Displays

Our understanding of subsurface processes suffers from a profound observation bias: ground-motion sensors are rare, sparse, clustered on continents and not available where they are most needed. A new seismic recording technology called distributed acoustic sensing (DAS), can transform existing telecommunication fiber-optic cables into arrays of thousands of sensors, enabling meter-scale recording over tens of kilometers of linear fiber length. DAS works in high-pressure and high-temperature environments, enabling long-term recordings of seismic signals inside reservoirs, fault zones, near active volcanoes, in deep seas or in highly urbanized areas.

In this talk, we will introduce this laser-based technology and present three recent cases of study. The first experiment is in the city of Stanford, California, where DAS measurements are used to provide geotechnical information at a scale normally unattainable (i.e., for each building) with traditional geophone instrumentation. In the second study, we will show how downhole DAS passive recordings from the San Andreas Fault Observatory at Depth can be used for seismic velocity estimation. In the third research, we use DAS (in collaboration with Fujitec) to understand the ocean physics and infer seismic properties of the seafloor under a 100 km telecommunication cable.

How to cite: Spica, Z., Akuhara, T., Beroza, G., Biondi, B., Ellsworth, W., Lellouch, A., Martin, E., Nishida, K., Pétrélis, F., Perton, M., Shinohara, M., Yamada, T., and Yuan, S.: Distributed acoustic sensing for seismic monitoring in challenging environments , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1673, https://doi.org/10.5194/egusphere-egu2020-1673, 2020.

iXblue company develops technologies to listen and image the Earth dynamics. Among them, Echoes high-resolution sub-bottom profilers, Seapix 3D multibeam echosounder, Canopus transponder and blueSeis rotational seismometers are particularly useful for imaging and monitoring marine and continental volcanic activities. Here, we present recent implementations and acquisitions of those systems, demonstrate the great potential of these technologies to record present and past volcanic dynamics in Hawaii, Stromboli, Sicilia and Eifel region, and emphasize their benefits to better anticipate volcanic hazard.

The Hawaii island experienced a dramatic volcanic crisis during the summer of 2018. To demonstrate the potential of observing the complete ground motion in the near field of seismic sources, Geophysical Observatory (LMU, Munich, Germany), in cooperation with USGS Hawaiian Volcano Observatory (USA), installed a high sensitive rotational motion sensor (blueSeis-3A) near the erupting crater returning spectacular data for almost daily M5 seismic events due to the collapse of the caldera. BlueSeis-3A, based on fiber optical gyroscope technology, at very close distance from the Stromboli volcano in 2016 and 2018, was installed together with classical instrumentation (i.e., translational seismometer, infra sound and tilt meter) and recorded four weeks of permanent strombolian activity at Stromboli during these two experiments. The resulting six axis measurements reveal clear rotations around all three-coordinate axis. We are furthermore able to demonstrate how these six component measurements can help to improve solving the inversion problem on large and complex system like volcanoes.

Eight Canopus transponders are involved in an ERC project in underwater geodesy, the FOCUS project headed by IUEM laboratory (Brest, France). Together with a 6 km-long optical fiber deployed across the trench at the base of the Etna volcano, two groups of four Canopus will be installed on tripods each side of the trench at 1500-2000 m of water depth. This will help quantify the speed of the southeastern flank collapsing of Etna volcano into the Ionian Sea.

In collaboration with French, Belgian and German geoscience laboratories, Echoes 10 000 (10 kHz) sub-bottom profiler and Seapix 3D multibeam echosounder, both installed on the kiXkat cataraft and remotely controlled, were mobilized to produce images of the water column and sediments of a lake formed in a volcanic crater in Germany (Laacher See). By using Seapix to obtain backscatter profiles of elements in the water column, it was possible to clearly distinguish fish and gas bubbles, which demonstrates a potential for the development of an automatic gas detection module using the Seapix software. Meanwhile, the Echoes 10 000 provided high-resolution images of the architecture of the lake deposits and visualized in real time using Delph Software. More than 30 m of penetration with a theoretical 8 cm-resolution highlight paleoenvironmental and paleoclimatic reconstruction perspectives and 3D modeling of remobilized materials and tephra deposits from volcanic activity.

How to cite: Jouve, G., Guattari, F., Laudat, T., Olivier, N., Pelletier, H., Ripepe, M., Igel, H., Wassermann, J., Bernauer, F., Braun, T., Caudron, C., and Gutscher, M.-A.: Listening the Womb of the Earth: iXblue sonars, transponder & rotational seismometers for extreme environment imaging & monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18086, https://doi.org/10.5194/egusphere-egu2020-18086, 2020.

Detecting seismic signals and identifying their origin is more and more used for understanding environmental activity. This usually depends on a good signal/noise ratio (S/N), especially for the more distant sources.

A test area for detection and identification is the urban setting of the University of Vienna, a challenging environment with more than 4000 strong-acceleration events per day. These repetitive noise events would normally classify the site as "too noisy" for any advanced earthquake research.

With the real-time open database from Wiener Linien it is possible to attribute many of the repetitive seismic signals (e.g. on a Raspberry Shake Citizen Science Station) to the surrounding trams and train lines. The detection challenge was initiated in a Citizen Science Hackathon, where public interest sparked this research. The available train schedule and more than one year of continuous seismic records is sufficient to train and test a machine learning classifier which finds most characteristic features in the signals of commuter trains and trams, such as the energy in each frequency band.

The labeled dataset can be used to train our detection algorithm to find similar signals and to help determine whether a certain signal is present or not. An additional second seismic Raspberry Shake sensor is installed in the vicinity, to further constrain the directionality of the trains.

Studying the vibrations of train signals and solving the classification task of these repetitive patterns first can help develop robust methods
for seismically loud environments, and might lead to the detection of lower magnitude events such as regional earthquakes or landslides. 

How to cite: Hein, G., Novoselov, A., Fuchs, F., and Bokelmann, G.: Matching seismic activity with potential sources using machine Learning , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1519, https://doi.org/10.5194/egusphere-egu2020-1519, 2020.

Runoff-generated debris flow has hazardous implications for downstream communities and infrastructure in alpine landscapes. Our understanding of fluid mechanisms of debris flows is very limited, in part, by a lack of direct observations and measurements. Seismic ground motion-based observations provide new constraints on debris flow physics, but it is still not widely applied due to the missing of validated inversion models for interpreting the impact force which generates seismic ground motion. Here we propose a physical model for the high-frequency spectral distribution of impact force signal generated by debris flows. Then we present a new inversion model based on the physical model for the impact force signal and apply this to the devastating debris flows in Dongchuang, China, on 25 August 2004. The amplitude and frequency characteristics of the impact force data can enable the estimation of grain size, sediment concentration, and sediment flux. Results suggest that in-situ data from three sensors could have provided a reconstruction of sediment flux profile in the vertical direction. Meanwhile, an inversion model designed for debris flows impact force would potentially provide hydrodynamics information as well.

How to cite: Tang, H., Yan, Y., and Hu, K.: Deriving sediment transport information from debris-flow impact force signals, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13054, https://doi.org/10.5194/egusphere-egu2020-13054, 2020.

Algorithms for the detection and extraction of river planforms from remotely sensed images are of great interest to numerous applications including land planning, water resource monitoring, and flood prediction. Synthetic Aperture Radar (SAR) is a very promising modality for river monitoring and analysis as it can provide high resolution imagery regardless of weather conditions and the day/night cycle.

In this work we present an algorithm for the detection and segmentation of rivers in SAR images, with emphasis on accurate riverbank extraction. The algorithm utilises a novel superpixel segmentation algorithm that segments the image into perceptually uniform clusters of pixels based on a modelling of the SAR data with the Generalised Gamma Distribution.

The generated superpixels adhere to the edges of objects in the image (such as riverbanks) with great accuracy. Superpixels are then characterised according to several features that describe their statistical and textural properties which allows for the discrimination between river- and land-cover superpixels. The river-forming superpixels are then grouped together using unsupervised agglomerative clustering to produce river planform masks.

We demonstrate our proposed method on high resolution SAR images from the SENTINEL-1 and ICEYE platforms. Future work will focus on incorporating more complex heuristics for the identification of false positives and to circumvent apparent river discontinuities (e.g. bridges), as well as on the release of a toolbox providing open access to the geosciences community.

How to cite: Pappas, O., Adams, B., Anantrasirichai, N., and Achim, A.: Extraction of River Planforms from Synthetic Aperture Radar Imagery using Superpixel Classification, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10080, https://doi.org/10.5194/egusphere-egu2020-10080, 2020.

Water is a critical resource that can range from being either available in short supply or excess, causing floods. In many locations the majority of this supply is underground. In some geological terrains such as karst these underground systems transport water primarily through crack or conduit flow. Determining the subsurface locations of the dominant flowing structures and their flow rates in such karst systems is a significant challenge. The details of these complex flow networks can, for example, have a first-order control on water supply, surface floods and the locations of seasonal lakes. Current geophysical methods focus on active geophysical imaging of karst structures but usually fail in determining if such structures are flowing. In this work, we take a different approach locating flowing conduits in Irish karst via a multi-method analysis of ground vibrations from temporary deployments of passive seismic sensors. We start by testing the methodology on surface rivers.

Hydrological processes including turbulent water flow and sediment transport create ground vibrations that can be detected on seismic stations. In the initial test, we deployed two small aperture arrays of 4 and 6 three-component (3C) short-period seismometers and a short linear array beside a river with a typical flow rate of 25 m3/second. We see clear spectral peaks associated with water flow at frequencies of 10 to 40 Hz. We locate the sources for these frequency bands using both conventional beamforming array analysis and an Amplitude Source Location Method (ASLM). Before ASLM, we constrain the velocity based on array analysis. Both methodologies perform well in determining the known locations of rapid flow in the river. We then move to a test karst location where the subsurface pathways of large conduits are known through cave dives. We deploy 3C short period seismometers for a few hours. Again we see clear peaks in the seismic spectra which, using ASLM and Frequency-Dependent Polarization Analysis (FDPA), located close to the known conduits. In the station close to a known conduit, we see sustained very high-frequency signals which are in agreement with numerical simulation of crack dominated flow for secondary short narrow cracks. This work is the prelude to a larger seismic nodal deployment that will take place in the winter/spring of 2020 in the same location. Initial results from that experiment will also be presented.

How to cite: Karbala Ali, H., Bean, C., Craig, D., Li, K. L., O’Brien, G., Hickey, C., and O'Keeffe, B.: Tracking surface and subterranean water flow using continuous seismic tremor, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20833, https://doi.org/10.5194/egusphere-egu2020-20833, 2020.

One current concern in climate science is the estimations of the amount of ice loss by glaciers each year and the corresponding rate of sea level rise. Greenland ice sheet contribution is significant with about 30% to the global ice mass losses. Ice loss in Greenland is distributed approximately equally between loss in land by surface melting and loss at the front of marine-terminating glaciers that is modulated by dynamic processes. Dynamic mass loss includes both submarine melting and iceberg calving. The processes that control ablation at tidewater glacier termini, glacier retreat and calving are complex, setting the limits to the estimation of dynamic mass loss and the relation to glacier dynamics. It involves interactions between bedrock – glaciers – icebergs – ice-mélange – water – atmosphere. Moreover, the capsize of cubic kilometer scale icebergs close to a glacier front can destabilize the glacier, generate tsunami waves, and induce mixing of the water column which can impact both the local fauna and flora.

We aim to improve the understanding of iceberg capsize using a mechanical modeling of iceberg rotation against the glacier terminus, constrained by the generated seismic waves that are recorded at teleseismic distances. To achieve this objective, we develop a fluid-structure interaction model for the capsizing iceberg. Full scale fluid-structure interaction models enable accurate simulation of complex fluid flows in presence of rigid or deformable solids and in presence of free surfaces. However, such models are computationally very expensive. Therefore, our strategy is to construct a simple solid dynamics model involving contact and friction, whose simplified interaction with water is governed by parametrized forces and moments. We fine tune these parametrized effects on an iceberg capsizing in contact with a glacier with the help of reference direct numerical simulations of fluid-structure interactions involving full resolution of Navier-Stokes equations. We assess the sensitivity of the glacier dynamics to the glacier-bedrock friction law and the conditions for triggering a stick-slip motion of the glacier due to iceberg capsize. The seismogenic sources of the capsizing iceberg in contact with a glacier simulated with our model are then compared to the recorded seismic signals for well documented events.

How to cite: Bonnet, P., Yastrebov, V., Leroyer, A., Queutey, P., Mangeney, A., Castelneau, O., Stutzmann, E., Montagner, J.-P., and Sergeant, A.: Modelling the source of glacial earthquakes for a better understanding of the impact of iceberg capsize on glacier stability, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7033, https://doi.org/10.5194/egusphere-egu2020-7033, 2020.

How to cite: Wenner, M., Walter, F., Allstadt, K., McArdell, B., and Lockhart, A.: What ground tilt tells us about debris flow parameters, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-728, https://doi.org/10.5194/egusphere-egu2020-728, 2020.

Normalized Difference Water Index (NDWI) has been widely used to detect water bodies and enhance them in the satellite imagery. In order to determine water bodies in Landsat TM, Mid-Infrared and Green bands are used but this combination is often encountered with vegetation, soil and build-up land noises and the water bodies area was not calculated accurately and most of the time the results are higher than the actual area and was overestimated, NDWI does not remove soil and vegetation noises completely because of using the NIR band reflection, therefore, to eliminate these noises, Modified Normalized Difference Water Index (MNDWI) with different bands in Landsat TM such as Shortwave and Near-Infrared bands has been used and best image that shows water bodies more accurate has been provided. We need to test different band combination and also different NDWI and MNDWI indexes in the range of Red, Near-Infrared, Shortwave Infrared and Mid-Infrared to determine the best performing index. For this purpose, Gorganroud river basin was selected as study area, which is located in north-east of Iran and is one of the largest rivers in Iran and because of 2 dams located in the river basin and long distance of river, studying water bodies could be easier in comparing with other river basins of Iran. we compared NDWI and MNDWI indices and results shown that MNDWI index using Landsat TM bands Green and Mid-infrared has higher accuracy than NDWI and other calculated indices with different bands of Landsat TM. It can remove the vegetation, soil and build-up noises better than NDWI and water bodies can be shown clearly. The MNDWI is more suitable to extract water bodies and study the information of water regions with dominating the soil, vegetation and build-up land noises because of its advantage in reducing or even removing those noises over NDWI.

Key words: Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Landsat 5, water bodies, Gorganroud river basin

How to cite: eishoeei, E. and Miryaghoubzadeh, M.: Capability assessment of two water indexes in remote sensing data in order to water bodies classification (case study: Gorganroud River - North east of Iran), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1135, https://doi.org/10.5194/egusphere-egu2020-1135, 2020.

The IRIS/PASSCAL Instrument Center is installing 5 seismic stations around the summit of Mt. Erebus, Antarctica. IRIS is funded by the National Science Foundation to install and maintain these stations long-term, a task undertaken by the Polar team at PASSCAL. The purpose of the network is to provide a baseline measurement of volcanic events and act as a fiducial array for future experiments. Each station’s instrument package comprises a data logger recording a broadband and strong-motion seismometer, and a separate data logger recording an infrasound sensor. Station state of health and near real-time data are transmitted via Iridium modems.

The Mt. Erebus network is installed between 2000 m and 3400 m elevation spaced around the volcano summit. This is a particularly harsh environment for operating autonomous seismic stations with extreme low temperatures and high winds. Station power systems need to have enough capacity to winter-over for roughly 6-months without recharge. Station enclosures need to provide sufficient insulation to keep the data logger within its temperature operating range.

To design these stations for long term, 365/24/7 operation, we leveraged proven station enclosure and power system designs developed over the last 12 years of PASSCAL engineering seismic systems for Antarctica. The Mt. Erebus station design is modular and standardized, separating the bulk of the power storage and electronics' enclosures, allowing for streamlined upgrades or additions without having to overhaul the entire station. Power for the system will rely on lead acid batteries and solar charging; forgoing higher efficiency primary lithium thionyl chloride batteries used elsewhere in Antarctica, to reduce long-term station costs.

Station health will be monitored at IRIS/PASSCAL and low sample rate (20 sps) broadband data will be captured in near-real time. Higher sample rate data are recorded locally and collected annually during the austral summer. All data will be available from the IRIS Data Management Center.

How to cite: Beaudoin, B., Arnell, K., Carpenter, P., Lingutla, N., Meyers, J., Nikolaus, K., and Roth, A.: Environmentally hardened, high-altitude, high-latitude seismic stations on Mt. Erebus, Antarctica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1950, https://doi.org/10.5194/egusphere-egu2020-1950, 2020.

Southeastern Mongolia has limited access due to its extreme environments (long and harsh winter) and lack of infrastructure (e.g., road). Satellite remote sensing technique is one of the most effective methods to get geological information in areas where field survey is difficult. WorldView-3 (WV3), launched in August 2014, is high-spatial resolution commercial multispectral sensor developed by DigitalGlobe. WV3 measures reflected radiation in eight visible near infrared (VNIR) bands between 0.42 and 1.04 ㎛ and in eight short-wave infrared (SWIR) bands between 1.20 and 2.33, which have 1.24- and 7.5-m spatial resolution, respectively. In this study, WV3 VNIR and SWIR data were used to identify and map the various minerals in the Ikh Shankhai porphyry Cu deposit district, Mongolia.

The Ikh-Shankhai porphyry Cu deposit is located within Gurvansayhan island arc terrane in southeastern (SE) Gobi mineral belt, Mongolia. The Ikh-Shankhai district include the porphyry system containing Cu-Au with primary chalcopyrite, which is classified into disseminated type and stockwork quartz type. This district consists of Late Devonian-Early Carboniferous andesite, tuff and siltstone intruded by Carboniferous-Permian granite, granodiorite and granodiorite porphyry.

The WV 3 data were analyzed using mixture-tuned-matched filter (MTMF) which locates a known spectral signature in the presence of a mixed or unknown background. MTMF does not require knowledge of all of the spectral endmembers and is suited for used where materials with distinct spectral signatures occur within a single pixel. From the WV3 analysis result using mixture-tuned-matched filter (MTMF), we identified the location and abundance of alteration minerals. Advanced argillic minerals (alunite, kaolinite (or dickite), and pyrophyllite) were dominant in the lithocaps of the Budgat and Gashuun Khudag prospects; whereas, phyllic (illite) and propylitic (calcite and epidote) minerals were dominant in the areas surrounding the lithocaps. In addition, the distribution of ferric minerals (hematite and goethite) was mapped because of the oxidation of pyrite. Field work at the Ikh-Shankhai porphyry Cu district to evaluate the accuracy of the mineral mapping results was carried out in August, 2018. Reflectance spectra acquisition using a portable ASD TerraSpec Halo mineral identifier (the attached GPS covered a spectral range of 0.35 – 2.5 µm) was conducted in the altered outcrops of the Ikh-Shankhai porphyry Cu district. Mineral mapping results compared well with the field spectral measurements collected for the ground truth and demonstrated WV3 capability for identifying and mapping minerals associated with hydrothermal alteration. Evaluation of the WV3 mineral mapping results using ground truth data indicates, however, a difficulty in mapping spectrally similar minerals (e.g., kaolinite and dickite) due to spectral resolution limitation.

How to cite: Youngsun, S. and Kwang-Eun, K.: Mineral mapping at the Ikh Shankhai porphyry Cu deposits, Mongolia using WorldView-3 data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2359, https://doi.org/10.5194/egusphere-egu2020-2359, 2020.

Impact sensors are increasingly used to indirectly monitor bedload transport in streams. Among them, the Swiss geophone impact plate system has notably proved its efficiency to continuously record bed load transport rates. Nevertheless, this approach still requires a robust calibration of the sensors to transform the relative signal of the geophones into an absolute mass of sediment in transport. Typically, the calibration is performed through the sampling during natural bedload transport events of all the particles that impact the plates, in order to build up rating curves between the signal recorded by the geophone sensors and the characteristics of the sediment that impact them (e.g. mass, grain size).  To better understand the system behavior it is important to quantify to what extent the signal response is similar (i) between sensors of a same geophone measuring station and (ii) between different geophone measuring stations. Also (iii), the amount of signal that propagates from impacted plates towards non-impacted plates (or ‘neighbouring noise’) needs to be quantified to improve the understanding of the system.

In this study, we investigate the above three elements by performing an impact experiment on the Swiss geophone plate system, and systematically record the signals produced at different plates by defined impacts of similar magnitude, and how the signal (maximum amplitude) propagates through neighbouring non-impacted plates. Each Swiss Geophone Plate of four measuring stations in the Swiss Alps – Vallon de Nant (VD), Albula (GR), Naviscence (VS) and Riedbach (VS) – were hit alternatively with impacts of increasing magnitude, and the signal they produced was systematically recorded over all the sensors of a given measuring station. Results of the study allow (i) to quantify the neighbouring noise that propagates from impacted plates towards non-impacted plates; (ii) to evaluate the attenuation rate of the signal for an impact of a given magnitude and (iii) to evaluate the variability in the propagation of neighbouring noise between sensors at a given measuring station and between different measuring stations.

How to cite: Antoniazza, G., Nicollier, T., Wyss, C. R., Boss, S., and Rickenmann, D.: Swiss Geophone Plate system: Quantification of the variability of signal response and of the signal propagation across plates using field-based impact experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2445, https://doi.org/10.5194/egusphere-egu2020-2445, 2020.

Rock hazard is a common geohazard event that occurs in the orogenic mountain belt and often causes the destruction of road and casualties. The steep topography, fractured bedrock and frequent earthquakes favor to happen. Those are usually fast and unpredictable, leading a lack of direct observation of physical process. Recent seismological studies highlighted the rock hazard induced seismic signals could improve understanding of its dynamics. This study focuses on the three provincial highways that cross the Taiwan Island from east to west. The regions along the highways have the complexity in tectonic structure and extreme climate-forced erosion, causing the hazard frequently occurred. In order to understanding seismic features and physical process of rock hazard, we conducted a series of seismic analyses using the seismic records collected form regional seismic network for ten events, which were reported by the government agency. Four of them have the video recordings, which would be helpful to understanding the relationships between physical process (falling, rolling, bouncing and fragmentation), movement type (fall, topple, slump, slide, avalanche or complex) and seismic features. We developed the hybrid method of determination of geohazard event location (GeoLoc) that combines the cross-correlation-based method and the amplitude-attenuation-based approach. We apply the GeoLoc scheme to locate the events recorded by the seismic station with epicentral distance ranging from 2 to 56 kilometers (km) and it helps to reduce the location error. The leading seismic signals of the mass detachment linked to the crack propagation or slope response can be observed, and we also found that the seismic feature caused by fragment of rock block exhibits the higher frequency than the seismic signals corresponding to impaction of rock particles. Our results highlight the possibility of the seismic technique for locating rock hazards distributed along highways in a regional scale and further understanding its physical process. The aforementioned results would be helpful to build the near-real-time monitoring system along the highways for hazard mitigation of events.

How to cite: Chang, J.-M., Chao, W.-A., and Chen, H.: Locating the rock hazard and understanding its physical process using seismic signals, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3357, https://doi.org/10.5194/egusphere-egu2020-3357, 2020.

Following the large June 17 2017 landslide in Karrat Isfjord, Central West Greenland the necessity to differentiate between different kinds of seismological events has become relevant for hazard assessment. Greenland is the origin of a many different kinds of seismic signals.  In addition to the than a thousand small to moderate magnitude tectonic earthquakes, most of them ranging between ML 1.0 and 3.0 are located along the coasts of Greenland every year, many other non-tectonic events are located. This is largely possible thanks to the data collected and distributed by the Greenland Ice Sheet Monitoring Network (GLISN) federation and its members (glisn.info). The non-tectonic events include cryo-generated events, and signals from landslides as for example illustrated by the globally seen seismological signal from the Karrat 2017 landslide. It is possible to separate tectonic events from non-tectonic events, based on the characteristics of the seismological signal alone, but the signals from cryo-generated events and landslides have many similar features. In the Karrat Isfjord area, several large glaciers terminate in the sea where for example calving generate seismological events. With poor location resolution due to large station spacing in the remote areas of Greenland, the differences in the seismological signals are important to determine the cause of the events.

How to cite: Dahl-Jensen, T., Larsen, T. B., and Voss, P. H.: Non-tectonic seismological events in Greenland - Cryo-generated events and landslides, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6680, https://doi.org/10.5194/egusphere-egu2020-6680, 2020.

Rock falls are important agents of erosion shaping the topography of bedrock slopes. Despite the considerable attention rock falls get when causing damage we still lack detailed information about the triggers, lag times, seasonal and elevation-dependent rock fall occurrence. This is due to the difficulty in observing rockfalls directly as the mobilisation of rock masses occurs rapidly, infrequently and distributed at a priori unknown locations. To identify seasonal and elevation-dependent rock fall activities and characteristics and their environmental drivers and triggers in an alpine setting, we have operated a monitoring network to detect and classify rock falls in the Reintal valley, German Alps, since 2014. The Reintal is an Alpine valley in the Wetterstein massif close to the Zugspitze, Germany’s highest mountain. The Reintal observatory produces nearly continuous datasets of seismic, meteorological and camera data. To our knowledge, these datasets are one of a few that permit a systematic study of rockfall patterns and their controls over a period of several years in an alpine setting.

In this contribution, we present the layout of the observatory and the instrumental network. Six seismometers record the motion of the ground; different types of seismic signals are shown and their sources discussed. This is done in combination with the meteorological data of the two weather stations in the valley and the images of the optical and infrared cameras of the observatory. We evaluate the performance, limitations and capabilities of the observatory. In addition, we discuss how we dealt with challenges such as power consumption of the instruments in the field, data storage and data loss. Our experience with the set-up and maintenance of the observatory can help guide the design and construction of other observatories in mountain environments.

How to cite: Schöpa, A., Hovius, N., and Turowski, J.: Set-up and performance evaluation of a seismic rock fall observatory in the Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14290, https://doi.org/10.5194/egusphere-egu2020-14290, 2020.

Here, we present data from lahars through the use of a 3-component broadband seismometer, accelerometer, and a video camera installed 3 m from the Lumbre channel on Volcán de Colima, Mexico to understand rheology differences within multiple events, which occurred in late 2016. We used a combination of peak frequency content, directionality, and video analysis to determine rheology changes amongst the multiple events. Our findings show that different peak frequency patterns in each seismic component correspond to differing rheologies and flow processes. For instance, in the vertical and flow parallel directions the transition from streamflow to lahar coincides with a narrow frequency distribution to wide. Conversely, the cross-channel frequency content is opposite with streamflow portraying a wide frequency distribution transitioning to a narrow distribution with the lahars. Furthermore, there is a drop in overall peak frequencies when transitioning from streamflow to lahar. The directionality ratios computed further yielded evidence for a rheologic change between streamflow and lahar. Directionality ratios >1 were calculated for each lahar, and <1 for streamflow. We go on to show that componential analyses yielded channelization or freedom of movement in the cross-channel, bedload transport in the flow parallel, and channel geology in the vertical direction are possibly the main drivers in the peak frequency output of debris flows.

How to cite: Walsh, B., Coviello, V., Capra, L., Procter, J., and Márquez-Ramirez, V.: Geophysical insights on the internal dynamics of lahars from Lumbre channel, Volcán de Colima, Mexico, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9528, https://doi.org/10.5194/egusphere-egu2020-9528, 2020.

Rockfalls affect steep slopes in several geographic regions. Different systems from remote to in-situ instruments are used for their detection and study. In this scenario, seismic signals produced by the detachment, bouncing, and rolling of rockfalls are being increasingly used for the detection and classification of such events. This is typically done by using different manual, semi-automatic and/or automatic signal processing strategies. In this work, we applied a new Deep Learning (DL) algorithm in order to test the performance on the automatic classification of seismic signals. We applied the method to seismic data acquired by a low-cost Raspberry Shake 1D seismometer (sampling rate 50Hz) in order to discriminate rockfall from not-rockfall events occurred at the Moosfluh active slope region in Wallis (CH). Here we present the methodology and show the results obtained on a continuous record of more than 2-years of seismic data. The performance accuracy of the DL approach reached values larger than 90%. Our results show that the application of DL strategies in this context can be very useful and save time on seismic data classification.

How to cite: Dazzi, N., Manconi, A., Prakash, N., and Bickel, V.: Classification of Seismic Events with Deep Learning Strategies: Insights from the Moosfluh Landslide, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9734, https://doi.org/10.5194/egusphere-egu2020-9734, 2020.

Sediment transport processes and fluxes play a key role in fluvial geomorphology and hazard triggering. In particular, extreme floods characterized by highly concentrated flows set the pace of mountain landscape evolution, where the linkage between streams and sediment sources leads to strong solid inputs characterized by significant grain sorting processes. The main observation that river processes generate ground vibrations has led to the application of seismic methods for monitoring purposes, which provides an innovative system that overcomes traditional monitoring difficulties especially during floods. Mechanistic models have been proposed in the attempt to invert river flow properties such as sediment fluxes from seismic measurements. Although those models have recently been validated in the laboratory and in the field for low transport rates, it remains unknown whether they are applicable to extreme floods.

Here we carry a set of laboratory experiments in a steep (18% slope) channel in order to investigate the link between seismic noise and sediment transport under extreme flow conditions with highly concentrated sediment flows. The originality of this set-up is that instead of feeding the flume section directly as usually done, we feed with liquid and solid discharge a low slope storage zone connected to the upstream part of the steep channel. This allows us to produce sediment pulses of varying magnitude (up to the transport capacity) and granulometric composition, traveling downstream as a result of alternate phases of deposition and erosion occurring in the storage area. We measure flow stage, seismic noise, sediment flux and grain size distribution. We find that the previously proposed relationships between seismic power, sediment flux and grain diameter often do not hold in such sediment transport situations. We support that this is due to granular interactions occurring between grains of different sizes within the sediment mixture and leading to complex grain sorting processes. In particular, we observe that bigger grains do not directly impact the bed but rather roll over fines or smaller grains, such that observed seismic power is much lower than expected. These results constitute a starting point for the development of a new mechanistic model for seismic power generated by highly concentrated bedload sediment flows.

How to cite: Piantini, M., Gimbert, F., Recking, A., and Bellot, H.: Testing seismic noise caused by highly concentrated sediment flows in laboratory experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9797, https://doi.org/10.5194/egusphere-egu2020-9797, 2020.

How to cite: Moores, A., Townsend, B., Pigeon, S., and Somerville, T.: A Versatile and Complete Technology Platform for Autonomous Ocean Bottom Seismometry , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12051, https://doi.org/10.5194/egusphere-egu2020-12051, 2020.

Heatwaves are extended periods of extremely hot weather and high temperature that have a major impact on human health, socioeconomics and natural systems. As predicted by climate models, ongoing global warming will potentially increase the incidence, intensity and duration of summertime heatwave events. Nevertheless, heat-related health impacts are largely preventable if populations, health and social care systems and public infrastructure are prepared. Therefore, this is plausible if heatwave events are studies for which heatwave real-time monitoring and assessment are central components. It is well recognized that land surface temperature retrieved by satellite sensors is an important variable associated with heatwaves and surface warming research. Land surface temperature retrieved by satellite sensors can be observed spatially and temporally, adequate for applications needing real-time and continuous measurements in quick response. In this study, Chinese Fengyun satellite data were used to monitor the land surface thermal environment during the heatwave event in Belt and Road communities. Split-window algorithm were applied to retrieve land surface temperature from thermal sensor. Spatial temporal distributions of Land surface high temperature are monitored in West Europe, India, and Australia as examples during their high temperature weather. The result shows that monitoring the real-time heatwave hazards in quick responds help provided information to the decision makers and get insight into the thermal environment characteristics over urban areas.

How to cite: Xu, R.: Land Surface High Temperature Monitoring in Belt and Road Communities, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13486, https://doi.org/10.5194/egusphere-egu2020-13486, 2020.

Operators of broadband seismic stations, particularly in hostile locations, are restricted in experiment design and deployment time-frames by the significant constraints of historical instrumentation. Manufacturers need to move away from the strict requirements on tilt tolerance and associated performance compromises, fixed frequency responses, unfriendly interfaces, slow data downloads and power-hungry systems in favour of simple, flexible and smart instruments that allow the operator to focus on the science at hand.

This transition is already happening with the evolution of seismic monitoring towards compact technologies: rapid-response deployments have, in recent years, become more and more feasible. However, installing low-noise, broadband instruments in remote areas has remained a challenge: low-noise force-balance broadband seismometers are typically heavy and delicate. They require significant infrastructure and logistics.

By developing the standalone, compact Certimus - with the same level of performance as traditional force-balance broadband seismometers - Güralp now offers researchers the opportunity to further push the boundaries of seismic monitoring and deploy stations in more and more challenging environments.

Unique sensor components allow Certimus to function up to 90 degrees tilt, removing the need for time-consuming centring, and allowing the station to be placed in small, hand-dug shallow holes. In 1s mode, the sensor will settle quickly and reliable data can be available in a matter of hours.  The frequency range is fully configurable in the long-period corner to allow this level of flexibility: 120s, 10s and 1s to 100Hz.

Certimus offers easy ways to check installation integrity – State-of-Health and live waveforms – before leaving the site: both with the surface and the burial variants, either via Bluetooth, LCD screen or Web Interface.

Since power consumption is a major limitation, Certimus comes with an ultra-low power mode (under 300mW) and a rugged battery module to gain up to six weeks of data before retrieval – or before a permanent power supply is arranged.

All files are recorded in industry standard miniSEED format making data download and management simplistic and universal. The metadata auxiliary channels record a vast range of state of health parameters to ensure optimal qualification of the seismic data with the environmental conditions of the seismic station.

All these advanced features are gathered in a compact, lightweight case that can be carried with all its accessories in a backpack to the most inaccessible areas. Quality seismic data is made available swiftly from anywhere, anytime.

How to cite: Balon, M., Filippi, S., Mohr, S., Hill, P., and Watkiss, N.: Certimus, a seismic station optimized for rapid deployment in rugged terrain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18637, https://doi.org/10.5194/egusphere-egu2020-18637, 2020.