt flow cycles, whereas its relationship with flow rate at a monthly scale varies positively, suggesting that bedload supply progressively increases during the season; (iii) there is a strong control exerted by air temperature on bedload transport, as the seismic energy reach maximum values during warm periods, while large variations of bedload rates cannot be explained in terms of differences in water discharge alone. Field evidence and direct bedload sampling campaigns performed after a glacier front collapse (August 2018) and after a small flood event (26 July 2019) confirmed such conclusions. These results prove how seismic techniques can provide precious insights into the dynamics of bedload export from Alpine glaciers.
How to cite: Coviello, V., Engel, M., Buter, A., Marchetti, G., Andreoli, A., Carrillo, R., and Comiti, F.: Seismic characterization of bedload temporal variability in a proglacial Alpine stream, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9738, https://doi.org/10.5194/egusphere-egu21-9738, 2021.
Seismic noise correlation is a broadly used method to monitor the subsurface, in order to detect physical processes into the surveyed medium such changes in rigidity, fluid injection or cracking (1). The influence of several environmental variables on measured seismic observables were studied, such as temperature, groundwater level fluctuations, and freeze-thawing cycles (2). In mountainous, cold temperate and polar sites, the presence of a snowcover can also affect relative seismic velocity changes (dV/V), but this relation is relatively poorly documented and ambiguous (3)(4). In this study, we analyzed raw seismic recordings from a snowy flat field site located above Davos (Switzerland), during one entire winter season (from December 2018 to June 2019). Our goal was to better understand the effect of snowfall and snowmelt events on dV/V measurements through both seismic and meteorological instrumentation.
We identified three snowfall events with a substantial response of dV/V measurements (drops of several percent between 15 and 25 Hz), suggesting a detectable change in elastic properties of the medium due to the additional fresh snow.
To better interpret the measurements, we used a physical model to compute frequency dependent changes in the Rayleigh wave velocity computed before and after the events. Elastic parameters of the ground subsurface were obtained from a seismic refraction survey, whereas snow cover properties were obtained from the snow cover model SNOWPACK. The decrease in dV/V due to a snowfall were well reproduced, with the same order of magnitude than observed values, confirming the importance of the effect of fresh and dry snow on seismic measurements.
We also observed a decrease in dV/V with snowmelt periods, but we were not able to reproduce those changes with our model. Overall, our results highlight the effect of the snowcover on seismic measurements, but more work is needed to accurately model this response, in particular for the presence of liquid water in the snowcover.
- (1) Larose, E., Carrière, S., Voisin, C., Bottelin, P., Baillet, L., Guéguen, P., Walter, F., et al. (2015) Environmental seismology: What can we learn on earth surface processes with ambient noise? Journal of Applied Geophysics, 116, 62–74. doi:10.1016/j.jappgeo.2015.02.001
- (2) Le Breton, M., Larose, É., Baillet, L., Bontemps, N. & Guillemot, A. (2020) Landslide Monitoring Using Seismic Ambient Noise Interferometry: Challenges and Applications. Earth-Science Reviews
- (3) Hotovec‐Ellis, A.J., Gomberg, J., Vidale, J.E. & Creager, K.C. (2014) A continuous record of intereruption velocity change at Mount St. Helens from coda wave interferometry. Journal of Geophysical Research: Solid Earth, 119, 2199–2214. doi:10.1002/2013JB010742
- (4) Wang, Q.-Y., Brenguier, F., Campillo, M., Lecointre, A., Takeda, T. & Aoki, Y. (2017) Seasonal Crustal Seismic Velocity Changes Throughout Japan. Journal of Geophysical Research: Solid Earth, 122, 7987–8002. doi:10.1002/2017JB014307
How to cite: Guillemot, A., Van Herwijnen, A., Baillet, L., and Larose, E.: Effect of snowfalls on relative seismic velocity changes measured by ambient noise correlation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12637, https://doi.org/10.5194/egusphere-egu21-12637, 2021.
Permafrost thawing affects mountain slope stability and can trigger hazardous rock falls. As rising temperatures promote permafrost thawing, spatio-temporal monitoring of long-term and seasonal variations in the perennially frozen rock is therefore crucial in regions with high hazard potential. With various infrastructure in the summit area and population in the close vicinity, Mt. Zugspitze in the German/Austrian Alps is such a site and permafrost has been monitored with temperature logging in boreholes and lapse-time electrical resistivity tomography. Yet, these methods are expensive and laborious, and are limited in their spatial and/or temporal resolution.
Here, we analyze continuous seismic data from a single station deployed at an altitude of 2700 m a.s.l. in a research station, which is separated by roughly 250 m from the permafrost affected ridge of Mt. Zugspitze. Data are available since 2006 (with some gaps) and reveal high-frequency (>1 Hz) anthropogenic noise likely generated by the cable car stations at the summit. We calculate single-station cross-correlations between the different sensor components and investigate temporal coda wave changes by applying the recently introduced wavelet-based cross-spectrum method. This approach provides time series of the travel time relative to the reference stack as a function of frequency and lag time in the correlation functions. In the frequency and lag range of 1-10 Hz and 0.5-5 s respectively, we find various parts in the coda that show clear annual variations and an increasing trend in travel time over the past 15 years of consideration. Converting the travel time variations to seismic velocity variations (assuming homogeneous velocity changes affecting the whole mountain) results in seasonal velocity changes of up to a few percent and on the order of 0.1% decrease per year. Yet, estimated velocity variations do not scale linearly with lag time, which indicates that the medium changes are localized rather than uniform and that the absolute numbers need to be taken with caution. The annual velocity variations are anti-correlated with the temperature record from the summit but delayed by roughly one month.
The phasing of the annual seismic velocity change (relative to the temperature record) is in agreement with a previous study employing lapse-time electrical resistivity tomography. Furthermore, the decreasing trend in seismic velocity happens concurrently with an increasing trend in temperature. The results therefore suggest that the velocity changes are related to seasonal thaw and refreeze and permafrost degradation and thus highlight the potential of seismology for permafrost monitoring. By adding additional receivers and/or a fiber-optic cable for distributed acoustic sensing, hence increasing the spatial resolution, the presented method holds promise for lapse-time imaging of permafrost bodies with high spatio-temporal resolution from passive measurements.
How to cite: Lindner, F. and Wassermann, J.: Single-station seismic monitoring of permafrost on Mt. Zugspitze (Germany) over the past 15 years, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9420, https://doi.org/10.5194/egusphere-egu21-9420, 2021.
Continuous long-term monitoring of the glacier is not an easy task. For the Woozle Hill ice cap near the Vernadsky Research Station, which is located on Galindez Island (Argentine Islands Archipelago), the task was solved by periodic ice sampling, GNSS measurements, photometry, and the use of GPR in the summer season. Some meteorological parameters were also periodically measured inside the ice cave in the glacier when conditions were favorable. In the past few years, GPR measurements have become more constant, and now they are carried out monthly. For continuous monitoring of the internal stresses of the glacier, we proposed using a network of seismoacoustic mini-arrays located along the perimeter of the glacier. Each array consists of four seismoacoustic sensors arranged in a cross. The length of the line between the extreme sensors reaches 100 meters. Proprietary sensors use an optical system for recording the seismic and infrasonic vibrations. The built-in microcontroller of each sensor transmits the digitized data (16 bit, 100(300) Hz) to the main unit based on the LattePanda, where preprocessing is performed. GPS receiver is also connected here for data synchronization. There is a Wi-Fi module for transmitting data to the collection station. Also, data can be transmitted to the collection station by wires installed on the cable-growth. Power is supplied 220 V through an adapter and a 12V battery. The sensors are waterproof, the rest of the equipment is assembled in a sealed waterproof box. There are three such arrays, in their turn, they form a regular triangle with a side of 700 meters, inside which there is a glacier. The processing consists of detecting signals in each array by the STA / LTA method, followed by correlation processing of the selected data fragment and calculating the azimuth to the signal, wave velocity, period, and amplitude. Also, the isolation of the coherent part of the low-intensity signal at the noise level can be carried out without preliminary STA / LTA detection, using algorithm F-statistics. Correlated interference is clipped in azimuth. The intersection of two or three azimuths allows you to locate the signal source. All parameters of detections with time stamps are recorded in the database and can be further processed using station meteorological data. The system began to be deployed around the glacier in January 2021. The presentation will present the first results of the deployed monitoring system.
How to cite: Liashchuk, L., Liashchuk, O., Zhukovsky, V., Karyagin, Y., Andrushchenko, Y., and Dovbysh, S.: The glacier seismo-acoustic monitoring system in the Ukrainian Antarctic Station region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6476, https://doi.org/10.5194/egusphere-egu21-6476, 2021.
The seismicity caused by the movement of glaciers was discovered only 30-40 years ago, and it was initially assumed that only glaciers in Greenland create this type of seismicity. Today, a significant part of the earthquakes registered by the Antarctic seismic stations are of glacial origin. In recent years, scientists' interest in studying the seismic activity of glaciers and its relationship to various environmental factors has increased due to the response of the ice mass to climate change.
The interest of studying seismicity of Antarctica has increased in the last decade with installation of a growing number of seismic stations in the region.
In 2015, with the first installation of the LIVV seismic station, Bulgarian seismologists began studying the seismicity of the Perunika Glacier, located on Livingston Island, Antarctica. Between 2015 and 2018, seismic recordings were made only in the astral summer, and from January 2020 the seismic station was installed for year-round operation. The seismic station is located near the glacier.
In this study, an approach to analyze the ice generated events recorded during all working period of the LIVV station is presented. Depending on the source mechanism and therefore the different waveform shapes, several types of icequakes and earthquakes are distinguished.
Registered icequakes are more than 16000. Its duration varies between less than a second and more than a minute. A few events are several minutes long. We have noticed that from 2015 to 2020, the number of glacier events is increasing while its duration is decreasing.
Localization of the ice generated events with duration below 1 s is calculated. In the localization procedure, a velocity model developed for the area of the seismic station is applied. The produced icequake epicenters are grouped in several clusters within the Perunika glacier. The nature of these glacier events are still studying.
Another approach to study the seismic activity of the glacier is carried out by estimating the ambient seismic noise. Frequent and spectral distribution of the power of seismic noise is made over the seismic data recorded during all working periods. It is concluded that the noise sources in the periods around 0.5 s are linked to the dynamic processes in the Perunika Glacier. Some relationship between the change in the noise power in the 0.2-0.6s period band and tidal cycles has been found.
Acknowledgment: The presented study is supported by project: No 70.25-171/22.11.2019 “Study the activity of the Perunika glacier during year-round deployment” funded by the National Center for Polar Studies, Bulgaria.
How to cite: Georgieva, G., Dimitrova, L., and Dragomirov, D.: Approach to study the seismicity in the Perunica Glacier, Livingston Island, Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7830, https://doi.org/10.5194/egusphere-egu21-7830, 2021.
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