GI1.2
New frontiers of multiscale monitoring, analysis, modeling and decisional support (DSS) of environmental systems

GI1.2

New frontiers of multiscale monitoring, analysis, modeling and decisional support (DSS) of environmental systems
Co-organized by EMRP2/NH8/NP8/SSS10
Convener: Pietro Tizzani | Co-conveners: Francesca Bianco, Antonello Bonfante, Raffaele Castaldo, Nemesio M. Pérez
vPICO presentations
| Wed, 28 Apr, 09:45–10:30 (CEST)

vPICO presentations: Wed, 28 Apr

Chairpersons: Pietro Tizzani, Antonello Bonfante, Raffaele Castaldo
09:45–09:50
5-minute convener introduction
09:50–09:52
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EGU21-11023
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ECS
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Highlight
Modelling ground deformation in Tenerife (Canary Islands) during 2003-2010 
Monika Przeor, Luca D'Auria, Susi Pepe, and Pietro Tizzani

Tenerife is the biggest island of the Canaries and one of the most active from the volcanological point of view. The island is geologically complex, and its main volcano-tectonic features are three volcanic rifts and the composite volcanic complex of Teide-Las Cañadas. The latter is located in the central part of the island at the intersection of Tenerife principal rifts. Teide volcano, with its 3718 m of elevation constitutes the most prominent topographical feature of the island. Being a densely populated active volcanic island, Tenerife is characterised by a high volcanic risk. For this reason, the island requires an advanced and efficient volcano monitoring system. Among the geophysical parameters that could be useful to forecast an oncoming volcanic eruption, the ground deformation is relevant for detecting the approach of magma to the surface.

This study aim is to analyse the ground deformation in the surroundings of the Teide-Las Cañadas complex.  For this purpose, we studied the ground deformation of Tenerife by using a set of Synthetic Aperture Radar (SAR) images acquired between 2003 and 2010 by the ENVISAT ASAR sensor and processed through a DInSAR-SBAS technique. The DInSAR SBAS time series revealed a ground deformation in the central part of the island, coinciding with the Teide volcano. A similar deformation was already evidenced by Fernández et al. (2009) from 2004 to 2005.

We investigated the source of this ground deformation by applying the statistical tool of Independent Component Analysis (ICA) to the dataset. ICA allowed separating the spatial patterns of deformation into four components. We attributed three of them to an actual ground deformation, while the fourth seems to be only related to the noise component of data. The first component (ICA1) displays a spatial pattern localised in Teide volcano neighbourhoods and consists of a ground uplift of few centimetres. The deformation associated with this component starts in 2005 and persists along the rest of the time series. The second component (ICA2) of the ground deformation is localised in the South/South-West part of Las Cañadas rim while the third component (ICA3) is localised to the East of Teide volcano. We performed inverse modelling to analyse the source of the ground deformation related to ICA1 to retrieve the location, the geometry and the temporal evolution of this source. The inversion was based on analytical models of ground deformation as well as on Finite-Element-Modelling. The result showed that the ground deformation is associated with a shallow sill-like structure, located beneath Teide volcano, possibly reflecting a hydrothermal reservoir. The knowledge of this source geometry could be of significant interest to better understand ground deformation data of possible future volcanic crisis. 

How to cite: Przeor, M., D'Auria, L., Pepe, S., and Tizzani, P.: Modelling ground deformation in Tenerife (Canary Islands) during 2003-2010, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11023, https://doi.org/10.5194/egusphere-egu21-11023, 2021.

09:52–09:54
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EGU21-9881
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ECS
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Non-uniqueness in the inversion of volcano deformation data: change of volume or change of position? 
Erika Ronchin, Raffaele Castaldo, Susi Pepe, Pietro Tizzani, Giuseppe Solaro, and Maurizio Battaglia

The detailed spatial and temporal information of surface deformation detected during volcanic unrest by InSAR images suggests a degree of complexity of volcanic systems (e.g., source geometries and distribution of material properties) that cannot be correctly represented by simple models of a pressure source embedded in an elastic, homogeneous, isotropic half-space.

The inversion of deformation data, performed for the characterization of the source of deformation, is based on the model we choose to represent the volcanic system. Therefore the quality of the chosen model influences the source size and its temporal changes estimated through the inversion, and thus their interpretation. In fact, our assumptions about geometries and/or magma and rock properties affect the estimations of changes in magma volumes and reservoir pressure. To obtain a more reliable interpretation of surface signals, it is thus paramount to have more realistic models, where the distribution of material properties is constrained by multiple data sets, with greater flexibility in the definition of sources in space and time.

Assuming we could invert InSAR data with models that can deal with a complex and arbitrarily shaped deformation source, how unique could this solution be? How much could we say about the evolution of the deformation source over time? Furthermore, how much information about the spatial complexity of the source and its evolution in space and time would be missed?

To answer these questions, we characterize the deformation source from the inversion of InSAR data based on a finite element method (FEM) forward model without an a-priori source geometry. The deformation source is bound by estimating the strength of an amorphous cluster of deformation sources distributed over a grid. This uses the principle of superposition already applied to point or cuboid volume elements, embedded in a homogeneous half-space. Also, the numerical model integrates the cluster-source with a heterogeneous distribution of material properties and the topography.

In our study, we quantify the ambiguity in the estimation of arbitrary geometries of sources of deformation composed by clusters of Finite Element Method unit sources distributed over a grid. The regularized least-squares solutions of the steady-state PDEs inverse model are obtained using a COMSOL Multiphysics-based routine. Through the inversion of the InSAR time series of the unrest at Uturuncu volcano (Bolivia), we quantify the ability of the employed cluster-source approach to identify the changes of deformation sources in time. 

This research is financed by an individual fellowship of the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 793811.

How to cite: Ronchin, E., Castaldo, R., Pepe, S., Tizzani, P., Solaro, G., and Battaglia, M.: Non-uniqueness in the inversion of volcano deformation data: change of volume or change of position?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9881, https://doi.org/10.5194/egusphere-egu21-9881, 2021.

09:54–09:56
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EGU21-11104
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ECS
Multiscale Spatial and Temporal Analysis of the b-value in volcanic areas 
Rubén García-Hernández, Luca D'Auria, José Barrancos, and German D. Padilla

Determining the b-value of the Gutenberg-Richter law is of great importance in Seismology. However, its estimate is strongly dependent upon selecting a proper temporal and spatial scale due to the multiscale nature of the seismicity. This characteristic is especially relevant in volcanoes where dense clusters of earthquakes often overlap the background seismicity and where this parameter displays a higher spatial and temporal variability.

For this reason, we devised a novel approach called MUST-B (MUltiscale Spatial and Temporal estimation of the B-value) which allows a consistent estimate of the b-value, avoiding subjective “a priori ” choices, by considering simultaneously different temporal or spatial scales. This approach also includes a consistent estimation of the completeness magnitude (Mc) and the uncertainties over both b and Mc. We applied this method to datasets in volcanic areas proving its effectiveness to analyze complex seismicity patterns and its utility in volcanic monitoring and geothermal exploration. Besides, it may provide a way to distinguish seismicity caused by tectonic faults and volcanic sources in zones where there is a mix of both of them.

We present MUST-B applications to three volcanic areas: Long Valley caldera (USA), Tenerife and El Hierro (Canary Islands). The spatial analysis of the b-value in Long Valley shows an impressive chimney-like volume characterized by high b-values which coincide with the main pathway of geothermal fluids inferred by independent studies. For Tenerife, we applied MUST-B to analyze both spatial and temporal variations. The spatial pattern shows an interesting variation between 2004-2005 and the period 2016-2020. In both cases, high b-values appear in an area that hosted increased seismicity because of seismo-volcanic crises. These high b-values are also evidenced by the temporal analysis, which shows an increase in correspondence between these two periods. For El Hierro, we analyzed the seismicity preceding the 2011 submarine eruption of Tagoro volcano using a joint spatio-temporal analysis. Results show high b-values in the area where the vent opened and a drop of this parameter just before the beginning of the eruption.

How to cite: García-Hernández, R., D'Auria, L., Barrancos, J., and Padilla, G. D.: Multiscale Spatial and Temporal Analysis of the b-value in volcanic areas, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11104, https://doi.org/10.5194/egusphere-egu21-11104, 2021.

09:56–09:58
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EGU21-12143
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ECS
Analysis of magnetotelluric data from Las Cañadas caldera (Tenerife, Spain) 
David Martínez van Dorth, Federico Di Paolo, Katarzyna Slezak, Iván Cabrera-Pérez, Perla Piña-Varas, Juanjo Ledo, Garazi Bidaurrazaga Aguirre, Lucía Sáez Gabarrón, Monika Przeor, William Hernández, Luca D'Auria, and Nemesio M. Pérez

Tenerife is the second-largest island in the Canarian archipelago with an area of 2034 km2. It consists of three ancient volcanic massifs (Anaga, Adeje and Teno) located at the edges of the island connected by rift zones to the centre of the island, in correspondence of Las Cañadas caldera. The caldera hosts the most relevant topographic element of Tenerife, the volcanic edifice of Teide – Pico Viejo. Previous studies already suggested the presence of geothermal resources inside and around the caldera. For this reason, in the present study, we have applied the magnetotelluric method (MT) in the central part of the island to better understand subsurface structures in this area.

The MT method is a useful tool successfully applied to detect conductive and resistive structures located in the subsoil. It is commonly used in volcanic areas to detect volcano-tectonic features and geothermal systems to evaluate exploitable geothermal resources. Furthermore, continuous magnetotelluric measurements can also be employed for volcanic monitoring, allowing tracking temporal changes of the resistivity because of fluid transfer processes in the volcanic system.

Between 2019 and 2020 we realised a detailed study of Las Cañadas caldera resistivity structure thought 45 magnetotelluric soundings. The instrumentation consisted of four Metronix ADU-08e, equipped with EPF-06 electrodes and MFS-06e magnetic coils, which registered electric and magnetic fields along the N-S and E-W directions. We also installed three remote stations at different times inside the caldera. Depending on the station quality, we obtained the MT response functions for periods of 0.001 – 1000 s. The dimensionality of the data has been analysed using the phase tensor.  The first preliminary results of dimensionality and strike analysis indicate a 1D/2D behaviour for the first layers which present a decreasing resistivity, evolving to a 3D behaviour from 1s and with an increase of resistivity with depth.

Furthermore, we present some results obtained by a permanent MT station to check the possibility of temporal changes in the electrical resistivity. During the time this station was recording two electrical blackouts which took place on the island. This allowed quantitatively estimating the level of anthropogenic electromagnetic noise in the recorded time series.

How to cite: Martínez van Dorth, D., Di Paolo, F., Slezak, K., Cabrera-Pérez, I., Piña-Varas, P., Ledo, J., Bidaurrazaga Aguirre, G., Sáez Gabarrón, L., Przeor, M., Hernández, W., D'Auria, L., and Pérez, N. M.: Analysis of magnetotelluric data from Las Cañadas caldera (Tenerife, Spain), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12143, https://doi.org/10.5194/egusphere-egu21-12143, 2021.

09:58–10:03
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EGU21-13038
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solicited
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Highlight
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Modeling of major environmental risks for the Kyiv city,  Ukraine from the Dnieper river waters  -  inundation of coastal areas and contamination by the radionuclides deposited in bottom sediments after the Chornobyl accident 
Sergii Kivva, Mark Zheleznyak, Roman Bezhenar, Oleksandr Pylypenko, Maxim Sorokin, Andriy Demydenko, Volodymyr Kanivets, Gennady Laptev, Oleg Votsekhovich, Victoria Boyko, and Dmitri Gudkov

There are two partially linked risks to the Kyiv city associated with the Dnieper river: (A) risk of the inundation of the urban coastal areas during the extremely high floods or due to the break of the Hydropower Plant dam located upstream Kyiv, and, (B) risk of the secondary radioactive contamination of the Dnieper waters due to the intensification of the dynamics of "Chornobyl" radionuclides during high floods and man-made impacts -  dredging in Kyiv Reservoirs for navigation routes and other purposes.

The Chornobyl Nuclear Power Plant has located 130 km from Kyiv at the bank of Pripyat river, which is 20 km downstream from ChNPP inflows into the Kyiv reservoir of the Dnieper River. After the Chornobyl accident, about 5.4×1013 Bq of 137Cs and 1013 Bq of 90Sr were deposited in the bottom sediments of the Kyiv Reservoir. Nowadays, 35 years after the Chornobyl accident, the population of Kyiv still is very sensitive to the risks of secondary environmental contaminations by the “Chornobyl radionuclides”. Therefore even low levels of such risks should be carefully assessed by well-grounded methods.

The main goals of our multidisciplinary study are:

  • to develop a model/data based Decision Support System (DSS) for the assessment of both kind of the described above risks A) and B),
  • to analyze the influence of the natural hazard – extremely high river floods on the resuspension of contaminated sediments and environmental risks due to the man-made impacts – dredging, dam breaks, and others.

The components of these research and development activities are following:

  • field and laboratory studies of the contemporary contamination of the bottom sediments and biota in the Kyiv reservoir to receive the input data for the model calibration and improvement of the model structure;
  • customization for the Kyiv Reservoir and the Dnieper river at Kyiv of the 2D COASTOX model which the hydrodynamic module is based on the nonlinear shallow water equations, and the sediment/radionuclide transport model using the advection-diffusion equations with specific sink/source terms for radionuclides;
  • customization for the Kyiv Reservoir of the hydro-ecological POSEIDON model that simulates the influence of resuspension of radioactive sediments on the contamination of fishes and other hydrobionts;
  • improvement of methods for the numerical solution of model equations and algorithms based on finite volume methods for their parallelization using multiprocessor systems and graphics cards to speed up computations;
  • to create high-performance DSS with a user-friendly interface that can use GPUs to quickly predict the radiation status of surface waters and inundation of river banks in emergencies.

The DSS is installed in the Department of Hydrological Forecasting of the Ukrainian Hydrometeorological Center and is used for the quantification of the risk scenarios and analyses of the links of both risks. Due to the high computational performance, the DSS can be used for the real-time numerical predictions with the zoning of the flood risks in a case of emergency.

How to cite: Kivva, S., Zheleznyak, M., Bezhenar, R., Pylypenko, O., Sorokin, M., Demydenko, A., Kanivets, V., Laptev, G., Votsekhovich, O., Boyko, V., and Gudkov, D.: Modeling of major environmental risks for the Kyiv city,  Ukraine from the Dnieper river waters  -  inundation of coastal areas and contamination by the radionuclides deposited in bottom sediments after the Chornobyl accident, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13038, https://doi.org/10.5194/egusphere-egu21-13038, 2021.

10:03–10:05
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EGU21-15403
Diffuse H2 degassing studies: a useful geochemical tool for monitoring Cumbre Vieja volcano, La Palma, Canary Islands 
Nemesio M. Pérez, Gladys V. Melián, Pedro A. Hernández, María Asensio-Ramos, Eleazar Padrón, Fátima Rodríguez, Mar Alonso, Alba Martín-Lorenzo, Cecilia Amonte, Luca D'Auria, José Barrancos, and Germán D. Padilla

Hydrogen (H2) is one of the most abundant trace species in volcano-hydrothermal systems and is a key participant in many redox reactions occurring in the hydrothermal reservoir gas. Although H2 can be produced in soils by N2-fixing and fertilizing bacteria, soils are considered nowadays as sinks of molecular hydrogen (Smith-Downey et al. 2006). Because of its chemical and physical characteristics, H2 generated within the crust moves rapidly and escapes to the atmosphere. These characteristics make H2 one of the best geochemical indicators of magmatic and geothermal activity at depth. Cumbre Vieja volcano (La Palma, Canary Islands) is the most active basaltic volcano in the Canaries with seven historical eruptions being Teneguía eruption (1971) the most recent one. Cumbre Vieja volcano is characterized by a main north–south rift zone 20 km long, up to 1950 m in elevation and covering an area of 220 km2 with vents located at the northwest and northeast. Cumbre Vieja does not show any visible degassing (fumaroles, etc.). For that reason, the geochemical volcano monitoring program at Cumbre Vieja volcano has been focused on soil degassing surveys.  Here we show the results of soil H2 emission surveys that have been carried out regularly since 2001. Soil gas samples were collected in about 600 sampling sites selected to obtain a homogeneous distribution at about 40 cm depth using a metallic probe and 60 cc hypodermic syringes and stored in 10 cc glass vials. H2 content was analysed later by a VARIAN CP4900 micro-GC. A simple diffusive emission mechanism was applied to compute the emission rate of H2 at each survey. Diffuse H2 emission values were used to construct spatial distribution maps by using sequential Gaussian simulation (sGs) algorithm, allowing the estimation of the emission rate from the volcano. Between 2001-2003, the average diffuse H2 emission rate was ∼2.5 kg·d−1 and an increase of this value was observed between 2013-2017 (∼16.6 kg·d−1), reaching a value of 36 kg·d−1 on June 2017, 4 month before the first recent seismic swarm in October, 2017 at Cumbre Vieja volcano. Six additional seismic swarms had occurred at Cumbre Vieja volcano (February 2018, July-August 2020; October 8-10, 2020; October 17-19, 2020, November 21, 2020 and December 23-26, 2020) and changes of diffuse H2 emission related to this unrest had been observed reaching values up to ∼70 kg·d−1. Diffuse H2 emission surveys have demonstrated to be sensitive and excellent precursors of magmatic processes occurring at depth in Cumbre Vieja. Periodic diffuse H2 emission surveys provide valuable information to improve and optimize the detection of early warning signals of volcanic unrest at Cumbre Vieja volcano.

How to cite: Pérez, N. M., Melián, G. V., Hernández, P. A., Asensio-Ramos, M., Padrón, E., Rodríguez, F., Alonso, M., Martín-Lorenzo, A., Amonte, C., D'Auria, L., Barrancos, J., and Padilla, G. D.: Diffuse H2 degassing studies: a useful geochemical tool for monitoring Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15403, https://doi.org/10.5194/egusphere-egu21-15403, 2021.

10:05–10:07
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EGU21-15421
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ECS
Changes in the thermal energy and the diffuse 3He and 4He degassing prior to the 2014-2015 eruption of Pico do Fogo volcano, Cape Verde 
Mar Alonso, Nemesio M. Pérez, Eleazar Padrón, Pedro A. Hernández, Gladys V. Melián, Hirochika Sumino, Germán D. Padilla, José Barrancos, Fátima Rodríguez, Samara Dionis, María Asensio-Ramos, Cecilia Amonte, Sonia Silva, and José Manuel Pereira

Cape Verde archipelago is a cluster of several volcanic islands arranged in a westward opening horseshoe shape located in the Atlantic Ocean, between 550 and 800 km-west of the coast of Senegal (Africa). Fogo Island is located in the southwest of the archipelago, and as main feature is a 9-km-north to south wide collapse caldera opened toward the east, within Pico do Fogo volcano rises 2,829 m.a.s.l. Pico do Fogo crater has an area of 0.142 km2 and its characterized by a fumarolic field composed by low and moderate temperature fumaroles, with temperatures around 95ºC and reaching 400ºC respectively. The last eruption of Fogo volcanic system took place between November 2014 and February 2015, when four new eruptive vents were formed, and destroyed partially the villages of Portela and Bangaeira (Silva et. al., 2015) forcing the evacuation of 1,300 inhabitants. In this work we present the temporal evolution of 3He/4He isotopic ratio, 3He and 4He emission and thermal energy released data measured from March 2007 to November 2018 in the crater of Pico do Fogo. In all the studied temporal evolutions, we can observe two main increases in the above parameters, the first in early 2010, suggesting a magmatic intrusion, and the second several months before the eruption onset. We have also observed that changes in the 3He emission might be accompanied by a significant increase in thermal output if the system is in an eruptive cycle. Our results confirm 3He emission studies are highly reliable indicator of imminent volcanic eruption and constitute a powerful tool to monitor the activity of volcanic areas around the world.

Silva et al., (2015), Geophysical Research Abstracts Vol. 17, EGU2015-13378, EGU General Assembly.

How to cite: Alonso, M., Pérez, N. M., Padrón, E., Hernández, P. A., Melián, G. V., Sumino, H., Padilla, G. D., Barrancos, J., Rodríguez, F., Dionis, S., Asensio-Ramos, M., Amonte, C., Silva, S., and Pereira, J. M.: Changes in the thermal energy and the diffuse 3He and 4He degassing prior to the 2014-2015 eruption of Pico do Fogo volcano, Cape Verde, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15421, https://doi.org/10.5194/egusphere-egu21-15421, 2021.

10:07–10:09
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EGU21-1698
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ECS
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Automatic tree species classification by using field data, image analysis and deep learning techniques in riparian forests 
Sarah Kentsch, Maximo Larry Lopez Caceres, and Yago Diez

Mixed forests are still little understood ecosystems. Their structure and composition are not well known and not clearly classified. In times of climate change, monitoring of forests is becoming increasingly important. Forest stands were usually researched by field work, which requires high costs and man-power. Field surveys are further only conducted in small patches of the forests, which does often not represent the whole forest. For mixed forests, usually only a dominate species is mentioned but the forests are not classified further. The greater need of better methods with high accuracies to detect and classify tree species in the forest encouraged this study.

UAVs have been proven to be an efficient tool to conduct automatic field surveys in forestry applications. These easy-to-use and cheap tools are able to gather images with a high resolution. Image processing with image analysis and deep learning techniques is an emerging part in forestry investigations. Therefore, we combined manual field surveys, image analysis and automatic classifications in our study.

The forests, we were investigating, are riparian forests in Shonai area, Japan, which are classified as mixed forests. 7 sites were chosen and field surveys were conducted. Most of the sites are located in flat areas, but 3 sites are located on slopes, where the access is difficult and field work barely possible. We imaged all sites in different seasons with UAVs and performed image analysis with computer vision and ArcGIS methods. Trees were detected and classified manually and automatically. A comparison of all applied methods was drawn, evaluated and will be provided.

Our first results are promising to characterize forests in a new dimension. We will provide detailed information about tree species composition, tree locations and forest structures. Mixed forests can be deeper analysed by maps of dominate and subdominant tree species. Area calculations for tree canopies will be highlighted for the main tree species. We will provide winter images for tree counting in heavy snowfall regions and classification accuracies of deep learning techniques.  

How to cite: Kentsch, S., Lopez Caceres, M. L., and Diez, Y.: Automatic tree species classification by using field data, image analysis and deep learning techniques in riparian forests, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1698, https://doi.org/10.5194/egusphere-egu21-1698, 2021.

10:09–10:11
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EGU21-10436
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ECS
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Contribution to the discussion on processing and measurement methodology of apatite fission-track analysis 
Lucie Novakova, Raymond Jonckheere, Bastian Wauschkuhn, and Lothar Ratschbacher

Apatite fission track dating and T,t-modelling are now a well-established thermochronological instruments for investigating geological problems (Malusà and Fitzgerald, 2019). In the course of their development, complicating factors that affect the track counts and confined track lengths in geological samples were corrected for, foremost among them the crystallographic orientation of the confined track and the chemical composition of the apatite (Green et al., 1986, and subsequent papers). Methods have also been proposed to improve the confined track statistics, using 252Cf irradiation, ion irradiation, fracturing, and re-etching (Yamada et al., 1998). However, there is to date no adequate correction for the protocol used to reveal the tracks, which differs from lab to lab although all are based on nitric acid.

Recent step-etch experiments with the most used etchants show that both the duration of the etch and the temperature and concentration of the solution have non-negligible effects on the measured lengths (Sobel and Seward, 2010; Jonckheere et al., 2017 and references therein; Tamer et al., 2019). Earlier attempt to overcome these problems investigated etching for such a time that the track openings conform to a pre-determined size (Ravenhurst et al., 2003) or measuring confined tracks of a given minimum width (Yamada et al., 1993). The first method has the drawback that the widths of the host tracks and confined tracks are not directly related, whereas the second fails to consider the anisotropic width of confined tracks.

In our geological investigation of the German Naab area, we adopt a step-etch approach, measuring the c-axis angle, length, width and dip of each individual confined track after 20s and 30s immersion in 5.5 M HNO3. From the width increase we calculate the rate of widening of the track (apatite etch rate; Aslanian et al., 2021), and from that the effective etch time tE, i.e., the true duration that the confined track has been etched, equal to the immersion time minus the time needed for the etchant to reach the specific confined track. Our results show that the confined track lengths are correlated with their effective etch times. This information is used to account for etch-protocol-related differences between the induced and fossil track lengths entered in the T,t-modelling software. We envisage this will improve the accurateness and resolution of the resulting T,t-paths. We will check this against the excellent independent geological constraints that exist for the Naab region.

The research was funded by the EU/MEYS (CZ.02.2.69/0.0/0.0/19_074/0014756).

 

References

Aslanian et al., 2021. American Mineralogist. In press.

Green et al., 1986. Chemical Geology 59, 237-253.

Jonckheere et al., 2017. American Mineralogist 102, 987-996.

Malusà and Fitzgerald, 2019.  Fission-Track Thermochronology and its Application to Geology. Pp 393.

Ravenhurst et al., 2003. Canadian Journal of Earth Sciences 40, 995-1007.

Sobel and Seward, 2010. Chemical Geology 271, 59-69.

Tamer et al., 2019. American Mineralogist 104(10), 1421-1435.

Yamada et al., 1993. Chemical Geology 122, 249-258

Yamada et al., 1998. Chemical Geology 149, 99–107.

How to cite: Novakova, L., Jonckheere, R., Wauschkuhn, B., and Ratschbacher, L.: Contribution to the discussion on processing and measurement methodology of apatite fission-track analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10436, https://doi.org/10.5194/egusphere-egu21-10436, 2021.

10:11–10:13
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EGU21-13772
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A Multi-Use Case Scientific Sensor Node 
Valarie Hamilton and Andrew Moores

Nanometrics' Pegasus digitizer is the basis for a scientific grade node and is the latest development in many years of designing and building reliable seismic instruments for the scientific and monitoring community. Coupled in a grab-and-go quick deploy package with a variety of sensors enables responses to many types of events and environmental measurements. These types of systems are not only for hazards, such as earthquakes and volcanoes, but can form the basis of better tools used for critical structure and microzonation studies using ambient noise.  Pegasus takes advantage of a complete ecosystem of software, making planning, deploying and data harvesting very simple and straightforward as well as providing a dataset that includes automatically generated metadata in the form of StationXML and standard miniSEED data files.  Pegasus design criteria was based on optimal SWaP (Size, Weight and Power) and makes it unique in short to long duration deployments without swapping of units in the field, while its broad sensor compatibility enables many types of measurements and is completely compatible with the advantages of Nanometrics smart sensors.

How to cite: Hamilton, V. and Moores, A.: A Multi-Use Case Scientific Sensor Node, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13772, https://doi.org/10.5194/egusphere-egu21-13772, 2021.

10:13–10:30
Meet the authors in their breakout text chats