Content:
Presentation type:
GI – Geosciences Instrumentation & Data Systems

EGU23-13597 | Orals | GI1.1 | Highlight | Christiaan Huygens Medal Lecture

Solving the ambiguity in the potential field exploration of complex sources 

Maurizio Fedi

It is theoretically demonstrated  that, even with perfectly complete and perfectly accurate data, there is a fundamental ambiguity in the analysis of potential field data. The ambiguity may be easily illustrated by computing some of the various kinds of structures that can give rise to the same anomaly field. To solve the ambiguity and yield reasonable geophysical models we must therefore supply a priori information. In gravimetry, the ambiguity comes from the fact that only the excess mass is uniquely determined by the anomaly, neither the density nor the source volume. However, not only the excess mass can be uniquely estimated. Examples are the center of a uniformly dense (or magnetized) sphere or the top of a deeply extended homogeneously-dense cylinder. A priori information may consist of direct information (e.g., depth, shape) and/or of assuming that the source distribution has some specified properties (e.g., compactness, positivity). If one tries to classify the physical source-distributions in terms of their complexity, we may however use two different scaling laws, based on homogeneity and self-similarity, which allow modeling of the Earth in its complex heterogeneity. While monofractals or homogeneous functions are scaling functions, that is they do not have a specific scale of interest, multi-fractal and multi-homogeneous models need to be described within a multiscale dataset. Thus, specific techniques are needed to manage the information contained on the whole multiscale dataset. In particular,  any potential field  generated by a complex source may be modeled as  a multi-homogeneous field, which typically present a fractional and spatially varying homogeneity degree. For a source of irregular shape, it may be convenient to invert not the  field but a related quantity, the scaling function, which is a multiscale function having the advantage of not involving the density among the unknown parameters. For density or magnetic susceptibility tomographies, the degree of spatially variable homogeneity can be incorporated in the model weighting function, which, in this way, does not require prior assumptions because it is entirely deductible from the data. We discover that difficult quantities, such as the bottom of the sources, or multiple source systems are reasonably well estimated by abandoning the analysis at a single scale and unraveling the scale-related complexity of geophysical signals. The inherent self-consistency of these new multiscale tools is a significant step forward, especially in the analysis of areas where there is scarce other information about the sources.

How to cite: Fedi, M.: Solving the ambiguity in the potential field exploration of complex sources, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13597, https://doi.org/10.5194/egusphere-egu23-13597, 2023.

EGU23-1641 | ECS | Orals | GI1.1 | GI Division Outstanding Early Career Scientist Award Lecture

Towards sustainable road transport infrastructure: Insights from GPR performance indicator development and enhancement of data quality 

Mezgeen Rasol

The wide use of the NDT technologies and the big database are produced, transmitted, collected, processed needs to be managed and well-presented towards monitoring of road transports. Using Ground Penetrating Radar (GPR) as one of the most efficient non-destructive tests in road transport monitoring.  Such database outcomes produced through on-site monitoring approaches are essential for providing the most reasonable decision-making tools to support best engineering judgment on-site. In addition to that the accuracy and precision of such decision-making tools are highly dependent on the data quality generated from different GPR images. Establishing performance indictor could avoid errors in dataset and unfavorable decisions in pavement management system. Consequently, GPR data management and transforming to local indicators is crucial to increase quality control of the dataset. This is still an ongoing challenging task for GPR support-knowledge.  

Establishing indicators are based on different criteria including intuitive outcomes, empirical outputs, and analytical results. Different GPR signal parameters can be correlated to the subsurface material changes and deterioration such as electromagnetic wave velocity, amplitude, centre frequency and signal attenuation to some local indicators. This can be under the category of the current challenges, the question is as follows, How GPR data can be converted to indicators based on the common defects in road transports. Therefore, establishing potential metrics to value GPR-related indicators in both a qualitative and quantitative approaches is crucial to provide better understanding of the defects and their propagation in road pavements.

How to cite: Rasol, M.: Towards sustainable road transport infrastructure: Insights from GPR performance indicator development and enhancement of data quality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1641, https://doi.org/10.5194/egusphere-egu23-1641, 2023.

GI1 – General sessions on geoscience instrumentation

EGU23-237 | ECS | Posters virtual | GI1.1

Scheduling System for Remote Control of Instruments used for Atmospheric Observation 

Martin Schumann, Johannes Munke, Stephan Hachinger, Patrick Hannawald, Inga Beck, Alexander Götz, Oleg Goussev, Jana Handschuh, Helmut Heller, Roland Mair, Till Rehm, Bianca Wittmann, Sabine Wüst, Michael Bittner, Jan Schmidt, and Dieter Kranzlmüller

In this poster contribution, we present a scheduling system for automated remote operation of instruments at high-altitude research facilities and similar remote sites. Via web-based interfaces, the system allows instrument owners as well as authorized third-party scientists to schedule and execute measurements and observations.

The system has been developed as a thesis project in the context of the AlpEnDAC-II ("Alpine Environmental Data Analysis Centre", www.alpendac.eu) collaboration (funded by the Bavarian State Ministry of the Environment and Consumer Protection). Consequently, the scheduler and interfaces have been integrated with the AlpEnDAC Operating-on-Demand functionalities. A first use case for the framework has been the operation of an airglow imager (FAIM) in Oberpfaffenhofen (DE).

We describe the design and implementation of our system for scheduling and execution of multi-user observations on instruments, including scheduling-data transfers and data retrieval. Our core implementation uses an optimization-based scheduler (Google's OR-Tools) to ensure maximum instrument use and to minimize idle times. Results show that the scheduler is reliable, fast, and is consistently able to provide optimal observation plans. The extensibility of the system is guaranteed by the usage of modern software in the core of the system, including well-defined and specified communication through REST APIs. Thus, it can easily be adapted to other settings and instruments, which is also facilitated by a modern deployment strategy using Docker and Kubernetes.

How to cite: Schumann, M., Munke, J., Hachinger, S., Hannawald, P., Beck, I., Götz, A., Goussev, O., Handschuh, J., Heller, H., Mair, R., Rehm, T., Wittmann, B., Wüst, S., Bittner, M., Schmidt, J., and Kranzlmüller, D.: Scheduling System for Remote Control of Instruments used for Atmospheric Observation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-237, https://doi.org/10.5194/egusphere-egu23-237, 2023.

EGU23-1220 | ECS | Posters on site | GI1.1

Analytical developments at the Potsdam SIMS user facility and the metrological limits on in situ isotope ratio data 

Maria Rosa Scicchitano, Michael Wiedenbeck, Frederic Couffignal, Sarah Glynn, Alicja Wudarska, Robert Trumbull, and Alexander Rocholl

The German Research Centre for Geosciences (GFZ) in Potsdam hosts a CAMECA 1280-HR large geometry secondary ion mass spectrometer (SIMS) with a web-based user node at the University of the Witwatersrand, South Africa. A major theme of our facility is high-precision, high-accuracy, high-spatial resolution analyses of light isotope ratios in a variety of natural and experimental materials.

The latest analytical developments from the GFZ SIMS laboratory focus on the development, assessment and use of new reference materials for stable isotope analysis. Particularly for oxygen, our repeatability from 15-µm diameter domains is now typically better than ±0.15‰ (1s). However, the total uncertainty on such analyses is commonly larger because of significant differences (in some cases more than one ‰) among the isotope ratios of reference materials reported by multiple, highly regarded gas source mass spectrometry laboratories. This issue of interlaboratory bias during reference material characterization inevitably impacts all in situ data employing such materials and must be duly considered.

How to cite: Scicchitano, M. R., Wiedenbeck, M., Couffignal, F., Glynn, S., Wudarska, A., Trumbull, R., and Rocholl, A.: Analytical developments at the Potsdam SIMS user facility and the metrological limits on in situ isotope ratio data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1220, https://doi.org/10.5194/egusphere-egu23-1220, 2023.

EGU23-1641 | ECS | Orals | GI1.1 | GI Division Outstanding Early Career Scientist Award Lecture

Towards sustainable road transport infrastructure: Insights from GPR performance indicator development and enhancement of data quality 

Mezgeen Rasol

The wide use of the NDT technologies and the big database are produced, transmitted, collected, processed needs to be managed and well-presented towards monitoring of road transports. Using Ground Penetrating Radar (GPR) as one of the most efficient non-destructive tests in road transport monitoring.  Such database outcomes produced through on-site monitoring approaches are essential for providing the most reasonable decision-making tools to support best engineering judgment on-site. In addition to that the accuracy and precision of such decision-making tools are highly dependent on the data quality generated from different GPR images. Establishing performance indictor could avoid errors in dataset and unfavorable decisions in pavement management system. Consequently, GPR data management and transforming to local indicators is crucial to increase quality control of the dataset. This is still an ongoing challenging task for GPR support-knowledge.  

Establishing indicators are based on different criteria including intuitive outcomes, empirical outputs, and analytical results. Different GPR signal parameters can be correlated to the subsurface material changes and deterioration such as electromagnetic wave velocity, amplitude, centre frequency and signal attenuation to some local indicators. This can be under the category of the current challenges, the question is as follows, How GPR data can be converted to indicators based on the common defects in road transports. Therefore, establishing potential metrics to value GPR-related indicators in both a qualitative and quantitative approaches is crucial to provide better understanding of the defects and their propagation in road pavements.

How to cite: Rasol, M.: Towards sustainable road transport infrastructure: Insights from GPR performance indicator development and enhancement of data quality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1641, https://doi.org/10.5194/egusphere-egu23-1641, 2023.

EGU23-1725 | ECS | Posters virtual | GI1.1

Analysis on the Uncertainty of the Coil Sensitivity based on the Principle of Scalar Calibration Method 

Manming Chen, Yiren Li, Xinjun Hao, Kai Liu, Zonghao Pan, Xin Li, and Tielong Zhang

Scalar calibration method is quite convenient and widely used in the coil sensitivity calibration for certain coil system. The uncertainties of the results are critical in evaluating the accuracy of the coil sensitivity. Based on the calibration principle, a mathematical description of the coil sensitivity uncertainty is given, which shows that the current, the environmental magnetic field and their uncertainties are the main factors attributing to the coil sensitivity uncertainty. Series of tests were conducted under different currents and stable environmental magnetic fields. The results show a very good accordance with the analytical description. With the increase of the current, the coil sensitivity uncertainty becomes smaller and goes to a limit decided by the current uncertainty while the influence of the environmental magnetic field is comparatively insignificant.

How to cite: Chen, M., Li, Y., Hao, X., Liu, K., Pan, Z., Li, X., and Zhang, T.: Analysis on the Uncertainty of the Coil Sensitivity based on the Principle of Scalar Calibration Method, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1725, https://doi.org/10.5194/egusphere-egu23-1725, 2023.

EGU23-2690 | Orals | GI1.1

A truly Very Broad Band (VBB) borehole seismometer with flat response over 5 decades of frequency 

Cansun Guralp, Horst Rademacher, Paul Minchinton, Robert Kirrage, Maksim Alimov, Rebekah Jones, and Nichola Boustead

Decades ago new opportunities in seismology were opened by the development of broadband seismic sensors with feedback. The three defining characteristics of these instruments were the bandwidth extension to longer periods, a much lower intrinsic noise and a higher dynamic range. However, the goal of further extending their bandwidth to frequencies above 100 Hz has proven elusive, because these sensors are plagued by parasitic resonances leading to modes not controllable by the feedback system.

Here we present a new low noise seismic borehole sensor with a truly VBB flat response over five frequency decades from 2.7 mHz (360 sec) to 270 Hz. The instrument has no mechanical resonances below 400 Hz. We achieved the bandwidth extension to high frequencies with improvements of the mechanical design, i.e. the arrangement of the pivots and the geometry of the spring.

The design is realized in a borehole arrangement, where three sensors are stacked in 90 degree angles to each other. Including a singe jaw holelock as a clamping mechanism the complete stack has a diameter of 89 mm, is 625 mm long and weighs about 24.5 kg. We show test results from three co-located complete borehole sensors with identical frequency responses.

How to cite: Guralp, C., Rademacher, H., Minchinton, P., Kirrage, R., Alimov, M., Jones, R., and Boustead, N.: A truly Very Broad Band (VBB) borehole seismometer with flat response over 5 decades of frequency, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2690, https://doi.org/10.5194/egusphere-egu23-2690, 2023.

Muography is a passive and non-destructive imaging technique that utilizes cosmic-ray muons for visualizing and monitoring the interior of geological structures and human-made objects. A rapid development of muographic observation technologies was achieved in the recent years, which allowed to resolve Earth's shallow subsurface with a resolution of a few meters and conduct long-term muon monitoring in harsh and varying environment. Muography can be applied as a complementary technique for Earth sciences and related engineering fields, e.g., for studying active volcanism, characterizing the overburden above underground sites, structural health monitoring infrastructures, exploring hidden cultural heritages, etc. We overview the recent progress in development of muography and we discuss case studies from volcanology to mining engineering from the Americas, Asia and Europe.

How to cite: Oláh, L.: Advances in cosmic-ray muography for Earth sciences and geophysical applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3288, https://doi.org/10.5194/egusphere-egu23-3288, 2023.

EGU23-3732 | ECS | Posters on site | GI1.1

Improving single particle ICP-TOFMS using a desolvation sample introduction system and collision cell technology 

Geunwoo Lee, Tobias Erhardt, Lyndsey Hendriks, Martin Tanner, Barbara Delmonte, and Hubertus Fischer

Inductively coupled plasma time-of-flight mass spectrometry (ICP-TOFMS) is increasingly used in various disciplines, especially for the characterization of single particles, because it allows truly simultaneous determination of isotopes over full mass range without sacrificing analytical sensitivity (Baalousha et al., 2021; Erhardt et al., 2019; Goodman et al., 2022). In particular, the extremely high time resolution of TOFMS allows us to detect individual mineral dust particles in the water stream obtained from Continuous Flow Analysis of Greenland Ice cores. Even though collision cell technology (CCT) and high-sensitivity sample introduction have been applied to the ICP-MS systems to overcome analytical limitations in spectral interferences and sensitivity (Burger et al., 2019; Lin et al., 2019), the impact of CCT and high-sensitivity desolvation sample introduction on analysis of single particles, unlikely to bulk analysis, are still relatively poorly understood. We investigated the effects of CCT and high-sensitivity desolvation sample introduction (individually and in combination) on the capability of single particle (sp) ICP-TOFMS including sensitivity and transport/transmission efficiency. To do so, we systemically investigated differences in the sensitivity of total Au, the transport efficiency of Au nano particles as well as the signal amplitude above the background of these nano particles. Application of the desolvation unit without CCT led to a significant improvement of the transport efficiency (number of particles introduced into the plasma) by a factor of about 5 but to a reduction of sensitivity (counts per particle) by about 30 percent. When CCT was used for sp-ICP-TOFMS without the high-sensitivity sample introduction system, the sensitivity for gold ion in particle signals increased by only about six percent. This is similar to the sensitivity improvement for gold ions in dissolved background signals from the ion focusing effect after the collision cell. However, when CCT was used in combination with the high-sensitivity sample introduction system, the sensitivity for gold ion in particle signals increased by another up to about 33 percent compared to the desolvation system without CCT. This could be because the collisional ion focusing is more effective under the high sample transport condition of the high-sensitivity sample introduction system. In conclusion, the high-sensitivity sample introduction system increased the number of detected particles by about 5 times while drying the sample and applying CCT enhanced the sensitivity of analyte ions in the ion optics of sp-ICP-TOFMS by about a third for gold particle signals and a factor of 2 for multi-elemental dissolved background signals. These enhancements will help us to analyze trace isotopes in ice core mineral dust particle analysis and to characterize the chemical composition of detected particles by sp-ICP-TOFMS.

How to cite: Lee, G., Erhardt, T., Hendriks, L., Tanner, M., Delmonte, B., and Fischer, H.: Improving single particle ICP-TOFMS using a desolvation sample introduction system and collision cell technology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3732, https://doi.org/10.5194/egusphere-egu23-3732, 2023.

EGU23-7349 | Orals | GI1.1

A Rugged, Portable and Intelligent Analogue Seismometer for Future and Pre-Existing Arrays – Güralp Certis 

Dan Whealing, James Lindsey, Neil Watkiss, and Will Reis

Seismic networks often face logistical and financial challenges that require portability, longevity and interoperability with existing equipment.

Güralp have combined proven ocean bottom, borehole and digitiser technology to produce an analogue seismometer with intelligence that benefits networks of all sizes. The Güralp Certis is a broadband analogue instrument that incorporates specific aspects of its sister digital instrument (Certimus) while still remaining compatible with third-party digitisers.

Each Certis stores its own serial number, calibration and response parameters internally and will automatically communicate these to a connected Minimus digitiser. This allows seismometer-digitiser pairings to be changed without manual entry of new parameters. If using GDI-link streaming protocol with the Minimus, these metadata parameters are transmitted within (and therefore inseparable from) the datastream itself. Therefore, this small piece of intelligence in the analogue sensor removes the need for any manual re-entry of response parameters anywhere along the sensor-digitiser-client chain.

Certis enables users to install in locations with poor horizontal stability (e.g., glaciers, dynamic landslide scarps, water-saturated soils), without the need for cement bases or precise levelling, as the sensor can be deployed at any angle regardless of which model digitiser is connected. Due to its small size, low weight and ultra-low power consumption, Certis significantly reduces logistical efforts and makes short term temporary deployments far easier.

Certis addresses many challenges of traditional seismometer deployments, including cost, but provides a flexible and simple solution for seismic monitoring applications across all disciplines.

How to cite: Whealing, D., Lindsey, J., Watkiss, N., and Reis, W.: A Rugged, Portable and Intelligent Analogue Seismometer for Future and Pre-Existing Arrays – Güralp Certis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7349, https://doi.org/10.5194/egusphere-egu23-7349, 2023.

EGU23-10047 | Orals | GI1.1

Stromboli volcano monitoring with airborne SAR systems 

Riccardo Lanari, Carmen Esposito, Paolo Berardino, Antonio Natale, Gianfranco Palmese, and Stefano Perna

Synthetic Aperture Radar (SAR) is an active sensor that can be mounted onboard satellite or airborne platforms for observing of Earth’s surface in any weather condition and even during night [1]. In the last years, it has been shown that the interferometric SAR (InSAR) technique allows [2] generating high quality Digital Elevation Models (DEMs) [1] from spaceborne [3] and airborne [4–7] SAR data.

Airborne SAR systems, unlike satellite SAR ones, are particularly suitable for environmental monitoring in case of emergencies due to their capability to maintain very tight revisit times and to acquire data practically without orbital constraints. The contribution of this work fits very nicely within this context. Indeed, in this work, we show the results obtained from the data collected during the acquisition campaigns carried out with the AXIS [5] and MIPS [8] airborne X-band interferometric SAR systems over the Stromboli island (Italy). In particular, starting from multiple single-pass interferometric SAR surveys we present the differences of the generated DEMs with the aim of measuring the topographic changes induced by the eruptive activity over the whole island during the July 2019 – October 2022 time interval. The work is supported by an agreement between IREA-CNR and the Civil Protection Department of Italy.

 

References

1. Franceschetti, G.; Lanari, R. Synthetic aperture radar processing; 1999;

2. Moreira, A.; Prats-Iraola, P.; Younis, M.; Krieger, G.; Hajnsek, I.; Papathanassiou, K.P. A tutorial on synthetic aperture radar. IEEE Geosci. Remote Sens. Mag. 2013.

3. Rabus, B.; Eineder, M.; Roth, A.; Bamler, R. The shuttle radar topography mission - A new class of digital elevation models acquired by spaceborne radar. ISPRS J. Photogramm. Remote Sens. 2003.

4. Perna, S.; Esposito, C.; Amaral, T.; Berardino, P.; Jackson, G.; Moreira, J.; Pauciullo, A.; Junior, E.V.; Wimmer, C.; Lanari, R. The InSAeS4 airborne X-band interferometric SAR system: A first assessment on its imaging and topographic mapping capabilities. Remote Sens. 2016, 8.

5. Esposito, C.; Natale, A.; Palmese, G.; Berardino, P.; Lanari, R.; Perna, S. On the Capabilities of the Italian Airborne FMCW AXIS InSAR System. Remote Sens. 2020, 12.

6. Pinheiro, M.; Reigber, A.; Scheiber, R.; Prats-Iraola, P.; Moreira, A. Generation of highly accurate DEMs over flat areas by means of dual-frequency and dual-baseline airborne SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2018.

7. Wimmer, C.; Siegmund, R.; Schwäbisch, M.; Moreira, J. Generation of high precision DEMs of the Wadden Sea with airborne interferometric SAR. IEEE Trans. Geosci. Remote Sens. 2000.

8. Natale, A.; Berardino, P.; Esposito, C.; Palmese, G.; Lanari, R.; Perna, S. The New Italian Airborne Multiband Interferometric and Polarimetric SAR (MIPS) System: First Flight Test Results. Int. Geosci. Remote Sens. Symp. 2022, 2022-July, 4506–4509.

How to cite: Lanari, R., Esposito, C., Berardino, P., Natale, A., Palmese, G., and Perna, S.: Stromboli volcano monitoring with airborne SAR systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10047, https://doi.org/10.5194/egusphere-egu23-10047, 2023.

EGU23-11295 | ECS | Orals | GI1.1

Analytical performance assessment of LMS-GT, a newly-developed laboratory-scale Laser Ablation Ionization Mass Spectrometry instrument, in the context of geo- and planetary sciences 

Coenraad de Koning, Salome Gruchola, Rustam Lukmanov, Peter Keresztes Schmidt, Nikita Boeren, Andreas Riedo, Marek Tulej, and Peter Wurz

Direct analysis of micrometer-scale features embedded in solid samples of a wide chemical variety is an integral part of many fields in geo-, geobio-, and planetary sciences. Examples range from microscopic mineral inclusions in meteoritic material, (e.g., zircons, CAIs, chondrules, etc.) to biological inclusions in a variety of mineralogical host materials, e.g., (putative) fossils of microbial species. In many of these use-cases, the determination of the element and/or isotope composition, specifically those of minor or trace abundance, is of prime interest, meaning mass spectrometry is typically the preferred analysis technique.

As a result, a growing group of instruments has been (and are being) developed specifically with the purpose of element and/or isotope analysis of microscale features in solid hosts, each with its specific advantages and limitations. Perhaps the most well-known technique is (nano)SIMS, which boasts analysis spot sizes down to the nanometer level as well as ppm to ppb detection limits, but struggles with quantitativeness and capital and operating expenses. In the field of laser-based solid sampling mass spectrometric techniques, LA-ICP-MS has become a well-established technique, mainly due to its reproducibility and ease of operation. However, due to necessity to transport particles from the ablation plume to the ICP, this technique is inherently limited through fractionation effects and isobaric interferences with the plasma and carrier gas. Furthermore, sample dilution in the plasma and the subsequent loss of sample at the ICP-MS interface result in diminished limits of detection.

Another member of the laser-based solid sampling techniques is Laser Ablation Ionization Mass Spectrometry (LIMS), in which the ions present in the ablation plume are directly introduced into the mass spectrometer. This direct sampling of the ablation plume results in both a significant advantage over LA-ICP-MS (high sensitivity) and a challenge (mass resolution). The limited mass resolution of typical LIMS instruments often makes (quantitative) analysis challenging due to isobaric interferences, especially when applied to more complex materials. To solve this issue, the Laser Mass Spectrometer – Gran Turismo (LMS-GT) was developed at the University of Bern with the aim of achieving mass resolutions sufficient to resolve the most common isobaric interferences (M/ΔM = 10.000).

Over the last years, commissioning and continuous improvement of the instrument has been ongoing, which has led to a set of analytical performance characteristics which highlight the potential complementary value of LMS-GT. In this talk, we will discuss the latest technological developments1, latest analytical performance metrics (mass resolution, mass accuracy, limits of detection, etc.), and element and isotope ratio accuracies2,3. We will also discuss a case-study in which LMS-GT was used to study fossilized microbial inclusions in Gunflint chert4, highlighting both the potential strength and challenges for LMS-GT in a geo- and geobiosciences context.

1. Gruchola, S. et al., Int. J. Mass Spectrom. 474, 116803 (2022).

2. Wiesendanger, R. et al.,  J. Anal. At. Spectrom. 34, 2061–2073 (2019).

3. de Koning, C. P. et al.,  Int. J. Mass Spectrom. 470, 116662 (2021).

4. Lukmanov, R. A. et al., Front. Space Technol. 3, (2022).

How to cite: de Koning, C., Gruchola, S., Lukmanov, R., Keresztes Schmidt, P., Boeren, N., Riedo, A., Tulej, M., and Wurz, P.: Analytical performance assessment of LMS-GT, a newly-developed laboratory-scale Laser Ablation Ionization Mass Spectrometry instrument, in the context of geo- and planetary sciences, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11295, https://doi.org/10.5194/egusphere-egu23-11295, 2023.

EGU23-13597 | Orals | GI1.1 | Highlight | Christiaan Huygens Medal Lecture

Solving the ambiguity in the potential field exploration of complex sources 

Maurizio Fedi

It is theoretically demonstrated  that, even with perfectly complete and perfectly accurate data, there is a fundamental ambiguity in the analysis of potential field data. The ambiguity may be easily illustrated by computing some of the various kinds of structures that can give rise to the same anomaly field. To solve the ambiguity and yield reasonable geophysical models we must therefore supply a priori information. In gravimetry, the ambiguity comes from the fact that only the excess mass is uniquely determined by the anomaly, neither the density nor the source volume. However, not only the excess mass can be uniquely estimated. Examples are the center of a uniformly dense (or magnetized) sphere or the top of a deeply extended homogeneously-dense cylinder. A priori information may consist of direct information (e.g., depth, shape) and/or of assuming that the source distribution has some specified properties (e.g., compactness, positivity). If one tries to classify the physical source-distributions in terms of their complexity, we may however use two different scaling laws, based on homogeneity and self-similarity, which allow modeling of the Earth in its complex heterogeneity. While monofractals or homogeneous functions are scaling functions, that is they do not have a specific scale of interest, multi-fractal and multi-homogeneous models need to be described within a multiscale dataset. Thus, specific techniques are needed to manage the information contained on the whole multiscale dataset. In particular,  any potential field  generated by a complex source may be modeled as  a multi-homogeneous field, which typically present a fractional and spatially varying homogeneity degree. For a source of irregular shape, it may be convenient to invert not the  field but a related quantity, the scaling function, which is a multiscale function having the advantage of not involving the density among the unknown parameters. For density or magnetic susceptibility tomographies, the degree of spatially variable homogeneity can be incorporated in the model weighting function, which, in this way, does not require prior assumptions because it is entirely deductible from the data. We discover that difficult quantities, such as the bottom of the sources, or multiple source systems are reasonably well estimated by abandoning the analysis at a single scale and unraveling the scale-related complexity of geophysical signals. The inherent self-consistency of these new multiscale tools is a significant step forward, especially in the analysis of areas where there is scarce other information about the sources.

How to cite: Fedi, M.: Solving the ambiguity in the potential field exploration of complex sources, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13597, https://doi.org/10.5194/egusphere-egu23-13597, 2023.

The detection of vessels is considered an attractive byproduct of satellite radar altimetry, because it may complement the conventional tracking systems with the possibility to build long-term global statistics of ship traffic based on relatively small and manageable datasets of freely available data. Satellite radar altimetry was initially conceived and applied to the observation of ocean topography, being later extended to the coastal zone and to the observation of inland water.

The potentiality of SAR altimetry for the detection of ships has already been demonstrated with Cryosat2, and today Sentinel-3 is the first operational mission offering global SAR coverage with a constellation of two satellites.

Thanks to the enhanced azimuth (along-track) resolution available in the synthetic aperture radar (SAR) mode, the radar altimeter on board the Sentinel-3 satellite could be beneficial to other applications than ocean topography. In particular, this work studies the performance of algorithms for the automatic detection of ship targets from SAR mode data. In addition, the pre-processing of altimeter data by reliable detection algorithms, filtering out signal outliers from the sea surface response, largely contributes to enhance geophysical products that are typical in ocean topography studies (e.g. mean sea level).  Thus, altimeter data of today could be regarded as an additional non-cooperative source for vessel traffic monitoring or to map global traffic patterns over long periods of time.

This work proposes a processing chain based on mathematical morphology filtering and robust statistics to estimate the structured background and detect target signatures from radargrams. The detection stage is followed by an additional binary morphological filtering phase that is useful to estimate target characteristics, such as the height. The study shows that robust statistics outperform non-robust ones, in terms of target signal to background ratio and of rejection of false alarms. The study finally provides a first attempt to validate the analysis comparing detected target contacts with automatic identification system (AIS) data. 

How to cite: Scozzari, A. and Grasso, R.: Radar altimetry for the detection of ship traffic: an improved byproduct of satellite radar altimetry, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13618, https://doi.org/10.5194/egusphere-egu23-13618, 2023.

EGU23-16127 | Orals | GI1.1

SBUDNIC: lessons learned in implementing a CubeSat mission 

Lorenzo Bigagli and Rick Fleeter

The SBUDNIC project was a collaboration between The National Research Council of Italy and Brown University’s School of Engineering. The project also got support from D-Orbit, AMSAT-Italy, La Sapienza-University of Rome and NASA Rhode Island Space Grant.

This scientific cooperation started in January 2021 and aimed to improve techniques and skills in Earth observation and its applications, with particular focus on teaching, research and knowledge transfer, as well as to promote open access to documentation, software and other information and resources for developing Earth observation capabilities.

The project was led by a team of students, professors and researchers and involved the construction of a 3U CubeSat according to an open and agile approach, using mostly commercial components commonly used on Earth, including an Arduino processor and AA Energizer batteries. The satellite was designed to allow the download of low resolution images in the amateur radio band.

SBUDNIC was launched on May 25, 2022 by a SpaceX Falcon 9 rocket and was released into orbit at an altitude of about 525 kilometers by the ION Satellite Carrier platform of the Space logistics company D-Orbit.

As a New Space experiment, SBUDNIC has provided useful insights on several organizational, technological and regulatory aspects of the implementation of a CubeSat mission and confirmed the increasingly rapid and affordable accessibility of Space to the scientific and academic community.

We hope that the SBUDNIC project may be able to inspire some of the future engineers in universities, research and industry, in their effort to advance Space exploration, Earth observation techniques and innovative satellite technologies, tools that may prove of fundamental importance in addressing global challenges.

How to cite: Bigagli, L. and Fleeter, R.: SBUDNIC: lessons learned in implementing a CubeSat mission, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16127, https://doi.org/10.5194/egusphere-egu23-16127, 2023.

EGU23-16665 | Posters virtual | GI1.1

Case study for the application of micro-computed tomography on a Miocene sample of Holstein Erratics to identify and asses included molluscs and foraminifera 

Ulrich Kotthoff, Karolin Engelkes, Muofhe Tshibalanganda, Andre Beerlink, Michael Hesemann, Yvonne Milker, and Gerhard Schmiedl

The assessment of fossils in sediments and sedimentary rocks often involves the destruction of the sedimentary matrix and even of parts of the fossil assemblage (e.g. via removing and/or dissolution). Therefore, the destruction-free assessment of fossils in sediments (e.g. sediment cores) and sedimentary rocks is of great interest to the geoscience community. In addition, the three-dimensional examination of fossils becomes more and more important to evaluate morphological features and improve morphometrical analyses.

The "Holsteiner Gestein" is a sandstone and glacial erratic which is frequently found at certain outcrops in northern Germany. While the material was transported during the Pleistocene, the original deposition of this sediment took place during the Miocene, perhaps also the upper Oliocene (Schallreuter et al. 1984).

Its fossil content and paleoecology has not been investigated in detail, and since the 1980s, scientific publications on this sediment are rare. This type of material, if analysed at all, is generally subjected to destructive methods to isolate fossils such as marine snails or foraminifers (marine protists), which both comprise taxa with calcareous shells. These fossils support the reconstruction of the paleo-ecosystem and depositional environment.

In the framework of a case study, a piece of glacial erratics – “Holsteiner Gestein” was scanned with a Comet Yxlon FF35 CT system employing the directional beam tube: First, an overview scan of the whole sample (210 kV, 160 µA, 1.0 mm Cu filter, 50.00 µm iso-voxel size) was used to identify a region with high fossil count and potentially interesting fossils. The region of interest was then scanned (210 kV, 160 µA, 1.0 mm Cu filter 7.23 µm iso-voxel size) with higher resolution using a scan trajectory with a flexible rotation center that allowed for maximal resolution by adjusting the position of the sample such that it was located as close as possible to the x-ray tube but a collision was prevented. In addition, a laminography scan (180 kV, 70 µA, 0. 5 mm Cu filter, 5.02x5.02x9.58 µm voxel size) was performed to achieve the maximally possible sharpness and resolution in cross-sectional images. Data were visualized and analysed in the software Amira (version 6.0.1).

Our approach did not only enable us to three-dimensionally assess relatively big snails shells, but also foraminifera of less than 1 mm in size. The scans additionally allow quantifying the number of microfossils inside a certain part of the sample.

The foraminiferal taxa comprise agglutinating foraminifers which closely resemble the genus Entzia. These imply a former salt marsh environment.

This work is distributed under the Creative Commons Attribution 4.0 License. This licence does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 4.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other.

References:

Schallreuter, R., Vinx, R., Lierl, H.J. (1984): Geschiebe in Südholstein. In Degens et al. (eds.): Exkursionsführer Erdgeschichte des Nordsee- und Ostseeraumes, Geologisch-Paläontologisches Institut der Universität Hamburg.

How to cite: Kotthoff, U., Engelkes, K., Tshibalanganda, M., Beerlink, A., Hesemann, M., Milker, Y., and Schmiedl, G.: Case study for the application of micro-computed tomography on a Miocene sample of Holstein Erratics to identify and asses included molluscs and foraminifera, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16665, https://doi.org/10.5194/egusphere-egu23-16665, 2023.

EGU23-16722 | Orals | GI1.1

Cost Efficient Station Monitoring and Remote Data Retrieval for Portable Seismic Stations 

Valarie Hamilton, Sylvain Pigeon, Tim Parker, Michael Perlin, and Michael Laporte

Remote monitoring as well as remote waveform data retrieval is an enabling capability for portable stations used in seismic hazards studies. Remote monitoring provides intra-deployment visibility of system performance to allow prompt detection, and subsequent resolution, of faults which may otherwise go undetected for the duration of the deployment and jeopardize a seismic campaign's successful outcome.  Waveform data retrieval allows intra-deployment quality control (QC) and can enable faster science. These benefits must be considered against the associated power consumption and telemetry bandwidth costs. These tradeoffs may drive a system implementation that limits remote retrieval to low resolution data or, in other use cases, restricts the retrieval of full resolution waveform data to specific periods of interest only.  In the case of deployments in harsh environments, such as polar or ocean bottom environments where field visits are cost prohibitive or may not be possible, even high cost remote retrieval of a complete data set may be preferable if it offers a savings and / or a reduction in operational risk in comparison to a station visit.

As part of this session, we discuss how advancement in low power portable geoscience instrumentation, combined with low power communication technology, deliver these new capabilities with flexible implementation balancing function and operational cost.

How to cite: Hamilton, V., Pigeon, S., Parker, T., Perlin, M., and Laporte, M.: Cost Efficient Station Monitoring and Remote Data Retrieval for Portable Seismic Stations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16722, https://doi.org/10.5194/egusphere-egu23-16722, 2023.

The deposition of heavy metals on water bodies and soil has adverse consequences on
human health. The elevated Coal-based energy production and increased industrial emissions
have also prompted us to study about heavy metals reactive nitrogen species in the
atmosphere. In the present work, the samples of rain water were collected from a residential
site in south-west Delhi. The samples were analyzed for selected heavy metals by using ICP-
OES. The heavy metals analysis involved voltammetry method using 797 VA Computrace
(Metrohm, Switzerland) instrument. The analysis of Total Nitrogen (TN) and dissolved
organic carbon (DOC) was carried out by using chemiluminescence based TN/TOC analyzer
(Shimadzu model TOC-LCPH E200 ROHS). The mean values of Cu, Mn, Zn, Al, As and Hg
were calculated as 34.5 mg/l, 19.5 mg/l, 52.7 mg/l, 392.3 mg/l, 9.8 mg/l and 1.6 mg/l
respectively. The mean values for TN and DOC were 12.7mg/l and 2.8 mg/l respectively. The
detailed results will be discussed in the EGU General Assembly Meeting.

Keywords: Total Nitrogen, wet deposition, ICP-OES, voltammetry, agricultural area.

How to cite: sunaina, S.: Wet deposition of heavy metals, reactive nitrogen species and dissolved organic carbonat a residential site in Delhi region, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-345, https://doi.org/10.5194/egusphere-egu23-345, 2023.

EGU23-1075 | ECS | Posters on site | GI1.3

What can we learn from nested IoT low-cost sensor networks for air quality?  A case study of PM2.5 in Birmingham UK. 

Nicole Cowell, Clarissa Baldo, William Bloss, and Lee Chapman

Birmingham is a city within the West Midlands region of the United Kingdom. In June 2021, coinciding with the introduction of the Clean Air Zone by Birmingham City Council (BCC), multiple low-cost IoT sensor networks for air pollution were deployed across the city by both the University of Birmingham and BCC. Low-cost sensor networks are growing in popularity due to their lower costs compared to regulatory instruments (£10’s-£1000’s per unit compared to £10,000+ per unit) and the reduced need for specialised staff allow for deployments at greater spatial scales (1-3).  Although such low-cost sensing is often associated with uncertainty, the measurement of PM2.5 optical particle counters have been generally shown to perform well, giving indicative insight into concentrations following calibrations and corrections for external influence such as humidity (4-7). 

One common problem with sensor networks is they tend to be isolated and unopen deployments, deployed and maintained by an interested party with the focus of their own monitoring goal. To tackle this, Birmingham Urban Observatory was an online platform created and used by researchers at the University of Birmingham to host and share open access meteorological and air pollution data from low-cost sensor deployments. Whilst hosting and displaying data from two of their own deployments of air quality sensors (Zephyrs by Earthsense and AltasensePM: an in-house designed PM sensor), the platform also pulled data from the DEFRA AURN sites and collaborated with local government to pull data from their own low-cost sensor network. The result was a real-time view of environmental data produced from a series of nested arrays of sensors.

This poster presents findings from this combined low-cost network, considering the successes and pitfalls of the low-cost monitoring network alongside insight into regional and local PM2.5 concentrations. Colocations against reference instruments within the network demonstrate good performance of the low-cost sensors after calibration and data validation but the project experienced challenges in deploying the network and sensor reliability. Low-cost sensor data generally gives novel insight into spatial analysis of PM2.5 across the city and this is presented alongside other experiences of deploying and using sensor networks for air quality.

1 Lewis et al., (2016) https://doi.org/10.1039/C5FD00201J

2 Chong and Kumar. (2003) doi: 10.1109/JPROC.2003.814918

3 Snyder et al., (2013) https://doi.org/10.1021/es4022602

4 Magi et al., (2020) https://doi.org/10.1080/02786826.2019.1619915

5 Crilley et al., (2018) https://doi.org/10.5194/amt-11-709-2018

6 Cowell et al., (2022) https://doi.org/10.3389/fenvs.2021.798485

7 Cowell et al., (2022) https://doi.org/10.1039/D2EA00124A

How to cite: Cowell, N., Baldo, C., Bloss, W., and Chapman, L.: What can we learn from nested IoT low-cost sensor networks for air quality?  A case study of PM2.5 in Birmingham UK., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1075, https://doi.org/10.5194/egusphere-egu23-1075, 2023.

EGU23-2847 | Posters on site | GI1.3

Atmospheric ammonia in-situ long-term monitoring: review worldwide strategies and recommendations for implementation 

Aude Bourin, Pablo Espina-Martin, Anna Font, Sabine Crunaire, and Stéphane Sauvage

Ammonia (NH3) is the major alkaline gas in the atmosphere and the third most abundant N-containing species, after N2 and N2O. It plays an important role in N deposition processes, responsible of several damages on ecosystems, and it is also a precursor of fine particulate matter, known to cause numerous impacts on human health. Despite this, not many countries have implemented long-term monitoring of NH3 in their air quality programs due to the lack of consensus on limit values for ambient levels and a reference method of measuring this gas. In the climate change context, governments and health organizations are increasingly concerned about NH3 and its effects. As a proof, the revision of the EU air quality directives proposes the inclusion of NH3 as a mandatory pollutant for several urban and rural supersites for all member states.

Currently, there are only 12 long term programs worldwide dedicated specifically to measure NH3 or including gas-phase measurements of NH3. The longest NH3 time series come from UK and Africa, where measurements start in mid-1990. The rest of locations have started after 2000 and they have lower temporal coverage, between 5 and 22 years. The objectives pursued by these networks are to follow long term spatio-temporal trends, assess the N deposition on sensitive ecosystems, validate emission and/or chemistry transport models and help to understand the effectiveness of air pollution control and mitigation policies. Most of these networks operate using a combination of low-cost samplers with a high spatial density with few collocated sites with high time resolution instrumentation to help calibrate passive samplers and to better monitor the fine temporal variability of NH3. This combined approach has proven to be successful for most of the proposed objectives.

However, there are several differences that may difficult harmonizing the information at both the technical and scientific level. At the technical level these include type and number of passive samplers per site, calibration protocol, data control and quality analysis, exposure duration and type of high time resolution sampling method. On the scientific level, increased difficulty understanding the operative parameters and scientific results may come from language barriers (non-English reports), availability of the data (whether it is public or not), and gaps on the knowledge of NH3 levels on a spatial scale due to differences in the implementation of monitoring strategies within the same country.

This work aims to review synthetically the world current long-term NH3 networks and provide some insight and recommendations for other countries and supranational programs aiming to establish long term monitoring networks of NH3, based on cost-effective, technical, and operational criteria.

How to cite: Bourin, A., Espina-Martin, P., Font, A., Crunaire, S., and Sauvage, S.: Atmospheric ammonia in-situ long-term monitoring: review worldwide strategies and recommendations for implementation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2847, https://doi.org/10.5194/egusphere-egu23-2847, 2023.

EGU23-2984 | ECS | Posters virtual | GI1.3

The COllaborative Carbon Column Observing Network COCCON: Showcasing GHG observations at the COCCON Tsukuba site 

Matthias Max Frey, Isamu Morino, Hirofumi Ohyama, Akihiro Hori, Darko Dubravica, and Frank Hase

Greenhouse gases (GHGs) play a crucial role regarding global warming. Therefore, precise and accurate observations of anthropogenic GHGs, especially carbon dioxide and methane, are of utmost importance for the estimation of their emission strengths, flux changes and long-term monitoring. Satellite observations are well suited for this task as they provide global coverage. However, like all measurements these need to be validated.

The COllaborative Carbon Column Observing Network (COCCON) performs ground-based observations to retrieve column-averaged dry air mole fractions of GHGs (XGAS) with reference precision. The instrument used by the network is the EM27/SUN, a solar-viewing Fourier Transform infrared (FTIR) spectrometer. COCCON data are of high accuracy as COCCON uses species dependent airmass-independent and airmass-dependent adjustments for tying the XGAS products to TCCCON (Total Carbon Column Observing Network) and thereby to the World Meteorological Organization (WMO) reference scale. Moreover, instrument specific characteristics are measured for each COCCON spectrometer, and taken into account in the data analysis.

Here we first introduce the COCCON network in general and summarize its capabilities for various challenges including satellite and model validation, long-term observation of GHGs, and local and regional GHG source emission strength estimations. By example of the COCCON Tsukuba station we highlight in detail its usefulness for the above-mentioned applications.

How to cite: Frey, M. M., Morino, I., Ohyama, H., Hori, A., Dubravica, D., and Hase, F.: The COllaborative Carbon Column Observing Network COCCON: Showcasing GHG observations at the COCCON Tsukuba site, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2984, https://doi.org/10.5194/egusphere-egu23-2984, 2023.

EGU23-7462 | ECS | Orals | GI1.3

Data infrastructure for nitrogen compound emissions monitoring 

Daniel Bertocci, Burcu Celikkol, Shaojie Zhuang, and Jasper Fabius

Emissions of nitrogen compounds, including nitrogen dioxide (NO2) and ammonia (NH3), have significant impacts on air quality and the environment. To effectively monitor the spatial and temporal variability of these emissions and the efficacy of emission mitigation measures, OnePlanet Research Center is developing a low-cost sensor system to monitor outdoor NO2 and NH3concentrations. This sensor system is designed to be deployable in fine-grained networks to accurately capture the dispersion from an emitting source. The deployment of multitudes of such sensor systems will result in large volumes of data. For this purpose, we developed a data infrastructure using the OGC SensorThings API and TimescaleDB, a time-series database extending PostgreSQL. This infrastructure allows for the efficient storage, management, and analysis of large volumes of spatiotemporal data from various sources, such as air quality monitoring networks, meteorological data, and agricultural practices. We demonstrate the potential of this infrastructure by using it in citizen science project COMPAIR, combining data from various sensors to gain insights on the air quality impact of urban circulation policies. The resulting data platform will facilitate the development of decision support tools and the implementation of targeted emission reduction strategies.

How to cite: Bertocci, D., Celikkol, B., Zhuang, S., and Fabius, J.: Data infrastructure for nitrogen compound emissions monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7462, https://doi.org/10.5194/egusphere-egu23-7462, 2023.

Even in the presence of more reliable air quality tools, low-cost sensors have the benefit of recording data on highly localized spatial and temporal scales, allowing for multiple measurements within a single satellite pixel and on pixel boundaries. However, they are less accurate than their regulatory-grade counterparts, requiring regular co-locations with accepted instruments to ensure their validity. Thus, the addition of low-cost sensors to a field campaign – where reference-grade air quality instruments are abundant – not only provides ample opportunities for low-cost sensor co-location and calibration, but also allows the low-cost instruments to be used for sub-pixel validation, covering more surface area than the regulatory instruments alone with a network of sensors. During the summer of 2014, our low-cost sensor network was deployed during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) campaign conducted to sample the composition of air at and above ground level in northeastern Colorado, USA. The low-cost sensor platform included a suite of gas-phase sensors, notably NO2 and two generalized volatile organic compound (VOC) sensors, which were leveraged together to quantify speciated hydrocarbons such as formaldehyde. These key pollutants were chosen for their impacts on human health and climate change, as well as their inclusion on the TEMPO satellite launching this year. Airborne campaign measurements included slant column optical observations of formaldehyde (HCHO), nitrogen dioxide (NO2), and ozone (O3). Myriad additional in-situ instruments described chemical composition up to approximately 5 km above surface level. Ground-based instrumentation included both stationary and mobile regulatory-grade instruments, which were used for sensor calibration. Machine learning techniques such as artificial neural networks (ANNs) were used to match the low-cost signals to that of the reference-grade instruments. Here, we compare calibrated low-cost sensor data collected at ground level in a variety of locations along Colorado’s Front Range to various data sources from the FRAPPÉ campaign to better understand how well airborne and regulatory ground-based measurements can be extrapolated to other locations. Further, as the slant column measurements act as satellite simulators, we explore how low-cost instruments can be used for satellite validation purposes. Comparisons among these different data types also have important implications in data fusion.

How to cite: Okorn, K., Iraci, L., and Hannigan, M.: Comparing Low-Cost Sensors with Ground-Based and Airborne In-Situ and Column Observations of NO2 and HCHO during the FRAPPE Field Campaign in Colorado, USA, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7839, https://doi.org/10.5194/egusphere-egu23-7839, 2023.

EGU23-8631 | Posters on site | GI1.3 | Highlight

Ambient conditions and infrared sky brightness in the Chilean Atacama Desert 

Wolfgang Kausch, Stefan Kimeswenger, Stefan Noll, and Roland Holzlöhner

The Atacama Desert in the Chilean Andes region is one of the dryest areas in the world. Due to its unique location with stable subtropical meteorological conditions and high mountains, it is an ideal site for the astronomical telescope facilities of the European Southern Observatory (ESO). The special meteorological conditions are continuously monitored at Cerro Paranal (the location of the Very Large Telescope) by measuring various parameters like temperature, pressure, humidity, precipitable water vapour (PWV), wind speed and direction, and sky radiance and bolometric sky temperature, respectively, the latter being crucial for astronomical observations in the thermal infrared regime. ESO operates several site monitoring systems for that purpose, e.g. the ESO MeteoMonitor, the Differential Image Motion Monitor (DIMM) and a Low Humidity And Temperature PROfiler (L-HATPRO) microwave radiometer providing detailed water vapour and temperate profiles up to a height of 12km in various directions. 


We have assembled all available data for a period of 4.5 years (2015-07-01 through 2019-12-31) and created a unique data set from it. This period also covers the strong El Niño event at the end of 2015. In this poster we present statistical results on the overall conditions and trends, and compare our measurements of the nocturnal sky brightness with an empirical model as function of the ambient temperature, PWV and zenith distance.

How to cite: Kausch, W., Kimeswenger, S., Noll, S., and Holzlöhner, R.: Ambient conditions and infrared sky brightness in the Chilean Atacama Desert, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8631, https://doi.org/10.5194/egusphere-egu23-8631, 2023.

Air quality monitoring networks provide invaluable data for studying human health, environmental impacts, and the effects of policy changes,  but obtaining high quality data can be costly, with each site in a monitoring network requiring instrumentation and skilled operator time. It is therefore important to ensure that each monitor in the network is providing unique data to maximize the value of the entire network.  Differences in measurement approaches for the same chemical between monitoring stations may also result in discontinuities in the network data.  Both of these factors suggest the need for objective, machine-learning methodologies for monitoring network data analysis.   

Air quality models are another valuable tool to augment monitoring networks.  The models simulate air quality over a large region where monitoring may be sparse. The gridded output from air-quality models thus contain inherent information on the similarity of sources, chemical oxidation pathways and removal processes for chemicals of interest, provided appropriate tools are available to identify these similarities on a gridded basis.  The output from these models can be immense, again requiring the use of special, highly optimized tools for post-processing analysis.

Spatiotemporal clustering is a family of techniques that have seen widespread use in air quality, whereby time-series taken at different locations are grouped based on the level of similarity between time-series data within the dataset.   Hierarchical clustering is one such algorithm, which has the advantage of not requiring an a priori assumption about how many clusters there might be (unlike K-means).  However, traditional approaches for hierarchical clustering become computationally expensive as the number of time-series increases in size, resulting in prohibitive computational costs  when the total number of time-series to be compared rises above 30,000, even on a supercomputer.  Similarly, the comparison and clustering of large numbers of discrete data (such as multiple mass spectrometer data sampled at high time resolution from a moving laboratory platform) becomes computationally prohibitive using conventional methods. 

In this study we present a high-performance hierarchical clustering algorithm which is able to run in parallel over many nodes on massively parallel computer systems, thus allowing for efficient clustering for very large monitoring network and model output datasets.   The new high-performance program is able to cluster 290,000 annual time series (from either monitoring network data or gridded model output) in 13 hours on 800 nodes. We present here some example results showing how the algorithm can be used to analyse very large datasets, providing new insights into “airsheds” depicting regions of similar chemical origin and history, different spatial regimes for nitrogen, sulphur, and base cation deposition, .  These analyses show how different processes control each species at different potential monitoring site locations, via cluster-generated airshed maps for each species. The efficiency and flexibility of the algorithm allows for extremely large datasets to be analysed in hours of wall-clock time instead of weeks or months. The new algorithm is being used as the numerical engine for a new tool for the analysis of EU monitoring network data. 

How to cite: Lee, C., Makar, P., and Soares, J.: Spatio-temporal clustering on a high-performance computing platform for high-resolution monitoring network analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8841, https://doi.org/10.5194/egusphere-egu23-8841, 2023.

22 cost-efficient (aka ‘low-cost’) commercially available particulate matter (PM) measurement devices were installed in a diverse urban area in Leipzig, Germany. The instruments measure mostly PM2.5, some additionally PM10, and are equipped with methods for quality assurance such as conditioning to a defined temperature and regular internal calibration. In order to investigate the spread between the instruments and to enable a pre-campaign calibration, all instruments were setup in the laboratory and the outside air and compared against the same reference measurements.

Since July 2022, the measurement network was installed. It covers roughly 2x2 km2 and holds different urban features like residential and commercial buildings, important main roads, city parks, and small open building gaps. Within the network there is an official air quality monitoring station located directly at a main road. In addition, at two further official monitoring stations as well as at observation stations of the Leibniz Institute for Tropospheric Research instruments were installed to study the long-term performance, dependence on meteorological conditions and comparison to reference measurements. The measurements will take place until end of 2023.

The cost-efficient instruments perform generally quite well after the calibration. In particularly for higher PM loads > 10 µg m-3 the agreement against references is mostly satisfying. However, under very high relative humidity and cold temperatures, some instruments lacked to condition the air sufficiently. Despite these difficulties, the chosen instruments have the potential for application in monitoring of air quality limit values, i.e. the answer the question how often are certain limits exceeded.

Furthermore, differences between different local features in the observation area could be observed in e.g., the diurnal cycle but also peak and mean concentrations.

This work is co-financed with tax funds on the basis of the budget passed by the Saxon State Parliament (funding number 100582357).

How to cite: Schrödner, R., Alas, H., and Voigtländer, J.: Application of cost-efficient particulate matter measurement devices in an urban network and comparison to state-of-the-art air quality monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9356, https://doi.org/10.5194/egusphere-egu23-9356, 2023.

EGU23-9537 | Posters on site | GI1.3

The Global Environmental Measurement and Monitoring Initiative – An International Network for Local Impact 

Daniel Klingenberg, D. Michelle Bailey, David Lang, and Mark Shimamoto

The Global Environmental Measurement and Monitoring (GEMM) Initiative is an international project of Optica and the American Geophysical Union seeking to provide precise and usable environmental data for local impact. The Initiative brings together science, technology, and policy stakeholders to address critical environmental challenges and provide solutions to inform policy decisions on greenhouse gases (GHGs) and air and water quality. GEMM Centers are currently established in Scotland, Canada, New Zealand, and the United States. These Centers represent partnerships with leading institutions that are actively working toward developing or deploying new measurement technology and improved climate models. Additional Centers are under development in India and Australia with plans to expand to Asia and Africa.

In addition to establishing monitoring centers worldwide, GEMM actively engages with other sectors (including industry, standards organizations, and regional or national governments) to support the incorporation or adoption of these evidence-based approaches into decision making processes. For example, Glasgow, Scotland is piloting the GEMM Urban Air Project, deploying a low-cost, real-time, ground-based network of devices that continuously monitors GHGs and air pollutants at a neighborhood scale. The sensor network in Glasgow is increasing the precision of local models that can provide the city with information to assess current policies and support future action. Here we will share the progress and outputs of the GEMM Initiative to date and highlight paths forward to grow the network.

How to cite: Klingenberg, D., Bailey, D. M., Lang, D., and Shimamoto, M.: The Global Environmental Measurement and Monitoring Initiative – An International Network for Local Impact, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9537, https://doi.org/10.5194/egusphere-egu23-9537, 2023.

Since the discovery of the chlorofluorocarbons (CFCs) implication in stratospheric ozone destruction, the Montreal Protocol (1987) has aimed at controlling the production of CFCs and other ozone depleting substances (ODS) in order to protect and then recover the ozone layer. Consequently, temporary substitutes for CFCs have been developed and produced by the industry. First substitute molecules were hydrochlorofluorocarbons (HCFCs), which have smaller ozone depletion potentials (ODP) than CFCs since their atmospheric lifetimes are shorter. Nevertheless, HCFCs still contain chlorine atoms and hence, also deplete the stratospheric ozone, requiring them to be banned in turn. Thus, chlorine-free molecules, i.e. hydrofluorocarbons (HFCs) such as CH2FCF3 (HFC-134a) were introduced to replace both CFCs and HCFCs. Even if HFCs do not contribute to ozone depletion, they are very powerful greenhouse gases since they have great global warming potentials (GWPs). Consequently, the Kigali amendment (2016) to the Montreal Protocol aimed for their phase-out.

The atmospheric concentrations of CFCs have decreased in response to the phase-out and ban of their production by the Montreal Protocol and its subsequent amendments, while the HCFCs burden is now leveling off. In contrast, the atmospheric concentrations of HFCs have increased notably in the last two decades.

We present the first retrievals of HFC-134a from Fourier Transform Infra-Red (FTIR) solar spectra obtained from a remote site of the Network for the Detection of Atmospheric Composition Change (NDACC.org): the Jungfraujoch station (Swiss Alps). We discuss of the applicability of our retrieval strategy to other NDACC sites, for future quasi global monitoring from ground-based observations. We further perform first comparisons with other datasets as ACE-FTS satellite observations.

 

How to cite: Pardo Cantos, I. and Mahieu, E.: First HFC-134a retrievals and analysis of long-term trends from FTIR solar spectra above NDACC network stations: the Jungfraujoch case, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11033, https://doi.org/10.5194/egusphere-egu23-11033, 2023.

Monitoring networks, able to effectively provide high-frequency geochemical data for characterizing the geochemical behavior of the main greenhouse gases (i.e., CO2 and CH4) and pollutants (e.g., heavy metals) are crucial tools for the assessment of air quality and its role in climate changes. However, the provision of measurement stations dedicated to monitor gas species and particulate in polluted areas is complicated by the high cost of their set-up and maintenance. In the last decade, traditional instruments have tentatively been coupled with low-cost sensors for improving spatial coverage and temporal resolution of air quality surveys. The main concerns of this new approach regard the in-field accuracy of the low-cost sensors, being significantly dependent on: (i) cross-sensitivities to other atmospheric pollutants, (ii) environmental parameters (e.g., relative humidity and temperature), and (iii) detector signal degradation over time.

This study presents the results of a geochemical survey carried out in the Greve River Basin (Chianti territory, Central Italy) from May to September 2022 by adopting two measuring strategies: (i) deployment of a mobile station, along predefined transepts within the Greve valley, equipped with a Picarro G2201-i analyzer to measure CO2 and CH4 concentrations and δ13C-CO2 and δ13C-CH4 values (‰ vs. V-PDB) by Wavelength-Scanned Cavity Ring-Down Spectroscopy (WS-CRDS); (ii) continuous monitoring, at five fixed sites positioned at different altitudes, of CO2 and CH4 concentrations through prototyped low-cost stations, coupled with atmospheric deposition and rain samplers to collect particulate samples for chemical lab analysis. The low-cost monitoring stations housed (i) a non-dispersive infrared (NDIR) sensor for CO2 concentrations, (ii) a solid-state metal oxide sensor (MOS) for CH4 concentrations, (iii) a laser light scattering sensor (LSPs) for PM2.5 and PM10 concentrations, and (iv) a sensor for temperature and relative humidity in the air. The CO2 and CH4 sensors have been calibrated in-field based on parallel measurements with the Picarro G2201-i and elaborating the calibration data with the Random Forest machine learning-based algorithm.

The measurements carried out along the transepts showed that the downstream areas next to the metropolitan city of Florence were affected by the highest concentrations of CO2 and CH4, marked by isotopic signatures revealing a clear anthropogenic origin, mainly ascribed to vehicular traffic. The distribution of these carbon species reflected the evolution of the atmospheric boundary layer, displaying higher concentrations during the early morning, when gas accumulation occurred due to stable atmospheric conditions, and lower concentrations during daytime when the heating of the surface favored the dilution of air pollutants due to the establishment of convective turbulence. These observations were confirmed by the network of low-cost stations, which allowed to simultaneously monitor the distribution of the atmospheric pollutants at different altitudes in the valley. The distribution of particulate was consistent with that of the gaseous species, and the main sources were clearly distinguished based on the chemical composition of the atmospheric deposition in the collection sites. The promising results from the present study could result in an affordable approach to effectively improve air quality monitoring strategies and support data-driven policy actions to reduce carbon emissions.

How to cite: Biagi, R., Ferrari, M., Tassi, F., and Venturi, S.: Multi-instrumental approach for air quality monitoring: characterization and distribution of greenhouse gases and atmospheric metal deposition in the Greve River Basin (Chianti territory, Central Italy)., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11385, https://doi.org/10.5194/egusphere-egu23-11385, 2023.

EGU23-13997 | ECS | Posters on site | GI1.3

Correction, gap filling and homogenization on daily level of the historical DMI station network temperature data 

Dina Rapp, Bo Møllesøe Vinther, Jacob L. Høyer, and Eigil Kaas

As climate change is amplified in the Arctic, it is crucial to have temperature records of high temporal resolution and quality in this area. This will help improve understanding of the involved physical mechanisms, assessment of the past changes and improve predictions for the future temperature development in the Arctic. In this study temperature measurements from the DMI Greenland station network spanning 1784-present day are corrected, gap-filled and homogenized on a daily level. Currently homogenized data is only available on a monthly level, and the more recent data has not been homogenized. The data is currently used for purposes like assessment and predictions of the surface mass balance of the Greenland Ice Sheet, temperature/climate reanalyses, validation of proxy data, etc.  

This study presents a method for improving the calculation of daily average temperatures, from the current practice of averaging the available measurements without considering what time of day they are from and how the measurements are distributed. The method is based on a moving average taking into consideration time of day, time of year and latitude/longitude of the station in question. An estimate of the related uncertainty is also calculated. Following the generation of daily average temperatures, different gap filling methods are tested. The different algorithms tested and compared are: simple gap filling by linear interpolation with other stations, single station temporal linear interpolation and MEM (Maximum Entropy Method). Finally, homogenization on daily level is performed. These steps will in turn also improve the monthly and annual average temperatures for the DMI Greenland station network. 

How to cite: Rapp, D., Møllesøe Vinther, B., L. Høyer, J., and Kaas, E.: Correction, gap filling and homogenization on daily level of the historical DMI station network temperature data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13997, https://doi.org/10.5194/egusphere-egu23-13997, 2023.

The Global Atmosphere Watch (GAW) Programme was established in 1989 in recognition of the need for improved scientific understanding of the increasing influence of human activities on atmospheric composition and subsequent societal impacts. It is implemented as an activity of the World Meteorological Organization, a specialized agency of the United Nations system, and is funded by the organization member countries.

As an international programme, GAW supports a broad spectrum of applications from atmospheric composition-related services to contribution to environmental policy. The examples of the later include provision of a comprehensive set of high quality and long-term globally harmonized observations and analysis of atmospheric composition for the United Nations Framework Convention on Climate Change (UNFCCC), the Montreal Protocol on Substances that Deplete the Ozone Layer and follow-up amendments, and the Convention on Long-Range Transboundary Air Pollution (CLRTAP).

The programme includes six focal areas: Greenhouse Gases, Ozone, Aerosols, Reactive Gases, Total Atmospheric Deposition and SolarUltraviolet Radiation.

The surface-based observational network of the programme includes Global (31 stations) and Regional (about 400 stations) stations where observations of various GAW parameters occur. These stations are complemented by regular ship cruises and various contributing networks. All observations are linked to common reference standards and the observational data are made available at seven designated World Data Centres (WDC).

Surface-based observations are complemented by airborne and space-based observations that help to characterize the upper troposphere and lower stratosphere, with regards to ozone, solar radiation, aerosols, and certain trace gases.

Requirements to become a GAW station are detailed in the GAW Implementation Plan 2016-2023 (WMO, 2017). A new IP is in preparation, the four strategic objectives will be presented.

  • The GAW Quality Management comprises: Data Quality Objectives, Measurement Guidelines, Standard Operating Procedures and Data Quality Indicators. Throughout the programme the common quality assurance principles apply, that include requirements for the long-term sustainability of the observations, use of one network standard for each variable and implementation of the measurement practices that satisfy the set data quality objectives. GAW implements open data policy and requires observational data be made available in the dedicated data centers operated by WMO Member countries.

The programme relies on different types of central facilities: Central Calibration Laboratories, Quality Assurance/Science Activity Centres, World and Regional Calibration Centres, which are also directly supported and implemented by the individual Member countries for the global services.

Majority of the recommendations regarding measurement and quality assurance procedures are developed by the expert and advisory groups within the programme, often those rely on the expertise withing the contributing networks and collaborating organizations, like the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) or the Integrated Carbon Observation System (ICOS).

One of the GAW priorities is to expand and strengthen partnerships with contributing networks, through development of statements and strategies to articulate the mutual benefits for the collaborations and stream-line processes of data reporting and exchange of QA standards and metadata. This involves collaboration with national and regional environmental protection agencies and the development of harmonized metadata and data exchange and quality information.

How to cite: Moreno, S.: The WMO Global Atmosphere Watch Programme new implementation plan and strategic objectives, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14442, https://doi.org/10.5194/egusphere-egu23-14442, 2023.

EGU23-14459 | ECS | Orals | GI1.3

Developing and testing a validation procedure to successfully use on-the-move sensors in urban environments 

Francesco Barbano, Erika Brattich, Carlo Cintolesi, Juri Iurato, Vincenzo Mazzarella, Massimo Milelli, Abdul Ghafoor Nizamani, Maryam Sarfraz, Antonio Parodi, and Silvana Di Sabatino

With the increasing attempt to empower citizens and civil society in promoting virtuous behaviours and relevant climate actions, novel user-friendly and low-cost tools and sensors are nowadays being developed and distributed on the market. Most of these sensors are typically easy to install with a ready-to-use system, while measured data are automatically uploaded on a mobile application or a web dashboard which also guarantees secure and open access to measurements gathered by other users. However, the quality of the datum and the calibration of these sensors are often ensured against research-grade instrumentations only in the laboratory and rarely in real-world measurement. The discrepancies arising between these low-cost sensors and research-grade instrumentations are such that the first might be impossible to use if a validation (and re-calibration if needed) under environmental conditions is not performed. Here we propose a validation procedure applied to the MeteoTracker, a recently developed portable sensor to monitor atmospheric quantities on the move. The ultimate scope is to develop and implement a general procedure to test and validate the quality of the MeteoTracker data to compile user guidelines tailored for on-the-move sensors. The result will evaluate the feasibility of MeteoTracker (and potentially other on-the-move sensors) to integrate the existing monitoring networks on the territory, improve the atmospheric data local coverage and support the informed decision by the authorities. The procedure will include multi-sensor testing of all the sensor functionalities, validation of all data simultaneously acquired by several sensors under similar conditions, methods and applications of comparisons with research-grade instruments. The first usage of the MeteoTracker will be also presented for different geographical contexts where the sensors will be used for citizen science activities and develop a monitoring network of selected Essential Variables within the HORIZON-EU project I-CHANGE (Individual Change of HAbits Needed for Green European transition).

How to cite: Barbano, F., Brattich, E., Cintolesi, C., Iurato, J., Mazzarella, V., Milelli, M., Nizamani, A. G., Sarfraz, M., Parodi, A., and Di Sabatino, S.: Developing and testing a validation procedure to successfully use on-the-move sensors in urban environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14459, https://doi.org/10.5194/egusphere-egu23-14459, 2023.

EGU23-15087 | Posters on site | GI1.3

Applications of an advanced clustering tool for EU AQ monitoring network data analysis 

Joana Soares, Christoffer Stoll, Islen Vallejo, Colin Lee, Paul Makar, and Leonor Tarrasón

Air quality monitoring networks provide invaluable data for studying human health, environmental impacts, and the effects of policy changes. In a European legislative context, the data collected constitutes the basis for reporting air quality status and exceedances under the Ambient Air Quality Directives (AAQD) following specific requirements. Consequently, the network's representativity and ability to accurately assess the air pollution situation in European countries become a key issue. The combined use of models and measurements is currently understood as the most robust way to map the status of air pollution in an area, allowing it to quantify both the spatial and temporal distribution of pollution. This spatial-temporal information can be used to evaluate the representativeness of the monitoring network and support air quality monitoring design using hierarchical clustering techniques.

The hierarchical clustering methodology applied in this context can be used as a screening tool to analyse the level of similarity or dissimilarity of the air concentration data (time-series) within a monitoring network. Hierarchical clustering assumes that the data contains a level of (dis)similarity and groups the station records based on the characteristics of the actual data. The advantage of this type of clustering is that it does not require an a priori assumption about how many clusters there might be, but it can become computationally expensive as the number of time-series increases in size. Three dissimilarity metrics are used to establish the level of similarity (or dissimilarity) of the different air quality measurements across the monitoring network: (1) 1-R, where R is the Pearson linear correlation coefficient, (2) the Euclidean distance (EuD), and (3) multiplication of metric (1) and (2). The metric based on correlation assesses dissimilarities associated with the changes in the temporal variations in concentration. The metric based on the EuD assesses dissimilarities based on the magnitude of the concentration over the period analysed. The multiplication of these two metrics (1-R) x EuD assesses time variation and pollution levels correlations, and it has been demonstrated to be the most useful metric for monitoring network optimization.

This study presents the MoNET webtool developed based on the hierarchical clustering methodology. This webtool aims to provide an easy solution for member states to quality control the data reported as a tier-2 level check and evaluate the representativeness of the air quality network reporting under the AAQD. Some examples from the ongoing evaluation of the monitoring site classification carried out as a joint exercise under the Forum for Air Quality Modeling (FAIRMODE) and the National Air Quality Reference Laboratories Network (AQUILA) are available to show the usability of the tool. MoNet should be able to identify outliers, i.e., issues with the data or data series with very specific temporal-magnitude profiles, and to distinguish, e.g., pollution regimes within a country and if it resembles the air quality zones required by the AAQD and set by the member states; stations monitoring high-emitting sources; background regimes vs. a local source driving pollution regime in cities.

How to cite: Soares, J., Stoll, C., Vallejo, I., Lee, C., Makar, P., and Tarrasón, L.: Applications of an advanced clustering tool for EU AQ monitoring network data analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15087, https://doi.org/10.5194/egusphere-egu23-15087, 2023.

EGU23-15609 | ECS | Posters on site | GI1.3

A compact and customisable street-level sensor system for real-time weather monitoring and outreach in Freiburg, Germany 

Gregor Feigel, Marvin Plein, Matthias Zeeman, Ferdinand Briegel, and Andreas Christen

Climate adaptation and emergency management are major challenges in cities, that benefit from the incorporation of real-time weather, air quality, differential exposure and vulnerability data. We therefore need systems that allow us to map, for example, localised thermal heat stress, heavy precipitation events or air quality spatially resolved across cities at high temporal resolution. Key to the assessment of average conditions and weather extremes in cities are systems that are capable of resolving intra-urban variabilities and microclimates at the level of people, hence in the urban canopy layer at street-level. Placing sensors at street-level, however, is challenging: Sensors need to be small, rugged, safe, and they must measure a number of quantities within limited space. Such systems may ideally require little or no external power, provide remote accessibility, sensor interoperability and real-time data transfer and must be cost-effective for mass deployment. However, these characteristics as well as a wide spectrum of observed variables are not available in current commercial sensor network solutions, hence we designed and implemented a custom partly in-house developed two-tiered sensor system for mounting and installation at 3 m height on city-owned street lights in Freiburg, Germany.

Our partly in-house developed two-tiered sensor network, consisting of fifteen fully self-developed, cost-effective “Tier-I stations” and 35 commercial “Tier-II stations” (LoRAIN, Pessl Instruments GmbH), aims to fill these gaps and to provide a modular, user-friendly WSN with a high spatial density and temporal resolution for research, practical applications and the general public. The Tier-I stations were designed and optimised from the ground up, including the printed circuit board (PCB), for temporally high-resolution WSNs that support wide ranges of sensors and that is expandable. The core of the system is a low-power embedded computer (Raspberry Pi Zero) running a custom multithreaded generic logging and remote control software that locally stores the data and transmits it to a custom vapor-based TCP server via GSM. The software also features system monitoring and error detection functions, as well as remote logging. The setup can easily be expanded on the fly by adding predefined sensors to a configuration file. For better modularity, each station registers itself on the server and will be automatically integrated in all further processes and vice versa. Custom frontends as well as bidirectional communication and task distribution protocols enable remote access and across node interaction, resulting in a more easy-to-maintain system. 

In addition to air temperature, humidity and precipitation measured by the Tier II stations, the Tier-I station feature a ClimaVUE 50 all-in-one weather sensor and a BlackGlobe (Campbell Scientific, Inc.) that provides data on wind, radiation, pressure, lightning, solar radiation and black globe temperatures. That allows for calculation of thermal comfort indices in real-time. A webpage and the self-developed “uniWeather” (iOS-App, API) offers near-realtime data access and data interpretation for stakeholders and public outreach.

How to cite: Feigel, G., Plein, M., Zeeman, M., Briegel, F., and Christen, A.: A compact and customisable street-level sensor system for real-time weather monitoring and outreach in Freiburg, Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15609, https://doi.org/10.5194/egusphere-egu23-15609, 2023.

EGU23-16779 | Orals | GI1.3 | Highlight

An integrated meteorological forecasting system for emergency response 

Alexander Haefele, Maxime Hervo, Philipp Bättig, Daniel Leuenberger, Claire Merker, Daniel Regenass, Pirmin Kaufmann, and Marco Arpagaus

EMER-Met is the new meteorological forecasting system for the protection of the population in Switzerland. It provides the meteorological basis for coping with all types of emergencies, especially in case of nuclear and chemical accidents. EMER-Met consists of a dedicated upper air measurement network and a high-resolution numerical weather prediction model. The measurement network is composed of state-of-the-art remote sensing instruments to measure accurate wind and temperature profiles in the boundary layer. At three sites, a radar wind profiler PCL1300, a Doppler lidar Windcube-200s and a microwave radiometer Hatpro-G5 are installed. The data from the measurement network are assimilated into the operational 1-km ensemble numerical weather prediction (NWP) system. In the case of the microwave radiometers, we assimilate the brightness temperatures using an adapted version of the RTTOV observation operator. To ensure best impact on the NWP results, the data quality of the measurements is of high importance and is monitored closely on a daily and monthly basis against radiosondes and the NWP model itself. EMER-Met is operational since 2022 and to our best knowledge, it is the first time that the brightness temperatures measured by surface-based microwave radiometers are assimilated operationally. This presentation will focus on the upper air network performance and its impact on NWP. 

How to cite: Haefele, A., Hervo, M., Bättig, P., Leuenberger, D., Merker, C., Regenass, D., Kaufmann, P., and Arpagaus, M.: An integrated meteorological forecasting system for emergency response, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16779, https://doi.org/10.5194/egusphere-egu23-16779, 2023.

EGU23-17535 | ECS | Orals | GI1.3

ACTRIS - CiGas side-by-side interlaboratory comparison of new and classical techniques for formaldehyde measurement in the nmol/mol range 

Therese Salameh, Emmanuel Tison, Evdokia Stratigou, Sébastien Dusanter, Vincent Gaudion, Marina Jamar, Ralf Tillmann, Franz Rohrer, Benjamin Winter, Teresa Verea, Amalia Muñoz, Fanny Bachelier, Véronique Daele, and Audrey Grandjean

Formaldehyde is an important hazardous air pollutant, classified as carcinogenic to humans by the International Agency for Research on Cancer (IARC). It is emitted directly by many anthropogenic and natural sources, and formed as a secondary product from volatile organic compounds (VOCs) photo-oxidation. Formaldehyde is, as well, a significant source of radicals in the atmosphere resulting in ozone and secondary organic aerosols formation. Routine measurements of formaldehyde in regulatory networks within Europe (EMEP) and USA (EPA Compendium Method TO 11A) rely on sampling with DNPH (2,4-Dinitrophenylhydrazine)- impregnated silica cartridges, followed by analysis with HPLC (High-performance liquid chromatography).

In the framework of the EURAMET-EMPIR project « MetClimVOC » (Metrology for climate relevant volatile organic compounds: http://www.metclimvoc.eu/), the European ACTRIS (Aerosol, Cloud and Trace Gases Research InfraStructure: https://www.actris.eu/) Topical Centre for Reactive Trace Gases in-situ Measurements (CiGas), IMT Nord Europe unit – France, organized a side-by-side intercomparison campaign in Douai-France, dedicated to formaldehyde measurement in a low amount fraction range of 2 - 20 nmol/mol, from 30 May to 8 June 2022. The objectives of the intercomparison are to evaluate the instruments metrological performance under the same challenging conditions, and to build best practices and instrumental knowledge.

Here, we present the results from the intercomparison, where ten instruments belonging to seven different techniques were challenged with the same formaldehyde gas mixture generated either from a cylinder or from a permeation system, in different conditions (amount fractions, relative humidity, interference, blanks, etc.), flowing through a high-flow (up to 50 L/min) Silcosteel-coated manifold. The advantages/drawbacks of the techniques will be discussed.

How to cite: Salameh, T., Tison, E., Stratigou, E., Dusanter, S., Gaudion, V., Jamar, M., Tillmann, R., Rohrer, F., Winter, B., Verea, T., Muñoz, A., Bachelier, F., Daele, V., and Grandjean, A.: ACTRIS - CiGas side-by-side interlaboratory comparison of new and classical techniques for formaldehyde measurement in the nmol/mol range, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17535, https://doi.org/10.5194/egusphere-egu23-17535, 2023.

EGU23-229 | ECS | Posters virtual | ESSI3.5

A web-based strategy to reuse grids in geographic modeling 

Yuanqing He, Min Chen, Yongning Wen, and Songshan Yue

Integrated application of geo-analysis models is critical for geo-process research. Due to the continuity of the real world, the geo-analysis model cannot be applied immediately over the entire space. To date, the method of regrading space as a sequence of computing units (i.e. grid) has been widely used in geographic study. However, the model's variances in division algorithms result in distinct grid data structures. At first, researchers must install and setup the various software to generate the structure-specific grid data required by the models. This method of localized processing is inconvenient and inefficient. Second, in order to integrate the models that use different structural grid data, researchers need to design a specific conversion method based on the integration scenario. Due to difference of researcher’s development habits, it is difficult to reuse the conversion method in another runtime environment. The open and cross-platform character of web services enables users to generate data without the assistance of software programs. It has the potential to revolutionize the present time-consuming process of grid generation and conversion, hence increasing efficiency.

Based on the standardized model encapsulation technology proposed by OpenGMS group, this paper presents a grid-service method tailored to the specific requirements of open geographic model integration applications, and the research work is carried out in the following three areas:

  • The basic strategy of grid servitization. The heterogeneity of the grid generation method is a major factor that prevents it from being invoked via a unified way by web services. To reduce the heterogeneous of the grid generation method, this study proposes a standardized description method based on the Model Description Language (MDL).
  • Method for constructing a grid data generating service. A unified representation approach for grid data is proposed in order to standardize the description of heterogeneous grid data; an encapsulation method for grid generating algorithms is proposed; and grid-service is realized by merging the main idea of grid servitization.
  • Method for constructing a grid data conversion service . A box-type grid indexing approach is provided to facilitate the retrieval of grid cells with a large data volume; two conversion types, topologically similar and topologically inaccessible grid data conversion, are summarized, along with the related conversion procedures. On this foundation, a grid conversion engine is built using the grid service-based strategy as a theoretical guide and integrated with the grid conversion strategy.

Based on the grid service approach proposed in this paper, researchers can generate and converse grid data without tedious steps for downloading and installing programs. Thus, there are more time spend on geography problem solving, hence increasing efficiency.

How to cite: He, Y., Chen, M., Wen, Y., and Yue, S.: A web-based strategy to reuse grids in geographic modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-229, https://doi.org/10.5194/egusphere-egu23-229, 2023.

EGU23-2744 | Orals | ESSI3.5

Provenance powered microservices: a flexible and generic approach fostering reproducible research in Earth Science 

Alessandro Spinuso, Ian van der Neut, Mats Veldhuizen, Christian Pagé, and Daniele Bailo

Scientific progress requires research outputs to be reproducible, or at least persistently traceable and analysable for defects through time. This can be facilitated by coupling analysis tools that are already familiar to scientists, with reproducibility controls designed around common containerisation technologies and formats to represent metadata and provenance. Moreover, modern interactive tools for data analysis and visualisation, such as computational notebooks and visual analytics systems, are built to expose their functionalities through the Web. This facilitates the development of integrated solutions that are designed to support computational research with reproducibility in mind, and that, once deployed onto a Cloud infrastructure, benefit from operations that are securely managed and perform reliably. Such systems should be able to easily accommodate specific requirements concerning, for instance, the deployment of particular scientific software and the collection of tailored, yet comprehensive, provenance recordings about data and processes. By decoupling and generalising the description of the environment where a particular research took place from the underlying implementation, which may become obsolete through time, we obtain better chances to recollect relevant information for the retrospective analysis of a scientific product in the long term, enhancing preservation and reproducibility of results.

In this contribution we illustrate how this is achievable via the adoption of microservice architectures combined with a provenance model that supports metadata standards and templating. We aim at empowering scientific data portals with Virtual Research Environments (VREs) and provenance services, that are programmatically controlled via high-level functions over the internet. Our system SWIRRL deals, on behalf of the clients, with the complexity of allocating the interactive services for the VREs on a Cloud platform. It runs staging and preprocessing workflows to gather and organise remote datasets, making them accessible collaboratively. We show how Provenance Services manage provenance records about the underlying environment, datasets and analysis workflows, and how these are exploited by researchers to control different reproducibility use cases. Our solutions are currently being implemented in more contexts in Earth Science. We will provide an overview on the progress of these efforts for the EPOS and IS-ENES research infrastructures, addressing solid earth and climate studies, respectively.

Finally, although the reproducibility challenges can be tackled to a large extent by modern technology, this will be further consolidated and made interoperable via the implementation and uptake of the FDOs. To achieve this goal, it is fundamental to establish the conversation between engineers, data-stewards and researchers early in the process of delivering a scientific product. This fosters the definition and implementation of suitable best practices to be adopted by a particular research group. Scientific tools and repositories built around modern FAIR enabling resources can be incrementally refined thanks to this mediated exchange. We will briefly introduce success stories towards this goal in the context of the IPCC Assessment Reports.

How to cite: Spinuso, A., van der Neut, I., Veldhuizen, M., Pagé, C., and Bailo, D.: Provenance powered microservices: a flexible and generic approach fostering reproducible research in Earth Science, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2744, https://doi.org/10.5194/egusphere-egu23-2744, 2023.

The AuScope 3D Geomodels Portal is a website designed to display a variety of geological models and associated datasets and information from all over the Australian continent. The models are imported from publicly available sources, namely Australian government geological surveys and research organisations. Often the models come in the form of downloadable file packages designed to be viewed in specialised geological software applications. They usually contain enough information to view the model’s structural geometry, datasets and a minimal amount of geological textual information. Seldom do they contain substantial metadata, often they were created before the term ‘FAIR’ was coined or the importance of metadata had dawned upon many of us. This creates challenges for data providers and aggregators trying to maintain a certain standard of FAIR compliance across all their offerings. How to improve the standard of FAIR compliance of metadata extracted from these models? How to integrate these models into existing metadata infrastructure? For the Geomodels portal, these concerns are alleviated within the automated model transformation software. This software transforms the source file packages into a format suitable for display in a modern WebGL compliant browser. Owing to the nature of the model source files only a very modest amount of metadata can be extracted. Hence other sources of metadata must be introduced. For example, often the dataset provider will publish a downloadable PDF report file or a description on a web page associated with the model. Automated textual analysis is used to extract more information from these sources. At the end of the transformation process, an ISO-compliant metadata record is created for importing into a geonetwork catalogue. The geonetwork catalogue record can be used for integration with other applications. For example, AuScope’s flagship portal, the AuScope Portal displays information, download links and a geospatial footprint of models on a map. The metadata can also be displayed in the Geomodels Portal.

How to cite: Fazio, V.: How AuScope 3D Geomodels Portal integrates relatively metadata poor geological models into its metadata infrastructure, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3006, https://doi.org/10.5194/egusphere-egu23-3006, 2023.

EGU23-3711 | Orals | ESSI3.5

Lessons in FAIR software from the Community Surface Dynamics Modeling System 

Gregory Tucker, Albert Kettner, Eric Hutton, Mark Piper, Tian Gan, Benjamin Campforts, Irina Overeem, and Matthew Rossi

The Community Surface Dynamics Modeling System (CSDMS) is a US-based science facility that supports computational modeling of diverse Earth and planetary surface processes, ranging from natural hazards and contemporary environmental change to geologic applications. The facility promotes open, interoperable, and shared software. Here we review approaches and lessons learned in advancing FAIR principles for geoscience modeling. To promote sharing and accessibility, CSDMS maintains an online Model Repository that catalogs over 400 shared codes, ranging from individual subroutines to large and sophisticated integrated models. Thanks to semi-automated search tools, the Repository now includes ~20,000 references to literature describing these models and their applications, giving prospective model users efficient access to information about how various codes have been developed and used. To promote interoperability, CSDMS develops and promotes the Basic Model Interface (BMI): a lightweight, language-agnostic API standard that provides control, query, and data-modification functions. BMI has been adopted by a number of academic, government, and quasi-private institutions for coupled-modeling applications. BMI specifications are provided for common scientific languages, including as Python, C, C++, Fortran, and Java. One challenge lies in broader awareness and adoption; for example, self-taught code developers may be unaware of the concept of an API standard, or may not perceive value in designing around such a standard. One way to address this challenge is to provide open-source programming libraries. One such library that CSDMS curates is Landlab Toolkit: a Python package that includes building blocks for model development (such as grid data structures and I/O functions) while also providing a framework for assembling integrated models from component parts. We find that Landlab can greatly speed model development, while giving user-developers an incentive to follow common patters and contribute new components to the library. However, libraries by themselves do not solve the reproducibility challenge. Rather than reinventing the wheel, the CSDMS facility has approached reproducibility by partnering with the Whole Tale initiative, which provides tools and protocols to create reproducible archives of computational research. Finally, we have found that a central challenge to FAIR modeling lies in the level of community knowledge. FAIR is a two-way street that depends in part on the technical skills of the user. Are they fluent in a particular programming language? How familiar are they with the numerical methods used by a given model? How familiar are they with underlying scientific concepts and simplifying assumptions? Are they conversant with modern version control and collaborative-development technology and practices? Although scientists should not need to become software engineers, in our experience there is a basic level of knowledge that can substantially raise the quality and sustainability of research software. To address this, CSDMS offers training programs, self-paced learning materials, and online help resources for community members. The vision is to foster a thriving community of practice in computational geoscience research, equipped with ever-improving modeling tools written by and for the community as a whole.

How to cite: Tucker, G., Kettner, A., Hutton, E., Piper, M., Gan, T., Campforts, B., Overeem, I., and Rossi, M.: Lessons in FAIR software from the Community Surface Dynamics Modeling System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3711, https://doi.org/10.5194/egusphere-egu23-3711, 2023.

This is a report from the chapter editor's perspective of a high visibility publication effort to foster the adoption of the FAIR principles (Findable, Accessible, Interoperable, Reusable) by encouraging the adoption of Persistent Identifiers (PID) and repository-based workflows in geospatial open source software communities as good practices. Lessons learned are detailed about how to communicate the benefits of PID adoption to software project communities focussing on professional software-development and meritocracy. Also encountered communication bottleneck patterns, the significance of cross-project  multiplicators, remaining challenges and emerging opportunities for publishers and repository infrastructures are reported. For the second Edition of the Springer Handbook of Geographic Information, a team of scientific domain experts from several software communities was tasked to rewrite a chapter about Open Source Geographic Information Systems (DOI: 10.1007/978-3-030-53125-6_30). For this, a sample of representative geospatial open source projects was selected, based on the range of projects integrated in the OSGeo live umbrella project (DOI: 10.5281/zenodo.5884859). The chapters authors worked in close contact with the respective Open Source software project communities. Since the editing and production process for the Handbook of Geographic Information was delayed due to the pandemic, this provided the opportunity to explore, improve and implement good practices for state of the art PID-based citation of software projects and versions, but also project communities, data and related scientific video ressources. This was a learning process for all stakeholders involved in the publication project. At the completion of the project, the majority of the involved software projects had minted Digital Object Identifiers (DOI) for their codebases. While the adoption level of software versioning with automated PID-generation and metadata quality remains heterogeneous, the insights gained from this process can simplify and accelerate the adoption of PID-based best software community practices for other open geospatial projects according to the FAIR principles.

How to cite: Löwe, P.: Going FAIR by the book: Accelerating the adoption of PID-enabled good practices in software communities through reference publication., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4354, https://doi.org/10.5194/egusphere-egu23-4354, 2023.

EGU23-4525 | ECS | Posters on site | ESSI3.5

GCIMS – Integration: Reproducible, robust, and scalable workflows for interoperable human-Earth system modeling 

Zarrar Khan, Chris Vernon, Isaac Thompson, and Pralit Patel

The number of models, as well as data inputs and outputs, are continuously growing as scientists continue to push the boundaries of spatial, temporal, and sectoral details being captured. This study presents the framework being developed to manage the Global Change Intersectoral Modeling System (GCIMS) eco-system of human-Earth system models. We discuss the challenges of ensuring continuous deployment and integration, reproducibility, interoperability, containerization, and data management for the growing suite of GCIMS models. We investigate the challenges of model version control and interoperability between models using different software, operating on different temporal and spatial scales, and focusing on different sectors. We also discuss managing transparency and accessibility to models and their corresponding data products throughout our integrated modeling lifecycle.

How to cite: Khan, Z., Vernon, C., Thompson, I., and Patel, P.: GCIMS – Integration: Reproducible, robust, and scalable workflows for interoperable human-Earth system modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4525, https://doi.org/10.5194/egusphere-egu23-4525, 2023.

EGU23-4939 * | Orals | ESSI3.5 | Highlight

Open Science: How Open is Open? 

Shelley Stall and Kristina Vrouwenvelder

Open science is transformative, removing barriers to sharing science and increasing reproducibility and transparency. The benefits of open science are maximized when its principles are incorporated throughout the research process, through working collaboratively with community members and sharing data, software, workflows, samples, and other aspects of scientific research openly where it can be reused, distributed, and reproduced. However, the paths toward Open Science are not always apparent, and there are many concepts, approaches, tools to learn along the way.  

Open Science practices are along a continuum where researchers can make incremental adjustments to their research practices that may seem small but can have valuable benefits. Here we will share the first steps in a researcher’s open science journey and how to lead your own research team in adopting Open Science practices.

How to cite: Stall, S. and Vrouwenvelder, K.: Open Science: How Open is Open?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4939, https://doi.org/10.5194/egusphere-egu23-4939, 2023.

EGU23-6375 | Posters on site | ESSI3.5

A machine-actionable workflow for the publication of climate impact data of the ISIMIP project 

Jochen Klar and Matthias Mengel

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) is a community-driven climate impact modeling initiative that aims to contribute to a quantitative and cross-sectoral synthesis of the various impacts of climate change, including associated uncertainties. ISIMIP is organized into simulation rounds for which a simulation protocol defines a set of common scenarios. Participating modeling groups run their simulations according to these scenarios and with a common set of climatic and socioeconomic input data. The model output data are collected by the ISIMIP team at the Potsdam Institute for Climate Impact Research (PIK) and made publicly available in the ISIMIP repository. Currently the ISIMIP Repository at data.isimip.org includes data from over 150 impact models spanning across 13 different sectors. It comprises of over 100 Tb of data.

As the world's largest data archive of model-based climate impact data, ISIMIP output data is used by a very diverse audience inside and outside of academia, for all kind of research and analyses. Special care is taken to enable persistent identification, provenience, and citablity. A set of workflows and tools ensure the conformity of the model output data with the protocol and the transparent management of caveats and updates to already published data. Datasets are referenced using unique internal IDs and hash values are stored for each file in the database.

In recent years, this process has been significantly improved by introducing a machine-readable protocol, which is version controlled on GitHub and can be accessed over the internet. A set of software tools for quality control and data publication accesses this protocol to enforce a consistent data quality and to extract metadata. Some of the tools can be used independently by the modelling groups even before submitting the data. After the data is published on the ISIMIP Repository, it can be accessed via web or using an API (e.g. for access from Jupyter notebooks) using the same controlled vocabularies from the protocol. In order to make the data citable, DOI for each output sector are registered with DataCite. For each DOI, a precise list of each contained dataset is maintained. If data for a sector is added or replaced, a new, updated DOI is created.

While the specific implementation is highly optimized to the peculiarities of ISIMIP, the general ideas should be transferable to other projects. In our presentation, we will discuss the various tools and how they interact to create an integrated curation and publishing workflow.

How to cite: Klar, J. and Mengel, M.: A machine-actionable workflow for the publication of climate impact data of the ISIMIP project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6375, https://doi.org/10.5194/egusphere-egu23-6375, 2023.

EGU23-6726 | ECS | Posters on site | ESSI3.5

Data compilations for enriched reuse of sea ice data sets 

Anna Simson, Anil Yildiz, and Julia Kowalski

A vast amount of in situ cryospheric data has been collected during publicly funded field campaigns to the polar regions over the past decades. Each individual data set yields important insights into local thermo-physical processes, but they need to be assembled into informative data compilations to unlock their full potential to produce regional or global outcomes for climate change related research. The efficient and sustainable interdisciplinary reuse of such data compilations is of large interest to the scientific community. Yet, the creation of such compilations is often challenging as they have to be composed of often heterogeneous data sets from various data repositories. We will focus on the reuse of data sets in this contribution, while generating extendible data compilations with enhanced reusability.

Data reuse is typically conducted by researchers other than the original data producers, and it is therefore often limited by the metadata and provenance information available. Reuse scenarios include the validation of physics-based process models, the training of data-driven models, or data-integrated predictive simulations. All these use cases heavily rely on a diverse data foundation in form of a data compilation, which depends on high quality information. In addition to metadata, provenance, and licensing conditions, the data set itself must be checked for reusability. Individual data sets containing the same metrics often differ in structure, content, and metadata, which challenges data compilation.

In order to generate data compilations for a specific reuse scenario, we propose to break down the workflow into four steps:
1) Search and selection: Searching, assessing, optimizing search, and selecting data sets.
2) Validation: Understanding and representing data sets in terms of the data collectors including structure, terms used, metadata, and relations between different metrics or data sets.
3) Specification: Defining the format, structure, and content of the data compilation based on the scope of the data sets.
4) Implementation: Integrating the selected data sets into the compilation.

We present a workflow herein to create a data compilation from heterogeneous sea ice core data sets following the previously introduced structure. We report on obstacles encountered in the validation of data sets mainly due to missing or ambiguous metadata. This leaves the (re)user space for subjective interpretation and thus increases uncertainty of the compilation. Examples are challenges in relating different data repositories associated with the same location or the same campaign, the accuracy of measurement methods, and the processing stage of the data. All of which often require a bilateral iteration with the data acquisition team. Our study shows that enriching data reusability with data compilations requires quality-ensured metadata on the individual data set level.

How to cite: Simson, A., Yildiz, A., and Kowalski, J.: Data compilations for enriched reuse of sea ice data sets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6726, https://doi.org/10.5194/egusphere-egu23-6726, 2023.

EGU23-7417 | ECS | Posters on site | ESSI3.5 | Highlight

Data-integrated executable publications for reproducible geohazards research 

Anil Yildiz and Julia Kowalski

Investigating the mechanics of physical processes involved in various geohazards, e.g. gravitational, flow-like mass movements, shallow landslides or flash floods, predicting their temporal or spatial occurrence, and analysing the associated risks clearly benefit from advanced computational process-based or data-driven models. Reproducibility is needed not only for the integrity of the scientific results, but also as a trustbuilding element in practical geohazards engineering. Various complex numerical models or pre-trained machine learning algorithms exist in the literature, for example, to determine landslide susceptibility in a region or to predict the run-out of torrential flows in a catchment. These use FAIR datasets with increasing frequency, for example DEM data to set up the simulation, or open access landslide databases for training and validation purposes. However, we maintain that workflow reproducibility is not ensured simply due to the FAIRness of input or output datasets. Underlying computational or machine learning model needs to be (re)structured to enable the reproducibility and replicability of every step in the workflow so that a model can be (re)built to either reproduce the same results, or can be (re)used to elaborate on new cases or new applications. We propose a data-integrated, platform-independent scientific model publication approach combining self-developed Python packages, Jupyter notebooks, version controlling, FAIR data repositories and high-quality metadata. Model development in the form of a Python package guarantees that model can be run by any end-user, and defining submodules of analysis or visualisation within the package helps the users to build their own models upon the model presented. Publishing the manuscript as a data- and model-integrated Jupyter notebook creates a transparent application of the model, and the user can reproduce any result either presented in the manuscript or in the datasets. We demonstrate our workflow with two applications from geohazards research herein while highlighting the shortcomings of the existing frameworks and suggesting improvements for future applications.

How to cite: Yildiz, A. and Kowalski, J.: Data-integrated executable publications for reproducible geohazards research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7417, https://doi.org/10.5194/egusphere-egu23-7417, 2023.

EGU23-7427 | Posters on site | ESSI3.5

Integrating sample management and semantic research-data management in glaciology 

Florian Spreckelsen, Henrik tom Wörden, Daniel Hornung, Timm Fitschen, Alexander Schlemmer, and Johannes Freitag

The flexible open-source research data management toolkit CaosDB is used in a diversity of fields such as turbulence physics, legal research, maritime research and glaciology. It is used to link research data and make it findable and retrievable and to keep it consistent, even if the data model changes.

CaosDB is used in the glaciology department at the Alfred Wegener Institute in Bremerhaven for the management of ice core samples and related measurements and analyses. Researchers can use the system to query for ice samples linked to, e.g., specific measurements for which they then can request to borrow for further analyses. This facilitates inter-laboratory collaborative research on the same samples. The system helped to solve a number of needs for the researchers, such as: A revision system which intrinsically keeps track of changes to the data and in which state samples were, when certain analyses were performed. Automated gathering of information for the publication in a meta-data repository (Pangaea). Tools for storing, displaying and  querying geospatial information and graphical summaries of all the measurements and analyses performed on an ice core. Automatic data extraction and refinement into data records in CaosDB so that users do not need to enter the data manually. A state machine which guarantees certain workflows, simplifies development and can be extended to trigger additional actions upon transitions.

We demonstrate how CaosDB enables researchers to create and work with semantic data objects. We further show how CaosDB's semantic data structure enables researchers to publish their data as FAIR Digital Objects.

How to cite: Spreckelsen, F., tom Wörden, H., Hornung, D., Fitschen, T., Schlemmer, A., and Freitag, J.: Integrating sample management and semantic research-data management in glaciology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7427, https://doi.org/10.5194/egusphere-egu23-7427, 2023.

EGU23-7532 | Posters on site | ESSI3.5

Virtual Earth Cloud: a multi-cloud framework for improving replicability of scientific models 

Mattia Santoro, Paolo Mazzetti, and Stefano Nativi

Humankind is facing unprecedented global environmental and social challenges in terms of food, water and energy security, resilience to natural hazards, etc. To address these challenges, international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan (e.g., the UN SDGs). The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions and avoid potentially negative impacts on society and the environment.

Scientific models are key tools to transform into information and knowledge the huge amount of data currently available online. Executing a scientific model (implemented as an analytical software) commonly requires the discovery and use of different types of digital resources (i.e. data, services, and infrastructural resources). In the present geoscience technological landscape, these resources are generally provided by different systems (working independently from one another) by utilizing Web technologies (e.g. Internet APIs, Web Services, etc.). In addition, a given scientific model is often designed and developed for execution in a specific computing environment. These are important barriers to enable reproducibility, replicability, and reusability of scientific models –becoming key interoperability requirements for a transparent decision-making process.

This presentation introduces the Virtual Earth Cloud concept, a multi-cloud framework for the generation of information/knowledge from Big Earth Data analytics. The Virtual Earth Cloud allows the execution of computational models to process and extract knowledge from Big Earth Data, in a multi-cloud environment, and thus improving their reproducibility, replicability and reusability.

The development and prototyping of the Virtual Earth Cloud is carried out in the context of the GEOSS Platform Plus (GPP) project, funded by the European Union’s Horizon 2020 Framework Programme, aims to contribute to the implementation of the Global Earth Observation System of Systems (GEOSS) by evolving the European GEOSS Platform components to allow access to tailor-made information and actionable knowledge.

How to cite: Santoro, M., Mazzetti, P., and Nativi, S.: Virtual Earth Cloud: a multi-cloud framework for improving replicability of scientific models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7532, https://doi.org/10.5194/egusphere-egu23-7532, 2023.

EGU23-8321 | Orals | ESSI3.5

Facilitating provenance documentation with a model-driven-engineering approach. 

Lucy Bastin, Owen Reynolds, Antonio Garcia-Dominguez, and James Sprinks

Evaluating the quality of data is a major concern within the scientific community: before using any dataset for study, a careful judgement of its suitability must be conducted. This requires that the steps followed to acquire, select, and process the data have been thoroughly documented in a methodical manner, in a way that can be clearly communicated to the rest of the community. This is particularly important in the field of citizen science, where a project that can clearly demonstrate its protocols, transformation steps, and quality assurance procedures have much more chance of achieving social and scientific impact through the use and re-use of its data.

A number of specifications have been created to provide a common set of concepts and terminology, such as ISO 19115-3 or W3C PROV. These define a set of interchange formats, but in themselves, they do not provide tooling to create high-quality dataset descriptions. The existing tools built on these standards (e.g. GeoNetwork, USGS metadata wizard, CKAN) are overly complex for some users (for example, many citizen science project managers) who, despite being experts in their own fields, may be unfamiliar with the structure and context of metadata standards or with semantic modelling. 

In this presentation, we will describe a prototype authoring tool that was created using a Model-driven engineering (MDE) software development methodology. The tool was authored using JetBrains Meta Programming System (MPS) to implement a modelling language based on the ISO19115-3 model. A user is provided with a “text-like” editing environment, which assists with the formal structures needed to produce a machine-parable document.

This allows a user to easily describe data lineage and generic processing steps while reusing recognised external vocabularies with automated validation, autocompletion, and transformation to external formats (e.g. the XML format 19115-3 or JSON-LD). We will report on the results of user testing aimed at making the tool accessible to citizen scientists (through dedicated projections with simplified structures and dialogue-driven model creation) and evaluating with those users any new possibilities that comprehensive and machine-parsable provenance information may create for data integration and sharing. The prototype will also serve as a test pilot of the integration between ISO 19115-3 and existing/upcoming third-party vocabularies (such as the upcoming ISO data quality measures registry).

How to cite: Bastin, L., Reynolds, O., Garcia-Dominguez, A., and Sprinks, J.: Facilitating provenance documentation with a model-driven-engineering approach., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8321, https://doi.org/10.5194/egusphere-egu23-8321, 2023.

EGU23-8526 | ECS | Orals | ESSI3.5

openEO Platform – showcasing a federated, accessible platform for reproducible large-scale Earth Observation analysis 

Benjamin Schumacher, Patrick Griffiths, Edzer Pebesma, Jeroen Dries, Alexander Jacob, Daniel Thiex, Matthias Mohr, and Christian Briese

openEO Platform holds a large amount of free and open as well as commercial Earth Observation (EO) data which can be accessed and analysed with openEO, an open API that enables cloud computing and EO data access in a unified and reproducible way. Additionally, client libraries are available in R, Python and Javascript. A JupterLab environment and the Web Editor, a graphical interface, allow a direct and interactive development of processing workflows. The platform is developed with a strong user focus and various use cases have been implemented to illustrate the platform capabilities. Currently, three federated backends support the analysis of EO data from pixel to continental scale.  

The use cases implemented during the platform’s main development phase include a dynamic landcover mapping, an on-demand analysis-ready-data creation for Sentinel-1 GRD, Sentinel-2 MSI and Landsat data, time series-based forest dynamics analysis with prediction functionalities, feature engineering for crop type mapping and large-scale fractional canopy mapping. Additionally, three new use cases are being developed by platform users. These include large scale vessel detection based on Sentinel-1 and Sentinel-2 data, surface water indicators using the ESA World Water toolbox for a user-defined area of interest and monitoring of air quality parameters using Sentinel-5P data. 

The future evolution of openEO Platform in terms of data availability and processing capabilities closely linked to community requirements, facilitated by feature requests from users who design their workflows for environmental monitoring and reproducible research purposes. This presentation provides an overview of the completed use cases, the newly added functionalities such as user code sharing, and user interface updates based on the new use cases and user requests. openEO Platform exemplifies how the processing and analysing large amounts of EO data to meaningful information products is becoming easier and largely compliant with FAIR data principles supporting the EO community at large. 

How to cite: Schumacher, B., Griffiths, P., Pebesma, E., Dries, J., Jacob, A., Thiex, D., Mohr, M., and Briese, C.: openEO Platform – showcasing a federated, accessible platform for reproducible large-scale Earth Observation analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8526, https://doi.org/10.5194/egusphere-egu23-8526, 2023.

EGU23-9852 | Posters on site | ESSI3.5

Proposal of a simple procedure to derive a more FAIR open data archive than a spreadsheet or a set of CSV files 

Filippo Giadrossich, Ilenia Murgia, and Roberto Scotti

NuoroForestrySchool (a study center of the Department of Agriculture, University of Sassari, Italy) has developed and published a ‘data documentation procedure’ (link to NFS-DDP) enabling the improvement of the dataset FAIRness that any data collector wishes to share as open data. Datasets are frequently shared as spreadsheet files. While this tool is very handy in data preparation and preliminary analysis, its structure and composition are not very effective for storing and sharing consolidated data, unless data structures are extremely simple. NFS-DDP takes in input a spreadsheet in which data are organized as relational tables, one per sheet, while four additional sheets contain metadata standardized according to the Dublin Core specifications. The procedure outputs an SQLite relational database (including data and metadata) and a pdf-file documenting the database structure and contents. A first example application of the proposed procedure was shared by Giadrossich et al. (2022) on the PANGEA repository, concerning experimental data of erosion in forest soil measured during artificial rainfall. The zip-archive that can be downloaded contains the experiment data and metadata processed by NFS-DDP. At the following link is available a test document where basic statistics are computed to show how NFS-DDProcedure facilitates the understanding and correct processing of the shared dataset. 

The NFS-DataDocumentationProcedure provides a simple solution for organizing and archiving data aiming to i) achieve a more FAIR archive, ii) exploit data consistency and comprehensibility of semantic connections in the relational database, ii) produce a report documenting the collection and organization of data, providing an effective and concise overview of the whole with all details at hand.

Giadrossich, F., Murgia, I., Scotti, R. (2022). Experiment of water runoff and soil erosion with and without forest canopy coverage under intense artificial rainfall. PANGAEA. DOI:10.1594/PANGAEA.943451



How to cite: Giadrossich, F., Murgia, I., and Scotti, R.: Proposal of a simple procedure to derive a more FAIR open data archive than a spreadsheet or a set of CSV files, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9852, https://doi.org/10.5194/egusphere-egu23-9852, 2023.

EGU23-12443 | Posters on site | ESSI3.5 | Highlight

Landlab: a modeling platform that promotes the building of FAIR research software 

Eric Hutton and Gregory Tucker

Landlab is an open-source Python package designed to facilitate creating, combining, and reusing 2D numerical models. As a core component of the Community Surface Dynamics Modeling System (CSDMS) Workbench, Landlab can be used to build and couple models from a wide range of domains. We present how Landlab provides a platform that fosters a community of model developers and aids them in creating sustainable and FAIR (Findable, Accessible, Interoperable, Reusable) research software.

Landlab’s core functionality can be split into two main categories: infrastructural tools and community-contributed components. Infrastructural tools address the common needs of building new models (e.g. a gridding engine, and numerical utilities for common tasks). Landlab’s library of community-contributed components consists of several dozen components that each model a separate physical process (e.g. routing of shallow water flow across a landscape, calculating groundwater flow, or biologic evolution over a landscape). As these user-contributed components are incorporated into Landlab, they are able to attach to the Landlab infrastructure so that they also become both findable and accessible (through, for example, standardized metadata and versioning) and are maintained by the core Landlab developers.

One key aspect of Landlab’s design is its use of a standard programming interface for all components. This ensures that all Landlab components are interoperable with one another and with other software tools, allowing researchers to incorporate Landlab's components into their own workflows and analyses. By separating processes into individual components, they become reusable and allow researchers to combine components in new ways without having to write new components from scratch.

Overall, Landlab's design and development practices support the principles of FAIR research software, promoting the ability for scientific research to be easily shared and built upon. This design also provides a platform onto which model developers are able to attach their model components and take advantage of Landlab’s development practices and infrastructure and ensure their components also follow FAIR principles.

How to cite: Hutton, E. and Tucker, G.: Landlab: a modeling platform that promotes the building of FAIR research software, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12443, https://doi.org/10.5194/egusphere-egu23-12443, 2023.

EGU23-12864 | Orals | ESSI3.5 | Highlight

Who Done It? Reproducibility of Data Products Also Requires Lineage to Determine Impact and Give Credit Where Credit is Due. 

Lesley Wyborn, Nigel Rees, Jens Klump, Ben Evans, Rebecca Farrington, and Tim Rawling

Reproducible research necessitates full transparency and integrity in data collection (e.g. from observations) or generation of data, and further data processing and analysis to generate research products. However, Earth and environmental science data are growing in complexity, volume and variety and today, particularly for large-volume Earth observation and geophysics datasets, achieving this transparency is not easy. It is rare for a published data product to be created in a single processing event by a single author or individual research group. Modern research data processing pipelines/workflows can have quite complex lineages, and it is more likely that an individual research product is generated through multiple levels of processing, starting from raw instrument data at full resolution (L0) followed by successive levels of processing (L1-L4), which progressively convert raw instrument data into more useful parameters and formats. Each individual level of processing can be undertaken by different research groups using a variety of funding sources: rarely are those involved in the early stages of processing/funding properly cited.

The lower levels of processing are where observational data essentially remains at full resolution and is calibrated, georeferenced and processed to sensor units (L1) and then geophysical variables are derived (L2). Historically, particularly where the volumes of the L0-L2 datasets are measured in Terabytes to Petabytes, processing could only be undertaken by a minority of specialised scientific research groups and data providers, as few had the expertise/resources/infrastructures to process them on-premise. Wider availability of colocated data assets and HPC/cloud processing means that the full resolution, less processed forms of observational data can now be processed remotely in realistic timeframes by multiple researchers to their specific processing requirements, and also enables greater exploration of parameter space allowing multiple values for the same inputs to be trialled. The advantage is that better-targeted research products can now be rapidly produced. However, the downside is that far greater care needs to be taken to ensure that there is sufficient machine-readable metadata and provenance information to enable any user to determine what processing steps and input parameters were used in each part of the lineage of any released dataset/data product, as well as be able to reference exactly who undertook any part of the acquisition/processing and identify sources of funding (including instruments/field campaigns that collected the data).

The use of Persistent Identifiers (PIDs) for any component objects (observational data, synthetic data, software, model inputs, people, instruments, grants, organisations, etc.) will be critical. Global and interdisciplinary research teams of the future will be reliant on software engineers to develop community-driven software environments that aid and enhance the transparency and reproducibility of their scientific workflows and ensure recogniton. The advantage of the PID approach is that not only will reproducibility and transparency be enhanced, but through the use of Knowledge Graphs it will also be possible to trace the input of any researcher at any level of processing, whilst funders will be able to determine the impact of each stage from the raw data capture through to any derivative high-level data product. 

 

How to cite: Wyborn, L., Rees, N., Klump, J., Evans, B., Farrington, R., and Rawling, T.: Who Done It? Reproducibility of Data Products Also Requires Lineage to Determine Impact and Give Credit Where Credit is Due., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12864, https://doi.org/10.5194/egusphere-egu23-12864, 2023.

EGU23-12971 | Posters on site | ESSI3.5

Reproducible quality control of time series data with SaQC 

David Schäfer, Bert Palm, Peter Lünenschloß, Lennart Schmidt, and Jan Bumberger

Environmental sensor networks produce ever-growing volumes of time series data with great potential to broaden the understanding of complex spatiotemporal environmental processes. However, this growth also imposes its own set of new challenges. Especially the error-prone nature of sensor data acquisition is likely to introduce disturbances and anomalies into the actual environmental signal. Most applications of such data, whether it is used in data analysis, as input to numerical models or modern data science approaches, usually rely on data that complies with some definition of quality.

To move towards high-standard data products, a thorough assessment of a dataset's quality, i.e., its quality control, is of crucial importance. A common approach when working with time series data is the annotation of single observations with a quality label to transport information like its reliability. Downstream users and applications are hence able to make informed decisions, whether a dataset in its whole or at least parts of it are appropriate
for the intended use.

Unfortunately, quality control of time series data is a non-trivial, time-consuming, scientifically undervalued endeavor and is often neglected or executed with insufficient rigor. The presented software, the System for automated Quality Control (SaQC), provides all basic and many advanced building blocks to bridge the gap between data that is usually faulty but expected to be correct in an accessible, consistent, objective and reproducible way. Its user interfaces address different audiences ranging from the scientific practitioner with little access to the possibilities of modern software development to the trained programmer. SaQC delivers a growing set of generic algorithms to detect a multitude of anomalies and to process data using resampling, aggregation, and data modeling techniques. However, one defining component of SaQC is its innovative approach to storing runtime process information. In combination with a flexible quality annotation mechanism, SaQC allows to extend quality labels with fine-grained provenance information appropriate to fully reproduce the system's output.

SaQC is proving its usefulness on a daily basis in a range of fully automated data flows for large environmental observatories. We highlight use cases from the TERENO Network, showcasing how reproducible automated quality control can be implemented into real-world, large-scale data processing workflows to provide environmental sensor data in near real-time to data users, stakeholders and decision-makers.

 

How to cite: Schäfer, D., Palm, B., Lünenschloß, P., Schmidt, L., and Bumberger, J.: Reproducible quality control of time series data with SaQC, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12971, https://doi.org/10.5194/egusphere-egu23-12971, 2023.

EGU23-13108 | Orals | ESSI3.5 | Highlight

The reality of implementing FAIR principles in the IPCC context to support open science and provide a citable platform to acknowledge the work of authors. 

Charlotte Pascoe, Lina Sitz, Diego Cammarano, Anna Pirani, Martina Stockhause, Molly MacRae, and Emily Anderson

A new paradigm for Intergovernmental Panel on Climate Change (IPCC) Working Group I (WGI) data publication has been implemented.  IPCC Data Distribution Centre (DDC) partners at the Centre for Environmental Data Analysis (CEDA), the German Climate Computing Centre (DKRZ) and the Spanish Research Council (CSIC) have worked with the IPCC Technical Support Unit (TSU) for WGI to publish figure data from the Sixth Assessment Report (AR6). The work was guided by the IPCC Task Group on Data Support for Climate Change Assessments (TG-Data) recommendations for Open Science and FAIR data (making data Findable, Accessible, Interoperable, and Reusable) with a general aim to enhance the transparency and accessibility of AR6 outcomes.  We highlight the achievement of implementing FAIR for AR6 figure data and discuss the lessons learned on the road to FAIRness in the unique context of the IPCC.

  • Findable - The CEDA catalogue record for each figure dataset enhances findability. Keywords can be easily searched. Records are organised into collections for each AR6 chapter. There is a two-way link between the catalogue record and the figure on the AR6 website. CEDA catalogue records are duplicated on the IPCC-DDC. 
  • Accessible - Scientific language is understandable, acronyms and specific terminology are fully explained. CEDA services provide tools to access and download the data. 
  • Interoperable - Where possible data variables follow standard file format conventions such as CF-netCDF and have standard names, where this is not feasible readme files describe the file structure and content. 
  • Reusable - The data can be reused, shared and adapted elsewhere, with credit, under a Creative Commons Attribution 4.0 licence (CC BY 4.0). Catalogue records link to relevant documentation such as the Digital Object Identifier (DOI) for the code and other supplementary information. The code used to create the figures allows users to reproduce the figures from the report independently. 

CEDA catalogue records provide a platform to acknowledge the specific work of IPCC authors and dataset creators whose work supports the scientific basis of AR6. 

Catalogue records for figure datasets were created at CEDA with data archived in the CEDA repository and the corresponding code stored on GitHub and referenced via Zenodo.  For instances where the data and code were blended in a processing chain that could not be easily separated, we developed criteria to categorise the different blends of data and code and created a decision tree to decide how best to archive them. Key intermediate datasets were also archived at CEDA.

Careful definition of metadata requirements at the beginning of the archival process is important for handling the diversity of IPCC figure data which includes data derived from climate model simulations, historical observations and other sources of climate information. The reality of the implementation meant that processes for gathering data and information from authors were specified later in the preparation of AR6. This presented challenges with data management workflows and the separation of figure datasets from the intermediate data and code that generated them. 

We present recommendations for AR7 and scaling up this work in a feasible way.

How to cite: Pascoe, C., Sitz, L., Cammarano, D., Pirani, A., Stockhause, M., MacRae, M., and Anderson, E.: The reality of implementing FAIR principles in the IPCC context to support open science and provide a citable platform to acknowledge the work of authors., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13108, https://doi.org/10.5194/egusphere-egu23-13108, 2023.

In our project we are employing semantic data management with the Open Source research data management system (RDMS) CaosDB [1] to link empirical data and simulation output from Earth System Models [2]. The combined management of these data structures allows us to perform complex queries and facilitates the integration of data and meta data into data analysis workflows.

One particular challenge for analyses of model output is to keep track of all necessary meta data of each simulation during the whole digital workflow. Especially for open science approaches it is of great importance to properly document - in human- and computer-readable form - all the information necessary to completely reproduce obtained results. Furthermore, we want to be able to feed all relevant data from data analysis back into our data management system, so that we are able to perform complex queries also on data sets and parameters stemming from data analysis workflows.

A specific aim of this project is to re-analyse existing sets of simulations under different research questions. This endeavour can become very time consuming without proper documentation in an RDMS.

We implemented a workflow, combining semantic research data management with CaosDB and Jupyter notebooks, that keeps track of data loaded into an analysis workspace. Procedures are provided that create snapshots of specific states of the analysis. These snapshots can automatically be interpreted by the CaosDB crawler that is able to insert and update records in the system accordingly. The snapshots include links to the input data, parameter information, the source code and results and therefore provide a high-level interface to the full chain of data processing, from empirical and simulated raw data to the results. For example, input parameters of complex Earth System Models can be extracted automatically and related to model performance. In our use case, not only automated analyses are feasible, but also interactive approaches are supported.

  • [1] Fitschen, T.; Schlemmer, A.; Hornung, D.; tom Wörden, H.; Parlitz, U.; Luther, S. CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows. Data 2019, 4, 83. https://doi.org/10.3390/data4020083
  • [2] Schlemmer, A., Merder, J., Dittmar, T., Feudel, U., Blasius, B., Luther, S., Parlitz, U., Freund, J., and Lennartz, S. T.: Implementing semantic data management for bridging empirical and simulative approaches in marine biogeochemistry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11766, https://doi.org/10.5194/egusphere-egu22-11766, 2022.

How to cite: Schlemmer, A. and Lennartz, S.: Transparent and reproducible data analysis workflows in Earth System Modelling combining interactive notebooks and semantic data management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13347, https://doi.org/10.5194/egusphere-egu23-13347, 2023.

EGU23-14845 | Orals | ESSI3.5

Open geospatial standards and reproducible research 

Massimiliano Cannata, Gregory Giuliani, Jens Ingensand, Olivier Ertz, and Maxime Collombin

In the era of cloud computing, big data and Internet of things, research is very often data-driven: based on the analysis of data, increasingly available in large quantities and collected by experiments, observations or simulations. These data are very often characterized as being dynamic in space and time and as continuously expanding (monitoring) or change (data quality management or survey). Modern Spatial Data Infrastructures (e.g.  swisstopo or INSPIRE), are based on interoperable Web services which expose and serve large quantities of data on the Internet using widely accepted and used open standards defined by the Open Geospatial Consortium (OGC) and the International Organization for Standardization (ISO). These standards mostly comply with FAIR principles but do not offer any capability to retrieve a dataset how it was in a defined instant, to refer to its status in that specific instant and to guarantee its immutability. These three aspects hinder the replicability of research based on such a kind of services. We discuss the issue here and the state of the art  and propose a possible solution to fill this gap, using or extending when needed the existing standards and or adopting best practices in the fields of sensor data, satellite data and vector data.

How to cite: Cannata, M., Giuliani, G., Ingensand, J., Ertz, O., and Collombin, M.: Open geospatial standards and reproducible research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14845, https://doi.org/10.5194/egusphere-egu23-14845, 2023.

EGU23-15384 | Orals | ESSI3.5 | Highlight

A peer review process for higher reproducibility of publications in GIScience can also work for Earth System Sciences 

Daniel Nüst, Frank O. Ostermann, and Carlos Granell

The Reproducible AGILE initiative (https://reproducible-agile.github.io/) successfully established a code execution procedure following the CODECHECK principles (https://doi.org/10.12688/f1000research.51738.2) at the AGILE conference series (https://agile-online.org/conference). The AGILE conference is a medium-sized community-led conference in the domains of Geographic Information Science (GIScience), geoinformatics, and related fields. The conference is organised under the umbrella of the Association of Geographic Information Laboratories in Europe (AGILE).

Starting with a series of workshops on reproducibility from 2017 to 2019, a group of Open Science enthusiasts with the support of the AGILE Council (https://agile-online.org/agile-actions/current-initiatives/reproducible-publications-at-agile-conferences) was able to introduce guidelines for sharing reproducible workflows (https://doi.org/10.17605/OSF.IO/CB7Z8) and establish a reproducibility committee that conducts code executions for all accepted full papers.
In this presentation, we provide details of the taken steps and the encountered obstacles towards the current state. We revisit the process and abstract a series of actions that similar events or even journals may take to introduce a shift towards higher reproducibility of research publications in a specific community of practice.

We discuss the taken approach in the light of the challenges for reproducibility in Earth System Sciences (ESS) around four main ideas.
First, Reproducible AGILE’s human-centered process is able to handle the increasingly complex, large and varying data-based workflows in ESS because of the clear guidance on responsibilities (What should the author provide? How far does the reproducibility reviewer need to go?).
Second, the communicative focus of the process is very well suited to, over time, help to establish a shared practice based on current technical developments, such as FAIR Digital Objects, and to reform attitudes towards openness, transparency and sharing. A code execution following the CODECHECK principles is a learning experience that may sustainably change researcher behaviours and practice. At the same time, Reproducible AGILE’s approach avoids playing catch-up with technology and does not limit researcher freedom or includes a need to unitise researcher workflows beyond providing instructions suitable for a human evaluator, similar to academic peer review.
Third, while being agnostic of technology and infrastructures, a supportive framework of tools and infrastructure can of course increase the efficiency of conducting a code execution. We outline how existing infrastructures may serve this need and what is still missing.
Fourth, we list potential candidates of event series or journals that could introduce a code checking procedure because of their organisational setup or steps towards more open scholarhip that were already taken.

How to cite: Nüst, D., Ostermann, F. O., and Granell, C.: A peer review process for higher reproducibility of publications in GIScience can also work for Earth System Sciences, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15384, https://doi.org/10.5194/egusphere-egu23-15384, 2023.

EGU23-15391 | Posters on site | ESSI3.5

Data Management for PalMod-II – data workflow and re-use strategy 

Swati Gehlot, Karsten Peters-von Gehlen, Andrea Lammert, and Hannes Thiemann

German climate research initiative PalMod phase II (www.palmod.de) is presented here as an exclusive example where the project end-product is unique, scientific paleo-climate data. PalMod-II data products include output from three state-of-the-art coupled climate models of varying complexity and spatial resolutions simulating the climate of the past 130,000 years. In addition to the long time series of modeling data, a comprehensive compilation of paleo-observation data is prepared to facilitate model-model and model-proxy intercomparison and evaluation. Being a large multidisciplinary project, a dedicated RDM (Research Data Management) approach is applied within the cross-cutting working group for PalMod-II. The DMP (Data Management Plan), as a living document, is used for documenting the data-workflow framework that defines the details of paleo-climate data life-cycle. The workflow containing the organisation, storage, preservation, sharing and long-term curation of the data is defined and tested.  In order to make the modeling data inter-comparable across the PalMod-II models and easily analyzable by the global paleo-climate community, model data standardization (CMORization) workflows are defined for individual PalMod models and their sub-models. The CMORization workflows contain setup, definition, and quality assurance testing of CMIP61 based standardization processes adapted to PalMod-II model simulation output requirements with a final aim of data publication via ESGF2. PalMod-II data publication via ESGF makes the paleo-climate data an asset which is (re-)usable beyond the project life-time.

The PalMod-II RDM infrastructure enables common research data management according to the FAIR3 data principles across all the working groups of PalMod-II using common workflows for the exchange of data and information along the process chain. Applying data management planning within PalMod-II made sure that all the data related workflows were defined, continuously updated if needed and made available to the project stakeholders. End products of PalMod-II which consist of unique long term scientific paleo-climate data (model as well as paleo-proxy data) are made available for re-use via the paleo-climate research community as well as other research disciplines (e.g., land-use, socio-economic studies etc.).

1. Coupled Model Intercomparison Project phase 6 (https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6)

2. Earth System Grid Federation (https://esgf.llnl.gov)

3. Findable, Accessible, Interoperable, Reusable

How to cite: Gehlot, S., Peters-von Gehlen, K., Lammert, A., and Thiemann, H.: Data Management for PalMod-II – data workflow and re-use strategy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15391, https://doi.org/10.5194/egusphere-egu23-15391, 2023.

EGU23-16288 | Orals | ESSI3.5 | Highlight

The UK’s NCAS Data Project: establishing transparent observational data workflows from field to user 

Graham Parton, Barbara Brooks, Ag Stephens, and Wendy Garland

Within the UK the National Centre for Atmospheric Science (NCAS) operates a suite of observational instruments for atmospheric dynamics, chemistry and composition studies. These are principally made available through two facilities: the Atmospheric Measurement and Observations Facility (AMOF) and the Facility for Airborne Atmospheric Measurements (FAAM). Between these two facilities instrumentation can be on either campaign or long-term deployed in diverse environments (from polar to maritime; surface to high altitude), on a range of platforms (aircraft, ships) or dedicated atmospheric observatories.

The wide range of instruments, spanning an operational time period from the mid 1990s to present, has traditionally been orientated to specific communities, resulting in a plethora of different operational practices, data standards and workflows. The resulting data management and usage challenges have been further exacerbated over time by changes of staff, instruments and end-user communities and their requirements. This has been accompanied by the wider end-user community seeking greater access to and improved use of the data, with necessary associated improvements in data production to ensure transparency, quality, veracity and, thus, overall reproducibility. Additionally, these enhancemed workflows further ensure FAIR data outputs, widening long-term re-use of the data. 

Seeking to address these challenges in a more harmonious approach across the range of AMOF and FAAM facilities, NCAS established the NCAS Data Project in 2018 bringing together key players in the data workflows to break down barriers and common standards and procedures through improved dialogue. The resulting NCAS ‘Data Pyramid’ approach, brings together representatives from the data provider, data archive and end-user communities alongside supporting software engineers within a common framework that enables cross-working between all partners. This has lead to new data standards and workflows being established to ensure 3 key objectives: 1) capturing and flow of the necessary metadata to automate data flows and quality control as much as possible in a timely fashion ‘from field to end-user’; 2) enhanced transparency and traceability in data production via linked externally visible documentation, calibration and code repositories; and, 3) data products meeting end-user requirements in terms of their content and established quality control. Finally, data workflows are further enhanced thanks to scriptable conformance checking throughout the data production lifecycle, built on the controlled data product and metadata standards.

Thus, through the established workflows of the NCAS Data Project, the necessary details are captured and conveyed by both internal file-level and catalogue-level metadata to ensure that all three corners of the triangle of reproducibility, quality information, and provenance are able to be achieved in combination.

How to cite: Parton, G., Brooks, B., Stephens, A., and Garland, W.: The UK’s NCAS Data Project: establishing transparent observational data workflows from field to user, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16288, https://doi.org/10.5194/egusphere-egu23-16288, 2023.

EGU23-17263 | Posters on site | ESSI3.5

Towards reproducible workflows in simulation based Earth System Science 

Ivonne Anders, Hannes Thiemann, Martin Bergemann, Christopher Kadow, and Etor Lucio-Eceiza

Some disciplines, e.g. Astrophysics or Earth system sciences, work with large to very large amounts of data. Storing this data, but also processing it, is a challenge for researchers because novel concepts for processing data and workflows have not developed as quickly. This problem will only become more pronounced with the ever increasing performance of High Performance Computing (HPC) – systems.

At the German Climate Computing Center, we analysed the users, their goals and working methods. DKRZ provides the climate science community with resources such as high-performance computing (HPC), data storage and specialised services and hosts the World Data Center for Climate (WDCC). In analysing users, we distinguish between two main groups: those who need the HPC system to run resource-intensive simulations and then analyse them, and those who reuse, build on and analyse existing data. Each group subdivides into subgroups. We have analysed the workflows for each identified user and found identical parts in an abstracted form and derived Canonical Workflow Modules. In the process, we critically examined the possible use of so-called FAIR Digital Objects (FDOs) and checked to what extent the derived workflows and workflow modules are actually future-proof.

We will show the analysis of the different users, the Canonical workflow and the vision of the FDOs. Furthermore, we will present the framework Freva and further developments and implementations at DKRZ with respect to the reproducibility of simulation-based research in the ESS.

How to cite: Anders, I., Thiemann, H., Bergemann, M., Kadow, C., and Lucio-Eceiza, E.: Towards reproducible workflows in simulation based Earth System Science, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17263, https://doi.org/10.5194/egusphere-egu23-17263, 2023.

As deep learning (DL) is gathering remarkable attention for its capacity to achieve accurate predictions in various fields, enormous applications of DL in geosciences also emerged. Most studies focus on the high accuracy of DL models by model selections and hyperparameter tuning. However, the interpretability of DL models, which can be loosely defined as comprehending what a model did, is also important but comparatively less discussed. To this end, we select thin section photomicrographs of five types of sedimentary rocks, including quartz arenite, feldspathic arenite, lithic arenite, dolomite, and oolitic packstone. The distinguishing features of these rocks are their characteristic framework grains. For example, the oolitic packstone contains rounded or oval ooids. A regular classification model using ResNet-50 is trained by these photomicrographs, which is assumed as accurate because its accuracy reaches 0.97. However, this regular DL model makes their classifications based on the cracks, cements, or even scale bars in the photomicrographs, and these features are incapable of distinguishing sedimentary rocks in real works. To rectify the models’ focus, we propose an attention-based dual network incorporating the microphotographs' global (the whole photomicrographs) and local features (the distinguishing framework grains). The proposed model has not only high accuracy (0.99) but also presents interpretable feature extractions. Our study indicates that high accuracy should not be the only metric of DL models, interpretability and models incorporating geological information require more attention.

How to cite: Zheng, D., Cao, Z., Hou, L., Ma, C., and Hou, M.: High accuracy doesn’t prove that a deep learning model is accurate: a case study from automatic rock classification of thin section photomicrographs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-244, https://doi.org/10.5194/egusphere-egu23-244, 2023.

EGU23-1183 | ECS | Orals | ITS1.5/GI1.5 | Highlight

Detection of anomalous NO2 emitting ships using AutoML on TROPOMI satellite data 

Solomiia Kurchaba, Jasper van Vliet, Fons J. Verbeek, and Cor J. Veenman

Starting from 2021 International Maritime Organization (IMO) introduced more demanding NOx emission restrictions for ships operating in waters of the North and Baltic Seas. All methods currently used for ship compliance monitoring are financially and time-demanding. Thus, it is important to prioritize the inspection of ships that have a high chance of being non-compliant. 

 

TROPOMI/S5P instrument for the first time allows a distinction of NO2 plumes from individual ships. Here, we present a method for the selection of potentially non-compliant ships using automated machine learning (AutoML) on TROPOMI/S5P satellite data. The study is based on the analysis of 20 months of data in the Mediterranean Sea region. To each ship, we assign a Region of Interest (RoI), where we expect the ship plume to be located. We then train a regression model to predict the amount of NO2 that is expected to be produced by a ship with specific properties operating in the given atmospheric conditions. We use a genetic algorithm-based AutoML for the automatic selection and configuration of a machine-learning pipeline that maximizes prediction accuracy. The difference between the predicted and actual amount of produced NO2 is a measure of inspection worthiness. We rank the analyzed ships accordingly. 

 

We cross-check the obtained ranks using a previously developed method for supervised ship plume segmentation.  We quantify the amount of NO2 produced by a given ship by summing up concentrations within the pixels identified as a “plume”. We rank the ships based on the difference between the obtained concentrations and the ship emission proxy.

 

Ships that are also ranked as highly deviating by the segmentation method need further attention. For example, by checking their data for other explanations. If no other explanations are found, these ships are advised to be the candidates for fuel inspection.

How to cite: Kurchaba, S., van Vliet, J., Verbeek, F. J., and Veenman, C. J.: Detection of anomalous NO2 emitting ships using AutoML on TROPOMI satellite data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1183, https://doi.org/10.5194/egusphere-egu23-1183, 2023.

Compaction of agricultural soil negatively affects its hydraulic proprieties, leading to water erosion and other negative effects on the quality of the environment. This study focused on the effect of compaction on soil hydrodynamic properties under unsaturated and saturated conditions using the Hydraulic Property Analyzer (HYPROP) system. We studied the impact of five levels of compaction among loam sand soils collected in a potato crop field in northern Québec, Canada. Soil samples were collected, and the soil bulk densities of the artificially compacted samples were developed by increasing the bulk density by 0% (C0), 30% (C30), 40% (C40), 50% (C50), and 70% (C70). First, the saturated hydraulic conductivity of each column was measured using the constant-head method. Soil water retention curve (SWRC) dry-end data and unsaturated hydraulic conductivities were obtained via the implementation and evaluation of the HYPROP evaporation measurement system and WP4-T Dew Point PotentioMeter equipment (METER group, Munich, Germany). Second, the soil microporosity was imaged and quantified using the micro-CT-measured pore-size distribution to visualize and quantify soil pore structures. The imaged soil microporosity was related to the saturated hydraulic conductivity, air permeability, porosity and tortuosity measured of the same samples.  Our results supported the application of the Peters–Durner–Iden (PDI) variant of the bimodal unconstrained van Genuchten model (VGm-b-PDI) for complete SWRC estimation based on the root mean square error (RMSE). The unsaturated hydraulic conductivity matched the PDI variant of the unconstrained van-Genuchten model (VGm-PDI) well. Finally, the preliminary results indicated that soil compaction could strongly influence the hydraulic properties of soil in different ways. The saturated conductivity decreased with increasing soil compaction, and the unsaturated hydraulic conductivity changed very rapidly with the ratio of water to soil. Overall, the HYPROP methodology performed extremely well in terms of the hydraulic behavior of compacted soils.

How to cite: Mbarki, Y. and Gumiere, S. J.: Study of the effect of compaction on the hydrodynamic properties of a loamy sand soil for precision agriculture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1583, https://doi.org/10.5194/egusphere-egu23-1583, 2023.

EGU23-1902 | Posters on site | ITS1.5/GI1.5

TACTICIAN: AI-based applications knowledge extraction from ESA’s mission scientific publications 

Omiros Giannakis, Iason Demiros, Konstantinos Koutroumbas, Athanasios Rontogiannis, Vassilis Antonopoulos, Guido De Marchi, Christophe Arviset, George Balasis, Athanasios Daglis, George Vasalos, Zoe Boutsi, Jan Tauber, Marcos Lopez-Caniego, Mark Kidger, Arnaud Masson, and Philippe Escoubet

Scientific publications in space science contain valuable and extensive information regarding the links and relationships between the data interpreted by the authors and the associated observational elements (e.g., instruments or experiments names, observing times, etc.). In this reality of scientific information overload, researchers are often overwhelmed by an enormous and continuously growing number of articles to access in their daily activities. The exploration of recent advances concerning specific topics, methods and techniques, the review and evaluation of research proposals and in general any action that requires a cautious and comprehensive assessment of scientific literature has turned into an extremely complex and time-consuming task.

The availability of Natural Language Processing (NLP) tools able to extract information from scientific unstructured textual contents and to turn it into extremely organized and interconnected knowledge, is fundamental in the framework of the use of scientific information. Exploitation of the knowledge that exists in the scientific publications, necessitates state-of-the-art NLP. The semantic interpretation of the scientific texts can support the development of a varied set of applications such as information retrieval from the texts, linking to existing knowledge repositories, topic classification, semi-automatic assessment of publications and research proposals, tracking of scientific and technological advances, scientific intelligence-assisted reporting, review writing, and question answering.

The main objectives of TACTICIAN are to introduce Artificial Intelligence (AI) techniques to the textual analysis of the publications of all ESA Space Science missions, to monitor and evaluate the scientific productivity of the science missions, and to integrate the scientific publications’ metadata into the ESA Space Science Archive. Through TACTICIAN, we extract lexical, syntactic, and semantic information from the scientific publications by applying NLP and Machine Learning (ML) algorithms and techniques. Utilizing the wealth of publications, we have created valuable scientific language resources, such as labeled datasets and word embeddings, which were used to train Deep Learning models that assist us in most of the language understanding tasks. In the context of TACTICIAN, we have devised methodologies and developed algorithms that can assign scientific publications to the Mars Express, Herschel, and Cluster ESA science missions and identify selected named entities and observations in these scientific publications. We also introduced a new unsupervised ML technique, based on Nonnegative Matrix Factorization (NMF), for classifying the Planck mission scientific publications to categories according to the use of the Planck data products.

These methodologies can be applied to any other mission. The combination of NLP and ML constitutes a general basis, which has proved that it can assist in establishing links between the missions’ observations and the scientific publications and to classify them in categories, with high accuracy.

This work has received funding from the European Space Agency under the "ArTificiAl intelligenCe To lInk publiCations wIth observAtioNs (TACTICIAN)" activity under ESA Contract No 4000128429/19/ES/JD.

How to cite: Giannakis, O., Demiros, I., Koutroumbas, K., Rontogiannis, A., Antonopoulos, V., De Marchi, G., Arviset, C., Balasis, G., Daglis, A., Vasalos, G., Boutsi, Z., Tauber, J., Lopez-Caniego, M., Kidger, M., Masson, A., and Escoubet, P.: TACTICIAN: AI-based applications knowledge extraction from ESA’s mission scientific publications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1902, https://doi.org/10.5194/egusphere-egu23-1902, 2023.

EGU23-2388 | ECS | Orals | ITS1.5/GI1.5

Deep learning based identification of carbonate rock components in core images 

Harriet Dawson and Cédric John

Identification of constituent grains in carbonate rocks is primarily a qualitative skill requiring specialist experience. A carbonate sedimentologist must be able to distinguish between various grains of different ages, preserved in differing alteration stages, and cut in random orientations across core sections. Recent studies have demonstrated the effectiveness of machine learning in classifying lithofacies from thin section, core and seismic images, with faster analysis times and reduction of natural biases.  In this study, we explore the application and limitations of convolutional neural network (CNN) based object detection frameworks to identify and quantify multiple types of carbonate grains within close-up core images. Nearly 400 images of carbonate cores we compiled of high-resolution core images from three ODP and IODP expeditions. Over 9,000 individual carbonate components of 11 different classes were manually labelled from this dataset. Using transfer learning, we evaluate one-stage (YOLO v3) and two-stage (Faster R-CNN) detectors under different feature extractors (Darknet and Inception-ResNet-v2). Despite the current popularity of one-stage detectors, our results show Faster R-CNN with Inception-ResNet-v2 backbone provides the most robust performance, achieving nearly 0.8 mean average precision (mAP). Furthermore, we extend the approach by deploying the trained model to ODP Leg 194 Sites 1196 and 1190, developing a performance comparison with human interpretation. 

How to cite: Dawson, H. and John, C.: Deep learning based identification of carbonate rock components in core images, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2388, https://doi.org/10.5194/egusphere-egu23-2388, 2023.

EGU23-3997 | ECS | Orals | ITS1.5/GI1.5

Artificial Intelligence Models for Detecting Spatiotemporal Crop Water Stress in schedule Irrigation: A review 

Elham Koohi, Silvio Jose Gumiere, and Hossein Bonakdari

Water used in agricultural crops can be managed by irrigation scheduling based on plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing stomatal conductance, growth rate, leaf water potential, and stem water potential. Calculating thresholds of soil matric potential, and available water content improves the precision of irrigation management by preventing water limitations between irrigations. Crop monitoring and irrigation management make informed decisions using geospatial technologies, the internet of things, big data analysis, and artificial intelligence. Remote sensing (RS) could be applied whenever in situ data are not available. High-resolution crop mapping extracts information through index-based methods fed by the multitemporal and multi-sensor data used in detection and classification. Precision Agriculture (PA) means applying farm inputs at the right amount, at the right time, and in the right place. RS in PA captures images in different spatial, and spectral resolutions through in-field, satellites, aerial, and handheld or tractor-mounted such as unmanned aerial vehicles (UAVs) sensors. RS sensors receive the electromagnetic signals of plant responses in different spectral domains. Optical satellite data, including narrow-band multispectral remote sensing techniques and thermal imagery, is used for water stress detection. To process and analysis RS data, cloud storage and computing platforms simplify the complex mathematical of incorporating various datasets for irrigation scheduling. Machine learning (ML) algorithms construct models for the regression and classification of multivariate and non-linear crop mapping. The web-based software gathered from all different datasets makes a reliable product to reinforce farmers’ ability to make appropriate decisions in irrigating agricultural crops.

Keywords: Agricultural crops; Crop water stress detection; Irrigation scheduling; Precision agriculture; Remote Sensing.

How to cite: Koohi, E., Gumiere, S. J., and Bonakdari, H.: Artificial Intelligence Models for Detecting Spatiotemporal Crop Water Stress in schedule Irrigation: A review, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3997, https://doi.org/10.5194/egusphere-egu23-3997, 2023.

EGU23-6696 | ECS | Orals | ITS1.5/GI1.5 | Highlight

Satellite-based continental-scale inventory of European wetland types at 10m spatial resolution 

Gyula Mate Kovács, Stefan Oehmcke, Stéphanie Horion, Dimitri Gominski, Xiaoye Tong, and Rasmus Fensholt

Wetlands provide invaluable services for ecosystems and society and are a crucial instrument in our fight against climate change. Although Earth Observation satellites offer cost-effective and accurate information about wetland status at the continental scale; to date, there is no universally accepted, standardized, and regularly updated inventory of European wetlands <100m resolution. Moreover, previous satellite-based global land cover products seldom account for wetland diversity, which often impairs their mapping performances. Here, we mapped major wetland types (i.e., peatland, marshland, and coastal wetlands) across Europe for 2018, based on high resolution (10m) optical and radar time series satellite data as well as field-collected land cover information (LUCAS) using an ensemble model combining traditional machine learning and deep learning approaches. Our results show with high accuracy (>85%) that a substantial extent of European peatlands was previously classified as grassland and other land cover types. In addition, our map highlights cultivated areas (e.g., river floodplains) that can be potentially rewetted. Such accurate and consistent mapping of different wetland types at a continental scale offers a baseline for future wetland monitoring and trend assessment, supports the detailed reporting of European carbon budgets, and lays down the foundation towards a global wetland inventory.

How to cite: Kovács, G. M., Oehmcke, S., Horion, S., Gominski, D., Tong, X., and Fensholt, R.: Satellite-based continental-scale inventory of European wetland types at 10m spatial resolution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6696, https://doi.org/10.5194/egusphere-egu23-6696, 2023.

EGU23-8409 | ECS | Orals | ITS1.5/GI1.5

Evaluation of lagoon eutrophication potential under climate change conditions: A novel water quality machine learning and biogeochemical-based framework. 

Federica Zennaro, Elisa Furlan, Donata Melaku Canu, Leslie Aveytua Alcazar, Ginevra Rosati, Sinem Aslan, Cosimo Solidoro, and Andrea Critto

Lagoons are highly valued coastal environments providing unique ecosystem services. However, they are fragile and vulnerable to natural processes and anthropogenic activities. Concurrently, climate change pressures, are likely to lead to severe ecological impacts on lagoon ecosystems. Among these, direct effects are mainly through changes in temperature and associated physico-chemical alterations, whereas indirect ones, mediated through processes such as extreme weather events in the catchment, include the alteration of nutrient loading patterns among others that can, in turn, modify the trophic states leading to depletion or to eutrophication. This phenomenon can lead, under certain circumstances, to harmful algal blooms events, anoxia, and mortality of aquatic flora and fauna, or to the reduction of primary production, with cascading effects on the whole trophic web with dramatic consequences for aquaculture, fishery, and recreational activities. The complexity of eutrophication processes, characterized by compounding and interconnected pressures, highlights the importance of adequate sophisticated methods to estimate future ecological impacts on fragile lagoon environments. In this context, a novel framework combining Machine Learning (ML) and biogeochemical models is proposed, leveraging the potential offered by both approaches to unravel and modelling environmental systems featured by compounding pressures. Multi-Layer Perceptron (MLP) and Random Forest (RF) models are used (trained, validated, and tested) within the Venice Lagoon case study to assimilate historical heterogenous WQ data (i.e., water temperature, salinity, and dissolved oxygen) and spatio-temporal information (i.e., monitoring station location and month), and to predict changes in chlorophyll-a (Chl-a) conditions. Then, projections from the biogeochemical model SHYFEM-BFM for 2049, and 2099 timeframes under RCP 8.5 are integrated to evaluate Chl-a variations under future bio-geochemical conditions forced by climate change projections. Annual and seasonal Chl-a predictions were performed out by classes based on two classification modes established on the descriptive statistics computed on baseline data: i) binary classification of Chl-a values under and over the median value, ii) multi-class classification defined by Chl-a quartiles. Results from the case study showed as the RF successfully classifies Chl-a under the baseline scenario with an overall model accuracy of about 80% for the median classification mode, and 61% for the quartile classification mode. Overall, a decreasing trend for the lowest Chl-a values (below the first quartile, i.e. 0.85 µg/l) can be observed, with an opposite rising fashion for the highest Chl-a values (above the fourth quartile, i.e. 2.78 µg/l). On the seasonal level, summer remains the season with the highest Chl-a values in all scenarios, although in 2099 a strong increase in Chl-a is also expected during the spring one. The proposed novel framework represents a valuable approach to strengthen both eutrophication modelling and scenarios analysis, by placing artificial intelligence-based models alongside biogeochemical models.

How to cite: Zennaro, F., Furlan, E., Melaku Canu, D., Aveytua Alcazar, L., Rosati, G., Aslan, S., Solidoro, C., and Critto, A.: Evaluation of lagoon eutrophication potential under climate change conditions: A novel water quality machine learning and biogeochemical-based framework., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8409, https://doi.org/10.5194/egusphere-egu23-8409, 2023.

EGU23-8702 | ECS | Orals | ITS1.5/GI1.5 | Highlight

Evaluating the risk of cumulative impacts in the Mediterranean Sea using a Random Forest model 

Angelica Bianconi, Elisa Furlan, Christian Simeoni, Vuong Pham, Sebastiano Vascon, Andrea Critto, and Antonio Marcomini

Marine coastal ecosystems (MCEs) are of vital importance for human health and well-being. However, their ecological condition is increasingly threatened by multiple risks induced by the complex interplay between endogenic (e.g. coastal development, shipping traffic) and exogenic (e.g. changes in sea surface temperature, waves, sea level, etc.) pressures. Assessing cumulative impacts resulting from this dynamic interplay is a major challenge to achieve Sustainable Development Goals and biodiversity targets, as well as to drive ecosystem-based management in marine coastal areas. To this aim, a Machine Learning model (i.e. Random Forest - RF), integrating heterogenous data on multiple pressures and ecosystems’ health and biodiversity, was developed to support the evaluation of risk scenarios affecting seagrasses condition and their services capacity within the Mediterranean Sea. The RF model was trained, validated and tested by exploiting data collected from different open-source data platforms (e.g. Copernicus Services) for the baseline 2017. Moreover, based on the designed RF model, future scenario analysis was performed by integrating projections from climate numerical models for sea surface temperature and salinity under the 2050 and 2100 timeframes. Particularly, under the baseline scenario, the model performance achieved an overall accuracy of about 82%. Overall, the results of the analysis showed that the ecological condition and services capacity of seagrass meadows (i.e. spatial distribution, Shannon index, carbon sequestration) are mainly threatened by human-related pressures linked to coastal development (e.g. distance from main urban centres), as well as to changes in nutrient concentration and sea surface temperature. This result also emerged from the scenario analysis, highlighting a decrease in seagrass coverage and related services capacity, in both 2050 and 2100 timeframes. The developed model provides useful predictive insight on possible future ecosystem conditions in response to multiple pressures, supporting marine managers and planners towards more effective ecosystem-based adaptation and management measures in MCEs.

How to cite: Bianconi, A., Furlan, E., Simeoni, C., Pham, V., Vascon, S., Critto, A., and Marcomini, A.: Evaluating the risk of cumulative impacts in the Mediterranean Sea using a Random Forest model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8702, https://doi.org/10.5194/egusphere-egu23-8702, 2023.

EGU23-10681 | Orals | ITS1.5/GI1.5

EarthQA: A Question Answering Engine for Earth Observation Data Archives 

Dharmen Punjani, Eleni Tsalapati, and Manolis Koubarakis

The standard way for earth observation experts or users to retrieve images from image archives (e.g., ESA's Copernicus Open Access Hub) is to use a graphical user interface, where they can select the geographical area of the image they are interested in and additionally they can specify some other metadata, such as sensing period, satellite platform and cloud cover.

In this work, we are developing the question-answering engine EarthQA that takes as input a question expressed in natural language (English) that asks for satellite images satisfying certain criteria and returns links to such datasets, which can be then downloaded from the CREODIAS cloud platform. To answer user questions, EarthQA queries two interlinked knowledge graphs: a knowledge graph encoding metadata of satellite images from the CREODIAS cloud platform (the SPARQL endpoint of CREODIAS) and the well-known knowledge graph DBpedia. Hence, the questions can refer to image metadata (e.g., satellite platform, sensing period, cloud cover), but also to more generic entities appearing in DBpedia knowledge graph (e.g., lake, Greece). In this way, the users can ask questions like “Find all Sentinel-1 GRD images taken during October 2021 that show large lakes in Greece having an area greater than 100 square kilometers”.

EarthQA follows a template-based approach to translate natural language questions into formal queries (SPARQL). Initially, it decomposes the user question by generating its dependency parse tree and then automatically disambiguates the components appearing in the question to elements of the two knowledge graphs.  In particular, it automatically identifies the spatial or temporal entities (e.g., “Greece”, “October 2021”), concepts (e.g., “lake”), spatial or temporal relations (e.g., “in”, “during”), properties (e.g., “area”) and product types (e.g., “Sentinel-1 GRD”) and other metadata (e.g., “cloud cover below 10%”) mentioned in the question and maps them to the respective elements appearing in the two knowledge graphs (dbr:Greece, dbo:Lake, dbp:area, etc). After this, the SPARQL query is automatically generated.

How to cite: Punjani, D., Tsalapati, E., and Koubarakis, M.: EarthQA: A Question Answering Engine for Earth Observation Data Archives, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10681, https://doi.org/10.5194/egusphere-egu23-10681, 2023.

EGU23-11527 | ECS | Posters on site | ITS1.5/GI1.5

Global Layer——An integrated, fully online, cloud based platform 

Xingchen Yang, Yang Song, Zhenhan Wu, and Chaowei Wu

In the current stage of scientific research, it is necessary to break the barriers between traditional disciplines and promote the cross integration of various related disciplines. As one of the important carriers of research achievements of various disciplines, maps can be superimposed and integrated to more intuitively display the results of multidisciplinary integration, promote the integration of disciplines and discover new scientific problems. Traditional geological mapping is often based on different scales for single scale mapping, aiming at the mapping mode of paper printing results. It is difficult to read maps between different scales at the same time. To solve this problem,an integrated platform named Global Layer is being built under the support of Deep-time Digital Earth (DDE). Global Layer is embedded with several core databases such as Geological Map of the World at a scale 1/5M, Global Geothermal Database etc. These databases presented in form of electronic map which enables the results of different scales to be displayed and browsed through one-stop hierarchical promotion. In addition, Users can also upload data in four ways: local file, database connection, cloud file and arcgis data service, and data or maping results can be shared to Facebook, Twitter and other platforms in the form of links, widgets, etc. Construction of Global Layer could provide experience and foundation for integrating global databases related to geological map and constructing data platforms.

How to cite: Yang, X., Song, Y., Wu, Z., and Wu, C.: Global Layer——An integrated, fully online, cloud based platform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11527, https://doi.org/10.5194/egusphere-egu23-11527, 2023.

EGU23-12373 | ECS | Posters on site | ITS1.5/GI1.5

Mapping streams and ditches using Aerial Laser Scanning 

Mariana Dos Santos Toledo Busarello, Anneli Ågren, and William Lidberg

Streams and ditches are seldom identified on current maps due to their small dimensions and sometimes intermittent nature. Estimates point out that only 9% of all ditches are currently mapped, and the underestimation of natural streams is a global issue. Ditches have been dug in European boreal forests and some parts of North America to drain wetlands and increase forest production, consequently boosting the availability of cultivable land and a national-scale landscape modification. Target 6.6 of the Agenda 2030 highlights the importance of protecting and restoring water-related ecosystems. Wetlands are a substantial part of this, having a high carbon storage capability, the property of mitigating floods, and purifying water. All things accounted for, the withdrawal of anthropogenic environment alterations can be on the horizon, even more because ditches are also strong emitters of methane and other greenhouse gases due to their anoxic water and sediment accumulation. However, streams and ditches that are missing from maps and databases are difficult to manage.

The main focus of this study was to develop a method to map channels combining deep learning and national Aerial Laser Scans (ALS). The performance of different topographical indices derived from the ALS data was evaluated, and two different Digital Elevation Model (DEM) resolutions were compared. Ditch channels and natural streams were manually digitized from ten regions across Sweden, summing up to 1923km of ditch channels and 248km of natural streams. The topographical indices used were: high-passing median filter, slope, sky-view factor and hillshade (with azimuths of 0°, 45°, 90° and 135°); while 0.5m and 1m were the DEM resolutions analysed. A U-net model was trained to segment images between ditches and stream channels: all pixels from each image were labelled in a way that those with the same class display similar attributes.

Results showed that ditches can be successfully mapped with this method and it can generally be applied anywhere since only local terrain indices are required. Additionally, when the natural streams are present in the dataset the model underperformed in predicting the location of ditches, while a higher resolution had the opposite effect. Streams were more challenging to map, and the model only indicated the channels, not whether or not they contained water. Further research will be required to combine hydrological modelling and deep learning.

How to cite: Dos Santos Toledo Busarello, M., Ågren, A., and Lidberg, W.: Mapping streams and ditches using Aerial Laser Scanning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12373, https://doi.org/10.5194/egusphere-egu23-12373, 2023.

EGU23-13099 | ECS | Posters virtual | ITS1.5/GI1.5

Mapping Swedish Soils with High-resolution DEM-derived Indices and Machine Learning 

Yiqi Lin, William Lidberg, Cecilia Karlsson, and Anneli Ågren

There is a soaring demand for up-to-date and spatially-explicit soil information to address various environmental challenges. One of the most basic pieces of information, essential for research and decision-making in multiple disciplines is soil classification. Conventional soil maps are often low in spatial resolution and lack the complexity to be practical for hands-on use. Digital Soil Mapping (DSM) has emerged as an efficient alternative for its reproducibility, updatablity, accuracy, and cost-effectiveness, as well as the ability to quantify uncertainties.

Despite DSM’s growing popularity and increasingly wider areas of application, soil information is still rare in forested areas and remote regions, and the integration with high-resolution data on a country scale remains limited. In Sweden, quaternary deposit maps created by the Geological Survey of Sweden (SGU) have been the main reference input for soil-related research and operation, though most parts of the country still warrant higher quality representation. This study utilizes machine learning to produce a high-resolution surficial deposits map with nationwide coverage, capable of supporting research and decision-making. More specifically, it: i) compares the performance of two tree-based ensemble machine learning models, Extreme Gradient Boosting and Random Forest, in predictive mapping of soils across the entire country of Sweden; ii) determines the best model for spatial prediction of soil classes and estimates the associated uncertainty of the inferred map; iii) discusses the advantages and limitations of this approach, and iv) outputs a map product of soil classes at 2-m resolution. Similar attempts around the globe have shown promising results, though at coarser resolutions and/or of smaller geographical extent. The main assumptions behind this study are: i) terrain indices derived from digital elevation model (DEM) are useful predictors of soil type, though different classification algorithms differ in their effectiveness; ii) machine learning can capture major soil classes that cover most of Sweden, but expert geological and pedological knowledge is required when identifying rare soil types.

To achieve this, approximately 850,000 labeled soil points extracted from the most accurate SGU maps will be combined with a stack of 12 LiDAR DEM-derived topographic and hydrological indices and 4 environmental datasets. Uncertainty estimates of the overall model and for each soil class will be presented. An independent dataset obtained from the Swedish National Forest Soil Inventory will be used to assess the accuracy of the machine learning model. The presentation will cover the method, data handling, and some promising preliminary results.

How to cite: Lin, Y., Lidberg, W., Karlsson, C., and Ågren, A.: Mapping Swedish Soils with High-resolution DEM-derived Indices and Machine Learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13099, https://doi.org/10.5194/egusphere-egu23-13099, 2023.

As human activities continue to expand and evolve, their impact on the planet is becoming more evident. These past years Murmuration has been studying one of the most recent and destructive trends that has taken off: mass tourism. In Malta, tourism has been on the rise since before the Covid-19 pandemic. Now that travel restrictions are beginning to lift, it's likely that this trend will go back to increasing in the coming years. While Malta’s economy is mostly based on tourism, it's essential that this activity does not alter the areas in which it takes place. To address these issues and ensure sustainable development, governments and organizations have developed a set of guidelines called Sustainable Development Goals (SDG). SDGs are a set of 17 goals adopted by the United Nations in 2015 to provide a framework to help countries pursue sustainable economic, social and environmental development. They include objectives for mitigating climate change, preventing water pollution and degradation of biodiversity, as well as providing economic benefits to local communities.

In order to help territories like the islands of Malta to cope with these environmental issues, Murmuration carries out studies on various ecological, human and economic indicators. Using the Sentinel satellites of the European Copernicus program for earth imagery data makes possible the collection of geolocated, hourly values on air quality indicators such as NO2, CO and other pollutants but also water quality and vegetation through the analysis of the vegetation health. Other data sources give access to land cover values at meter resolution, tourism infrastructures locations and many more human activity variables. This information is processed into understandable indicators, aggregated indexes which take international standards and SDGs in their design and usage. An example of these standards are the WHO air quality guidelines providing thresholds quantifying the impact on health of the air pollution in the area of interest. The last step is to gather all the data, maps and correlations computed and design understandable visualizations to make it usable by territory management instances, enabling efficient decision making and risk management. The goal here is to achieve a link between satellite imagery, internationally agreed political commitment  and ground level decision-making.

This meaningful aggregation comes in the shape of operational dashboards. A dashboard is an up-to-date, interactive, evolving online tool hosting temporal and geographical linked visualizations on various indicators. This kind of tool allows for a better understanding of the dynamic of a territory in terms of environmental state, human impact and ecological potential.

How to cite: Plantec, M. and Castel, F.: From satellite data and Sustainable Development Goals to interactive tools and better territorial decision making, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14519, https://doi.org/10.5194/egusphere-egu23-14519, 2023.

EGU23-15656 | Posters virtual | ITS1.5/GI1.5

Karst integration into groundwater recharge simulation in WaterGAP 

Wenhua Wan and Petra Döll

Karst aquifers cover a significant portion of the global water supply. However, a proper representation of groundwater recharge in karst areas is completely absent in the state-of-art global hydrological models. This study, based on the new version of the global hydrological model WaterGAP, (1) presented the first modeling of diffuse groundwater recharge (GWR) in all karst regions using the global map of karstifiable rocks; and (2) adjusted the current GWR algorithm with the up-to-date databases of slope and soil. A large number of ground-based recharge estimates on 818 half degree cells including 75 in karst areas were compared to model results. GWR in karst landscapes assuming equal to the runoff from soil leads to unbiased estimation. The majority of simulated mean annual recharge ranges from 0.6 mm/yr (10th percentile) to 326.9 mm/yr (90th) in nonkarst regions, and 7.5 mm/yr (10th) to 740.2 mm/yr (90th) in karst regions. The recharge rate ranges from 2% to 66% of precipitation according to ground-based estimates in karst regions, while the simulated GWR produces global recharge fractions between 4% (10th) to 68% (90th) in karst areas while that in nonkarst areas rarely exceeds 25%. Unlike the previous studies that claimed global hydrological models consistently underestimate recharge, we observed underestimation only in the very humid regions where recharge exceeds 300 mm/yr. These very high recharge estimates are likely to include preferential flow and adopt a finer spatial and temporal scale than the global model. In karst landscapes and arid regions, we demonstrate that WaterGAP incorporating karst algorithm gives a worthy performance.

 

How to cite: Wan, W. and Döll, P.: Karst integration into groundwater recharge simulation in WaterGAP, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15656, https://doi.org/10.5194/egusphere-egu23-15656, 2023.

EGU23-16252 | ECS | Posters on site | ITS1.5/GI1.5

GEOTEK: Extracting Marine Geological Data from Publications 

Muhammad Asif Suryani, Christian Beth, Klaus Wallmann, and Matthias Renz

In Marine Geology, scientists persistently perform extensive experiments to measure diverse features across the globe, hence to estimate environmental changes. For example, Mass Accumulation Rate (MAR) and Sedimentation Rate (SR) are measured by marine geologists at various oceanographic locations and are largely reported in research publications but have not been compiled in any central database. Furthermore, every MAR and SR observation normally carries i) exact locational information (Longitude and Latitude), ii) the method of measurement (stratigraphy, 210Pb), iii) a numerical value and units (2.4 g/m2/yr), iv) temporal feature (e.g. hundred years ago). The contextual information attached to MAR and SR observations is heterogeneous and manual approaches for information extraction from text are infeasible. It is also worth mentioning that MAR and SR are not denoted in standard international (SI) units.

We propose the comprehensive end-to-end framework GEOTEK (Geological Text to Knowledge) to extract targeted information from marine geology publications. The proposed framework comprises three modules. The first module carries a document relevance model alongside a PDF extractor, capable of filtering relevant sources using metadata, and the extraction module extracts text, tables, and metadata respectively. The second module mainly comprises of two information extractors, namely Geo-Quantities and Geo-Spacy, particularly trained on text from the Marine Geology domain. Geo-Quantities is capable of extracting relevant numerical information from the text and covers more than 100 unit variants for MAR and SR, while Geo-Spacy extracts a set of relevant named entities as well as locational entities, which are further processed to obtain respective geocode boundaries. The third module, the Heterogeneous Information Linking module (HIL), processes exact spatial information from tables and captions and forms links to the previously extracted measurements. Finally, the all-linked information is populated in an interactive map view.

How to cite: Suryani, M. A., Beth, C., Wallmann, K., and Renz, M.: GEOTEK: Extracting Marine Geological Data from Publications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16252, https://doi.org/10.5194/egusphere-egu23-16252, 2023.

EGU23-16813 | ECS | Posters on site | ITS1.5/GI1.5 | Highlight

The Use of Artificial Intelligence in ESA’s Climate Change Initiative 

Anna Jungbluth, Ed Pechorro, Clement Albergel, and Susanne Mecklenburg

Climate change is arguably the greatest environmental challenge facing humankind in the twenty-first century. The United Nations Framework Convention on Climate Change (UNFCCC) facilitates multilateral action to combat climate change and its impacts on humanity and ecosystems. To make decisions on climate change mitigation and adaptation, the UNFCCC requires systematic observations of the global climate system.

The objective of the ESA’s climate programme, currently delivered via the Climate Change Initiative (CCI), is to realise the full potential of the long-term, global-scale, satellite earth observation archive that ESA and its Member States have established over the last 35 years, as a significant and timely contribution to the climate data record required by the UNFCCC.

Since 2010, the programme has contributed to a rapidly expanding body of scientific knowledge on >22 Essential Climate Variables (ECVs), through the production of Climate Data Records (CDRs). Although varying across geophysical parameters, ESA CDRs follow community-driven data standards, facilitating inter- and cross-ECV research of the climate system.

In this work, we highlight the use of artificial intelligence (AI) in the context of the ESA CCI. AI has played a pivotal role in the production and analysis of these Climate Data Records. Eleven CCI projects - Greenhouse Gases (GHG), Aerosols, Clouds, Fire, Ocean Colour, Sea Level, Soil Moisture, High Resolution Landcover, Biomass, Permafrost, and Sea Surface Salinity - have applied AI in their data record production and research or have identified specific AI usage for their research roadmaps.

The use of AI in these CCI projects is varied, for example - GHG CCI algorithms using random forest machine learning techniques; Aerosol CCI algorithms to retrieve dust aerosol optical depth from thermal infrared spectra; Fire CCI algorithms to detect burned areas. Moreover, the ESA climate community has identified climate science gaps in context to ECVs with the potential for meaningful advancement through AI.

We specifically focus on showcasing the use of AI for data homogenization and super-resolution of ESA CCI datasets. For instance, both the land cover and fire CCI dataset were generated globally in low resolution, while high resolution data only exists for specific geographical regions. By adapting super-resolution algorithms to the specific science use cases, we can accelerate the generation of global, high-resolution datasets with the required temporal coverage to support long-term climate studies. 

How to cite: Jungbluth, A., Pechorro, E., Albergel, C., and Mecklenburg, S.: The Use of Artificial Intelligence in ESA’s Climate Change Initiative, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16813, https://doi.org/10.5194/egusphere-egu23-16813, 2023.

In most places on the planet vegetation thrives: it is known as “greening Earth”. However in certain regions, especially in the Arctic, there are areas exhibiting a browning trend. This phenomenon is well known but not fully understood yet, and grasping its impact on local ecosystems requires involvement of scientists from different disciplines, including social sciences and humanities, as well as local populations. Here we focus on the Troms and Finnmark counties in northern Norway to assess the extent of the problem and any link with local environmental conditions as well as potential impacts. 

We have chosen to adopt an open and collaborative process and take advantage of the services offered by RELIANCE on the European Open Science Cloud (EOSC). RELIANCE delivers a suite of innovative and interconnected services that extend the capabilities of the European Open Science Cloud (EOSC) to support the management of the research lifecycle within Earth Science Communities and Copernicus Users. The RELIANCE project has delivered 3 complementary  technologies: Research Objects (ROs), Data Cubes and AI-based Text Mining. RoHub is a Research Object management platform that implements these 3 technologies and enables researchers to collaboratively manage, share and preserve their research work. 

We will show how we are using these technologies along with EGI notebooks to work open and share an executable Jupyter Notebook that is fully reproducible and reusable. We use a number of Python libraries from the Pangeo software stack such as Xarray, Dask and Zarr. Our Jupyter Notebook is bundled with its computational environment, datacubes and related bibliographic resources in an executable Research Object. We believe that this approach can significantly speed up the research process and can drive it to more exploitable results. 

Up to now, we have used indices derived from satellite data (in particular Sentinel-2) to assess how the vegetation cover in Troms and Finnmark counties has changed. To go a bit further we are investigating how to relate such information to relevant local parameters obtained from meteorological reanalysis data (ERA5 and ERA5-land from ECMWF). That should give a good basis for training an Artificial Intelligence algorithm and testing it, with the objective of getting an idea about the possibility of “predicting” what is likely to happen in the near future with certain types of vegetation like mosses and lichens which are essential for local populations and animals.

How to cite: Iaquinta, J. and Fouilloux, A.: Using FAIR and Open Science practices to better understand vegetation browning in Troms and Finnmark (Norway), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2579, https://doi.org/10.5194/egusphere-egu23-2579, 2023.

EGU23-3639 | Orals | ESSI2.8

Data Proximate Computation; Multi-cloud approach on European Weather Cloud and Amazon Web Services  

Armagan Karatosun, Michael Grant, Vasileios Baousis, Duncan McGregor, Richard Care, John Nolan, and Roope Tervo

Although utilizing the cloud infrastructure for big data processing algorithms is increasingly common, the challenges of utilizing cloud infrastructures efficiently and effectively are often underestimated. This is especially true in multi-cloud scenarios where data are available only on a subset of the participating clouds. In this study, we have iteratively developed a solution enabling efficient access to ECMWF’s Numerical Weather Prediction (NWP) and EUMETSAT’s satellite data on the European Weather Cloud [1], in combination with UK Met Office assets in Amazon Web Services (AWS), in order to provide a common template for multi-cloud processing solutions in meteorological application development and operations in Europe.  

Dask [2] was chosen as the computing framework due to its widespread use in the meteorological community, its ability to automatically spread processing, and its flexibility in changing how workloads are distributed across physical or virtualized infrastructures while maintaining scalability. However, the techniques used here are generally applicable to other frameworks. The primary limitation in using Dask is that all nodes should be able to intercommunicate freely, which is a serious limitation when nodes are distributed over multiple clouds. Although it is possible to route between multiple cloud environments over the Internet, this introduces considerable administrative work (firewalls, security) as well as networking complexities (e.g., due to extensive use of potentially-clashing private IP ranges and NAT in clouds, or cost for public IPs). Virtual Private Networks (VPNs) can hide these issues, but many use a hub-and-spokes model, meaning that communications between workers pass through a central hub. By use of a mesh network VPN (WireGuard) between clusters using IPv6 private addressing, all these difficulties can be avoided, in addition to providing a simplified network addressing scheme with extremely high scalability. Another challenge was to ensure the Dask worker nodes were aware of data locality, both in terms of placing work near data and in terms of minimizing transfers. Here, the UK Met Office’s work on labeling resource pools (in this case, data) and linking scheduling decisions to labels was the key. 

In summary, by adapting Dask's concept of resourcing [3] into resource pools [4], building an automated start-up process, and effectively utilizing self-configuring IPv6 VPN mesh networks, we managed to provide a “cloud-native” transient model where all resources can be easily created and disposed of as needed. The resulting “throwaway” multi-cloud Dask framework is able to efficiently place processing on workers proximate to the data while minimizing necessary data traffic between clouds, thus achieving results more quickly and cheaper than naïve implementations, and with a simple, automated setup suitable for meteorological developers. The technical basis of this work was published on the Dask blog [5] but is covered more holistically here, particularly regarding the application side and challenges of developing cloud-native applications which can effectively utilize modern multi-cloud environments, with future applicability to distributed (e.g., Kubernetes) and serverless computing models. 

References: 

[1] https://www.europeanweather.cloud 
[2] https://www.dask.org 
[3] https://distributed.dask.org/en/stable/resources.html
[4] https://github.com/gjoseph92/dask-worker-pools  
[5] https://blog.dask.org/2022/07/19/dask-multi-cloud  

How to cite: Karatosun, A., Grant, M., Baousis, V., McGregor, D., Care, R., Nolan, J., and Tervo, R.: Data Proximate Computation; Multi-cloud approach on European Weather Cloud and Amazon Web Services , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3639, https://doi.org/10.5194/egusphere-egu23-3639, 2023.

The National Oceanic and Atmospheric Administration (NOAA) established the Earth Prediction Innovation Center (EPIC) to be the catalyst for community research and modeling focused on informing and accelerating advances in our nation’s operational NWP forecast modeling systems. The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth modeling system. The UFS numerical applications span local to global domains and predictive time scales from sub-hourly analyses to seasonal predictions. It is designed to support the Weather Enterprise and to be the source system for NOAA‘s operational numerical weather prediction applications. EPIC applies an open-innovation and open-development framework that embraces open-source code repositories integrated with automated Continuous Integration/Continuous Deployment (CI/CD) pipelines on cloud and on-prem HPCs. EPIC also supports UFS public releases, tutorials and training opportunities (e.g., student workshops, hackathons, and codesprints), and advanced user support via a virtual community portal (epic.noaa.gov). This framework allows community developers to track the status of their contributions, and facilitate rapid incorporation of innovation by implementing consistent and transparent, standardized and community-driven validation and verification tests. In this presentation, I will demonstrate capabilities in the EPIC framework using the UFS Short-range Weather (SRW) Application as an example in the follow aspects:

  • Public Releases of a Cloud-ready UFS SRW application with a scalable container following a modernize continuous release paradigm 
  • Test cases for challenging forecast environments released with datasets
  • Training and Tutorials for users and developers
  • Baseline for benchmarking in skill and computation on cloud HPCs , and
  • An Automated CI/CD pipeline to enable seamless transition to operations

How to cite: Huang, M.: An Open-innovation and Open-development Framework for the Unified Forecast System Powered by the Earth Prediction Innovation Center, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3738, https://doi.org/10.5194/egusphere-egu23-3738, 2023.

EGU23-4298 | Orals | ESSI2.8

BUILDSPACE: Enabling Innovative Space-driven Services for Energy Efficient Buildings and Climate Resilient Cities 

Stamatia Rizou, Vaggelis Marinakis, Gema Hernández Moral, Carmen Sánchez-Guevara, Luis Javier Sánchez-Aparicio, Ioannis Brilakis, Vasileios Baousis, Tijs Maes, Vassileios Tsetsos, Marco Boaria, Piotr Dymarski, Michail Bourmpos, Petra Pergar, and Inga Brieze

BUILDSPACE aims to couple terrestrial data from buildings (collected by IoT platforms, BIM solutions and other) with aerial imaging from drones equipped with thermal cameras and location annotated data from satellite services (i.e., EGNSS and Copernicus) to deliver innovative services for the building and urban stakeholders and support informed decision making towards energy-efficient buildings and climate resilient cities. The platform will allow integration of these heterogeneous data and will offer services at building scale, enabling the generation of high fidelity multi-modal digital twins and at city scale providing decision support services for energy demand prediction, urban heat and urban flood analysis. The services will enable the identification of environmental hotspots that increase pressure to local city ecosystems and raise probability for natural disasters (such as flooding) and will issue alerts and recommendations for action to local governments and regions (such as the support of policies for building renovation in specific vulnerable areas). BUILDSPACE services will be validated and assessed in four European cities with different climate profiles. The digital twin services at building level will be tested during the construction of a new building in Poland, and the city services validating the link to digital twin of buildings will be tested in 3 cities (Piraeus, Riga, Ljubljana) across EU. BUILDSPACE will create a set of replication guidelines and blueprints for the adoption of the proposed applications in building resilient cities at large. 

How to cite: Rizou, S., Marinakis, V., Hernández Moral, G., Sánchez-Guevara, C., Sánchez-Aparicio, L. J., Brilakis, I., Baousis, V., Maes, T., Tsetsos, V., Boaria, M., Dymarski, P., Bourmpos, M., Pergar, P., and Brieze, I.: BUILDSPACE: Enabling Innovative Space-driven Services for Energy Efficient Buildings and Climate Resilient Cities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4298, https://doi.org/10.5194/egusphere-egu23-4298, 2023.

EGU23-5807 | Orals | ESSI2.8

The EuroHPC Center of Excellence for Exascale in Solid Earth 

Arnau Folch, Josep DelaPuente, Antonio Costa, Benedikt Halldórson, Jose Gracia, Piero Lanucara, Michael Bader, Alice-Agnes Gabriel, Jorge Macías, Finn Lovholt, Vadim Montellier, Alexandre Fournier, Erwan Raffin, Thomas Zwinger, Clea Denamiel, Boris Kaus, and Laetitia le Pourhiet

The second phase (2023-2026) of the Center of Excellence for Exascale in Solid Earth (ChEESE-2P), funded by HORIZON-EUROHPC-JU-2021-COE-01 under the Grant Agreement No 101093038, will prepare 11 European flagship codes from different geoscience domains (computational seismology, magnetohydrodynamics, physical volcanology, tsunamis, geodynamics, and glacier hazards). Codes will be optimised in terms of performance on different types of accelerators, scalability, containerisation, and continuous deployment and portability across tier-0/tier-1 European systems as well as on novel hardware architectures emerging from the EuroHPC Pilots (EuPEX/OpenSequana and EuPilot/RISC-V) by co-designing with mini-apps. Flagship codes and workflows will be combined to farm a new generation of 9 Pilot Demonstrators (PDs) and 15 related Simulation Cases (SCs) representing capability and capacity computational challenges selected based on their scientific importance, social relevance, or urgency. The SCs will produce relevant EOSC-enabled datasets and enable services on aspects of geohazards like urgent computing, early warning forecast, hazard assessment, or fostering an emergency access mode in EuroHPC systems for geohazardous events including access policy recommendations. Finally, ChEESE-2P will liaise, align, and synergise with other domain-specific European projects on digital twins and longer-term mission-like initiatives like Destination Earth.

How to cite: Folch, A., DelaPuente, J., Costa, A., Halldórson, B., Gracia, J., Lanucara, P., Bader, M., Gabriel, A.-A., Macías, J., Lovholt, F., Montellier, V., Fournier, A., Raffin, E., Zwinger, T., Denamiel, C., Kaus, B., and le Pourhiet, L.: The EuroHPC Center of Excellence for Exascale in Solid Earth, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5807, https://doi.org/10.5194/egusphere-egu23-5807, 2023.

EGU23-6768 | ECS | Orals | ESSI2.8

SarXarray: an Xarray extension for SLC SAR data processing 

Ou Ku, Francesco Nattino, Meiert Grootes, Pranav Chandramouli, and Freek van Leijen

Satellite-based Interferometric Synthetic Aperture Radar (InSAR) plays a significant role for numerous surface motion monitoring applications, e.g. civil-infrastructure stability, hydrocarbons extraction, etc. InSAR monitoring is based on a coregistered stack of Single Look Complex (SLC) SAR images. Due to the long temporal coverage, broad spatial coverage and high spatio-temporal resolution of an SLC SAR stack, handling it in an efficient way is a common challenge within the community. Aiming to meet this need, we present SarXarray: an open-source Xarray extension for SLC SAR stack processing. SarXarray provides a Python interface to read and write a coregistered stack of SLC SAR data, with basic SAR processing functions. It utilizes Xarray’s support on labeled multi-dimensional datasets to stress the space-time character of an SLC SAR stack. It also leverages Dask to perform lazy evaluation of the operations. SarXarray can be integrated to existing Python workflows in a flexible way. We provide a case study of creating a SAR Mean Reflectivity Map to demonstrate the functionality of SarXarray.

How to cite: Ku, O., Nattino, F., Grootes, M., Chandramouli, P., and van Leijen, F.: SarXarray: an Xarray extension for SLC SAR data processing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6768, https://doi.org/10.5194/egusphere-egu23-6768, 2023.

EGU23-6857 | ECS | Posters on site | ESSI2.8

Convergence of HPC, Big Data and Machine Learning for Earth System workflows 

Donatello Elia, Sonia Scardigno, Alessandro D'Anca, Gabriele Accarino, Jorge Ejarque, Francesco Immorlano, Daniele Peano, Enrico Scoccimarro, Rosa M. Badia, and Giovanni Aloisio

Typical end-to-end Earth System Modelling (ESM) workflows rely on different steps including data pre-processing, numerical simulation, output post-processing, as well as data analytics and visualization. The approaches currently available for implementing scientific workflows in the climate context do not properly integrate the entire set of components into a single workflow and in a transparent manner. The increasing usage of High Performance Data Analytics (HPDA) and Machine Learning (ML) in climate applications further exacerbate the issues. A more integrated approach would allow to support next-generation ESM and improve the workflow in terms of execution and energy consumption.

Moreover, a seamless integration of components for HPDA and ML into the ESM workflow will open the floor to novel applications and support larger scale pre- and post-processing. However, these components typically have different deployment requirements spanning from HPC (for ESM simulation) to Cloud computing (for HPDA and ML). It is paramount to provide scientists with solutions capable of hiding the technical details of the underlying infrastructure and improving workflow portability.

In the context of the eFlows4HPC project, we are exploring the use of innovative workflow solutions integrating approaches from HPC, HPDA and ML for supporting end-to-end ESM simulations and post-processing, with a focus on extreme events analysis (e.g., heat waves and tropical cyclones). In particular, the envisioned solution exploits PyCOMPSs for the management of parallel pipelines, task orchestration and synchronization, as well as PyOphidia for climate data analytics and ML frameworks (i.e., TensorFlow) for data-driven event detection models. This contribution presents the approaches being explored in the frame of the project to address the convergence of HPC, Big Data and ML into a single end-to-end ESM workflows.

How to cite: Elia, D., Scardigno, S., D'Anca, A., Accarino, G., Ejarque, J., Immorlano, F., Peano, D., Scoccimarro, E., Badia, R. M., and Aloisio, G.: Convergence of HPC, Big Data and Machine Learning for Earth System workflows, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6857, https://doi.org/10.5194/egusphere-egu23-6857, 2023.

EGU23-6960 | Orals | ESSI2.8

Remote Sensing Deployable Analysis environmenT 

Pranav Chandramouli, Francesco Nattino, Meiert Grootes, Ou Ku, Fakhereh Alidoost, and Yifat Dzigan

Remote-sensing (RS) and Earth observation (EO) data have become crucial in areas ranging from science to policy, with their use expanding beyond the ‘usual’ fields of geosciences to encompass ‘green’ life sciences, agriculture, and even social sciences. Within this context, the RS-DAT project has developed and made available a readily deployable framework enabling researchers to scale their analysis of EO and RS data on HPC systems and associated storage resources. Building on and expanding the established tool stack of the Pangeo Community, the framework integrates tools to access, retrieve, explore, and process geospatial data, addressing common needs identified in the EO domain. On the computing side RS-DAT leverages Jupyter (Python), which provides users a web-based interface to access (remote) computational resources, and Dask, which enables to scale analysis and workflows to large computing systems. Both Jupyter and Dask are well-established tools in the Pangeo community and can be deployed in several ways and on different infrastructures. RS-DAT provides an easy-to-use deployment framework for two targets: the generic case of SLURM-based HPC systems (for example, Dutch Supercomputer Snellius/Spider) which offer flexibility in computational resources; and the special case of an ansible-based cloud-computing infrastructure (Surf Research Cloud (SRC)) which is more straight-forward for the user but less flexible. Both these frameworks enable the easy scale-up of workflows, using HPCs, to access, manipulate and process large-scale datasets as commonly found in EO. On the data access and storage side RS-DAT integrates two python packages, STAC2dCache and dCacheFS, which were developed to facilitate data retrieval from online STAC catalogs (STAC2dCache) and its storage on the HPC system or local mass storage, specifically dCache.  This ensures efficient computation for large-scale analyses where data retrieval and handling can cause significant bottlenecks. User-defined input/output to Zarr file format is also supported within the framework. We present an application of the tools developed to the calculation of leaf-spring indices for North America using the Daymet dataset at a 1km resolution for 42 years (~940 GiB, completed in under 5 hours using 60 cores on the Dutch supercomputing system) and look forward to on-going work integrating both deployment targets in the case of the Dutch HPC ecosystem.

How to cite: Chandramouli, P., Nattino, F., Grootes, M., Ku, O., Alidoost, F., and Dzigan, Y.: Remote Sensing Deployable Analysis environmenT, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6960, https://doi.org/10.5194/egusphere-egu23-6960, 2023.

With the amount of high resolution earth observation data available it is not feasible anymore to do all analysis on local computers or even local cluster systems. To achieve high performance for out-of-memory datasets we develop the YAXArrays.jl package in the Julia programming language. YAXArrays.jl provides both an abstraction over chunked n-dimensional arrays with labelled axes and efficient multi-threaded and multi-process computation on these arrays.
In this contribution we would like to present the lessons we learned from scaling an analysis of high resolution Sentinel-1 time series
data. By bringing a Sentinel-1 change detection use case which has been performed on a small local area of interest to a whole region we test the ease and performance of distributed computing on the European Open Science Cloud (EOSC) in Julia.

How to cite: Gans, F. and Cremer, F.: Scaling up a Sentinel 1 change detection pipeline using the Julia programming language, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7825, https://doi.org/10.5194/egusphere-egu23-7825, 2023.

EGU23-8096 | ECS | Posters on site | ESSI2.8

Spatio-Temporal Asset Catalog (STAC) for in-situ data 

Justus Magin and Tina Odaka

In order to make use of a collection of datasets – for example, scenes from a SAR satellite – more efficient, it is important to be able to search for datasets relevant for a specific application. In particular, one might want to search for a specific period in time, for the spatial extent, or perform searches over multiple collections together.

For SAR data or data obtained from optical satellites, Spatio-Temporal Asset Catalogs (STAC) have become increasingly popular in the past few years. Defined as JSON and backed by databases with geospatial extensions, STAC servers (endpoints) have the advantage of being efficient, language-agnostic and following a standardized API.

Just like satellite scenes, in-situ data is growing in size very quickly and thus would benefit from being catalogued. However, the sequential nature of in-situ data and its sparse distribution in space makes it difficult to fit into STAC's standard model.

In the session, we present a experimental STAC extension that defines the most common properties of in-situ data as identified from ArgoFloat and  biologging data.

How to cite: Magin, J. and Odaka, T.: Spatio-Temporal Asset Catalog (STAC) for in-situ data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8096, https://doi.org/10.5194/egusphere-egu23-8096, 2023.

EGU23-8756 | Posters on site | ESSI2.8

Pangeo framework for training: experience with FOSS4G, the CLIVAR bootcamp and the eScience course 

Anne Fouilloux, Pier Lorenzo Marasco, Tina Odaka, Ruth Mottram, Paul Zieger, Michael Schulz, Alejandro Coca-Castro, Jean Iaquinta, and Guillaume Eynard Bontemps

The ever increasing number of scientific datasets made available by authoritative data providers (NASA, Copernicus, etc.) and provided by the scientific community opens new possibilities for advancing the state of the art in many areas of the natural sciences. As a result, researchers, innovators, companies and citizens need to acquire computational and data analysis skills to optimally exploit these datasets. Several educational programs dispense basic courses to students, and initiatives such as “The Carpentries” (https://carpentries.org/) complement this offering but also reach out to established researchers to fill the skill gap thereby empowering them to perform their own data analysis. However, most researchers find it challenging to go beyond these training sessions and face difficulties when trying to apply their newly acquired knowledge to their own research projects. To this regard, hackathons have proven to be an efficient way to support researchers in becoming competent practitioners but organising good hackathons is difficult and time consuming. In addition, the need for large amounts of computational and storage resources during the training and hackathons requires a flexible solution. Here, we propose an approach where researchers  work on realistic, large and complex data analysis problems similar to or directly part of  their research work. Researchers access an infrastructure deployed on the European Ocean Science Cloud (EOSC)  that supports intensive data analysis (large compute and storage resources). EOSC is a European Commission initiative for providing a federated and open multi-disciplinary environment where data, tools and services can be shared, published, found and re-used. We used jupyter book for delivering a collection of FAIR training materials for data analysis relying on Pangeo EOSC deployments as its primary computing platform. The training material (https://pangeo-data.github.io/foss4g-2022/intro.html, https://pangeo-data.github.io/clivar-2022/intro.html, https://pangeo-data.github.io/escience-2022/intro.html) is customised (different datasets with similar analysis) for different target communities and participants are taught the usage of Xarray, Dask and more generally how to efficiently access and analyse large online datasets. The training can be completed by group work where attendees can work on larger scale scientific datasets: the classroom is split into several groups. Each group works on different scientific questions and may use different datasets. Using the Pangeo (http://pangeo.io) ecosystem is not always new for all attendees but applying Xarray (http://xarray.pydata.org)  and Dask (https://www.dask.org/) on actual scientific “mini-projects” is often a showstopper for many researchers. With this approach, attendees have the opportunity to ask questions, collaborate with other researchers as well as Research Software Engineers, and apply Open Science practices without the burden of trying and failing alone. We find the involvement of scientific computing research engineers directly in the training is crucial for success of the hackathon approach. Feedback from attendees shows that it provides a solid foundation for big data geoscience and helps attendees to quickly become competent practitioners. It also gives infrastructure providers and EOSC useful feedback on the current and future needs of researchers for making their research FAIR and open. In this presentation, we will provide examples of achievements from attendees and present the feedback EOSC providers have received.

How to cite: Fouilloux, A., Marasco, P. L., Odaka, T., Mottram, R., Zieger, P., Schulz, M., Coca-Castro, A., Iaquinta, J., and Eynard Bontemps, G.: Pangeo framework for training: experience with FOSS4G, the CLIVAR bootcamp and the eScience course, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8756, https://doi.org/10.5194/egusphere-egu23-8756, 2023.

EGU23-9095 | Posters on site | ESSI2.8

Pangeo@EOSC: deployment of PANGEO ecosystem on the European Open Science Cloud 

Guillaume Eynard-Bontemps, Jean Iaquinta, Sebastian Luna-Valero, Miguel Caballer, Frederic Paul, Anne Fouilloux, Benjamin Ragan-Kelley, Pier Lorenzo Marasco, and Tina Odaka

Research projects heavily rely on the exchange and processing of data and in this context Pangeo (https://pangeo.io/), a world-wide community of scientists and developers, thrives to facilitate the deployment of ready to use and community-driven platforms for big data geoscience. The European Open Science Cloud (EOSC) is the main initiative in Europe for providing a federated and open multi-disciplinary environment where European researchers, innovators, companies and citizens can share, publish, find and re-use data, tools and services for research, innovation and educational purposes. While a number of services based on Jupyter Notebooks were already available, no public Pangeo deployments providing fast access to large amounts of data and compute resources were accessible on EOSC. Most existing cloud-based Pangeo deployments are USA-based, and members of the Pangeo community in Europe did not have a shared platform where scientists or technologists could exchange know-how. Pangeo teamed up with two EOSC projects, namely EGI-ACE (https://www.egi.eu/project/egi-ace/) and C-SCALE (https://c-scale.eu/) to demonstrate how to deploy and use Pangeo on EOSC and emphasise the benefits for the European community. 

The Pangeo Europe Community together with EGI deployed a DaskHub, composed of Dask Gateway (https://gateway.dask.org/) and JupyterHub (https://jupyter.org/hub), with Kubernetes cluster backend on EOSC using the infrastructure of the EGI Federation (https://www.egi.eu/egi-federation/). The Pangeo EOSC JupyterHub deployment makes use of 1) the EGI Check-In to enable user registration and thereby authenticated and authorised access to the Pangeo JupyterHub portal and to the underlying distributed compute infrastructure; and 2) the EGI Cloud Compute and the cloud-based EGI Online Storage to distribute the computational tasks to a scalable compute platform and to store intermediate results produced by the user jobs. 

To facilitate future Pangeo deployments on top of a wide range of cloud providers (AWS, Google Cloud, Microsoft Azure, EGI Cloud Computing, OpenNebula, OpenStack, and more), the Pangeo EOSC JupyterHub deployment is now possible through the Infrastructure Manager (IM) Dashboard (https://im.egi.eu/im-dashboard/login). All the computing and storage resources are currently supplied by CESNET (https://www.cesnet.cz/?lang=en) in the frame of EGI-ACE project (https://im.egi.eu/). Several deployments have been made to serve the geoscience community, both for teaching and for research work. To date, more than 100 researchers have been trained on Pangeo@EOSC deployments and more are expected to join, in particular with easy access to large amounts of Copernicus data through a recent collaboration established with the C-SCALE project. In this presentation, we will provide details on the different deployments, how to get access to JupyterHub deployments and more generally how to contribute to Pangeo@EOSC.



How to cite: Eynard-Bontemps, G., Iaquinta, J., Luna-Valero, S., Caballer, M., Paul, F., Fouilloux, A., Ragan-Kelley, B., Marasco, P. L., and Odaka, T.: Pangeo@EOSC: deployment of PANGEO ecosystem on the European Open Science Cloud, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9095, https://doi.org/10.5194/egusphere-egu23-9095, 2023.

EGU23-10697 | Orals | ESSI2.8 | Highlight

The Joint Effort for Data Assimilation Integration (JEDI): A unified data assimilation framework for Earth system prediction supported by NOAA, NASA, U.S. Navy, U.S. Air Force, and UK Met Office 

Dom Heinzeller, Maryam Abdi-Oskouei, Stephen Herbener, Eric Lingerfelt, Yannick Trémolet, and Tom Auligné

The Joint Effort for Data assimilation Integration (JEDI), is an innovative data assimilation system for Earth system prediction, spearheaded by the Joint Center for Satellite Data Assimilation (JCSDA) and slated for implementation in major operational modeling systems across the globe in the coming years. Funded as an inter-agency development by NOAA, NASA, the U.S. Navy and Air Force, and with contributions from the UK Met Office, JEDI must operate on a wide range of computing platforms. The recent move towards cloud computing systems puts portability, adaptability and performance across systems, from dedicated High Performance Computing systems to commercial clouds and workstations, in the critical path for the success of JEDI.

JEDI is a highly complex application that relies on a large number of third-party software packages to build and run. These packages can include I/O libraries, workflow engines, Python modules for data manipulation and plotting, several ECMWF libraries for complex arithmetics and grid manipulations, and forecast models such as the Unified Forecast System (UFS), the Goddard Earth Observing System (GEOS), the Modular Ocean Model (MOM6), the Model for Prediction across Scales (MPAS), the Navy Environmental Prediction sysTem Utilizing the NUMA corE (NEPTUNE), and the Met Office Unified Model (UM).

With more than 100 contributors and rapid code development it is critical to perform thorough automated testing, from basic unit tests to comprehensive end-to-end-tests. This presentation summarizes recent efforts to leverage cloud computing environments for research, development, and near real-time applications of JEDI, as well as for developing a Continuous Integration/Continuous Delivery (CI/CD) pipeline. These efforts rest on a newly developed software stack called spack-stack, a joint effort of JCSDA, the NOAA Environmental Modeling Center (EMC) and the U.S. Earth Prediction Innovation Center (EPIC). Automatic testing in JEDI is implemented with modern software development tools such as GitHub, Docker containers, various Amazon Web Services (AWS), and CodeCov for testing and evaluation of code performance. End-to-end testing is realized in JCSDA’s newly developed Skylab Earth system data assimilation application, which combines JEDI with the Research Repository for Data and Diagnostics (R2D2) and the Experiments and Workflow Orchestration Kit (EWOK), and which leverages the AWS Elastic Compute Cloud (EC2) for testing, research, development and production.

How to cite: Heinzeller, D., Abdi-Oskouei, M., Herbener, S., Lingerfelt, E., Trémolet, Y., and Auligné, T.: The Joint Effort for Data Assimilation Integration (JEDI): A unified data assimilation framework for Earth system prediction supported by NOAA, NASA, U.S. Navy, U.S. Air Force, and UK Met Office, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10697, https://doi.org/10.5194/egusphere-egu23-10697, 2023.

EGU23-11117 | Orals | ESSI2.8

Modeling the Earth System on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON 

Olaf Stein, Abhiraj Bishnoi, Luis Kornblueh, Lars Hoffmann, Norbert Eicker, Estela Suarez, and Catrin I. Meyer

Significant progress has been made in recent years to develop km-scale versions of global Earth System Models (ESM), combining the chance of replacing uncertain model parameterizations by direct treatment and the improved representation of orographic and land surface features (Schär et al., 2020, Hohenegger et al., 2022). However, adapting climate codes to new hardware and at the same time keeping the performance portability, still remains a major issue. Given the long development cycles, the various maturity of ESM modules and their large code bases, it is not expected that all code parts can be brought to the same level of exascale readiness in the near future. Instead, short term model adaptation strategies need to focus on software abilities as well as hardware availability. Moreover, energy use efficiency is of growing importance on both sides, supercomputer providers and scientific projects employing climate simulations.

Here, we present results from first simulations of the coupled atmosphere-ocean modelling system ICON-v2.6.6-rc on the supercomputing system JUWELS at the Jülich Supercomputing Centre (JSC) with a global resolution of 5 km, using significant parts of the HPC system. While the atmosphere part of ICON (ICON-A) is capable of running on GPUs, model I/O currently performs better on a CPU cluster and the ocean module (ICON-O) has not been ported to modern accelerators yet. Thus, we make use of the modular supercomputing architecture (MSA) of JUWELS and its novel batch job options for the coupled ICON model with ICON-A running on the NVIDIA A100 GPUs of JUWELS Booster, while ICON-O and the model I/O are running simultaneously on the CPUs of the JUWELS Cluster partition. As expected, ICON performance is limited by ICON-A. Thus we chose the performance-optimal Booster-node configuration for ICON-A considering also memory requirements (84 nodes) and adapted ICON-O configuration to achieve minimum waiting times for simultaneous time step execution and data exchange (63 cluster nodes).  We compared runtime and energy efficiency to cluster-only simulations (on up to 760 cluster nodes) and found only small improvements in runtime for the MSA case, but energy consumption is already reduced by 26% without further improvements in vector length applied with ICON. When switching to even higher ICON resolutions, cluster-only simulations are not fitting to most of current HPC systems and upcoming exascale systems will rely to a large extent on GPU acceleration. Thus exploiting MSA capabilities is an important step towards performance portable and energy efficient use of km-scale climate models.

References:

Hohenegger et al., ICON-Sapphire: simulating the components of the Earth System and their interactions at kilometer and subkilometer scales, https://doi.org/10.5194/gmd-2022-171, in review, 2022.

Schär et al., Kilometer-Scale Climate Models: Prospects and Challenges, https://doi.org/10.1175/BAMS-D-18-0167.1, 2020.

 

How to cite: Stein, O., Bishnoi, A., Kornblueh, L., Hoffmann, L., Eicker, N., Suarez, E., and Meyer, C. I.: Modeling the Earth System on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11117, https://doi.org/10.5194/egusphere-egu23-11117, 2023.

EGU23-12539 | Orals | ESSI2.8

European Weather Cloud: A community cloud tailored for big Earth modelling and EO data processing 

Roberto Cuccu, Vasileios Baousis, Umberto Modigliani, Charalampos Kominos, Xavier Abellan, and Roope Tervo

The European Centre for Medium-Range Weather Forecasts (ECMWF) together with the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) have worked together to offer to their Member States a new paradigm to access and consume weather data and services. The “European Weather Cloud-(EWC)” (https://www.europeanweather.cloud/), concluded its pilot phase and is expected to become operational during the first months of 2023.

This initiative aims to offer a community cloud infrastructure on which Member and Co‐operating States of both organizations can create on demand virtual compute (including GPUs) and storage resources to gain easy and high throughput access to the ECMWF’s Numerical Weather Predication (NWP) and EUMETSAT’s satellite data in a timely and configurable fashion. Moreover, one of the main goals is to involve more National Meteorological Services to jointly form a federation of clouds/data offered from their Member States, for the maximum benefit of the European Meteorological Infrastructure (EMI). During the pilot phase of the project, both organizations have jointly hosted user and technical workshops to actively engage with the meteorological community and align the evolution of the EWC to reflect and satisfy their operational goals and needs.

The EWC, in its pilot phase hosted several use cases, mostly aimed at users in the developers’ own organisations. These broad categories of these cases are:

  • Web services to explore hosted datasets
  • Data processing applications
  • Platforms to support the training of machine learning models on archive datasets
  • Workshops and training courses (e.g., ICON model training, ECMWF training etc)
  • Research in collaboration with external partners
  • World Meteorological Organization (WMO) support with pilots and PoC.

Some examples of the use cases currently developed at the EWC are:

  • The German weather service DWD, which is already feeding maps generated by a server it deployed on the cloud into its public GeoPortal service.
  • EUMETSAT and ECMWF joint use case assesses bias correction schemes for the assimilation of radiance data based on several satellite data time series
  • the Royal Netherlands Meteorological Institute (KNMI) hosts a climate explorer web application based on KNMI climate explorer data and ECMWF weather and climate reanalyses
  • The Royal Meteorological Institute of Belgium prepares ECMWF forecast data for use in a local atmospheric dispersion model.
  • NordSat, a collaboration of northern European countries which is developing and testing imagery generation tools in preparation for the Meteosat Third Generation (MTG) satellite products.
  • UK Met Office with the DataProximateCompute use case, which distributes compute workload close to data, with the automatic creation and disposal of Dask clusters, as well as the data plane VPN network, on demand and in heterogeneous cloud environments.

In this presentation, the status of the project, the offered services and how these are accessed by the end users along with examples of the existing use cases will be analysed. The plans, next steps for the evolution of the EWC and its relationship with other projects and initiatives (like DestinE) will conclude the presentation.

How to cite: Cuccu, R., Baousis, V., Modigliani, U., Kominos, C., Abellan, X., and Tervo, R.: European Weather Cloud: A community cloud tailored for big Earth modelling and EO data processing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12539, https://doi.org/10.5194/egusphere-egu23-12539, 2023.

EGU23-12785 | Orals | ESSI2.8

A Scalable Near Line Storage Solution for Very Big Data 

Neil Massey, Jack Leland, and Bryan Lawrence

Managing huge volumes of data is a problem now, and will only become worse with the advent of exascale computing and next generation observational systems. An important recognition is that data needs to be more easily migrated between storage tiers. Here we present a new solution, the Near-Line Data store (NLDS), for managing data migration between user facing storage systems and tape by using an object storage cache.  NLDS builds on lessons learned from previous experience developing the ESIWACE funded Joint Data Migration App (JDMA) and deploying it at the Centre for Environmental Data Analysis (CEDA). 
 
CEDA currently has over 50PB of data stored on a range of disk based storage systems.  These systems are chosen on cost, power usage and accessibility via a network, and include three different types of POSIX disk and object storage. Tens of PB of additional data are also stored on tape. Each of these systems has different workflows, interfaces and latencies, causing difficulties for users.  

NLDS, developed with ESIWACE2 and other funding, is a multi-tiered storage solution using object storage as a front end to a tape library.  Users interact with NLDS via a HTTP API, with a Python library and command-line client provided to support both programmatic and interactive use.  Files transferred to NLDS are first written to the object storage, and a backup is made to tape.  When the object storage is approaching capacity, a set of policies is interrogated to determine which files will be removed from it.  Upon retrieving a file, NLDS may have to first transfer the file from tape to the object storage, if it has been deleted by the policies.  This implements a multi-tier of hot (disk), warm (object storage) and cold (tape) storage via a single interface. While systems like this are not novel, NLDS is open source, designed for ease of redeployment elsewhere, and for use from both local storage and remote sites. 

NLDS is based around a microservice architecture, with a message exchange brokering communication between the microservices, the HTTP API and the storage solutions.  The system is deployed via Kubernetes, with each microservice in its own Docker container, allowing the number of services to be scaled up or down, depending on the current load of NLDS.  This provides a scalable, power efficient system while ensuring that no messages between microservices are lost.  OAuth is used to authenticate and authorise users via a pluggable authentication layer. The use of object storage as the front end to the tape allows both local and remote cloud-based services to access the data, via a URL, so long as the user has the required credentials. 

NLDS is a a scalable solution to storing very large data for many users, with a user-friendly front end that is easily accessed via cloud computing. This talk will detail the architecture and discuss how the design meets the identified use cases.

How to cite: Massey, N., Leland, J., and Lawrence, B.: A Scalable Near Line Storage Solution for Very Big Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12785, https://doi.org/10.5194/egusphere-egu23-12785, 2023.

EGU23-12851 | Orals | ESSI2.8

From the Copernicus satellite data to an environmentally aware field decision 

Fabien Castel and Emma Rizzi

Tackling complex environmental issues requires accessing and processing a wide range of voluminous data. The Copernicus spatial data is a very complete and valuable source for many earth science domains, in particular thanks to its Core Services (Land, Atmosphere, Marine…). For almost five years now, Copernicus DIAS platforms have provided broad access to the core services products through the cloud. Among these platforms, the Wekeo platform operated by EUMETSAT, Mercator Ocean, ECMWF and EEA provides wider access to Copernicus Core Service data.

However, Copernicus data needs an additional layer of processing and preparation to be presented and understood by the general public and decision makers. Murmuration has developed data processing pipelines to produce environmental indicators from Copernicus data constituting powerful tools to put environmental issues at the centre of decision-making processes.

Throughout its use, limitations on the DIAS platforms were observed. Firstly, the cloud service offerings are basic in comparison to the market leaders (such as AWS and GCP). In particular, there is no built-in solution for automating and managing data processing pipelines, which must be set up at the user's expense. Secondly, the cost of resources is higher than market price. Limiting the activities on DIAS to edge data processing and relying on a cheaper offering for applications not requiring the direct access to raw Copernicus data is a cost effective choice.  FInally, the performance and reliability requirements to access the data can sometimes not be met when relying on a single DIAS platform. Implementing a multi-DIAS approach ensures backup data sources. This raises the question of the automation and orchestration of such a multi-cloud system.

We propose an approach combining the wide data offer of the DIAS platforms, the automation features provided by the Prefect platform and the usage of efficient cloud technologies to build a repository of environmental indicators. Prefect is a hybrid orchestration platform dedicated to automation of data processing flows. It does not host any data processing flow itself and rather connects in a cloud-agnostic way to any cloud environment, where periodic and triggered flow executions can be scheduled. Prefect centrally controls flows that run on different cloud environments through a single platform.

Technologies leveraged to build the system allow to efficiently produce and disseminate the environmental indicators: firstly, containerisation and clustering (using Docker and Kubernetes) to manage processing resources; secondly object storage combined with cloud native access (Zarr data format); and finally, the Python scientific software stack (including pandas, scikit-learn, etc.) complemented by the powerful Xarray library. Data processing pipelines ensure a path from the NetCDF Copernicus Core Services products to cloud-native Zarr products. The Zarr format allows windowed read/write operations, avoiding unnecessary data transfers. This efficient data access allows plugging into the data repository fast data dissemination services following well-established OGC standards and feeding interactive dashboards for decision makers. The cycle is complete, from the Copernicus satellite data to an environmentally aware field decision.

How to cite: Castel, F. and Rizzi, E.: From the Copernicus satellite data to an environmentally aware field decision, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12851, https://doi.org/10.5194/egusphere-egu23-12851, 2023.

EGU23-13768 | ECS | Posters on site | ESSI2.8

FAIR Notebooks: opportunities and challenges for the geoscience community 

Alejandro Coca-Castro, Anne Fouilloux, J. Scott Hosking, and Environmental Data Science Book community

Making assets in scientific research Findable, Accessible, Interoperable and Reusable (FAIR) is still overwhelming for many scientists. When considered as an afterthought, FAIR research is indeed challenging, and we argue that its implementation is by far much easier when considered at an early stage and focusing on improving the researchers' day to day work practices. One key aspect is to bundle all the research artefacts in a FAIR Research Object (RO) using RoHub (https://reliance.rohub.org/), a Research Object management platform that enables researchers to collaboratively manage, share and preserve their research work (data, software, workflows, models, presentations, videos, articles, etc.). RoHub implements the full RO model and paradigm: resources associated to a particular research work are aggregated into a single FAIR digital object, and metadata relevant for understanding and interpreting the content is represented as semantic metadata that are user and machine readable. This approach provides the technical basis for implementing FAIR executable notebooks: the data and the computational environment can be “linked” to one or several FAIR notebooks that can then be executed via EGI Binder Service with scalable compute and storage capabilities. However, the need for defining clear practises for writing and publishing FAIR notebooks that can be reused to build upon new research has quickly arised. This is where a community of practice is required. The Environmental Data Science Book (or EDS Book) is a pan-european community-driven resource hosted on GitHub and powered by Jupyter Book. EDS Book provides practical guidelines and templates that help to translate research outputs into curated, interactive, shareable and reproducible executable notebooks. The quality of the FAIR notebooks is ensured by a collaborative and transparent reviewing process supported by GitHub related technologies. This approach provides immediate benefits for those who adopt it and can feed fruitful discussions to better define a reward system that would benefit Science and scientific communities. All the resources needed for understanding and executing the notebook are gathered into an executable Research Object in RoHub. To date, the community has successfully published ten FAIR notebooks covering a wide range of topics in environmental data science. The notebooks consume open-source python libraries e.g. intake, iris, xarray, hvplot for fetching, processing and interactively visualising environmental research.  While these notebooks are currently python-based, EDS Book supports other programming languages such as R and Julia, and we are aiming at engaging with computational notebooks communities alike towards improving the research practices in environmental science.

How to cite: Coca-Castro, A., Fouilloux, A., Hosking, J. S., and community, E. D. S. B.: FAIR Notebooks: opportunities and challenges for the geoscience community, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13768, https://doi.org/10.5194/egusphere-egu23-13768, 2023.

EGU23-14507 | Orals | ESSI2.8

geokube: A Python Package for Data Analysis and Visualization in Geoscience 

Marco Mancini, Mirko Stojiljkovic, and Jakub Walczak

geokube is a Python package for data analysis and visualisation in geoscience that  provides high level abstractions in terms of both Data Model, inspired by Climate Forecast and Unidata Common Data Models, and Application Programming Interface (API), inspired by xarray. Key features of geokube are the capabilities to: (i) perform georeferenced axis-based indexing on data structures and specialised geospatial operations according to different types of geo scientific datasets like structured grids, point observations, profiles etc. (e.g. extracting a bounding box or a multipolygon of variable values defined on a rotated pole grid), (ii) perform operations on the variables that are either instantaneous or defined over intervals, (iii) convert to/from xarray data structures and to read/write CF-compliant netCDF datasets.

How to cite: Mancini, M., Stojiljkovic, M., and Walczak, J.: geokube: A Python Package for Data Analysis and Visualization in Geoscience, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14507, https://doi.org/10.5194/egusphere-egu23-14507, 2023.

EGU23-14515 | ECS | Orals | ESSI2.8

Intaking DKRZ ESM data collections 

Fabian Wachsmann

In this showcase, we present to you how Intake and its plugin Intake-ESM are utilized at DKRZ to provide highly FAIR data collections from different projects, stored on different types of storages in different formats.

The Intake Plugin Intake-ESM allows users to not only find the data of interest, but also load them as analysis-ready-like Xarray datasets. We utilize this tool to provide users with access to many available data collections at our institution from only one single access point, the main DKRZ intake catalog at www.dkrz.de/s/intake. The functionality of this package works independently of data standards and formats and therefore enables full metadata-driven data access including data processing. Intake-esm catalogs increase the FAIRness of the data collections in all aspects but especially in terms of Accessibility and Interoperability.

Started with a collection of DKRZ’s CMIP6 Data Pool, DKRZ now hosts catalogs for more than 10PB of data on different local storages. The Intake-ESM package has been well integrated into ESM data provisioning workflows.

  • Early sharing and making accessible: The co-developed inhouse ICON model generates an intake-esm catalog on each run.
  • Uptake from other technologies: E.g., intake-esm catalogs serve as templates for the more advanced DKRZ STAC Catalogs. 
  • Making accessible all storage types: tools used for writing data to the local institutional cloud allow users to create Intake-ESM catalogs for the written data.
  • Data archiving: Catalogs for projects in the archive can be created from its metadata database.

For future activities, we plan to make use of new functionalities like the support for kerchunked data and the derived variable registry.

The DKRZ data management team develops and maintains local services around intake-esm for a positive user experience. In this showcase, we will present excerpts of seminars, workflows and integrations.

How to cite: Wachsmann, F.: Intaking DKRZ ESM data collections, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14515, https://doi.org/10.5194/egusphere-egu23-14515, 2023.

EGU23-14547 | Orals | ESSI2.8

PANGEO multidisciplinary test case for Earth and Environment Big data analysis in FAIR-EASE Infra-EOSC project 

Marine Vernet, Erwan Bodere, Jérôme Detoc, Christelle Pierkot, Alessandro Rizzo, and Thierry Carval

Earth observation and modelling is a major challenge for research and a necessity for environmental and socio-economic applications. It requires voluminous and heterogeneous data from distributed and domain-dependent data sources, managed separately by various national and European infrastructures.

In a context of unprecedented data wealth and growth, new challenges emerge to enable inter-comparison, inter-calibration and comprehensive studies and uses of earth system and environmental data.

To this end, the FAIR-EASE project aims to provide integrated and interoperable services through the European Open Science Cloud to facilitate the discovery, access and analysis of large volumes of heterogeneous data from distributed sources and from different domains and disciplines of Earth system science.

This presentation will explain how the PANGEO stack will be used within FAIR EASE to improve data access, interpolation and analysis, but will also explore its integration with existing services (e.g. Galaxy) and underlying IT infrastructure to serve multidisciplinary research uses.

How to cite: Vernet, M., Bodere, E., Detoc, J., Pierkot, C., Rizzo, A., and Carval, T.: PANGEO multidisciplinary test case for Earth and Environment Big data analysis in FAIR-EASE Infra-EOSC project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14547, https://doi.org/10.5194/egusphere-egu23-14547, 2023.

Observational meteorological data is central to understanding atmospheric processes, and is thus a key requirement for the calibration and validation of atmospheric and numerical weather prediction models. While recent decades have seen the development of notorious platforms to make satellite data easily accessible, observational meteorological data mostly remains scattered through the sites of regional and national meteorological service, each potentially offering different magnitudes, temporal coverage and data formats. 

In order to overcome these shortcomings, we propose meteostations-geopy, a Pythonic library to access data from meteorological stations. The central objective is to provide a common interface to retrieve observational meteorological data, therefore reducing the amount of time required to process and wrangle the data. The library interacts with APIs from different weather services, handling authentication if needed and transforming the requested information into geopandas data frames of geolocated and timestamped observations that are homogeneously structured independently of the provider. 

The project is currently in an early development stage with support for two providers only. Current and future work is organized in three interrelated main axes, namely integration of further providers, implementation of native support of distributed data structures and organization of the library into the intake technical structure with drivers, catalogs, metadata sharing and plugin packages that are provider specific.

How to cite: Bosch, M.: meteostations-geopy: a Pythonic interface to access data from meteorological stations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14774, https://doi.org/10.5194/egusphere-egu23-14774, 2023.

EGU23-15964 | ECS | Orals | ESSI2.8

A novel data ecosystem for coastal analyses 

Floris Calkoen, Fedor Baart, Etiënne Kras, and Arjen Luijendijk

The coastal community widely anticipates that in the next years data-driven studies are going to make essential contributions to bringing about long-term coastal adaptation and mitigation strategies at continental scale. This view is also supported by CoCliCo, a Horizon 2020 project, where coastal data form the fundamental building block for an open-web portal that aims to improve decision making on coastal risk management and adaptation. The promise of data is likely triggered by several coastal analyses that showed how the coastal zone can be be monitored at unprecedented spatial scales using geospatial cloud platforms . However, we note that when analyses become more complex, i.e., require specific algorithms, pre- and post-processing or include data that are not hosted by the cloud provider, the cloud-native processing workflows are often broken, which makes analyses at continental scale impractical.

We believe that the next generation of data-driven coastal models that target continental scales can only be built when: 1) processing workflows are scalable; 2) computations are run in proximity to the data; 3) data are available in cloud-optimized formats; 4) and, data are described following standardized metadata specifications. In this study, we introduce these practices to the coastal research community by showcasing the advantages of cloud-native workflows by two case studies.

In the first example we map building footprints in areas prone to coastal flooding and estimate the assets at risk. For this analysis we chunk a coastal flood-risk map into several tiles and incorporate those into a coastal SpatioTemporal Asset Catalog (STAC). The second example benchmarks instantaneous shoreline mapping using cloud-native workflows against conventional methods. With data-proximate computing, processing time is reduced from the order of hours to seconds per shoreline km, which means that a highly-specialized coastal mapping expedition can be upscaled from regional to global level.

The analyses mostly rely on "core-packages" from the Pangeo project, with some additional support for scalable geospatial data analysis and cloud I/O, although they can essentially be run on a standard Python Planetary Computer instance. We publish our code, including self-explanatory Juypter notebooks, at https://github.com/floriscalkoen/egu2023.

To conclude, we foresee that in next years several coastal data products are going to be published, of which some may be considered "big data". To incorporate these data products into the next generation of coastal models, it is urgently required to agree upon protocols for coastal data stewardship. With this study we do not only want to show the advantages of scalable coastal data analysis; we mostly want to encourage the coastal research community to adopt FAIR data management principles and workflows in an era of exponential data growth.

How to cite: Calkoen, F., Baart, F., Kras, E., and Luijendijk, A.: A novel data ecosystem for coastal analyses, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15964, https://doi.org/10.5194/egusphere-egu23-15964, 2023.

EGU23-16117 | ECS | Orals | ESSI2.8

Virtual aggregations to improve scientific ETL and data analysis for datasets from the Earth System Grid Federation 

Ezequiel Cimadevilla, Maialen Iturbide, and Antonio S. Cofiño

The ESGF Virtual Aggregation (EVA) is a new data workflow approach that aims to advance the sharing and reuse of scientific climate data stored in the Earth System Grid Federation (ESGF). The ESGF is a global infrastructure and network of internationally distributed research centers that together work as a federated data archive, supporting the distribution of global climate model simulations of the past, current and future climate. The ESGF provides modeling groups with nodes for publishing and archiving their model outputs to make them accessible to the climate community at any time. The standardization of the model output in a specified format, and the collection, archival and access of the model output through the ESGF data replication centers have facilitated multi-model analyses. Thus, ESGF has been established as the most relevant distributed data archive for climate data, hosting the data for international projects such as CMIP and CORDEX. As of 2022 it includes more than 30 PB of data distributed across research institutes all around the globe and it is the reference archive for Assessment Reports (AR) on Climate Change produced by the Intergovernmental Panel on Climate Change (IPCC). However, explosive data growth has confronted the climate community with a scientific scalability issue. Conceived as a distributed data store, the ESGF infrastructure is designed to keep file sizes manageable for both sysadmins and end users. However, use cases in scientific research often involve calculations on datasets spanning multiple variables, over the whole time period and multiple model ensembles. In this sense, the ESGF Virtual Aggregation extends the federation capabilities, beyond file search and download, by providing out of the box remote climate data analysis capabilities over data analysis ready, virtually aggregated, climate datasets, on top of the existing software stack of the federation. In this work we show an analysis that serves as a test case for the viability of the data workflow and provides the basis for discussions on the future of the ESGF infrastructure, contributing to the debate on the set of reliable core services upon which the federation should be built.

Acknowledgements

This work it’s been developed under support from IS-ENES3 which is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824084.

This work it’s been developed under support from CORDyS (PID2020-116595RB-I00) funded by MCIN/AEI/10.13039/501100011033.

How to cite: Cimadevilla, E., Iturbide, M., and Cofiño, A. S.: Virtual aggregations to improve scientific ETL and data analysis for datasets from the Earth System Grid Federation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16117, https://doi.org/10.5194/egusphere-egu23-16117, 2023.

EGU23-17029 | Orals | ESSI2.8

Establishing a Geospatial Discovery Network with efficient discovery and modeling services in multi-cloud environments 

Campbell Watson, Hendrik Hamann, Kommy Weldemariam, Thomas Brunschwiler, Blair Edwards, Anne Jones, and Johannes Schmude

The ballooning volume and complexity of geospatial data is one of the main inhibitors for advancements in climate & sustainability research. Oftentimes, researchers need to create bespoke and time-consuming workflows to harmonize datasets, build/deploy AI and simulation models, and perform statistical analysis. It is increasingly evident that these workflows and the underlying infrastructure are failing to scale and exploit the massive amounts of data (Peta and Exa-scale) which reside across multiple data centers and continents. While there have been attempts to consolidate relevant geospatial data and tooling into single cloud infrastructures, we argue that the future of climate & sustainability research relies on networked/federated systems. Here we present recent progress towards multi-cloud technologies that can scale federated geospatial discovery and modeling services across a network of nodes. We demonstrate how the system architecture and associated tooling can simplify the discovery and modeling process in multi-cloud environments via examples of federated analytics for AI-based flood detection and efficient data dissemination inspired by AI foundation models.

How to cite: Watson, C., Hamann, H., Weldemariam, K., Brunschwiler, T., Edwards, B., Jones, A., and Schmude, J.: Establishing a Geospatial Discovery Network with efficient discovery and modeling services in multi-cloud environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17029, https://doi.org/10.5194/egusphere-egu23-17029, 2023.

EGU23-17494 | Orals | ESSI2.8

Enabling simple access to a data lake both from HPC and Cloud using Kerchunk and Intake 

Thierry Carval, Erwan Bodere, Julien Meillon, Mathiew Woillez, Jean Francois Le Roux, Justus Magin, and Tina Odaka

We are experimenting with hybrid access from Cloud and HPC environments using the Pangeo platform to make use of a data lake in an HPC infrastructure “DATARMOR”.  DATARMOR is an HPC infrastructure hosting ODATIS services (https://www.odatis-ocean.fr) situated at “Pôle de Calcul et de Données pour la Mer” in IFREMER. Its parallel file system has a disk space dedicated for shared data, called “dataref”.  Users of DATARMOR can access these data, and some of those data are cataloged by sextant service (https://sextant.ifremer.fr/Ressources/Liste-des-catalogues-thematiques/Datarmor-Donnees-de-reference ) and is open and accessible from the internet, without duplicating the data. 

In the cloud environment, the ability to access files in a parallel manner is essential for improving the speed of calculations. The Zarr format (https://zarr.readthedocs.io) enables parallel access to data sets, as it consists of numerous chunked “object data” files and some “metadata” files. Although it enables multiple data access, it is simple to use since all the collections of data stored in a Zarr format are accessible through one access point.  

For HPC centers, the numerous “object data” files create a lot of metadata on parallel file systems, slowing the data access time. Recent progress on development of Kerchunk (https://fsspec.github.io/kerchunk/), which recognize the chunks in a file (e.g. NetCDF / HDF5) as a Zarr chunk and its capability to recognize a series of files as one Zarr file, is solving these technical difficulties in our PANGEO use cases at DATARMOR. Thanks to Kerchunk and Intake (https://intake.readthedocs.io/) it is now possible to use different sets of data stored in DATARMOR in an efficient and simple manner.    

We are further experimenting with this workflow using the same use cases on the PANGEO-EOSC cloud.   We make use of the same data stored at the data lake in DATARMOR, but based on Kerchunk and Intake catalog through ODATIS access, without duplicating the source data. In the presentation we will share our recent experiences from these experiments. 

How to cite: Carval, T., Bodere, E., Meillon, J., Woillez, M., Le Roux, J. F., Magin, J., and Odaka, T.: Enabling simple access to a data lake both from HPC and Cloud using Kerchunk and Intake, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17494, https://doi.org/10.5194/egusphere-egu23-17494, 2023.

EGU23-515 | ECS | Posters on site | HS1.2.1

Estimating sheet flow velocities using quinine as a fluorescent tracer in low luminosity conditions: laboratory and field experiments 

Soheil Zehsaz, João L. M. P. de Lima, M. Isabel P. de Lima, Jorge M. G. P. Isidoro, and Ricardo Martins

This study presents a technique based on the use of quinine as a fluorescent tracer, to estimate sheet flow velocities over various surface coverings (e.g., bare; mulched; vegetated; paved) in low luminosity conditions (e.g., night; twilight; shielded environments). Quinine glows when exposed to UVA light and in the concentrations used is not harmful to the environment. Experimental work was conducted for studying sheet flows in the i) laboratory (using a soil flume), over bare and mulched surfaces, and ii) field, over vegetated and paved surfaces. Flow velocities were estimated based on the injection of a quinine solution into the water flow.  In these experiments, dye and thermal tracer techniques were used as a benchmark for assessing the performance of the quinine tracer. Optical and infrared cameras were used to record the movement of the tracers’ plumes in the flow. The surface velocity of the flow was estimated by tracking the tracers’ plumes leading-edge and calculating their travel distance over a certain time lapse. Overall, the visibility of the quinine tracer was better in comparison to the dye tracer. However, under some circumstances, lower than the visibility of the thermal tracer. Nonetheless, the results show that all three tracers yielded similar estimations of the flow velocities. Therefore, when exposed to UVA light the quinine tracer can be useful to estimate sheet flow velocities over a wide variety of soil and urban surfaces in low luminosity conditions. Despite some inherent limitations of this technique (e.g., invisible under bright light conditions or heavy mulched/vegetated cover; need of a UVA lamp), its main advantage is the high visibility of the quinine fluorescent tracer under UVA light for fade light conditions (e.g., night; twilight; shielded environments such as close conduits), which creates new opportunities for tracer-based surface flow velocity measurements in surface hydrology studies.

How to cite: Zehsaz, S., de Lima, J. L. M. P., de Lima, M. I. P., Isidoro, J. M. G. P., and Martins, R.: Estimating sheet flow velocities using quinine as a fluorescent tracer in low luminosity conditions: laboratory and field experiments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-515, https://doi.org/10.5194/egusphere-egu23-515, 2023.

EGU23-649 | ECS | Posters on site | HS1.2.1

Near Real-Time Depth Change Monitoring on Inland Water Bodies Using Sentinel-1 and Dynamic World Data 

Utku Berkalp Ünalan, Onur Yüzügüllü, and Ayşegül Aksoy

Monitoring the depth changes in lakes is crucial to understanding hydrological dynamics and water quality changes. In developed countries, the authorities monitor the lake depths regularly; however, it might be different in developing and underdeveloped countries. In this study, we aim to develop a near-real-time SAR-based depth change monitoring system for lakes by focusing on shoreline pixels. For this purpose, we developed a framework using the Sentinel-1 GRD and Sentinel-2 Dynamic World land cover datasets available on the Google Earth Engine. Sentinel-1 data provides us with the necessary temporal resolution for frequent monitoring. For the initial development phase, we consider five ground monitoring stations in Sweden and one in Turkey. The approach starts by detecting water bodies within a selected area of interest using Sentinel-1. Then it extracts shoreline pixels to calculate the change in the VV and VH sigma naught and VV-VH and VV+VH Pauli vectors. Extracted differences are further classified according to the temporally closest Dynamic World data to handle the temporal difference for each land cover type. Next, we eliminate outlier values based on the percentiles, and from the remaining data, we sample each landcover class for modeling. From many of the tested frameworks, we obtained an R2 of 0.79 with Gaussian Process Regression. Currently, in this framework, we observed an underestimation of higher values and an overestimation of lower values within a range of ±0.4 cm. Furthermore, considering the chosen six lakes, we observed a negative correlation between depth change and polarimetric features obtained from samples taken from land covers of grass and flooded vegetation, which is typical for natural lakes. In the second step of the development, we will increase the number of samples by including lakes from Switzerland and further develop the model.

How to cite: Ünalan, U. B., Yüzügüllü, O., and Aksoy, A.: Near Real-Time Depth Change Monitoring on Inland Water Bodies Using Sentinel-1 and Dynamic World Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-649, https://doi.org/10.5194/egusphere-egu23-649, 2023.

Monitoring dissolved methane in aquatic ecosystems contributes significantly to advancing our understanding of the carbon cycle in these habitats and capturing their impact on methane emissions. Low-cost metal oxide semiconductors (MOS) gas sensors are becoming an increasingly attractive tool to perform such measurements, especially at the air-water interface. However, the performance of MOS sensors in aquatic environmental sciences has come under scrutiny because of their cross-sensitivity to temperature, moisture, and sulfide interference. In this study, we evaluated the performance and limitations of a MOS methane sensor when measuring dissolved methane in waters. A MOS sensor was encapsulated in a hydrophobic ePTFE membrane to impede contact with water but allow gas perfusion. Therefore, the membrane enabled us to submerge the sensor in water and overcome cross-sensitivity to humidity. A simple portable, low-energy, flow-through cell system was assembled that included an encapsulated MOS sensor and a temperature sensor. Waters (with or without methane) were injected into the flow cell at a constant rate by a peristaltic pump. The signals from the two sensors were recorded continuously with a cost-efficient Arduino UNO microcontroller.. Our experiments revealed that the lower limit of the sensor was in the range of 0.1-0.2 uM and that it provided a stable response at water temperatures in the range of 18.5-28oC. More information at Butturini, A., & Fonollosa, J. (2022). Use of metal oxide semiconductor sensors to measure methane in aquatic ecosystems in the presence of cross‐interfering compounds. Limnology and Oceanography: Methods20(11), 710-720.

How to cite: Butturini, A. and Fonollosa, J.: Metal oxide semiconductor (MOS) sensors to measure methane in aquatic ecosystems. An eficient DIY low  cost application., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1221, https://doi.org/10.5194/egusphere-egu23-1221, 2023.

EGU23-1636 | Posters virtual | HS1.2.1

Using the hydrological model for filling the missing discharge data by using multi-site calibration 

Ankit Singh, Hemant Kumar Dhaka, Pragati Prajapati, and Sanjeev Kumar Jha

The river discharge data is one of the most important pieces of information to regulate various water resources, including flood frequency analysis, drought and flood prediction, etc. The missing observer discharge data, even a short gap, influences the whole analysis and gives a totally different result. Filling data gaps in streamflow data is thus a critical step in any hydrological study. Interpolation, regression-based analysis, artificial neural networks, and modeling are all methods for generating missing data. While using the hydrological model to generate the data, we first need to calibrate the hydrological model. The single-site calibration of the hydrological model has its own limitations, due to which it does not correctly predict the streamflow at intermediate gauge locations. This is because, while calibrating the model for the final outlet, we tune the parameters that affect the results for the final outlet only and neglect the intermediate sites' output. In this study, we demonstrate the importance of multi-site calibration and use the calibrated hydrological model to generate the missing data at intermediate sites.

For this study, we selected the Godavari River basin and calibrated it at the final outlet (single-site calibration) and at 18 + 1 outlets (multi-site calibration). The whole basin is divided into 103 subbasins, and the Soil and Water Assessment Tool (SWAT) hydrological model is used for this study. After the successful multi-site calibration, we generated the missing data at 25 different gauging locations. The initial results from single-site calibration (NSE (0.57) and R2 (0.61)) show good agreement between observed and simulated discharge for the final outlet. The multi-site calibration analysis is in progress, and full results will be presented at the conference.

How to cite: Singh, A., Dhaka, H. K., Prajapati, P., and Jha, S. K.: Using the hydrological model for filling the missing discharge data by using multi-site calibration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1636, https://doi.org/10.5194/egusphere-egu23-1636, 2023.

EGU23-2681 | Posters on site | HS1.2.1

A low cost real-time kinematic dGPS system for measuring glacier movement 

Kirk Martinez, Jane Hart, Sherif Attia, Graeme Bragg, Marcus Corbin, Michael Jones, Christian Kuhlmann, Elliot Weaver, Richard Wells, Ioannis Christou, and Emily James

Glacier movement has been measured over the years using commercial units such as those from Leica. The aim is to measure point movements on the glacier surface in order to capture fine-grained data about its movement. This can also help to calibrate satellite-based approaches which have much lower resolution. Commercial dGPS recorders cost thousands of Euros so our project is creating a solution using new lower cost dGPS boards which could enable their use by more earth scientists.

The u-blox Zed-F9P based boards from Sparkfun can be used as a base station to send dGPS corrections to “rover” units on the glacier via a radio link. Each measurement is accurate to about 2cm depending on conditions. In our design the radio is used by the rovers to forward good fixes back to the base station, which then uses off-site communications to send the data home. Two types of internet link have been enabled: using a nano-satellite board (by SWARM) and a more traditional GSM mobile phone board (for locations with coverage). Both these boards are also available from Sparkfun – making most of the modules off-the-shelf. However our power supply is optimised to save power and charge the lithium ion battery from a solar panel. A real-time clock chip is used to wake up the system to take readings and transmit data, so the sleep power is only 0.03 mW enabling a year-long lifetime. The whole system is controlled by a Sparkfun Thing Plus SAMD51 which provides the required four serial connections and a circuitpython  environment. The full system will be installed in Iceland in the summer of 2023 and replace the previous prototype based on Swift Piksi Multi units which had shown the measurement principle to be sound.

How to cite: Martinez, K., Hart, J., Attia, S., Bragg, G., Corbin, M., Jones, M., Kuhlmann, C., Weaver, E., Wells, R., Christou, I., and James, E.: A low cost real-time kinematic dGPS system for measuring glacier movement, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2681, https://doi.org/10.5194/egusphere-egu23-2681, 2023.

EGU23-4844 | Posters on site | HS1.2.1

Quality control of stream water-stage using Hilbert-Huang Transform 

Yen- Chang Chen and Wu-Hsien Hsiao

Hydrological data, especially water stage and discharge, is very important for water resources planning and development, hydraulic structure design, and water resources management. Thus the hydrological data has to be observed and collected regularly and continuously. The hydrological data can be affected by many factors such as people, instruments, and climate. Therefore, the collected hydrological data still need to be subject to quality control and inspection to eliminate unreasonable data to ensure the accuracy and reliability. Traditionally, the quality control and inspection of stream water-stage is mainly manual. The verification of water stage data needs experienced hydrologists to judge the correctness of the data, and cannot be processed automatically. It is time consumed, costly, and labor intensive to process the quality control of stream water stage. Therefore, it is necessary to develop a feasible model to automatically check stream water-stage for providing reliable and accurate hydrological data.

This study applies Hilbert-Huang Transform (HHT) to process stream water-stage. The HHT is composed of Empirical Mode Decomposition (EEMD) and Hilbert transform (HT). The EEMD decomposes stream water-stage into many intrinsic mode functions (IMFs) and a residual. The first IMF component is used for Hilbert transform conversion to obtain the time amplitude energy relationship diagram. The amplitude fluctuation of the corresponding component of the stream water-stage, the amplitude value of the outliers can be revealed. When the amplitude value is larger than usual, there may be outliers, and vice versa. It depends on the threshold that is established in this study as the basis for filtering the incorrect water-stage. Therefore automatically inspecting the water-stage data can be achieved. The model for automatic inspecting procedure developed by this study will greatly reduce the manual quality control, not only shorten the checking time, save manpower, but also provide reliable and correct river water stage data.

How to cite: Chen, Y.-C. and Hsiao, W.-H.: Quality control of stream water-stage using Hilbert-Huang Transform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4844, https://doi.org/10.5194/egusphere-egu23-4844, 2023.

EGU23-4878 | Posters on site | HS1.2.1

Trials and design iterations experienced developing a low-cost depth trawl to sample macroplastic through the water column of a tidal river. 

David Higgins, Renata Correia, Hooi Siang Kang, Lee Kee Quen, Tan Lit Ken, Andre Vollering, Stijn Pinson, Thaine H. Assumpção, and Thomas Mani

Understanding the transport behaviour of mismanaged plastic waste in riverine and estuarine environments is growing. However, many studies to date focus on the surface layer transport while a limited number look to measure the vertical distribution of plastic waste within these systems. Factors such as density, shape, the influence of wind and flow velocity can determine the vertical distribution of the plastic waste in a river, but many knowledge gaps remain. With this, and as technology developers move to create innovative river surface focused interception solutions to extract plastic waste, a greater understanding of the transport behaviour of sub-surface plastic debris is required. Here, we present a comprehensive overview of the development stages required to build and deploy a low-cost depth trawl tool designed to sample plastic waste at a depth of up to 5m in a heavily polluted river in Malaysia. Topics covered include tool design concepts, manufacturing methods, onsite testing, river deployment learnings and sampling results. Field data is compiled from over 60 sampling surveys conducted over 14 days in several locations along the Klang River, Malaysia. The depth trawl is mounted to a locally available fishing boat (sampan) and consists of two steel horizontal arms, a steel frame, two winches, cables, weights, five nets, and is operated manually with the assistance of a solar-powered motor. The dimensions of each net are 30cm (W) x 50cm (H) x 100cm (L) with a mesh size of 30mm x 30mm. To ensure that the nets remain aligned vertically during deployment, a weight of 15kg is tied to the bottom of the net system on both sides. Samples were collected every 1 metre to a depth of 5 metres. Each sampling was conducted for 15 minutes, six times per day with an interval of 1 hour between samples to allow for changes in the tide and river flow direction. An ADCP was deployed in parallel to the depth trawl to provide measurements of flow velocity variation at the river surface and with depth. In addition, this paper reviews the depth trawl system’s capabilities and recommendations for further studies and applications in the field.

How to cite: Higgins, D., Correia, R., Kang, H. S., Quen, L. K., Ken, T. L., Vollering, A., Pinson, S., H. Assumpção, T., and Mani, T.: Trials and design iterations experienced developing a low-cost depth trawl to sample macroplastic through the water column of a tidal river., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4878, https://doi.org/10.5194/egusphere-egu23-4878, 2023.

EGU23-5922 | Posters on site | HS1.2.1

Effectiveness-assessment of nature-based flood mitigation using networked, low cost DIY environmental monitoring from FreeStation 

Sophia Burke, Arnout van Soesbergen, and Mark Mulligan

FreeStations are mature low-cost, networked, DIY environmental sensors and data loggers, developed since 2014  and now deployed around the world.  Build instructions are open source at www.freestation.org and based on high availability, low cost but accurate and robust components (with builds typically 3% the parts-cost of an equivalent proprietary monitoring systems).  This allows investment in a network of environmental loggers at the cost of a single, proprietary logger.  

FreeStations have been widely deployed in the DEFRA Natural Flood Management (NFM) national trials in the UK, and analytical methods developed to examine the performance of leaky dams, retention ponds, regenerative agricultural practices and other nature based solutions in mitigating flood risk at downstream assets.

These deployments usually consist of FreeStation weather stations: recording rainfall volume, rainfall intensity, air temperature, humidity and pressure as well as solar radiation, wind speed and direction.  The rainfall volume and instantaneous intensity are the most important for NFM studies.  Alongside weather stations, FreeStation sonar-based stage sensors are used, alongside river profile scan from a FreeStation LIDAR, to monitor change in river discharge due to an NFM intervention, relative to discharge at a downstream asset at risk.  Readings are taken at 10-minute intervals over multiple years.

A series of web based methods have been built as part of the FreeStation //Smart: platform to monitor and manage data from deployments and to analyse data to better understand flood mitigation by the key types of intervention.  In testing at more than 10 sites in the UK over a period of 2-3 years per site, large volumes of data have been collected at low cost and in support of local stakeholders during the H2020NAIAD and H2020ReSET projects.  

The data indicate the importance of careful design in leaky debris dams, the limited impact of inline retention ponds and the significant capacity of low-till farming methods to mitigate downstream flooding.  The effectiveness of NFM depends upon the number and scale of interventions, the proportion of the discharge at the downstream asset at risk which they affect (i.e. the downstream proximity of the asset at risk) and the capital and maintenance costs of the interventions. 

Low-cost approaches to environmental monitoring will be critical for developing the evidence base needed to better understand what nature based solutions work, where for water.  Low cost, internet-connected devices are easy to monitor and maintain, low risk and capable of extensive deployment to address the challenge of geographical variability which means that the impacts of specific NFM interventions are highly site specific. 

How to cite: Burke, S., van Soesbergen, A., and Mulligan, M.: Effectiveness-assessment of nature-based flood mitigation using networked, low cost DIY environmental monitoring from FreeStation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5922, https://doi.org/10.5194/egusphere-egu23-5922, 2023.

EGU23-8165 | Posters on site | HS1.2.1

Developing a smart sensor network for soil moisture monitoring in forests 

Nikita Aigner, Christine Moos, and Estelle Noyer

Forests play a crucial role in regulating the water content of soils and thus influence runoff formation, but also the susceptibility to drought or forest fires. However, the extent to which forests influence soil moisture is difficult to quantify and depends on several parameters, such as precipitation intensity and duration, and terrain or soil properties. To capture the temporal and spatial variability of soil moisture in forests, large-scale and long-term measurements are necessary. Currently, such measurements are relatively expensive and complex and thus generally lacking or restricted to agricultural areas.  

Our current work focuses on the development of a low-cost soil moisture sensor that uses off the shelf parts and can be deployed at scale to provide continuous long-term measurements. To increase adoption and ensure the digital sustainability of our concept, the project will be released open source to the general public.  

The sensor design is based around an ESP32 microcontroller to manage measurements with capacitive soil moisture sensors. For communication, we leverage the LoRa protocol and use infrastructure provided by the Things Network (TTN). Herein, we present the soft- and hardware architecture of a sensor prototype and results obtained from a proof-of-concept deployment. In addition, we discuss the calibration procedure and evaluation of capacitive soil moisture sensors (in comparison to time-domain reflectometry (TDR) sensors). Finally, we provide an outlook on future developments of our measurement system. The final goal of this project is to deploy sensors in several areas of interest that will allow for gathering data for a better understanding of the interaction of forests and soil moisture content.  

How to cite: Aigner, N., Moos, C., and Noyer, E.: Developing a smart sensor network for soil moisture monitoring in forests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8165, https://doi.org/10.5194/egusphere-egu23-8165, 2023.

EGU23-10497 | ECS | Posters virtual | HS1.2.1

Synchronized mapping of water quantity and quality of a reservoir through an unmanned surface vehicle: A case study of the Daljeon reservoir, South Korea 

Kwang-Hun Lee, Shahid Ali, Yena Kim, Ki-Taek Lee, Sae Yun Kwon, and Jonghun Kam

This study developed a synchronized mapping technique for water quantity and quality via an unmanned surface vehicle (USV). The USV with the acoustic doppler current profiler (ADCP) and the multiparameter sonde of water quality sensors (YSI EXO2) was used for identifying spatial and seasonal patterns of the Daljeon reservoir in South Korea. With this technique, we measured bathymetry and nitrate concentration from August 2021 through July 2022 at the high resolution spatial resolution and tested the sensitivity of estimated nitrate loads to spatial variations of input variables (water volumes and nitrate concentrations). Results showed that measured bathymetry and nitrate concentration varies over the water surface of the reservoir and time, which are associated with seasonal variations of temperature and precipitation. Despite weak spatial variations of the nitrate concentration, the water level of the reservoirs showed strong spatiotemporal variations depending on the topography of the reservoir and the  rainfall occurrence. Furthermore, we figured out using the mean for nitrate load was underestimated by -20% of the nitrate load estimates by considering spatial variation. High-resolution bathymetry measurement play a role in estimating nitrate loads with a minor impact of spatial variations of measured nitrate concentrations. We found that rainfall occurrences more likely increase estimated nitrate loads when it accounts for spatially variations of input variables, particularly water volumes. This study proved the potential utility of USV in simultaneously monitoring water quantity and quality for integrative water resource management for sustainably development of our communities.

How to cite: Lee, K.-H., Ali, S., Kim, Y., Lee, K.-T., Kwon, S. Y., and Kam, J.: Synchronized mapping of water quantity and quality of a reservoir through an unmanned surface vehicle: A case study of the Daljeon reservoir, South Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10497, https://doi.org/10.5194/egusphere-egu23-10497, 2023.

EGU23-11411 | Posters on site | HS1.2.1

Automated ablation stakes to constrain temperature-index melt models 

Andrew D. Wickert, Katherine R. Barnhart, William H. Armstrong, Matías Romero, Bobby Schulz, Gene-Hua Crystal Ng, Chad T. Sandell, Jeff D. La Frenierre, Shanti B. Penprase, Maximillian Van Wyk de Vries, and Kelly R. MacGregor

We developed automated ablation stakes to measure colocated in-situ changes in ice-surface elevation and climatological drivers of ablation. The designs implement open-source hardware, including the Margay data logger, which records information from a MaxBotix ultrasonic rangefinder as well as a sensor to detect atmospheric temperature and relative humidity. The stakes and sensor mounts are assembled using commonly available building materials, including electrical conduit and plastic pipe. The frequent (typically 1–15 minute) measurement intervals permit an integral approach to estimating temperature-index melt factors for ablation. Regressions of ablation vs. climatological drivers improve when relative humidity is included alongside temperature. We present all materials required to construct an automated ablation stake, alongside examples of their deployment and use in Alaska (USA), Ecuador, Patagonia (Argentina), and the Antarctic archipelago.

 

a: Alaska, 2012
b: Alaska, 2013
c: Ecuador, 2016
d: Argentina, 2020
e: Antarctica, 2021

How to cite: Wickert, A. D., Barnhart, K. R., Armstrong, W. H., Romero, M., Schulz, B., Ng, G.-H. C., Sandell, C. T., La Frenierre, J. D., Penprase, S. B., Van Wyk de Vries, M., and MacGregor, K. R.: Automated ablation stakes to constrain temperature-index melt models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11411, https://doi.org/10.5194/egusphere-egu23-11411, 2023.

EGU23-11777 | Posters on site | HS1.2.1

A low cost multi-chamber system (“Greenhouse Coffins”) to monitor CO2 and ET fluxes under semi-controlled conditions: Design and first results 

Mathias Hoffmann, Wael Al Hamwi, Matthias Lück, Marten Schmidt, and Maren Dubbert

Determining greenhouse gas (GHG) fluxes, water (ET) fluxes and their interconnectivity within the soil-plant-atmosphere-intersphere is crucial, not only when aiming to find solutions for current agricultural systems to mitigate the global climate crises but also to adapt them to related challenges ahead, such as more frequent and severe droughts. In a first attempt for a better understanding, often laboratory and/or greenhouse pot experiments are performed, during which gas exchange is predominately measured using especially manual closed chamber systems. Commercially available systems to determine gas exchange in terms of CO2 and ET are, however, costly and measurements itself labour-intensive. This limits the amounts of variables to be studied as well as possible repetitions during a study. Additionally, it resulted in the long-term focus on agroecosystems of the northern hemisphere while agroecosystems of sub-Saharan Africa as well as Southeast Asia are still being underrepresented.

We present an inexpensive (<1.000 Euro), Arduino based, multi-chamber system to semi-automatically measure 1) CO2 and 2.) ET fluxes. The systems consists of multiple, self-sufficient, closet-shaped PVC “coffins”. The “coffins” a closed by a frontal door and periodically ventilated through a sliding window. Relays connected to the microcontroller are used to steer closure/opening (linear actuator) and ventilation (axial fans). CO2 and ET fluxes are determined through the respective concentration increase during closure by a low-cost NDIR CO­2 (K30FR; 0-10,000 ppm, ± 30 ppm accuracy) and rH sensor (SHT-41). Parallel measurements of relevant environmental parameters inside and outside the “coffins” are conducted by DS18B20 (temperature) and BMP280 (air pressure) sensors. Sensor control, data visualization and storage, as well as steering closure/opening and ventilation is implemented in terms of a wifi and bluetooth enabled, socket powered (9V), compact microcontroller (D1 RS32) based logger unit. Here, we present the design, and first results of the developed, low-cost multi-chamber system. Results were validated against results of customized CO2 and ET measurement systems using regular scientific sensors (LI-COR 850) and data logger components (CR1000), connected to each “coffin” by a multiplexer.  Flow-meter were used for measurement synchronization.

How to cite: Hoffmann, M., Al Hamwi, W., Lück, M., Schmidt, M., and Dubbert, M.: A low cost multi-chamber system (“Greenhouse Coffins”) to monitor CO2 and ET fluxes under semi-controlled conditions: Design and first results, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11777, https://doi.org/10.5194/egusphere-egu23-11777, 2023.

EGU23-12622 | ECS | Posters on site | HS1.2.1

Water user Fab Labs: co-design of low-tech sensors for irrigated systems 

Paul Vandôme, Crystele Leauthaud, Simon Moinard, Insaf Mekki, Abdelaziz Zairi, and Gilles Belaud

Mediterranean agriculture is facing the challenge to produce sustainably with a water resource under pressure. As irrigated areas expand in response to increasing vulnerability to drought, it is essential to support water users towards better agricultural water management. We set up two Fab Labs on the shores of the Mediterranean (France and Tunisia) to bring together water users around a collective project: co-constructing innovations to address local water management issues. A range of low-tech, low-cost and open source IoT-based sensors emerged from this process. The technologies were tested with users during the 2022 irrigation season. The aim of this study is to provide feedback on this participatory method as a facilitator for creating and sharing innovation in rural territories and to discuss the opportunities, benefits and limitations related to the use of these new technologies. We believe that this work contributes to make the measurement of water flows - and thus their understanding and better management - more accessible to the agricultural sector.     

How to cite: Vandôme, P., Leauthaud, C., Moinard, S., Mekki, I., Zairi, A., and Belaud, G.: Water user Fab Labs: co-design of low-tech sensors for irrigated systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12622, https://doi.org/10.5194/egusphere-egu23-12622, 2023.

EGU23-13072 | ECS | Posters on site | HS1.2.1

Precipitation Measurement from Raindrops’ Sound and Touch Signals 

Seunghyun Hwang, Jinwook Lee, Jeemi Sung, Hyochan Kim, Beomseo Kim, and Changhyun Jun

This study proposes a novel method for rainfall intensity estimation from acoustic and vibration data with low-cost sensors. At first, a precipitation measurement device was developed to collect sound and touch signals from raindrops, composed of Raspberry Pi, a condenser microphone, and an accelerometer with 6 degrees of freedom. To figure out whether rainfall occurred or not, a binary classification model with the XGBoost algorithm was considered to analyze long-term time series of vibration data. Then, high-resolution acoustic data was used to investigate the main characteristics of rainfall patterns at a frequency domain for the period when it was determined that rainfall occurred. As a result of the Short Time Fourier Transform (STFT), the highest frequency, mean and standard deviation of amplitudes were selected as representative values for minute data. Finally, different types of regression models were applied to develop the method for rainfall intensity estimation from comparative analysis with other precipitation measurement devices (e.g., PARSIVEL, etc.). It should be noted that the new device with the proposed method functions reliably under extreme environmental conditions when the estimated rainfall intensity was compared with measured data from ground-based precipitation devices. It shows that low-cost sensors with sound and touch signals from raindrops can be effectively used for rainfall intensity estimation with easy installation and maintenance, indicating a strong possibility of being considered in a wide range of areas for precipitation measurement with high resolution and accuracy

Acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022R1A4A3032838).

How to cite: Hwang, S., Lee, J., Sung, J., Kim, H., Kim, B., and Jun, C.: Precipitation Measurement from Raindrops’ Sound and Touch Signals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13072, https://doi.org/10.5194/egusphere-egu23-13072, 2023.

EGU23-14370 | Posters on site | HS1.2.1

Monitoring an ephemeral stream with a Teensy 3.2 + audio shield to determine water level only from the noise of a stream 

Linus Fässler, Natalie Ceperley, Peter Leiser, and Bettina Schaefli

River networks in the Alps are very complex and hold many unanswered research questions. For example, various assumptions must be made to when studying tributaries and small rivers. Namely, there is not a widely accepted tool to measure streamflow in small, mountain streams that can overcome their specific challenges affordably without large installations. For example, alteration between extremely high and no discharge volume is characteristic of intermittent rivers and ephemeral streams (IRES). Conventional measuring devices all require streambed installation, which exposes them to displacement or destruction by abruptly rising water levels. One solution, thus, is to remove the sensor from the streambed and measure from a distance. We have experimented with an acoustic sound recorder mounted above the stream as an alternative tool to assess water level. We designed a low-cost audio sensor powered by a microcontroller with an audio shield specifically for recording IRES. To ensure reproducibility, we used Arduino for programming the Teensy 3.2. Images of the water level in an IRES were simultaneously captured when possible (daylight) and used for calibration. The water level visible in the images correlated well with that determined from the audio recordings from our self-developed audio sensor (R2 = 95%). Based exclusively on the audio recording of an IRES, we can obtain a time series of the water level, at least when water was present. We are currently unable to determine consistently whether water is present nor state with certainty when the streambed is dry based solely on acoustic data. Nevertheless, this new sensor allows us to measure an alpine channel network at more locations and over longer time periods than previously feasible.

How to cite: Fässler, L., Ceperley, N., Leiser, P., and Schaefli, B.: Monitoring an ephemeral stream with a Teensy 3.2 + audio shield to determine water level only from the noise of a stream, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14370, https://doi.org/10.5194/egusphere-egu23-14370, 2023.

The development of artificial reservoirs plays a considerable role in regulating the spatial and temporal distribution of irrigated rainfall and guaranteeing sustainable agricultural development. Many studies have used the area-storage relationship to obtain the storage capacity of on-farm reservoirs (OFRs), but it does not work for OFRs with persistent water surface area. In this study, we proposed an effective method to estimate the water storage of irrigated OFRs by combining multi-source remote sensing data and ground observation. We quickly derived the location of irrigated OFRs by using seasonal characteristics of irrigated OFRs and obtained high-precision water surface area using an object-oriented segmentation. We estimated water storage of irrigated OFRs by combining three different ways (i.e., Lidar-based, ground observation-based (photos), and surface area-based). The method performs well in three aspects, i.e., identifying on-farm reservoirs, extracting water surface area, and calculating water storage. The accuracy of identification reaches 94.1%, and the derived water area agrees well with the surveyed results, i.e., an overall accuracy of 97.8%, the root mean square error (RMSE) and the mean absolute errors (MAE) are 962 m2 and 766 m2, respectively. The obtained water storage is reliable using three different ways (i.e., the area-storage, Lidar-based, and photo observations-based methods), with accuracy of 98.8%, 95.2%, and 94.1%, respectively. The proposed method enables monitoring of the storage of multiple types of irrigated OFRs, particularly the photo observation-based method can deal with the storage of OFRs with persistent water areas, showing huge potential to promote irrigated water resource utilization efficiency.

How to cite: wang, Y.: Monitoring water storage of on-farm reservoirs using remote sensing and ground observation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15372, https://doi.org/10.5194/egusphere-egu23-15372, 2023.

Hydrology is still one of the most data scarce natural sciences. The large number of variables to measure, their extreme spatiotemporal gradients, and the often harsh and hostile environmental conditions all contribute to this issue. This challenge is even more pronounced in remote and extreme environments such as the tropics, and mountain regions, where the need for robust data is most acute.

Many new and emergent technologies can help with building more cost-effective, robust, and versatile hydrological monitoring systems. However, the speed at which these new technologies are being incorporated in commercially available systems is slow and dictated by commercial interests and bottlenecks.

An alternative solution is for scientists to build their own systems using off the shelf components. Open-source hardware and software, such as the Arduino and Raspberry Pi ecosystems, make this increasingly feasible. As a result, a plethora of global initiatives for open-source sensing and logging solutions have emerged.

But despite these new technologies, it remains a major challenge to build open-source solutions that equal the reliability and robustness of the high-end commercial systems that are available on the market. Sharing experiences, best practices, and evidence on the real-world performance of different designs may help with overcoming this bottleneck.

In this contribution, I summarize the experience gained from developing and operating over 300 open-source data loggers, built around the Riverlabs platform. This platform is mostly a compilation of existing open-source hardware and software components and solutions, which were refined further and tweaked for robustness and reliability in extreme environments. Our loggers have been installed in locations as diverse as Arctic Norway, the high Andes of Peru and Chile, the Nepalese and Indian Himalayas, the Somali desert, and the Malaysian rainforest, providing a wide range of real-world test-cases and performances.

How to cite: Buytaert, W.: Towards a robust, open-source logging platform for environmental monitoring in challenging environments: the Riverlabs toolbox, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15989, https://doi.org/10.5194/egusphere-egu23-15989, 2023.

EGU23-17527 | ECS | Posters on site | HS1.2.1

Design of an affordable and highly flexible IoT station for multiple gas concentration monitoring 

Francesco Renzi, Flavio Cammillozzi, Giancarlo Cecchini, Alessandro Filippi, and Riccardo Valentini

The air quality monitoring is a core topic for European environmental policies and worldwide. At the same time technologies such as electrochemical or NDIR gas sensors became affordable and easy to implement in a customized design. A highly flexible monitoring station has been designed and build in order to obtain a customizable and affordable device. It is composed of two boards, one in charge of connectivity and processing while the other allows to insert up to 11 gas sensors. Such number is achieved through the use of three multiplexers that allow to spare input pins of the processor. Moreover the flexibility at the moment is achieved using sensors with the same form factor but adapters are under development to increase the adaptability of the system, both hardware and software. An Arduino MKR zero runs the application that can be run in three different modes: single measurement, time driven or position driven. The last feature is obtained through an optional on-board U-blox GNSS module that allows to georeference the performed measurements. This mode is mainly used when the measurement cell is applied on moving object, such as drones. The system is able to send the data collected and receive commands using MQTT protocol (HiveMQ broker) through a NB-IoT connection and interact with the user from an online dashboard created using Thingsboard. The use of the MQTT protocol allows to send the data to multiple endpoints if the data should be provided also to third parties. Moreover, the data and some parameters are also saved on a sd card. All the system is built on stand alone boards to achieve easy maintaince of the system and to allow a rapid change in the used technology (a plug and play LoRaWan module is under development). Being a multi-application platform, price of the device is of course highly dependent on the chosen set of sensors thus, in the end, on the application itself (i.e. Air pollution or gas emission in barns). To sum up, the device described is a possible solution for an affordable gas concentration measurement system that can be adapted to fit a large variety of use cases combining software and hardware solutions.

How to cite: Renzi, F., Cammillozzi, F., Cecchini, G., Filippi, A., and Valentini, R.: Design of an affordable and highly flexible IoT station for multiple gas concentration monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17527, https://doi.org/10.5194/egusphere-egu23-17527, 2023.

GI2 – Data networks and analysis

EGU23-1562 | ECS | Posters virtual | GI2.1

A new finite-difference stress modeling method governed by elastic wave equations 

Zhuo Fan, Fei Cheng, and Jiangping Liu

Numerical stress or strain modeling has been a focused subject in many fields, especially in assessing the stability of key engineering structures and better understanding in local or tectonic stress patters and seismicity. Here we proposed a new stress modeling method governed by elastic wave equations using finite-difference scheme. Based on the modeling scheme of wave propagation, the proposed method is able to solve both the dynamic stress evolution and the static stress state of equilibrium by introducing an artificial damping factor to the particle velocity. We validate the proposed method in three geophysical benchmarks: (a) a layered earth model under gravitational load, (b) a rock mass model under nonuniform loads on its exterior boundaries and (c) a fault zone with strain localization driven by regional tectonic loading that measured by GPS velocity field.  Because the governing equations of the proposed method are wave equations instead of equilibrium equations, we are able to use the perfectly matched layer as the artificial boundary conditions for models in unbounded domain, which will substantially improve the accuracy of them. Also, the proposed scheme maps the physical model on simple computational grids and therefore is more memory efficient for grid points’ positions not been stored. Besides, the efficient parallel computing of the finite-different method guarantees the proposed method’s advantage in computational speed. As a minor modification to wave modeling scheme, the proposed stress modeling method is not only accurate for geological models through different scales, but also physically reasonable and easy to implement for geophysicists.

How to cite: Fan, Z., Cheng, F., and Liu, J.: A new finite-difference stress modeling method governed by elastic wave equations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1562, https://doi.org/10.5194/egusphere-egu23-1562, 2023.

EGU23-2228 | ECS | Posters on site | GI2.1

Non-destructive geophysical damage analysis of medieval plaster in the cloister of the St. Petri Cathedral Schleswig (Germany) 

Yunus Esel, Ercan Erkul, Detlef Schulte-Kortnack, Christian Leonhardt, Julika Heller, and Thomas Meier

Buildings that have existed for centuries undergo structural changes over time due to variations in use. In addition, many structures are severely damaged for example by moisture intrusion. To determine the distribution of moisture in the structure, they are often examined pointwise by core sampling. In addition to invasive methods, non-destructive methods may be applied to obtain three-dimensional hints on the moisture distribution with structures of interest.            
The purpose of this paper is to show that non-destructive determination of moisture distribution is possible by using and combining geophysical measurement methods such as infrared thermography (IR), ultrasound (US) and ground penetrating radar (GPR). There are examples for the combination of these methods for non-destructive examination, but it is not yet commonly applied in the field of restoration and conservation of historic buildings.            
We present results of geophysical investigations of medieval wall paintings in the cloister of the cathedral in Schleswig (Federal State Schleswig-Holstein, Northern Germany) in the framework of a project funded by the German Federal Foundation for the Environment (Deutsche Bundesstiftung Umwelt - DBU). In the cloister, large-scale alterations of the medieval red-line paintings occurred due to gypsum deposits and a shellac coating. In order to quantify the material properties of a vault section (yoke) in the cloister during the restoration ultrasound surface wave measurements, passive and active thermography and ground penetrating radar measurements were carried out.
Repeating measurements at intervals of several months made it possible to evaluate the effectiveness of the test treatments by different solvents to remove the shellac as well as the gypsum deposits. In addition, our results from the passive thermography measurements show that in one section a defect in the horizontal barrier could be responsible for moisture ingress and associated damage. The radargrams recorded in this area confirm that a significant change in reflection amplitudes is present in the areas of increased moisture.

How to cite: Esel, Y., Erkul, E., Schulte-Kortnack, D., Leonhardt, C., Heller, J., and Meier, T.: Non-destructive geophysical damage analysis of medieval plaster in the cloister of the St. Petri Cathedral Schleswig (Germany), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2228, https://doi.org/10.5194/egusphere-egu23-2228, 2023.

EGU23-2347 | ECS | Posters on site | GI2.1

Non-destructive testing methods and numerical development for enhancing airfield pavement management 

Konstantinos Gkyrtis, Christina Plati, and Andreas Loizos

Pavements are an essential component of airport facilities. Airport infrastructures serve to safely transport people and goods on a day-to-day basis. They promote economic development, both regionally and internationally, by also boosting tourist flows. In times of crisis, they can be used for societal emergencies, such as managing migration flows. Therefore, airports need pavements in good physical condition to ensure uninterrupted operations. However, interventions on airfield pavements are costly and labor intensive. Aspects of pavement structural performance related to bearing capacity and damage potential remain of paramount importance as the service life of a pavement extends beyond its design life. Therefore, structural condition evaluation is required to ensure the long-term bearing capacity of the pavement. 

The design and evaluation of flexible airfield pavements are generally based on the Multi-Layered Elastic Theory (MLET) in accordance with Federal Aviation Administration (FAA) principles. The most informative tool for structural evaluation is the Falling Weight Deflectometer (FWD), which senses pavement surfaces using geophones that record load-induced deflections at various locations. Additional geophysical inspection data using Ground Penetrating Radar (GRP) is processed to estimate the stratigraphy of the pavement. The integration of the above data provides an estimate of the pavement's performance and potential for damage. However, GRP is not always readily applicable.

In addition, the most important concern in pavement evaluation is the mechanical characterization of pavement materials. At the top of pavement structures, asphalt mixtures behave as a function of temperature and loading frequency. This viscoelastic behavior deviates from MLET and this issue needs further investigation. Therefore, this study integrates measured NDT data and sample data from cores taken in-situ. The pavement under study is an existing asphalt pavement of a runway at a regional airport in Southern Europe. A comparative evaluation of the strain state within the pavement body is performed both at critical locations and at the pavement surface, taking into account elastic and viscoelastic behaviors. Strains are an important input to models of long-term pavement performance, which has a critical influence on aircraft maneuverability. In turn, the significant discrepancies found highlight the need for more mechanistic considerations in predicting the damage and stress potential of airfield pavements so that maintenance and/or rehabilitation needs can be better managed and planned.

Overall, this study highlights the sensing capabilities of NDT data towards a structural health monitoring of airfield pavements. Ground-truth data from limited destructive testing enrich pavement evaluation processes and enhance conventional FAA evaluation procedures. The study proposes a numerical development for accurate field inspections and improved monitoring protocols for the benefit of airfield pavement management and rehabilitation planning. 

How to cite: Gkyrtis, K., Plati, C., and Loizos, A.: Non-destructive testing methods and numerical development for enhancing airfield pavement management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2347, https://doi.org/10.5194/egusphere-egu23-2347, 2023.

The Laacher See Event- (LSE-) volcanism isochrone of 12.850 yrs BP (Bujatti-Narbeshuber, 1997), proxy for P/H boundary KISS (Bujatti-Narbeshuber, 1996), was improved from Gerzensee varves to 13.034 cal yrs BP (Van Raden, 2019).

    This LSE date now separates end Pleistocene, first, mainly oceanic-water KISS, from the second, Holocene-Younger Dryas Onset (YDO), continental-ice impact, as predicted by KISS-hypothesis, separating:„ a continental Koefels-comet ice-impact, from the mainly oceanic KISS, at the Pleistocene/Holocene boundary, associated with global warming, dendro C14 spikes, faunal mass extinction...“ (Bujatti-Narbeshuber, 1996; Max, 2022).

    Oceanic-water LSE-KISS (13.034 cal yrs BP, varves) of end Alleroed temperature maximum, separates by 157 yrs from continental-ice YDO-KISS (12.877 cal yrs BP, varve-date). A larger gap of 184 yrs results, taking C 14 dated YD-KISS (12.850 cal yrs BP), approaching 200 yrs of earlier varve-studies (Bujatti-Narbeshuber, 1997).

    LSE-KISS varve-date differs by 47 yrs from geo-magnetic Gothenberg Excursion Onset- (GEO-) isochrone of 13.081 cal yrs BP (Chen, 2020), suggesting geo-magnetic reversal, True Polar Wander (TPW) GEO-TPW-KISS from 2 Koefels-comet (Taurid-) fragments. This considers end-paleolithic Magdalenian Impact Sequelae Symbolisations (MISS).

    Questioning P/H isostatic-unloading volcanism (Zielinsky, 1996), LSE-KISS volcanism is from Mid Atlantic Ridge & Mid Atlantic Plateau (MAR&MAP) impact (Bujatti-Narbeshuber, 1997, 2022), as further corroborated by Greenland (NGRIP) ice-core sulfate monitoring: from LSE-KISS-volcanism (12.978 cal yrs) to YDO (12.867 cal yr BP), within 110 yrs, an unprecedented, bipolar-volcanic-eruption-quadruplet resulted (Lin, 2022).

    The first Taurid LSE-KISS (Varves-date: 13.034 cal yrs BP, GEO-date: 13.084 cal yrs BP.) into oceanic-water is evident from two 700 km Mid Atlantic Ridge & Plateau Lowering Events (MARPLES) releasing two separate Tsunamis (Bujatti-Narbeshuber, 2022): Resulting in submarine explosive-magmatism-silicates, seafloor-carbonates, volcanic-ash and sea-water in huge strato-meso-spheric overheated steam-plume moving eastward by eolian transport, descending in drowning rain-flood, largely contributing to Eurasian loess sediment layer (Muck, 1976).

    This is stratigraphically verified in e.g. relative stratigraphic positions in Netherland, Geldrop-Aalsterhut, with Younger Coversand I, bleached (!) (AMS 13.080- 12.915 cal yrs BP) underlying intercalated (!), charcoal rich (AMS 12.785-12.650 cal yrs BP) Usselo Horizon (Andronikov, 2016). It corresponds to US, Black Mats stratigraphy from second Taurid, continental-ice, YD-KISS (12.850 cal yrs BP, C14) plus Carolina Bays (CB) with: 1. Soft, white, loess sediment from first oceanic LSE-KISS. 2. YD-KISS proxies-stratum. 3. e.g. Carolina-Florida-coast-sand-disturbances, within 1.500 km radius of continental-ice YD-KISS ice-ejecta impact-curtain of 500.000 CB (LIDAR) 4. Black Mats after YD-KISS.

    After visiting Koefels-crater an “below continental-glacier-ice, circular geomagnetic-anomaly with paleoseismic Koefels-corridor of twelfe Holocene rockfalls”, Eugene Shoemaker (Vienna, May 5th 1997), when asked about Carolina Bays causation, is quoted: “Eugene spoke of a late Pleistocene origin of the Bays and as glaciological features while I preferred the paleoseismic interpretation. I interprete them as paleoseismic impact-seismic liquefaction features. They … are the first evidence for a late Pleistocene impact event. Dated by me …12.850 BP (1950) in calendar years”. (Bujatti-Narbeshuber, NHM letter to John Grant III, Sept. 22nd 1997).

    Both P/H-impacts break&make, Pleistocene criticality&Holocene damped flow, through 700 km geomorphological threshold (GLOVES) submersion & through (GTT) water, CO2 Greenhouse-gas-production, beyond glaciation threshold for hot climate prediction.

How to cite: Bujatti-Narbeshuber, M.: Pleistocene/Holocene (P/H) boundary oceanic Koefels-comet Impact Series Scenario (KISS) of 12.850 yr BP Global-warming Threshold Triad (GTT)-Part III, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2869, https://doi.org/10.5194/egusphere-egu23-2869, 2023.

To evaluate the feasibility of CO2 sequestration in offshore, South Korea, we studied numerical modelling with elastic velocity model. The CO2 storage candidate is a brine saturated aquifer formation overlain by basalt caprock in the Southern Continental Shelf of Korea. Basalt formation without joint and fracture can seal a storage volume preventing leakage of injected CO2. Result of preliminary two-dimensional seismic exploration estimated that storage potential would be from 42.07 to 143.79 Mt of CO2. The input model include P- and S-wave velocity and density of shallow sediment and vasalt layer. To simulate CO2 injection, we assumed an area of CO2 plume at the interval beneath the depth of basalt formation and artificially decreased P-, S-wave velocities, and density values. Synthesized seismic records are comparable with survey's gather as direct arrival and primary reflections. The ongoing work can be extended on a quantitative verification concerning serveral cased of varying velcoties and densities.

How to cite: Cheong, S., Kang, M., and Kim, K. J.: Numerical modelling of seismic field record with elastic velocity construction for CO2 sequestration in offshore, South Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2980, https://doi.org/10.5194/egusphere-egu23-2980, 2023.

EGU23-4861 | Orals | GI2.1

Decay diagnosis of tree trunks using 3D point cloud and reverse time migration of GPR data 

Zhijie Chen, Hai Liu, Meng Xu, Yunpeng Yue, and Bin Zhang

Health monitoring and disease mitigation of trees are essential to ensure the sustainability of wood industry, safety of ecosystems, and maintenance of climatic conditions. Several non-destructive testing methods have been applied to monitor and detect the decays inside the trunks. Among them, ground penetrating radar (GPR) has gained recognition due to its high efficiency and good resolution. However, due to the wide beam width of the antenna pattern and the complicated scattering caused by the trunk structure, the recorded GPR profile is far from the actual geometry of the tree trunk. Moreover, the irregular contour of the tree trunk makes traditional data processing algorithms difficult to be performed. Therefore, an efficient migration algorithm with high resolution, as well as a high accuracy survey-line positioning method for curved contour of the trunk should be developed.

In this paper, a combined approach is proposed to image the inner structures inside the irregular-shaped trunks. In the first step, the 3D contour of the targeted tree trunk is built up by a 3D point cloud technique via photographing around the trunk at various angles. Subsequently, the 2D irregular contour of the cross-section of trunk at the position of the GPR survey line is extracted by the Canny edge detection method to locate the accurate position of each GPR A-scans [1]. Thirdly, the raw GPR profile is pre-processed to suppress undesired noise and clutters. Then, an RTM algorithm based on the zero-time imaging condition is applied for image reconstruction using the extracted 2D contour [2]. Lastly, a denoising method based on the total variation (TV) regularization is applied for artifact suppression in the reconstructed images [3].

Numerical, laboratory and field experiments are carried out to validate the applicability of the proposed approach. Both numerical and laboratory experimental results show that the RTM can yield more accurate and higher resolution images of the inner structures of the tree cross section than the BP algorithm. The proposed approach is further applied to a diseased camphor tree, and an elliptical decay defect is found the in the migrated GPR image. The results are validated by a visual inspection after the tree trunk was sawed down.

Fig. 1 Field experiment. (a) Geometric reconstruction result using point cloud data, (b) migrated result by the RTM algorithm and (c) bottom view of the tree trunk after sawing down. The red and yellow ellipses indicate the cavity and the decay region in the trunk, respectively.

References:

[1] Canny, "A Computational Approach to edge detection," IEEE Transactions on Pattern Analysis and Machine Interllgent, vol. PAMI-8, no. 6, pp. 679-698, 1986, doi: 10.1109/TPAMI.1986.4767851.

[2] S. Chattopadhyay and G. A. McMechan, "Imaging conditions for prestack reverse-time migration," Geophysics, vol. 73, no. 3, pp. S81-S89, 2008, doi: 10.1190/1.2903822.

[3] L. I. Rudin, S. Osher, and E. Fatemi, "Nonlinear total variation based noise removal algorithms," Physica D, vol. 60, pp. 259-268, 1992, doi: 10.1016/0167-2789(92)90242-F.

How to cite: Chen, Z., Liu, H., Xu, M., Yue, Y., and Zhang, B.: Decay diagnosis of tree trunks using 3D point cloud and reverse time migration of GPR data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4861, https://doi.org/10.5194/egusphere-egu23-4861, 2023.

EGU23-6795 | ECS | Orals | GI2.1

Relaxing requirements for spatio-temporal data fusion 

Harkaitz Goyena, Unai Pérez-Goya, Manuel Montesino-San Martín, Ana F. Militino, Peter M. Atkinson, and M. Dolores Ugarte

Satellite sensors need to make a trade-off between revisit frequency and spatial resolution. This work presents a spatio-temporal image fusion method called Unpaired Spatio-Temporal Fusion of Image Patches (USTFIP). This method combines data from different multispectral sensors and creates images combining the best of each satellite in terms of frequency and resolution. It generates synthetic images and selects optimal information from cloud-contaminated images, to avoid the need of cloud-free matching pairs of satellite images. The removal of this restriction makes it easier to run our fusion algorithm even in the presence of clouds, which are frequent in time series of satellite images. The increasing demand of larger datasets makes necessary the use of computationally optimized methods. Therefore, this method is programmed to run in parallel reducing the run-time with regard to other methods. USTFIP is tested through an experimental scenario with similar procedures as Fit-FC, STARFM and FSDAF. Finally, USTFIP is the most robust, since its prediction accuracy deprecates at a much lower rate as classical requirements become progressively difficult to meet.

How to cite: Goyena, H., Pérez-Goya, U., Montesino-San Martín, M., F. Militino, A., Atkinson, P. M., and Ugarte, M. D.: Relaxing requirements for spatio-temporal data fusion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6795, https://doi.org/10.5194/egusphere-egu23-6795, 2023.

Continual monitoring of tree roots, which is essential when considering tree health and safety, is possible using a digital model. Non-destructive techniques, for instance, laser scanning, acoustics, and Ground Penetrating Radar (GPR) have been used in the past to study both the external and internal physical dimensions of objects and structures [1], including trees [2,3]. Recent studies have shown that GPR is effective in mapping the root system's network in street trees [3]. Light Detection and Ranging (LiDAR) technology has also been employed in infrastructure management to generate 3D data and to detect surface displacements with millimeter accuracy [4]. However, scanning such structures using current state-of-the-art technologies can be expensive and time consuming. Further, continual monitoring of tree roots requires multiple visits to tree sites and, oftentimes, repeated excavations of soil.

This work proposes a Virtual Reality (VR) system using smartphone-based LiDAR and GPR data to capture ground surface and subsurface information to monitor the location of tree roots. Both datasets can be visualized in 3D in a VR environment for future assessment. LiDAR technology has recently become available in smartphones (for instance, the Apple iPhone 12+) and can scan a surface, e.g., the base of a tree, and export the data to a 3D modelling and visualization application. Using GPR data, we combined subsurface information on the location of tree roots with the LiDAR scan to provide a holistic digital model of the physical site. The system can provide a relatively low-cost environmental modelling and assessment solution, which will allow researchers and environmental professionals to a) create digital 3D snapshots of a physical site for later assessment, b) track positional data on existing tree roots, and c) inform the decision-making process regarding locations for potential future excavations.

Acknowledgments: Sincere thanks to the following for their support: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. The Authors would also like to thank Mr Dale Mortimer (representing the Ealing Council) and the Walpole Park for facilitating this research.

References

[1] Alani A. M. et al., Non-destructive assessment of a historic masonry arch bridge using ground penetrating radar and 3D laser scanner. IMEKO International Conference on Metrology for Archaeology and Cultural Heritage Lecce, Italy, October 23-25, 2017.

[2] Ježová, J., Mertens, L., Lambot, S., 2016. “Ground-penetrating radar for observing tree trunks and other cylindrical objects,” Construction and Building Materials (123), 214-225.

[3] Lantini, L., Alani, A. M., Giannakis, I., Benedetto, A. and Tosti, F., 2020. "Application of ground penetrating radar for mapping tree root system architecture and mass density of street trees," Advances in Transportation Studies (3), 51-62.

[4] Lee, J. et al., Long-term displacement measurement of bridges using a LiDAR system. Struct Control Health Monit. 2019; 26:e2428.

How to cite: Uzor, S., Lantini, L., and Tosti, F.: Low-cost assessment and visualization of tree roots using smartphone LiDAR, Ground-Penetrating Radar (GPR) data and virtual reality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6908, https://doi.org/10.5194/egusphere-egu23-6908, 2023.

EGU23-8384 | ECS | Orals | GI2.1

A Study on the Effect of Target Orientation on the GPR Detection of Tree Roots Using a Deep Learning Approach 

Livia Lantini, Federica Massimi, Saeed Sotoudeh, Dale Mortimer, Francesco Benedetto, and Fabio Tosti

Monitoring and protection of natural resources have grown increasingly important in recent years, since the effect of emerging illnesses has caused serious concerns among environmentalists and communities. In this regard, tree roots are one of the most crucial and fragile plant organs, as well as one of the most difficult to assess [1].

Within this context, ground penetrating radar (GPR) applications have shown to be precise and effective for investigating and mapping tree roots [2]. Furthermore, in order to overcome limitations arising from natural soil heterogeneity, a recent study has proven the feasibility of deep learning image-based detection and classification methods applied to the GPR investigation of tree roots [3].

The present research proposes an analysis of the effect of root orientation on the GPR detection of tree root systems. To this end, a dedicated survey methodology was developed for compilation of a database of isolated roots. A set of GPR data was collected with different incidence angles with respect to each investigated root. The GPR signal is then processed in both temporal and frequency domains to filter out existing noise-related information and obtain spectrograms (i.e. a visual representation of a signal's frequency spectrum relative to time). Subsequently, an image-based deep learning framework is implemented, and its performance in recognising outputs with different incidence angles is compared to traditional machine learning classifiers. The preliminary results of this research demonstrate the potential of the proposed approach and pave the way for the use of novel ways to enhance the interpretation of tree root systems.

 

Acknowledgements

The Authors would like to express their sincere thanks and gratitude to the following trusts, charities, organisations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. The Authors would also like to thank the Ealing Council and the Walpole Park for facilitating this research.

 

References

[1] Innes, J. L., 1993. Forest health: its assessment and status. CAB International.

[2] Lantini, L., Tosti, F., Giannakis, I., Zou, L., Benedetto, A. and Alani, A. M., 2020. "An Enhanced Data Processing Framework for Mapping Tree Root Systems Using Ground Penetrating Radar," Remote Sensing 12(20), 3417.

[3] Lantini, L., Massimi, F., Tosti, F., Alani, A. M. and Benedetto, F. "A Deep Learning Approach for Tree Root Detection using GPR Spectrogram Imagery," 2022 45th International Conference on Telecommunications and Signal Processing (TSP), 2022, pp. 391-394.

How to cite: Lantini, L., Massimi, F., Sotoudeh, S., Mortimer, D., Benedetto, F., and Tosti, F.: A Study on the Effect of Target Orientation on the GPR Detection of Tree Roots Using a Deep Learning Approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8384, https://doi.org/10.5194/egusphere-egu23-8384, 2023.

EGU23-8667 | ECS | Posters on site | GI2.1

An Investigation into the Acquisition Parameters for GB-SAR Assessment of Bridge Structural Components 

Saeed Sotoudeh, Livia Lantini, Kevin Jagadissen Munisami, Amir M. Alani, and Fabio Tosti

Structural health monitoring (SHM) is a necessary measure to maintain bridge infrastructure safe. To this purpose, remote sensing has proven effective in acquiring data with high accuracy in relatively short time. Amongst the available methods, the ground-based synthetic aperture radar (GB-SAR) can detect sub-zero deflections up to 0.01 mm generated by moving vehicles or the environmental excitation of the bridges [1]. Interferometric radars are also capable of data collection regardless of weather, day, and night conditions (Alba et al., 2008). However, from the available literature - there is lack of studies and methods focusing on the actual capabilities of the GB-SAR to target specific structural elements and components of the bridge - which makes it difficult to associate the measured deflection with the actual bridge section. According to the antenna type, the footprint of the radar signal gets wider in distance which encompasses more elements and the presence of multiple targets in the same resolution cell adds uncertainty to the acquired data (Michel & Keller, 2021). To this effect, the purpose of the present research is to introduce a methodology for pinpointing targets using GB-SAR and aid the data interpretation. An experimental procedure is devised to control acquisition parameters and targets, and being able to analyse the returned outputs in a more clinical condition. The outcome of this research will add to the existing literature in terms of collecting data with enhanced precision and certainty.

 

Keywords

Structural Health Monitoring (SHM), GB-SAR, Remote Sensing, Interferometric Radar

 

Acknowledgements

This research was funded by the Vice-Chancellor’s PhD Scholarship at the University of West London.

 

References

[1] Benedettini, F., & Gentile, C. (2011). Operational modal testing and FE model tuning of a cable-stayed bridge. Engineering Structures, 33(6), 2063-2073.

[2] Alba, M., Bernardini, G., Giussani, A., Ricci, P. P., Roncoroni, F., Scaioni, M., Valgoi, P., & Zhang, K. (2008). Measurement of dam deformations by terrestrial interferometric techniques. Int.Arch.Photogramm.Remote Sens.Spat.Inf.Sci, 37(B1), 133-139.

[3] Michel, C., & Keller, S. (2021). Advancing ground-based radar processing for bridge infrastructure monitoring. Sensors, 21(6), 2172.

How to cite: Sotoudeh, S., Lantini, L., Munisami, K. J., Alani, A. M., and Tosti, F.: An Investigation into the Acquisition Parameters for GB-SAR Assessment of Bridge Structural Components, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8667, https://doi.org/10.5194/egusphere-egu23-8667, 2023.

EGU23-8762 | ECS | Orals | GI2.1

Joint Interpretation of Multi-Frequency Ground Penetrating Radar and Ultrasound Data for Mapping Cracks and Cavities in Tree Trunks 

Saeed Parnow, Livia Lantini, Stephen Uzor, Amir M. Alani, and Fabio Tosti

As the Earth's lungs, trees are a natural resource that provide, amongst others, food, lumber, and oxygen. Therefore, monitoring these wooden structures with non-destructive testing (NDT) techniques such as ground penetrating radar (GPR) and ultrasound can provide valuable information about inner flaws and decays, which is an essential step for tree conservation.  

In recent years, GPR and ultrasound have been used to delineate the interior architecture of tree trunks [1-3]. However, more research is required to improve results and consequently have a more reliable interpretation. Due to limitations in depth penetration and signal-to-noise ratio [4], these approaches have a limited capacity for resolving features. The use of gain functions and higher frequencies to compensate for wave attenuation may exaggerate events and reduce resolution, respectively.

In this context, an integration between GPR multi-frequency and ultrasound data can be used to address this issue. Data were collected on a tree trunk log at the Faringdon Centre for Non-Destructive Testing and Remote Sensing using two high-frequency GPR systems (2GHz and 4GHz central frequencies) and an ultrasound (supporting a wide range of transducers from 24 kHz up to 500 kHz) testing equipment. Internal features of interest in terms of extended perimetric air gaps at the bark-wood interface, natural cracks and small artificial cavities were investigated through electromagnetic and mechanical waves. After compilation of data, a joint interpretation strategy for data analysis is developed. The processed data were mapped against the cut sections of the tree for validity purposes.

Although study of stand tree trunks would be more challenging, the findings of this research may be applied for wood timbers and pave the way to future research for living tree trunks.

 

Acknowledgements

This research was funded by the Vice-Chancellor’s PhD Scholarship at the University of West London.

 

References

[1] Arciniegas, A., et al., Literature review of acoustic and ultrasonic tomography in standing trees. Trees, 2014. 28(6): p. 1559-1567. 

[2] Giannakis, I., et al., Health monitoring of tree trunks using ground penetrating radar. IEEE Transactions on Geoscience and Remote Sensing, 2019. 57(10): p. 8317-8326.

[3] Espinosa, L., et al., Ultrasound computed tomography on standing trees: accounting for wood anisotropy permits a more accurate detection of defects. Annals of Forest Science, 2020. 77(3): p. 1-13.

[4] Tosti, F., et al., The use of GPR and microwave tomography for the assessment of the internal structure of hollow trees. IEEE Transactions on Geoscience and Remote Sensing, 2021. 60: p. 1-14.

 

How to cite: Parnow, S., Lantini, L., Uzor, S., Alani, A. M., and Tosti, F.: Joint Interpretation of Multi-Frequency Ground Penetrating Radar and Ultrasound Data for Mapping Cracks and Cavities in Tree Trunks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8762, https://doi.org/10.5194/egusphere-egu23-8762, 2023.

EGU23-10874 | ECS | Orals | GI2.1

Ground subsidence risk mapping and assessment along Shanghai metro lines by PS-InSAR and LightGBM 

Long Chai, Xiongyao Xie, Biao Zhou, and Li Zeng

Ground subsidence is a typical geological hazard in urban areas. It endangers the safety of infrastructures, such as subways. In this study, the ground subsidence risk of Shanghai metro lines was mapped and assessed. Firstly, PS-InSAR was used for the ground subsidence survey, and subsidence intensity was divided into five classes according to subsidence velocity. 10 subsidence causal factors were collected and the frequency ratio method was applied to analyze the correlation between subsidence and its causal factors. Then LightGBM model was used to generate a ground subsidence susceptibility map. And receiver operating characteristic curve and area under the curve (AUC) were adopted to assess the model. And AUC is 0.904, which suggests the model's performance is excellent. Finally, a risk matrix was introduced to consider the intensity and susceptibility of ground subsidence. The risk of ground subsidence was mapped and classified into five levels: R1 (very low), R2 (low), R3 (medium), R4 (high), and R5 (very high). The results showed that the risk of subway ground subsidence exhibited a regional-related characteristic. Metro lines located in areas with higher ground subsidence risk levels also had higher ground subsidence risk levels. Meanwhile, the statistical results of subway ground subsidence risk levels showed that subway stations were safer than sections.

How to cite: Chai, L., Xie, X., Zhou, B., and Zeng, L.: Ground subsidence risk mapping and assessment along Shanghai metro lines by PS-InSAR and LightGBM, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10874, https://doi.org/10.5194/egusphere-egu23-10874, 2023.

EGU23-12226 | ECS | Orals | GI2.1

Evaluation of Spectral Mixing Techniques for Geological Mixture in a Laboratory Setup: Insights on the nature of mixing 

Maitreya Mohan Sahoo, Kalimuthu Rajendran, Arun Pattathal Vijayakumar, Shibu K. Mathew, and Alok Porwal

Geological mixtures having endmembers mixed at a fine scale pose a challenge to estimating their fractional abundances. Light incident on these mixtures interacts both at multilayered and surface levels, resulting in volumetric and albedo scattering, respectively. Accounting for these effects necessitates a nonlinear spectral mixing model approach rather than conventional linear mixing. In this study, we evaluate the performances of linear and various nonlinear spectral mixing models for an intimately mixed geological mixture, i.e., a banded hematite quartzite (BHQ) sample. The BHQ sample with distinct endmembers of hematite and quartzite facilitated our study of the behavior of light on two-component nonlinear mixtures. In a laboratory-based experimental setup, we used a spectroradiometer of full spectral range in the visible and near-infrared regions (350 to 2500nm) to acquire a hyperspectral image of the BHQ sample. It was followed by the identification of nonlinearly mixed regions and inferring changes in their spectral features. The nonlinearity induced in these regions was attributed to two significant causes- (1) the fine scale of spectral mixing and (2) the spectroradiometer sensor’s limited ability to spatially distinguish between focused and neighboring points, thereby producing a point spread effect. We observed the effects of nonlinear spectral mixing for our sample by changing the sensor’s height from 1mm to 5mm, to simulate fine and coarse-resolution images, respectively. The spectral mixing was modeled using the existing mapped ground truth fractional abundances and library endmembers’ spectra by linear mixing and established nonlinear techniques of the generalized bilinear model (GBM), polynomial post-nonlinear model (PPNM), kernel-based support vector machines (k-SVMs). The evaluated performance metric of reconstruction error revealed the nonlinearity effect in image pixels through statistical tests and nonlinearity parameters used in these models. It was further observed that the associated nonlinearity increases from fine to coarse-resolution images. The minimum error of image reconstruction was observed for the polynomial post-nonlinear model, with a single nonlinearity parameter and an average reconstruction error (ARE) of 0.05. Our study provided insights into the nature of nonlinear mixing with endmember composition and particle sizes.

How to cite: Sahoo, M. M., Rajendran, K., Pattathal Vijayakumar, A., Mathew, S. K., and Porwal, A.: Evaluation of Spectral Mixing Techniques for Geological Mixture in a Laboratory Setup: Insights on the nature of mixing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12226, https://doi.org/10.5194/egusphere-egu23-12226, 2023.

EGU23-13163 | ECS | Orals | GI2.1

High-resolution grain-size analysis and non-destructive hyperspectral imaging of sediments from the Gaoping canyon levee to establish past typhoon and monsoon activities affecting Taiwan during the late Holocene 

Joffrey Bertaz, Kévin Jacq, Christophe Colin, Zhifei Liu, Maxime debret, Hongchao Zhao, and Andrew Tien-Shun Lin

Non-destructive and high-resolution hyperspectral analyses are widely used in planetary and environmental sciences and in mining exploration. In recent years, the scanning method was applied to lacustrine sediment cores in complement to XRF core scanning. However, this approach was rarely applied to marine sediments. The Gaoping canyon, located south of Taiwan island, is connected to the Gaoping River and is a very active canyon with large sediment transfer capacity. In particular, about 4 typhoon-driven hyperpycnal flows have been recorded by mooring systems in every recent year. Studying their frequency and intensity responding to past climate and environmental changes is a key to understand future tropical storm frequency and related climate variability. Core MD18-3574 was collected on the western levee of the Gaoping canyon and displays numerous fine laminations (millimetric to centimetric) recording the deposition of the gravity flows occurring in the canyon and on the slope. In this study, we combined non-destructive analyses such as XRF core scanning and hyperspectral imaging with high-resolution grain size and XRD bulk mineralogy analyses to understand the sedimentological and geochemical variations at the scale of the laminae. Core MD18-3574 sediments consist mainly of fine silt, presenting an alternance of fine-grained and coarse-grained laminations. The average mean grain size is 13.4 µm ranging from 9 to 20.5 µm. Thick coarser grained laminations are showing grain size distributions and asymmetric sorting of typical turbidite sequence. Grain size and bulk mineralogy display great visual and statistical correlation with XRF (Fe/Ca, Si/Al) and hyperspectral proxies (sediment darkness (Rmean), Clay_R2200). Principal component analyses (PCA) demonstrates that darker laminae are composed of coarser sediments with high Si/Al (quartz and feldspar-rich) and Clay_R2200 values and low Fe/Ca (calcite-rich) resulting from gravity flows.  Inversely, lighter laminae consist of finer sediments with low Si/Al (muscovite and illite-rich), Clay_R2200 and high Fe/Ca resulting from hemipelagic deposition. Thus, such interpretation was extended to the core scale to identify gravity flows deposits layers. Moderate intensity tropical storm frequency is decreasing since the last 4 ka in response to the sea surface temperature (SST) decrease and enhanced East Asian winter monsoon since the middle Holocene. Tropical storm intensity increased after 2 ka in La Niña like periods indicating that the surge of super-typhoons hitting Taiwan could be triggered by El Niño Southern Oscillation (ENSO) state and variability. We can then assess that tropical storm activity is controlled by SST, monsoon system and ENSO conditions. This study brings new insights in the prediction of the ongoing climate change impacts on storms activity in the western Pacific Ocean.

How to cite: Bertaz, J., Jacq, K., Colin, C., Liu, Z., debret, M., Zhao, H., and Lin, A. T.-S.: High-resolution grain-size analysis and non-destructive hyperspectral imaging of sediments from the Gaoping canyon levee to establish past typhoon and monsoon activities affecting Taiwan during the late Holocene, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13163, https://doi.org/10.5194/egusphere-egu23-13163, 2023.

EGU23-13329 | ECS | Orals | GI2.1

Combined use of NDT methods for steel rebar corrosion monitoring 

Giacomo Fornasari, Federica Zanotto, Andrea Balbo, Vincenzo Grassi, and Enzo Rizzo

This paper describes laboratory tests performed with an NDT geophysical methods: Ground Penetrating Radar (GPR), Self Potential (SP) and Direct Current (DC) methods in order to monitor the corrosion of a rebar embedded in concrete. Even if the GPR is a common geophysical method for reinforced concrete structures, the SP and DC techniques are not widely used. Rebar corrosion is one of the main causes of deterioration of engineering reinforced structures and this degradation phenomena reduces their service life and durability. Non-destructive testing and evaluation of the rebar corrosion is a major issue for predicting the service life of reinforced concrete structures.

Several new experiments were performed at Applied Geophysical laboratory of University of Ferrara, following the experiences coming from previous tests (Fornasari et al., 2022), where two reinforced concrete samples of about 50 cm x 30 cm were cast, with a central ribbed steel rebar of 10 mm diameter and 35 cm long, were partially immersed in a plastic box with salty and distilled water. In this experiment, we applied a new protocol, where an epoxy resin was used in order to focalize the corrosion only along the exposed part of the rebar. The steel rebar was partially painted with a waterproof resin in order to leave only the central part uncovered for a length of 8 cm. The same waterproof epoxy resin was applied on part of the concrete sample, in order to have a specific chlorides diffusion across a freeway zone of about 10cm x 8cm defined below the exposed rebar.

The experiments were carried out on two identically constructed reinforced concrete samples, exposed to distilled water (sample “A”) and the second, exposed to a salty water with chlorides (sample “B”). Both samples were partially immersed for only 1 cm form the lower surface. The sample B was immersed in a salty water plastic box with different NaCl concentrations. An initial NaCl concentration of 0.1 % was adopted for 7 days, then the concentration was increased to 1% and finally to 3.5% for further 7 days. The experiment was set up in two phases. In the first phase of this study, we monitored the "natural" corrosion occurred on sample "B" due to the diffusion of chlorides towards the steel rebar comparing the obtained data with those of sample "A" exposed to distilled water. In the second phase of the study, accelerated corrosion was applied to sample "B" in order to induce an increment of the corrosion phenomena. The accelerated corrosion was designed in order to reach different theoretical levels of mass weight loss in the steel rebar, which were of 2%, 5%, 10% and 20%. During the experiments, 2GHz C-Thrue GPR antenna, Multivoltmeter with non-polarized calomel referenced electrode for SP and ABEM Terrameter LS for resistivity data, were used to monitor the rebar corrosion monitoring. The collected data were used for an integration observation to detect the evolution of the corrosion phenomenon on the reinforcement steel rebar and to define a quantitative analysis of the phenomena.

 

How to cite: Fornasari, G., Zanotto, F., Balbo, A., Grassi, V., and Rizzo, E.: Combined use of NDT methods for steel rebar corrosion monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13329, https://doi.org/10.5194/egusphere-egu23-13329, 2023.

EGU23-13720 | ECS | Posters on site | GI2.1

A fully customizable data management system for Built Cultural Heritage surveys through NDT 

Irene Centauro, Teresa Salvatici, Sara Calandra, and Carlo Alberto Garzonio

A fully customizable data management system for Built Cultural Heritage surveys through NDT

The diagnosis of Built Cultural Heritage using non-invasive methods is useful to deepen the understanding of building characteristics, assessing the state of conservation of materials, and monitoring over time the effectiveness of restoration interventions.

Ultrasonic and sonic tests are Non-Destructive Techniques widely used to evaluate the consistency of historic masonry and stone elements and to identify on-site internal defects such as voids, detachments, fractures. These tests, in addition to being suitable for Cultural Heritage because they are non-invasive, provide a fundamental preliminary screening useful to better address further analysis.

Ultrasonic and Sonic velocity tests performed on monuments involve a lot of different information obtained from many surveys.  It is therefore important to optimize the amount of data collected both during documentation and diagnostic phase, making them easily accessible and meaningful for analysis and monitoring. In addition, investigations set-up should be following a standard methodology, repeatable over time, suitable for different types of artifacts, and prepared for comparison with other techniques.

An integrated data management system is then also useful to support the decision-making processes behind maintenance actions.

This work proposes the development of a complete management IT solution for the Ultrasonic and Sonic measurements of different types of masonry, and stone artifacts. The system consists of a browser-based collaboration and document management platform, a mobile/desktop application for data entry, and a data visualization and reporting tool. This set of tools enable the complete processing of data, from the on-site survey to their analysis and visualization.

The proposed methodology allows the standardization of the data entry workflow, and it is scalable, so it can be adapted to different types of masonry and artifacts. Moreover, this system provides real-time verification of data, optimizes survey and analysis times, and reduces errors. The platform can be integrated with machine learning models, useful to gain insight from data.

This solution, aimed to improve the approach to diagnostics of Cultural Heritage, has been successfully applied by the LAM Laboratory of the Department of Earth Sciences (University of Florence) on different case studies (e.g., ashlar, frescoed walls, plastered masonries, stone columns, coat-of-arms, etc.) belonging to many important monuments.

How to cite: Centauro, I., Salvatici, T., Calandra, S., and Garzonio, C. A.: A fully customizable data management system for Built Cultural Heritage surveys through NDT, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13720, https://doi.org/10.5194/egusphere-egu23-13720, 2023.

EGU23-13934 | Orals | GI2.1

Pavements Layered Media Characterizations using deep learning-based GPR full-wave inversion 

Li Zeng, Biao Zhou, Xiongyao Xie, and Sébastien Lambot

The possibility to estimate accurately the subsurface electric properties of the pavements from ground-penetrating radar (GPR) signals using inverse modeling is obstructed by the appropriateness of the forward model describing the GPR subsurface system. In this presentation, we improved the recently developed approach of Lambot et al. whose success relies on a stepped-frequency continuous-wave (SFCW) radar combined with an off-ground monostatic transverse electromagnetic horn antenna. The deep-learning based method were adopted to train an intelligent model including the waveform of the Green’s functions. The method was applied and validated in laboratory conditions on a tank filled with a two-layered sand subject to different water contents. Results showed agreement between the predictions of measured Green’s functions deep-learning model and the measured ones. Model inversions for the dielectric permittivity and heights of antenna further demonstrated for a comparison of presented method.

How to cite: Zeng, L., Zhou, B., Xie, X., and Lambot, S.: Pavements Layered Media Characterizations using deep learning-based GPR full-wave inversion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13934, https://doi.org/10.5194/egusphere-egu23-13934, 2023.

EGU23-14658 | Orals | GI2.1

Influence of tectonic deformation on the mechanical properties of calcareous rocks: drawbacks of the non-destructive techniques  

Elisa Mammoliti, Veronica Gironelli, Danica Jablonska, Stefano Mazzoli, Antonio Ferretti, Michele Morici, and Mirko Francioni

Discontinuity surfaces are well known to influence the mechanical behaviour of rocks under compression. Non-destructive techniques, such as ultrasonic pulse velocity and sclerometers, are increasingly used to estimate uniaxial compressive strength of rocks. In this study, several core samples derived from the doubling works of the railway network near Genga (Marche Region, Central Italy) were analysed in order to assess the influence of the structural geological context (proximity to folds, faults etc.) and tectonic deformation on rock strength. Tests were conducted in rock specimens through: i) conventional uniaxial compressive experiment, ii) non-destructive rebound-based methods such as Schmidt Hammer and Equotip  and iii) ultrasound. In this way, it was possible to make a critical analysis of the use of these techniques in the estimation of the uniaxial compressive strength (considering also information about discontinuity type, orientation and nature of the filling). Finally, a petrographic analysis using optical microscope has been undertaken as a support to the observations derived from the analysis at the sample scale. The results indicate that there are two main factors influencing the strength at the scale of the specimen. The first and most decisive factor is the presence of natural pre-existing fractures. The second is the tectonic deformation ratio: the greater the deformation is, the little the strength. Furthermore, through the combined use of uniaxial compressive experiment, non-destructive rebound-based methods and ultrasounds it was possible to highlights the advantages and limitations of each technique and define/propose new guidelines for their use. 

How to cite: Mammoliti, E., Gironelli, V., Jablonska, D., Mazzoli, S., Ferretti, A., Morici, M., and Francioni, M.: Influence of tectonic deformation on the mechanical properties of calcareous rocks: drawbacks of the non-destructive techniques , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14658, https://doi.org/10.5194/egusphere-egu23-14658, 2023.

EGU23-14846 | ECS | Orals | GI2.1

Combined NDT data for road management through BIM models 

Luca Bertolini, Fabrizio D'Amico, Antonio Napolitano, Jhon Romer Diezmos Manalo, and Luca Bianchini Ciampoli

One of the main priorities for road administrations and stakeholders is the management and monitoring of critical infrastructures, especially transportation infrastructures. In this context, Building Information Modeling (BIM) can be one of the more effective methodologies to be used to optimize the management process. In Italy, several laws and regulations have been issued, making the use of BIM procedures mandatory for the design of new infrastructures and emphasizing its role in the management of existing civil works [1, 2].

Monitoring operations of transportation infrastructures are generally conducted by on-site surveys. Non-Destructive Testing methods (i.e., GPR, LiDAR, Laser Profilometer, InSAR, etc.) have been used to perform these inspections as their outputs have been proven to be effective in determining the conditions of the infrastructure and its assets [3]. Moreover, BIM methodology could prove a valuable tool to manage the data provided by these surveys, as it consists in the creation of digital models capable of containing information related to the object that they are representing. These models can be used to store over time the different information obtained by the NDT surveys to carry out integrated analysis on the conditions of the infrastructure [4].

This study aims to analyze a potential BIM process capable of integrating different NDT surveys’ outputs, to generate an informative digital model of an infrastructure and its assets. The proposed methodology is then able to merge the data provided by the inspections, which is typically obtained by different operators and comes in different file formats, in a single BIM model. The main goal of the research is to provide a process to optimize the management procedures of transportation infrastructures, by creating digital models capable of reducing the problems typically associated with the monitoring and maintenance of these critical civil works. By merging different information in a single environment and relying on survey data that are commonly analyzed separately, an integrated analysis of the infrastructure can be carried out and data loss can be reduced.

The study was developed by relying on real data, obtained from on-site surveys carried out over Italian infrastructures. As different outputs have been collected, BIM models of different assets of the analyzed infrastructures were defined. Preliminary results have shown that the proposed methodology can be a viable tool for optimizing the management process of these critical civil works.

Acknowledgements

The research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017. Prot. 20179BP4SM.

References

[1] MIT, 2018. Ministero delle Infrastrutture e dei Trasporti, D. Lgs 109/2018

[2] MIT, 2021. Ministero delle Infrastrutture e dei Trasporti, D.M. 312/2021

[3] D’Amico F. et al., 2020. Integration of InSAR and GPR Techniques for Monitoring Transition Areas in Railway Bridges. NDT&E Int

[4] D’Amico, F. et al., 2022. Integrating Non-Destructive Surveys into a Preliminary BIM-Oriented Digital Model for Possible Future Application in Road Pavements Management. Infrastructures 7, no. 1: 10

How to cite: Bertolini, L., D'Amico, F., Napolitano, A., Manalo, J. R. D., and Bianchini Ciampoli, L.: Combined NDT data for road management through BIM models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14846, https://doi.org/10.5194/egusphere-egu23-14846, 2023.

EGU23-14899 | ECS | Orals | GI2.1

Fusion of in-situ and spaceborne sensing for environmental monitoring 

Konstantinos Karyotis, Nikolaos Tsakiridis, and George Zalidis

Measuring soil reflectance in the field, rather than in a laboratory setting, can be very useful when it comes to numerous applications such as mapping the distribution of various soil properties, especially when prompt estimations are needed.  Recent advances in spectroscopy, and specifically in the development of low-cost Micro-Electro-Mechanical-Systems (MEMS) based spectrometers, pave the way for developing real-time applications in agriculture and environmental monitoring. Compared to high-end spectrometers, whose spectral range extends from Visible (VIS) and Near-InfraRed (NIR) to Shortwave InfraRed (SWIR), MEMS cover limited parts of the electromagnetic spectrum resulting in missing important information. In parallel, new space missions such as Planet Fusion are operationally ready and provide optical imagery (RGB and NIR) with high spatial (3m) and temporal (daily) resolution. To this end, we assessed the potential of augmenting the bands captured from a commercial MEMS sensor (Spectral Engines Nirone S2.2 @ 1750 – 2150 nm) by adjoining the Planet Fusion bands at the exact sampling date and location that in-situ scans originate.

Employing the above, a set of portable MEMS was used at a pilot area in Cyprus (Agia Varvara, Nicosia district) to develop a regional in-situ Soil Spectral Library (SSL). A set of 60 distinct locations were selected for capturing in situ spectral reflectance after the stratification of Planet Fusion pixels of the pilot area, while a physical soil sample was analyzed at the laboratory for the determination of Soil Organic Carbon (SOC) content. During the visit, topsoil moisture was also measured.

The resulting SSL, containing the in-situ spectra, SOC, and moisture content was further augmented by the 4 bands of Planet Fusion imagery acquired on the exact date of the field visit. At this stage, three Random Forest models for SOC content estimation were fitted using as explanatory variables initially only the MEMS data with moisture content, then Planet Fusion bands, and finally all three available inputs.

The results presented an observable decrease in RMSE of SOC content estimations when fusing in-situ with spaceborne data, highlighting the importance of the information contained at VIS-NIR when modeling SOC. On the other hand, the synergy of the two sensors is mutually beneficial; SOC absorption bands can also be found in the SWIR region and are hard to detect with remote sensing means since they fall within the strong water absorption region (around 1950 nm). MEMS-based systems operating at the SWIR part can support this process, and if combined with ancillary environmental measurements such as soil moisture, can provide a cost-effective solution for measuring SOC and other soil-related parameters. To loosen the necessity of laboratory analysis, it is necessary to establish protocols and guidelines for spectral data collection and management to ensure that the data collected is consistent and of high quality and develop representative SSLs that can be used to serve different modeling scenarios. 

How to cite: Karyotis, K., Tsakiridis, N., and Zalidis, G.: Fusion of in-situ and spaceborne sensing for environmental monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14899, https://doi.org/10.5194/egusphere-egu23-14899, 2023.

EGU23-14981 | ECS | Orals | GI2.1

Implementation of a Digital Twin integrating remote sensing information for network-level infrastructure monitoring 

Antonio Napolitano, Valerio Gagliardi, Luca Bertolini, Jhon Romer Diezmos Manalo, Alessandro Calvi, and Andrea Benedetto

Nowadays, there is an emerging demand from public authorities and managing bodies, to evaluate the overall health of infrastructures and identify the most critical transport assets. Considering the national-scale level, thousands of transport infrastructure are in critical conditions and require urgent maintenance actions. Currently, most of available Digital Twins (DT) allow to explore and visualize data including limited kind of information. This issue still limits the operative and practical use by infrastructure owners, that require fast solutions for managing several amount of data. Moreover, this idea is perfectly in line with European and national actions related to the development of a DT of the earth’s systems, including the “DestinE” programme of the European Commission by EUSPA and the European Space Agency (ESA). For this purpose, a dynamic DT model of a critical infrastructure is developed, using the available data about design information, historical maintenance operations and monitoring surveys based on satellite imageries.

In this context, this study presents an innovative concept of Digital Twin, which integrates all the details coming from NDTs surveys, on-site inspections and satellite-based information, to store, manage and visualize valuable information. This is made possible by analysing the main several gaps and limitations of existing platforms, providing a viable integrated solution developing an upgradable strategic analysis tool. To this purpose, remote sensing methods are identified as viable technologies for continuous monitoring operations. More specifically, data coming from satellites and the processing techniques, such as the Multi-Temporal SAR Interferometry approach, are strategic for the continuous monitoring of the displacements associated to transport infrastructures. An advantage of these techniques is the lighter data-processing required for the assessment of displacements and the detection of critical areas [1, 2].

The study introduces two main levels of innovation. The first one is associated to the integrated approach for transportation planning, integrating quantitative data from multi-sources, into the more traditional territorial analysis models. The second one is related to the technological engineering discipline, and it consists of the fusion of observation data from multi-source, with the last-generation dynamic data connected to the environment.

Acknowledgements

This research is supported by the Project “M.LAZIO”, accepted and funded by the Lazio Region, Italy.

References

[1] D'Amico, F. et al., “Implementation of an interoperable BIM platform integrating ground based and remote sensing information for network-level infrastructures monitoring”, Spie Remote Sensing 2022.

[2] Gagliardi, V. et al., “Bridge monitoring and assessment by high-resolution satellite remote sensing technologies”, Spie Future Sensing Technologies 2020.

How to cite: Napolitano, A., Gagliardi, V., Bertolini, L., Manalo, J. R. D., Calvi, A., and Benedetto, A.: Implementation of a Digital Twin integrating remote sensing information for network-level infrastructure monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14981, https://doi.org/10.5194/egusphere-egu23-14981, 2023.

EGU23-15542 | ECS | Orals | GI2.1

Novel perspectives in transport infrastructure management: Data-Fusion, integrated monitoring and augmented reality 

Valerio Gagliardi, Luca Bianchini Ciampoli, Fabrizio D'Amico, Alessandro Calvi, and Andrea Benedetto

Infrastructure networks are crucial elements to ensure the sustainability of the current development model in which the movement of people and goods is essential. On the other hand, transport assets are increasingly exposed to several issues, including climatic conditions changing, vulnerability and exposure to natural hazards such as hydraulic, geomorphological, landslides and seismic phenomena, which can affect the structural integrity causing damages and deteriorations. The context is made even more serious by the degradation of materials and the progressive ageing of infrastructure, often accelerated by environmental conditions and inadequate, or not always effective, maintenance actions. This requires the investigation of novel methods for the large-scale detection of network-scale linear infrastructures, and simultaneously, of detail to diagnose causes and determine the priorities for the most effective countermeasures.

The proposed solution is based on a Data-Fusion approach, merging data coming from multi-source and multi-scale data, to enhance the interpretation process in a holistic sense. The information comes from spaceborne Multi-temporal SAR Interferometry, complemented by more detailed aerial data, detected by UAVs and Ground Based Non-Destructive Testing Methods, including laser scanner surveys for resolution and digital integrability, high-resolution camera measurements assisted by artificial intelligence for the surface degradation and from prospecting data collected by Ground Penetrating Radar technology. All these data can be simultaneously analyzed into a comprehensive digital platform, providing a useful tool to support operators and public bodies to prioritize maintenance actions.

The digital platform can be investigated also using augmented reality tools, capable of generating and reproducing the Digital Twin of the inspected infrastructure into a real environment. This allows any monitoring evaluation through a diagnostic technique that integrates spatial, aerial, ground-based and geophysical surveys, allowing navigation within the infrastructure. Potential applications are numerous, ranging from mapping of wide areas affected by potential criticality to the definition of the main vulnerabilities related to the seismic and hydraulic risks, the analysis of land changes surrounding the assets following extreme natural events, and the reconstruction of historical deformative trends of roads, railways and bridges through the interpretation of SAR data.

Acknowledgments

This research is supported by the Italian Ministry of Education, University, and Research under the National Project “EXTRA TN”, PRIN2017, Prot. 20179BP4SM. In addition, this research is supported by the Project “MLAZIO” funded by Lazio Region (Italy).

How to cite: Gagliardi, V., Bianchini Ciampoli, L., D'Amico, F., Calvi, A., and Benedetto, A.: Novel perspectives in transport infrastructure management: Data-Fusion, integrated monitoring and augmented reality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15542, https://doi.org/10.5194/egusphere-egu23-15542, 2023.

EGU23-16471 | ECS | Orals | GI2.1

Hydrogen isotope fractionation between leaf wax compounds and source water in tropical angiosperms 

Amrita Saishree, Shreyas Managave, and Vijayananda Sarangi

The hydrogen isotope fractionation between leaf wax compounds and source water, the apparent fractionation (εapp), necessary for the reconstruction of hydrogen isotopic composition (δD) of precipitation, is mainly assessed through field and transect studies. The current εapp dataset, however, exhibit a bias toward mid-latitude regions of the Northern Hemisphere. Here we report the results of an outdoor experiment wherein four evergreen and three deciduous species were grown with water of known δD value (-1.8‰) in a tropical semi-arid monsoon region. This allowed us to estimate εapp more accurately and also quantify εapp variability within a species and among different species. Among-species εapp values varied by -119 ± 23‰ (for n-alkane of chain length n-C31) and -126 ± 27‰   (for n-alkanoic acid of chain length n-C30). The similarity of the among-species variability in εapp reported here and that observed in field and transect studies suggested the species-effect, rather than uncertainty in δD of source water, control the uncertainty in community-averaged εapp. The fractionation of  δD between n-C29 alkane and n-C30 alkanoic acid (ε29/30) and between n-C31 alkane and n-C32 alkanoic acid (ε31/32) were 7 ± 25‰ and 6 ± 15‰, respectively, suggesting minimal fractionation of hydrogen isotopes during decarboxylation. Further, as we did not observe a systematic difference between the εapp of deciduous and evergreen species; changes in the relative proportion of this vegetation in a community might not affect its εapp value.

How to cite: Saishree, A., Managave, S., and Sarangi, V.: Hydrogen isotope fractionation between leaf wax compounds and source water in tropical angiosperms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16471, https://doi.org/10.5194/egusphere-egu23-16471, 2023.

EGU23-16632 | ECS | Orals | GI2.1

Development of a flexible 2D DC Resistivity modelling technique for use in space domain 

Deepak Suryavanshi and Rahul Dehiya

Geoelectric non-destructive imaging and monitoring of the earth's subsurface requires robust and adaptable numerical methods to solve the governing differential equation. Most of the time, the DC data is acquired along a straight line. Hence, we solve the DC problem for the 2D case. But the source for the DC method exhibits a 3D nature. To account for the source's 3D nature, the 2D DC resistivity modeling is often carried out in the wavenumber domain. There have been studies that suggest ways for the selection of optimum wavenumbers and weights. But, this does not guarantee a universal choice of wavenumbers. The chosen wavenumbers and related weights strongly influence the precision of the resulting solution in the space domain. Many forward modeling studies demonstrate that selecting effective wavenumbers is challenging, especially for complicated models with topography, anisotropy, and significant resistivity differences. Moreover, forward modeling requires many wavenumbers as the models get more complex. 

This study focuses on developing a method that can completely omit wavenumbers for 2D DC resistivity modeling. The present work finds its motivation in a numerical experiment on a simple half-space model. Since the analytical response for such a model can be easily calculated, we match the analytical solution against the responses obtained from various wavenumbers and weights used in the literature. All the responses deviated from the analytical solution after a certain distance, and none of them were found to be accurate for large offsets. It was discovered after thorough testing of the numerical scheme that the wavenumbers selected for the forward modeling significantly impacted how practical the approach is for large offsets. 

To overcome this problem, a new boundary condition is derived and implemented in the existing numerical scheme. The numerical scheme chosen to perform the forward modeling is Mimetic Finite Difference Method (MFDM). We consider that the source is placed on the origin of the coordinate system. This removes the dependency of the source term, expressed in the Fourier domain, on the wavenumber. The solution obtained by solving the resulting equation will be an even function of the wavenumber and be real-valued. This ensures that the potential in the space domain for the 2D model will also be a real-valued even function with a symmetry about a plane perpendicular to the strike direction and passing through the origin. Because the first-order derivative of an even function at the plane of symmetry vanishes, mathematically, it can be expressed as a Neumann boundary condition at the considered plane. Therefore, we propose a scheme to solve the 2D resistivity problem in the space domain using the boundary condition mentioned here.

The developed algorithm is tested on isotropic and anisotropic two-layer models with large contrasts. It is found that the numerical solutions obtained using the modified boundary condition described above show considerable accuracy even for large offsets when compared with the analytical solution. On the other hand, the results obtained using available wavenumbers in the literature are also compared and are found to deviate considerably from the analytical solution at large offsets.

How to cite: Suryavanshi, D. and Dehiya, R.: Development of a flexible 2D DC Resistivity modelling technique for use in space domain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16632, https://doi.org/10.5194/egusphere-egu23-16632, 2023.

Approximately eight years ago, after a research activity that I started in the nineties on the application of GPR and, later, of NDTs to civil engineering, I realized that no technology can be considered as self standing. This is the consequence of the high complexity related to the civil engineering works and to the highly unpredictable impacts of ordinary processes and exceptional natural events. At the beginning of this century it was clear that a reliable and comprehensive monitoring of a phenomenon affecting bridges, tunnels, structures, or any civil engineering work is possible only by integrating data from different sources.

GPR was at that time a very promising technology, and many investigated in this field measuring e.g. pavement deformation, asphalt moisture, ballast degradation, also the mechanical properties of materials. The accurate outcomes represent a great step forward for the science in this sector, but the final results demonstrated to be partial, because the approach failed under a holistic perspective.

So, in the second decade of 2000, the need of a novel paradigm for investigation raised, in order not only to identify and quantify the problem, but also to diagnose its causes.

It was the stimulus to fuse data from different NDTs, under the assumption that information A and B give much more than A+B. It means that one information (A) can be explanatory of one or more characters contained in a second (B) that cannot be inferred by the knowledge of only one single standing information (B).

Based on this I decided, with very high level international colleagues, to establish a new session at EGU. It was the 2018. Today the sixth edition!

During these years a number ranging from 80 to 120 of researchers took part to each session. Also the number of countries involved is impressive, ranging for each session from 10 to 17. The institutions ranged from 36 to 50.

The number of contributions presented in the five editions is 141.

After 2018 we have seen several special issues of prominent journals were dedicated to data fusion. Recently, beyond the typical technologies as GPR, UT, ERT, a great attention was given to Lidar, Satellite and UAV.

Data fusion was also directed to other interesting and promising fields as archaeology, agriculture, urban planning, only to cite a few.

I would like to underline that this great interest started in Europe and in USA, but actually the geographical coverage is much wider and it includes at a same level also Asiatic and emerging countries.

There is now a new frontier that has to be. My vision is that this holistic approach can be used to develop an innovative immersive environment through the integration in augmented reality platforms on which a digital twin can be generated and dynamically upgraded through an adaptive interface, as well as using AI and machine learning paradigms.

How to cite: Benedetto, A.: Data fusion in civil engineering: personal experience, vision and historical considerations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16864, https://doi.org/10.5194/egusphere-egu23-16864, 2023.

Building Information Modeling is a software-based parametric design approach that allows a full interoperability between the various actors involved in a design or management process. Notwithstanding It has been specifically created for buildings projects, its use has been adapted to a wide range of applications, including transport infrastructure design and, more recently, cultural heritage. In regard to this field, it has been mainly applied to raise accuracy and effectiveness of restoring and stabilization activities for historical architectures.
The present study aims at demonstrating how the use of BIM may return remarkable outcomes in improving the current quality level of digital valorisation and virtual reconstructions of historical structures, especially when their rate of conservation is limited. Indeed, even though current digital reconstruction models are, usually, verified under an archaeological perspective, their structural consistency is never tested. This involves that many virtual reconstruction models are likely to represent structures that are historically accurate but that have no structural sense as, according to their geometric features and the construction materials/techniques, they would not stand their weight.
In this perspective, this study proposes a novel BIM-based methodology capable of both driving the archaeological reconstruction hypotheses and testing the reconstruction hypotheses on a structural basis. The model can be schematically represented by the following process:
1- Survey of the emerging: acquisition of data from superficial archaeological surveys (topographic data, laser scanner, aero photogrammetry, satellite images)
2- Survey of the hidden: acquisition of data from hypogeal surveys (georadar, electrical tomography, magnetometry);
3- Mechanical characterization: gathering of information concerning the materials of the find, proven in their mechanic qualities also through load stress tests;
4- Virtual reconstruction: proposal of a possible hypothesis of virtual reconstruction linked to structural and morphological features known to be present in the referred historical periods;
5- Structural test: engineering and structural confirmation of the forwarded hypothesis by means of finite element algorithms.
The proposed methodology was tested on the archaeological area of the Villa and Circus of Maxentius along the Ancient Appian Way in Rome; all the planned activities have been shared and authorized by the Sovrintendenza Capitolina ai Beni Culturali, within the context of the Project BIMHERIT, funded by Regione Lazio (DTC Lazio Call, Prot. 305-2020-35609).

How to cite: Santarelli, R. and Ten, A.: Integration of non-destructive surveys for BIM-based and structural-verified digital reconstruction of archaeological sites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17489, https://doi.org/10.5194/egusphere-egu23-17489, 2023.

In the wake of Chernobyl and Fukushima accidents radiocesium has become a radionuclide of most environmental concern. The ease with which this radionuclide moves through the environment and is taken up by plants and animals is governed by its chemical forms and site-specific environmental characteristics. Distinctions in climate and geomorphology, as well as 137Cs speciation in the fallout result in differences in migration rates of 137Cs in the environment and rates of its natural attenuation. In Fukushima areas 137Cs was found to be strongly bound to soil and sediment particles, its bioavailability being reduced as a result.  Up to 80% of the deposited 137Cs on the soil were reported to be incorporated in hot glassy particles (CsMPs) insoluble in water. Disintegration of these particles in the environment is much slower than of Chernobyl-derived fuel particles. The higher annual precipitation and steep slopes in Fukushima contaminated areas are conducive to higher erosion and higher total radiocesium wash-off. Typhoons Etou in 2015 and Hagibis in 2019 demonstrated the pronounced redistribution of 137Cs on river watersheds and floodplains, and in some cases natural self-decontamination occurred. Among the common features in 137Cs behavior in Chernobyl and Fukushima is a slow decrease in 137Cs activity concentration in small, closed, and semi-closed lakes and its particular seasonal variations: increase in summer and decrease in winter.

How to cite: Konoplev, A.: Fukushima and Chernobyl: similarities and differences of radiocesium behavior in the soil-water environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1081, https://doi.org/10.5194/egusphere-egu23-1081, 2023.

After the Fukushima nuclear accident, atmospheric 134Cs and 137Cs measurements were taken in Fukushima city for 8 years, from March 2011 to March 2019. The airborne surface concentrations and deposition of radiocesium (radio-Cs) were high in winter and low in summer; these trends are the opposite of those observed in a contaminated forest area. The effective half-lives of 137Cs in the concentrations and deposition before 2015 (0.754 and 1.30 years, respectively) were significantly shorter than those after 2015 (2.07 and 4.69 years, respectively), which was likely because the dissolved radio-Cs was discharged from the local terrestrial ecosystems more rapidly than the particulate radio-Cs. In fact, the dissolved fractions of precipitation were larger than the particulate fractions before 2015, but the particulate fractions were larger after 2016. X-ray fluorescence analysis suggested that biotite may have played a key role in the environmental behavior of particulate forms of radio-Cs after 2014. 

Resuspension of 137Cs from the contaminated ground surface to the atmosphere is essential for understanding the long-term environmental behaviors of 137Cs. We assessed the 137Cs resuspension flux from bare soil and forest ecosystems in eastern Japan in 2013 using a numerical simulation constrained by surface air concentration and deposition measurements. In the estimation, the total areal annual resuspension of 137Cs is 25.7 TBq, which is equivalent to 0.96% of the initial deposition (2.68 PBq). The current simulation underestimated the 137Cs deposition in Fukushima city in winter by more than an order of magnitude, indicating the presence of additional resuspension sources. The site of Fukushima city is surrounded by major roads. Heavy traffic on wet and muddy roads after snow removal operations could generate superlarge (approximately 100 μm in diameter) road dust or road salt particles, which are not included in the model but might contribute to the observed 137Cs at the site.

The current presentation based on the two published papers: Watanabe et al., ACP, https://doi.org/10.5194/acp-22-675-2022 (2022) and Kajino et al., ACP, https://doi.org/10.5194/acp-22-783-2022 (2022). The presenters would like to thank all of the co-authors of the two papers for their significant contributions.

How to cite: Kajino, M. and Watanabe, A.: Eight-year variations in atmospheric radiocesium in Fukushima city and simulated resuspension from contaminated ground surfaces in eastern Japan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1607, https://doi.org/10.5194/egusphere-egu23-1607, 2023.

EGU23-2540 | Posters on site | GI2.2

Hydrological setting control 137Cs and 90Sr concentration at headwater catchments in the Chornobyl Exclusion Zone 

Yasunori Igarashi, Yuichi Onda, Koki Matsushita, Hikaru Sato, Yoshifumi Wakiyama, Hlib Lisovyi, Gennady Laptev, Dmitry Samoilov, Serhii Kirieiev, and Alexei Konoplev

Concentration-discharge relationships are widely used to understand the hydrologic processes controlling river water chemistry. We investigated how hydrological processes affect radionuclide concentrations (137Cs and 90Sr) in surface water in the headwater catchment at the Chornobyl exclusion zone in Ukraine. In flat wetland catchment, the depth of saturated soil layer changed little throughout the year, but changes in saturated soil surface area during snowmelt and immediately after rainfall affected water chemistry by changing the opportunities for contact between suface water and the soil surface. On the other hand, slope catchments with little wetlands, the water chemistry in river water is formed by changes in the contribution of "shallow water" and "deep water" due to changes in the water pathways supplied to the river. Dissolved and suspended 137Cs concentrations did not correlate with discharge rate or competitive cations, but the solid/liquid ratio of 137Cs showed a significant negative relationship with water temperature, and further studies are needed in terms of sorption/desorption reactions. 90Sr concentrations in surface water were strongly related to water pathways for each the catchments. The contact between surface water and the soil surface and the change in the contribution of shallow and deep water to stream water could changes 90Sr concentrations in surface water for in wetland and slope catchments, respectively. In this study, we revealed that the radionuclide concentrations in rivers in Chornobyl is strongly affected by the water pathways at headwater catchments.

How to cite: Igarashi, Y., Onda, Y., Matsushita, K., Sato, H., Wakiyama, Y., Lisovyi, H., Laptev, G., Samoilov, D., Kirieiev, S., and Konoplev, A.: Hydrological setting control 137Cs and 90Sr concentration at headwater catchments in the Chornobyl Exclusion Zone, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2540, https://doi.org/10.5194/egusphere-egu23-2540, 2023.

EGU23-2561 | Posters on site | GI2.2

Dispersion of particle-reactive elements caused by the phase transitions in scavenging 

Kyeong Ok Kim, Vladimir Maderich, Igor Brovchenko, Kyung Tae Jung, Sergey Kivva, Katherine Kovalets, and Haejin Kim

A generalized model of scavenging of the reactive radionuclide 239,240Pu was developed, in which the sorption-desorption processes of oxidized and reduced forms on multifraction suspended particulate matter are described by first-order kinetics. One-dimensional transport-diffusion-reaction equations were solved analytically and numerically. In the idealized case of instantaneous release of 239,240Pu on the ocean surface, the profile of concentrations asymptotically tends to the symmetric spreading bulge in the form of a Gaussian moving downward with constant velocity. The corresponding diffusion coefficient is the sum of the physical diffusivity and the apparent diffusivity caused by the reversible phase transitions between the dissolved and particulate states. Using the method of moments, we analytically obtained formulas for both the velocity of the center mass and apparent diffusivity. It was found that in ocean waters that have oxygen present at great depths, we can consider in the first approximation a simplified problem for a mixture of forms with a single effective distribution coefficient, as opposed to considering the complete problem. This conclusion was confirmed by the modeling results for the well-ventilated Eastern Mediterranean. In agreement with the measurements, the calculations demonstrate the presence of a maximum that is slowly descending for all forms of concentration. The ratio of the reduced form to the oxidized form was approximately 0.22-0.24. At the same time, 239,240Pu scavenging calculations for the anoxic Black Sea deep water reproduced the transition from the oxidized to reduced form of 239,240Pu with depth in accordance with the measurement data.

How to cite: Kim, K. O., Maderich, ., Brovchenko, ., Jung, . T., Kivva, ., Kovalets, ., and Kim, .: Dispersion of particle-reactive elements caused by the phase transitions in scavenging, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2561, https://doi.org/10.5194/egusphere-egu23-2561, 2023.

EGU23-3049 | ECS | Posters on site | GI2.2

Changes in Air Dose Rates due to Soil Water Content in Forests in Fukushima Prefecture, Japan 

Miyu Nakanishi, Yuichi Onda, Hiroaki Kato, Junko Takahashi, Hikaru Iida, and Momo Takada

Radionuclides released and deposited by the 2011 Fukushima Daiichi Nuclear Power Plant accident caused an increase in air dose rates in forests in Fukushima Prefecture. It has been reported that air dose rates increase during rainfall, but we found that air dose rates decreased during rainfall in forests in Fukushima. This is said to be due to the shielding effect of soil moisture. This study aimed to develop a method for estimating changes in air dose rates due to rainfall even in the absence of soil moisture data. Therefore, we used the preceding rainfall (Rw), an indicator that also takes into account past rainfall; we calculated Rw in Namie-Town, Futaba-gun, Fukushima Prefecture from May to July 2020, and estimated air dose rates. In this area, air dose rates decreased with increasing soil moisture. Furthermore, air dose rates could be estimated by combining Rw with a half-life of 2 hours and 7 days, and by considering hysteresis in the absorption and drainage processes. The coefficient of determination (R2) exceeded 0.70 for the estimation of soil water content at this time. Furthermore, good agreement was also observed in the estimation of air dose rates from Rw (R2 > 0.65). The same method was used to estimate air dose rates at the Kawauchi site from May to July 2019. Due to the high water repellency of the Kawauchi site, the increase in soil water content was very small and the change in air dose rate was almost negligible when soil water content was less than 15% and rainfall was less than 10 mm. This study enabled the estimation of soil water content and air dose rate from rainfall and captured the effect of rainfall on the decreasing trend of air dose rate. Therefore, in the future, This study can be used as an indicator to determine whether temporary changes in air dose rates are caused by influences other than rainfall. This study also contributes to the improvement of methods for estimating external dose rates for humans and terrestrial animals and plants in forests.

How to cite: Nakanishi, M., Onda, Y., Kato, H., Takahashi, J., Iida, H., and Takada, M.: Changes in Air Dose Rates due to Soil Water Content in Forests in Fukushima Prefecture, Japan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3049, https://doi.org/10.5194/egusphere-egu23-3049, 2023.

Wet scavenging modeling remains a challenge of the atmospheric transport of 137Cs following the Fukushima Daiichi Nuclear Power Plant accident, which significantly influences the detailed spatiotemporal 137Cs distribution. Till now, numerous wet deposition schemes have been proposed for 137Cs, but it is often difficult to evaluate them consistently, due to the limited resolution of meteorological field data and detailed differences in model implementations. This study evaluated the detailed behavior of 25 combinations of in- and below-cloud wet scavenging models in the framework of the Weather Research and Forecasting-Chemistry model, using high-resolution (1 km × 1 km) meteorological input. The above implementation enables consistent evaluation with great details, revealing complex local behaviors of these combinations. The 1-km-resolution simulations were compared with simulations obtained previously using 3-km-resolution meteorological field data, with respect to the rainfall pattern of the east Japan during the accident, atmospheric concentrations acquired at the regional SPM monitoring sites and the total ground deposition. The capability of these models in reproducing local-scale observations were also investigated with a local-scale observations at the Naraha site, which his only 17.5 km from the Fukushima Daiichi Nuclear Power Plant. The performance of the ensemble mean was also evaluated. Results revealed that the 1-km simulations better reproduce the cumulative rainfall pattern during the Fukushima accident than those revealed by the 3-km simulations, but showing with spatiotemporal variability in accuracy. And rainfall below 1 mm/h is critical for the simulation accuracy. Those single-parameter wet deposition models that rely solely on the rainfall showed improvements in performance in the 1-km simulations relative to that in the 3-km simulations, because of the improved rainfall simulation in the 1-km results. Those multiparameter models that rely on both cloud and rainfall showed more robust performance in both the 3-km and -1km simulations, and the Roselle–Mircea model presented the best performance among the 25 models considered. Besides rainfall, wind transport showed substantial influence on the removal process of atmospheric 137Cs, and it was nonnegligible even during periods in which wet deposition was dominant. The ensemble mean of the 1-km simulations better reproduces the high deposition area and the total deposition amount is closer to the observations than the 3-km simulation. At the local scale, the 1-km-resolution simulations effectively reproduced the 137Cs concentrations observed at the Naraha site, but with deviations in peak timing, mainly because of biased wind direction. These findings indicate the necessity of a multi-parameter model for robust regional-scale wet deposition simulation and a refined wind and dispersion model for local-scale simulation of 137Cs concentration.

How to cite: Zhuang, S., Dong, X., Xu, Y., and Fang, S.: Modeling and sensitivity study of wet scavenging models for the Fukushima accident using 1-km-resolution meteorological field data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4152, https://doi.org/10.5194/egusphere-egu23-4152, 2023.

EGU23-4697 | ECS | Orals | GI2.2

Quantifying the riverine sources of sediment and associated radiocaesium deposited off the coast of Fukushima Prefecture 

Pierre-Alexis Chaboche, Wakiyama Yoshifumi, Hyoe Takata, Toshihiro Wada, Olivier Evrard, Toshiharu Misonou, Takehiko Shiribiki, and Hironori Funaki

The Fukushima-Daiichi Nuclear Power Plant (FDNPP) accident trigged by the Great East Japan Earthquake and subsequent tsunami in March 2011 released large quantities of radionuclides in terrestrial and marine environments of Fukushima Prefecture. Although radiocaesium (i.e. 134Cs and 137Cs) activity in these environments has decreased since the accident, the secondary inputs via the rivers draining and eroding the main terrestrial radioactive plume were shown to sustain high levels of 137Cs in riverine and coastal sediments, which are likely deposited off the coast of the Prefecture. Accordingly, identifying the sources of sediment is required to elucidate the links between terrestrial and marine radiocaesium dynamics and to anticipate the fate of persistent radionuclides in the environment.

The objective of this study is to develop an original sediment source tracing technique to quantify the riverine sources of sediment and associated radionuclides accumulated in the Pacific Ocean. Target coastal sediment cores (n=6) with a length comprised between 20 and 60cm depth were collected during cruise campaigns between July and September 2022 at the Ota (n=2), Niida (n=1) and Ukedo (n=3) river mouths. Prior to gamma spectrometry measurements, sediment cores were opened and cut into 2 cm increments, oven-dried at 50°C for at least 48 hours, ground and passed through a 2-mm sieve.

Preliminary results regarding the spatial and depth distribution of radiocaesium in these samples show a strong heterogeneity, with highest radiocaesium levels (up to 134 ± 2 and 4882 ± 11 Bq kg-1 for 134Cs and 137Cs, respectively) found in coastal sediment cores located at the Ukedo river mouth. On the opposite, no trace or low levels of Fukushima-derived radiocaesium were found in the Niida and in one sediment core of the Ota River mouths. Additional measurements will be conducted to determine the physico-chemical properties of this sediment, in order to select the optimal combination of tracers, which will then be introduced into un-mixing models. This increase knowledge will undoubtedly be useful for watershed and coastal management in the FDNPP post-accidental context.

How to cite: Chaboche, P.-A., Yoshifumi, W., Takata, H., Wada, T., Evrard, O., Misonou, T., Shiribiki, T., and Funaki, H.: Quantifying the riverine sources of sediment and associated radiocaesium deposited off the coast of Fukushima Prefecture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4697, https://doi.org/10.5194/egusphere-egu23-4697, 2023.

EGU23-4925 | Posters on site | GI2.2

Verification of reproductivity of 137Cs activity concentration in the database by an ocean general circulation model 

Daisuke Tsumune, Frank Bryan, Keith Lindsay, Kazuhiro Misumi, Takaki Tsubono, and Michio Aoyama

Radioactive cesium (137Cs) is distributed in the global ocean due to global fallout from atmospheric nuclear tests, release from reprocessing plants in Europe, and supply to the ocean due to the Fukushima Daiichi Nuclear Power Plant accident. In order to detect future contamination by radionuclides, it is necessary to understand the global distribution of radionuclides such as 137Cs. For this purpose, the IAEA is compiling a database of observation results (MARIS). However, since the spatio-temporal densities of observed data vary widely, it is difficult to obtain a complete picture from the database alone. Comparative validation using ocean general circulation model (OGCM) simulations is useful in interpreting these observations, and global ocean general circulation model (CESM2, POP2) simulations were conducted to clarify the behavior of 137Cs in the ocean. The horizontal resolution is 1.125° longitude and 0.28° to 0.54° latitude. The minimum spacing near the sea surface is 10 m, and the spacing increases with depth to a maximum of 250 m with 60 vertical levels. Climatic values were used for driving force. As a source term for 137Cs to the ocean, atmospheric fallout from atmospheric nuclear tests was newly established based on rainfall data and other data, and was confirmed to be more reproducible than before. Furthermore, the release from reprocessing plants in Europe and the leakage due to the accident at the Fukushima Daiichi Nuclear Power Plant were taken into account. 2020 input conditions were assumed to continue after 2020, and calculations were performed from 1945 to 2030. The simulated 137Cs activities were found to be in good agreement, especially in the Atlantic and Pacific Oceans, where the observed densities are large. On the other hand, they were underestimated in the Southern Hemisphere, suggesting the need for further improvement of the fallout data. 137Cs concentrations from the Fukushima Daiichi Nuclear Power Plant accident in March 2011 were generally in good agreement, although the reproducibility remained somewhat problematic due to insufficient model resolution. In other basins, the concentration characteristics were able to be determined, although the observed values were insufficient. Radioactivity concentrations of atmospheric nuclear test-derived 137Cs may continue to be detected in the global ocean after 2030. The results of this simulation are useful for planning future observations to fill the gaps in the database.

How to cite: Tsumune, D., Bryan, F., Lindsay, K., Misumi, K., Tsubono, T., and Aoyama, M.: Verification of reproductivity of 137Cs activity concentration in the database by an ocean general circulation model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4925, https://doi.org/10.5194/egusphere-egu23-4925, 2023.

EGU23-4947 | ECS | Posters on site | GI2.2

Vertical distribution of radioactive cesium-rich microparticles in forest soil of Hamadori area, Fukushima Prefecture 

Takahiro Tatsuno, Hiromichi Waki, Naoto Nihei, and Nobuhito Ohte

A lot of radionuclides were scattered after the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. Previous studies showed that there were FDNPP-derived radioactive cesium-rich microparticles (CsMPs) with the size of a few μm in the soil and river water around Fukushima Prefecture[1]. CsMPs have high radioactive cesium (Cs) concentration per unit mass, therefore they can be one of the factor in overestimating the Cs concentration in samples. Because Cs in CsMPs may not react directly with clay particles unlike the Cs ion in liquid phase, it is considered that CsMPs work as Cs carrier in soils[2]. However, unlike ionic Cs and Cs adsorbed onto clay particles, the distribution and dynamics of CsMPs in soils have not been clarified. In this study, we investigated vertical distribution of CsMPs in the forest soil and the soil properties in Fukushima Prefecture, Japan.

Soil samples were collected from the forest in the difficult-to-return zone, approximately 10 km away from the FDNPP. The undisturbed soil samples were collected from 0-35 cm soil depth at 5 cm intervals using core sampler to investigate soil properties. Furthermore, litter samples on the surface soil layer were collected. Using these samples, the vertical distribution of Cs concentration in the soil and Cs derived from CsMPs were investigated. Cs concentration in samples placed in 100 mL of U8 container was measured using a germanium semiconductor detector. Cs derived from CsMPs was evaluated using an Imaging plate with reference to the method ffor quantification of CsMPs[3].

Like Cs adsorbed on the soil, CsMPs were also mostly distributed in the soil surface layer between o and 5 cm of soil depth. We considered that straining may be one of the mechanism of CsMPs retention on the soil surface. Bradford et al. (2006) [4] showed that straining might be a significant mechanism for colloid retention when the average particle size in the porous medium is less than 200 times larger than the colloidal particle size. In this study, assuming the CsMPs size of approximately 1 µm, the average particle size of the soil collected from surface layer 0-5 cm was less than 200 times that of CsMPs. However, the average particle size decreased in deeper layer than 5 cm, therefore, it was considered that straining mechanism could be stronger.

This work was supported by FY2022 Sumitomo Foundation and FY2022 Internal Project of Institute of Environmental Radioactivity, Fukushima University.

 

References

[1] Igarashi, Y. et al., 2019. J. Environ. Radioact. 205–206, 101–118.

[2]  Tatsuno, T et al., 2022. J. Environ. Manage. 329, 116983.

[3] Ikehara et al., 2018. Environ. Sci. Technol. 52, 6390–6398.

[4] Bradford et al., 2003. Environ. Sci. Technol. 37, 2242–2250.

How to cite: Tatsuno, T., Waki, H., Nihei, N., and Ohte, N.: Vertical distribution of radioactive cesium-rich microparticles in forest soil of Hamadori area, Fukushima Prefecture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4947, https://doi.org/10.5194/egusphere-egu23-4947, 2023.

EGU23-5042 | ECS | Posters on site | GI2.2

Changes in 90Sr transport dynamics in groundwater after large-scale groundwater drawdown in the vicinity of the cooling pond at the Chornobyl Nuclear Power Plant 

Hikaru Sato, Naoaki Shibasaki, Maksym Gusyev, Yuichi Onda, and Dmytro Veremenko

Migration of long-lived radioactive 90Sr introduced by nuclear accidents and radioactive waste requires long-term monitoring and protection management due to its half-life of 28.8 years and high mobility in water. Presently, 37 years have passed since the largest worldwide 90Sr contamination was released and deposited around the Chornobyl Nuclear Power Plant (ChNPP). In the vicinity of the ChNPP, the water level of the cooling pond (CP) has declined since May 2014 following the decommissioning phase of the Unit 3 reactor. The drawdown of the CP lowered the groundwater level in a massive vicinity (about 70 km2), and the change in the groundwater system due to the drawdown has caused concerns about possible changes in 90Sr concentrations in water and transport dynamics to the Pripyat River. Therefore, this study evaluated how 90Sr transport dynamics were influenced due to changes in the groundwater flow system from 2011 to 2020 based on observed data and results of the groundwater flow simulation in the CP vicinity.

The numerical simulation was conducted from 2011 to 2020 on monthly time-step using USGS MODFLOW with PM11 GUI and calibrated to groundwater heads measured at monitoring wells. In the location between the CP and the Pripyat River, estimated pore velocities near the river were reduced compared to velocities before the CP drawdown due to the decrease in the hydraulic gradient between the CP and the river. Decrease in groundwater velocity results decrease in groundwater discharge and delay of 90Sr transport. Therefore, the amount of 90Sr transported from the CP to the river is smaller than the period prior to the CP drawdown. The reduced 90Sr transport is expected to have less impact on the radioactivity in the river water even in the Pripyat River floodplain northwest of the CP where 90Sr concentrations significantly increased after the CP drawdown. In addition, the measured and simulated changes in groundwater flow direction and velocity suggested the possibility of 90Sr accumulation at the floodplain caused by stagnant groundwater from reduced velocity and additional 90Sr infiltration from surrounding ponds located at the Pripyat River floodplain. Therefore, enhancing the current monitoring of 90Sr concentrations near the floodplain would be needed for long-term monitoring and protection management to prevent the risk.

How to cite: Sato, H., Shibasaki, N., Gusyev, M., Onda, Y., and Veremenko, D.: Changes in 90Sr transport dynamics in groundwater after large-scale groundwater drawdown in the vicinity of the cooling pond at the Chornobyl Nuclear Power Plant, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5042, https://doi.org/10.5194/egusphere-egu23-5042, 2023.

The 3D model THREETOX was applied for the long-term simulation of the planned release of radioactively contaminated water from Fukushima storage tanks to marine environment. Two radionuclides were considered: 3H that has the largest activity in tanks and 129I that can caused the largest dose of radiation to human. The constant release rate of 3H equal to 22 TBq/y according to TEPCO estimations and the constant release rate of 129I equal to 361 MBq/y according to estimations from the current study were used in the simulations.

The THREETOX model used monthly averaged currents from the KIOST-MOM model. A dynamic food web model was included in the THREETOX model. In the model, organisms uptake the activity directly from water and through the food chain. The food chain consists of phytoplankton, zooplankton, non-piscivorous (prey) fish, and piscivorous (predatory) fish. In case of 129I, macro-algae was also considered. The modelling area covers Fukushima coastal waters and extends for 1600 km from the coast to the East. From North to South this area extends for 1300 km.

From model results, we can see how contamination will spread along the coast in different seasons. For example, in summer time the currents near the coast are directed to the North that leads to contamination of the Sendai Bay. This means that at different points along the coast, the concentration of radionuclides can periodically change according to currents that change during the year. Calculated concentrations of activity at several points along the coast of Japan, which correspond to largest cities in the area of interest, were extracted from model results. For example, calculated concentration of 3H in water in Tomioka point, which is quite close to FDNPP, sometimes can exceed 200 Bq/m3. In Soma point, the concentration will exceed 50 Bq/m3, while in point Iwaki-Onahama – 20 Bq/m3 at some moments of time. In other points, the calculated concentration of 3H in water will not exceed 10 Bq/m3 that is less than background concentration 50 Bq/m3. Concerning 129I, its maximum concentration in water will be around 10-3 – 10-2 Bq/m3 in points close to FDNPP and around 10-4 Bq/m3 in points further from the NPP that is around 100 000 times less than the calculated concentrations of 3H.

Calculated concentrations of OBT (organically bounded tritium) in predatory and prey fish are less than 0.01 Bq/kg in all points except FDNPP point where it is around 0.02 Bq/kg. This value is 10 times less than measured concentration of OBT in fish (0.2 Bq/kg) that was made in 2014 in the coastal area near the damaged NPP. Calculated concentrations of 129I in predatory and prey fish are in the range 10-6 – 10-4 Bq/kg in all considered points. Concentrations of 129I in macro-algae are about 100 times higher due to ability of iodine to accumulate in macro-algae. 

How to cite: Bezhenar, R., Takata, H., and Maderich, V.: Transport of H-3 and I-129 in water and their uptake by marine organisms due to the planned release of Fukushima storage water, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6019, https://doi.org/10.5194/egusphere-egu23-6019, 2023.

EGU23-6026 | Orals | GI2.2

Dynamic change of dissolved Cs-137 from headwaters to downstream in the Kuchibuto River catchment 

Yuichi Onda, Taichi Kawano, Keisuke Taniguchi, and Junko Takahashi

The Fukushima Daiichi Nuclear Power Plant (FDNPP) accident on March 11, 2011 resulted in the release of large amounts of radioactive cesium-137 (137Cs) into the environment. It is important to characterize the Cs-137 dynamics throughout the river from the headwaters to the downstream. Previous studies have suggested the importance of dissolved forms of Cs-137 in organic matter in small watersheds and dissolved forms in suspended solids in large watersheds. Since the concentration of suspended-form Cs has been shown to decrease significantly after decontamination in evacuated areas (Feng et al. 2022), this rapid decrease in suspended-form Cs-137 concentration can be used to determine the cause of dissolved-form Cs. Therefore, we attempted to evaluate whether the dissolved Cs-137 was derived from organic matter or suspended solids by comparing data before and after decontamination.

 The objective of this study is to compare the decreasing trends of Cs-137 concentrations in decontaminated and undecontaminated areas based on long-term monitoring of suspended solids, dissolved solids, and coarse organic matter Cs-137 concentrations since 2011. The study area includes four headwater basins and four river basins (eight sites in total) in the Kuchibuto River watershed in the Yamakiya district of Fukushima Prefecture, located approximately 35 km northwest of the FDNPP.

In the Kuchibuto River watershed, a large inflow of decontaminated soil with low Cs-137 concentrations due to an increase in the amount of bare land caused by decontamination resulted in a rapid decrease in the concentration of suspended-form 137Cs in the decontaminated area in the headwaters and in the upper reaches of the river. However, no clear effect of decontamination was observed in the concentrations of dissolved Cs-137 and Cs-137 in coarse organic matter. Comparison of the slopes of Cs-137 concentrations in the suspended, dissolved, and coarse organic matter showed that the slope of the dissolved form was similar to that of the coarse organic matter in the source watersheds, and similar to that of the SS in the downstream watersheds. These results suggest that the contribution of dissolved Cs-137 from organic matter in small watersheds and that from suspended solids in large watersheds is significant.

How to cite: Onda, Y., Kawano, T., Taniguchi, K., and Takahashi, J.: Dynamic change of dissolved Cs-137 from headwaters to downstream in the Kuchibuto River catchment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6026, https://doi.org/10.5194/egusphere-egu23-6026, 2023.

EGU23-10093 | Posters on site | GI2.2

Riverine 137Cs dynamics and remoralization in coastal waters during high flow events 

Yoshifumi Wakiyama, Hyoe Takata, Keisuke Taniguchi, Takuya Niida, Yasunori Igarashi, and Alexei Konoplev

Understanding riverine 137Cs dynamics during high-flow events is crucial for improving predictability of 137Cs transportation and relevant hydrological responses. It is frequently documented that the majority of 137Cs is exported during high-flow events triggered by intensive rainfall. Studies on 137Cs in coastal seawater suggested that a huge high-flow events resulted in high dissolved 137Cs concentration in seawater. Different temporal patterns of 137Cs concentrations in river water are found in the existing literature on 137Cs dynamics during high-flow events. Although such differences may reflect catchment characteristics, there is no comprehensive analysis for the relationships. This study explores catchment characteristics affecting 137Cs transport via river to ocean based on datasets obtained by sampling campaigns during high-flow events. 137Cs datasets obtained at 13 points in 6 river water systems were subject to the analysis. The analyses intended to explore relationship between catchment characteristics (scale and land use composition) and 137Cs dynamics in terms of variations in concentration, fluxes, and potential remobilization in seawater. We could not find any significant correlations between the parameters of catchment characteristics and mean values of normalized concentrations of 137Cs and apparent Kd. However, when approximating 137Cs concentrations and Kd value as a power function of suspended solid concentration (Y=α X^β), the power of β in the equations for dissolved 137Cs concentration and Kd showed negative and positive correlations with the logarithm of the watershed area, respectively, and the positive β was found when the catchment area was on the order of 100 km2 or larger and vice versa. This indicates that the concentration of dissolved 137Cs tends to decrease with increased water discharge in larger catchments for smaller catchments. These results suggest that the temporal pattern of dissolved 137Cs concentrations depends on watershed scale. 137Cs flux during a single event ranged from 1.9 GBq to 1.1 TBq and accounted for 0.00074% to 0.22% of total 137Cs deposited in relevant catchments. Particulate 137Cs flux accounted for more than 92% of total 137Cs flux, except for Ukedo River basin with a large dam reservoir. R-factor, an erosivity index in the Universal Soil Loss Equation model family, is a good parameter for reproducing sediment discharge and particulate 137Cs flux. Efficiency of particulate 137Cs flux, calculated by dividing the flux by R-factor of event, tended to be high in catchments with relatively low forest cover. Desorption ratio of 137Cs, obtained by 1-day shaking experiment of SS in seawater, ranged from 2.8 to 6.6%. The ratio was almost proportional of ratio of exchangeable 137Cs. The estimated amounts of desorbed 137Cs, obtained by multiplying particulate 137Cs and the desorption ratios, were greater than direct flux of dissolved 137Cs. Reanalysis of riverine 137Cs dataset in high flow events is revealing relationship between catchment characteristics and 137Cs dynamics. Further analyses, such as evaluation of decontamination impacts and inter-catchment comparisons of 137Cs fluxes, are required for better understanding.

How to cite: Wakiyama, Y., Takata, H., Taniguchi, K., Niida, T., Igarashi, Y., and Konoplev, A.: Riverine 137Cs dynamics and remoralization in coastal waters during high flow events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10093, https://doi.org/10.5194/egusphere-egu23-10093, 2023.

EGU23-10539 | Posters on site | GI2.2 | Highlight

Long-term dynamics of 137Cs accumulation at an urban pond 

Honoka Kurosawa, Kenji Nanba, Toshihiro Wada, and Yoshifumi Wakiyama

It is known that the semi-enclosed water area such as pond and dam reservoir is readily subject to 137Cs accumulation because of the secondary inflow from the catchment area. We present the long-term monitoring data of the 137Cs concentration in bottom sediment and pond water in an urban pond located in the central area of Koriyama City, Fukushima Prefecture to discuss the 137Cs dynamics of the urban pond. The pond was decontaminated by the bottom sediment removal in 2017. The bottom sediment core and pond water were collected in 2015 and 2018-2021. The inflow and outflow water were collected in 2020-2021. The river water around the pond was collected in 2021. The bottom sediment and water samples were measured for 137Cs concentration, particulate size distribution, and N and C stable isotopes. Compared between 2015 and 2018, the 137Cs inventory and 0-10 cm depth of 137Cs concentration in the bottom sediment at 7 points were decreased by 81 % (mean 1.50 to 0.28 MBq/m2) and 85 % (mean 31.5 to 4.8 kBq/kgDW), respectively. Although mean 137Cs inventory in bottom sediment did not drastically change during 2018-2021, its variability became wider. Points with increased 137Cs inventory in bottom sediment showed year-by-year increase in thickness of layer with concentrations higher than 8 kBq/kgDW, a criterion for considered decontamination. The 137Cs concentration in suspended solids (SS) in pond water was lowered after decontamination, although it still remained above 8 kBq/kgDW. The 137Cs concentrations in SS of inflow water were also high, exceeding 8 kBq/kgDW. The 137Cs concentration in SS of the river water around the pond was higher when it passed through the urban area, suggesting that the inflow of particles from urban origin maintained high 137Cs level in the pond. 

How to cite: Kurosawa, H., Nanba, K., Wada, T., and Wakiyama, Y.: Long-term dynamics of 137Cs accumulation at an urban pond, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10539, https://doi.org/10.5194/egusphere-egu23-10539, 2023.

EGU23-10868 | Posters on site | GI2.2

Estimation of annual Cesium-137 influx from the FDNPP to the coastal water 

Shun Satoh and Hyoe Takata

Due to the accident at the Fukushima Daiichi Nuclear Power Plant (1F) in March 2011, radionuclides were introduced into the environment, and one of the release pathways to the ocean is the direct discharge from the 1F (on-going release). This was mainly caused immediately after the accident, but even now, the on-going release is continuing. In this study, firstly we estimated the on-going release of 137Cs from 1F over 10 years after the accident, using the TEPCO’s 137Cs monitoring results in the coastal area around 1F. Secondly, change in the monitoring data related to countermeasures by TEPCO (e.g. construction of iced walls) to reduce the introduction of contaminated water into the ocean or detect 137Cs in nearby seawater, so their effects on the on-going release estimation were also discussed. A box model including inside and outside of the port was assumed for the area around 1F, and the amount of 137Cs in the box was estimated (estimated value: modeled data). Then, the difference between the estimated value and the amount of 137Cs obtained from actual observed concentrations (measured value: monitoring data) was calculated. The result showed that the measured value was higher than the estimated value, suggesting the on-going release from 1F. As for decrease in monitoring data after the countermeasures, it is implied that the estimation of rate of on-going release has been reduced by the countermeasures.

How to cite: Satoh, S. and Takata, H.: Estimation of annual Cesium-137 influx from the FDNPP to the coastal water, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10868, https://doi.org/10.5194/egusphere-egu23-10868, 2023.

EGU23-11671 | Posters on site | GI2.2

Changes in Cs-137 concentrations in river-bottom sediments and their factors in Fukushima Prefecture rivers 

Naoyuki Wada, Yuichi Onda, Xiang Gao, and Chen Tang

The Fukushima Daiichi Nuclear Power Plant accident (FDNPP) in 2011 resulted in the release of large amounts of Cs-137 into the atmosphere. Cs-137 deposited on land was mainly distributed in forests, but some of it has been discharged to the sea through rivers. The dissolved and suspended forms of Cs-137 in rivers have been focused on, and it is known that the discharge mechanism and concentration formation of Cs-137 differ depending on the land use in the river basin. On the other hand, there are few cases that focus on the dynamics of Cs-137 in river bottom sediments. River-bottom sediment is less likely to flow downstream than suspended sediments, so contamination in the downstream area may be long-term.
We will clarify the migration mechanism of Cs-137 in rivers including river-bottom sediment.Therefore, we will analyze data collected from 2011 to 2018 in 89 watersheds in Fukushima prefecture. In analyzing the data, we removed sampling points with brackish water using electrical conductivity and corrected for particle size to standardize the surface area of particles that absorb Cs-137.As a result, it was found that unlike dissolved and suspended forms, the Cs concentration in river-bottom sediments can increase within the initial year. This is related to the average initial deposition in the watershed and the amount of initial deposition at the river-bottom sediment sampling sites, with a tendency to increase with relatively higher initial deposition in the upstream area. It was also known that the decrease in suspended Cs concentration was more pronounced when anthropogenic activities in the watershed were more active, but there was no clear relationship between land use in the watershed and changes in river-bottom sediment Cs concentration. This indicates that suspended sediment Cs concentrations are controlled by initial deposition to suspended sediment production sources, whereas river-bottom Cs concentrations are controlled by multiple factors such as sediment traction and Cs supply from river water.

How to cite: Wada, N., Onda, Y., Gao, X., and Tang, C.: Changes in Cs-137 concentrations in river-bottom sediments and their factors in Fukushima Prefecture rivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11671, https://doi.org/10.5194/egusphere-egu23-11671, 2023.

EGU23-12670 | ECS | Orals | GI2.2

Minimizing the loss of radioactively contaminated sediment from the Niida watershed (Fukushima, Japan) through spatially targeted afforestation. 

Floris Abrams, Lieve Sweeck, Johan Camps, Grethell Castillo-Reyes, Bin Feng, Yuichi Onda, and Jos Van Orshoven

Government-led decontamination of agricultural land in the Fukushima accident (2011) region has lowered the on-site radiation risk considerably. From 2013 to early 2017, 11.9% of the land in the Fukushima disaster affected Niida watershed in Japan was remediated through topsoil removal. However, this resulted in a 237.1% increase in suspended sediment loads in the river for 2016 compared to 2013.  In contrast, sediment loads decreased by 41% from 2016 to 2017; this can be attributed to the effect of natural vegetation restoration on sediment yield and transfer patterns (Bin et al., 2022). Since radiocaesium firmly binds to the clay minerals in the soil, it is inevitably transported along with the sediments downstream to the river systems. These observations confirm that rapid, spatially targeted interventions, such as revegetation, e.g., through afforestation, have the potential to decrease the magnitude and period of increased exports of contaminated sediments. The CAMF tool (Cellular Automata-based Heuristic for Minimizing Flow) (Vanegas et al., 2012) was originally designed to find the cells in a raster representation of a watershed for which afforestation would lead to a maximal reduction of sediment exports with minimal effort or cost while taking sediment flow from cell to cell into account. In our research, we adapted the CAMF tool to account for the radiocaesium budgets associated with the transported sediments. We applied the approach to the Niida catchment, where land-cover changes in upstream decontaminated regions are detected using drone imagery and linked to increased sediment loads in the Niida river using long-term river monitoring systems. For example In 2014, agricultural land (18.02 km2) was one of the major land uses in the regions where decontamination was ordered, resulting in increased sediment loads from 2014 to 2016. By recognizing both the on- and off-site impacts of the remediation interventions and their temporal dynamics, the modified CAMF tool offers scope for supporting the formulation of spatio-temporal schemes for the remediation of agricultural land. These schemes aim to decrease the radiation risk for downstream communities and minimize the potential recontamination of already decontaminated sites.

How to cite: Abrams, F., Sweeck, L., Camps, J., Castillo-Reyes, G., Feng, B., Onda, Y., and Van Orshoven, J.: Minimizing the loss of radioactively contaminated sediment from the Niida watershed (Fukushima, Japan) through spatially targeted afforestation., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12670, https://doi.org/10.5194/egusphere-egu23-12670, 2023.

EGU23-13366 | Orals | GI2.2

Similarity of long-term temporal decrease in atmospheric Cs-137 between Chernobyl and Fukushima 

Kentaro Akasaki, Shu Mori, Eiichi Suetomi, and Yuko Hatano

We compare the atmospheric concentrations of Cs-137 after a decade between Chernobyl and Fukushima cases. We plotted 8 datasets on log-log axes (5 cases in Chernobyl and 3 cases Fukushima) and found that they appear to follow a single function.

There have been measured the atmospheric concentration after the Chernobyl accident for more than 30 years [1]. On the other hand, several teams of Japanese researchers have been measured in Fukushima and its vicinity for almost 10 years. [2][3] In this study, we compare 5 sites in Chernobyl (Pripyat, Chernobyl, Baryshevka, Kiev, and Polesskoe) and 3 sites in Fukushima (FDNPP O-6 and O-7, Univ. Fukushima).

We adjust the magnitude of the data because it depends on the amount of the initial deposition. After the adjustment, we plot the 8 cases on a log-log plot. We found that the 8 cases collapse together, with the power index of -1.6. Namely,

C(t) ~ t^{-1.6}.               …(1)

Incidentally, we have been proposed a formula which reproduce the long-term behavior of atmospheric concentration at a fixed location as

C(t) = A exp(-bt) t^{-4/3}    …(2)

where A is a parameter which relates to the amount of the initial deposition and b as the reaction rate of all the first-order reactions (including the radioactive decay rate, the vegetation uptake rate, the runoff rate, etc). We will investigate the difference in the power-law index in Eq. (1) and (2). The parameter b is highly dependent on the environment. When we take a proper value of b, the apparent decrease of the concentration will change from t^{-4/3}. We may make the apparent power-index close to -1.6.

 

[1] E. K. Garger, et al., J. Env. Radioact., 110 (2012) 53-58.

[2] A. Watanabe, et al., Atmos. Chem. Phys. 22 (2022) 675-692.

[3] T. Abe, K. Yoshimura, Y. Sanada, Aerosol and Air Quality Research, 21 (2021) 200636.

How to cite: Akasaki, K., Mori, S., Suetomi, E., and Hatano, Y.: Similarity of long-term temporal decrease in atmospheric Cs-137 between Chernobyl and Fukushima, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13366, https://doi.org/10.5194/egusphere-egu23-13366, 2023.

EGU23-13486 | ECS | Posters virtual | GI2.2

Distributions of tritium in the marine water and biota around Rokkasho Reprocessing Plant 

Satoru Ohtsuki, Yuhei Shirotani, and Hyoe Takata

For decommissioning of Fukushima Daiichi Nuclear Power Station (FDNPS), it is one of the biggest problems to treat the radioactive contaminated stagnant water in the building. It is difficult to remove H-3 from the contaminated water by only Advanced Liquid Processing System (ALPS) treatment. Thus, the Japanese Government announced to release the ALPS treated water containing H-3. To predict the alteration of the dose rate of the marine biota by the change of H-3 concentration in marine water after the release of ALPS water, it is necessary to understand the dynamics of H-3 in marine ecosystem. In this study, we studied the behavior of H-3 in the marine environment (water and biota) off Aomori and Iwate prefectures from FY2003 to FY2012, as the background data of the Pacific Ocean along the coast of the North East Japan. To clarify the dynamics of H-3 in marine biota, we compared H-3 and Cs-137. Excluding the period of the intermittent test operation of the Rokkasho Reprocessing Plant (FY2006-FY2008), the concentration of H-3 in seawater, tissue free water tritium (TFWT) and organically bound tritium (OBT) were 0.052-0.20 Bq/L with a mean of 0.12±0.031 Bq/L, 0.050-0.34 Bq/kg-wet with a mean of 1.1±0.039 Bq/kg-wet and 0.0070-0.099 Bq/kg-wet with a mean of 0.042±0.019 Bq/kg-wet, respectively. Before the FDNPS accident (FY2003-FY2010), Cs-137 concentration in seawater and marine biota were 0.00054-0.0027 Bq/L with a mean of 0.0016±0.00041 Bq/L and 0.022-1.8 Bq/kg-wet with a mean of 0.090±0.037 Bq/kg-wet, respectively. Concentration Ratio (CR), the ratio of the concentration of marine biota and seawater for TFWT, was to be 0.34-2.37 with a mean of 0.97±0.31 in all spices, meaning the concentration of marine biota was almost equal to seawater. For Cs-137, CR were 46-78 with a mean of 56±22. We compared CRs for TFWT of Gadus macrocephalus, Lophius litulon and Oncorhynchus keta with those of Cs-137. Comparing CR-TFWT and CR-Cs-137 for these three species, Spearman-R was <0.4 and p was >0.05, indicating that the dynamics of TFWT and Cs-137 in marine ecology is decoupled.

How to cite: Ohtsuki, S., Shirotani, Y., and Takata, H.: Distributions of tritium in the marine water and biota around Rokkasho Reprocessing Plant, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13486, https://doi.org/10.5194/egusphere-egu23-13486, 2023.

EGU23-15515 | Posters on site | GI2.2

137Cs transport flux to surface water due to shallow groundwater discharge from forest hillslope 

Yuma Niwano, Hiroaki Kato, Satoru Akaiwa, Donovan Anderson, Hikaru Iida, Miyu Nakanishi, Yuichi Onda, Hikaru Sato, and Tadafumi Niizato

Groundwater systems and surface water can interact in a complex manner that influences catchment discharge, which then becomes more complex in forest slopes. A large amount of Radioactive cesium (137Cs) deposited on forests due to the Fukushima Daiichi Nuclear Power Plant accident remains in terrestrial environments and is transported downstream as suspended or dissolved forms by surface water. Generally, the concentration of dissolved 137Cs in surface water increases especially during runoff. While the leaching behavior of 137Cs from contaminated forest materials and soils to surface water has been heavily studied, the influence of 137Cs concentration in shallow groundwater systems in forest slopes have not been investigated. Therefore, detailed hydrological observations of groundwater on a forest hillslope will enable quantitative analysis of the influence of groundwater flow on the formation of dissolved 137Cs concentrations in surface water during base flow and during runoff. Our results showed that the dissolved 137Cs concentration in surface water increases during water discharge. The average concentration of dissolved 137Cs in shallow groundwater was 0.64 Bq/L, which was higher than that in surface water (average 0.10 Bq/L). Furthermore, it was also observed that a part of the shallow groundwater on the slope moves toward the river channel at the time of water runoff. This suggests that shallow groundwater may have flowed into the surface water during the outflow and contributed to the increase of 137Cs in the surface water. In this study, the contribution of groundwater in forest slopes to the dissolved 137Cs concentration in surface water was estimated using the hydrodynamic gradient distribution of groundwater in forest slopes and the measured dissolved 137Cs concentration in groundwater.

How to cite: Niwano, Y., Kato, H., Akaiwa, S., Anderson, D., Iida, H., Nakanishi, M., Onda, Y., Sato, H., and Niizato, T.: 137Cs transport flux to surface water due to shallow groundwater discharge from forest hillslope, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15515, https://doi.org/10.5194/egusphere-egu23-15515, 2023.

Understanding, modeling and predicting the future of the Earth System in response to global change is a challenge for the Earth system scientific community, but a necessity to address pressing societal needs related to the UN Sustainable Development Goals and risk monitoring and prediction. These “wicked” environmental problems require the building of integrated modeling tools . The latter will only provide reliable response if they integrate all existing multi-disciplinary data sources. Open science and data sharing using the FAIR (Findable, Accessible, Interoperable, Reusable) principles provide the framework for such data sharing. However, when trying to put it into practice, we face a large fragmentation of the landscape, with different communities having developed their own data management systems, standards and tools.

When starting to work on the Theia/OZCAR Information System (IS) that aims to Facilitate the discovery, to make FAIR, in-situ data of continental surfaces collected by French research organizations and their foreign partners, we performed a “Tour de France” to understand the critical zone science users’ needs when searching for data. The common criterion that emerged was the variables names. We believe that this need is general to all disciplines involved in Earth System sciences and is all the more important when data is searched by scientists of other disciplines that are not familiar with the vocabularies of the other communities. This abstract aim is to share our experience in building the tools aiming at harmonizing and sharing variables names using FAIR principles.

In the Theia/OZCAR critical zone research community, long term observatories that produce the data have heterogeneous data description practices and variable names. They may be different for the same variable (i.e.: "soil moisture", "soil water content", "humidité des sols", etc.). Moreover, it is not possible to infer automatically or semi-automatically similarities between these variables names. In order to identify these similarities and implement data discovery functionalities on these dimensions in the IS, we built the Theia/OZCAR variable thesaurus. To enable technical interoperability of the thesaurus, it is published on the web using the SKOS vocabulary description standard. Other thesauri used in environmental sciences in Europe and worldwide have been identified and the definition of associative relationships with these vocabularies ensures the semantic interoperability of the Theia/OZCAR thesaurus. However, it is quite common that the variable names used for the search dimensions remain general (e.g. "soil moisture") and are not specific enough for the end user to interpret exactly what has been measured (e.g. "soil moisture at 10 cm depth measured by TDR probe"). Therefore, to improve data reuse and interoperability, the thesaurus now follows a recommendation of the Research Data Alliance and implements the I-ADOPT framework to describe the variables more precisely. Each variable is composed and described by relationships with atomic concepts whose definition is specified. The use of these atomic concepts enhances interoperability with other catalogues or services and contributes to the reuse of the data by other communities that those who collected them.

How to cite: Braud, I., Coussot, C., Chaffard, V., and Galle, S.: Theia/OZCAR Thesaurus: a terminology service to facilitate the discovery, interoperability and reuse of data from continental surfaces and critical zone science in interdisciplinary research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1099, https://doi.org/10.5194/egusphere-egu23-1099, 2023.

EGU23-1294 | Posters on site | GI2.3

A data integration system for ocean climate change research in the Northwest Pacific 

Sung Dae Kim, Hyuk Min Park, Young Shin Kwon, and Hyeon Gyeong Han

A data integration and processing system was established to provide long-time data and real-time data to the researcher who are interested in long-term variation of ocean data in the Northwest Pacific area. All available ocean data of 6 variables (ocean temperature, salinity, dissolved oxygen, ocean CO2, nutrients) in the NWP area (0°N - 65°N, 95°E - 175°E) are collected from the Korean domestic organizations (KIOST, NFIS, KHOA, KOEM), the international data systems (WOD, GTSPP, SeaDataNet, etc.), and the international observation networks (Argo, GOSHIP, GLODAP, etc.). Total number of data collected is over 5 millions and observation dates are from 1938 to 2022. After referring to several QC manuals and related papers, QC procedures and test criteria for 6 data items were determined and documented. Several Matlab programs complying with QC procedures were developed and used to check quality of all collected data. We excluded duplicated data from the data set and saved them in 0.25° grid data files. Long-term average over 40 years and standard deviation of data at each standard depths and grid point were calculated. All quality controlled data, qc flag, average, standard deviation of each ocean variables are saved in format of netCDF and provided to ocean climate researchers and numerical modelers. We also have 2 plans using the collected data from 2023 to 2025. The one is production of long-term grid data set focused on the NWP area, the other is developing a data service system providing observation data and reanalysis data together.

Acknowledgement : This research was supported by Korea Institute of Marine Science & Technology Promotion(KIMST) funded by the Ministry of Oceans and Fisheries(KIMST-20220033)

How to cite: Kim, S. D., Park, H. M., Kwon, Y. S., and Han, H. G.: A data integration system for ocean climate change research in the Northwest Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1294, https://doi.org/10.5194/egusphere-egu23-1294, 2023.

EGU23-1599 | Posters on site | GI2.3

Overview of the services provided to marine data producers by ODATIS, the French ocean data center 

Sabine Schmidt, Erwann Quimbert, Marine Vernet, Joël Sudre, Caroline Mercier, Dominique Obaton, Jean-François Piollé, Frédéric Merceur, Gérald Dibarboure, and Gilbert Maudire

The consequences of global change on the ocean are multiple such as increase in temperature and sea level, stronger storms, deoxygenation, impacts on ecosystems. But the detection of changes and impacts is still difficult because of the diversity and variability of marine environments. While there has been a clear increase in the number of marine and coastal observations, whether by in situ, laboratory or remote sensing measurements, each data is both costly to acquire and unique. The number and variety of data acquisition techniques require efficient methods of improving data availability via interoperable portals, which facilitate data sharing according to FAIR principles for producers and users. ODATIS, the ocean cluster of Data Terra, the French research infrastructure for Earth data, is the entry point to access all the French Ocean observation data (Ocean Data Information and Services ; www.odatis-ocean.fr/en/). The first challenge of ODATIS is to get data producers to share data. To that purpose, ODATIS offers several services to help them define Data Management Plan (DPM), implement the FAIR principles, make data more visible and accessible by being referenced in the ODATIS catalog, and better tracked and cited through a Digital Object Identifier (DOI). ODATIS also offers a service for publishing open scientific data on the sea, through SEANOE (www.seanoe.org) that provides a DOI that can be cited in scientific articles in a reliable and sustainable way. In parallel to the informatic development of the ocean cluster, further communication and training are needed to inform the research community of these new tools. Through technical workshops, Odatis offers data providers practical experience and support in implementing data access, visualization and processing services. Finally, ODATIS relies on scientific consortia in order to promote and develop innovative processing methods and products for remote, airborne, or in situ observations of the ocean and its interfaces (atmosphere, coastline, seafloor) with the other clusters of the RI Data Terra.

How to cite: Schmidt, S., Quimbert, E., Vernet, M., Sudre, J., Mercier, C., Obaton, D., Piollé, J.-F., Merceur, F., Dibarboure, G., and Maudire, G.: Overview of the services provided to marine data producers by ODATIS, the French ocean data center, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1599, https://doi.org/10.5194/egusphere-egu23-1599, 2023.

EGU23-5626 | Orals | GI2.3

An integration of digital twin technology, GIS and VR for the service of environmental sustainability 

Chen Wang, David Miller, Alessandro Gimona, Maria Nijnik, and Yang Jiang

A digital twin is a digital representation of real-world physical product, system, or process. Digital twins potentially offer a much richer capability to model and analyze real-world systems and improve environment sustainability.

In this work, an integrated 3D GIS and VR model for scenarios modeling and interactive data visualisation has been developed and implemented through the Digital Twin technology at the Glensaugh research farm. Spatial Multi-criteria Analysis has been applied to decide where to plant new woodlands, recognizing a range of land-use objectives while acknowledging concerns about possible conflicts with other uses of the land. The virtual contents (e.g., forest spatial datasets, monitored climate data, analyzed carbon stocks and natural capital asset index) have been embedded in the virtual landscape model which help raise public awareness of changes in rural areas.

The Digital twin prototype for Glensaugh Climate-Positive Farming was used at the STFC workshop 2021, GISRUK 2022, 2022 Royal Highland Show which provides an innovative framework to integrate spatial data modelling, analytical capabilities and immersive visualization.

Audience feedback suggested that the virtual environment was very effective in providing a more realistic impression of the different land-use and woodland expansion scenarios and environmental characteristics. This suggests considerable added value from using digital twin technology to better deal with complexity of data analysis, scenarios simulation and enable rapid interpretation of solutions.

Findings show this method has a potential impact on future woodland planning and enables rapid interpretation of forest and climate data which increases the effectiveness of their use and contribution to wider sustainable environment.

How to cite: Wang, C., Miller, D., Gimona, A., Nijnik, M., and Jiang, Y.: An integration of digital twin technology, GIS and VR for the service of environmental sustainability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5626, https://doi.org/10.5194/egusphere-egu23-5626, 2023.

EGU23-5866 | ECS | Posters on site | GI2.3

Mapping and Analysis of Anthrax Cases in Humans and Animals 

Tamar Chichinadze, Zaza Gulashvili, Nana Bolashvili, Lile Malania, and Nikoloz Suknidze

Anthrax is a rare but serious disease caused by gram-positive, stem-shaped bacteria Bacillus anthracis, which are toxin-producing, encapsulated, facultative anaerobic organisms. Anthrax is found naturally in the soil and mainly harms livestock and wildlife. It can cause serious illness in both humans and animals. Anthrax, an often fatal disease of animals, is spread to humans through contact with infected animals or their products. People get infected with anthrax when spores get into the body.

The study aims to monitor the anthill localization map of anthrax on geographical maps and identify geographical variables that are significantly associated with environmental risk factors for anthrax recurrence in Georgia (Caucasus), as specific diseases affect the geographical environment, soil, climate. etc.

We carefully analyzed a set of 1664 cases of anthrax in humans and 621 cases of anthrax in animals, up to 1430 locations in anthrax foci (animal burial sites, slaughterhouses, BP roads, construction, etc.) observed in Georgia. Literature and the National Center for Disease Control for over 70 years. We analyzed more than 30 geographical variables such as climate, topography, soil (soil type, chemical composition, acidity), landscape, etc., and created several digital thematic maps, and foci of ant distribution and detection. The identified variable will help you to monitor anthrax development foci.

How to cite: Chichinadze, T., Gulashvili, Z., Bolashvili, N., Malania, L., and Suknidze, N.: Mapping and Analysis of Anthrax Cases in Humans and Animals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5866, https://doi.org/10.5194/egusphere-egu23-5866, 2023.

EGU23-6357 | Posters on site | GI2.3

PANAME: a portal laboratory for city's environmental data 

Vincent Douet, Sophie Bouffiès-Cloché, Joanne Dumont, Martial Haeffelin, Jean-Charles Dupoont, Simone Kotthaus, Valéry Masson, Aude Lemonsu, Valerie Gros, Christopher Cantrell, Vincent Michoud, and Sébastien Payan

The urban is at the heart of many disciplinary projects covering very broad scientific areas. Acquired data or simulations are often accessible (when they are) via targeted thematic portals. However, the need for transdisciplinarity has been essential for several years to answer specific scientific questions or societal demands. For this, the crossing of human sciences data, health, air quality, land use, emissions inventories, biodiversity, etc., would allow new innovative studies in connection with the city.

PANAME (PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch) developed by AERIS was designed as the first brick of a data portal that can promote the discovery, access, cross-referencing and representation of urban data from various sectors with air quality and urban heat islands as a starting point. The portal and future developments will be discussed in this presentation.

How to cite: Douet, V., Bouffiès-Cloché, S., Dumont, J., Haeffelin, M., Dupoont, J.-C., Kotthaus, S., Masson, V., Lemonsu, A., Gros, V., Cantrell, C., Michoud, V., and Payan, S.: PANAME: a portal laboratory for city's environmental data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6357, https://doi.org/10.5194/egusphere-egu23-6357, 2023.

EGU23-6873 | Posters on site | GI2.3

From local to global: Community services in interdisciplinary research data management  

Hela Mehrtens, Janine Berndt, Klaus Getzlaff, Andreas Lehmann, and Sören Lorenz

GEOMAR research covers a unique range of physical, chemical, biological and geological ocean processes. The department Digital Research Services develops and provides advice and tools to support scientific data workflows, including metadata description of expeditions, model experiments, lab experiments, and samples. Our focus lies on standardized internal data exchange in large interdisciplinary scientific projects and citable data and software publications in discipline specific repositories to meet the FAIR principles. GEOMAR aims at providing their services not only internally but as a collaborative RDM platform for marine projects as a community service. How to achieve this on the operational level is currently worked on jointly with other research institutions in community projects, e.g. within the DAM (German Alliance of Marine Research), the DataHUB, an initiative of several research centres within the Helmholtz research area Earth and Environment, and within the national research infrastructure NFDI4Earth, a network of more than 60 partners.  

Our latest use cases are the inclusion of the seismic data and numerical model simulations into the community portals to increase their visibility and reusability. We present the success stories and pitfalls of bringing a locally well established system in larger communities and address the challenges we are facing. 

How to cite: Mehrtens, H., Berndt, J., Getzlaff, K., Lehmann, A., and Lorenz, S.: From local to global: Community services in interdisciplinary research data management , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6873, https://doi.org/10.5194/egusphere-egu23-6873, 2023.

EGU23-7015 | ECS | Orals | GI2.3

Evaluation of five reanalysis products over France: implications for agro-climatic studies 

Mariam Er-rondi, Magali Troin, Sylvain Coly, Emmanuel Buisson, Laurent Serlet, and Nourddine Azzaoui

Agriculture is extremely vulnerable to climate change. Increase in air temperature alongside the more frequent extreme climate events are the main climate change’s negative impacts influencing the yields, safety, and quality of crops. One approach to assess the impacts of climate change on agriculture is the use of agro-climatic indicators (AgcIs). Agcls characterize plant-climate interactions and are practical and understandable for both farmers and decision makers.

Climate and climate change impact studies on crop require long samples of reliable past and future datasets describing both spatial and temporal variability. The lack of observed historical data with an appropriate temporal resolution (i.e., 30 years of continuous daily data) and a sufficient local precision (i.e., 1km) is a major concern. To overcome that, the reanalysis products (RPs) are often used as a potential reference data of observed climate in impact studies. However, RPs have some limitations as they contain some biases and uncertainties. In addition, the RPs’ evaluation is often conducted on climate indicators which raises questions about their suitability for agro-climatic indicators.

This work aims to evaluate the ability of five of the most used RPs to reproduce observed AgcIs for three specific crops (i.e., apple, corn, and vine) over France. The five RPs selected for this study are the SCOPE Climate, FYRE Climate, ERA5, ERA5 Land and the gridded dataset RFHR. They are compared to the SYNOP meteorological data provided by Météo-France, considered as a reference dataset from 1996 to 2021.

Our findings show a higher agreement between the five RPs and SYNOP for the temperature-based Agcls than the precipitation-based Agcls. RPs tend to overestimate the precipitation-based Agcls. We also note that, for each RP, the discrepancies between the AgcIs and the reference SYNOP dataset do not depend on the geographical location or the crop. This study emphasizes the need to quantify uncertainty in climate data in climate variability and climate change impact studies on agriculture.

How to cite: Er-rondi, M., Troin, M., Coly, S., Buisson, E., Serlet, L., and Azzaoui, N.: Evaluation of five reanalysis products over France: implications for agro-climatic studies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7015, https://doi.org/10.5194/egusphere-egu23-7015, 2023.

We present a method for publishing high performance compute (HPC) code and results in a scalable, portable and ready-to-use interactive environment in order to enable sharing, collaborating, peer-reviewing and teaching. We show how we utilize cloud native elements such as kubernetes, containerization, automation and webshells to achieve this and demonstrate such an OpenScienceLab for the MAGE (Multiscale Atmosphere Geospace Environment) model, being developed by the recently selected NASA DRIVE Center for Geospace Storms.
We argue that a key factor in the successful design of such an environment is its (cyber)-security, as  these labs require non-trivial compute resources open to a vast audience. Benefits as well as implied costs of different hosting options are discussed, comparing public cloud, hybrid, private cloud and even large desktops.
We encourage HPC centers to test our method using our fully open source blueprints. We hope to thus unburden the research staff and scientists to follow FAIR principles and support open source goals without needing a deep knowledge of cloud computing.

How to cite: Roedig, C. and Sorathia, K.: Cloud native OpenScienceLabs for HPC : Easing the road to FAIR collaboration and OpenSource, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7703, https://doi.org/10.5194/egusphere-egu23-7703, 2023.

EGU23-8585 | Orals | GI2.3

Programmatic Update for NASA’s Commercial Smallsat Data Acquisition (CSDA) Program 

Aaron Kaulfus, Alfreda Hall, Manil Maskey, Will McCarty, and Frederick Policelli

Established in 2017 as a pilot project, the NASA Commercial Smallsat Data Acquisition (CSDA) Program evaluates and acquires commercial datasets that compliment NASA Earth Science research and application goals. The success of the pilot and recognition of the value commercial data provide to the scientific community led to establishment of a sustained program within NASA’s Earth Science Division (ESD) with objectives of providing continuous on-ramp of new commercial vendors to evaluate the potential to advance NASA’s Earth science research and application activities, enable sustained use of the purchased data by the scientific community, ensure long-term preservation of purchased data for scientific reproducibility, and coordinate with other U.S. Government agencies and international partners on the evaluation and use of commercial data. This presentation will focus on data made available for scientific use through the CSDA Program, especially those datasets added since the conclusion of the original pilot project, describe the process for end users to access of CSDA managed datasets, and provide a status overview of ongoing and upcoming vendor evaluation activities will be given. Recent scientific research results from CSDA subject matter experts utilizing commercial data will also be provided.

How to cite: Kaulfus, A., Hall, A., Maskey, M., McCarty, W., and Policelli, F.: Programmatic Update for NASA’s Commercial Smallsat Data Acquisition (CSDA) Program, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8585, https://doi.org/10.5194/egusphere-egu23-8585, 2023.

EGU23-12144 | Orals | GI2.3

FAIR & Open Material Samples: The IGSN ID 

Rorie Edmunds

Material samples are a vital output of the scientific endeavour. They underpin research in the Earth, Space, and Environmental Sciences, and are a necessary component of ensuring the transparency and reproducibility of such research. While there has been a lot of discussion in recent years about the openness and FAIRness of data, code, methods, and so on, material samples have been much less under the spotlight.

The lack of focus on material samples is in part due to them being unique as a research output, in the sense that they are inherently physical and thus they are mostly transported and managed by human beings rather than machines; it is rather more straightforward to archive and share both information about an output—and the output itself—for something that is already a digital object. However, it is for this reason that materials samples must be made more FAIR and treated as first-class citizens of Open Science. To do this, one needs to connect the physical and digital worlds. IGSN IDs enable these connections to be made.

The IGSN ID is a globally unique and persistent identifier (PID) specifically for labelling material samples themselves (i.e., they are for neither images nor data about a sample). Functionally a Digital Object Identifier (DOI) registered under DataCite services, the IGSN ID can be applied to all types of material samples coming from any discipline. Not only can IGSN IDs be used to identify individual material samples that currently exist in a repository, museum, or otherwise, but they can also be registered

  • At the aggregate level for sample collections.
  • For the sites from which the samples are taken.
  • For ephemeral samples.

Importantly, in all cases, when registering an IGSN IDs, one must supply metadata in the DataCite Metadata Schema, as well as create landing pages that supply additional, disciplinary, user-focussed information about the collection, site, or (sub)sample. Hence, by registering a PID for a physical object, it is given a permanently resolvable URI to a findable and accessible digital footprint, and through the provision of rich metadata, enables its interoperability and reusability. Sharing of associated data is also possible within the metadata, and one may even include the potential for relocation of a sample itself for reuse.

This presentation will briefly introduce the IGSN ID and the partnership between DataCite and the IGSN e.V. to transfer the IGSN PID infrastructure under DataCite DOI services. It will mainly highlight practical use cases of IGSN IDs, including what is needed to include them in the sample workflow. It will also talk about efforts to better support IGSN IDs and sample metadata within the DataCite Metadata Schema.

How to cite: Edmunds, R.: FAIR & Open Material Samples: The IGSN ID, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12144, https://doi.org/10.5194/egusphere-egu23-12144, 2023.

EGU23-12173 | Orals | GI2.3

ESPRESSO: Earth Science Problems for the Evaluation of Strategies, Solvers and Optimizers 

Andrew Valentine, Jiawen He, Juerg Hauser, and Malcolm Sambridge

Many Earth systems cannot be observed directly, or in isolation. Instead, we must infer their properties and characteristics from their signature in one or more datasets, using a variety of techniques (including those based on optimization, statistical methods, or machine learning). Development of these techniques is an area of focus for many geoscience researchers, and methodological advances can be instrumental in enhancing our understanding of the Earth.         

In our experience, progress is substantially hindered by the absence of infrastructure facilitating communication between sub-disciplines. Researchers tend to focus on one area of the earth sciences — such as seismology, hydrology or oceanography — with only slow percolation of ideas and innovations from one area to another. Indeed, silos often exist even within these subfields. Testing new ideas on new problems is challenging as it requires the acquisition of domain knowledge, an often difficult and time-consuming endeavour with uncertain returns. Key questions that arise include: What is a relevant field data set, and how has it been processed? Which simulation package is most appropriate to predict the data? What would a 'good' model look like and what should it be able to resolve? What is the current best practice?

To address this, we introduce the ESPRESSO project — a collection of Earth Science Problems for the Evaluation of Strategies, Solvers and Optimisers. It aims to provide  access to a suite of ‘test problems’, spanning a wide range of inference and inversion scenarios. Each test problem defines appropriate dataset(s) and simulation routines, accessible within a standardised Python interface. This will allow researchers to rapidly test new techniques across a spectrum of problems, share domain-specific inference problems and ultimately identify areas where there may be potential for fruitful collaboration and development. ESPRESSO is envisaged as an open, community-sourced project, and we invite contributions from across the geosciences.

How to cite: Valentine, A., He, J., Hauser, J., and Sambridge, M.: ESPRESSO: Earth Science Problems for the Evaluation of Strategies, Solvers and Optimizers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12173, https://doi.org/10.5194/egusphere-egu23-12173, 2023.

EGU23-12381 | ECS | Posters on site | GI2.3 | Highlight

An Exploratory Study on the Methodology for the Analysis of Urban Environmental Characteristics in Seoul City based on S-Dot Sensor Data 

Daehwan Kim, Kwanchul Kim, Dasom Lee, Jae-Hoon Yang, Seong-min Kim, and Jeong-Min Park

This paper identifies the aspects of living environment elements (PM2.5, PM10, Noise) throughout Seoul and the urban planning characteristics that affect them by utilizing the big data of the S-Dot sensor in Seoul, which has recently become a hot topic. In other words, it proposes a big data-based research methodology and research direction to confirm the relationship between urban characteristics and environmental sectors that directly affect citizens.  The temporal range is from 2020 to 2022, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500m*500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning characteristics of each cluster, basic statistical analysis such as ANOA and OLS, and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of PM2.5, PM10, noise and urban planning characteristics that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to studies related to data in various fields related to environmental data in the future.

How to cite: Kim, D., Kim, K., Lee, D., Yang, J.-H., Kim, S., and Park, J.-M.: An Exploratory Study on the Methodology for the Analysis of Urban Environmental Characteristics in Seoul City based on S-Dot Sensor Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12381, https://doi.org/10.5194/egusphere-egu23-12381, 2023.

EGU23-13420 | ECS | Orals | GI2.3

Development of interoperable web applications for paleoclimate research 

Alessandro Morichetta, Anne-Marie Lézine, Aline Govin, and Vincent Douet

Studying how the Earth’s climate changed in the past requires a joint interdisciplinary effort of scientists from different scientific domains. Paleoclimatic records are increasingly obtained on multiple archives (e.g. marine and terrestrial sediments, ice cores, speleothems, corals) and they document past changes in various climatic variables of the different components of the climatic system (e.g. ocean, atmosphere, vegetation, ice). 

Most paleoclimatic records still rely on independent observations with no standard format describing their data or metadata, resulting in a progressive increase of variables and taxonomies. Therefore, despite the achievements of the last decades (e.g. NOAA, NEOTOMA and PANGAEA databases), the lack of a common language strongly limits the systematic reusability of paleoclimate data, for example for the construction of paleoclimatic data syntheses or the evaluation of climate model simulations.

The international project “Abrupt Change in Climate and Ecosystems: Data and e-infrastructure” (ACCEDE, funded by the Belmont Forum) aims at creating an ecosystem for paleoclimatic data in order to investigate the tipping points of past climatic changes. In this context, the recently formalized Linked PaleoData (LiPD) format is the core for the standardization of paleoclimate data and metadata, and it is acting as communication protocol between the different databases that compose the e-infrastructure.

Here we show two web-based solutions that are part of this effort and that take advantage of the LiPD ecosystem. The African Pollen Database, and the IPSL Paleoclimate Database, both hosted and developed by Institut Pierre-Simon Laplace, France, have the objectives (1) to give open access, while respecting the FAIR principles, to a variety of paleoclimate datasets - from pollen fossils to various tracers measured on marine sediments, ice cores or tree rings -, and (2) to combine and compare, using visualization tools, carefully selected and well dated paleoclimatic records from different disciplines to address specific research questions. 

The two databases are the result of data recovery from pre-existing and obsolete archives that followed a process of data (and metadata) consolidation, enrichment and formatting, in order to respect the LiPD specification and ensure the interoperability between them and the already existing databases. We designed harmonised web interfaces and REST APIs to explore and export existing datasets with the help of filtering tools. Datasets are published with DOI under an open license, allowing free access to the completeness of information. A LiPD upload form is embedded to the websites, in order to encourage both users and data stewards to propose, edit, add new records, and to bring the community into the use of LiPD format. We are currently working on finalizing visualization tools to evaluate aggregate data for research and education purposes.

With this effort we are developing a framework in which heterogeneous paleoclimatic records are fully interoperable, allowing scientists from the whole community to take advantage of the completeness of the available data, and to reuse them for very different research applications.

How to cite: Morichetta, A., Lézine, A.-M., Govin, A., and Douet, V.: Development of interoperable web applications for paleoclimate research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13420, https://doi.org/10.5194/egusphere-egu23-13420, 2023.

EGU23-13455 | Posters on site | GI2.3

The Transnational access and training in the Geo-INQUIRE EU-project, an opportunity for researchers to develop leading-edge science at selected facilities and test-beds across Europe 

Gaetano Festa, Shane Murphy, Mariusz Majdanski, Iris Christadler, Fabrice Cotton, Angelo Strollo, Marc Urvois, Volker Röhling, Stefano Lorito, Andrey Babeyko, Daniele Bailo, Jan Michalek, Otto Lange, Javier Quinteros, Mateus Prestes, and Stefanie Weege

The Geo-INQUIRE (Geosphere INfrastructure for QUestions into Integrated REsearch) project, supported by the Horizon Europe Programme, is aimed at enhancing services to make data and high-level products accessible to the broad Geoscience scientific community. Geo-INQUIRE’s goal is to encourage curiosity-driven studies into understanding the geosphere dynamics at the interface between the solid Earth, the oceans and the atmosphere using long data streams, high-performance computing and cutting-edge facilities.

In the framework of Geo-INQUIRE, Transnational Access (TA, both virtual and on-site) will be provided at six test beds across Europe: the Bedretto Laboratory, Switzerland; the Ella-Link Geolab, Portugal; the Liguria-Nice-Monaco submarine infrastructure, Italy/France; the Irpinia Near-Fault Observatory, Italy; the Eastern Sicily facility, Italy; and the Corinth Rift Laboratory, Greece. These test beds are state-of-the-art research infrastructures, covering the Earth’s surface, subsurface, and marine environments over different spatial scales, from small-scale experiments in laboratories to kilometric submarine fibre cables. The TA will revolve around answering scientific key-questions on the comprehension of fundamental processes associated with geohazards and georesources such as: the preparatory phases of earthquakes, the role of the fluids within the Earth crust, the fluid-solid interaction at the seabed, and the impact of geothermal exploitation. TA will be also offered for software and workflows belonging to the EPOS-ERIC and the ChEESE Centre of Excellence for Exascale in Solid Earth, to develop awarded user’s projects. These are grounded on simulation of seismic waves and rupture dynamics in complex media, tsunamis, subaerial and submarine landslides. HPC-based Probabilistic Tsunami, Seismic and Volcanic Hazard workflows are offered to assess hazard at high-resolution with extensive uncertainty exploration. Support and collaboration will be offered to the awardees to facilitate the access and usage of HPC resources for tackling geoscience problems. Geo-INQUIRE will grant TA to researchers to develop their own lab or numerical experiments with the aim of advancing scientific knowledge of Earth processes while fostering cross-disciplinary research across Europe. To be granted, researchers submit a proposal to the yearly TA calls that will be issued three times during the project life. Calls will be advertised at the Geo-INQUIRE web page https://www.geo-inquire.eu/ and through the existing community channels.

To encourage the cross-disciplinary research, Geo-INQUIRE will also organize a series of training and workshops, focused on data, data products and software delivered by research infrastructures, and useful for researchers. In addition, two summer schools will be organized, dedicated to cross-disciplinary interactions of solid earth and marine science.

The proposals, for both transnational access and training, will be evaluated by a panel that reviews the technical and scientific feasibility of the project, ensuring equal opportunities and diversity in terms of gender, geographical distribution and career stage. The first call is expected to be issued by the end of Summer 2023. The data and products generated during the TAs will be made available to the scientific community via the project’s strict adherence to FAIR principles.

How to cite: Festa, G., Murphy, S., Majdanski, M., Christadler, I., Cotton, F., Strollo, A., Urvois, M., Röhling, V., Lorito, S., Babeyko, A., Bailo, D., Michalek, J., Lange, O., Quinteros, J., Prestes, M., and Weege, S.: The Transnational access and training in the Geo-INQUIRE EU-project, an opportunity for researchers to develop leading-edge science at selected facilities and test-beds across Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13455, https://doi.org/10.5194/egusphere-egu23-13455, 2023.

EGU23-14423 | Posters on site | GI2.3

EPOS-GNSS DATA GATEWAY: a portal to European GNSS Data and Metadata 

Mathilde Vergnolle and Jean-Luc Menut

EPOS-GNSS is the Thematic Core Service dedicated to GNSS data and products for the European Plate Observing System.
EPOS-GNSS provides a service to explore and download validated and quality controlled data and metadata. This service is based on a network of 10 data nodes connected to a centralized portal, called "EPOS-GNSS Data Gateway". The service aims to follow the FAIR principles and continues to evolve to better meet them. It currently provides more than 4 millions of daily files in the RINEX standardized format for 1670 European GNSS stations and their associated metadata.
In addition to the integration into the multi-disciplinary EPOS data portal, the service proposes a direct access to the data and metadata for users with a need for more complex or more specific queries and filtering. A GUI (web client) and a specialized command line client are provided to facilitate the exploration and download of the data and metadata.
The presentation introduces the EPOS GNSS-Data Gateway (https://gnssdata-epos.oca.eu), its clients, and its use.

How to cite: Vergnolle, M. and Menut, J.-L.: EPOS-GNSS DATA GATEWAY: a portal to European GNSS Data and Metadata, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14423, https://doi.org/10.5194/egusphere-egu23-14423, 2023.

EGU23-14605 | Posters on site | GI2.3

Towards an interoperable digital ecosystem in Earth System Science research 

Wolfgang zu Castell, Jan Bumberger, Peter Braesicke, Stephan Frickenhaus, Ulrike Kleeberg, Ralf Kunkel, and Sören Lorenz

Earth System Science (ESS) relies on the availability of data from varying resources and ranging over different disciplines. Hence, data sources are rich and diverse, including observatories, satellites, measuring campaigns, model simulations, case studies, laboratory experiments as well as citizen science etc. At the same time, practices of professional research data management (RDM) are differing significantly among various disciplines. There are many well-known challenges in enabling a free flow of data in the sense of the FAIR criteria. Such are data quality assurance, unique digital identifiers, access to and integration of data repositories, just to mention a few. 

The Helmholtz DataHub Earth&Environment is addressing digitalization in ESS by developing a federated data infrastructure. Existing RDM practices at seven centers of the Helmholtz Association working together in a joint research program within the Research Field Earth and Environment (RF E&E) are harmonized and integrated in a comprehensive way. The vision is to establish a digital research ecosystem fostering digitalization in geosciences and environmental sciences. Hereby, issues of common metadata standards, digital object identifiers for samples, instruments and datasets, defined role models for data sharing certainly play a central role. The various data generating infrastructures are registered digitally in order to collect metadata as early as possible and enrich them along the flow of the research cycle.

Joint RDM bridging several institutions relies on professional practices of distributed software development. Apart from operating cross-center software development teams, the solutions rely on concepts of modular software design. For example, a generic framework has been developed to allow for quick development of tools for domain specific data exploration in a distributed manner. Other tools incorporate automated quality control in data streams. Software is being developed following guiding principles of open and reusable research software development.

A suite of views is being provided, allowing for varying user perspectives, monitoring data flows from sensor to archive, or publishing data in quality assured repositories. Furthermore, high-level data products are being provided for stakeholders and knowledge transfer (for examples see https://datahub.erde-und-umwelt.de). Furthermore, tools for integrated data analysis, e.g. using AI approaches for marine litter detection can be implemented on top of the existing software stack.

Of course, this initiative does not exist in isolation. It is part of a long-term strategy being embedded within national (e.g. NFDI) and international (e.g. EOSC, RDA) initiatives.

How to cite: zu Castell, W., Bumberger, J., Braesicke, P., Frickenhaus, S., Kleeberg, U., Kunkel, R., and Lorenz, S.: Towards an interoperable digital ecosystem in Earth System Science research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14605, https://doi.org/10.5194/egusphere-egu23-14605, 2023.

EGU23-15072 | Posters virtual | GI2.3

Automated Extraction of Bioclimatic Time Series from PDF Tables 

Sabino Maggi, Silvana Fuina, and Saverio Vicario

Since the development of the original specifications in the '90s the PDF document format has become the de-facto standard for the distribution and archival of documents in electronic form because of its ability to preserve the original layout of the documents, independently of the hardware, operating system and application software used to visualize them.

Unfortunately the PDF format does not contain explicit structural and semantic information, making it very difficult to extract structured information from them, in particular data presented in tabular form. 
The automatic extraction of tabular data is a difficult and challenging task because tables can have extremely different formats and layouts, and involves several complex steps, from the proper recognition and conversion of printed text into machine-encoded characters, to the identification of logically coherent table constructs (headers, columns, rows, spanning elements), and to the breaking down of the data constructs into elemental objects.

Several tools have been developed to support the extraction process. In this work we survey the most interesting tools for the automatic detection and extraction of tabular data, analyzing their respective advantages and limitations. A particular emphasis is given on programmable open source tools because of their flexibility and long-term availability, together with the possibility to easily tweak them to meet the peculiar needs of the problem at hand.

As a practical application, we also present a workflow based on a set of R and AWK scripts that can automatically extract daily temperature and precipitation data from the official PDF documents made available each year by Regione Puglia, in Italy. The lessons learned from the development of this workflow and the possibility to generalize the approach to different kinds of PDF documents are also discussed.

How to cite: Maggi, S., Fuina, S., and Vicario, S.: Automated Extraction of Bioclimatic Time Series from PDF Tables, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15072, https://doi.org/10.5194/egusphere-egu23-15072, 2023.

EGU23-15293 | ECS | Posters virtual | GI2.3 | Highlight

Environmental parameters as a critical factor in understanding mosquito population 

Anastasia Angelou, Sandra Gewehr, Spiros Mourelatos, and Ioannis Kioutsioukis

The transmission of West Nile Virus is known to be affected by multiple factors related to the behavior and interactions between reservoir (birds), vector (Culex-mosquitos), and hosts (humans). Environmental parameters can play a critical role in understanding WNV epidemiology. The aim of this research was to determine the association of various climatic factors with the Culex mosquito abundance in Greece during the period 2011-2022. Climate data were acquired from ERA5 (European Centre for Medium-Range Weather Forecasts), while Culex abundance data were obtained through the mosquito surveillance network of ECODEVELOPMENT S.A, who hold the biggest mosquito surveillance network in Greece. The research was conducted at the municipality level. Culex abundance depends in a nonlinear fashion from temperature (Figure 1). The spread of the measurements indicates however there are other factors that affect the abundance of mosquitoes.

Figure 1 Scatter plot of air temperature VS Culex abundance in a municipality (Delta) with relatively sizeable mosquito population.

Correlation heatmaps were used as a tool to visualize the correlation of vector abundance and average monthly temperature up to 2 months before at several municipalities in the Region of Central Macedonia. The correlations decrease with increasing the lag in temperature (Figure 2). Moreover, there are some municipalities in which the correlation coefficient is considerably greater than others. Those correlations cannot be explained without considering the mosquito breeding sites found in these municipalities. In these municipalities there is a presence of important water resources, such as rice paddies, drainage canals, wetland systems or a combination of all the above. When surface waters warm and the outside temperature rises, the mosquito life cycle is completed more quickly, resulting in more generations being produced in a shorter period of time.

Figure 2 Correlation heatmap of the correlation coefficient between the mosquito abundance (municipality scale) and the average monthly temperature up to 2 months before.

Scatterplots and correlation heatmaps calculated with the Culex abundance and total precipitation, relative humidity or wind speed did not reveal similar patterns. Ongoing analysis focuses in more factors, environmental and not, which affect the abundance of mosquitoes that transmit WNV.

Acknowledgments 
This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: Τ2ΕΔΚ-02070). 

How to cite: Angelou, A., Gewehr, S., Mourelatos, S., and Kioutsioukis, I.: Environmental parameters as a critical factor in understanding mosquito population, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15293, https://doi.org/10.5194/egusphere-egu23-15293, 2023.

EGU23-15863 | Orals | GI2.3

Building an Open Source Infrastructure for Next Generation End User Climate Services 

Benedikt Gräler, Katharina Demmich, Johannes Schnell, Merel Vogel, Stefano Bagli, and Paolo Mazzoli

Climate Services (CS) are crucial in empowering citizens, stakeholders and decision-makers in defining resilient pathways to adapt to climate change and extreme weather events. Despite advances in scientific data and knowledge (e.g. Copernicus, GEOSS), current CS fail to achieve their full value proposition to end users. Challenges include incorporation of social and behavioral factors, local needs, knowledge and the customs of end users. In I-CISK, we put forward a co-design based requirement analysis to develop a Spatial Data Infrastructure and Platform that empowers a next generation of end user CS, which follow a social and behaviorally informed approach to co-producing services that meet climate information needs of the Living Labs of the European I-CISK project. Core to the project are climate extremes such as droughts, floods and heatwaves. The use-cases touch upon agriculture, forestry, tourism, energy, health, and the humanitarian sectors. We will present the summarized stakeholders' requirements regarding the new climate-service platform and their technical implications for the open source spatial infrastructure. The design also includes assessing, managing and presenting uncertainties that are an inherent component of climate models.

How to cite: Gräler, B., Demmich, K., Schnell, J., Vogel, M., Bagli, S., and Mazzoli, P.: Building an Open Source Infrastructure for Next Generation End User Climate Services, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15863, https://doi.org/10.5194/egusphere-egu23-15863, 2023.

EGU23-16416 | Posters virtual | GI2.3

The set up of the “UNO” project relational database for Stromboli volcano 

Simone Tarquini, Francesco Martinelli, Marina Bisson, Emanuela De Beni, Claudia Spinetti, and Gabriele Tarabusi

Active volcanoes are complex, poorly predictable systems that can pose a threat to humans and their infrastructures. As such, it is important to improve as much as possible the understanding of their behavior. The Stromboli volcano, in Italy, is one of the most active volcanoes in the world, and its almost persistent activity is documented since centuries. The persistent background activity is sometimes interrupted by much more energetic, dangerous episodes. The Istituto Nazionale di Geofisica e Vulcanologia (Italy) set up the interdisciplinary “UNO” project, aimed to understand when the Stromboli volcano is about to switch from the ordinary to the extraordinary activity. The UNO project includes an outstanding variety of research activities, such as sampling in the field, the modeling of Stromboli topography from ALS technique and satellite data, the 3D numerical simulations of ballistic trajectories, or the set up of an ultrasonic microphones system. Key to the success of the project is the collection of integrated high spatial and temporal resolution data and their joint analyses in a shared relational database. We present here the simplified logical model of such database, focusing on the identification of entities and their relationships.

How to cite: Tarquini, S., Martinelli, F., Bisson, M., De Beni, E., Spinetti, C., and Tarabusi, G.: The set up of the “UNO” project relational database for Stromboli volcano, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16416, https://doi.org/10.5194/egusphere-egu23-16416, 2023.

EGU23-16605 | ECS | Orals | GI2.3

NASA’s Science Discovery Engine: An Interdisciplinary, Open Science Data and Information Discovery Service 

Kaylin Bugbee, Ashish Acharya, Carson Davis, Emily Foshee, Rahul Ramachandran, Xiang Li, and Muthukumaran Ramasubramanian

NASA’s Science Plan includes a strategy to advance discovery by leveraging cross-disciplinary opportunities between scientific disciplines. In addition, NASA is committed to building an inclusive, open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI supports many activities to promote open science including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to NASA’s open science data and information and promotes interdisciplinary scientific discovery. In this presentation, we describe our work to develop the Science Discovery Engine in Sinequa, a Cognitive Search capability. We also share lessons learned about data governance, curation and information access.

How to cite: Bugbee, K., Acharya, A., Davis, C., Foshee, E., Ramachandran, R., Li, X., and Ramasubramanian, M.: NASA’s Science Discovery Engine: An Interdisciplinary, Open Science Data and Information Discovery Service, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16605, https://doi.org/10.5194/egusphere-egu23-16605, 2023.

EGU23-2843 | ECS | PICO | ESSI1.1

Geography-Aware Masked Autoencoders for Change Detection in Remote Sensing 

Lukas Kondmann, Caglar Senaras, Yuki M. Asano, Akhil Singh Rana, Annett Wania, and Xiao Xiang Zhu

Increasing coverage of commercial and public satellites allows us to monitor the pulse of the Earth in ever-shorter frequency (Zhu et al., 2017). Together with the rise of deep learning in artificial intelligence (AI) (LeCun et al., 2015), the field of AI for Earth Observation (AI4EO) is growing rapidly. However, many supervised deep learning techniques are data-hungry, which means that annotated data in large quantities are necessary to help these algorithms reach their full potential. In many Earth Observation applications such as change detection, this is often infeasible because high-quality annotations require manual labeling which is time-consuming and costly.  

Self-supervised learning (SSL) can help tackle the issue of limited label availability in AI4EO. In SSL, an algorithm is pretrained with tasks that only require the input data without annotation. Notably, Masked Autoencoders (MAE) have shown promising performances recently where a Vision Transformer learns to reconstruct a full image with only 25% of it as input. We hypothesize that the success of MAEs also extends to satellite imagery and evaluate this with a change detection downstream task. In addition, we provide a multitemporal DINO baseline which is another widely successful SSL method. Further, we test a second version of MAEs, which we call GeoMAE. GeoMAE incorporates the location and date of the satellite image as auxiliary information in self-supervised pretraining. The coordinates and date information are passed as additional tokens to the MAE model similar to the positional encoding. 
The pretraining dataset used is the RapidAI4EO corpus which contains multi-temporal Planet Fusion imagery for a variety of locations across Europe. The dataset for the downstream task also uses Planet Fusion in pairs as input data. These are provided on a 600m * 600m patch level three months apart together with a classification if the respective patch has changed in this period. Self-supervised pretraining is done for up to 150 epochs where we take the model with the best validation performance on the downstream task as a starting point for the test set. 

We find that the regular MAE model scores the best on the test set with an accuracy of 81.54% followed by DINO with 80.63% and GeoMAE with 80.02%. Pretraining MAE with ImageNet data instead of satellite images results in a notable performance loss down to 71.36%. Overall, our current pretraining experiments can not yet confirm our hypothesis that GeoMAE is advantageous compared to regular MAE. However, in similar spirit, Cong et al. (2022) recently introduced SatMAE which outlines that for other remote sensing applications, the combination of auxiliary information and novel masking strategies is a key factor. Therefore, it seems that a combination of location and time inputs together with adapted masking may also hold the most potential for change detection. There is ample potential for future research in geo-specific applications of MAEs and we provide a starting point for this with our experimental results for change detection. 

How to cite: Kondmann, L., Senaras, C., Asano, Y. M., Rana, A. S., Wania, A., and Zhu, X. X.: Geography-Aware Masked Autoencoders for Change Detection in Remote Sensing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2843, https://doi.org/10.5194/egusphere-egu23-2843, 2023.

EGU23-3267 | ECS | PICO | ESSI1.1

Decomposition learning based on spatial heterogeneity: A case study of COVID-19 infection forecasting in Germany 

Ximeng Cheng, Jost Arndt, Emilia Marquez, and Jackie Ma

New models are emerging from Artificial Intelligence (AI) and its sub-fields, in particular, Machine Learning and Deep Learning that are being applied in different application areas including geography (e.g., land cover identification and traffic volume forecasting based on spatial data). Different from well-known datasets often used to develop AI models (e.g., ImageNet for image classification), spatial data has an intrinsic feature, i.e., spatial heterogeneity, which leads to varying relationships across different regions between the independent (i.e., the model input X) and dependent variables (i.e., the model output Y). This makes it difficult to conduct large-scale studies with a single robust AI model. In this study, we draw on the idea of modular learning, i.e., to decompose large-scale tasks into sub-tasks for specific sub-regions and use multiple AI models to achieve these sub-tasks. The decomposition is based on the spatial characteristics to ensure that the relationship between independent and dependent variables is similar in each sub-region. We explore this approach for forecasting COVID-19 cases in Germany using spatiotemporal data (e.g., weather data and human mobility data) as an example and compare the prediction tasks with a single model to the proposed decomposition learning procedure in terms of accuracy and efficiency. This study is part of the project DAKI-FWS which is funded by the Federal Ministry of Economic Affairs and Climate Action in Germany to develop an early warning system to stabilize the German economy.

How to cite: Cheng, X., Arndt, J., Marquez, E., and Ma, J.: Decomposition learning based on spatial heterogeneity: A case study of COVID-19 infection forecasting in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3267, https://doi.org/10.5194/egusphere-egu23-3267, 2023.

EGU23-4929 | PICO | ESSI1.1

Using AI and ML to support marine science research 

Ilaria Fava, Peter Thijsse, Gergely Sipos, and Dick Schaap

The iMagine project is devoted to developing and delivering imaging data and services for aquatic science. Started in September 2022, the project will provide a portfolio of image data collections, high-performance image analysis tools empowered with Artificial Intelligence, and best practice documents for scientific image analysis. These services and documentation will enable better and more efficient processing and analysis of imaging data in marine and freshwater research, accelerating our scientific insights about processes and measures relevant to healthy oceans, seas, and coastal and inland waters. By building on the European Open Science Cloud compute platform, iMagine delivers a generic framework for AI model development, training, and deployment, which researchers can adopt for refining their AI-based applications for water pollution mitigation, biodiversity and ecosystem studies, climate change analysis and beach monitoring, but also for developing and optimising other AI-based applications in this field. The iMagine AI development and testing framework offers neural networks, parallel post-processing of extensive data, and analysis of massive online data streams in distributed environments. The synergies among the eight aquatic use cases in the project will lead to common solutions in data management, quality control, performance, integration, provenance, and FAIRness and contribute to harmonisation across RIs. The resulting iMagine AI development and testing platform and the iMagine use case applications will provide another component to the European marine data management landscape, valid for the Digital Twin of the Ocean, EMODnet, Copernicus, and international initiatives. 

How to cite: Fava, I., Thijsse, P., Sipos, G., and Schaap, D.: Using AI and ML to support marine science research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4929, https://doi.org/10.5194/egusphere-egu23-4929, 2023.

EGU23-6818 | ECS | PICO | ESSI1.1

Eddy identification from along-track altimeter data with multi-modal deep learning 

Adili Abulaitijiang, Eike Bolmer, Ribana Roscher, Jürgen Kusche, and Luciana Fenoglio-Marc

Eddies are circular rotating water masses, which are usually generated near the large ocean currents, e.g., Gulf Stream. Monitoring eddies and gaining knowledge on eddy statistics over a large region are important for fishery, marine biology studies, and testing ocean models.

At mesoscale, eddies are observed in radar altimetry, and methods have been developed to identify, track and classify them in gridded maps of sea surface height derived from multi-mission data sets. However, this procedure has drawbacks since much information is lost in the gridded maps. Inevitably, the spatial and temporal resolution of the original altimetry data degrades during the gridding process. On the other hand, the task of identifying eddies has been a post-analysis process on the gridded dataset, which is, by far, not meaningful for near-real time applications or forecasts. In the EDDY project at the University of Bonn, we aim to develop methods for identifying eddies directly from along track altimetry data via a machine (deep) learning approach.

Since eddy signatures (eddy boundary and highs and lows on sea level anomaly, SLA) are not possible to extract directly from along track altimetry data, the gridded altimetry maps from AVISO are used to detect eddies. These will serve as the reference data for Machine Learning. The eddy detection on 2D grid maps is produced by open-source geometry-based approach (e.g., py-eddy-tracker, Mason et al., 2014) with additional constraints like Okubo-Weiss parameter. Later, Sea Surface Temperature (SST) maps of the same region and date (also available from AVISO) are used for manually cleaning the reference data. Noting that altimetry grid maps and SST maps have different temporal and spatial resolution, we also use the high resolution (~6 km) ocean modeling simulation dataset (e.g., FESOM, Finite Element Sea ice Ocean Model). In this case, the FESOM dataset provides a coherent, high-resolution SLA and SST, salinity maps for the study area and is a potential test basis to develop the deep learning network.

The single modal training via a Conventional Neural Network (CNN) for the 2D altimetry grid maps produced excellent dice score of 86%, meaning the network almost detects all eddies in the Gulf Stream, which are consistent with reference data. For the multi-modal training, two different training networks are developed for 1D along-track altimetry data and 2D grid maps from SLA and SST, respectively, and then they are combined to give the final classification output. A transformer model is deemed to be efficient for encoding the spatiotemporal information from 1D along track altimetry data, while CNN is sufficient for 2D grid maps from multi-sensors.

In this presentation, we show the eddy classification results from the multi-modal deep learning approach based on along track and gridded multi-source datasets for the Gulf stream area for the period between 2017 and 2019. Results show that multi-modal deep learning improve the classification by more than 20% compared to transformer model training on along-track data alone.

How to cite: Abulaitijiang, A., Bolmer, E., Roscher, R., Kusche, J., and Fenoglio-Marc, L.: Eddy identification from along-track altimeter data with multi-modal deep learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6818, https://doi.org/10.5194/egusphere-egu23-6818, 2023.

EGU23-8479 | ECS | PICO | ESSI1.1

Model evaluation strategy impacts the interpretation and performance of machine learning models 

Lily-belle Sweet, Christoph Müller, Mohit Anand, and Jakob Zscheischler

Machine learning models are able to capture highly complex, nonlinear relationships, and have been used in recent years to accurately predict crop yields at regional and national scales. This success suggests that the use of ‘interpretable’ or ‘explainable’ machine learning (XAI) methods may facilitate improved scientific understanding of the compounding interactions between climate, crop physiology and yields. However, studies have identified implausible, contradicting or ambiguous results from the use of these methods. At the same time, researchers in fields such as ecology and remote sensing have called attention to issues with robust model evaluation on spatiotemporal datasets. This suggests that XAI methods may produce misleading results when applied to spatiotemporal datasets, but the impact of model evaluation strategy on the results of such methods has not yet been examined.

In this study, machine learning models are trained to predict simulated crop yield, and the impact of model evaluation strategy on the interpretation and performance of the resulting models is assessed. Using data from a process-based crop model allows us to then comment on the plausibility of the explanations provided by common XAI methods. Our results show that the choice of evaluation strategy has an impact on (i) the interpretations of the model using common XAI methods such as permutation feature importance and (ii) the resulting model skill on unseen years and regions. We find that use of a novel cross-validation strategy based on clustering in feature-space results in the most plausible interpretations. Additionally, we find that the use of this strategy during hyperparameter tuning and feature selection results in improved model performance on unseen years and regions. Our results provide a first step towards the establishment of best practices for model evaluation strategy in similar future studies.

How to cite: Sweet, L., Müller, C., Anand, M., and Zscheischler, J.: Model evaluation strategy impacts the interpretation and performance of machine learning models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8479, https://doi.org/10.5194/egusphere-egu23-8479, 2023.

EGU23-9437 | PICO | ESSI1.1

On Unsupervised Learning from Environmental Data 

Mikhail Kanevski

Predictive learning from data usually is formulated as a problem of finding the best connection between input and output spaces by optimizing well-defined cost or risk functions.

In geo-environmental studies input space is usually constructed from the geographical coordinates and features generated from different sources of available information (feature engineering), by applying expert knowledge, using deep learning technologies and taking into account the objectives of the study. Often, it is not known in advance if the input space is complete or contains redundant features. Therefore, unsupervised learning (UL) is essential in environmental data analysis, modelling, prediction and visualization. UL also helps better understand the data and phenomena they describe as well as in interpreting/communicating modelling strategies and the results in the decision-making process.

The main objective of the present investigation is to review some important topics in unsupervised learning from environmental data: 1) quantitative description of the input space (“monitoring network”) structure using global and local topological and fractal measures, 2) dimensionality reduction, 3) unsupervised feature selection and clustering by applying a variety of machine learning algorithms (kernel-based, ensemble learning, self-organizing maps) and visualization tools.

Major attention is paid to the simulated and real spatial data (pollution, permafrost, geomorphological and wind fields data).  Considered case studies have different input space dimensionality/topology and number of measurements. It is confirmed that UL should be considered an integral part of a generic methodology of environmental data analysis. Comprehensive comparisons and discussions of the results conclude the research.

 

 

How to cite: Kanevski, M.: On Unsupervised Learning from Environmental Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9437, https://doi.org/10.5194/egusphere-egu23-9437, 2023.

EGU23-11601 | PICO | ESSI1.1

Clustering Geodata Cubes (CGC) and Its Application to Phenological Datasets 

Francesco Nattino, Ou Ku, Meiert W. Grootes, Emma Izquierdo-Verdiguier, Serkan Girgin, and Raúl Zurita-Milla

Unsupervised classification techniques are becoming essential to extract information from the wealth of data that Earth observation satellites and other sensors currently provide. These datasets are inherently complex to analyze due to the extent across multiple dimensions - spatial, temporal, and often spectral or band dimension – their size, and the high resolution of current sensors. Traditional one-dimensional cluster analysis approaches, which are designed to find groups of similar elements in datasets such as rasters or time series, may come short of identifying patterns in these higher-dimensional datasets, often referred to as data cubes. In this context, we present our Clustering Geodata Cubes (CGC) software, an open-source Python package that implements a set of co- and tri-clustering algorithms to simultaneously group elements across two and three dimensions, respectively. The package includes different implementations to most efficiently tackle datasets that fit into the memory of a single machine as well as very large datasets that require cluster computing. A refining strategy to facilitate data pattern identification is also provided. We apply CGC to investigate gridded datasets representing the predicted day of the year when spring onset events (first leaf, first bloom) occur according to a well-established phenological model. Specifically, we consider spring indices computed at high spatial resolution (1 km) and continental scale (conterminous United States) for the last 40+ years and extract the main spatiotemporal patterns present in the data via CGC co-clustering functionality.  

How to cite: Nattino, F., Ku, O., Grootes, M. W., Izquierdo-Verdiguier, E., Girgin, S., and Zurita-Milla, R.: Clustering Geodata Cubes (CGC) and Its Application to Phenological Datasets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11601, https://doi.org/10.5194/egusphere-egu23-11601, 2023.

EGU23-12773 | PICO | ESSI1.1

Industrial Atmospheric Pollution Estimation Using Gaussian Process Regression 

Anton Sokolov, Hervé Delbarre, Daniil Boldyriev, Tetiana Bulana, Bohdan Molodets, and Dmytro Grabovets

Industrial pollution remains a major challenge in spite of recent technological developments and purification procedures. To effectively monitor atmosphere contamination, data from air quality networks should be coupled with advanced spatiotemporal statistical methods.

Our previous studies showed that standard interpolation techniques (like inverse distance weighting, linear or spline interpolation, kernel-based Gaussian Process Regression, GPR) are quite limited for the simulation of a smoke-like narrow-directed industrial pollution in the vicinity of the source (a few tenths of kilometers). In this work, we try to apply GPR, based on statistically estimated covariances. These covariances are calculated using СALPUFF atmospheric pollution dispersion model for a one-year simulation in the Kryvyi Rih region. The application of GPR permits taking into account high correlations between pollution values in neighboring points revealed by modeling. The result of the GPR covariance-based technique is compared with other interpolation techniques. It can be used then in the estimation and optimization of air quality networks.

How to cite: Sokolov, A., Delbarre, H., Boldyriev, D., Bulana, T., Molodets, B., and Grabovets, D.: Industrial Atmospheric Pollution Estimation Using Gaussian Process Regression, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12773, https://doi.org/10.5194/egusphere-egu23-12773, 2023.

EGU23-12933 | ECS | PICO | ESSI1.1

Estimating vegetation carbon stock components by linking ground databases with Earth observations 

Daniel Kinalczyk, Christine Wessollek, and Matthias Forkel

Land ecosystems dampen the increase of atmospheric CO2 by storing carbon in soils and vegetation. In order to estimate how long carbon stays in land ecosystems, a detailed knowledge about the distribution of carbon in different vegetation components is needed. Current Earth observation products provide estimates about total above-ground biomass but do not further separate between carbon stored in trees, understory vegetation, shrubs, grass, litter or woody debris. Here we present an approach in which we link several Earth observation products with a ground-based database to estimate biomass in various vegetation components. Therefore, we use information about the statistical distribution of biomass components provided by the North American Wildland Fuels Database (NAWFD), which are however not available as geocoded data. We use ESA CCI AGB version 3 data from 2010 as a proxy in order to link the NAWFD data to the spatial information from Earth observation products. The biomass and corresponding uncertainty from the ESA CCI AGB and a map of vegetation types are used to select the likely distribution of vegetation biomass components from the set of in-situ measurements of tree biomass. We then apply Isolation Forest outlier detection and bootstrapping for a robust comparison of both datasets and for uncertainty estimation. We use Random Forest and Gaussian Process regression to predict the biomass of trees, shrubs, snags, herbaceous vegetation, coarse and fine woody debris, duff and litter from ESA CCI AGB and land cover, GEDI canopy height, Sentinel-3 LAI and bioclimatic data. The regression models reach high predictive power and allow to also extrapolate to other regions. Our derived estimates of vegetation carbon stock components provide a more detailed view on the land carbon storage and contribute to an improved estimate of potential carbon emissions from respiration, disturbances and fires.

How to cite: Kinalczyk, D., Wessollek, C., and Forkel, M.: Estimating vegetation carbon stock components by linking ground databases with Earth observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12933, https://doi.org/10.5194/egusphere-egu23-12933, 2023.

EGU23-13196 | ECS | PICO | ESSI1.1

From Super-Resolution to Downscaling - An Image-Inpainting Deep Neural Network for High Resolution Weather and Climate Models 

Maximilian Witte, Danai Filippou, Étienne Plésiat, Johannes Meuer, Hannes Thiemann, David Hall, Thomas Ludwig, and Christopher Kadow

High resolution in weather and climate was always a common and ongoing goal of the community. In this regards, machine learning techniques accompanied numerical and statistical methods in recent years. Here we demonstrate that artificial intelligence can skilfully downscale low resolution climate model data when combined with numerical climate model data. We show that recently developed image inpainting technique perform accurate super-resolution via transfer learning using the HighResMIP of CMIP6 (Coupled Model Intercomparison Project Phase 6) experiments. Its huge data base offers a unique training opportunity for machine learning approaches. The transfer learning purpose allows also to downscale other CMIP6 experiments and models, as well as observational data like HadCRUT5. Combined with the technology of Kadow et al. 2020 of infilling missing climate data, we gain a neural network which reconstructs and downscales the important observational data set (IPCC AR6) at the same time. We further investigate the application of our method to downscale quantities predicted from a numerical ocean model (ICON-O) to improve computation times. In this process we focus on the ability of the model to predict eddies from low-resolution data.

An extension to:

Kadow, C., Hall, D.M. & Ulbrich, U. Artificial intelligence reconstructs missing climate information. Nature Geoscience 13, 408–413 (2020). https://doi.org/10.1038/s41561-020-0582-5

How to cite: Witte, M., Filippou, D., Plésiat, É., Meuer, J., Thiemann, H., Hall, D., Ludwig, T., and Kadow, C.: From Super-Resolution to Downscaling - An Image-Inpainting Deep Neural Network for High Resolution Weather and Climate Models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13196, https://doi.org/10.5194/egusphere-egu23-13196, 2023.

EGU23-14716 | ECS | PICO | ESSI1.1

Spatial-temporal transferability assessment of remote sensing data models for mapping agricultural land use 

Jayan Wijesingha, Ilze Dzene, and Michael Wachendorf

To assess the impact of anthropogenic and natural causes on land use and land use cover change, mapping of spatial and temporal changes is increasingly applied. Due to the availability of satellite image archives, remote sensing (RS) data-based machine learning models are in particular suitable for mapping and analysing land use and land cover changes. Most often, models trained with current RS data are employed to estimate past land cover and land use using available RS data with the assumption that the trained model predicts past data values similar to the accuracy of present data. However, machine learning models trained on RS data from particular locations and times may not be well transferred to new locations and time datasets due to various reasons. This study aims to assess the spatial-temporal transferability of the RS data models in the context of agricultural land use mapping. The study was designed to map agricultural land use (5 classes: maize, grasslands, summer crops, winter crops, and mixed crops) in two regions in Germany (North Hesse and Weser Ems) between the years 2010 and 2018 using Landsat archive data (i.e., Landsat 5, 7, and 8). Three model transferability scenarios were evaluated, a) temporal - S1, b) spatial - S2 and c) spatial-temporal - S3. Two machine learning models (random forest - RF and Convolution Neural Network - CNN) were trained. For each transferability scenario, class-level F1 and macro F1 values were compared between the reference and targeted transferability systems. Moreover, to explain the results of transferability scenarios, transferability results were further explored using dissimilarity index and area of applicability (AOA) concepts. The average macro F1 value of the trained model for the reference scenario (no transferability) was 0.75. For assessed transferability scenarios, the average macro F1 values were 0.70, 0.65 and 0.60, for S1, S2, and S3 respectively. It shows that, when predicting data from different spatial-temporal contexts, the model performance is decreasing. In contrast, the average proportion of the data inside the AOA did not show a clear pattern for different scenarios. In the context of RS data-related model building, spatial-temporal transferability is essential because of the limited availability of the labelled data. Thus, the results from this case study provide an understanding of how model performance changes when the model is transferred to new settings with data from different temporal and spatial domains.

How to cite: Wijesingha, J., Dzene, I., and Wachendorf, M.: Spatial-temporal transferability assessment of remote sensing data models for mapping agricultural land use, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14716, https://doi.org/10.5194/egusphere-egu23-14716, 2023.

EGU23-16096 | ECS | PICO | ESSI1.1

Limitations of machine learning in a spatial context 

Jens Heinke, Christoph Müller, and Dieter Gerten

Machine learning algorithms have become popular tools for the analysis of spatial data. However, a number of studies have demonstrated that the application of machine learning algorithms in a spatial context has limitations. New geographic locations may lie outside of the data range for which the model was trained, and estimates of model performance may be too optimistic, when spatial autocorrelation of geographic data is not properly accounted for in cross-validation. We here use artificially created spatial data fields to conduct a series of experiments to further investigate the potential pitfalls of random forest regression applied to spatial data. We provide new insights on previously reported limitations and identify further limitations. We demonstrate that the same mechanism that leads to overoptimistic estimates of model performance (when based on ordinary random k-fold cross-validation) can also lead to a deterioration of model performance. When covariates contain sufficient information to deduce spatial coordinates, the model can reproduce any spatial pattern in the training data even if it is entirely or partly unrelated to the covariates. The presence of spatially correlated residuals in the training data changes how the model utilizes the information of the covariates and impedes the identification of the actual relationship between covariates and response. This reduces model performance when the model is applied to data with a different spatial structure. Under such conditions, machine learning methods that are sufficiently flexible to fit to autocorrelated residuals (such as random forest) may not be an optimal choice. Better models may be obtained using less flexible but more transparent approaches such as generalized linear models or additive models.

How to cite: Heinke, J., Müller, C., and Gerten, D.: Limitations of machine learning in a spatial context, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16096, https://doi.org/10.5194/egusphere-egu23-16096, 2023.

EGU23-16768 | PICO | ESSI1.1

Knowledge Representation of Levee Systems - an Environmental Justice Perspective 

Armita Davarpanah, Anthony.l Nguy Robertson, Monica Lipscomb, Jacob.w. McCord, and Amy Morris

Levee systems are designed to reduce the risk of water-related natural hazards (e.g., flooding) in areas behind levees. Most levees in the U.S. are designed to protect people and facilities against the impacts of the 100-year floods. However, the current climate change is increasing the probability of the occurrence of 500-year flood events that in turn increases the likelihood of economic loss, environmental damage, and fatality that disproportionately impacts communities of color and low-income groups facing socio-economic inequities in leveed areas. The increased frequency and intensity of flooding is putting extra pressure on emergency responders that often require diverse, multi-dimensional data originating from different sources to make sound decisions. Currently, the integration of these heterogeneous data acquired by diverse sensors and emergency agencies about environmental, hydrological, and demographic indicators requires costly and complex programming and analysis that hinder rapid disaster management efforts. Our domain ‘Levee System Ontology (LSO)’ resolves the data integration and software interoperability issues by semantically modeling the static aspects, dynamic processes, and information content of the levee systems by extending the well-structured, top-level Basic Formal Ontology (BFO) and mid-level Common Core Ontologies (CCO). LSO’s class and property names follow the terminology of the National Levee Database (NLD), allowing data scientists using NLD data to constrain their classifications based on the knowledge represented in LSO. In addition to modeling the information related to the characteristics and status of the structural components of the levee system, LSO represents the residual risk in leveed areas, economic and environmental losses, and damage to facilities in case of breaching and/or overtopping of levees. LSO enables reasoning to infer components and places along levees and floodwalls where the system requires inspection, maintenance, and repair based on the status of system components. The ontology also represents the impact of flood management activities on different groups of people from an environmental justice perspective, based on the principles of DEI (diversity, equity, inclusion) as defined by the U.N. Sustainable Development Goals.

How to cite: Davarpanah, A., Nguy Robertson, A. L., Lipscomb, M., McCord, J. w., and Morris, A.: Knowledge Representation of Levee Systems - an Environmental Justice Perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16768, https://doi.org/10.5194/egusphere-egu23-16768, 2023.

EGU23-2454 | ECS | Orals | ESSI2.2

The future of NASA Earth Science in the commercial cloud: Challenges and opportunities 

Alexey Shiklomanov, Manil Maskey, Yoseline Angel, Aimee Barciauskas, Philip Brodrick, Brian Freitag, and Jonas Sølvsteen

NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).

How to cite: Shiklomanov, A., Maskey, M., Angel, Y., Barciauskas, A., Brodrick, P., Freitag, B., and Sølvsteen, J.: The future of NASA Earth Science in the commercial cloud: Challenges and opportunities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2454, https://doi.org/10.5194/egusphere-egu23-2454, 2023.

EGU23-3657 | Orals | ESSI2.2

CADS 2.0: A FAIRest Data Store infrastructure blooming in a landscape of Data Spaces. 

Angel lopez alos, Baudouin raoult, Edward comyn-platt, and James varndell

First launched as the Climate Data Store (CDS) supporting the Climate Change Service (C3S) and later instantiated as the Atmosphere Data Store (ADS) for the Atmosphere Monitoring Service (CAMS), the shared underlaying Climate & Atmosphere Data Store Infrastructure (CADS) represents the technical backbone for the implementation of Copernicus services entrusted to ECMWF on behalf of the European Commission. CDS in addition also offer access to a selection of datasets from the Emergency Management Service (CEMS).  As the flagship instance of the infrastructure, CDS counts with more than 160k registered users and delivers a daily average over 100 TBs of data from a catalogue of 141 datasets.

CADS Software Infrastructure is designed as a distributed system and open framework that facilitates improved access to a broad spectrum of data and information via a powerful service-oriented architecture offering seamless web-based and API-based search and retrieve capabilities. CADS also provides a generic software toolbox that allow users to make use of available datasets and a series of state-of-the-art data tools that can be combined into more elaborated processes, and present results graphically in the form of interactive web applications.  CADS Infrastructure is hosted in an on-premises Cloud physically located within ECMWF Data Centre and implemented using a collection of virtual machines, networks and large data volumes.  Fully customized instances of CADS, including dedicated Virtual Hardware Infrastructure, Software Application and Catalogued content can be easily deployed thanks to implemented automatization and configuration software tools and a set of configuration files which are managed by a distributed version control system. Tailored scripts and templates allow to easily accommodate different standards and interoperate with external platforms.

ECMWF in partnership with EUMETSAT, ESA and EEA also implement the Data and Information Access Services (DIAS) platform called WEkEO, a distributed cloud-computing infrastructure used to process and make the data generated by Copernicus Services accessible to users together with derived products and all satellite data from the Copernicus Sentinels. Within the partnership ECMWF is responsible for the procurement of the software to implement Data Access Services, Processing and Tools which specifications build on the same fundamentals than CADS.  Adoption of FAIR principles has demonstrated cornerstone to maximize synergies and interactions between CADS, WEkEO and other related platforms.

 

Driven by the increasing demand and the evolving landscape of platforms and services a major project for the modernization of the CADS infrastructure is currently underway. The coming CADS 2.0 aims to capitalize experience, feedbacks, lesson learned, know-how from current CADS, embrace advanced technologies, engage with a broader user community, make the current platform more versatile and cloud oriented, improve workflows and methodologies, ensure compatibility with state-of-the-art solutions such as machine learning, data cubes and interactive notebooks, consolidate the adoption of FAIR principles and strength synergies with related platforms.

 

As complementary Infrastructures, WEkEO will allow users to harness compute resources without the networking and storage costs associated with public Cloud offerings in where CADS Toolbox 2.0  will deploy and run allowing heavy jobs (retrieval and reduction) to be submitted to CADS 2.0 core infrastructure as services.

How to cite: lopez alos, A., raoult, B., comyn-platt, E., and varndell, J.: CADS 2.0: A FAIRest Data Store infrastructure blooming in a landscape of Data Spaces., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3657, https://doi.org/10.5194/egusphere-egu23-3657, 2023.

EGU23-5038 | Posters on site | ESSI2.2

EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation 

Vasileios Baousis, Stathes Hadjiefthymiades, Charalampos Andreou, Kakia Panagidh, and Armagan Karatosun

EO4EU is a European Commission-funded innovation project bringing forward the EO4EU Platform which will access and use of EO data easier for environmental, government, and even business forecasts and operations.

The EO4EU Platform, which will be accessible at www.eo4eu.eu, will link already existing major EO data sources such as GEOSS, INSPIRE, Copernicus, Galileo, DestinE among others and provide a number of tools and services to assist users to find and access the data they are interested in, as well as to analyse and visualise this data. The platform will leverage machine learning to support the handling of the characteristically large volume of EO data as well as a combination of Cloud computing infrastructure and pre-exascale high-performance computing to manage processing workloads.

Specific attention is also given to developing user-friendly interfaces for EO4EU allowing users to intuitively use EO data freely and easily, even with the use of extended reality.

EO4EU objectives are:

  • Holistic DataOps ecosystem to enhance access and usability of EO information.
  • A semantic-enhanced knowledge graph that augments the FAIRness of EO data and supports sophisticated data representation and dynamics.
  • A machine learning pipeline that enables the dynamic annotation of the various EO data sources.
  • Efficient, reliable and interoperable inter- and intra- data layer communications
  • Advance stakeholders’ knowledge capacity through informed decision-making and policy-making support.
  • A full range of use case scenarios addressing current data needs, capitalizing existing digital services and platforms, fostering their usability and practicality, and taking into account ethical aspects aiming at social impact maximization.

Technical and scientific innovation can be summarised as follows:

  • Improve compression rates for image quality and reduce data volumes.
  • Improve the quality of reconstructed compressed images, maintaining the same comparison rates
  • Facilitate the design of custom services with a minimized labelled data requirement
  • Learn robust and transferable representations of EO data
  • Publishing original trained models on EO data with all relevant assisting material to support reusability in a public repository.
  • Data fusion optimized execution in HPC and GPU environment
  • Better accuracy of data representation
  • Customizable visualization tools tailored to the needs of each use case
  • Dedicated graphs for end-users with various granularities, modalities, metrics and statistics to observe the overall trends in time, correlations, and cause-and-effect relationships through a responsive web-interfaced module.

In this presentation, the status of the project, the adopted architecture and the findings from our initial user surveys pertaining to EO data access and discovery will be analysed. Finally, the next steps of the project, the early access to the developed platform and the challenges and opportunities will be discussed.  

How to cite: Baousis, V., Hadjiefthymiades, S., Andreou, C., Panagidh, K., and Karatosun, A.: EO4EU - AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5038, https://doi.org/10.5194/egusphere-egu23-5038, 2023.

EGU23-5862 | Orals | ESSI2.2

The ESA Green Transition Information Factories – using Earth Observation and cloud-based analytics to address the Green Transition information needs. 

Patrick Griffiths, Stefanie Lumnitz, Christian Retscher, Frank-Martin Seifert, and Yves-Louis Desnos

In response to the global climate and sustainability crisis, many countries have expressed ambitions goals in terms of carbon neutrality and a green economy. In this context, the European Green Deal comprises several policy elements aimed to achieve carbon neutrality by 2050.

In response to these ambitions, the European Space Agency (ESA) is initiating various efforts to leverage on space technologies and data and support various Green Deal ambitions. The ESA Space for Green Future (S4GF) Accelerator will explore new mechanisms to promote the use of space technologies and advanced modelling approaches for scenario investigations on the Green Transition of economy and society.

A central element of the S4GF accelerator are the Green Transition Information Factories (GTIF). GTIF takes advantage of Earth Observation (EO) capabilities, geospatial and digital platform technologies, as well as cutting edge analytics to generate actionable knowledge and decision support in the context of the Green Transition.

A first national scale GTIF demonstrator has now been developed for Austria.
It addressed the information needs and national priorities for the Green Deal in Austria. This is facilitated through a bottom-up consultation and co-creation process with various national stakeholders and expert entities. These requirements are matched with various EO industry teams that

The current GTIF demonstrator for Austria (GTIF-AT) builds on top of federated European cloud services, providing efficient access to key EO data repositories and rich interdisciplinary datasets. GTIF-AT initially addresses five Green Transition domains: (1) Energy Transition, (2) Mobility Transition, (3) Sustainable Cities, (4) Carbon Accounting and (5) EO Adaptation Services.

For each of these domains, scientific narratives are provided and elaborated using scrollytelling technologies. The GTIF interactive explore tools allow various users to explore the domains and subdomains in more detail to investigate better understand the challenges, complexities, and underlying socio-economic and environmental conflicts. The GTIF interactive explore tools combine domain specific scientific results with intuitive Graphical User Interfaces and modern frontend technologies. In the GTIF Energy Transition domain, users can interactively investigate the suitability of locations at 10m resolution for the expansion of renewable (wind or solar) energy production. The tools also allow investigating the underlying conflicts e.g., with existing land uses or biodiversity constraints. Satellite based altimetry is used to dynamically monitor the water levels in hydro energy reservoirs to infer the related energy storage potentials. In the sustainable cities’ domain, users can investigate the photovoltaic installments on rooftops and assess the suitability in terms of roof geometry and expected energy yields.

GTIF enables various users to inform themselves and interactively investigate the challenges but also opportunities related to the Green Transition ambitions. This enables, for example, citizens to engage in the discussion process for the renewable energy expansion or support energy start-ups to develop new services. The GTIF development follows an open science and open-source approach and several new GTIF instances are planned for the next years, addressing the Green Deal information needs and accelerating the Green Transition. This presentation will showcase some of the GTIF interactive explore tools and provide an outlook on future efforts.

How to cite: Griffiths, P., Lumnitz, S., Retscher, C., Seifert, F.-M., and Desnos, Y.-L.: The ESA Green Transition Information Factories – using Earth Observation and cloud-based analytics to address the Green Transition information needs., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5862, https://doi.org/10.5194/egusphere-egu23-5862, 2023.

EGU23-5936 | Orals | ESSI2.2

What does the European Spatial Data Infrastructure INSPIRE need in order to become a Green Deal Data Space? 

Joan Masó, Alba Brobia, Ivette Serral, Ingo Simonis, Francesca Noardo, Lucy Bastin, Carlos Cob Parro, Joaquín García, Raul Palma, and Sébastien Ziegler

In May 2007, the INSPIRE directive established the path towards creating the European Spatial Data Infrastructure (ESDI). While the Joint Research Centre (JRC) defined a set of detailed implementation guidelines, the European member states determined the agencies responsible for delivering the different topics specified in the directive’s annexes. INSPIRE’s goal was - and still is - to organize and share Europe’s data supporting environmental policies and actions. However, the way that INSPIRE was defined limited contributions to the public sector, and limited topics to those specifically listed in its annexes. Technical challenges and a lack of appropriate tools have impeded INSPIRE from implementing its own guidelines, and even after 15 years, the dream of a continuous, consistent description of Europe’s environment has still not completely materialized. We should apply the lessons learnt in INSPIRE when we build the Green Deal Data Space (GDDS). To create the GDDS, we should start with ESDI (the European Spatial Data Infrastructure), but also engage and align with the ongoing preparatory actions for data spaces (e.g., for green deal and agriculture) as well as include actors and networks that have emerged or been organized in the recent years. These include: networks of in situ observations (e.g. the  Environmental Research Infrastructures (ENVRI) community); Citizen Science initiatives (such as the biodiversity observations integrated in the Global Biodiversity Information Facility (GBIF), or sensor communities for e.g. air quality); predictive algorithms and machine learning models and simulations based on artificial intelligence (such as the ones deployed in the European Open Science Cloud, International Data Space Association and Gaia-X; services driven both by the scientific community and the private sector); remote sensing derived products developed by the Copernicus Services. Most of these data providers have already embraced the FAIR principles and open data, providing many examples of best practice which can assist newer adopters on the path to open science. In the Horizon Europe project AD4GD (AllData4GreenDeal), we believe that, instead of trying to force data producers to adopt cumbersome new protocols, we should take advantage of the latest developments in geospatial standards and APIs. These allow loosely coupled but well documented and interlinked data sources and models in the GDDS while achieving scientifically robust integration  and easy access to data in the resulting workflows. Another fundamental element will be the adoption of a common and extensible information model enabling the representation and exchange of Green Deal related data in an unambiguous manner, including vocabularies for Essential Variables to organize the observable measurements and increase the level of semantic interoperability. This will allow systems and components from different technology providers to seamless interoperate and exchange data, and to have an integrated view and access to exploit the full value of the available data. The project will validate the approach in three pilot cases: water quality and availability of Berlin lakes, biodiversity corridors in the metropolitan area of Barcelona and low cost air quality sensors in Europe. The AD4GD project is funded by the European Union under the Horizon Europe program.

How to cite: Masó, J., Brobia, A., Serral, I., Simonis, I., Noardo, F., Bastin, L., Cob Parro, C., García, J., Palma, R., and Ziegler, S.: What does the European Spatial Data Infrastructure INSPIRE need in order to become a Green Deal Data Space?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5936, https://doi.org/10.5194/egusphere-egu23-5936, 2023.

EGU23-7052 | Orals | ESSI2.2

FAIRiCUBE: Enabling Gridded Data Analysis for All 

Katharina Schleidt and Stefan Jetschny

Previously, collecting, storing, owning and, if necessary, digitizing data was vital for any data-driven application. Nowadays, we are swimming in data, whereby one could postulate that we are drowning. However, downloading vast data to local storage and subsequent in-house processing on dedicated hardware is inefficient and not in line with the big data processing philosophy. While the FAIR principles are fulfilled as the data is findable, accessible, and interoperable, the actual reuse of the data to gain new insights depends on the data user’s local capabilities. Scientists aware of the potentially available data and processing capabilities are still not able to easily leverage these resources as required to perform their work; while the analysis gap entailed by the information explosion is being increasingly highlighted, remediation lags.

The core objective of the FAIRiCUBE project is to enable players from beyond classic Earth Observation (EO) domains to provide, access, process, and share gridded data and algorithms in a FAIR and TRUSTable manner. To reach this objective, we are creating the FAIRiCUBE HUB, a crosscutting platform and framework for data ingestion, provision, analysis, processing, and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces.

In order to gain a better understanding of the various obstacles to leveraging available assets in regard to both data as well as analysis and processing modalities, several use cases have been defined addressing diverse aspects of European Green Deal (EGD) priority actions. Each of the use cases has a defined objective, approach, research question and data requirements.

The use cases selected to guide the creation of the FAIRiCUBE HUB are as follows:

  • Urban adaptation to climate change
  • Biodiversity and agriculture nexus
  • Biodiversity occurrence cubes
  • Drosophila landscape genomics
  • Spatial and temporal assessment of neighborhood building stock

Many of the issues encountered within the FAIRiCUBE project are formally considered solved. Catalogues are available detailing the available datasets, standards define how the datasets are to be structured and annotated with the relevant metainformation. A vast array of processing functionality has emerged that can be applied to such resources. However, while all this is considered state-of-the-art in the EO community, there is a subtle delta blocking access to wider communities that could make good use of the available resources pertaining to their own domains of work. These include, but are not limited to:

  • Identifying available data sources
  • Determining fitness for use
  • Interoperability of data with divergent spatiotemporal basis
  • Understanding access modalities
  • Scoping required resources
  • Providing non-gridded data holdings in a gridded manner

There is great potential in integrating the diverse gridded resources available from EO sources within wider research domains. However, at present, there are subtle barriers blocking this potential. Within FAIRiCUBE, these issues are being collected and evaluated, mitigation measures are being explored together with researchers not from traditional EO domains, with the goal of breaking down these barriers, and enabling powerful research and data analysis potential to a wide range of scientists.

How to cite: Schleidt, K. and Jetschny, S.: FAIRiCUBE: Enabling Gridded Data Analysis for All, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7052, https://doi.org/10.5194/egusphere-egu23-7052, 2023.

EGU23-7074 | ECS | Posters on site | ESSI2.2

An EOSC-enabled Data Space environment for the climate community 

Fabrizio Antonio, Donatello Elia, Guillaume Levavasseur, Atef Ben Nasser, Paola Nassisi, Alessandro D'Anca, Alessandra Nuzzo, Sandro Fiore, Sylvie Joussaume, and Giovanni Aloisio

The exponential increase in data volumes and complexities is causing a radical change in the scientific discovery process in several domains, including climate science. This affects the different stages of the data lifecycle, thus posing significant data management challenges in terms of data archiving, access, analysis, visualization, and sharing. The data space concept can support scientists' workflow and simplify the process towards a more FAIR use of data.

In the context of the European Open Science Cloud (EOSC) initiative launched by the European Commission, the ENES Data Space (EDS) represents a domain-specific implementation of the data space concept. The service, developed in the frame of the EGI-ACE project, aims to provide an open, scalable, cloud-enabled data science environment for climate data analysis on top of the EOSC Compute Platform. It is accessible in the European Open Science Cloud (EOSC) through the EOSC Catalogue and Marketplace (https://marketplace.eosc-portal.eu/services/enes-data-space) and it also provides a web portal (https://enesdataspace.vm.fedcloud.eu) including information, tutorials and training materials on how to get started with its main features. 

The EDS integrates into a single environment ready-to-use climate datasets, compute resources and tools, all made available through the Jupyter interface, with the aim of supporting the overall scientific data processing workflow.  Specifically, the data store linked to the ENES Data Space provides access to a multi-terabyte set of variable-centric collections from large-scale global climate experiments.  The data pool consists of a mirrored subset of CMIP (Coupled Model Intercomparison Project) datasets from the ESGF (Earth System Grid Federation) federated data archive, collected and kept synchronized with the remote copies by using the Synda tool developed within the scope of the IS-ENES3 H2020 project. Community-based, open source frameworks (e.g., Ophidia) and libraries from the Python ecosystem provide the capabilities for data access, analysis and visualisation. Results  and experiment definitions (i.e., Jupyter Notebooks) can be easily shared among users promoting data sharing and application re-use towards a more Open Science approach. 

An overview of the data space capabilities along with the key aspects in terms of data management will be presented in this work.

How to cite: Antonio, F., Elia, D., Levavasseur, G., Ben Nasser, A., Nassisi, P., D'Anca, A., Nuzzo, A., Fiore, S., Joussaume, S., and Aloisio, G.: An EOSC-enabled Data Space environment for the climate community, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7074, https://doi.org/10.5194/egusphere-egu23-7074, 2023.

EGU23-7786 | Posters on site | ESSI2.2

Constructing a Searchable Knowledge Repository for FAIR Climate Data 

Mark Roantree, Branislava Lalić, Stevan Savić, Dragan Milošević, and Michael Scriney

The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers who's skills include design and building a knowledge repository, and machine learning researchers who provide expertise on data preparation tasks such as gap filling and advise on different machine learning models that can exploit this data.

One of the main goals of the CA20108 cost action is to develop a knowledge portal that is fully compliant with the FAIR principles for scientific data management. In the first year, a bespoke knowledge portal was developed to capture metadata for FAIR datasets. Its purpose was to provide detailed metadata descriptions for shareable micro-meteorological (micromet) data using the WMO standard. While storing Network, Site and Sensor metadata locally, the system passes the actual data to Zenodo, receives back the DOI and thus, creates a permanent link between the Knowledge Portal and the storage platform Zenodo. While the user searches the Knowledge portal (metadata), results provide both detailed descriptions and links to data on the Zenodo platform. Our adherence to FAIR principles are documented below:

  • Findable. Machine-readable metadata is required for automatic discovery of datasets and services. A metadata description is supplied by the data owners for all micro-meteorological data shared on the system which subsequently drives the search engine, using keywords or network, site and sensor search terms.
  • Accessible. When suitable datasets have been identified, access details should be provided. Assuming data is freely accessible, Zenodo DOIs and links are provided for direct data access.
  • Interoperable. Data interoperability means the ability to share and integrate data from different users and sources. This can only happen if a standard (meta)data model is employed to describe data, an important concept which generally requires data engineering skills to deliver. In the knowledge portal presented here, the WMO guide provides the design and structure for metadata.    
  • Reusable. To truly deliver reusability, metadata should be expressed in as detailed a manner as possible. In this way, data can be replicated and integrated according to different scientific requirements. While the Knowledge Portal facilitates very detailed metadata descriptions, not all metadata is compulsory as it was accepted that in some cases, the overhead in providing this information can be very costly. 

Simple analytics are in place to monitor the volume and size of networks in the system. Current metrics include: network count; average size of network (number of sites); dates and size of datasets per network/site; numbers and types of sensors in each site, etc. The current Portal is in Beta version meaning that the system is currently functional but open only to members of the Cost Action who are nominated testers. This status is due to change in Q1/2023 when access will be open to the wider climate science community.  

Current plans include new Tools and Services to assess the quality of data, including the level of gaps and in some cases, machine learning tools will be provided to attempt gap filling for datasets meeting certain requirements.

 

How to cite: Roantree, M., Lalić, B., Savić, S., Milošević, D., and Scriney, M.: Constructing a Searchable Knowledge Repository for FAIR Climate Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7786, https://doi.org/10.5194/egusphere-egu23-7786, 2023.

EGU23-7842 | Orals | ESSI2.2 | Highlight

Destination Earth - Processing Near Data and Massive Data Handling 

Danaele Puechmaille, Jordi Duatis Juarez, Miruna Stoicescu, Michael Schick, and Borys Saulyak

Destination Earth is an operational service under the lead of the European Commission being implemented jointly by ESA, ECMWF and EUMETSAT.

The presentation will provide insights of how Destination Earth provides Near Data Processing and deals with Massive Data.

The objective of the European Commission’s Destination Earth (DestinE) initiative is to deploy several highly accurate digital replicas of the Earth (Digital Twins) in order to monitor and simulate natural as well as human activities and their interactions, to develop and test “what-if” scenarios that would enable more sustainable developments and support European environmental policies. DestinE addresses the challenge to manage and make accessible the sheer amount of data generated by the Digital Twins and observation data located at external sites such as the ones depicted in the figure below. This data will be made available fast enough and in a format ready to support analysis scenarios proposed by the DestinE service users.

 

Figure 1 :  DestinE Data Sources (green) and Stakeholders (orange)

 

The “DestinE Data Lake” (DEDL) is one of the three Destination Earth components interacting with:

  • the Digital Twin Engine (DTE), which runs the simulation models, under ECMWF responsibility
  • the DestinE Core Service Platform (DESP), which represents the user entry point to the DestinE services and data, under ESA responsibility

The DestinE Data Lake (DEDL) fulfils the storage and access requirements for any data that is offered to DestinE users. It provides users with a seamless access to the datasets, regardless of data type and location. Furthermore, the DEDL supports big data processing services, such as near-data processing to maximize throughput and service scalability. The data lake is built inter alia upon existing data lakes such as Copernicus DIAS, ESA, EUMETSAT, ECMWF as well as complementary data from diverse sources like federated data spaces, in-situ or socio-economic data. The DT Data Warehouse is a sub-component of the DEDL which stores relevant subsets of the output from each  digital twin (DT) execution being powered by ECMWFs Hyper-Cube service.

During the session, EUMETSAT’s representative will share to the community how the Destination Earth Data Lake component implements and takes advantage of Near Data Processing and also how the System handles massive data access and exchange. The Destination Earth Data Portfolio will be presented.

Figure 2: Destination Earth Data Portfolio

How to cite: Puechmaille, D., Duatis Juarez, J., Stoicescu, M., Schick, M., and Saulyak, B.: Destination Earth - Processing Near Data and Massive Data Handling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7842, https://doi.org/10.5194/egusphere-egu23-7842, 2023.

EGU23-8041 | Posters on site | ESSI2.2

Coastal Digital Twins: building knowledge through numerical models and IT tools 

Anabela Oliveira, André B. Fortunato, Gonçalo de Jesus, Marta Rodrigues, and Luís David

Digital Twins integrate continuously, in an interactive, two-way data connection, the real and the virtual assets. They provide a virtual representation of a physical asset enabled through data and models and can be used for multiple applications such as real-time forecast, system optimization, monitoring and controlling, and support enhanced decision making. These recent tools take advantage of the huge online volume of data streams provided by satellites, IoT sensing and many real time surveillance platforms, and the availability of powerful computational resources that made process-solving, high resolution models or AI-based models possible, to build high accuracy replicas of the real world.
In this paper, the adaptation of the concept of Digital Twins is extended from the ocean to the coastal zones, handling the high non-linear physics and the complexity of monitoring these regions, using the on-demand coastal forecast framework OPENCoastS (Oliveira et al., 2020; Oliveira et al., 2021) to build a user-centered data spaces where multiple services, from early-warning tools to collaboratory platforms, are customized to meet the users needs. Computational effort and data requirements for these services is high, integration of Coastal Digital Twins in federated computational infrastructures, such as European Open Science Cloud (EOSC) or INCD in Portugal, to guarantee the capacity to serve multiple users simultaneously.

This tool is demonstrated in the coastal area of Albufeira, located in the southern part of Portugal, in the scope of the SINERGEA innovation project. Coastal cities face growing challenges from flooding, sea water quality and energy sustainability, which increasingly require an intelligent, real-time management. The urban drainage infrastructures  transport to the wastewater treatment plants all waters likely to pollute downstream beaches. Real-time tools are required to support the assessment and prediction of the quality of bathing waters, to assess the possible need to prohibit beach water usage. During heavy rainfall events, a decentralized management systems can also contribute to mitigate downstream flooding. This requires the operation of the entire system to be optimized depending on the specific environmental conditions, and the participation and access to all the information by the several stakeholders. This system integrates real-time information provided by different entities, including monitoring networks, infrastructure operation data and a forecasting framework. The forecasting system includes several models covering all relevant water compartments: atmospheric, rivers and streams, urban stormwater and wastewater infrastructure, and receiving coastal water bodies circulation and water quality predictions.

References

A. Oliveira, A.B. Fortunato, M. Rodrigues, A. Azevedo, J. Rogeiro, S. Bernardo, L. Lavaud, X. Bertin, A. Nahon, G. Jesus, M. Rocha, P. Lopes, 2021. Forecasting contrasting coastal and estuarine hydrodynamics with OPENCoastS, Environmental Modelling & Software, Volume 143,105132, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2021.105132.

A. Oliveira, A.B. Fortunato, J. Rogeiro, J. Teixeira, A. Azevedo, L. Lavaud, X. Bertin, J. Gomes, M. David, J. Pina, M. Rodrigues, P. Lopes, 2019. OPENCoastS: An open-access service for the automatic generation of coastal forecast systems, Environmental Modelling & Software, Volume 124, 104585, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2019.104585.

How to cite: Oliveira, A., B. Fortunato, A., de Jesus, G., Rodrigues, M., and David, L.: Coastal Digital Twins: building knowledge through numerical models and IT tools, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8041, https://doi.org/10.5194/egusphere-egu23-8041, 2023.

Data Spaces promise an innovative packaging of data and services into targeted one-stop shops of insight. A key ingredient for the fulfilment of the Data Space promise is easier, analysis-ready and fit-for-purpose access in particular to the Big Data which EO pixels and voxels constitute. Datacubes have proven to offer suitable service concepts and today are considered an acknowledge cornerstone.

In the GAIA-X EO Expert Group, a subgroup of the Geoinformation Working Group, one of the use cases investigated is the EarthServer federation. It bridges a seeming contradiction: a decentralized approach of independent data providers - with heterogeneous offerings, paid as well as free - versus
a single, common pool of datacubes where users do not need to know where data sit inorder to access, analyse, mix, and match them. Currently, a total of 140+ Petabyte is online available.

Membership in EarthServer is open and free, with a Charter being finalized ensuring transparent and democratic governance (one data provider - one vote). EarthServer thereby presents a key building block for the forthcoming Data Spaces: not only does it allow unifying data within a given Data Space, it also acts as a natural enabler for bridging and integrating different Data Spaces. This is amplified by the fact that the technology underlying EarthServer
is both the OGC datacube reference implementation and the INSPIRE Good Practice.

In our talk we present concept and practice of location-transparent datacube federations, exemplified by EarthServer, and its opportunities for future-directed Data Spaces.

How to cite: Baumann, P.: Spatio-Temporal Datacube Infrastructures as a Basis for Targeted Data Spaces, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8394, https://doi.org/10.5194/egusphere-egu23-8394, 2023.

EGU23-8788 | Orals | ESSI2.2 | Highlight

Towards the European Green Deal Data Space 

Marta Gutierrez David, Mark Dietrich, Nevena Raczko, Sebastien Denvil, Mattia Santoro, Charis Chatzikyriakou, and Weronika Borejko

The European Commission has a program to accelerate the Digital Transition and is putting forward a vision based on cloud, common European Data Spaces and AI. As the data space paradigm unfolds across Europe, the Green Deal Data Space emerges. Its foundational pillars are to be built by the GREAT project. 

Data Spaces will be built over federated data infrastructures with common technical requirements (where possible) taking into account existing data sharing initiatives. Services and middleware developed to enable a federation of cloud-to-edge capacities will be at the disposal of all data spaces.

GREAT, the Green Deal Data Space Foundation and its Community of Practice, has the ambitious goal of defining how data with the potential to help combat climate and environmental related challenges, in line with the European Green Deal, can be shared more broadly among many stakeholders, sectors and boundaries, according to European values such as fair access, privacy and security. 

The project will consider and incorporate community defined requirements and use case analyses to ensure that the resulting data space infrastructure is designed and built with and for the users. 

An implementation roadmap will guide the efforts of multiple actors to converge toward a blueprint technical architecture, a data governance scheme that enables innovative business cases, and an inventory of high value datasets, that will enable proof of concept, implementation and scale-up of a minimum viable green deal data space.This roadmap will identify the resources and other key ingredients needed for the Green Deal Data Space to be successful. Data sharing by design and data sovereignty are some of the main principles that will apply from the early stages ensuring cost effective and sustainable infrastructures that will drive Europe towards a single data market and green economic growth. 

This talk will present how to engage with the project, the design methodology, progress towards the roadmap for deployment and the collaborative approach to building data spaces in conjunction with all the sectoral data spaces and the Data Space Support Centre.

How to cite: Gutierrez David, M., Dietrich, M., Raczko, N., Denvil, S., Santoro, M., Chatzikyriakou, C., and Borejko, W.: Towards the European Green Deal Data Space, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8788, https://doi.org/10.5194/egusphere-egu23-8788, 2023.

EGU23-9291 | Orals | ESSI2.2

Harmonising the sharing of marine observation data considering data quality information 

Simon Jirka, Christian Autermann, Joaquin Del Rio Fernandez, Markus Konkol, and Enoc Martínez

Marine observation data is an important source of information for scientists to investigate the state of the ocean environment. In order to use data from different sources it is critical to understand how the data was acquired. This includes not only information about the measurement process and data processing steps, but also details on data quality and uncertainty. The latter aspect becomes especially important if data from different types of instruments shall be used. An example for this is the combined use of expensive high-precision instruments in conjunction with lower-cost but less precise instruments in order to densify observation networks.

Within this contribution we will present the work of the European MINKE project which intends, among further objectives, to facilitate the quality-aware and interoperable exchange of marine observation data.

For this purpose, a comprehensive review of existing interoperability standards and encodings has been performed by the project partners. This included aspects such as:

  • standards for encoding observation data
  • standards for describing sensor data (metadata)
  • Internet of Things protocols for transmitting data from sensing devices
  • interfaces for data access

From a technical perspective, the evaluation has especially considered developments such as the OGC API family of standards, lightweight data and metadata encodings, as well as developments coming from the Internet of Things community. This has been complemented by an investigation of relevant vocabularies that may be used for enabling semantic interoperability through a common terminology within data sets and corresponding metadata.

Furthermore, specific consideration was given to the description of different properties that help to assess the quality of an observation data sets. This comprises not only the description of the data itself but also quality related aspects of data acquisition processes. For this purpose, the MINKE project is working on recommendations how to enhance the analysed (meta) data models and encodings with further elements to better transport critical information for better interpreting data sources with regard to the accuracy, uncertainty and re-usability.

Within our contribution we will present the current state of the work within the MINKE project, the results achieved so far and the practical implementations that are performed in cooperation with the project partners.

How to cite: Jirka, S., Autermann, C., Del Rio Fernandez, J., Konkol, M., and Martínez, E.: Harmonising the sharing of marine observation data considering data quality information, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9291, https://doi.org/10.5194/egusphere-egu23-9291, 2023.

EGU23-10223 | Orals | ESSI2.2

Identifying and Describing Billions of Objects: an Architecture to Tackle the Challenges of Volume, Variety, and Variability 

Jens Klump, Doug Fils, Anusuriya Devaraju, Sarah Ramdeen, Jesse Robertson, Lesley Wyborn, and Kerstin Lehnert

Persistent identifiers are applied to an ever-increasing diversity of research objects, including data, software, samples, models, people, instruments, grants, and projects. There is a growing need to apply identifiers at a finer and finer granularity. The systems developed over two decades ago to manage identifiers and the metadata describing the identified objects struggle with this increase in scale. Communities working with physical samples have grappled with these challenges of the increasing volume, variety, and variability of identified objects for many years. To address this dual challenge, the IGSN 2040 project explored how metadata and catalogues for physical samples could be shared at the scale of billions of samples across an ever-growing variety of users and disciplines. This presentation outlines how identifiers and their describing metadata can be scaled to billions of objects. In addition, it analyses who the actors involved with this system are and what their requirements are. This analysis resulted in the definition of a minimum viable product and the design of an architecture that addresses the challenges of increasing volume and variety. The system is also easy to implement because it reuses commonly used Web components. Our solution is based on a Web architectural model that utilises Schema.org, JSON-LD and sitemaps. Applying these commonly used architectural patterns on the internet allows us not only to handle increasing volume, variety and variability but also enable better compliance with the FAIR Guiding Principles.

How to cite: Klump, J., Fils, D., Devaraju, A., Ramdeen, S., Robertson, J., Wyborn, L., and Lehnert, K.: Identifying and Describing Billions of Objects: an Architecture to Tackle the Challenges of Volume, Variety, and Variability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10223, https://doi.org/10.5194/egusphere-egu23-10223, 2023.

EGU23-13331 | Posters on site | ESSI2.2

Data challenges and opportunities from nascent kilometre-scale simulations 

Valentine Anantharaj, Samuel Hatfield, Inna Polichtchouk, and Nils Wedi

Computational experiments using earth system models, approaching kilometre-scale (k-scale) horizontal resolutions, are becoming increasingly common across modeling centers. Recent advances in high performance computing systems, along with efficient parallel algorithms that are capable of leveraging accelerator hardware, have made k-scale models affordable for specific purposes. Surrogate models developed using machine learning methods also promise to further reduce the computational cost while enhancing model fidelity. The “avalanche of data from k-scale models” (Slingo et al., 2022) has also posed new challenges in processing, managing, and provisioning data to the broader user community. 

During recent years, a joint effort between the European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) has succeeded in simulating “a baseline for weather and climate simulations at 1-km resolution,” (Wedi et al., 2020) using the Summit supercomputer at the Oak Ridge Leadership Facility (OLCF). The ECMWF hydrostatic Integrated Forecasting System (IFS), with explicit deep convection on an average grid spacing of 1.4 km, was used to perform a set of experimental nature runs (XNR) spanning two seasons corresponding to a northern hemispheric winter (NDJF), and August - October (ASO) months corresponding the tropical cyclone season in the North Atlantic. 

We developed a bespoke workflow to process and archive over 2 PB of data from the 1-km XNR simulations (XNR1K). Further, we have also facilitated access to the XNR1K data via an open science data hackathon. The hackathon projects also have access to a data analytics cluster to further process and analyze the data. The OLCF data center supports high speed data sharing via globus data transfer mechanism. External users are using the XNR1K data for a number of ongoing research projects, including observing system simulation experiments, designing satellite instruments for severe storms, developing surrogate models, understanding atmospheric processes, and generating high-fidelity visualizations.

During our presentation we will share our challenges, experiences and lessons learned related to the processing, provisioning and management of the large volume of data, and the stakeholder engagement and logistics of the open science data hackathon.

Slingo, J., Bates, P., Bauer, P. et al. (2022) Ambitious partnership needed for reliable climate prediction. Nat. Clim. Chang.  https://doi.org/10.1038/s41558-022-01384-8

Wedi, N., Polichtchouk, I., et al. (2020) A Baseline for Global Weather and Climate Simulations at 1 km Resolution, JAMES. https://doi.org/10.1029/2020MS002192

How to cite: Anantharaj, V., Hatfield, S., Polichtchouk, I., and Wedi, N.: Data challenges and opportunities from nascent kilometre-scale simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13331, https://doi.org/10.5194/egusphere-egu23-13331, 2023.

EGU23-13501 | Posters on site | ESSI2.2

The brokering approach empowering the WMO data space for hydrology 

Enrico Boldrini, Paolo Mazzetti, Fabrizio Papeschi, Roberto Roncella, Massimiliano Olivieri, Washington Otieno, Igor Chernov, Silvano Pecora, and Stefano Nativi

WMO is coordinating the efforts to build a data space for hydrology, called the WMO Hydrological Observing System (WHOS). 
Hydrological datasets have intrinsic value and are worth the enormous human, technological and financial resources required to collect them over long periods of time. Their value is maximized when data is open, of quality, discoverable, accessible, interoperable, standardized, and addressing user needs, enabling various sector users to use and reuse the data. It is essential that hydrological data management and exchange is implemented effectively to maximize the benefits of data collection and optimize reuse.
WHOS provides a service-oriented framework that connects data providers to data consumers. It realizes a system of systems that provides registry, discovery, and access capabilities to hydrology data at different levels (local, basin, regional, global). In 2015, the World Meteorological Congress supported the full implementation of WHOS, which is currently publicly available at https://community.wmo.int/activity-areas/wmo-hydrological-observing-system-whos, along with information for both end users and data providers about how to use and join it.
End users (such as hydrologists, forecasters, decision makers, general public, academia) can discover, access, download and further process hydrological data available through WHOS portal by means of their preferred clients (web applications, tools and libraries).
Data providers (such as National Meteorological and Hydrological Services - NMHSs, river basin authorities, private companies, academia) can share their data through WHOS by publishing it online by means of machine-to-machine web services.
The brokering approach powered by the Discovery and Access Broker (DAB) technology enables the interoperability between data providers’ services and end users’ clients. A mediation layer implemented by the DAB brokering framework mediates between the different standard protocols and data models used by both providers and consumers to seamlessly enable the data flow from  heterogeneous data providers to the clients of each end user.
In parallel, WHOS experts are working in constant collaboration with the data providers to support the implementation of the latest standards required by the international guidelines (e.g., WaterML2.0 and WIGOS Metadata Standard), optimize the data publication and improve the metadata and data quality.
The WHOS Distance Learning course has been successfully conducted; attenders from NMHSs were provided updated information and guidelines to optimize their hydrological data sharing. The course is currently being translated into Spanish to carry out it for Spanish speaking countries in 2023.
WHOS is a hydrological component of WMO Information System (WIS), which is currently in its pilot phase. WHOS and WIS Interoperability tests are currently being piloted and expected to end in 2023. The aim of this interoperability is to promote smooth data exchange between Hydrology community and the wider WMO community. Finally, hydrological data shared through WHOS will be accessible to general WIS users (all piloted programmes, including climate through OpenCDMS, and cryoshere) and at the same time WHOS users will make use of observations made available by WIS.

How to cite: Boldrini, E., Mazzetti, P., Papeschi, F., Roncella, R., Olivieri, M., Otieno, W., Chernov, I., Pecora, S., and Nativi, S.: The brokering approach empowering the WMO data space for hydrology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13501, https://doi.org/10.5194/egusphere-egu23-13501, 2023.

EGU23-14237 | Orals | ESSI2.2

Environmental data value stream as traceable linked data - Iliad Digital Twin of the Ocean case 

Piotr Zaborowski, Rob Atkinson, Alejandro Villar Fernandez, Raul Palma, Ute Brönner, Arne Berre, Bente Lilja Bye, Tom Redd, and Marie-Françoise Voidrot

In the distributed heterogeneous environmental data ecosystems, the number of data sources, volume and variances of derivatives, purposes, formats, and replicas are increasingly growing. In theory, this can enrich the information system as a whole, enabling new data value to be revealed via the combination and fusion of several data sources and data types, searching for further relevant information hidden behind the variety of expressions, formats, replicas, and unknown reliability. It is now visible how complex data alignment is, and even more, it is not always justified due to capacity and business issues. One of the challenging, but also most rewarding approaches is semantic alignment, which promises to fill the information gap of data discovery and joins. To formalise one, an inevitable enabler is an aligned, linked, and machine readable data model enabling the specification of relations between data elements generated information. The Iliad - digital twins of the ocean are cases of this kind, where in-situ data and citizen science observations are mixed with multidimensional environmental data to enable data science and what-if models implementation and to be integrated into even broader ecosystems like the European Digital Twin Ocean (EDITO) and European Data Spaces. An Ocean Information Model (OIM) that will enable traversals and profiles is the semantic backbone of the ecosystem. Defined as the multi-level ontology, it will explain data using well known generic (Darwin Core, WoT), spatio-temporal (SOSA/SSN, OGC Geo, W3C Time, QUDT, W3C RDF Data Cube, WoT) and domain (WORMS, AGROVOC) ontologies. Machine readability and unambiguity allow for both automated validation and some translations.
On the other hand, efficient use of this requires yet another skill in data management and development besides GIS, ICT and domain expertise. In addition, as the semantics used in the data and metadata have not yet been stabilised on the implementation level, it introduces a few more flexibilities of data expression. Following the GEO data sharing and data management principles along with FAIR, CARE and TRUST, the environmental data is prepared for harmonisation. Furthermore, to ease the entry and to harmonise conventions, the authors introduce a multi-touchpoint data value chain API suite with an aligned approach to semantically enrich, entail and validate data sets such as observations streams in JSON or JSON-LD based on OIM, through storage and scientific data in NetCDF to exposing this semantically aligned data via the newly endorsed and already successful OGC Environmental Data Retrieval API. The practical approach is supported by a ready-to-use toolbox of components that presents portable tools to build and validate multi-source geospatial data integrations keeping track of the information added during mesh-up and predictions and what-if implementations.

How to cite: Zaborowski, P., Atkinson, R., Villar Fernandez, A., Palma, R., Brönner, U., Berre, A., Bye, B. L., Redd, T., and Voidrot, M.-F.: Environmental data value stream as traceable linked data - Iliad Digital Twin of the Ocean case, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14237, https://doi.org/10.5194/egusphere-egu23-14237, 2023.

EGU23-15907 | Posters on site | ESSI2.2

GSSC Now - ESA's Thematic Exploitation Platform for Navigation Science Data 

Vicente Navarro, Sara del Rio, Emilio Fraile, Luis Mendes, and Javier Ventura

Nowadays, the sheer amount of data collected from space-borne and ground-based sensors, is changing past approaches towards data processing and storage. In the Information Technology domain, the rapid growth of data generation rates, expected to produce 175 zettabytes worldwide by 2025, is changing approaches to data processing and storage dramatically. This landscape has led to a new golden age of Machine learning (ML), able to extract knowledge and discover patterns between input and output variables given the sheer volume of available training data.

In space, over 120 satellites from four Global Navigation Satellite Systems (GNSS), including Galileo, will provide, already this decade, continuous, worlwide signals in several frequencies. On ground, the professional market represented by thousands of permanent GNSS stations has been complemented by billions of mass-market receivers integrated in smartphones and Internet-of-Things (IoT) devices.

Along their travel down to Earth through the atmosphere, multiple sources alter the precisely modulated GNSS signals. As they pass through irregular plasma patches in the ionosphere, GNSS signals undergo delay and fading, formally known as 'scintillation'. Further down, they are modified by the amount of water vapor in the troposphere. These alterations, recorded by GNSS receivers as digital footprints in massive streams of data, represent a valuable resource for science, increasingly employed to study Earth’s atmosphere, oceans, and surface environments.

In order to realize the scientific potential of GNSS data, at the European Space Astronomy Centre (ESAC) near Madrid, the GNSS Science Support Centre (GSSC) led by ESA’s Navigation Science Office, hosts ESA’s data archive for scientific exploitation of GNSS data.

Analysis of Global Navigation Satellite Systems (GNSS) data has traditionally pivoted around the idea of datasets search and download from multiple repositories that act as data-hubs for different types of GNSS resources generated worldwide. In this work we introduce an innovative GNSS Thematic Exploitation Platform, GSSC Now, which expands a GNSS-centric data lake with novel capabilities for discovery and high-performance-computing.

We explain how this platform performs GNSS data fusion from multiple data sources, enabling the deployment of Machine Learning (ML) processors to unleash synergies across science domains.

Finally, through the presentation of several GNSS science use cases, we discuss the implementation of GSSC Now’s cyber-infrastructure, current status, and future plans to accelerate the development of innovative applications and citizen-science.

How to cite: Navarro, V., del Rio, S., Fraile, E., Mendes, L., and Ventura, J.: GSSC Now - ESA's Thematic Exploitation Platform for Navigation Science Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15907, https://doi.org/10.5194/egusphere-egu23-15907, 2023.

EGU23-16662 | Posters on site | ESSI2.2

NLP-based Cognitive Search Engine for the GEOSS Platform data 

Yannis Kopsinis, Zisis Flokas, Pantelis Mitropoulos, Christos Petrou, Thodoris Siozos, and Giorgos Siokas

Effectively querying unstructured text information in large databases is a highly demanding task. Conventional approaches, such as an exact match or fuzzy search, return valid and thorough results only when the user query adequately matches the wording within the text or the query is included in keyword-tag lists. The GEOSS portal relies on conventional search tools for data and services exploration and retrieval, limiting its capacity. This challenge, recent advances in Artificial Intelligence (AI)-based Natural Language Processing (NLP) try to surpass with enhanced information retrieval and cognitive search. Rather than relying on exact or fuzzy text matching, it detects documents that semantically and conceptually are close enough to the search query. 

The EIFFEL EU-funded project aims to reveal the role of GEOSS as the default Digital Portal for building Climate Change (CC) adaption and mitigation applications and offer the Earth Observation community the ground-breaking capacity of exploiting existing GEOSS datasets. To this end, as a lead technological partner of the EIFFEL consortium, LIBRA AI Technologies, designs and develops an end-to-end advanced cognitive search system dedicated to the GEOSS Portal and exceeds current challenges.

The proposed system comprises an AI language model optimized for CC-related text and queries, a framework for collecting a sizeable CC-specific corpus used for the language model specialization, a back-end that adopts modern database technologies with advanced capabilities for embedding-based cognitive search matching, and an open Application Programming Interface (API). The cognitive search component is the backbone of the EIFFEL visualisation engine, which will allow any GEOSS user, as well as the EIFFEL Climate Change application developing teams, to detect GEOSS data objects and services that are of interest for their research and application but could not effectively get accessed with the available GEOSS Portal search engine.

The work described in this abstract is part of the EIFFEL European project. The EIFFEL project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101003518. We thank all partners for their valuable contributions.

How to cite: Kopsinis, Y., Flokas, Z., Mitropoulos, P., Petrou, C., Siozos, T., and Siokas, G.: NLP-based Cognitive Search Engine for the GEOSS Platform data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16662, https://doi.org/10.5194/egusphere-egu23-16662, 2023.

EGU23-16795 | Posters on site | ESSI2.2

Harmonizing Diverse Geo-Spatiotemporal Data for Event Analytics 

Michael Rilee, Kwo-Sen Kuo, Michael Bauer, Niklas Griessbaum, and Dai-Hai Ton-That

Parallelization is the only means by which it is possible to process large amounts of diverse data on reasonably short time scales. However, while parallelization is necessary for performant and scalable BigData analysis, it is insufficient. We observe that we most often require spatiotemporal coincidence (i.e., at the same space and time) in geo-spatiotemporal analyses that integrate diverse datasets. Therefore, for parallelization, these large volumes of diverse data must be partitioned and distributed to cluster nodes with spatiotemporal colocation to avoid data movement among the nodes necessitated by misalignment. Such data movement devastates scalability.

The prevalent data structure for most geospatial data, e.g., simulation model output and remote sensing data products, is the (Raster) Array, with accompanying geolocation arrays, i.e., longitude-latitude,  of the same shape and size establishing, through the array index, a correspondence between a data array element and its geolocation. However, this array-index-to-geolocation relation is ever-changing from dataset to dataset and even within a dataset (e.g., swath data from LEO satellites). Consequently, it is impossible to use array indices for partitioning and distribution to achieve consistent spatiotemporal colocation.

A simplistic way to address this diversity is through homogenization, i.e., resampling (aka re-gridding) all data involved onto the same grid to establish a fixed array-index-to-geolocation relation. Indeed, this crude approach has become the existing common practice. However, different applications have different requirements for resampling, influencing the choice of the interpolation algorithm (e.g., linear, spline, flux-conserved, etc.). Regardless of which algorithm is applied, large amounts of modified and redundant data are created, which not only exacerbates the BigData Volume challenge but also obfuscates the processing and data provenance.

SpatioTemporal Adaptive-Resolution Encoding, STARE, was invented to address the scalability challenge through data harmonization, allowing efficient spatiotemporal colocation of the “native data” without re-gridding. STARE (1) ties its indices directly to space-time coordinate locations, unlike raster array indices used in the current practice which must go indirectly through the floating-point longitude-latitude arrays to reference geolocation, and (2) embeds neighborhood information in the indices to enable highly performant numerical operations for “joins” such as intersect, union, difference, and complement. These two properties together give STARE its exceptional data-harmonizing power because, when given a pair of STARE indices are associated with a data element, we know not only its spatiotemporal location but also its neighborhood, i.e., the spatiotemporal volume (2D in space plus 1D in time) that the data element represents.

These capabilities of STARE-based technologies allow not only the harmonization of diverse datasets but also sophisticated event analytics. In this presentation, we will discuss the application of STARE to the integrative analysis of Extra-Tropical Cyclones and precipitation events, wherein we use STARE to identify and catalog co-occurrences of these two kinds of events so that we may study their relationships using diverse data of the best spatiotemporal resolution available.

How to cite: Rilee, M., Kuo, K.-S., Bauer, M., Griessbaum, N., and Ton-That, D.-H.: Harmonizing Diverse Geo-Spatiotemporal Data for Event Analytics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16795, https://doi.org/10.5194/egusphere-egu23-16795, 2023.

EGU23-529 | ECS | Posters on site | HS3.8

How consistent are citizens in their observation of temporary streams? 

Mirjam Scheller, Ilja van Meerveld, Sara Blanco, and Jan Seibert

Half of the global river network dries up from time to time. However, these so-called temporary streams are not represented well in traditional gauging networks. One reason is the difficulty in measuring zero flows. Therefore, new approaches, such as low-cost sensors and citizen science, have been developed in the past few years. CrowdWater is such a citizen science project, in which citizens can submit observations of the state of temporary streams with the help of a smartphone app. The flow state of the stream is assessed visually and assigned to one of the following six classes: dry streambed, wet/damp streambed, isolated pools, standing water, trickling water, and flowing.

To determine the consistency of observations by different citizens, we asked questions regarding the flow state to more than 1200 people, who passed by temporary streams of various sizes in Switzerland and Germany. The survey consisted of 19 multiple-choice questions (with 14 being yes/no questions), three rating scale questions, two open-ended questions and five demographic questions, and was available in German and English. Most participants were interested in the topic and happy to participate. We estimate that about 80% of the people we approached participated in the survey.

Over 90% of the participants were native German speakers. When the expert assessment of the flow state was dry streambed, isolated pools or flowing water multiple surveys (4-6) could be done for up to four streams. Other states (standing water and trickling water) were assessed at only one stream. The surveys covered all six flow state classes: dry streambed: 4 times with a total of 244 participants; wet/damp streambed: 3 times with 179 participants; isolated pools: 5 times with 265 participants; standing water: 3 times with 177 participants; trickling water: 2 times with 106 participants; flowing: 6 times with 297 participants.

The answers of the participants were consistent for the driest and wettest states (dry streambed and flowing water) but differed for the in-between states. For example, half of the participants at one stream chose the wet streambed category, while the other half decided on standing water. This suggests that visual assessments of flow states for multiple classes are more complicated than could be assumed initially, but still give additional information beyond the flowing or dry categories. Above all, it provides information for streams that otherwise would be unmonitored.

How to cite: Scheller, M., van Meerveld, I., Blanco, S., and Seibert, J.: How consistent are citizens in their observation of temporary streams?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-529, https://doi.org/10.5194/egusphere-egu23-529, 2023.

Floods are one of the most common and catastrophic natural events worldwide, making studies on the magnitude, severity and frequency of past events essential for risk management. On this wise, remote sensing techniques have been widely used in flooding diagnoses, where Sentinel-2 images are one of the main resources employed in surface water mapping. These studies have developed single band, spectral indexes and machine learning-based methods, which have typically been applied to large water bodies. However, one of the issues in identifying water surfaces remains their size. When water surfaces have sizes close to the spatial resolution of satellite images, they are difficult to detect and map. To improve remotely sensed images' spatial resolution, an algorithm for super-resolving imagery has been developed, giving good results, especially in areas covered by agricultural land with large uniform surfaces. Although this method has proved effective on Sentinel-2 images, it has not been tested for enhancing flood mapping. Thus, flood mapping is still considered an open research topic, as no suitable method has been found for all datasets and all conditions. Consequently, the present study has developed a methodology for flood delineation in small-sized water bodies. The method leverages the advantages of Sentinel-2 MSI data, image preprocessing techniques, thresholding algorithms, spectral indexes and an unsupervised classification method. Thus, this framework includes a) the generation of super-resolved Sentinel-2 images, b) the application of seven spectral indexes to highlight flood surfaces and evaluation of their effectiveness, c) the application of fifteen methods for flood extent mapping, including fourteen thresholding algorithms and one unsupervised classification method and, d) the evaluation and comparison of the performance of flood mapping methods. The technique was applied in the Carrión River, located in the Duero basin, province of Palencia, Spain. This river is classified as a narrow water body, which presents recurrent flood events due to its morphometric characteristics, fluvial dynamics, and land uses. The results obtained show optimal performances when highlighting flood zones by combining AWE spectral indices with methods such as those of Huang and Wang, Li and Tam, Otsu, and momentum-preserving thresholding algorithms and EM cluster classification.

How to cite: Lombana, L.: Flood mapping in small-size water rivers: Analysis of spectral indexes using super-resolved Sentinel-2 images, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-690, https://doi.org/10.5194/egusphere-egu23-690, 2023.

EGU23-2029 | ECS | Posters on site | HS3.8

Showcasing the Potential of Crowd-sourced Observations for Flood Model Calibration 

Antara Dasgupta, Stefania Grimaldi, Raaj Ramsankaran, Valentijn Pauwels, and Jeffrey Walker

Floods are one the costliest natural disasters, having caused global economic losses worth over USD 51 million and >6000 fatalities just in 2020. Hydrodynamic modelling and forecasting of flood inundation requires distributed observations of flood depth and extent to enable effective evaluation and to minimize uncertainties. Given the decline of in situ hydrological monitoring networks, Earth Observation (EO) has emerged as a valuable tool for model calibration and evaluation in data scarce regions, as it provides synoptic observations of flood variables. However, low temporal frequencies and the (currently) instantaneous nature of EO, still limits the ability to characterize fast moving floods. The concurrent rise of smartphones, social media, and internet access has recently led to the emerging discipline of citizen sensing in hydrology, which has the potential to complement real-time EO and in situ flood observations. Despite this, methods to effectively utilise crowd-sourced flood observations to quantitatively assess model performance are yet to be developed. In this study the potential of crowd-sourced flood observations for hydraulic model evaluation is demonstrated for the first time. The channel roughness for the hydraulic model LISFLOOD-FP was calibrated using just 32 distributed high-water marks and wrack marks collected by the community and provided by the Clarence Valley Council for the 2013 flood event. Since the timings of acquisition of these data points were unknown, it was assumed that these provide information on the peak flow. Maximum model simulated and observed water levels were thus compared at observation locations for each model realization, and errors were quantified through the root mean squared error (RMSE) and the mean percentage difference (MPD), respectively. Peak flow information was also extracted from the 11 available hydrometric gauges along the Clarence River and used to constrain the roughness parameter, to enable the quantification of value addition from the citizen sensed observations. Identical calibrated parameter values were obtained for both data types resulting in a mean RMSE value of ∼50 cm for peak flow simulation across all gauges. Outcomes from this study demonstrate the utility of uncertain crowd-sourced flood observations for hydraulic flood model calibration in ungauged catchments.

How to cite: Dasgupta, A., Grimaldi, S., Ramsankaran, R., Pauwels, V., and Walker, J.: Showcasing the Potential of Crowd-sourced Observations for Flood Model Calibration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2029, https://doi.org/10.5194/egusphere-egu23-2029, 2023.

Due to the influence of climate change, the range of change in precipitation and regional variation have increased over the past 10 years, and the occurrence of local drought is increasing. The existing water supply and demand analysis system in Korea is produced by each management department, so there are limitations in data collection and decision-making on water distribution. For efficient water management, integration of water information should be prioritized. Based on this, actual water use monitoring, evaluation and water shortage prediction technology can be developed.

In this study, the DB of water-cycle system was constructed focusing on domestic water and transfer function model was developed. DB construction was classified into 3 stages (pre-preparation/investigation and analysis/application and evaluation), and the first stage was defined as the concept of water inflow/delivery/outflow from the urban perspective and the current status of data by point was identified. In the second stage, research directions were established through expert consultation and undisclosed data were collected through cooperation with related organizations. The third stage was applied to Gongju-si and Nonsan-si in Korea, which are the study sites, and the supplementations were reviewed. A transfer function model was developed using the constructed DB. It is expected that it will be possible to construct a useful transfer function model when analyzing the performance index by learning the outflow of the Singwan sewage treatment equipment based on the water intake amount of the Hyeondo intake station and confirming the autocorrelation of the non-significant residual.

In the future, additional considerations (outlet location, service area, and sewage treatment area subdivision) are required in national reports on river basins and droughts, and precipitation is also considered as a major input factor for outflow.

 

(This work was supported by a grant from the Korea Environmental Industry & Technology Institute (KEITI), funded by the Ministry of Environment (ME) of the Republic of Korea (2022003610003))

How to cite: Lee, S. and Lee, S.: Construction of integrated DB for domestic water-cycle system and development of transfer function model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2201, https://doi.org/10.5194/egusphere-egu23-2201, 2023.

EGU23-2493 | ECS | Posters virtual | HS3.8

pyRCIT - A rainfall nowcasting tool based on a synthetic approach 

Ting He and Thomas Einfalt

Operating precise rainfall nowcasting with the help of observations from weather radar can give an effective warning before hydrometerological hazards occur. A common radar based rainfall nowcasting procedure includes: rain cell identification and tracking, spatial and temporal analysis of rain cell, rainfall nowcasting and nowcasting results evaluation.

In this study, an open source rainfall nowcasting tool - pyRCIT is designed and developed which is purely based on qualified weather radar data. It have four main modules: (1) weather radar data processing; (2) rainfall spatial and temporal analysis; (3) deterministic rainfall nowcasting and (4) ensemble rainfall nowcasting. In pyRCIT, rainfall is firstly obtained from weather radar data sets with a series of data quality adjustment procedures. Secondly, rain cells are identified and their spatial and temporal properties are analyzed by the RCIT algorithm. Thirdly, deterministic rainfall nowcasting is operated following the extrapolating schema using lagrangian persistence and semi-lagrangian methods separately, nowcasting results are evaluated by the object oriented verification method - SAL (Structure-Amplitude-Location). Finally, nowcasting uncertainties are analyzed by the random field theory and the quantified uncertainties are implemented as the aid of ensemble rainfall nowcasting.

Nowcasting quality of pyRCIT are evaluated by comparing it with some main rainfall nowcasting methods: TREC, SCOUT and pySTEPS. Comparative results showed that deterministic nowcasting score of pyRCIT were higher than the TREC and SCOUT methods but is nearly equal to the score of pySTEPS, for the ensemble nowcasting, score of pyRCIT is higher than all three methods for the selected cases. The pyRCIT can serve as the basis for further hydro-meteorological applications such as spatial and temporal analysis of rainfall events and flash flood forecasting.

The code of pyRCIT is available at https://github.com/greensubriane/PYRCIT.git

How to cite: He, T. and Einfalt, T.: pyRCIT - A rainfall nowcasting tool based on a synthetic approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2493, https://doi.org/10.5194/egusphere-egu23-2493, 2023.

EGU23-5818 | Posters on site | HS3.8

Application of multimodal deep learning using radar and water level data for water level prediction 

Seongsim Yoon, Seyong Kim, and Sangmin Bae

In general, water level prediction models using deep learning techniques have been developed using time-series water level observation data from upstream water level stations and target water level stations even though many of physical data are necessary to predict water level. The changes of the water level are greatly affected by rainfall in the basin, therefore rainfall information is needed to more accurately predict the water level. In particular, radar data has the advantage of being able to directly acquire the amount of rainfall occurring within a watershed. This study aims to develop the multimodal deep learning model to predict the water level using 2D grid radar rainfall data and 1D time-series water level observation data. This study proposed two multimodal deep learning models which have different structures. Both multimodal deep learning models predict the water level by simultaneously using the observed water level data up to the present time and the radar rainfall data that affects the water level in the future. The first proposed model consists of a deep learning network that links 2D Average Pooling (AvgPool2D), which compresses 2D radar data to 1D data, and Long Short-Term Memory (LSTM), which predicts 1D time series water level data. The second proposed model consists of a deep learning network that predicts water levels by linking Conv2DLSTM and LSTM, which can reflect the characteristics of 2D radar data without deformation.  The two proposed multimodal deep learning models were learned and evaluated in the upper basin of Hantan River. In addition, it was compared with the results of single-modal LSTM using only water level data. There are three water level stations in the study area, and the objective was to predict the water level of the downstream station up to 180 minutes in advance. For learning and verification of the deep learning model, 10-minute water level and radar rainfall data were collected from May 2019 to October 2021. For the radar data used as input, the grid data included in the target watershed were extracted and used among composite radar data with a resolution of 1 km operating by Ministry of Environment. As a result of evaluating each learned deep learning model, two multimodal models had higher prediction accuracy than the single-modal using only water level data. In particular, second proposed model (Conv2dLSTM+LSTM) had better predictive performance than first proposed model (AvgPool2D+LSTM) at the time of the sudden rise in water level due to rainfall.

Acknowledgments

Research for this paper was carried out under the KICT Research Program (project no. 202200175-001, Development of future-leading technologies solving water crisis against to water disasters affected by climate change) funded by the Ministry of Science and ICT.

How to cite: Yoon, S., Kim, S., and Bae, S.: Application of multimodal deep learning using radar and water level data for water level prediction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5818, https://doi.org/10.5194/egusphere-egu23-5818, 2023.

EGU23-7700 | ECS | Orals | HS3.8

Improved flush detection and classification in combined sewer monitoring 

Markus Pichler and Dirk Muschalla

During rain events, rainwater reaches the combined sewer system and causes additional hydraulic and pollutant load. Due to the limited capacity of the sewer system and the wastewater treatment plant, overflow structures are constructed to reduce the discharge and thus create a potential hazard for the environment. For optimal management of these structures, it is necessary to know the runoff and pollutant load of the events and their distribution over time. When these distributions have a significant peak, they are often referred to as a flush, the best-known phenomenon being the first flush at the beginning of a rainfall event. This knowledge can be used for the design of retention facilities and the calibration of sewer models. The flush phenomena are mainly caused by the erosion of contaminants on the surface as well as the remobilisation of sediments in the sewer network.

Although many papers have investigated the first flush, no common pattern for the occurrence of these flushes has been identified. While the concentration of the flushes in rainwater sewers can be measured directly, the rain flushes in combined sewers are mixed with more polluted wastewater, which leads to a reduction in signal strength.

The sensor site for the used measurement data is located in a combined sewer overflow in the western part of Graz, Austria with a catchment area of 460 ha, consisting mainly of residential areas and with about 19500 inhabitants.

This work aims to separate and classify pollution flush signals from rainfall events in combined sewer systems to better understand the relationship between these signals and rainfall event characteristics.

For this reason, the continuous hydraulic and pollution data are first analysed to determine the representative dry weather contribution. By subtracting the dry weather contribution from the combined wastewater volume and the mass flux, the stormwater contribution and thus the flushes can be estimated. In addition, automatic event detection of combined sewer events was done.

Next, the wet weather events are classified by clustering the stormwater runoff-induced pollutant distribution (flush signals) and the event parameters. For the clustering of the temporal pollutant load distribution of events of different duration, the events are normalised by the mass-volume curves. To obtain the best possible clustering result, the dimension of the mass-volume curves is reduced by a principal component analysis. Different clustering methods, such as partitioning or hierarchical methods, are applied and compared.

How to cite: Pichler, M. and Muschalla, D.: Improved flush detection and classification in combined sewer monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7700, https://doi.org/10.5194/egusphere-egu23-7700, 2023.

EGU23-8802 | Orals | HS3.8

Improving Early Warning System for Urban Flooding in Chinese Mega Cities using Advanced Active Phased Array Radar 

Dehua Zhu, Yunqing Xuan, Richard Body, Dongming Hu, and Xiaojun Bao

This two-year trial aims to bring together academics and industrial partners from UK and China to conduct a pilot study on the use of the active phased array radar to provide early urban flood warnings for Chinese mega cities, which facing challenging urban flood issues. This is the first in the world of cascade modelling using the cutting-edge active phase array radar (APRA) to provide rainfall monitoring and nowcasting information for a real-time two-dimension urban drainage model. The collaboration built up by this project and the first-hand experiment data will serve well to further catalyse the taking-up of state-of-the-art weather radars for urban flood risk management, and to tackle the innovation in tuning the radar technology to fit the complex urban environment as well as advanced modelling facilities that are designed to link the observations, providing decision making support to the city government. Recommendations for applying high spatial-temporal resolution precipitation data to real-time flood forecasting on an urban catchment are provided and suggestions for further investigation are discussed.

How to cite: Zhu, D., Xuan, Y., Body, R., Hu, D., and Bao, X.: Improving Early Warning System for Urban Flooding in Chinese Mega Cities using Advanced Active Phased Array Radar, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8802, https://doi.org/10.5194/egusphere-egu23-8802, 2023.

EGU23-9494 | Orals | HS3.8

A Nonstationary Multivariate Framework for Modelling Compound Flooding 

Yunqing Xuan and Han Wang

 Flooding is widely regarded as one of the most dangerous natural hazards worldwide. It often arises from various sources either individually or combined such as extreme rainfall, storm surge, high sea level, large river discharge or the combination of them. However, the concurrence or close succession of these different source mechanisms can lead to compound flooding, resulting in larger damages and even catastrophic consequences than those from the events caused by the individual mechanism. Here, we present a modelling framework aimed at supporting risk analysis of compound flooding in the context of climate change, where nonstationary joint probability of multiple variables and their interactions need to be quantified.The framework uses the Block Bootstrapping Mann-Kendall test to detect the temporal changes of marginals, and the correlation test associated with the Rolling Window method to estimate whether the correlation structure varies with time; it then evaluates various combinations of marginals and copulas under stationary and nonstationary assumptions. Meanwhile, a Bayesian Markov Chain Monte Carlo method is employed to estimate the time-varying parameters of copulas.

How to cite: Xuan, Y. and Wang, H.: A Nonstationary Multivariate Framework for Modelling Compound Flooding, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9494, https://doi.org/10.5194/egusphere-egu23-9494, 2023.

EGU23-9546 | ECS | Orals | HS3.8

DeepRain: a separable residual convolutional neural algorithm with squeeze-excitation blocks for rainfall nowcasting 

Ahmed Abdelhalim, Miguel Rico-Ramirez, and Dawei Han

Precipitation nowcasting is critical for mitigating the natural disasters caused by severe weather events. State-of-the-art operational nowcasting methods are radar extrapolation techniques that calculate the motion field from sequential radar images and advect the precipitation field into the future. However, these methods assume the motion field's invariance, and prediction is based solely on recent observations, rather than historical radar sequences. To overcome these limitations, deep learning methods such as convolutional neural networks have recently been applied in radar rainfall nowcasting. Although, the promising progress of using deep learning techniques in rainfall nowcasting, these methods face some challenges. These challenges include producing blurry predictions, inaccurate forecasting of high rainfall intensities and degradation of the prediction accuracy with rising lead times. Therefore, the aim of this study is to develop a more performant deep-learning model capable of overcoming these challenges and preventing information loss in order to produce more accurate nowcasts. DeepRain is a convolutional neural network that uses a spatial and channel Squeeze & Excitation Block after each convolutional layer, local importance-based pooling, and residual connections to improve model performance. The algorithm is trained and validated using the UK Met Office's radar rainfall mosaic, which is produced by the UK Met Office Nimrod system. Using verification metrics, the model's predictive skill is compared to another deep learning model and a range of extrapolation methods.

Keywords: deep learning; rainfall nowcasting; radar; convolutional neural networks; Squeeze-and-Excitation

How to cite: Abdelhalim, A., Rico-Ramirez, M., and Han, D.: DeepRain: a separable residual convolutional neural algorithm with squeeze-excitation blocks for rainfall nowcasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9546, https://doi.org/10.5194/egusphere-egu23-9546, 2023.

EGU23-9588 | ECS | Orals | HS3.8

Comparative performance of recently introduced Deep Learning models for Rainfall-Runoff Modelling 

Yirgalem Gebremichael, Gerald Corzo Perez, and Dimitri Solomatine

Machine learning and specifically deep learning has been applied in solving numerous hydrology related problems in the past. Furthermore, extensive research has been done on the evaluation and comparison of performances of different Machine learning techniques applied in solving hydrology related problems. In this research, the possible reasons behind these performance variations are being assessed. The performance of recently introduced deep learning techniques for rainfall-runoff modelling are being evaluated by looking in to the possible modelling set-up and training procedures. Therefore, model set-up and training procedures such as: normalization techniques, input variable selection (feature selection), sampling techniques, model complexity, optimization techniques and random initialization of weights are being examined closely in order to improve the performances of different deep learning techniques for rainfall-runoff modelling. As a result, this study is trying to answer whether these factors have significant effect on the model accuracy.

The experiments are being conducted on different deep learning models such as: LSTMs, GRUs and MLPs as well as non-deep learning models such as: XGBoost, Random Forest, Linear Regression and Naïve models. Deep learning frameworks including TensorFlow and Keras are being implemented on Python. For better generalization, study areas from three different climatic zones namely: Bagmati catchment in Nepal, Yuna catchment in Dominican Republic and Magdalena catchment in Colombia are chosen to implement this experimental research. Additionally, in situ meteorological and stream flow data are being used for the rainfall-runoff modelling.

The preliminary model results show that model performances in case of Bagmati catchment are higher as compared to the other catchments. The LSTMs and MLPs are performing good with NSE values of 0.71 and 0.72 respectively. Most importantly, the linear regression model was outperforming the other models with NSE up to 0.75 in case of considering 6 days lagged rainfall input. This implies the relationship between daily rainfall and runoff data from Bagmati catchment may not be as complex. On the contrary, the 3-hourly data from Yuna catchment shows results with lower values for the performance metrics. This may be an indication of more complex relationships within the Yuna catchment.

This research provides key elements of the modelling process, especially in setting up and training deep learning models for rainfall-runoff modelling. The comparative analysis performed here, provides a basis of performance variations on different basins. This work contributes to the experiences in understanding machine learning requirements for different types of river basins.

How to cite: Gebremichael, Y., Corzo Perez, G., and Solomatine, D.: Comparative performance of recently introduced Deep Learning models for Rainfall-Runoff Modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9588, https://doi.org/10.5194/egusphere-egu23-9588, 2023.

EGU23-10491 | ECS | Posters on site | HS3.8

Addressing discoverability, trust and data quality in peer-to-peer distributed databases for citizen science 

Julien Malard-Adam, Sheeja Krishnankutty, Anandaraja Nallusamy, and Wietske Medema

Peer-to-peer distributed databases show promise for lowering the barrier to entry for citizen science projects. These databases, which do not require a centralised server to store and exchange data, instead use participants’ devices (phones or computers) to store and transfer data directly between project participants. This offers concrete advantages in terms of avoiding usually very costly and time-consuming server maintenance for the research team, as well as improving data access and sovereignty for the participating communities.

However, several technical challenges remain to the routine use of distributed databases in citizen science projects. In particular, indexing data and discovering peers who hold data of interest or from the same project; managing safety, trust and permissions; and ensuring data quality all without relying on a central server to perform these functions requires a rethinking of the standard paradigms of database and user account management.

This presentation will give a brief overview of the Constellation software for distributed scientific databases before presenting several novel approaches (concentric recursive data search, user network-centric trust, and multiple data quality verification layers) it has adopted to respond to the above-mentioned challenges. Examples of concrete applications of Constellation for data sharing in the fields of hydrology and agronomy will be included.

How to cite: Malard-Adam, J., Krishnankutty, S., Nallusamy, A., and Medema, W.: Addressing discoverability, trust and data quality in peer-to-peer distributed databases for citizen science, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10491, https://doi.org/10.5194/egusphere-egu23-10491, 2023.

Population growth and economic development increase water demand, while human activities degrade the quality of available water resources along the adjacent rivers. The U.S. state of Alabama has been suffering from floods causing the degraded water quality by scouring pollutants into the water. In recent decades, Alabama has been experiencing persistent precipitation deficits and unusual severe droughts, resulting in limited economic and water-based recreation activities within downstream states. Since 2020, The COVID-19 pandemic aroused a series policies like quarantine and lock down, which slowed down the economic development and reduced chances of people going outside to witness the water pollution accidents.

In this study, we conducted a sentiment analysis of over 9,900 water pollution complaints (2012-2020) from residents in Alabama. Overall, it is found that complaints are dominated by negative and objective complaints no matter what extremes events or environmental accidents. Results show that sentiment alteration during climate extremes and COVID period was detected. Potential causes of the sentimental alteration in the public water pollution complaint reports were explored. Results show more complaints during summer seasons, which can be explained as higher temperature and intensive precipitation at that time. More complaints are distributed in the counties that are higher socioeconomically developed, to be more specific, counties with more population and higher GDP level. The severity of antecedent extreme events can affect the sentiment of environmental pollution complaints related to on-going extreme events due to limited human judgements. Key words extracted from the complaints point out the pollution resources and locations, which provide important clues from local government to resolved problems.

This study provides an example of how unstructured data such as public complaints can be used as a technology to improve the water pollution and public health monitoring with the help of big data and artificial intelligent technologies. While the results of this study were based water pollution complaints from residents of Alabama state, it is applicable to other environmental pollutions (like air and land) and other regions with available long-term textual data.

 

How to cite: Liu, A. and Kam, J.: Observed Sentimental Alteration in the Public Water Pollution Complaints during Climatic Extremes and the COVID-19 Pandemic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10886, https://doi.org/10.5194/egusphere-egu23-10886, 2023.

EGU23-10937 | ECS | Orals | HS3.8

Feature engineering strategies based on GIS and the SCS-CN method for improving hydrological forecasting in a complex mountain basin 

María José Merizalde, Paul Muñoz, Gerald Corzo, and Rolando Célleri

Hydrological modeling and forecasting are important tools for adequate water resources management, especially in complex systems (basins) characterized by high spatio-temporal variability of runoff driving forces, landscape heterogeneity, and insufficient hydrometeorological monitoring. Yet, during the last decades, the use of machine learning (ML) techniques has become popular for runoff forecasting, and the current research trend focuses on performing feature engineering (FE) strategies aimed both at improving forecasting efficiencies and allowing model interpretation. Here, we employed three ML techniques, the Random Forest (RF) algorithm, traditional Artificial Neural Networks (ANN), and specialized Long-Short Term Memory (LSTM) networks, assisted by FE strategies for developing short-term runoff forecasting models for a 3300-km2 complex basin representative of the tropical Andes of Ecuador. We exploited the information of two readily-available satellite products, the IMERG and GSMaP to overcome the absence of ground precipitation data, and the FE strategies proposed were based on GIS and the Soil Conservation Service Curve Number (SCS-CN) method to synthesize the use of land use and land cover, soil types, slope, among other hydrological concepts. To assess the forecasting improvement, we contrasted a set of efficiency metrics calculated both for the developed specialized models and for referential models without the application of  FE strategies. In terms of results, we were first able to develop accurate forecasting models by exploiting precipitation satellite data powered by ML techniques with different complexity levels. Second, the referential forecasting models reached efficiencies (Nash-Sutcliffe efficiency, NSE) varying from 0.9 (1-hour lead time) to 0.5 (11-hours), which were comparable for the RF, ANN, and LSTM techniques. Whereas for the specialized models, we found an improvement of 5–20 % in NSE-values for all lead times. The proposed methodology and the insights of this study provide hydrologists with new tools for developing short-term runoff forecasting systems in complex basins otherwise limited by data scarcity and model complexity issues.

How to cite: Merizalde, M. J., Muñoz, P., Corzo, G., and Célleri, R.: Feature engineering strategies based on GIS and the SCS-CN method for improving hydrological forecasting in a complex mountain basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10937, https://doi.org/10.5194/egusphere-egu23-10937, 2023.

EGU23-11217 | ECS | Posters on site | HS3.8

International Natural Disasters Research and Analytics (INDRA) Reporter: A multi-platform Citizen Science Framework and Tools for Disaster Risk Reduction 

Manabendra Saharia, Dhiraj Saharia, Shreya Gupta, and Satyakam Singhal

With pervasive access to mobile phones with powerful sensors and processors, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from traditional sensors. But there is a lack of a comprehensive application programming interface (API)-based framework that can collect data from multiple sources through user-friendly workflows. INDRA Reporter has been designed with a mobile-first approach geared towards real-time applications and an emphasis on user-interface/user-experience (UI/UX) to maximize collection of higher fidelity data. This paper details a comprehensive suite of tools for active and passive crowdsensing of natural hazards such as floods, storm, lightning, rain etc. Currently the framework includes mobile applications, telegram chatbots, and a publicly available dashboard. Most citizen science applications in flooding are quantitative, which makes it difficult for non-specialists to provide accurate scientific information along with providing user insight into prevailing situation within a single coherent workflow. It is imperative that workflows targeting dangerous situations emphasize on speed and visual acuity while collecting critical data.  The main objective of INDRA is to provide a simple and intuitive way of collecting qualitative and quantitative data from people. Since traditional data collection through ground-based sensors and satellites suffer from various limitations, measurements collected using INDRA will supplement these sources and form the basis of developing multi-sensor data products. We are reporting the development and release of four components of the framework – a) open INDRA API b) INDRA Reporter mobile application, c) Telegram Chat bot, and d) web dashboard. The API has been kept extensible in order to expand the data collection to other hydrologic and meteorological phenomenon.

How to cite: Saharia, M., Saharia, D., Gupta, S., and Singhal, S.: International Natural Disasters Research and Analytics (INDRA) Reporter: A multi-platform Citizen Science Framework and Tools for Disaster Risk Reduction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11217, https://doi.org/10.5194/egusphere-egu23-11217, 2023.

EGU23-11419 | ECS | Posters on site | HS3.8

Spatio-temporal analysis of storm surge in the Korean Peninsula 

Jung-A Yang

The Korean Peninsula (KP) located in the Northwest Pacific have different topographic features. West coast of the KP has large tidal variations. If storm surge occurred at high tide, the west coast is vulnerable to flooding. The south coast has a complex coastline with hundreds of islands. Its complex topography can amplify storm surge height (SSH) and it also makes it difficult to conduct numerical modeling for storm surge. Moreover, as the KP is located in the pathways of typhoons, it has been affected by an average of three typhoons every year. The KP has actually suffered from storm surge-induced disaster several times in the past. In order to plan efficient and effective countermeasures against storm surge disasters, it is required to identify the vulnerability of coastal regions in the KP. Therefore, this study quantitatively analyzed the frequency and cause of occurrence of storm surges that occurred along the Korean coast in the past.

First, this study collected observed tidal data at 48 tide stations which are installed along the coast of the KP and performed a hormonic analysis on the observed tidal data to build a database of SSH information that occurred along the coast of the KP from 1979 to 2021. Next, the cause of the storm surge was evaluated based on the occurrence time of the high-level SSH. If the storm surge occurred in winter season, it was treated as being caused by an extra-tropical cyclone, and if in summer season, by and tropical cyclone. Lastly, storm surge vulnerable areas were assessed based on frequency and level of the SSH. To this end, the coast of the KP was divided into five zones: the northwest coast, the southwest coast, Jeju island, the southeast coast and northeast coast. The frequency of the high-level SSH generated in those zones was calculated, and areas where storm surge occurred a lot were selected as vulnerable areas.

As a result of the study, it was found that the high-level SSH with more than 1 m in the KP are caused by tropical cyclone in summer, and the area most vulnerable to storm surge is the southeast coast.

However, the observed tidal data used in this study has a limitation in that the collection period differs depending on the zone: the observation period is longer for the southeast coast than for the southwest coast. Looking at the paths of past typhoons, many typhoons passed through the west coast, so the possibility that the southwest coast would have been judged to be more vulnerable than the southeast coast cannot be ignored if the observed tidal data for the southwest coast were more abundant. In addition, since storm surge is phenomenon that is affected not only by meteorological conditions but also by topographic conditions (e.g., complexity of coastline, water depth, etc.), spatio-temporal analysis of storm surge by topographic conditions is going to be conducted through future research.

 

Acknowledgement

This work was supported by the National Research Foundation of Korea grant funded by the Korea government(MSIT) (No. 2022R1C1C2009205).

 

How to cite: Yang, J.-A.: Spatio-temporal analysis of storm surge in the Korean Peninsula, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11419, https://doi.org/10.5194/egusphere-egu23-11419, 2023.

EGU23-12475 | Posters on site | HS3.8

Comparing different radar-raingauge precipitation merging methods for Tuscany region 

Rossano Ciampalini, Andrea Antonini, Alessandro Mazza, Samantha Melani, Alberto Ortolani, Ascanio Rosi, Samuele Segoni, and Sandro Moretti

Radar-based rainfall estimation represents an effective tool for hydrological modelling. Nevertheless, this data type is subject to systemic and natural perturbations that need to be considered before to use it. Because of that and to improve data quality, corrections based on raingauge observations are frequently adopted. Here, we compared the efficacy of different radar-raingauge merging procedures over a regional raingauge-radar network focusing on a selected number of rainfalls events.
We adopted the methods: 1) Kriging with External Drift (KED) interpolation (Wackernagel 1998), 2) Probability-Matching-Method (PMM, Rosenfeld et al., 1994), and 3) a kriging mixed method exploiting the Conditional Merging (CM) process (Sinclair-Pegram, 2005) based on elaborations available at DPCN (Italian National Civil Protection Department). These methods have been applied on the Tuscany Regional Territory using raingauge recorded rainfalls at 15’ time-step and CAPPI (Constant altitude plan position indicator) reflectivity data at 2000/3000/5000 m at 5’ and 10’.
Relationships describing precipitation VS radar reflectivity were integrated and elaborated as part of the development of the merging procedures, while the comparison involved the analysis of variance and diversity coefficients. Kriging-based elaborations showed different spatial patterns depending on the applied procedure, with patterns closer to radar variability when using DPCN, and more reflecting the gauge data structure when adopting KED. The probabilistic method (PMM), instead, had the advantage of integrating the gauge data while preserving the spatial radar patterns, confirming interesting perspectives.

How to cite: Ciampalini, R., Antonini, A., Mazza, A., Melani, S., Ortolani, A., Rosi, A., Segoni, S., and Moretti, S.: Comparing different radar-raingauge precipitation merging methods for Tuscany region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12475, https://doi.org/10.5194/egusphere-egu23-12475, 2023.

EGU23-12857 | Orals | HS3.8

Surge-tide interaction along the Italian coastline 

Alessandro Antonini, Elisa Ragno, and Davide Pasquali

Storm surge events are probably one of the most studied phenomena in coastal regions since they can lead to coastal flooding, environmental damage, and sometimes loss of human life. In regions of shallow water, among other localized processes, surges occurring at high astronomical tides tend to be damped while surges occurring at rising tides are amplified affecting water level extremes. This requires accounting for tide-surge interaction when defining the coastal hazards due to extreme water levels.

Cities along the Italian coast, such as Venice, Ravenna, Bari (Adriatic sea), Genova, Livorno, Napoli, and Palermo (Tyrrhenian sea), are vulnerable to coastal flooding. Hence, a thorough understanding of the interaction between water level components, i.e., storm surge and astronomical tides, is required to define a proper framework for coastal risk assessment.

Here, we analyze water level observations in several Italian coastal locations to investigate possible correlation and interaction between astronomical tide and the storm surge. Then we study the effect that such interaction has on extreme water level statistics to support the development of flood-resilient adaptation strategies.

How to cite: Antonini, A., Ragno, E., and Pasquali, D.: Surge-tide interaction along the Italian coastline, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12857, https://doi.org/10.5194/egusphere-egu23-12857, 2023.

EGU23-12909 | Posters on site | HS3.8

Smart Groundwater Monitoring System for Managed Aquifer Recharge Based on Enabled Real-Time Internet of Things 

Khan Zaib Jadoon, Muhammad Zeeshan Ali, Hammad Ullah Khan Yousafzai, Khalil Ur Rehman, Jawad Ali Shah, and Nadeem Ahmed Shiekh

Groundwater has provided a reliable source of high-quality water for human use. After India, USA and China, Pakistan is the fourth largest groundwater user in the world and around 60x109 m3 of groundwater is extracted annually. The situation in Pakistan has further exacerbated when government subsidized electricity for agricultural purposes – paving the way for installation of myriad tube wells across the country which resulted in excessive withdrawal of groundwater. The major challenges in sustainable groundwater management system are twofold. First, increasing withdrawals to meet growing human needs have led to significant groundwater depletion, which is usually not monitored due to high cost of monitoring system. Second, data limitations and the application of regional groundwater models for future prediction.

In this research, Internet of Things (IoT) enabled smart groundwater monitoring system has been developed and tested to monitor in-situ real-time dynamics of groundwater depletion. Each groundwater monitoring sensor is connected to an embedded module that consists of a microcontroller and a wireless transceiver based on Long Range Radio (LoRa) technology. The readings from each LoRa enabled module is aggregated at one (or more) gateways which is then connected to a central server typically through an IP connection. Sensors of the smart groundwater monitoring system were calibrated in the lab by fluctuation water levels in a 3-meter water column. A network of the low-cost groundwater sensors was installed in managed aquifer recharge wells to provide real-time assessment of groundwater level measurement remotely. The smart and resource efficient groundwater monitoring system help to reduce number of physical visits to the field and also enhance stakeholders participation to get social benefits (promote equity among groundwater users), economic benefit (optimize pumping, which reduces energy cost) and technical benefit (better estimates of groundwater abstraction) for sustainable groundwater management.

How to cite: Jadoon, K. Z., Ali, M. Z., Yousafzai, H. U. K., Rehman, K. U., Shah, J. A., and Shiekh, N. A.: Smart Groundwater Monitoring System for Managed Aquifer Recharge Based on Enabled Real-Time Internet of Things, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12909, https://doi.org/10.5194/egusphere-egu23-12909, 2023.

EGU23-13505 | Posters on site | HS3.8

Water observations by the public- experiences from the CrowdWater project 

Ilja van Meerveld, Franziska Schwarzenbach, Rieke Goebel, Mirjam Scheller, Sara Blanco Ramirez, and Jan Seibert

Hydrology is a data limited science, especially spatially distributed observations are lacking. Citizen science observations can complement existing monitoring networks and provide useful data. Engaging the public in data collection can also increase people’s interest and awareness about water-related topics. In this PICO, we will present the CrowdWater project, in which citizen scientists share, with the help of a smartphone app, hydrological observations on stream water levels, the presence of water in temporary streams, soil moisture conditions, plastic pollution, and general information on water quality. We will highlight the type of data that are collected, our quality control procedures, and the value of the data for hydrological model calibration. We will also discuss the motivations of the citizen scientists to join the project and to continue to contribute to the project. Although the majority of our frequent contributors are adults, we try to engage the youth in the project by giving presentations in schools and at science fairs. Therefore, we will end the PICO presentation with some examples of our outreach work and lessons learned.

How to cite: van Meerveld, I., Schwarzenbach, F., Goebel, R., Scheller, M., Blanco Ramirez, S., and Seibert, J.: Water observations by the public- experiences from the CrowdWater project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13505, https://doi.org/10.5194/egusphere-egu23-13505, 2023.

EGU23-15389 | ECS | Posters on site | HS3.8

An innovative data driven approach improves drought impact analysis using earth observation data 

Ye Tuo, Xiaoxiang Zhu, and Markus Disse

Drought is a devastating natural hazard that can be of diverse magnitude, duration and intensity. It leads to economic and social losses and ecological imbalances. Ascribing to climate change, drought has occurred more frequently with high intensity worldwide in recent decades, such as the striking droughts in the summer of year 2022. In water resource aspect, one direct consequence of drought is the decrease of water amount in the rivers, which could further develop into water shortage for irrigation and drinking water supply, and cargo shipping disruption. Therefore, in order to make management decisions that help mitigate the drought damage, it is important to monitor river water anomalies and identify the vulnerable shrinking sections along the river network. Traditional river gauging stations only provide us limited observations of particular spots. A proper utilization of spatially distributed remote sensing data is necessary and effective. In this work, we develop a novel framework to monitor river water shrinking anomaly by including image processing and machine learning approaches, based on earth observation data. The Rhine, a major cargo-route river, is selected as the pilot case, because it had huge water decrease and caused shipping disruption during the 2022 summer’s drought in Germany. The Modified Normalized Difference Water Index (MNDWI) is calculated from the green and Shortwave-Infrared bands of Sentinel-2 satellite images.  MNDWI images of a specific non-drought period is defined as the reference datasets representing normal conditions. Afterwards, a new water shrinking index is introduced to quantify the river water anomaly during drought periods.  Specifically, a python based algorithm which includes image processing and machine learning clustering methods is developed to scan along the MNDWI images to compute the water shrinking index with adjustable river section size. With the index datasets, river sections are further grouped into categories with drought vulnerable levels. By parameterizing the section size, the algorithm is able to quantify and identify the vulnerable shrinking river sections with varying scales. It provides classified references of drought affected hotspots for the regional water management plans in case of drought mitigation. Such a scalable framework can offer a timely distributed monitoring of the drought impacts on the water resource along the river network. As a long term benefit, numerical connections can be identified between the river shrinking status and the economic losses of cargo shipping disruption due to drought.  This is of great value to facilitate the drought impact analysis and forecasts.

How to cite: Tuo, Y., Zhu, X., and Disse, M.: An innovative data driven approach improves drought impact analysis using earth observation data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15389, https://doi.org/10.5194/egusphere-egu23-15389, 2023.

EGU23-16292 | ECS | Posters on site | HS3.8

Hydrological decision-making systems using high-resolution weather radar observations –  a case study from Hungary 

Zsolt Zoltán Fehér, Erika Budayné-Bódi, Attila Nagy, Tamás Magyar, and Tamás János

According to past observations and long-term forecasts, the Carpathian Basin is distinguished by two precipitation trends. The frequency, length, and severity of periods of precipitation deficit and drought are increasing. Furthermore, as small-scale convective updrafts intensify, heavy thunderstorms become more intense. Both trends pose significant risks from an anthropogenic perspective. The former increases food insecurity due to intensifying droughts, which damages agricultural yields, while the latter mainly increases property damage via heavy hailstorms.

The 2022 drought year demonstrated that effective use of available water is the foundation for sustainable growth, which may be supported by well-designed infrastructure investments and smart water management technologies. A rainfall radar system with a high spatial and temporal resolution that contributes to near real-time machine decision-making is one conceivable component of such a complex system.

The Furuno WR-2100 precipitation radar, which was deployed on the outskirts of Debrecen in 2020 for benchmarking purposes, is the first component of such an intelligent decision-making system in Hungary. The radar's range comprises both urban and rural areas, allowing it to continually gather high-resolution test data for both urban hydrology and agricultural irrigation system developments.

The research presented in the article was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project.

How to cite: Fehér, Z. Z., Budayné-Bódi, E., Nagy, A., Magyar, T., and János, T.: Hydrological decision-making systems using high-resolution weather radar observations –  a case study from Hungary, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16292, https://doi.org/10.5194/egusphere-egu23-16292, 2023.

The quality of mosaic QPE directly determines the accuracy of QPF products from nowcasting models. However, there is a common spatial discontinuity phenomenon caused by the biases of multiple radars in mosaic QPE. Consistency correction, a type of multi-radar quality control method, can be used to mitigate the spatial discontinuity of mosaic QPE, but its improving effect on QPF products should be analyzed.

For this consideration, a consistency correction method based on GPM KuPR proposed by Chu et al (2018a) was applied to the three S-band operational radars of China, and the improvement on QPE by Z-R relationship, deterministic QPF by S-SPROG (Spectral Prognosis), and ensemble QPF by STEPS (Short-Term Ensemble Prediction System) were analyzed. The results showed: 1) the raw reflectivity factors by the three operational radars over the same equidistance area were significantly different. After the consistency correction, the differences decreased to be less than 0.5 dB and the spatial discontinuity of mosaic products disappeared. 2) The precision of mosaic QPE was significantly improved after the correction, and the average RMSE of QPE decreased by 19.5%, and the TS of heavy rainfall and above rose by 44.8%. 3) The 0-1h deterministic QPF by S-SPROG, and ensemble QPF by STEPS were significantly improved after the correction. The deterministic (ensemble) TS of moderate rain and above rose by 11.9% (10.2%), and that of heavy rain and above increased by 34.2% (38.7%). 4) Furthermore, the consistency correction method contributed to precipitation velocity estimation, and decreased its RMSE by 25.0%. Clearly, the consistency correction method is significantly contributive to multi-radar mosaic QPE and precipitation nowcasting.

How to cite: Chu, Z.: Improvement of Multi-Radar Quantitative Precipitation Nowcasting with Consistency Correction Method, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16647, https://doi.org/10.5194/egusphere-egu23-16647, 2023.

GI3 – Planetary and Earth Observation instrumentation

EGU23-320 | ECS | Orals | GI3.1 | Highlight

A comparison of Perseverance rover and HiRISE data: siteinterpretations in Jezero Crater 

Constantijn Vleugels, Bernard Foing, and Okta Swida

Large parts of the Martian surface have been imaged with orbiters. The High Resolution Imaging Science Experiment (HiRISE) can be used to build Digital Terrain Models (DTMs) of Mars with high horizontal and vertical resolution – distinguishing metre-size objects with a vertical error of tens of centimetres – and interpret the geologic history of a site. These maps may aid in rover landing site selection and finding science targets for these missions. However, rover-based imaging ultimately brings the most detailed view of a site and provides ‘ground-truth’ data to orbital observations on much smaller scales. Studying the differences between geologic interpretations from larger scale orbital observations and smaller scale rover images helps understand the limits of orbital maps and the added value of rover observations. We compare remote sensing data from orbit with rover panoramic camera data. The validity of geologic interpretations derived from orbital image data (such as HiRISE) in Jezero Crater is examined with ground-based, publicly available data from Mastcam-Z on the Mars 2020 Perseverance rover. Mastcam-Z can provide stereo colour images of the scene around the rover. 

The rover is currently in its Delta Campaign after landing at the Octavia E. Butler site and its subsequent trip to the Séítah formation, indicated in the figure below which shows Perseverance’s traverse near the western delta of Jezero crater (the basemap is a HiRISE DTM overlaid on a Context Camera mosaic produced by The Murray Lab).  Along the way, it has imaged the Séítah and Máaz formations and outcrops of the western delta formation. These units are expected to be volcanic (Séítah and Máaz) and deltaic (western delta) deposits. We can use the Mastcam-Z images made along the traverse to test what geologic interpretations we can reliably infer from orbital data.

How to cite: Vleugels, C., Foing, B., and Swida, O.: A comparison of Perseverance rover and HiRISE data: siteinterpretations in Jezero Crater, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-320, https://doi.org/10.5194/egusphere-egu23-320, 2023.

EGU23-1679 | ECS | Posters virtual | GI3.1

Improving the Accessibility of Borehole Geophysics: A Cost-Efficient, Highly Modifiable Borehole Tilt Sensor 

Ian Lee, Robert Hawley, David Collins, and Joshua Elliott

We present a cost-efficient borehole tilt sensor that was developed by our group at Dartmouth College to study ice deformation on Jarvis Glacier in Alaska. We first detail the entire sensor development, deployment, and data collection process, along with showcasing successful use cases of our sensors on Jarvis and other glaciers both by our and other geophysical research groups. For our Jarvis work, we installed our tilt sensor system in two boreholes drilled close to the lateral shear margin of Jarvis Glacier and successfully collected over 16 months of uninterrupted borehole deformation data in a harsh polythermal glacial environment. The data included gravity and magnetic measurements that tracked the orientation of the sensors in the borehole as ice flows, and we used the resultant kinematic measurements to compute borehole deformation that provided insights into the ice flow dynamics on polythermal glaciers. Our tilt sensors can house many types of sensors to accommodate different scientific needs (e.g., temperature, pressure, electrical conductivity), and can be adapted for the different glacial thermal regimes and conditions like Athabasca Glacier in Canada, which is a temperate glacier in contrast to Jarvis’ polythermal regime. There remains a high knowledge and financial barrier to entry for borehole geophysics research for both development and procurement of a tilt sensor system, and our goal is to lower this barrier by supporting production efforts of our tilt sensor system for both research and educational needs. With our established sensor development plan and demonstrated success in the field, our group has collaborated with Polar Research Equipment (PRE), a Dartmouth alumni-founded company specializing in the development of polar research tools, to serve as a commercial resource to help support polar researchers during the development and/or production of an effective and cost-efficient (~80% cheaper than commercial versions) tilt sensor and its associated systems.

How to cite: Lee, I., Hawley, R., Collins, D., and Elliott, J.: Improving the Accessibility of Borehole Geophysics: A Cost-Efficient, Highly Modifiable Borehole Tilt Sensor, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1679, https://doi.org/10.5194/egusphere-egu23-1679, 2023.

EGU23-2676 | Orals | GI3.1

MaQuIs - Mars Quantum Gravity Mission 

Lisa Woerner, Bart Root, Philippe Bouyer, Claus Braxmaier, Dominic Dirkx, Joao Encarnacao, Ernst Hauber, Hauke Hussmann, Ozgur Karatekin, Alexander Koch, Lee Kumanchik, Federica Migliaccio, Mirko Reguzzoni, Birgit Ritter, Manuel Schilling, Christian Schubert, Cedric Thieulot, Wolf von Klitzing, and Olivier Witasse

With MaQuIs we propose a mission to investigate the gravitational field of Mars. Observing the gravitational field over time yields information about the planets tectonic lithoshphere, mass distribution, and composition. Consequently, this mission allows to study static and dynamic processes on and under the surface of Mars, including phenomena such as melting cycles and tectonic activity.

MaQuIs will deploy quantum mechanical means to measure Mars gravitational field with the highest precision yet. In addition, the nature of the proposed instrumentation achieves high sensitivities without needing more complex satellite constellations. As such, MaQuIs follows successful missions for the Earth and Moon, extending the technology to Mars.

In this presentation we will outline the expected scientific merit and explain the underlying technology and planned configuration of the mission.  

How to cite: Woerner, L., Root, B., Bouyer, P., Braxmaier, C., Dirkx, D., Encarnacao, J., Hauber, E., Hussmann, H., Karatekin, O., Koch, A., Kumanchik, L., Migliaccio, F., Reguzzoni, M., Ritter, B., Schilling, M., Schubert, C., Thieulot, C., von Klitzing, W., and Witasse, O.: MaQuIs - Mars Quantum Gravity Mission, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2676, https://doi.org/10.5194/egusphere-egu23-2676, 2023.

EGU23-2838 | ECS | Orals | GI3.1

Development of a 3D-printed ion-electron plasma spectrometer with an hemispheric field of view for microsats and planetary missions 

Gwendal Hénaff, Matthieu Berthomier, Leblanc Frédéric, Techer Jean-Denis, Degret Gabriel, and Pledel Sylvain

One of the challenges in space instrumentation is to measure the energy and 3D angular distribution of charged particles within the limited resources available on planetary missions. Current electrostatic energy analyzers allow the measurement of the energy and angular distribution of charged particles around a 2D viewing plane.

Since most planetary probes are three-axis stabilized, electrostatic scanning deflectors are needed to provide the 3D distribution of charged particles using a minimum of two sensors. However, deflections up to +/- 90° cannot be achieved at high energy (above 10-15 keV) while higher energy accelerated particles play a key role in the dynamics of planetary magnetospheres. In addition, electrons and positive ions have to be measured with dedicated sensors which increases the complexity of plasma payloads and of their accommodation on planetary platforms.

We introduce a novel instrument design, that would allow measurement of the energy spectrum and 3D angular distribution of charged particles on three-axis stabilized platforms without using scanning deflectors. The design is possible using new electrostatic geometries and the capability of additive manufacturing technology. An innovative and compact ion/electron detection system is used to simultaneously observe both type of particles with a single sensor.

 We show that we reach the performance of current reference designs while having a true 3D field of view and significantly reducing the payload needs. With a mass budget of 2 kg, our combined electron/ion instrument fits the requirements to fly aboard small satellites. It would significantly reduce the size and cost of the platform and may open new perspectives for planetary exploration by a fleet of micro/nano-satellites.

How to cite: Hénaff, G., Berthomier, M., Frédéric, L., Jean-Denis, T., Gabriel, D., and Sylvain, P.: Development of a 3D-printed ion-electron plasma spectrometer with an hemispheric field of view for microsats and planetary missions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2838, https://doi.org/10.5194/egusphere-egu23-2838, 2023.

NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer was launched to the International Space Station (ISS) on the 14th of July 2022.  EMIT measures the spectral range from 380 to 2500 nm with 285 contiguous spectral channels with 60 m spatial sampling and an 80 km swath.  The EMIT imaging spectrometer is optically fast at F/1.8 to deliver high signal-to-noise ratio observations.  Novel methods are used for on-orbit calibration, dark signal measurement, and geolocation.  The EMIT measurement characteristics and processing results through calibration, atmospheric corrections, and surface mineralogy retrievals are reported.  The EMIT science team will use these new comprehensive observations of surface mineralogy across the Earth’s arid land dust source regions to update the initial conditions of Earth System Models to understand and reduce uncertainties in mineral dust radiative forcing at the regional and global scale now and in the future.  EMIT’s measurements, products, and results with be available to other investigators for the broad set of science and applications they enable through the NASA Land Processes Data Active Archive Center.  The connection between EMIT, Carbon Plume Mapper, the Mapping Imaging Spectrometer for Europa, and the High-resolution Volatiles and Minerals Moon Mapper on Lunar Trailblazer is also described.

How to cite: Green, R.: Imaging Spectroscopy Observations from NASA’s Earth Surface Mineral Dust Source Investigation launched in 2022 and Connections to Imaging Spectrometers for Greenhouse Gas Measurement, Europa, the Moon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4510, https://doi.org/10.5194/egusphere-egu23-4510, 2023.

EGU23-7046 | ECS | Orals | GI3.1

Evolution of the oxygen escape from Earth over geological time scales 

Maria Luisa Alonso Tagle, Romain Maggiolo, Herbert Gunell, Johan De Keyser, Gael Cessateur, Giovanni Lapenta, Viviane Pierrard, and Ann Carine Vandaele

Atmospheric erosion plays a significant role in the long-term evolution of planetary atmospheres, and therefore on the development and sustainability of habitable conditions. Atmospheric escape varies over time, due to changes in planetary conditions and the evolution of the Sun. In the case of a magnetized planet like Earth, the dominant scavenging mechanisms are polar wind and polar cusp escape. Both processes are sensitive to the ion supply from the atmosphere, which depends on the solar EUV radiation and the composition of the neutral atmosphere. Moreover, they are modulated by the coupling between the solar wind and the ionosphere, which depends on the solar wind dynamic pressure and the planetary magnetic moment.

We developed a semi-empirical model of atmospheric loss to extrapolate from current measurements of oxygen escape from Earth to past conditions. This model takes into account the variations of the solar EUV/UV flux, the solar wind dynamic pressure, and the Earth’s magnetic moment. In this study, we identify the main factors and processes that control oxygen escape from Earth, considering present-day atmospheric conditions. We constrain the variation of the oxygen loss rate over time and estimate the total oxygen loss during the last ~2 billion years.

How to cite: Alonso Tagle, M. L., Maggiolo, R., Gunell, H., De Keyser, J., Cessateur, G., Lapenta, G., Pierrard, V., and Vandaele, A. C.: Evolution of the oxygen escape from Earth over geological time scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7046, https://doi.org/10.5194/egusphere-egu23-7046, 2023.

EGU23-7363 | Posters on site | GI3.1

On modeling of silicon detector for space applications using Geant4 

Mikhail Rashev

Silicon detectors are widely used for analyses of particles/radiation in space. They show a good response for a wide spectrum of different particles. Via construction of an appropriate shielding, one can select and analyze only a single sort of particles/their energy and suppress detection of particles of all other kinds. It is difficult to find a good solution for shielding only experimentally. A modeling software such as Geant4 allows us to find a solution for the shielding. This software calculates interaction of particles with shielding or detector and the resulting energy deposition.

The current work is based on modeling of aluminum shielding of the RAPID/IES instrument on board of four Cluster spacecrafts. Since 2000 Cluster mission encounters the Earth's radiation belts and measures energetic electrons among other particles, waves and electromagnetic fields. Accurate modeling using Geant4 allows us to filter unwanted particles out of the result and possibly remove some artifacts in space.

The Geant4 code calculates an attenuation of radiation. Preliminary this software does not calculate electrical signal. There is, however, a possibility to extend the code and add other functionalities. We are exploring possibilities to include signal processing in the Geant4 code for the detector, analog and digital processing units.

How to cite: Rashev, M.: On modeling of silicon detector for space applications using Geant4, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7363, https://doi.org/10.5194/egusphere-egu23-7363, 2023.

EGU23-7966 | ECS | Posters on site | GI3.1

Faraday cup instruments for solar wind and interplanetary dust monitoring 

Oleksii Kononov, Jiří Pavlů, Tereza Ďurovcová, Jana Šafránková, Zdeněk Němeček, and Lubomír Přech

Importance of solar wind monitoring for space weather applications increases with expansion of power networks and oils or gas pipelines to larger geomagnetic latitudes and development of new communication networks. Instruments based on Faraday cups are an ideal solution for these purposes because they are robust and their light weight and low power consumption facilitate their applications for a small spacecraft. Another important feature of Faraday cups is their capability of detection of impacts of interplanetary dust. Such instruments are currently a part of two planned ESA missions that will be briefly introduced. In the core of contribution, we describe the preliminary instrument design and concentrate on most important technical aspects of their development including a computer modeling of the most important parts of detectors. Among others, we present the effects of the grid geometry on the detector capability to determine the plasma velocity vector and temperature and search for optimum detector configuration for small spacecraft missions. We also discuss the data strategy allowing maximum scientific income with limited spacecraft telemetry.

How to cite: Kononov, O., Pavlů, J., Ďurovcová, T., Šafránková, J., Němeček, Z., and Přech, L.: Faraday cup instruments for solar wind and interplanetary dust monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7966, https://doi.org/10.5194/egusphere-egu23-7966, 2023.

EGU23-8161 | ECS | Posters on site | GI3.1

Formulation of spectral indexes from M3 cubes for lunar mineral exploration using python 

Javier Eduardo Suarez Valencia, Angelo Pio Rosi, and Giacomo Nodjourmi

Introduction

The scientific exploration of planetary bodies is enhanced using spectral indexes, and specific band combinations/operations that allow the interpretation of the compositional properties of planetary surfaces. The best hyperspectral sensor for the study of the Moon is M3 onboard Chandrayan-1 (Pieters et al., 2008), it has 86 channels, and covers the range between 450 to 3000 nm, a region that shows the main properties of the rock-forming minerals of the Moon. Although the data of M3 has been widely used with different techniques, there is no unified set of spectral indexes for this instrument, and the ones defined are usually produced in proprietary software. In this work, we compiled spectral indexes from several sources and recreated them in python.

Methods

We compiled spectral indexes from the literature, namely the ones defined by Zambon et al. (2020), Bretzfelder et al. (2020), and Horgan et al. (2014). Before applying the indexes, an M3 cube was processed in ISIS3 (Laura et al., 2022) and filtered in python to reduce the noise. Subsequently, the spectral indexes were replicated according to the procedures described by the authors and compared with the original results. Most of the process was done with common scientific libraries such as rioxarray (Guillies, 2013), OpenCV (Bradski, 2000), specutils (Earl et al., 2022), and NumPy (Harris et al., 2020).

Results

We were able to reproduce fourteen indexes with high fidelity. All of them are formulated to highlight the spectral features around the absorptions in 1000 nm and 2000 nm, which are the location with the major expressions from olivine and pyroxenes. Comparing our results with the ones in the literature, we found that the color ramps are similar in both results and that the surface features showcased in both cases are consistent with each other and their known compositions.

Discussion and conclusions

Small differences between the original indexes and the ones recreated here are expected, due to variations in the internal methods across libraries, the different ways of preprocessing and filtering, and the quality of the original cubes. Further comparison and validation of the procedures is planned.

Nevertheless, we believe that the results are consistent enough to be used as scientific inputs, thus providing an open-source alternative for the analysis of spectral indexes of the surface of the Moon. This work is in progress, and the code is going to be available via EuroPlanet GitHub organization (https://github.com/europlanet-gmap), as well as in the Space Browser of the EXPLORE platform (https://explore-platform.eu/space-browser).

Acknowledgments

This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 101004214.

References

Bradski, G. (2000). The OpenCV Library.

Bretzfelder et al., (2020). Identification of Potential Mantle Rocks Around the Lunar Imbrium Basin.

Earl et al., (2022). astropy/specutils: V1.9.1 

Gillies, S. & others. (2013). Rasterio: Geospatial raster I/O for Python programmers. 

Harris et al., (2020). Array programming with NumPy.

Horgan et al., (2014). Near-infrared spectra of ferrous mineral mixtures and methods for their identification in planetary surface spectra.

Laura et al., (2022). Integrated Software for Imagers and Spectrometers 

Zambon et al., (2020). Spectral Index and RGB maps.

How to cite: Suarez Valencia, J. E., Pio Rosi, A., and Nodjourmi, G.: Formulation of spectral indexes from M3 cubes for lunar mineral exploration using python, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8161, https://doi.org/10.5194/egusphere-egu23-8161, 2023.

EGU23-8918 | ECS | Posters on site | GI3.1

Strofio: A Status Update 

Jared Schroeder, Stefano Livi, and Frederic Allegrini

Strofio is a neutral mass spectrometer designed to measure the chemical composition of Mercury’s exosphere. Neutral species enter the instrument through one of two inlets before they are ionized via electron impact. The product ions are then guided by dozens of individually programmed electrodes toward the detector. A rotating electric field determines the time-of-flight (TOF) of each particle before they collide with a microchannel plate (MCP). Upon launch, one of the system’s electrodes (D5) suffered an anomaly that disrupted communications between the commanded value and the value reported in telemetry. This particular electrode is responsible for steering the particles into the MCP. Laboratory tests with the engineering model confirm mission requirements are satisfied regardless of the electrode state with the caveat being a reduced first-order mass range; however, second-order manipulation can extend the mass range to pre-anomaly standards. I will present the latest advances we have made in optimizing the instrument in its current state.

How to cite: Schroeder, J., Livi, S., and Allegrini, F.: Strofio: A Status Update, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8918, https://doi.org/10.5194/egusphere-egu23-8918, 2023.

EGU23-9318 | ECS | Orals | GI3.1

Training the future Space Entrepreneurs and Astronauts: the experience of the EuroSpaceHub Academy with the Analog Missions for validation of planetary instruments, protocols and techniques 

Serena Crotti, Jara Pascual, Bernard Foing, Agata Kołodziejczyk, Brent Reymen, Ioana Roxana Perrier, Henk Rogers, Sofia Pavanello, Celia Avila Rauch, Gabriel De La Torre, and Armin Wedler

EuroSpaceHub is a project funded by the EIT HEI initiative, led by EIT Manufacturing and Raw Materials. The main goal of the project is fostering collaborative innovation and entrepreneurship in the Space-Tech ecosystem. EuroSpaceHub includes several initiatives; among them is the EuroSpaceHub Academy: an educational programme to train young students, researchers and professionals as Analog Astronauts and Space entrepreneurs.

Thanks to the experience of one of the founding partners of EuroSpaceHub - Lunex EuroMoonMars - students have the opportunity to participate as analog astronauts in various campaigns, which makes them learn with a hands-on approach. Analog missions are both important for carrying out investigations with a view to future Space exploration  and for developing technical scientific knowledge in students. EuroMoonMars has been involved in the organization of these campaigns since 2009, starting at the MDRS (Utah). Other missions were organized at the HISEAS base on the Mauna Loa (Hawaii), in Iceland (CHILL-ICE), in Etna/Vulcano Italy, Atacama Desert (Chile), at the AATC in Poland, ESTEC Netherlands, Eifel Germany and others [1-10]. During analog simulations, students learn to control on-board instruments and to structure their own experiments, collecting data and processing the results efficiently. EuroSpaceHub and Lunex support not only student participation in these missions and their organisation, but also a set of specific trainings under the umbrella of the ESH Academy, complementary to the missions. During the missions, PhD and Master's students can take advantage of special settings and equipment to conduct their investigations, which range from Space and planetary science, instruments, protocols, data analysis,
(biology, psychology, physiology and engineering, to name but a few).

EuroSpaceHub and Lunex are also developing an innovative habitat for analog missions and outreach, ExoSpaceHab Express. Its easy transportation, which is conceived on wheels, makes it a unique contribution in the landscape of existing habitats. Thanks to ExoSpaceHab-X, an increasing number of students will have access to the missions and dedicated training. Also, more and more data will be collected to investigate crews’ reactions in confinement, mission protocols, planning and operations. 

References: [1] Foing, B. et al (2022) LPSC 53, 2042 [2] Foing B. et al (2021) LPSC52, 2502 [3] Musilova M. et al (2020) LPSC51, 2893 [4] Perrier I.R. et al (2021) LPSC52, 2562 [5] Crotti, S. et al (2022) EGU22, 5974 [6] Foing, B. et al (2021) LPSC52, 2502 [7] Heemskerk, M. et al (2021) LPSC52, 2762 [8] Foing, B. et al (Editors, 2011) Astrobiology field Research in Moon/Mars Analogue Environments, Special Issue IJA, 10, vol. 3. 137-305; [9] Foing B. et al. (2011) Field astrobiology research at Moon-Mars analogue site: Instruments and methods, IJA 2011, 10 (3), 141 [10] Foing, B. H. et al, (2017) LPICo2041, 5073 

Acknowledgments: We thank EuroSpaceHub Consortium, collaborators, EIT HEI initiative, EIT Manufacturing and Raw Materials, VilniusTech, Collabwith, International Space University, Universidad Complutense de Madrid, Igor Sikorsky Kyiv Polytechnic Institute, Lunex Foundation and EuroMoonMars. We thank Adriano Autino and Space Renaissance International, all EMMPOL participants and the staff of AATC.

How to cite: Crotti, S., Pascual, J., Foing, B., Kołodziejczyk, A., Reymen, B., Perrier, I. R., Rogers, H., Pavanello, S., Rauch, C. A., De La Torre, G., and Wedler, A.: Training the future Space Entrepreneurs and Astronauts: the experience of the EuroSpaceHub Academy with the Analog Missions for validation of planetary instruments, protocols and techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9318, https://doi.org/10.5194/egusphere-egu23-9318, 2023.

EGU23-9912 | Orals | GI3.1

The Magnetometer on the Psyche mission 

Jose M. G. Merayo, Benjamin P. Weiss, Jodie Ream, Rona Oran, Peter Brauer, Corey J. Cochrane, Kyle D. Cloutier, Lindy Elkins-Tanton, John Leif Jørgensen, Clara Maurel, Ryan S. Park, Carol A. Polanskey, Maria De Soria-Santacruz Pich, Carol A. Raymond, Christopher Russell, Daniel Wenkert, Mark A. Wieczorek, Maria T. Zuber, and Kyle Webster

The asteroid (16) Psyche is the target of the NASA Psyche mission, where the magnetometer is one of the three science instruments on board. Its purpose is to prove whether the asteroid formed from the core of a differentiated planetesimal. The magnetometer will measure the magnetic field at different distances from the asteroid in order to detect any remanent magnetization, where a magnetic moment larger than 2×10^14 Am2 could imply that the body once generated a core dynamo, and therefore formed as an igneous differentiation.

The Psyche spacecraft carries two three-axis fluxgate magnetometers mounted on a fixed boom at 2.15m and 1.45m, respectively, which provide redundancy and gradiometer capabilities to compensate for spacecraft-generated magnetic fields. The magnetometers will be powered on early in the initial checkout phase and remain on throughout cruise and orbital operations and producing 50 vectors per second. The in-flight temperature of the magnetometers is expected to span a large range, therefore an extensive calibration program has been carried out in order to characterize the instruments and prove the performance pre-flight.

How to cite: Merayo, J. M. G., Weiss, B. P., Ream, J., Oran, R., Brauer, P., Cochrane, C. J., Cloutier, K. D., Elkins-Tanton, L., Jørgensen, J. L., Maurel, C., Park, R. S., Polanskey, C. A., Pich, M. D. S.-S., Raymond, C. A., Russell, C., Wenkert, D., Wieczorek, M. A., Zuber, M. T., and Webster, K.: The Magnetometer on the Psyche mission, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9912, https://doi.org/10.5194/egusphere-egu23-9912, 2023.

EGU23-10104 | Orals | GI3.1

Sense-checking the calibration of the Cluster FGM magnetometer spin-axis offsets using mirror mode waves in the magnetosheath 

Leah-Nani Alconcel, Timothy Oddy, Patrick Brown, and Chris Carr

The calibrated data from the Cluster fluxgate magnetometer instruments (FGMs) aboard the four Cluster spacecraft are accessible through the European Space Agency (ESA) Cluster Science Archive (CSA). The FGM team at Imperial College – the PI institute that built and supports operation of the magnetometers – has regularly provided validated data to the CSA since its inception. The calibration and validation pipeline is well established and provides measurements at the highest instrument resolution within an uncertainty as low as 0.1 nT. New methods for magnetic field calibration have been proposed in the many years since Cluster’s commissioning. One of these uses mirror mode waves in the Earth’s magnetosheath to determine the spin-axis offsets of an in-flight magnetometer instrument. The FGM team applied this method to the Cluster instrument data during periods when the spacecraft spend a substantive proportion of their orbits in the magnetosheath, typically May-June and October-November. The offsets determined by this method were compared to those determined by the method already integrated into the pipeline. Good agreement was found between the two methods.

Due to the limitations in resource, the substantial effort that would be required to change calibration methods and re-deliver over 20 years of FGM data, and the potential impact on literature already published, the team would not recommend retroactive integration of the new method into the pipeline. However, the study provides a useful sense check of the pipeline and the data already delivered, as well as the remaining data to be delivered through to the end of the Cluster mission.

How to cite: Alconcel, L.-N., Oddy, T., Brown, P., and Carr, C.: Sense-checking the calibration of the Cluster FGM magnetometer spin-axis offsets using mirror mode waves in the magnetosheath, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10104, https://doi.org/10.5194/egusphere-egu23-10104, 2023.

EGU23-10788 | Orals | GI3.1 | Highlight

Botany on The Moon 

Heather Smith

We propose a suite of instruments, Botany on The Moon, designed to investigate the feasibility of plant growth on the Moon. Botany is composed of two single-species plant growth modules (Arabidopsis, & radish) plus two environmental monitoring instruments that record (1) direct and scattered sunlight in the photosynthetically active radiation or wavelengths (termed PAR), and (2) level of cosmic radiation and induced lunar neutrons. Together these four investigations contribute to our understanding of how plants can be grown on the Moon.

The core perspective in Botany is that physical experiments are needed to understand plant growth on the Moon. Little is known about plant behavior in reduced (fractional) gravity environments (less than the nominal 1g that occurs on Earth). How biology responds to partial gravity (in combination with radiation effects) remains unexplored.

Botany’s primary science goals can be achieved during the sunlit timeframe of a Lunar Day. However, significantly more data and knowledge is gained by extending the growth duration window to approximately 45 Earth days. Hence, Botany is proposing to take advantage of the CLPS provided Survive-the-Night service.  If the CLPS provider is able to provide power for Botany to survive the night, our secondary science goal to determine the feasibility of transitioning the plants from a normal growth phase (at 22oC during the sunlit time) to a slow growth phase (at 5oC during the nighttime), returning to normal growth phase (at 22oC during the second sunlit time) can be achieved. However, all of Botany’s primary science goals can be achieved during the lunar sunlit timeframe, albeit with the loss of data due to the shorter growth duration. The Botany instrument suite including the LPX plant chambers are designed for a 45 Earth-day mission on the Lunar surface, including surviving the 354 hours of the Lunar night. The Botany on The Moon proposed project has a payload mass of ~ 12kg and estimated cost of ~ $11.5 Million U.S. dollars.

The 20-person Botany payload team is led by a mid-career women scientist and involves a gender diverse science and engineering team at various stages in their career from 10 institutions located within three countries. The Botany team includes NASA ARC, KIPR (a long-term NASA ARC contract organization), SDL, UNC-G (a minority serving institution (MSI)), a Canadian instrument provided by McMaster University, and a science team from various institutions. Our team combines complimentary skills, mission management experience, and expertise in plant science.

How to cite: Smith, H.: Botany on The Moon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10788, https://doi.org/10.5194/egusphere-egu23-10788, 2023.

The HyTI (Hyperspectral Thermal Imager) mission, funded by NASA’s Earth Science Technology Office InVEST (In-Space Validation of Earth Science Technologies) program, will demonstrate how high spectral and spatial long-wave infrared image data can be acquired from a 6U CubeSat platform. The mission will use a spatially modulated interferometric imaging technique to produce spectro-radiometrically calibrated image cubes, with 25 channels between 8-10.7 microns, at 13 cm-1 resolution), at a ground sample distance of ~60 m. The HyTI performance model indicates narrow band NEDTs of <0.3 K. The small form factor of HyTI is made possible via the use of a no-moving-parts Fabry-Perot interferometer, and JPL’s cryogenically-cooled HOT-BIRD FPA technology. Launch is scheduled for June 2023. The value of HyTI to Earth scientists will be demonstrated via on-board processing of the raw instrument data to generate L1 and L2 products, with a focus on rapid delivery of data regarding volcanic degassing, and land surface temperature. This presentation will describe the mission and the technology, including the interferometric imaging approach, and how the Cube Sat will support instrument operations and data processing.

How to cite: Wright, R. and the HyTI Team: The HyTI Mission: High Spatial and Spectral Sesolution Imaging from a 6U Cube Satellite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10917, https://doi.org/10.5194/egusphere-egu23-10917, 2023.

EGU23-11555 | Posters on site | GI3.1

BepiColombo: Operations and Data Analysis through the Quick-Look Analysis (QLA) tool 

Thomas Cornet, Alan Macfarlane, Elena Racero, Sebastien Besse, and Santa Martinez

The ESA-JAXA BepiColombo mission is currently en route to Mercury since October 2018. It consists of the ESA Mercury Planetary Orbiter (MPO) and the JAXA Mercury Magnetospheric Orbiter (MMO) spacecraft which, along with the Mercury Transfer Module (MTM), are stacked all together during the seven years’ cruise phase. This long cruise phase is interspersed by nine planetary flybys used to reach Mercury’s orbit capture. In this configuration, most of the MPO instruments located on the nadir side are obstructed by the MTM and cannot observe. Nevertheless, a subset of “side-looking” instruments can be operated in the stacked-spacecraft configuration during the cruise and gather scientific data. These instruments, mostly dedicated to the study of the Hermean environment (magnetic field, solar wind, exosphere), are operated during the planetary flybys as well as for several cruise science observations. Such events are used to test the BepiColombo Science Ground Segment (SGS) operating systems and processes. The SGS develops the Quick-Look Analysis (QLA) tool that will support the rapid analysis of the instruments’ operational and scientific data acquired during the mission science phase observations, starting in 2026. At present, the tool is used to support cruise and flybys operations, in addition to fostering science collaborations between the BepiColombo instrument teams through its data sharing capabilities. We will present the current status and functionalities.

How to cite: Cornet, T., Macfarlane, A., Racero, E., Besse, S., and Martinez, S.: BepiColombo: Operations and Data Analysis through the Quick-Look Analysis (QLA) tool, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11555, https://doi.org/10.5194/egusphere-egu23-11555, 2023.

In response to the problem that ground-based optical monitoring systems cannot monitor near-Earth asteroids which are too close to the Sun on the celestial sphere, we raise a method that tracks and determines the orbit of asteroids by Distant Retrograde Orbit (DRO) platforms with optical monitoring. Through data filtering by visibility analysis and the initial orbit information of the asteroids provided by Jet Propulsion Laboratory (JPL), the asteroids' orbits are determined and compared with the reference orbit. Simulation results show that with a measurement accuracy of two arcseconds and an arc length of three years, the orbit determination accuracy of the DRO platform for near-Earth asteroids can reach tens of kilometers, especially the asteroids with Atira orbits to an accuracy of fewer than ten kilometers. In conclusion, the near-Earth asteroids monitoring systems based on DRO platforms are capable to provide sufficient monitoring effectiveness which enables precise tracking of the target asteroids and forecast of their positions.

How to cite: Yezhi, S.: Near-Earth asteroids orbit determination by DRO space-based optical observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13233, https://doi.org/10.5194/egusphere-egu23-13233, 2023.

EGU23-13996 | ECS | Posters on site | GI3.1

Simulation Study for Precise Orbit Determination of a Callisto Orbiter and Geodetic Parameter Recovery 

William Desprats, Daniel Arnold, Stefano Bertone, Michel Blanc, Adrian Jäggi, Lei Li, Mingtao Li, and Olivier Witasse

Callisto, the outermost of the four Galilean satellites, is identified as a key body to answer present questions about the origin and the formation of the Jovian system. Callisto appears to be the least differentiated and the geologically least evolved of the Galilean satellites, and therefore the one best reflecting the early ages of the Jovian system.

While the ESA JUICE mission plans several flybys of Callisto, an orbiter would allow it to measure geodetic parameters to much higher resolution, as it was suggested by several recent mission proposals,e.g., the Tianwen-4 (China National Space Administration) and MAGIC (Magnetics, Altimetry, Gravity, and Imaging of Callisto) proposals. Recovering parameters such as those describing Callisto’s gravity field, its tidal Love numbers, and its orientation in space would help to significantly constrain Callisto’s interior structure models, including the characterization of a potential subsurface ocean.

We perform a closed-loop simulation of spacecraft tracking, altimetry, and accelerometer data of a high inclination, low altitude orbiter, which we then use for the recovery of its precise orbit and of Callisto’s geodetic parameters. We compare our sensitivity and uncertainty results to previous covariance analyses. We estimate geodetic parameters, such as gravity field, rotation, and orientation parameters and the k2 tidal Love number, based on radio tracking (2-way Doppler) residuals. We consider several ways to mitigate the mismodeling of non-gravitational accelerations, such as using empirical accelerations and pseudo stochastic pulses, and we evaluate the benefits of an on-board accelerometer.

We also investigate the added value of laser altimeter measurements to enable the use of altimetry crossovers to improve orbit determination and gravity-related geodetic parameters, but also to estimate the recovery of surface tidal variations (via the h2 Love number). For our closed-loop analyses, we use both a development version of the Bernese GNSS Software and the open-source pyXover software.

How to cite: Desprats, W., Arnold, D., Bertone, S., Blanc, M., Jäggi, A., Li, L., Li, M., and Witasse, O.: Simulation Study for Precise Orbit Determination of a Callisto Orbiter and Geodetic Parameter Recovery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13996, https://doi.org/10.5194/egusphere-egu23-13996, 2023.

EGU23-14692 | Orals | GI3.1

Project DragLiner: Harnessing plasma Coulomb drag for satellite deorbiting to keep orbits clean 

Maria Genzer, Pekka Janhunen, Harri Haukka, Antti Kestilä, Maria Hieta, Pyry Peitso, Perttu Yli-Opas, Hannah Ploskonka, Petri Toivanen, Janne Sievinen, Marco Marques, David Macieira, Ahmed El Moumen, Farzaneh Gholami, Miguel Olivares-Mendez, Baris Can Yalcin, and Carol Martinez Luna

When a high-voltage charged tether is put into streaming space plasma, the tether’s electric field disturbs the flow of plasma ions and thereby taps momentum from the plasma flow [1-4]. The effect is called electrostatic Coulomb drag. One application is the electric solar wind sail which uses the solar wind to generate interplanetary propulsion [1, 2]. Another application is the Plasma Brake [3, 4] which uses the ionospheric ram flow to generate Coulomb drag that slowly de-orbits the satellite. Both positive and negative tether polarities work. The plasma physics is different, but the net effect is a transfer of momentum in both cases. The reasons are somewhat complicated, but there is good motivation to select positive polarity in the solar wind case and negative polarity in the ionospheric Plasma Brake case. Measurement of Coulomb drag in Low Earth Orbit and testing deployment of tether is to be carried out by ESTCube-2 cubesat [5] which is scheduled for launch in spring 2023, and forthcoming Foresail cubesat scheduled for launch later in 2023-2024.

Project DragLiner is ongoing and funded by ESA to define requirements and a preliminary design of a passive Coulomb Drag based deorbit system capable of bringing down LEO spacecrafts in an order of magnitude shorter time than the current regulations of re-enter time for the spacecraft (25 years). Other main requirements for the deorbiting system are low mass and independence from the spacecraft resources. The project will also create a TRL 4 prototype of a Plasma Brake module that can be used to deorbit a few hundred kilogram satellite or launcher upper stage from Low Earth Orbit. The module deploys ~5 km long tether that is made of four 25-50 micrometre diameter conductive wires. In addition to aluminium wires used previously in Cubesat projects we will also evaluate more advanced carbon fibre composite wires. The redundant multi-wire tether structure is used so that the tether does not break even when micrometeoroids cut some of its wires. The tether is deployed from a storage reel. The tether is kept at -1 kV voltage by an onboard high-voltage source. A ~100 m long metal-coated tape tether is used as an electron-gathering surface that closes the current loop. Alternatively, conducting parts of the debris satellite could be used for electron gathering. The power consumption is a few watts. 

Project Dragliner uses basic Space Plasma Physics to solve a practical and important problem of keeping satellite orbits clean for future generations and preventing a catastrophic Kessler syndrome scenario.

[1] Janhunen, P., Electric sail for spacecraft propulsion, J. Prop. Power, 20, 763-764, 2004.

[2] Janhunen, P. and A. Sandroos, Simulation study of solar wind push on a charged wire: basis of solar wind electric sail propulsion, Ann. Geophys., 25, 755-767, 2007.

[3] Janhunen, P., Electrostatic plasma brake for deorbiting a satellite, J. Prop. Power, 26, 370-372, 2010.

[4] Janhunen, P., Simulation study of the plasma-brake effect, Ann. Geophys., 32, 1207-1216, 2014.

[5] Iakubivskyi, I., et al., Coulomb drag propulsion experiment of ESTCube-2 and FORESAIL-1, Acta Astronautica, 177, 771-783, 2020.

How to cite: Genzer, M., Janhunen, P., Haukka, H., Kestilä, A., Hieta, M., Peitso, P., Yli-Opas, P., Ploskonka, H., Toivanen, P., Sievinen, J., Marques, M., Macieira, D., El Moumen, A., Gholami, F., Olivares-Mendez, M., Yalcin, B. C., and Martinez Luna, C.: Project DragLiner: Harnessing plasma Coulomb drag for satellite deorbiting to keep orbits clean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14692, https://doi.org/10.5194/egusphere-egu23-14692, 2023.

EGU23-14760 | ECS | Posters on site | GI3.1

A novel user-friendly Jupyter-based tool for analysing orbital subsurface sounding radar data. 

Giacomo Nodjoumi, Sebastian Emanuel Lauro, and Angelo Pio Rossi

Orbital radars, such as the SHAllow RADar (SHARAD) [1] or the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) [2] instruments on board Mars Reconnaissance Orbiter (MRO) and Mars Express (MEX) respectively, provide valuable data about the Martian subsurface [3,4].

Common analysis methodologies comprise a direct comparison between the radargram (RDR) and the corresponding Surface Clutter Simulation (SCS) to visually spot any subsurface reflector. The surface time delays converted in the space domain are then compared with the corresponding topographic profile to check if any discrepancy occurred. and thus be mistaken for subsurface reflections. Once confirmed that the subsurface reflector is valid, the proper picking can be performed by looking at the radargram and both the radargram and the simulation power intensities. Finally, it is possible to estimate the real dielectric constant ε', which is the real component of the complex permittivity ε' - iε'' using Equation Eq1 [3]:

where Δt is the two-way travel time between the surface and the subsurface reflector, c is the speed of light in a vacuum and h is the reflector’s depth. Assuming different values for ε' and inverting Eq1, is possible to estimate the depth, thus the thickness of the reflector’s unit. In this work, we present the first pre-release of a user-friendly interface, with which is possible to easily perform the above analysis while granting robustness and reproducibility. Besides, it is possible to implement further custom processing functions to increase the accuracy of the results and/or expand the tool capabilities. We started the development using SHARAD US RDR and SCS, while MARSIS compatibility is under implementation. We provided also additional Jupyter notebooks for data download. This tool is based on the Jupyter lab environment and open-source python packages served as a docker container.

Open Research: The tool presented here is available on GitHub [5]

Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No 101004214 and No 871149.

References:

[1] Seu, R., et al., SHARAD Sounding Radar on the Mars Reconnaissance Orbiter., doi:10.1029/2006JE002745.

[2] Jordan, R., et al., The Mars Express MARSIS Sounder Instrument. doi:10.1016/j.pss.2009.09.016.

[3] Shoemaker, E.S., et al., New Insights Into Subsurface Stratigraphy Northwest of Ascraeus Mons, Mars, Using the SHARAD and MARSIS Radar Sounders. doi:10.1029/2022JE007210.

[4] Lauro, S.E., et al., Using MARSIS Signal Attenuation to Assess the Presence of South Polar Layered Deposit Subglacial Brines. doi:10.1038/s41467-022-33389-4.

[5] Nodjoumi, G. MORDOR - Mars Orbital Radar Data Open-Reader 2023.

How to cite: Nodjoumi, G., Lauro, S. E., and Rossi, A. P.: A novel user-friendly Jupyter-based tool for analysing orbital subsurface sounding radar data., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14760, https://doi.org/10.5194/egusphere-egu23-14760, 2023.

EGU23-14810 | ECS | Orals | GI3.1

Statistics of Alfvénic structures in the Solar Wind and their impact on Magnetometer Calibration 

Johannes Z. D. Mieth, Ferdinand Plaschke, Uli Auster, David Fischer, Daniel Heyner, and Werner Magnes

Exploiting the Alfvénic structures of the solar wind is an established method for calibrating spaceborne magnetometers. However, not every statistical property of Alfvén waves follows a uniform distribution, so calibration accuracy in certain sensor directions may be significantly affected by the choice of the data set used. This work examines the statistical properties of Alfvénic disturbances and other structures of the solar wind in a wide range of spatial and temporal scales using data from the current BepiColombo mission, now in the inner solar system, the lunar and Earth-bound satellites of the THEMIS and ARTEMIS missions, and the Earth-bound MMS mission. The influence of the data selection on calibration is characterized and quantified. We benefit from the fact that the magnetometers of the above-mentioned missions have been partially calibrated by independent methods, using the spacecraft spin or alternative observations of the total magnetic field.

How to cite: Mieth, J. Z. D., Plaschke, F., Auster, U., Fischer, D., Heyner, D., and Magnes, W.: Statistics of Alfvénic structures in the Solar Wind and their impact on Magnetometer Calibration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14810, https://doi.org/10.5194/egusphere-egu23-14810, 2023.

EGU23-15409 | ECS | Orals | GI3.1

Callio SpaceLab – Sustainable living, sustaining life 

Jari Joutsenvaara, Antti Tenetz, Julia Puputti, and Ossi Kotavaara

Callio SpaceLab is an initiative for international space testing, R&D for future human space exploration. SpaceLab's extremely confined environment of the mine and surroundings provide testbeds to simulate human space exploration, analogue astronaut training and experiences for space research and systems in extreme environments on Earth.

Many steps need to be taken here on Earth to put a (hu)man on the Moon and later on Mars. The Earth-based simulation environments are called Terrestrial analogue sites or space analogues. Some analogues are more general, but some have characteristics similar to the extra-terrestrial conditions: e.g., Venus has an analogue environment at Mt. Etna (1), Italy, Mars at Atacama desert (2), Chile and Moon (3), Mauna Kea, Hawai, USA.

Space analogues research covers many topics ranging from testing of habitats and other constructions, fieldwork, in-situ resource utilisation and vehicles; some concentrate on low gravity  (simulated, e.g., in pools) and confinement from the existing world in enclosed environments.

Callio SpaceLab is a concept being developed at the Pyhäsalmi mine, Finland. It is one of Europe’s deepest  (1.4 km) base metal mines. The underground mining ended in 8/2022, but that is just the beginning. The Pyhäjärven Callio is developing the site for a second life, including underground pumped-hydro energy storage, a solar park, FUTUREMINE testing environment for autonomous mining equipment, and more (4,5). Research activities are coordinated by the University of Oulu´s Kerttu Saalasti Institute.

In order to survive on the extraterrestrial landscapes Moon and Mars, one needs to bring enough protection to sustain life and activities. Mine is a suitable terrestrial analogue test environment for confinement studies, biology, astrobiology, in-situ resource utilisation, scientific drilling, rover testing (inclines up to1:7), communications systems testing, space design-, art- and culture projects, etc. (6). The mine has extensive connectivity. Deep space communications can be simulated for different missions, from spaceflights to extraterrestrial bases and activities both on surfaces and in the depth of space objects and celestial bodies.

The site´s hosting rock is a massive volcanogenic sulfide (VMS) deposit formed 1.9 Ga (7). Exploration drilling has found saline water pockets dated at least 30 Ma old. The water samples have shown traces of bacteria common to deep subsurface environments (8).

 

References

  • Gabriel V.,  et al. Mineralogy and Spectroscopy of Mount Etna Lava Flows as an Analogue to Venus. https://ui.adsabs.harvard.edu/abs/2022LPICo2678.2255E
  • Azua-Bustos A.,  et al. The Atacama Desert in Northern Chile as an Analog Model of Mars. 2022. https://doi.org/10.3389/fspas.2021.810426
  • Inge IL ten K.,  et al. Mauna Kea, Hawaii, as an Analog Site for Future Planetary Resource Exploration: Results from the 2010 ILSO-ISRU Field-Testing Campaign. Journal of Aerospace Engineering. https://doi:10.1061/(ASCE)AS.1943-5525.0000200
  • Callio - Mine for Business. 2023. https://callio.info
  • Joutsenvaara J.,  et al. Callio Lab - the deep underground research centre in Finland, Europe. 2021.  https://doi.org/10.1088/1742-6596/2156/1/012166
  • Tenetz A., More than Planet - Deep residency and workshop, creative Eu-project - 2022-2025. http://www.photonorth.fi/fi/projektit/more-than-planet/
  • Imaña M,  et al., 3D modeling for VMS exploration in the Pyhäsalmi district, Central Finland in. In: Proceedings of the 12th Biennial SGA Meeting. 2013. p. 12–5.
  • Miettinen H, et al., Microbiome composition and geochemical characteristics of deep subsurface high-pressure environment, Pyhasalmi mine Finland. https://doi.org/10.3389%2Ffmicb.2015.01203

How to cite: Joutsenvaara, J., Tenetz, A., Puputti, J., and Kotavaara, O.: Callio SpaceLab – Sustainable living, sustaining life, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15409, https://doi.org/10.5194/egusphere-egu23-15409, 2023.

EGU23-2395 | ECS | PICO | GI3.2

Performance of water indices using large-scale sentinel-2 data in Google Earth Engine Computing 

Mathias Tesfaye Abebe and Lutz Breuer

Evaluating the performance of water indices and quantifying the spatial distribution of water-related ecosystems are important for monitoring surface water resources of our study area since there is a limited study available to compute water indices using high-resolution and multi-temporal sentinel-2 data on a large scale. In addition, a comparative performance analysis of water indices methods using the aforementioned dataset on a country scale, showing their strengths and weaknesses, was missing too. To address these problems, this paper evaluated the performance of water indices for surface water extraction in Ethiopia. For this purpose, high spatial and multi-temporal resolution large-scale sentinel-2 data were employed and processed using the Google Earth Engine cloud computing system. In this study, seven indices, namely water index (WI) and automatic water extraction index (AWEI) with shadow and no shadow, normalized difference water index (NDWI), modified normalized difference water index (MNDWI), sentinel water index (SWI), and land surface water index (LSWI) were evaluated with overall accuracy, producer’s accuracy, user’s accuracy, and Kappa coefficient. The result revealed that the WI and AWEIshadow were the most accurate to extract the surface water compared to other indices in qualitative and quantitative evaluation of accuracy indicators obtained with a kappa coefficient of 0.96 and 0.95, respectively, and with overall accuracy for both in 0.98. In addition, the AWEIshadow index was also relatively better at suppressing shadow and urban areas. The accuracy difference between LSWI and other indices was significant which performed the worst with overall accuracy and kappa coefficients of 0.82 and 0.31, respectively. Using best-performing indices of WI and AWEIshadow, 82650 and 86530 square km of surface water fractions were extracted, respectively. Therefore, our result confirmed that WI and AWEIshadow indices generated better water extraction outputs using a high spatial and multi-temporal resolution of sentinel-2 data under a wide range of environmental conditions and water body types on the country scale.

How to cite: Abebe, M. T. and Breuer, L.: Performance of water indices using large-scale sentinel-2 data in Google Earth Engine Computing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2395, https://doi.org/10.5194/egusphere-egu23-2395, 2023.

EGU23-5297 | PICO | GI3.2

DC and FDEM salt wedge monitoring of the Po di Goro river (Italy). 

Enzo Rizzo, Paola Boldrin, Alessandro Bondesan, Francesco Droghetti, Luigi Capozzoli, Gregory De MArtino, Enrico Ferrari, Giacomo Fornasari, Valeria Giampaolo, and Federica Neri

The global warming is affecting the rising seas, which increase the saltwater contamination of the coastal zone in terms of intrusion and penetration in the delta system. The delta systems are characterized by complex dynamic between freshwater coming from continent and saltwater. The hydrodynamic system is greatly affected by the problem of climate change producing a scarce recharge of the aquifers and an increase of the upstream of the mixing zone in the surface waters. These conditions can hinder the water use for irrigation purpose leading to salinization of soils. This summer the Po River underwent a large saltwater intrusion crisis endangering the sustainability of the freshwater resources. The saline wedge in the Po Delta area defined salinisation of groundwater and the soil. These phenomena allow for the active ingression of seawater from the east because the hydraulic head is not sufficient to avoid water to flow inland from the sea. In order to define the water quality, the electrical conductivity (EC) is one of the typical used chemical-physical parameters. However, a common probe defines a punctual acquisition and, therefore, it is time consuming to make a monitor along a long river (> 50km), such as the Po di Goro, that is one of the Po River branches. The research group defined two fast geophysical approach for the monitoring of the saltwater penetration and intrusion. The FDEM method was used to detect the saline wedge in the river and the Electrical Resistivity Tomography was applied to monitor the hydrodynamic iteration between the river and the subsoil around the riverbanks. Two geophysical field activities were planned before and after the salt penetration crisis in the Po River, defined in the last summer. In detail, two ERTs and two long FDEM profiles were carried out along the Po di Goro river. Moreover, a “moving boat” approach with a multilevel EC probe was applied to join the acquired geophysical data set. The ERT sections highlighted how the salty water in the river contaminated the surrounding subsoil. The FDEM data sets defined the hydrodynamic of the saltwater wedge in the river detecting the salty plume front. These results highlight the great potential of the proposed geophysical approach to monitor the saline plume during crisis periods.

How to cite: Rizzo, E., Boldrin, P., Bondesan, A., Droghetti, F., Capozzoli, L., De MArtino, G., Ferrari, E., Fornasari, G., Giampaolo, V., and Neri, F.: DC and FDEM salt wedge monitoring of the Po di Goro river (Italy)., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5297, https://doi.org/10.5194/egusphere-egu23-5297, 2023.

The first recorded environmental protests in Bor, Serbia, began in 1906, only 3 years after the mining and smelting of copper ores started. In 1931, one of the first results of chemical analysis of river water were issued, stating that the content of free acid (as H2SO4) in Bor River just after the mine was 0.0168 %. Another report from 1935 stated that the pH value of Bor River was 4.5, the concentration of Fe was 81 mg/L, and the concentration of Cu was 22 mg/L. At that time, sampling and analysis of river water were initiated by the rebellious local community who wanted compensation for the damage made to their agricultural fields. Throughout the years, the pollution of Bor River became a norm, and researchers from Serbia and the world investigated the pollution from the physical, chemical, mineralogical, and microbiological aspects. From 2015 to 2021, the pH value of Bor River ranged from 2.1 to 6.3, the concentration of Fe ranged from 66 to 355 mg/L, and the concentration of Cu ranged from 4 to 116 mg/L, depending on the intensity of mining and smelting activities. These more recent results are not so different from those about a century before. However, since the mining and smelting combine Bor changed its ownership in 2018, the monitoring of the pollution became more advanced, and there are more reclamation activities. Several automatic monitoring stations with inductively coupled plasma optical emission spectrometers or mass spectrometers (ICP-OES or ICP-MS) were installed in the field by the polluted rivers for the purpose of monitoring. Water from the largest acid mine drainage accumulation, the Robule Lake, was treated, drained, and in 2023. the Robule Lake does not exist anymore. Additional monitoring and reclamation activities are expected which could reduce the pollution of Bor River in the future.

How to cite: Stefan, D.: Past and present monitoring results of acid mine drainage around copper mines and smelter in Bor, Serbia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9667, https://doi.org/10.5194/egusphere-egu23-9667, 2023.

EGU23-9701 | ECS | PICO | GI3.2

Applicability of remote sensing evapotranspiration products in reducing uncertainty and equifinality in hydrological model calibration of Oued El Abid watershed. 

Soufiane Taia, Lamia Erraioui, Jamal Chao, Bouabid El Mansouri, and Andrea Scozzari

Typically, hydrological models are calibrated using observed streamflow at the outlet of the watershed. This approach may fail to mimic landscape characteristics, which significantly impact runoff generation because the streamflow incorporates contributions from several hydrological components. However, remotely sensed evapotranspiration (AET) products are commonly used as additional data with streamflow to better constrain model parameters. Several researchers demonstrated the efficacy of AET products in reducing the degree of equifinality and predictive uncertainty, resulting in a significant enhancement in hydrological modelling. Due to the variety of publicly available AET datasets, which vary in their methods, parameterization, and spatiotemporal resolution, selecting an appropriate AET for hydrological modelling is of great importance. The purpose of this study is to investigate the difference in simulated hydrologic responses resulting from the inclusion of different remotely sensed AET products in a single and multi-objective calibration with observed streamflow data. The GLEAM_3.6a, GLEAM_3.6b, MOD16A2, GLDAS, PML_V2, TerraClimate, FLDAS, and SSEBop datasets were downloaded and incorporated into the calibration of the SWAT hydrological model. The findings indicate that the incorporation of remotely sensed AET data in multi-objective calibration tends to improve model performance and decrease predictive uncertainty, as well as significantly improves parameter identification. Furthermore, AET single-variable calibration results show that the model would have performed well in simulating streamflow even without streamflow data. Moreover, each dataset included in this investigation responded differently. GLEAM_3.6b and GLEAM_3.6a performed the best, followed by FLDAS and PML_V2, while MOD16A2 was the least performing dataset. Thus, this research supports the use of remotely sensed AET in the calibration of hydrological models as a best practice.

 

How to cite: Taia, S., Erraioui, L., Chao, J., El Mansouri, B., and Scozzari, A.: Applicability of remote sensing evapotranspiration products in reducing uncertainty and equifinality in hydrological model calibration of Oued El Abid watershed., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9701, https://doi.org/10.5194/egusphere-egu23-9701, 2023.

EGU23-10657 | PICO | GI3.2 | Highlight

Evaluating the applicability of transient electromagnetic (TEM) data to characterize aquifer geometry in urban areas 

Adrián Flores Orozco, Lukas Aigner, and Josef Ferk

Understanding subsurface properties within urban areas is critical for an adequate management of groundwater, for instance to delineate the migration of pollutants, artificial recharge systems or geothermal collectors. Information is available from extraction wells, yet the resolution of the information is limited to the locations where wells are available. Geophysical methods offer an alternative to gain subsurface information. However, asphalted roads and limited accessibility might reduce the applicability of electrical methods for investigations beyond a few meters, whereas vibrations due to traffic and railroads might hinder the application of seismic methods. In this work, we investigate the use of the transient electromagnetic (TEM) method to resolve the geometry of aquifers in urban areas. We propose the use of relative small loops to gain separation from buried structures and increase data quality in late times as required to reach a depth of investigations of ca. 40 m. Measurements were conducted in gardens located within cities deploying single-loop as well as in-loop geometries using two different instruments. Additionally, we evaluate our small loop configuration in a quasi noise-free site through comparison to larger loops and electrical methods. Analysis of the data demonstrate that relative small loops (12.5 m x 12.5 m) may be a possible solution to gain information in urban areas down to a depth of 30 m, yet a minimal separation to anthropogenic structures of ca. 5 m is required. Information at such depth can not be easily gain with refraction seismic or electrical resistivity tomographic measurements in such small areas. Moreover, our results reveal the possibility to gain similar information with smaller loops (6.25 m x 6.25 m), offering the possibility to increase the separation to sources of noise (i.e., buried infrastructure) and increase the data quality. The inversion of TEM measurements collected along a 100 m profile permitted to obtain vertical and lateral variations in aquifer geometry with a maximal depth of investigation of ca. 40 m, while DC-resistivity measurements in the same profile were limited to less than 10 m depth. Stochastic inversion of the data permitted to investigate the uncertainty in the obtained model parameters (resistivity and thickness of the resolved layers, i.e., aquifer).

How to cite: Flores Orozco, A., Aigner, L., and Ferk, J.: Evaluating the applicability of transient electromagnetic (TEM) data to characterize aquifer geometry in urban areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10657, https://doi.org/10.5194/egusphere-egu23-10657, 2023.

EGU23-11724 | PICO | GI3.2

The IceWorm: an improved low-cost, low-power sensor for measuring dissolved CH4 in water bodies 

Jesper Christiansen, Sarah Elise Sapper, and Christian Juncher Jørgensen

Recent studies show emissions of dissolved methane (CH4) in the meltwater from the Greenland Ice Sheet. To better understand the phenomenon and evaluate its potential significance for the Arctic CH4 budget, continuous long-term measurements of dissolved CH4 concentrations are needed. Commercially available dissolved CH4 analyzers (DGEU-UGGA (LGR), CONTROS HydroC CH4 (Kongsberg) and Mini CH4 (pro-Oceanus)) generally have high power consumption and are very costly, limiting their operation in remote off-grid locations.

Here we present calibrations and field tests of a low-cost, low-power alternative – the "IceWorm" - for long-term monitoring of dissolved CH4. The IceWorm uses a Figaro TGS2611-E00 metal oxide sensor (MOS). While MOS are cheap and power efficient, a known drawback is the sensitivity of the sensor's resistance to changes in humidity and temperature. In a previous prototype, we showed that by encasing the MOS in a hydrophobic and gas-permeable silicone membrane, a constant humidity in the headspace around the sensor can be achieved, yielding consistent results when deployed in glacial meltwater at constant temperature (0.0 – 0.1˚C)1. In this updated version, the sensor was encased in a hydrophobic and gas-permeable Teflon membrane allowing for fast (~1 min) equilibrium between the water and headspace around the sensor and hence a rapid detection of changes in dissolved CH4 concentrations.

The first calibration was performed by exposing the IceWorm to stepwise increasing Two field calibrations of the sensor performance in meltwater at 0.0˚C were done: Afterwards, the sensors remained in the field for several weeks in the subglacial meltwater stream and the sensors were recalibrated in lab air under the same conditions to check for long-term sensor drift. Initially, field calibrated to measure dissolved CH4 in glacial meltwater at 0.0˚C, the IceWorm was also tested in a freshwater surface stream at temperatures between 1.6 – 15.7˚C. To account for the temperature difference, we compared the laboratory and field calibrations allowing us to correct the sensor output to temperature variations in the stream.

We will present time series of long-term measurements of dissolved CH4 in two different types of water bodies and discuss the promising performance of the sensor at temperatures different to stable 0˚C as well as the usability of in-air calibrations compared to the field calibrations with discrete samples.

1. Sapper et al. (2022) DOI:10.5194/egusphere-egu22-9972

How to cite: Christiansen, J., Sapper, S. E., and Juncher Jørgensen, C.: The IceWorm: an improved low-cost, low-power sensor for measuring dissolved CH4 in water bodies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11724, https://doi.org/10.5194/egusphere-egu23-11724, 2023.

EGU23-12141 | PICO | GI3.2

A framework for cost-effective enrichment of water demand records at fine spatio-temporal scales 

Panagiotis Kossieris, Ioannis Tsoukalas, and Christos Makropoulos

Residential water demand is a key element of urban water systems, and hence its analysis, modelling and simulation is of paramount importance to feed modelling applications. During the last decades, the advent of smart metering technologies has released new streams of high-resolution water demand data, allowing the modelling of demand process at fine spatial (down to appliance level) and temporal (down to 1 sec) scales. However, high-resolution data (i.e., lower than 1 min) remains limited, while longer series at coarser resolution (e.g., 5 min or 15 min) do exist and are becoming increasingly more available, while the metering devices with such sampling capabilities have potential for a wider deployment in the near future. This work attempts to enrich the information at fine scales addressing the issue of data unavailability in a cost-effective way. Specifically, we present a novel framework that enables the generation of synthetic (yet statistically and stochastically consistent) water demand records at fine time scales, taking advantage of coarser-resolution measurements. The framework couples: a) lower-scale extrapolation methodologies to provide estimations of the essential statistics (i.e., probability of no demand and second-order properties) for model’s setup at fine scales, and b) stochastic disaggregation approaches for the generation of synthetic series that resamples the regime of the process at multiple temporal scales. The framework, and individual modules, are demonstrated in the generation of 1-min synthetic water demands at the household level, using 15 min data from the available smart meter.

How to cite: Kossieris, P., Tsoukalas, I., and Makropoulos, C.: A framework for cost-effective enrichment of water demand records at fine spatio-temporal scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12141, https://doi.org/10.5194/egusphere-egu23-12141, 2023.

EGU23-14097 | PICO | GI3.2

Geofluids inferences using deep electrical resistivity tomography for a sustainable energy transition 

Valeria Giampaolo, Luigi Capozzoli, Gregory De Martino, Vincenzo Lapenna, Giacomo Prosser, Fabio Olita, Paola Boldrin, and Enzo Rizzo

In the last years, the use of Deep Electrical Resistivity Tomography (DERT) has become more common for the investigation of areas with complex geological setting. The considerable resolution obtained through such a technique makes it possible to discriminate much more effectively the resistivity contrasts existing in the shallower crustal levels, thus providing more reliable information on the physical conditions of the rocks, the presence of structural discontinuity surfaces, on the presence and trend in the subsoil of aquifers and/or fluids of various origins.

For these reasons, some DERT investigations were carried out in a structurally complex area located close to Tramutola village, in the western side of the Agri Valley, where the largest onshore hydrocarbon reservoir in west Europe is present.

The Tramutola site represented a key sector for the early petroleum exploration and exploitation of the area. Natural oil spills were historically known since the 19th century in the investigated area, and these helped the national oil company to identify the first shallower hydrocarbon traces. Furthermore, a considerable amount of sulphureous hypothermal water (~28 °C with a flow rate of 10 l/s) with associated gases (mainly CH4 and CO2) was found during the drilling of the “Tramutola2” well (404.4 m) in 1936. From a geological point of view, the study area, is characterized by the presence of a complete section of the tectonic units of the southern Apennines and a complex structural framework, not yet fully clarified, which affect fluids circulation.

To foster the efficient and sustainable use of the geothermal resource in Tramutola area, surface and subsurface geological, hydrogeological and new geophysical data were combined in order deepen our knowledges about the reservoir of the hypothermal fluids and their circulation.

The municipality of Tramutola is interested in the rehabilitation of the abandoned oil wells, both in terms of exploitation of the geothermal resource and for the realisation of a tourist “Park of energy”. The aim is to provide a wide audience with strategies, models, and technical skills capable of making visitors more active and critical towards the sustainable use of energy resources. Furthermore, the possible exploitation of geothermal resources of the Tramutola site represents a strategic action in the Basilicata region as a prototype of energy transition from fossil fuels to more environmentally friendly energy resources. This is also essential to satisfy the increased demand for clean energy in the area (no. 7 affordable and clean energy United Nations’ SDGs) and also contribute to climate change mitigation through the reduction of CO2 emissions (13 climate action).

How to cite: Giampaolo, V., Capozzoli, L., De Martino, G., Lapenna, V., Prosser, G., Olita, F., Boldrin, P., and Rizzo, E.: Geofluids inferences using deep electrical resistivity tomography for a sustainable energy transition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14097, https://doi.org/10.5194/egusphere-egu23-14097, 2023.

EGU23-14977 | PICO | GI3.2

A low-cost novel optical sensor for water quality monitoring 

Sean Power, Louis Free, Chloe Richards, Ciprian Briciu-Burghina, Adrian Delgado Ollero, Ruth Clinton, and Fiona Regan

With increasing environmental pressure due to global climate change, increases in global
population and the need for sustainable obtained resources, water resources management
is critical. In-situ sensors are fundamental to the management of water systems by providing
early warning, forecasting and baseline data to stakeholders. To be fit-for-purpose,
monitoring using in-situ sensors has to be carried out in a cost effective way and allow
implementation at larger spatial scales. If networks of sensors are to become not only a
reality but common place, it is necessary to produce reliable, inexpensive, rugged sensors
integrated with data analytics.


In this context, the aim of this project was to design and develop a low cost, robust and
reliable optical sensor which capable of continuous measurement of chemical and physical
parameters in aquatic environments. An iterative engineering design method cycling
between sensor design, prototyping and testing was used for the realisation and optimisation
of the sensor. The sensor can provide absorption, scatter, and fluorescence readings over a
broad spectral range (280nm to 850nm) and temperature readings in real-time using a suite
of optical sensors (CMOS Spectrometers and photodiode detector), custom designed LED
array light source and a digital temperature probe. Custom electronics and firmware were
developed to control the sensor and facilitate data transmission to an external network.
Sensor electronics are housed in a marine grade watertight housing; the optical components
are mounted inside a custom designed 3D-printed optical head which joins with the sensor
housing. The sensor is capable of measuring a range of optical parameters and temperature
in a single measurement cycle. Sensor analytical performance was demonstrated in the
laboratory, for detection and quantification of turbidity using analytical standards and in the
field by comparison with a commercially available multi- parameter probe (YSI, EXO 2).
The laboratory and field trials demonstrate that the sensor is fit-for-purpose and an excellent
tool for early warning monitoring by providing high frequency time-series data, operate
unattended in-situ for extended periods of times and capture pollution events.

Acknowledgement - This research is carried out with the support of Project Ireland’s 2040’s
Disruptive Technologies Innovation Fund.

How to cite: Power, S., Free, L., Richards, C., Briciu-Burghina, C., Delgado Ollero, A., Clinton, R., and Regan, F.: A low-cost novel optical sensor for water quality monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14977, https://doi.org/10.5194/egusphere-egu23-14977, 2023.

EGU23-15083 | PICO | GI3.2

Gedi Data Within Google Earth Engine: Potentials And Analysis For Inland Surface Water Monitoring 

Alireza Hamoudzadeh, Roberta Ravanelli, and Mattia Crespi

Inland surface water is the source of about 60% and a key component of the hydrological cycle. The monitoring of inland surface water is fundamental to understanding the effects of climate change on this key resource and preventing water stresses. Water levels traditionally measured by ground instruments like gauge stations are expensive and have high maintenance costs. Conversely, Earth Observation technologies can nowadays collect frequent and regular data with continuous monitoring of water reservoirs, reducing monitoring costs.

 

With the availability of new data, the need for a capable computation tool is crucial. Google Earth Engine (GEE), a cloud-based computation platform capable of integrating a high variety of datasets with powerful analysis tools [1], has recently added the Global Ecosystem Dynamics Investigation (GEDI) [4] to its wide archive. 

 

The GEDI [2] instrument, hosted onboard the International Space Station,  is a geodetic-class, light detection and ranging (LiDAR) system, having a 25 m spot (footprint) on the surface over which 3D structure is measured. The footprints are separated by 60 m along-track, with an across-track distance of about 600 m. The measurements are made over the Earth's surface nominally between the latitudes of 51.6° and -51.6°. GEDI was originally developed to enable radically improved quantification and understanding of the Earth’s carbon cycle and biodiversity. 

 

The available literature highlights that the quality of GEDI data is variable and impacted by several factors (e.g., latitude, orbit). Our preliminary analysis is focused on the accuracy assessment of the GEDI data, at first addressing the problem of outliers detection and removal, and secondly comparing the water levels measured by GEDI with reference ground truth; thus, we considered four lakes in Northern Italy for which level measurements from gauge stations are available.

The proposed outlier detection consists of two steps for each GEDI passage over water surfaces.

The first step is based on two flags implanted within GEDI bands. Specifically, the “quality_flag” indicates if the considered footprint has valid waveforms (1=valid, 0=invalid), due to anomalies in the energy, sensitivity, and amplitude of signals; the “degrade_flag” indicates the degraded state of pointing (saturation intensity of returned photons might reduce the accuracy of measurements) and/or positioning information (GPS data gap, GPS receiver clock drift).

The second step relies on the robust version of the standard 3σ test, implemented considering the NMAD (Normalized Median Absolute Deviation): every GEDI measurement not within -/+3*NMAD from the median is removed as outlier.

To assess the outlier detection procedure and to preliminarily evaluate the accuracy of the GEDI data, we compared the water levels inferred from the median of GEDI measurements after outlier removal with the contemporary water levels from hydrometric stations at four major lakes (Como, Garda, Iseo, Maggiore) in Northern Italy [3]. The comparison is ongoing over the period from GEDI activation until June 2022, for 3 years.

References

[1] Cardille, et al., 2022. Cloud-Based Remote Sensing with Google Earth Engine.

[2] Dubayah, et al., 2021. GEDI L3 gridded land surface metrics, version 1

[3] Enti Regolatori dei Grandi Laghi, 2022. Home Page - Laghi. www.laghi.net.

[4] University of Maryland, 2022. GEDI ecosystem lidar

How to cite: Hamoudzadeh, A., Ravanelli, R., and Crespi, M.: Gedi Data Within Google Earth Engine: Potentials And Analysis For Inland Surface Water Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15083, https://doi.org/10.5194/egusphere-egu23-15083, 2023.

EGU23-15274 | PICO | GI3.2 | Highlight

Cost-effective full monitoring system for long-term measurements in lake ecosystems 

Daniele Strigaro, Massimiliano Cannata, Camilla Capelli, and Fabio Lepori

The concomitance of climate changes and human activities effects is a mix of co-factors that can induce unknown dynamics and feedbacks which need to be studied and monitored. Lakes are one of the most affected natural resources. Due to their importance for economy, water supply, tourism it is essential to safeguard their health. Unfortunately, lake monitoring is dominated by very high costs of materials and by proprietary solutions that are a barrier for data interoperability. To this end, an integrated system which uses as much open source licensed technology as possible and is open source itself will be presented. The main idea is to create a complete pipeline that can integrate different data sources by means of processes that can make the time series organized and accessible and then be served via standard services. Data integration allows further analysis of the data to produce new time series either by manual or automatic processes. This proposition also includes the creation of an Automatic High-Frequency Monitoring (AHFM) system built using cost-effective principles and meeting open design requirements. The preliminary results and the applications of this solution will be described such as the calculation of the primary production and the quasi real-time detection of algal blooms. The study area where this system has been developed and tested is Lake Lugano in the southern part of Switzerland, which is a very productive lake affected by climate changes effects. The developed system permits the integration of the historical data measured with the traditional campaigns on the lake with new datasets collected with innovative technologies so that the comparison and validation of datasets can be more easily performed. In this way it is possible to detect biases and create automatic data pipelines to calculate indicators and notify alerts. 

How to cite: Strigaro, D., Cannata, M., Capelli, C., and Lepori, F.: Cost-effective full monitoring system for long-term measurements in lake ecosystems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15274, https://doi.org/10.5194/egusphere-egu23-15274, 2023.

EGU23-15814 | ECS | PICO | GI3.2 | Highlight

Low-cost in-situ sensor networks for soil moisture and water table measurements: experiences and recommendations. 

Ciprian Briciu-Burgina, Jiang Zhou, Muhammad Intizar Ali, and Fiona Regan

Soil moisture is an essential parameter for irrigation management, transport of pollutants and estimation of energy, heat, and water balances. Soil moisture is one of the most important soil spatial-temporal variables due to the highly heterogeneous nature of soils which in turn drives water fluxes, evapotranspiration, air temperature, precipitation, and soil erosion. Recent developments have seen an increasing number of electromagnetic sensors available commercially for soil volumetric water content (θ) and their use is expanding providing decision support and high-resolution data for models and machine learning algorithms.

In this context, two demonstrations of in-situ LoRaWAN sensor networks are presented. The 1st one is from a grassland site, Johnstown Castle, Wexford Ireland where a network of 10 low-cost soil moisture (SM) sensors has been operating for 12 months. The 2nd network has been operating for 6 months at a peatland site (Cavemount Bog, Offaly, Ireland) which is currently undergoing a rehabilitation process through re-wetting. At this site, in addition to SM sensors, ultrasonic sensors are used for continuous measurement of the water table at 7 locations. For both sites, the analytical performance of the SM sensors has been determined in the laboratory, through calibrations in liquids of known dielectric permittivity and through field validation via sample collection or time domain-reflectometry instrumentation (TDR). Experiences and recommendations in deploying, maintaining, and servicing the sensor networks, and data management (cleaning, validation, analysis) will be presented and discussed. Emphasis will be placed on the key learnings to date and the performance of the low-cost sensor networks in terms of collected data.

Small-scale sensor networks like these are expected to bridge the gap between the low spatial resolution provided by the satellite-derived products and the single point/field measurements. Within the project, the sensor network will provide spatial observations to complement existing fixed point measurements. It will allow researchers to investigate SM dynamics at field scale in response to different soil types, soil density, elevation, and land cover.

How to cite: Briciu-Burgina, C., Zhou, J., Ali, M. I., and Regan, F.: Low-cost in-situ sensor networks for soil moisture and water table measurements: experiences and recommendations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15814, https://doi.org/10.5194/egusphere-egu23-15814, 2023.

EGU23-16053 | ECS | PICO | GI3.2 | Highlight

Multiparametric water quality sensor based on carbon nanotubes: Performance assessment in realistic environment 

Balakumara Vignesh M, Stéphane Laporte, Yan Ulanowski, Senthilmurugan Subbiah, and Bérengère Lebental

Good quality water is crucial to most developing nations' sustainability. However, there is a clear lack of affordable and reliable solutions to monitor water quality. According to the WHO 2022 Sustainable Development Goals report, about 3 billion people do not have information on their water quality. While off-line measurements are commonly practiced, the availability of in-situ monitoring solutions is considered critical to the generalization of water monitoring, but current technologies are bulky, expensive and usually do not target  a sufficient number of quality parameters. [1]

To meet this challenge, the LOTUS project (https://www.lotus-india.eu/) brings forward a low-cost, compact, versatile multiparametric chemical sensor aiming at real-time monitoring of chlorine, pH, temperature and conductivity in potable water. The proposed solution –a tube of 21.2 cm in length by 3.5 cm in diameter – is composed of a replaceable sensor head incorporating the sensing elements and a sensor body containing the acquisition and communication electronics. The sensor head integrates a 1cm² silicon chip with 2 temperature sensors (serpentine-shaped thermistors), 3 conductivity sensors (parallel electrodes in a 4-probe configuration) and a 10x2 sensor array of multi-walled carbon nanotube (CNT) chemistors. The CNT are arranged in random networks between interdigitated electrodes and are either non-functionalized or functionalized with a dedicated polymer. [1]

We evaluated the performance of 7 units of this solution in Sense-city facility (located at University Gustave Eiffel, France - https://sense-city.ifsttar.fr/ ),  exploiting its 44m potable water loop with 93.8-mm PVC pipes. The system was operated at 25 m3/h and 1 bar, at temperature ranging between 15°C and 20°C, conductivity between 870 µS/cm and 1270 µS/cm; and chlorine between 0 and 5 mg/L. Because of the high-level of electromagnetic interferences in Sense-City and limited shielding of the acquisition system, the sensor signal is severely noisy and various steps of denoising are required. From the initial dataset were extracted a small number of devices and time periods with both sufficient variations in the target parameters and manageable level of signal-over-noise ratio. 

For chip 141, over 150hours of testing, CNT-based chemistors showed sensitivity to pH and active chlorine (HClO) with differentiated response between functionalized and non-functionalized devices. However, pH and chlorine can only be estimated with MAE respectively 0.17 and 0.18mg/L due to the high noise level. Over 400h, with chip 141, the real-time temperature of the water can be estimated with an MAE of 0.4°C in flowing water and 0.1°C  in static water. The chip 141 dataset did not feature enough conductivity variation to assess performances. This was achieved on chip AS001 with an MAE of 176.2 µS/cm over 80 hours.

Overall, these results provide a preliminary proof of operation of the solution in realistic environment, with the high noise level being a major limitation. A new version of system is being designed to reduce the noise, to be tested in Sense-City in 2023.

[1] Cousin, P. et al. (2022). Improving Water Quality and Security with Advanced Sensors and Indirect Water Sensing Methods. Springer Water. https://doi.org/10.1007/978-3-031-08262-7_11

How to cite: Vignesh M, B., Laporte, S., Ulanowski, Y., Subbiah, S., and Lebental, B.: Multiparametric water quality sensor based on carbon nanotubes: Performance assessment in realistic environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16053, https://doi.org/10.5194/egusphere-egu23-16053, 2023.

EGU23-16460 | PICO | GI3.2

Using hard and soft data from direct and indirect methods to develop a model for the investigation of a metamorphic aquifer 

Salvatore Straface, Francesco Chidichimo, Michele De Biase, and Francesco Muto

In Italy, despite large areas of the country being covered by metamorphic rocks, the hydrogeological properties of these formations are not yet well known. The productivity of metamorphic aquifers is generally lower than the more common ones such as alluvial or carbonates. However, in some Mediterranean areas such as in Calabria region the scarcity of water resources and their considerable extension (metamorphic aquifers make up 39% of the total) determines a request for further studies either on their hydrodynamic properties and their hydraulic behaviour in order to achieve their sustainable exploitation. Interest in these metamorphic aquifers becomes ever greater if climate changes are considered. The purpose of this study is to provide the geological-structural and hydrogeological modeling of a metamorphic aquifer, through the measurement of direct and indirect data and the application of a numerical model, in a large area of the Sila Piccola, in Calabria. To recognize and characterize the geometries of the aquifer in metamorphic rocks in a complex geological setting, data on springs, wells and piezometers installed in boreholes and located at various depths were collected. These surveys were implemented by geoelectric tomography profiles and by geognostic investigations. The recognition of the geometries and above all the stratigraphic relationships between the various outcropping rocks and lithological units have been accompanied by macrostructural and meso-structural analysis to better evaluate the state of fracturing of the rock mass. The characterization of hydrodynamic properties in crystalline-metamorphic aquifers, that is constituted by granite and metamorphic rocks, is extremely complex given the lateral-vertical anisotropies. Among the main fractures there is a network of secondary connections of different order and degree which determines a continuous variation of these properties at different scales and defines the modality and direction of the groundwater flow. The MODFLOW-2005 groundwater model was used to simulate the flow phenomena in the aquifer, obtaining hydraulic conductivity values of 2.7 × 10-6 m / s, corresponding to two orders of magnitude higher than that calculated with the slug-tests inside the slope. In summary, the mathematical model was able to estimate the equivalent permeability of the aquifer and the presence of a lateral recharge from a neighboring deep aquifer that materializes a significant water supply.

How to cite: Straface, S., Chidichimo, F., De Biase, M., and Muto, F.: Using hard and soft data from direct and indirect methods to develop a model for the investigation of a metamorphic aquifer, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16460, https://doi.org/10.5194/egusphere-egu23-16460, 2023.

Currents transport the sediment discharge of the Amazon River as far as the Orinoco Delta (Venezuela).  The combined actions of waves (predominately from the NE) and the Guiana Current create mud banks of 30 km in width.  A continuous process of mud erosion and accretion propagates the mud banks westward  

The talk demonstrates tracking the mud banks with satellite-derived bathymetry (SDB).  The SDB method used here is not the familiar Lyzenga bottom radiance to depth inversion which works only in clear waters.  Here there is no bottom visibility.  Instead, the SDB uses the interaction of ocean waves with the bottom.  Ocean waves exhibit refraction, slower celerity, and reduced wavelength as they ‘feel’ the bottom.   These phenomena are observable regardless of water turbidity.

WKB has been successfully implemented with X-band radars on coastal towers and ships (by German and UK researcher groups); and with the WorldView and Pleiades satellites (by this author and others).  However, all these sensor modalities have small ground footprints (~10 km2 to 100 km2).

The European Sentinel-2 satellites have dramatically increased WKB coverage to a regional scale.  This talk presents a Sentinel-2 view of the 1500 km muddy coastline, extending up to 50 km offshore (a total area of 75,000 km2).    

The leap in WKB possibilities was made possible by a 220 km image swath, repeat visits every five days, and the free distribution of the images from the Copernicus portal.

How to cite: Abileah, R.: Tracking mud banks on the 1500 km coastline from the Amazon to the Orinoco Delta, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16881, https://doi.org/10.5194/egusphere-egu23-16881, 2023.

EGU23-1981 | ECS | Posters on site | GI3.3

Total stratospheric bromine inferred from balloon-borne solar occultation bromine oxide (BrO) measurements using the new TotalBrO instrument 

Karolin Voss, Philip Holzbeck, Ralph Kleinschek, Michael Höpfner, Gerald Wetzel, Björn-Martin Sinnhuber, Klaus Pfeilsticker, and André Butz

Halogenated organic and inorganic compounds, in particular those containing chlorine, bromine and iodine are known to contribute to the global ozone depletion as well as directly and indirectly to climate forcing. As a result of the Montreal Protocol (1987), the chlorine and bromine loadings of the stratosphere are closely monitored, while the role of iodinated compounds to the stratospheric ozone photochemistry is still uncertain.

To address the questions concerning bromine and iodine compounds, a compact solar occultation instrument (TotalBrO) has been specifically designed to measure BrO, IO (iodine oxide) and other UV/Vis absorbing gases by means of Differential Optical Absorption Spectroscopy (DOAS) from aboard a stratospheric balloon. The instrument (power consumption < 100 W) comprises of an active camera-based solar tracker (LxWxH ~ 0.40 m x 0.40 m x 0.50 m, weight ~ 12 kg) and a spectrometer unit (LxWxH ~ 0.45 m x 0.40 m x 0.40 m, weight ~ 25 kg). The spectrometer unit houses two grating spectrometers which operate in vacuum and under temperature stabilization by an ice-water bath.

We discuss the performance of the TotalBrO instrument during the first two deployments on stratospheric balloons launched from Kiruna in August, 2021 and from Timmins in August, 2022 within the HEMERA program. Once the balloon gondola was azimuthally stabilized the solar tracker was able to follow the sun with a 1σ precision lower than 0.02° up to solar zenith angles (SZAs) of 95°. The spectral retrieval (of 46 spectra acquired at SZA between 84° and 90°) allowed us to infer the BrO mixing ratio above 32 km altitude. The total bromine in the middle stratosphere is inferred by accounting for the BrO/Bry partitioning derived from a photochemical model.

How to cite: Voss, K., Holzbeck, P., Kleinschek, R., Höpfner, M., Wetzel, G., Sinnhuber, B.-M., Pfeilsticker, K., and Butz, A.: Total stratospheric bromine inferred from balloon-borne solar occultation bromine oxide (BrO) measurements using the new TotalBrO instrument, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1981, https://doi.org/10.5194/egusphere-egu23-1981, 2023.

EGU23-2923 | ECS | Posters on site | GI3.3

Total organic carbon measurements reveal large discrepancies in reported petrochemical emissions 

Megan He, Jenna Ditto, Lexie Gardner, Jo Machesky, Tori Hass-Mitchell, Christina Chen, Peeyush Khare, Bugra Sahin, John Fortner, Katherine Hayden, Jeremy Wentzell, Richard Mittermeier, Amy Leithead, Patrick Lee, Andrea Darlington, Junhua Zhang, Samar Moussa, Shao-Meng Li, John Liggio, and Drew Gentner

Oil sands are a prominent unconventional source of petroleum. Total organic carbon measurements via an aircraft campaign (Spring-Summer 2018) revealed emissions above Canadian oil sands exceeding reported values by 1900-6300%. The “missing” compounds were predominantly intermediate- and semi-volatile organic compounds, which are prolific precursors to secondary organic aerosol formation. 

Here we use a novel combination of aircraft-based measurements (including total carbon emissions measurements) and offline analytical instrumentation to characterize the mixtures of organic carbon and their volatility distributions above oil sands facilities. These airborne, real-time observations are supplemented by laboratory experiments identifying substantial, unintended emissions from waste management practices, emphasizing the importance of accurate facility-wide emissions monitoring and total carbon measurements to detect potentially vast missing emissions across sources.

Detailed chemical speciation confirms these observations near both surface mining and in-situ facilities were oil sands-derived, with facility-wide emissions around 1% of extracted petroleum—a comparable loss rate to natural gas extraction. Total emissions, spanning extraction through waste processing, were equivalent to total Canadian anthropogenic emissions from all sources. These results demonstrate that the full air quality and environmental impacts of oil sands operations cannot be captured without complete coverage of a wider volatility range of emissions.

How to cite: He, M., Ditto, J., Gardner, L., Machesky, J., Hass-Mitchell, T., Chen, C., Khare, P., Sahin, B., Fortner, J., Hayden, K., Wentzell, J., Mittermeier, R., Leithead, A., Lee, P., Darlington, A., Zhang, J., Moussa, S., Li, S.-M., Liggio, J., and Gentner, D.: Total organic carbon measurements reveal large discrepancies in reported petrochemical emissions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2923, https://doi.org/10.5194/egusphere-egu23-2923, 2023.

EGU23-3473 | Posters on site | GI3.3 | Highlight

The FAAM large atmospheric research aircraft: a brief history and future upgrades 

James Lee

The UK’s large atmospheric research aircraft is a converted BAe 146 operated by the Facility for Airborne Atmospheric Measurements (FAAM). With a range of 2000 nautical miles, the FAAM aircraft is capable of operating all over the world and it has taken part in science campaigns in over 30 different countries since 2004. The aircraft can fly as low as 50 feet over the sea and sustain flight at 100 feet high. The service ceiling is nearly 11 km high. Typically, flights will last anywhere between one and six hours, and we will carry up to 18 scientists onboard, who guide the mission and support the operation of up to 4 tonnes of scientific equipment. Currently, the aircraft is undergoing a £49 million mid-life upgrade (MLU) program, which will extend its lifetime to at least 2040. The three overarching objectives of the MLU are to:

Safeguard the UK’s research capability – allowing the facility to meet the needs of the research community, enhance the range of services available, and respond to environmental emergencies.

Provide frontier science capability – meeting new and existing research needs and supporting ground-breaking science discoveries, with a flexible and world-class airborne laboratory.

Reduce environmental impact – maintaining and improving the performance of the facility, and minimising emissions and resource use from aircraft operation.

Presented here will be a brief history of the aircraft operations, including example science outcomes from all flights all over the world. In addition, detail of the ongoing upgrades, in particular the new and cutting-edge measurement capability for gases, aerosols, clouds, radiation and meteorology. Also presented will be the expected reductions in environmental impact of the aircraft and how these will be monitored.

How to cite: Lee, J.: The FAAM large atmospheric research aircraft: a brief history and future upgrades, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3473, https://doi.org/10.5194/egusphere-egu23-3473, 2023.

EGU23-6620 | ECS | Posters on site | GI3.3

Airborne observations over the North Atlantic Ocean reveal the first gas-phase measurements of urea in the atmosphere 

Emily Matthews, Thomas Bannan, M. Anwar Khan, Dudley Shallcross, Harald Stark, Eleanor Browne, Alexander Archibald, Stéphane Bauguitte, Chris Reed, Navaneeth Thamban, Huihui Wu, James Lee, Lucy Carpenter, Ming-xi Yang, Thomas Bell, Grant Allen, Carl Percival, Gordon McFiggans, Martin Gallagher, and Hugh Coe

Despite the reduced nitrogen (N) cycle being central to global biogeochemistry, there are large uncertainties surrounding its sources and rate of cycling. Here, we present the first observations of gas-phase urea (CO(NH₂)₂) in the atmosphere from airborne high-resolution mass spectrometer measurements over the North Atlantic Ocean. We show that urea is ubiquitous in the marine lower troposphere during the Summer, Autumn and Winter flights but was found to be below the limit of detection during the Spring flights. The observations suggest the ocean is the primary emission source but further studies are required to understand the processes responsible for the air-sea exchange of urea. Urea is also frequently observed aloft due to long-range transport of biomass-burning plumes. These observations alongside global model simulations point to urea being an important, and as yet unaccounted for, component of reduced-N to the remote marine environment.  Since we show it readily partitions between gas and particle phases, airborne transfer of urea between nutrient rich and poor parts of the ocean can occur readily and could impact ecosystems and oceanic uptake of CO2, with potentially important atmospheric implications.  

How to cite: Matthews, E., Bannan, T., Khan, M. A., Shallcross, D., Stark, H., Browne, E., Archibald, A., Bauguitte, S., Reed, C., Thamban, N., Wu, H., Lee, J., Carpenter, L., Yang, M., Bell, T., Allen, G., Percival, C., McFiggans, G., Gallagher, M., and Coe, H.: Airborne observations over the North Atlantic Ocean reveal the first gas-phase measurements of urea in the atmosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6620, https://doi.org/10.5194/egusphere-egu23-6620, 2023.

EGU23-7804 | Posters virtual | GI3.3

In-situ trace-gas measurements from the ground to the stratosphere by an OF-CEAS balloon-borne instrument 

Valery Catoire, Chaoyang Xue, Gisèle Krysztofiak, Patrick Jacquet, Michel Chartier, and Claude Robert

Monitoring climate change and stratospheric ozone budget requires accurate knowledge of the abundances of greenhouse gases and ozone depleting substances from the lower troposphere to the stratosphere. An infrared laser absorption spectrometer called SPECIES (acronym for SPECtromètre Infrarouge à lasErs in Situ) has been developed for balloon-borne trace gases measurements.

The complete instrument has been validated on the occasion of a flight in August 2021 in the polar region (Kiruna, Sweden) within the frame of the “KLIMAT 2021” campaign managed by CNES for the “MAGIC” project using concomitant balloon and aircraft flights. Results of this flight concerning CH4 and CO2 will be presented.

How to cite: Catoire, V., Xue, C., Krysztofiak, G., Jacquet, P., Chartier, M., and Robert, C.: In-situ trace-gas measurements from the ground to the stratosphere by an OF-CEAS balloon-borne instrument, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7804, https://doi.org/10.5194/egusphere-egu23-7804, 2023.

EGU23-7986 | ECS | Posters on site | GI3.3

Ship emissions and apparent sulphur fuel content measured of board of a large research aircraft in international waters and Sulphur Emission Control Area 

Dominika Pasternak, James Lee, Beth Nelson, Magdalini Alexiadou, Loren Temple, Stéphane Bauguitte, Steph Batten, James Hopkins, Stephen Andrews, Emily Mathews, Thomas Bannan, Huihui Wu, Navaneeth Thamban, Nicholas Marsden, Ming-Xi Yang, Thomas Bell, Hugh Coe, and Keith Bower

Since 1st January 2020 the legal sulphur content of shipping fuel was decreased – from 3.5% to 0.5% by mass outside of the Sulphur Emission Control Areas (SECAs) to improve coastal air quality. A possible downside of this change was acceleration of climate change since sulphur is believed to be a negative climate forcer and sipping is one of its main sources. Further question was the level of compliance to the new rules, especially in the open waters. Another climate related aspect of shipping is recent growth in the liquified natural gas (LNG) tanker fleets. LNG is considered the greenest of the fossil fuels, however there are few empirical studies of methane emissions from marine LNG transport.

The Atmospheric Composition and Radiative forcing changes due to UN International Ship Emissions regulations (ACRUISE) project aims to address the above considerations. During three field campaigns the FAAM Airborne Laboratories’ large research aircraft was deployed to target ships in coastal shipping lanes and open waters. First measurements were performed in July 2019 (before regulation change) in shipping lanes along the Portuguese coast, the English Channel SECA and the Celtic Sea. Further two campaigns were delayed by the COVID-19 pandemic until September 2021 and April 2022, targeting ships in the Bay of Biscay, the English Channel SECA and the Celtic Sea. Throughout the project, nearly 300 ships were measured during 30 research flights, varying from plume aging and cloud interaction studies, through collecting bulk statistics in busy shipping lanes to comparing emissions in and out of SECA. This work focuses on the gaseous species measurements (SO2, CO2, CH4 and VOCs from whole air samples). They are used to study changes in apparent sulphur fuel content of the ships observed throughout ACRUISE, plume composition and methane emissions from LNG tankers.

How to cite: Pasternak, D., Lee, J., Nelson, B., Alexiadou, M., Temple, L., Bauguitte, S., Batten, S., Hopkins, J., Andrews, S., Mathews, E., Bannan, T., Wu, H., Thamban, N., Marsden, N., Yang, M.-X., Bell, T., Coe, H., and Bower, K.: Ship emissions and apparent sulphur fuel content measured of board of a large research aircraft in international waters and Sulphur Emission Control Area, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7986, https://doi.org/10.5194/egusphere-egu23-7986, 2023.

EGU23-8329 | ECS | Posters on site | GI3.3 | Highlight

Airborne remote sensing research infrastructure for strengthening science, international collaboration and capacity building in the Arctic 

Shridhar Jawak, Agnar Sivertsen, William D. Harcourt, Rudolf Denkmann, Ilkka Matero, Øystein Godøy, and Heikki Lihavainen

Svalbard Integrated Arctic Earth Observing System (SIOS) is an international collaboration of 28 scientific institutions from 10 countries to build a collaborative research infrastructure that will enable better estimates of future environmental and climate changes in the Arctic. SIOS' mission is to develop an efficient observing system in Svalbard, share technology and data using FAIR principles, fill knowledge gaps in Earth system science and reduce the environmental footprint of science in the Arctic. This study presents SIOS' efforts to strengthen science, international collaboration and capacity building in the high Arctic archipelago of Svalbard through its airborne research infrastructure. SIOS supports the coordinated usage of its airborne remote sensing resources such as the Dornier aircraft and uncrewed aerial vehicles (UAVs) for improved research activities in Svalbard, complementing in situ and space-borne measurements and reducing the environmental footprint of research in Svalbard. Since 2019, SIOS in collaboration with its member institution Norwegian Research Centre (NORCE) installed, tested, and operationalised optical imaging sensors in the Lufttransport Dornier (DO228) passenger aircraft stationed in Longyearbyen under the SIOS-InfraNor project making it compatible with research use in Svalbard. Two optical sensors are installed onboard the Dornier aircraft; (1) the PhaseOne IXU-150 RGB camera and (2) the HySpex VNIR-1800 hyperspectral sensor. The aircraft with these cameras is configured to acquire aerial RGB imagery and hyperspectral remote sensing data in addition to its regular logistics and transport operation in Svalbard. Since 2020, SIOS has supported and coordinated around 50 flight hours to acquire airborne data using the Dornier aircraft and UAVs in Svalbard supporting around 20 scientific projects. The use of airborne imaging sensors in these projects enabled a variety of applications within glaciology, biology, hydrology, and other fields of Earth system science: Mapping glacier crevasses, generating DEMs for glaciological applications, mapping and characterising earth (e.g., minerals, vegetation), ice (e.g., sea ice, icebergs, glaciers and snow cover) and ocean surface features (e.g., colour, chlorophyll). The use of passenger aircraft warrants the following benefits: (1) regular logistics and research activities are optimally coordinated to reduce flight hours in carrying scientific observations, (2) project proposals for the usage of aircraft-based measurements facilitate international collaboration, (3) measurements conducted during 2020-21 are useful in filling the gaps in field based observations occurred due to the Covid-19 pandemic, (4) airborne data are used to train polar scientists as a part of the annual SIOS training course and upcoming data usability contest, (5) data is also useful for Arctic field safety as it can be used to make products such as high-resolution maps of crevassed areas on glaciers. In short, SIOS airborne remote sensing activities represent optimized use of infrastructure, promote capacity building, Arctic safety and facilitate international cooperation.

How to cite: Jawak, S., Sivertsen, A., Harcourt, W. D., Denkmann, R., Matero, I., Godøy, Ø., and Lihavainen, H.: Airborne remote sensing research infrastructure for strengthening science, international collaboration and capacity building in the Arctic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8329, https://doi.org/10.5194/egusphere-egu23-8329, 2023.

EGU23-11813 | Posters on site | GI3.3

First evaluation of a 6-months Meteodrone campaign 

Maxime Hervo, Julie Pasquier, Lukas Hammerschmidt, Tanja Weusthoff, Martin Fengler, and Alexander Haefele

 From December 2021 to May 2022, MeteoSwiss conducted a proof of concept with Meteomatics to demonstrate the capability of drones to provide data of sufficient quality and reliability on a routine operational basis. Meteodrones MM-670 were operated automatically 8 times per night at Payerne, Switzerland. 864 meteorological profiles were measured and compared to co-localized measurements including radiosoundings and remote-sensing instruments. To our knowledge, it is the first time that Meteodrone measurements are evaluated in such an intensive campaign.

The availability of the Meteodrone measurements over the whole campaign was 75.7% with 82.2% of the flights reaching the nominal altitude of 2000m above sea level. Using the radiosondes as a reference, the quality of the Meteodrone measurements can be quantified according to WMO requirements (WMO OSCAR , 2022). Applying this method, the temperature measured by the Meteodrone can be considered as a “breakthrough”, meaning that they are a significant improvement if they are used for high resolution Numerical Weather Prediction. The Meteodrone’s humidity and wind profiles are classified as “useful” for high-resolution numerical weather predictions, suggesting they can be used for assimilation in numerical models. The quality is similar compared to the temperature measured by a microwave radiometer and the humidity measured by a Raman Lidar. However, the wind measured by a Doppler Lidar was more accurate than the estimation of the Meteodrone.

This campaign opens the door for operational usage of automatic drones for meteorological applications.

How to cite: Hervo, M., Pasquier, J., Hammerschmidt, L., Weusthoff, T., Fengler, M., and Haefele, A.: First evaluation of a 6-months Meteodrone campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11813, https://doi.org/10.5194/egusphere-egu23-11813, 2023.

EGU23-13766 | ECS | Posters on site | GI3.3

How inlet tubing material affects the response time of water vapor concentration measurements 

Markus Miltner, Tim Stoltmann, and Erik Kerstel

Measurements involving water in the vapor phase have to deal with the stickiness of the H2O molecule: The associated adsorption and desorption processes can increase the response time of these measurements significantly. To achieve short response times in scientific instrument design, hydrophobic surface materials are used to reduce surface interactions in the tubing that guides the sample towards the analyzer. The study presented here focuses on the effects of the tubing material choice, length, humidity level, gas flow rate, and temperature on the observed response time. We use an Optical Feedback Cavity Enhanced Absorption Spectrometer (OFCEAS) designed for stable water isotope measurements at low water concentration (< 1000 ppm), which we connect to two bottles containing humidified synthetic air of different water concentration using 6.6-m tubing of different materials and surface treatments. Other parameters that are varied are the flow rate and the temperature of the tubing. With proper selection of tubing material and surface treatment, the contribution from the tubing to the overall response time for low water concentration isotopic measurements can be sufficiently suppressed for it to be neglected.

How to cite: Miltner, M., Stoltmann, T., and Kerstel, E.: How inlet tubing material affects the response time of water vapor concentration measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13766, https://doi.org/10.5194/egusphere-egu23-13766, 2023.

EGU23-14164 | ECS | Posters virtual | GI3.3

Multi-angular airborne thermal observations: A new hyperspectral setup for simulating thermal radiation and emissivity directionality at the satellite scale 

Mary Langsdale, Callum Middleton, Martin Wooster, Mark Grosvenor, and Dirk Schuettemeyer

Land Surface Temperature (LST) is a key parameter to the understanding and modelling of many Earth system processes. Viewing and illumination geometry are known to have significant impacts on remotely sensed retrieval of LST, particularly for heterogeneous regions with mixed components. However, it is difficult to accurately quantify these impacts, in part due to the challenges of retrieving high-quality data for the different components in a scene at a variety of different viewing and illumination geometries over a time period where the real surface temperature and sun-sensor geometries are invariant. Previous field studies have attempted this through observations with aircraft-mounted single-band thermal cameras to further understanding of real-world conditions, but these sensors have limited accuracies and cannot be used to consider the angular variability of emissivity or to simulate multi-band satellite observations.

To redress this, the National Centre for Earth Observation’s Airborne Earth Observatory (NAEO) have developed and manufactured a modified mount for their state-of-the-art commercial pushbroom longwave hyperspectral airborne sensor, the Specim AisaOWL (102 narrowband channels across the 7.6 – 12.6 µm region). When mounted in standard mode, the field-of-view of the OWL sensor is 24° (± 12°), however the modified mount enables off-nadir measurements up to 48°. This has the potential to evaluate both thermal radiation and spectral emissivity directionality up to and beyond the view angles of most thermal satellite sensors. With LST now classified as an Essential Climate Variable, this work is particularly relevant as it will help to improve the accuracy of retrievals from current and future satellites (e.g. LSTM, SBG, TRISHNA).

In this presentation, we first present an overview of the design modifications that enable these high-angle observations and preliminary results from test flights before detailing how this setup will be used in an upcoming joint ESA-NASA campaign dedicated to quantifying and simulating thermal radiation directionality over agricultural regions at the satellite scale.

How to cite: Langsdale, M., Middleton, C., Wooster, M., Grosvenor, M., and Schuettemeyer, D.: Multi-angular airborne thermal observations: A new hyperspectral setup for simulating thermal radiation and emissivity directionality at the satellite scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14164, https://doi.org/10.5194/egusphere-egu23-14164, 2023.

EGU23-14187 | ECS | Posters on site | GI3.3

Aircraft observations of NH3 from agricultural sources 

Lara Noppen, Lieven Clarisse, Frederik Tack, Thomas Ruhtz, Alexis Merlaud, Martin Van Damme, Michel Van Roozendael, Dirk Schuettemeyer, and Pierre Coheur

Ammonia (NH3) is mainly emitted in the atmosphere by anthropogenic activities, especially by agriculture. Excess emissions greatly disturb ecosystems, biodiversity, and air quality. Despite our awareness of these deleterious consequences, NH3 concentrations are increasing in most industrialized countries. This underlines the need for more stringent regulations and good knowledge of the species gained through effective monitoring.

Since a decade, NH3 is monitored from space, daily and globally, with thermal infrared sounders. However, their coarse spatial resolution (above 10 km) renders accurate quantification of NH3 sources particularly challenging. Indeed, only the largest and most isolated NH3 point sources have been identified and quantified from current observations and often only by exploiting long-term averages. To address the urgent need for better constraining NH3 emissions, a new satellite, called Nitrosat, has been proposed in response to the 11th ESA’s Earth Explorer call. The mission aims at mapping simultaneously NO2 and NH3 at a spatial resolution of 500 m at a global scale. With the support of ESA, almost 30 aircraft demonstration flights took place in Europe between 2020 and 2022. These flights mapped gapless areas of at least 10 by 20 km containing various sources of NO2 and NH3 using two instruments: the SWING instrument targeting NO2 in the UV-VIS and Hyper-Cam LW measuring infrared spectra to observe NH3.

Here we present NH3 observations from campaigns performed in Italy in spring 2022. The Po Valley was the main target, as it is the largest (agricultural) hotspot of NH3 in Europe.  Despite the presence of large background concentrations in the Po Valley, we show that the infrared measurements are able to expose a multitude of local agricultural hotspots such as cattle farms. A particularly successful campaign covering the region from Vetto to Colorno demonstrates measurement sensitivity to the gradual increase of NH3 background concentrations outside and inside the Po Valley. We also discuss flights carried out further south in Italy targeting other emissions of NH3, such as those from a soda ash plant, and the emissions from a fertilizer release experiment that was organized in collaboration with a farmer. We present the measurements both at their native horizontal resolution of 4 m and downsampled at the 500 m resolution of Nitrosat.

How to cite: Noppen, L., Clarisse, L., Tack, F., Ruhtz, T., Merlaud, A., Van Damme, M., Van Roozendael, M., Schuettemeyer, D., and Coheur, P.: Aircraft observations of NH3 from agricultural sources, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14187, https://doi.org/10.5194/egusphere-egu23-14187, 2023.

EGU23-15334 | ECS | Posters on site | GI3.3

Global measurements of cloud properties using commercial aircraft 

Gary Lloyd and Martin Gallagher

In-Service Aircraft for a Global Observing System (IAGOS) is a European research infrastructure that uses the infrastructure of commercial aviation to make in-situ measurements of the atmosphere. We present data from the cloud sensing instrument installed on these aircraft between 2011 and 2021. This includes 1000s of flights across the globe that detect the concentration of cloud particles over the range 5-75 um and this provides information about seasonal variation in cloud frequency across different parts of the globe. From these measurements we are able to estimate properties such as Liquid/Ice Water Content (LWC/IWC), The Effective Diameter (ED) and Mean Volume Diameter (MVD).

How to cite: Lloyd, G. and Gallagher, M.: Global measurements of cloud properties using commercial aircraft, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15334, https://doi.org/10.5194/egusphere-egu23-15334, 2023.

EGU23-17533 | ECS | Posters on site | GI3.3

Synergy of active and passive airborne observations for the evaluation of the radiative impacts of aerosols. Application to the AEROCLO-SA field campaign in Namibia 

Mégane Ventura, Fabien Waquet, Gerard Brobgniez, Frederic Parol, Marc Mallet, Nicolas Ferlay, Oleg Dubovic, Philippe Goloub, Cyrille Flamant, and Paola Formenti

Aerosols have important effects on both local and global climate, as well as on clouds and precipitations. We present here some original results of the AErosol RadiatiOn and CLOud in Southern Africa (AEROCLO-sA) field campaign led in Namibia in August and September 2017. This region shows a strong response to climate change and is associated with large uncertainties in climate models. Large amounts of biomass burning aerosols emitted by vegetation fires in Central Africa are transported far over the Namibian deserts and are also detected over the stratocumulus clouds covering the South Atlantic Ocean along the coast of Namibia. Absorbing aerosols above clouds are associated with strong positive direct radiative forcing (warming) that are still underestimated in climate models (De Graaf etal.,2021). The absorption of solar radiation by absorbing above clouds may also cause a warming where the aerosol layer is located. This warming would alter the thermodynamic properties of the atmosphere, which would impact the vertical development of low-level clouds impacting the cloud top height and its brightness.

The airborne field campaign consisted in ten flights performed with the French F-20 Falcon aircraft in this region of interest. Several instruments were involved: the OSIRIS polarimeter, prototype of the next 3MI spaceborne instrument of ESA (Chauvigné etal.,2021), the LNG lidar, an airborne photometer called PLASMA, as well as fluxmeters and dropsondes used to measure thermodynamical quantities, supplemented with in situ aerosol measurements of particles size distribution.

In order to quantify the aerosols radiative impact on the Namibian regional radiative budget, we use an original approach that combines polarimeter and lidar data to derive heating rate of the aerosols. This approach is evaluated during massive transports of biomass burning particles. To calculate this parameter, we use a radiative transfer code and additional meteorological parameters, provided by the dropsondes. We will introduce, the flight of September 8, 2017, aerosol pollution was very important. Emissions and dust were carried along the Namibian coast, and an aerosol plume was observed above a stratocumulus. We will present vertical profiles of heating rates computed in the solar and thermal parts of the spectrum with this technique. Our results indicated particularly strong heating rate values retrieved above clouds due to aerosols, in the order of 8K per day, which is likely to perturbate the dynamic of the below cloud layers.

In order to validate and to quantify this new methodology, we used the flux measurements acquired during loop descents performed during dedicated parts of the flights, which provides unique measurements of flux distribution (upwelling and downwelling) and heating rates in function of the altitude.

Finally, we will discuss the possibility to apply this method to available spaceborne passive and active observations in order to provide the first estimates of heating rate profiles above clouds at global scale.

How to cite: Ventura, M., Waquet, F., Brobgniez, G., Parol, F., Mallet, M., Ferlay, N., Dubovic, O., Goloub, P., Flamant, C., and Formenti, P.: Synergy of active and passive airborne observations for the evaluation of the radiative impacts of aerosols. Application to the AEROCLO-SA field campaign in Namibia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17533, https://doi.org/10.5194/egusphere-egu23-17533, 2023.

EGU23-894 | Orals | ESSI4.2

Remote Sensing based Evapotranspiration Estimation and Sensitivity Analysis 

Mahesh Kumar Jat, Ankan Jana, and Mahender Choudhary

Evapotranspiration (ET) is an important factor to calculate the water loss to the atmosphere and water demand for crops. Global and regional estimates of daily evapotranspiration are essential for our understanding of the hydrologic cycle. Remote sensing methods have many advantages in estimating daily ET for a large heterogeneous area.  In the present study, the sensitivity of ET with respect to different remote sensing-derived variables has been quantified while using the energy balance algorithm for land (SEBAL) method to estimate daily ET. The sensitivity of SEBAL-based ET has been determined for NDVI, LST, albedo, and SAVI using Extended Fourier Amplitude Sensitivity Test (eFAST) method. Relative changes in ET estimates for a range ± 20% of important parameters i.e., NDVI, albedo, SAVI, and LST have been determined and the sensitivity coefficient was estimated. Further, the sensitivity of SEBAL estimated ET has been investigated for different land cover and land use classes i.e., cropland, barren land, settlement, forest, and sparse vegetation. Results show that ET is significantly sensitive to the albedo and LST, however, other LULC classes have a different level of sensitivity. For cropland, ET is sensitive to NDVI. The sensitivity coefficient also indicates a significant effect of albedo and LST on the SEBAL estimated ET. For cropland, a 20% decrease in albedo and LST resulted in a 4.24% and 4.19% reduction in ET, and a 20% increase leads to an increase in ET by 13% and 5.53%, respectively. For sparse vegetation, a 20% reduction in albedo leads to an increase in ET by 7.46% while a 20% increase in albedo may reduce the ET by 15.70%. SAVI has an inverse relationship with ET for forest, barren land, settlement, and sparse vegetation as compared to other variables. The study concludes that SEBAL estimated ET is sensitive to albedo and LST significantly. The study helps in understanding the scope of uncertainty in remote sensing-based ET estimation.

How to cite: Jat, M. K., Jana, A., and Choudhary, M.: Remote Sensing based Evapotranspiration Estimation and Sensitivity Analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-894, https://doi.org/10.5194/egusphere-egu23-894, 2023.

EGU23-2551 | ECS | Posters on site | ESSI4.2

Impact of hail events on agriculture: A remote sensing-based analysis of hail damage in the context of climate change 

Vanessa Streifeneder, Daniel Hölbling, and Zahra Dabiri

In the project HAGL (“Impact of hail events on agriculture: A remote sensing-based analysis of hail damage in the context of climate change”), we analyse the effects of hail damage on agriculture. In the context of climate change and the associated increased risk of extreme weather events to society and the economy, this project deals with a locally catastrophic natural hazard that causes high costs, namely hail. Hail, combined with severe storms, causes millions of Euros of damage to agriculture every year. The influence of climate change on local weather patterns (e.g. thunderstorms) is still relatively unexplored, but early evidence points to an increase in weather patterns causing hail and an increase in hailstone sizes. In Austria, especially southeastern Styria with its various crops is frequently affected by extreme hail events. Yield losses due to hail damage can be existence-threatening for farmers, which is why an effective damage assessment is of great interest.

We aim to develop an efficient method to determine the damage to agriculture caused by hail using various remote sensing data. Through a spatial hotspot analysis, we identify regions in southeastern Styria that are particularly affected by hailstorms to test and validate our method. We perform a combined analysis of Sentinel-2 optical and Sentinel-1 synthetic aperture radar (SAR) data using object-based image analysis (OBIA) methods and different vegetation indices derived from the multispectral data as well as radar backscatter signals to detect hail damage. Finally, we aim to create a damage categorisation that could support insurance work in the event of a disaster and make it more efficient by providing a first estimation of the damage before an on-side assessment is conducted. Especially for large agricultural fields, this would save time and resources by making it possible to prioritise areas with high damage and organise the fieldwork of insurance employees accordingly.

How to cite: Streifeneder, V., Hölbling, D., and Dabiri, Z.: Impact of hail events on agriculture: A remote sensing-based analysis of hail damage in the context of climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2551, https://doi.org/10.5194/egusphere-egu23-2551, 2023.

Climate change can be described as the dominant factor all these decades concerning changes in forest phenology while, at the same time, temperature affects the development time (Barrett & Brown, 2021; X.Zhou et al., 2020; Suepa et al., 2016). Satellite image-time series data have proven their value regarding forest health and forest phenology observation. Monitoring continuous plant phenology is critical for the ecosystem at a regional and global level since the high sensitivity of vegetation life cycle to climate change; the so-called phenophases are essential biological indicators to comprehend how climate change has impacted these ecosystems and how this will change the ensuing years. (Buitenwerf, Rose, and Higgins 2015; Johansson et al. 2015).  

This study conducts a time-series analysis using the breaks for additive season and trend (BFAST) time-series decomposition algorithm, to detect possible abrupt changes in forest seasonality and the impacts of extreme climatic events on forest health, examining Sentinel-1 and Sentinel-2 data for the period 2017-2021. The backscatter coefficient from Sentinel-1, Normalised Difference Moisture Index (NDMI), Enhanced Vegetation Index (EVI), and Green Chlorophyll Index (GCI) were created by Sentinel-2 and assessed to find possible correlations between them. All the satellite time-series data derived through the Google Earth Engine platform.

The study area is the Paphos Forest, managed by the Department of Forest which could be described as a representative Mediterranean forest; thus, it is vital to monitor it because Mediterranean forests are expected to experience the first climate change in Europe. More specifically, the study focus on the Nortwest, West and Southwest areas of the Paphos Forest since the SAR images are from Ascending orbit. Moreover, Paphos forest has unspoiled vegetation, and a highly reduced number of forest wildfires have occurred in recent years, favouring the reliability of the research's results. 

 

 

Acknowledgements

The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

How to cite: Theocharidis, C., Gitas, I., Danezis, C., and Hadjimitsis, D.: Satellite times-series analysis and assessment of the BFAST algorithm to detect possible abrupt changes in forest seasonality utilising Sentinel-1 and Sentinel-2 data. Case study: Paphos forest, Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2620, https://doi.org/10.5194/egusphere-egu23-2620, 2023.

EGU23-3514 | ECS | Orals | ESSI4.2

England Peat Map: The challenges of using Earth observation data and machine learning approaches at the national scale 

Alex Hamer, Sam Dixon, Christoph Kratz, Craig Dornan, Chris Miller, Michael Prince, Charlie Hart, Tom Hunt, and Andrew Webb

The world’s peatlands are our largest terrestrial carbon store whilst also providing a sustainable source of drinking water, a haven for wildlife and storing a record of our past. The England Peat Map aims to provide baseline maps for the extent, depth, and condition of peaty soils in England by 2024. This will enable targeting of future restoration, support nature recovery, improve greenhouse emissions reporting and natural capital accounting.

The maps will be created using a combination of multi-scale Earth observation imagery (satellite and airborne), existing and new ecological field survey data and machine/deep learning. Extent and depth mapping is implemented with random forest models and uses Sentinel satellite imagery and airborne LiDAR in combination with other ancillary datasets (e.g., geology and climate) for prediction. Assessment of peatland condition requires looking at these landscapes in different ways. Land cover mapping is used as a proxy for condition by targeting reflective classes for condition (e.g., Sphagnum, heather, and bare peat). Random forest and convolutional neural network (CNN) models are used in combination with Sentinel satellite imagery, aerial photography, and airborne LiDAR to produce national outputs. Mapping erosion/drainage features (grips, gullies and haggs) across the landscape is essential in understanding the underlying hydrological condition of the peatland and promising results have been achieved using CNNs with LiDAR and aerial photography. The final aspect of assessed condition is the movement of peat, also termed bog breathing, and is measured using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR). This opportunity is a result of novel in-situ peat movement cameras being installed across pilot sites to provide ground truth data.

The final maps will be released free of charge under an open UK government license, allowing wider application and new opportunities for use compared with currently available datasets. For example, these baseline maps have the potential to contribute towards national peatland monitoring to address further decline of peatland habitats and target restoration interventions to achieve cost effective results. Several challenges have occurred during the initial phase of the project such as the difficulty in licensing suitable training data and in defining what we are mapping when features lack a globally agreed definition (e.g., surface features). The talk will discuss these challenges as well as the future direction of the project and how these challenges can be overcome.

How to cite: Hamer, A., Dixon, S., Kratz, C., Dornan, C., Miller, C., Prince, M., Hart, C., Hunt, T., and Webb, A.: England Peat Map: The challenges of using Earth observation data and machine learning approaches at the national scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3514, https://doi.org/10.5194/egusphere-egu23-3514, 2023.

EGU23-6396 | Posters on site | ESSI4.2

Evolution of biologically active ultraviolet doses in Cyprus 

Ilias Fountoulakis, Konstantinos Fragkos, Kyriakoula Papachristopoulou, Argyro Nisantzi, Antonis Gkikas, Diofantos Hadjimitsis, and Stelios Kazadzis

Solar ultraviolet (UV) radiation is only a very small fraction of the total solar radiation reaching the Earth's surface. Nevertheless, it is of exceptional significance for life on Earth. In the last two decades, significant trends in biologically effective doses have been reported over many mid-latitude sites, due to changes in total ozone, aerosols, and cloudiness. In the present study, reanalysis and satellite information for aerosols, clouds, and total ozone, from Copernicus Atmospheric Monitoring Service (CAMS), MIDAS (ModIs Dust AeroSol) dataset, Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) satellite, and Ozone Monitoring Instrument (OMI) aboard Aura satellite respectively, for the period 2004 - 2021 are used as inputs to a radiative transfer model and UV spectra are simulated for the island of Cyprus on fine spatial (0.05° x 0.05°) and temporal (15 mins) resolution. Effective doses for the production of vitamin D in the human skin, erythema, and DNA damage are calculated from the produced spectra. There is also an effort to attribute the changes in the UV biological doses to the corresponding changes in total ozone, aerosols, and cloudiness. The significant role of dust in the changes in UV doses over the island is also discussed.

Acknowledgments: The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The Department of Meteorology of the Republic of Cyprus is acknowledged for providing the ground-based data for the validation of the modelled quantities. 

How to cite: Fountoulakis, I., Fragkos, K., Papachristopoulou, K., Nisantzi, A., Gkikas, A., Hadjimitsis, D., and Kazadzis, S.: Evolution of biologically active ultraviolet doses in Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6396, https://doi.org/10.5194/egusphere-egu23-6396, 2023.

EGU23-7269 | Posters on site | ESSI4.2

Modelled-based Photosynthetically Active Radiation climatology for Cyprus: Validation with measurements and trends 

Konstantinos Fragkos, Ilias Fountoulakis, Argyro Nisantzi, Kyriakoula Papachristopoulou, Diofantos Hadjimitsis, and Stelios Kazadzis

The visible part of the surface downward solar radiation (400 – 700 nm) known as Photosynthetically Active Radiation (PAR) is a key parameter for many land process models and terrestrial applications. More specifically, it is a critical ecological factor affecting agriculture productivity, ecosystem-atmosphere energy, CO2 fluxes, canopy architecture in forest ecosystems, and the growth of phytoplankton, among others. 

Despite its high importance, PAR measurements are rather scarce and no relevant worldwide radiometric networks for this quantity, in contrast with other actinometric quantities (e.g., global horizontal irradiance), exist. For these reasons, PAR levels are mostly estimated by satellite observations and modeling techniques.   

In the current study, we present a 16-year PAR climatology over Cyprus, based on the combined use of radiative transfer (RT) models and satellite imagery. Copernicus Atmospheric Monitoring Service (CAMS) AOD and PWV, aerosol climatology of SSA and AE based on the MACv3 aerosol climatology, Ozone – OMI data for the period 2005 – 2021, are used as input to the RT model LibRadtran to obtain the clear sky PAR levels. Consequently, the CAMS Cloud Modification Factor based on MSG images will be used to derive the PAR under all sky conditions. The derived climatology has a spatial resolution of 0.05x0.05 degrees and a temporal variation of 15 minutes, as constrained by the availability of Seviri/MSG images. Finally, the quality of the retrieved climatology is assessed by comparison with ground-based PAR measurements and PAR retrievals from measurements of GHI through relevant conversion algorithms, from quantum sensors and pyranometers that are installed in selected stations of the Meteorological Service of Cyprus.

 

Acknowledgments: The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The Department of Meteorology of the Republic of Cyprus is acknowledged for providing ground-based data for validating the modelled quantities.

How to cite: Fragkos, K., Fountoulakis, I., Nisantzi, A., Papachristopoulou, K., Hadjimitsis, D., and Kazadzis, S.: Modelled-based Photosynthetically Active Radiation climatology for Cyprus: Validation with measurements and trends, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7269, https://doi.org/10.5194/egusphere-egu23-7269, 2023.

EGU23-8315 | Orals | ESSI4.2

A coupled GIS-MCDA approach to map the feasibility of Managed Aquifer Recharge 

Anis Chekirbane, Constantinos F. Panagiotou, Aloui Dorsaf, and Stefan Catalin

Managed aquifer recharge (MAR) is a water resource management technique that involves the intentional recharge and storage of water into groundwater systems. MAR is considered an innovative nature-based solution for increasing water availability, improving water quality, and reducing surface water runoff. However, the feasibility of implementing MAR projects depends on several factors, for example recharge water availability, water demand, and the intrinsic site characteristics (e.g., geology, hydrogeology) of the area.

The current study proposes an adapted approach of MAR feasibility mapping through the integration of GIS and multi-criteria decision analysis (GIS-MCDA). The geospatial feasibility of MAR application is evaluated by considering the suitability maps of four thematic layers, namely intrinsic, water availability, non-physical and water demand.  The applicability of this approach is demonstrated in Enfidha plain (NE Tunisia), for which multiple types of spatial and temporal datasets have been collected.   The selection of the criteria is done based on literature studies and MAR experts’ opinions with respect to their relevance to MAR implementation, whereas the weights are determined using analytical hierarchy process (AHP). Hence, an intrinsic suitability map was established via the integration of ArcGIS software and MCDA in a web-based platform, called INOWAS (https://inowas.com/). The results suggest that more than 80% of the total plain area is considered intrinsically suitable for MAR implementation.  The potential MAR feasibility of the demonstration site is expected to be established by overlaying the suitability maps of the three thematic layers.

In addition to standardizing the process of MAR feasibility, the derived maps constitute an asset in the process of planning and implementing effective MAR projects that help to ensure the long-term sustainability of water resources in the Sahel region of Tunisia.

Acknowledgement

This work is funded by National Funding Agencies from Germany (Bundesministerium für Bildung und Forschung – BMBF), Cyprus (Research & Innovation Foundation – RIF), Portugal (Fundação para a Ciência e a Tecnologia – FCT), Spain (Ministerio de Ciencia e Innovación – MCI) and Tunisia (Ministère de l’Enseignement Supérieur et de la Recherche Scientifique – MESRS) under the Partnership for Research and Innovation in the Mediterranean Area (PRIMA). The PRIMA programme is supported under Horizon 2020 by the European Union’s Framework for Research and Innovation.

How to cite: Chekirbane, A., F. Panagiotou, C., Dorsaf, A., and Catalin, S.: A coupled GIS-MCDA approach to map the feasibility of Managed Aquifer Recharge, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8315, https://doi.org/10.5194/egusphere-egu23-8315, 2023.

EGU23-10910 | Posters on site | ESSI4.2

Spatio-temporal prediction of aerosol optical thickness using machine learning and spatial analysis techniques 

Seonghun Pyo, Kwonho Lee, and Seunghan Park

Emission sources, meteorology, and topography are the major factors that make it difficult to predict aerosols in space and time. In this study, the moderate resolution imaging spectro-radiometer (MODIS) aerosol optical thickness (AOT) and the surface meteorology observed in Korea have been used to predict spatio-temporal AOT by using the machine learning with spatial analysis techniques. This method enables timeseries based prediction and spatial distribution modeling, and allows modeling values where there are no observation points. The model results show root mean square error (RMSE) 0.33 which is smaller than the standard deviation of the observed value 0.43. Using this technique, the trend of aerosol change in the future was estimated, and it was found that the aerosol in the area of interest decreased by about 7.4%. The methodology will be useful to analyze the regional scale aerosol evaluations, air quality, and climate study.

 

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF-2019R1I1A3A01062804)”

How to cite: Pyo, S., Lee, K., and Park, S.: Spatio-temporal prediction of aerosol optical thickness using machine learning and spatial analysis techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10910, https://doi.org/10.5194/egusphere-egu23-10910, 2023.

EGU23-12336 | ECS | Posters on site | ESSI4.2

Assessment of airborne remote sensing data for high-resolution mapping of invasive Prosopis spp. in a semi-arid environment in Kenya 

Ilja Vuorinne, Janne Heiskanen, Ian Ocholla, Rose Kihungu, and Petri Pellikka

Invasive alien plant species are a major global problem threatening biodiversity and livelihoods and their mapping is needed for understanding their distribution dynamics, and for facilitating control and eradication measures. Prosopis spp., a fast-growing woody species native to South America, have been widely introduced into the tropics to restore degraded areas, but they have spread uncontrollably. For example, in East Africa, Prosopis spp. have invaded rangelands and thus decreased plant diversity and affected the livelihoods of pastoral communities. Remote sensing instruments mounted on an aircraft can be used to map such species and especially a combination of different sensors holds a potential for accurate detection.

The objective of this study was to test how a combination of airborne light detection and ranging (LiDAR), hyperspectral, and fine resolution multispectral data can be used to map Prosopis spp. in a semi-arid environment in Kenya. The remotely sensed spectral, structural, and textural features were used in a one-class machine learning algorithms to detect these species in a complex landcover. The results provide information on the use of different airborne remote sensing instruments and their combination in mapping woody alien invasive species and offer insights on the distribution of Prosopis spp. in the study area.

How to cite: Vuorinne, I., Heiskanen, J., Ocholla, I., Kihungu, R., and Pellikka, P.: Assessment of airborne remote sensing data for high-resolution mapping of invasive Prosopis spp. in a semi-arid environment in Kenya, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12336, https://doi.org/10.5194/egusphere-egu23-12336, 2023.

EGU23-12887 | ECS | Orals | ESSI4.2

Demonstrating the enhanced research capacity of the ERATOSTHENES Centre of Excellence for detecting ground displacements in Cyprus using advanced SAR satellite image processing techniques 

Kyriaki Fotiou, Christos Theocharidis, Maria Prodromou, Stavroula Alatza, Alex Apostolakis, Athanasios V. Argyriou, Thomaida Polydorou, Constantinos Loupasakis, Charalampos Kontoes, Diofantos Hadjimitsis, and Marios Tzouvaras

In the last few years, the consequences of the active landslides that occurred in Cyprus have determined the necessity to provide a systematic displacement monitoring system of different areas using satellite-based techniques. Earth Observation and more specifically satellite remote sensing techniques using Synthetic Aperture Radar (SAR) imagery is the way forward exploiting the freely available Copernicus datasets that offer frequent revisit times and large spatial coverage. Moreover, Persistent Scatterer Interferometry (PSI) is among the most effective methods to monitor ground displacements, such as landslides, and assess their impact in residential areas. The purpose of this study is to showcase the use of advanced satellite image processing techniques, exploiting SAR satellite images to effectively identify ground displacements in different regions in Cyprus. The enhanced scientific and expertise skills of the ERATOSTHENES Centre of Excellence (ECoE) personnel on the application of PSI were acquired through a capacity building activity carried out by the National Observatory of Athens within the framework of EXCELSIOR project. The multi-temporal InSAR analysis in Cyprus revealed several deforming sites, which were also confirmed by the national authority responsible, i.e., the Geological Survey Department of the Ministry of Agriculture, Rural Development and Environment. ThCe villages of Pedoulas in Nicosia District and Pyrgos-Parekklisia in Limassol District are indicative deforming areas in Cyprus and were selected as test sites for further investigation. The ongoing implementation of additional InSAR techniques, fusion of remote sensing data and site visits for further validation, build a complete ground deformation monitoring system, aiming to migrate to a national scale project and serve as a valuable tool for natural hazards monitoring and risk reduction in Cyprus. 

 

Acknowledgements 

The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. 

How to cite: Fotiou, K., Theocharidis, C., Prodromou, M., Alatza, S., Apostolakis, A., Argyriou, A. V., Polydorou, T., Loupasakis, C., Kontoes, C., Hadjimitsis, D., and Tzouvaras, M.: Demonstrating the enhanced research capacity of the ERATOSTHENES Centre of Excellence for detecting ground displacements in Cyprus using advanced SAR satellite image processing techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12887, https://doi.org/10.5194/egusphere-egu23-12887, 2023.

EGU23-12958 | Posters on site | ESSI4.2

Development of algorithms based on the integration of meteorological data and remote sensing indices for the identification of low-productivity agricultural areas 

Rosa Coluzzi, Francesco Di Paola, Vito Imbrenda, Maria Lanfredi, Letizia Pace, Elisabetta Ricciardelli, Caterina Samela, and Valerio Tramutoli

Agricultural areas of Mediterranean regions host an extraordinary wealth of biodiversity and represent the source of income for a large population often living below the average economic conditions of the most advanced regions of Europe. In these areas, the semi-arid climates, the impact of climate change, the parcelization of land property, and the poor soils, contribute to create widespread conditions of low profitability of agricultural areas. This is likely to have an impact on the increasing occurrence of land abandonment phenomena and on growing hydrogeological risk linked to the lack of land maintenance.

The productivity estimation of these agricultural areas represents a crucial information to detect hotspots of degradation helping policy makers in taking specific actions to increase productivity and reduce migration fluxes.

In this work, realized in the framework of the ODESSA (On DEmand Services for Smart Agriculture) project (financed by the European Regional Development Fund Operational Programme 2014-2020 of Basilicata Region), the procedure adopted involves the use of climate and vegetation geospatial data, including both direct observational data (temperature, rainfall, etc.) and satellite-derived vegetation indexes. For the climatic component, we exploited a database of daily temperature and rainfall data (2000-2021) acquired by the agrometeorological network of ALSIA (Lucana Agency for Development and Innovation in Agriculture) and the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) dataset providing rainfall data (1981-2020) at a spatial resolution of 0.050 to produce different diagnostic indices able to capture low-productivity areas. We tested this procedure in two districts of Basilicata (Southern Italy): the Vulture-Melfese and the Metapontino, representing the core areas of regional agricultural specialization for vineyards and intensive fruit and vegetable crops, respectively.

 

How to cite: Coluzzi, R., Di Paola, F., Imbrenda, V., Lanfredi, M., Pace, L., Ricciardelli, E., Samela, C., and Tramutoli, V.: Development of algorithms based on the integration of meteorological data and remote sensing indices for the identification of low-productivity agricultural areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12958, https://doi.org/10.5194/egusphere-egu23-12958, 2023.

EGU23-13385 | ECS | Orals | ESSI4.2

The synergy of Sentinel missions for fire damage assessment on land surface and atmosphere: the Arakapas village case study 

Maria Prodromou, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Dragos Ene, Ioannis Gitas, Kyriacos Themistocleous, Chris Danezis, and Diofantos Hadjimitsis

Fires are a widespread ecological factor since ancient times. It has a negative impact not only on the environment but on the economy, society and people. A forest fire can lead to a change in land surface, the destruction of large areas of vegetation and soil erosion. As a result, the economy is negatively affected, the balance of ecosystems is disturbed, and the flora, fauna and natural beauty are destructed. Also, biomass burning smoke affects air quality due to the large quantities of trace gases and aerosol particles that are emitted, leading to global climate change and playing a significant role in troposphere chemistry. A fundamental tool for forest fire management is the science of remote sensing. Remote sensing is commonly used for mapping burnt areas as well as for studying the effects of fire incidents and this statement is very well supported by the literature at local, regional and global levels. This study is mainly focused on burned area mapping and damage assessment on land surface and atmosphere for the case of the Arakapas fire in Cyprus. For the purposes of this study, the satellite images acquired from Sentinel-2 were used for the burnt area mapping and the fire severity estimation based on the dNBR (difference Normalized Burn Ratio) spectral index, and the Corine land cover was used for the assessment of the vegetation type that was disturbed. This event considered one of the largest in recent years is explored using data from Sentinel-5P, where carbon monoxide product is studied in the region affected by the fires. Furthermore, on the morning of the 5th of July, due to the change of wind direction, the smoke travelled from the centre of the island to the southwest, and it was detected by the multiwavelength Raman lidar, installed in Limassol. Thus, the optical properties of the smoke plume retrieved from the lidar are presented. The PollyXT-CYP lidar system of the ECoE, observed multiple layers between 500m and 2.5km with depolarization ratio of 5-8% and lidar ratio of 75sr for the upper layers.For the purposes of this study, the image processing was performed using custom scripts in the GEE (Google Earth Engine) platform with the JavaScript programming interface. The area affected by the fire was calculated to be ~40Km2. The spatial distribution map of the dNBR was classified according to the USGS fire severity levels, where high dNBR values indicate a more severe fire and values near zero and negative values indicate unburned and/or decreased vegetation after the fire.

 

Acknowledgements

The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

How to cite: Prodromou, M., Mamouri, R.-E., Nisantzi, A., Ene, D., Gitas, I., Themistocleous, K., Danezis, C., and Hadjimitsis, D.: The synergy of Sentinel missions for fire damage assessment on land surface and atmosphere: the Arakapas village case study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13385, https://doi.org/10.5194/egusphere-egu23-13385, 2023.

EGU23-14742 | ECS | Orals | ESSI4.2

Comparing reflectivity measurements between satellite- and ground-based radar observations: A case study for precipitation and drought monitoring in Cyprus 

Eleni Loulli, Johannes Bühl, Silas Michaelides, Athanasios Loukas, and Diofantos Hadjimitsis

Drought is a multidimensional phenomenon that is imperceptible at its early stages, it evolves slowly and cumulatively and results to adverse consequences, for example depletion of water volumes from rivers and reservoirs, decrease of carbon uptake in vegetation etc. Cyprus is characterized by semi-arid to arid climate conditions, experiencing extensive droughts that have a negative impact on the ecosystem, the economy and the agricultural production.

Existing research on drought events in Cyprus is limited to the usage of in-situ data, mainly temperature and precipitation measurements at meteorological stations. Polarimetric weather radars can offer more detailed information regarding precipitation phenomena, especially in areas with sparse network of meteorological stations or remote areas of interest.

This study compares reflectivity measurements from the two ground-based X-band dual polarization radars of the Department of Meteorology of the Republic of Cyprus with measurements obtained from NASA’s Global Precipitation Measurement (GPM) mission.

The DPR (Dual-frequency Precipitation Radar) aboard of GPM is employed in order to derive the radar reflectivity factor with a spatial resolution of 5-25 km for 120 km wide swath. The ground-based radars operate since 2017. They scan in PPI mode at eight (8) constant elevation angles, whereas their azimuth angle varies with a spatial resolution of 0.1° and the radius of each scan is 150 km. The radar stations are located in Rizoelia, Larnaca district, and Nata, Paphos district, providing a full coverage of the island.

Satellite-based radar reflectivity values are used to adjust the ground-based radar measurements. Consequently, the adjusted values of the ground-based radar reflectivity are used as input to modelling expressions for estimating the ground-based radar precipitation.

In order to ensure that the observations are spatially coincident, we have developed a collocated grid, hereafter called universal grid, on which both the ground- and satellite-based radar observations are interpolated at the same locations. The universal grid is a three-dimensional (3D) grid with grid cell size of approximately 2500 m along both horizontal directions, whereas the vertical resolution is set equal to the height resolution of GPM, i.e. 150 m. Regarding temporal resolution, GPM overpasses Cyprus approximately once a week. For the purposes of this study, we selected overflights after the beginning of the ground-based radar operation that coincide with precipitation events.

Additionally, statistical analysis of the reflectivity measurements has been conducted to understand the relationship between the ground-based and the satellite-based datasets and identify spatio-temporal patterns of precipitation.

Acknowledgements:

The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

The authors acknowledge also the Department of Meteorology of the Republic of Cyprus for the provision of the X-band radar data.

How to cite: Loulli, E., Bühl, J., Michaelides, S., Loukas, A., and Hadjimitsis, D.: Comparing reflectivity measurements between satellite- and ground-based radar observations: A case study for precipitation and drought monitoring in Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14742, https://doi.org/10.5194/egusphere-egu23-14742, 2023.

EGU23-15837 | ECS | Posters on site | ESSI4.2

Exploring the benefits of building a data cube towards the efficient risk monitoring and assessment of cultural heritage assets 

Georgios Leventis, Georgios Melillos, Athanasios Argyrioy, Ioannis Varvaris, Zampella Pittaki, Kyriacos Themistocleous, and Diofantos Hadjimitsis

The Eastern Mediterranean, Middle East, and North Africa (EMMENA) region encompasses three continents (Europe, Asia, and Africa). The region is not only strategically vital for political and military forces, but it is also archaeologically and culturally significant due to the large amount of cultural wealth, due to being an important crossroad in archaic times for various civilizations [1]. However, the cultural assets of the region are often susceptible to risks associated either to nature (like land deformation, earthquakes etc.) or to human activity (looting, war atrocities, etc.).

To protect cultural heritage in uncertain crisis scenarios, it is critical to recognize any risk situation early and support the decision-makers and cultural stakeholders with timely, accurate and relevant information, while raising at the same time public awareness on important issues that pertain to the cultural destruction, alteration and/or looting. Towards the end of responding properly in due time to any threats, ERATOSTHENES Centre of Excellence through its two departments; Big Earth Data Analytics and Cultural Heritage at the current work showcases its efforts in building and exploiting a cultural data cube based and building upon the open-source project called Open Data Cube [2]. Taking advantage of such endeavor, centre’s researchers are able to store, extract and analyse geospatial and satellite data, which due to their cube-shaped transformation can be accessed quickly thus providing a better understanding of any critical risk situations that might affect possible cultural assets. As the scale and pattern of occurrence fluctuate based on the type of disaster, as well as the extent of damage may vary from time to time depending on regional features, the timing of incident(s) and of the response, the proposed work encapsulates various forms of data acquired throughout an entire risk scenario (prior to the event, during the event and post to the event), to ensure the best possible assessment of any ongoing risk(s).

It becomes perceivable that damaged cultural assets cannot be restored to their former condition, hence is crucial to preserve them as much as possible and increase the resilience of cultural properties by reducing the harm brought on by disaster scenarios. Fostering on geospatial advances, the particular work aspires to become a common ground and valuable tool for efficient incident management within the EMMENA region starting from the field of Cultural Heritage and extending to others (i.e., marine security, agriculture, water resources management etc.).

 

Acknowledgements

The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

 

References

[1] - Longuet, R.: Encyclopaedia of the History of Science, Technology, and Medicine in Non-Western Cultures. Springer, Netherlands, Dordrecht (2008)

[2] – Open Data Cube, open-source project, https://www.opendatacube.org/about. Last accessed on 8/01/2023.

How to cite: Leventis, G., Melillos, G., Argyrioy, A., Varvaris, I., Pittaki, Z., Themistocleous, K., and Hadjimitsis, D.: Exploring the benefits of building a data cube towards the efficient risk monitoring and assessment of cultural heritage assets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15837, https://doi.org/10.5194/egusphere-egu23-15837, 2023.

EGU23-16436 | Orals | ESSI4.2

Monitoring natural and geo- hazards at cultural heritage sites using Earth observation: the case study of Choirokoitia, Cyprus 

Kyriacos Themistocleous, Kyriaki Fotiou, and Marios Tzouvaras

Monitoring natural hazards due to climate change and natural hazards at cultural heritage sites facilitates the early recognition of potential risks and enables effective conservation monitoring and planning. Landslides, earthquakes, rock falls, ground subsidence and erosion are the predominant natural hazards in Cyprus, which pose serious disadvantages to cultural heritage sites as well as potential danger to visitors. To identify and monitor natural hazards and environmental displacements Earth observation techniques, such as SAR, can be used in combination with in-situ methods.

The EXCELSIOR H2020 Widespread Teaming project under Grant Agreement No 857510 and the TRIQUETRA project Horizon Europe, Grant Agreement No. 101094818 will study the use of Earth observation techniques for examining cultural heritage sites. The TRIQUETRA project will examine Choirokoitia, Cyprus as a pilot project using these techniques. Choirokoitia is a UNESCO World Heritage Site and is one of the best-preserved Neolithic sites in the Mediterranean. The project will examine the potential risk of rockfall at the Choirokoitia site, as the topology of the site is vulnerable to movements as a result of extreme climate change as well as of daily/seasonal stressing actions. Rockfall poses a significant danger to visitor safety as well as damage to cultural heritage sites.

As well, the Choirokoitia site will be used to detect and analyse natural hazards induced ground deformation based on InSAR ground motion data and field survey techniques for cultural heritage applications. InSAR data, satellite positioning and conventional surveying techniques will be employed to measure micromovements, while other techniques such as UAVs and photogrammetry will be used for documentation purposes and 3D modelling comparisons. In order to identify and monitor natural hazards and their severity, a permanent GNSS station and corner reflector, as well as analysing multitemporal SAR satellite data will be used to estimate the rate of land movement. SAR monitoring provides the opportunity to identify deformation phenomena resulting from natural hazards for monitoring and assessing potential hazards using remote sensing techniques to measure and document the extent of change caused by the natural and/or geo-hazards. PSI (Persistent Scatterer Interferometry) analysis can be used in the wider area to determine potential displacements.

The study is expected to lead towards the systematic monitoring of geohazards, and more specifically those of ground deformation and rock falls to facilitate the early recognition of potential risks and enable effective conservation monitoring and planning. The methodology can be used to monitor cultural heritage sites worldwide which are vulnerable to natural hazards.

How to cite: Themistocleous, K., Fotiou, K., and Tzouvaras, M.: Monitoring natural and geo- hazards at cultural heritage sites using Earth observation: the case study of Choirokoitia, Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16436, https://doi.org/10.5194/egusphere-egu23-16436, 2023.

EGU23-16794 | Orals | ESSI4.2

Evaluating the influence of human induced landscape alterations on ecosystem services in semiarid regions of India. 

Vinay Shivamurthy, Thokala Manoj, Kamera Arun Kumar, Maddela Harsha Vardhan, Sangannagari Lavanya, and Sankalamaddi Manasa

In the Anthropocene, with human centric planning, the landscapes are continually altered endangering the existence of biota, triggering climate changes, affecting the ecosystem services provided by the regional landscapes. However in special cases, meticulous planning and prioritized alterations of landscape has aided in improving the regional economy and the services provided by them. In the current communication we spatially evaluate the influence of irrigation projects on the lentic ecosystems and agrarian ecosystems at regional scale. Karimnagar, located in Telangana State India, along with 25km buffer from the city center was analyzed. Being in the semiarid zones, Karimnagar experience sever temperature during summer. Spatiotemporal variation in Zaid cropping pattern and water bodies were studied using Landsat series satellite data for the past 5 decades i.e., between 1973 to 2022. Indices based methods such as Normalized Difference Vegetation Index and modified Normalized Difference Water index were used followed by segmentation to determine the areas under Zaid cropping and extent of water. It was evident that during 1973 area under Zaid crops were as low as 231km2 with water bodies about 1.7km2. with commission of lower Manair in the year 1985, downstream regions of the reservoir showed large scale improvement i.e., the lakes were rejuvenated and the area under Zaid cropping improved significantly. Area under Zaid agriculture improved by four folds i.e., over 1000km2 and water bodies increased to 53km2. In the recent past, Mid Manair was commissioned in the year 2018 post which area under water has increase to 113km2 and area under Zaid cropping has increased to 1569km2. Post Lower Manair and Mid Manair Projects, most of the lentic ecosystems in the study area have become perennial catering to agrarian, domestic and environment. The Agriculture Ecosystem Service Value in the study area particularly due the Zaid Cropping has increased from 34 Million US$ in 1973 to ~128Million US$ after commission of Lower Manair and the same has increased to 235 Million US$ by 2022, like wise ecosystem services of lentic ecosystems have increased from 0.59Million US$ in 1973 to 39.57 Million US$ in 2022. The results indicates that with sensible planning and development, both society and regional environs get mutually benefitted thus ensuring superior wellbeing.

How to cite: Shivamurthy, V., Manoj, T., Arun Kumar, K., Harsha Vardhan, M., Lavanya, S., and Manasa, S.: Evaluating the influence of human induced landscape alterations on ecosystem services in semiarid regions of India., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16794, https://doi.org/10.5194/egusphere-egu23-16794, 2023.

EGU23-16909 | ECS | Posters virtual | ESSI4.2

Sea Surface Temperature and Ocean Wind Speed Data in the Cyprus region from Sentinel-3 using Sentinel Application Platform (SNAP) and Arc GIS Pro. 

Eleftheria Kalogirou, George Melillos, Diofantos Hadjimitsis, and Despoina Makri

The ability to measure sea surface temperature allows us to observe the global system and quantify ongoing weather and climate change. Several industries are particularly affected by increased SST the shipping industry, the offshore oil and gas industry, the fishing industry, etc. Knowledge of ocean wind behaviour will enable ship masters to choose routes that avoid heavy seas or high headwinds that may slow the ship's travel, increase fuel consumption, or possibly cause damage to vessels and loss of life. This paper aims to realise the Cyprus region's sea surface temperature and wind speed data. The comparison of results obtained using Sentinel Application Platform (SNAP) and ArcGIS Pro, shows that both tools can be used to realise Sea Surface Temperature and Ocean Wind Speed Data and give satisfactory results.

Keywords: Sea surface temperature, Ocean Wind Speed Data, Sentinel-3, SNAP, ArcGIS Pro.

How to cite: Kalogirou, E., Melillos, G., Hadjimitsis, D., and Makri, D.: Sea Surface Temperature and Ocean Wind Speed Data in the Cyprus region from Sentinel-3 using Sentinel Application Platform (SNAP) and Arc GIS Pro., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16909, https://doi.org/10.5194/egusphere-egu23-16909, 2023.

EGU23-17144 | Orals | ESSI4.2

Comparison of three algorithms for tree crown area and available pruning biomass monitoring 

Sofia Fidani, Ioannis Maroufidis, Stavros Chlorokostas, Ioannis N. Daliakopoulos, Dimitrios Papadimitriou, Ioannis Louloudakis, Georgios Daskalakis, Betty Charalambopoulou, and Thrassyvoulos Manios

Fast and rigorous assessment of tree characteristics from earth observation products has many environmental applications, including monitoring of the canopy biomass available for pruning and utilisation as soil amendment or energy source. Here we explore the efficiency of three supervised classification algorithms in assessing canopy area of olive trees, the staple food crop of the Mediterranean that annually produces an estimated 2,82 Μt ha-1 of residual biomass (Velázquez-Martí et al., 2011) which is currently largely unexploited and often an environmental hazard due to on-site fires. The algorithms include (a) a thresholding algorithm (Daliakopoulos et al., 2009) processing Normalized Difference Vegetation Index values, (b) a supervised machine learning algorithm comprised on an Artificial Neural Network (ANN) with 4 hidden layers, and (c) the AdaBoost supervised deep learning algorithm. Following Yang et al. (2009), the latter two methods use image colour, texture, and entropy as inputs. Ground truth was developed by manually producing a binary mask where pixels depicting tree crown were marked with 1 and otherwise 0, and classification results were evaluated using the Dice similarity coefficient (DSC; Nisio et al., 2020). The three algorithms were tested on assessing olive tree crown projected surface area on a WorldView II image of resolution 0.5 × 0.5 m of a rural area of Heraklion, Crete, Greece, acquired on November 10, 2020. Masking was performed in 42 olive tree plots including a total of 1,080 olive trees, including on-site visual validation of the masking results. Results show that the ANN performed better than AdaBoost and NDVI thresholding, scoring 81.98%, compared to 75.06 and 70.03%, respectively. The trained ANN is currently used to provide olive tree canopy estimates, used as input to assess canopy biomass available for pruning for the CompOlive system, an online platform that facilitates matchmaking of olive tree farms, olive mills, and mobile composting equipment, to optimise on-farm compost production and utilisation.

Acknowledgements

This research is co-financed by the European Union and Greek national funds through the Operational Program CRETE 2014-2020, under Project “CompOlive: Integrated System for the Exploitation of Olive Cultivation Byproducts Soil Amendments” (KPHP3-0028773).

References

Daliakopoulos, I. N., Grillakis, E. G., Koutroulis, A. G., & Tsanis, L. K. (2009). Tree Crown Detection on Multispectral VHR Satellite Imagery. Photogrammetric Engineering and Remote Sensing, 75(10), 1201–1211. https://doi.org/10.14358/PERS.75.10.1201

Velázquez-Martí, B., Fernández-González, E., López-Cortés, I., & Salazar-Hernández, D. M. (2011). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass and Bioenergy, 35(7), 3208–3217. https://doi.org/10.1016/J.BIOMBIOE.2011.04.042

Yang, L., Wu, X., Praun, E., & Ma, X. (2009). Tree detection from aerial imagery. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 131–137. https://doi.org/10.1145/1653771.1653792

 

How to cite: Fidani, S., Maroufidis, I., Chlorokostas, S., Daliakopoulos, I. N., Papadimitriou, D., Louloudakis, I., Daskalakis, G., Charalambopoulou, B., and Manios, T.: Comparison of three algorithms for tree crown area and available pruning biomass monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17144, https://doi.org/10.5194/egusphere-egu23-17144, 2023.

EGU23-969 | Posters on site | PS5.3

Lunar Mission Planning and Exploration using NASA’s Moon Trek Portal 

Emily Law and Brian Day and the Solar System Treks

NASA’s Moon Trek (https://trek.nasa.gov/moon/) is one of a growing number of interactive, browser-based, online portals for planetary data visualization and analysis produced by NASA’s Solar System Treks Project (SSTP). Moon Trek continues to be enhanced with new data and new capabilities enabling it to facilitate the planning and conducting of upcoming lunar missions by NASA, its commercial partners, and its international partners, as well as scientific research.

Moon Trek’s innovation visualization and analysis tools are already being used by a growing number of missions and scientists around the world. The tools deployed including interactive 2D and 3D visualization, a DEM and Ortho Mosaic Image production pipeline as well as tools for distance measurement, elevation profile generation, solar altitude and azimuth calculation, 3D print file generation, virtual reality visualization generation, lighting analysis, electrostatic surface potential analysis, slope analysis, rock detection, crater detection, rockfall detection, and profiling of raster data.

Moon Trek has added a new set of visualization and analysis tools include line of sight analysis (facilitating communications planning and detailed studies of solar illumination), traverse path planning, and 3D traverse path visualization tool, among others. This presentation for EGU will highlight Moon Trek’s latest tools and demonstrate their usage targeted for Lunar mission planning and exploration in this exciting Artemis era.

How to cite: Law, E. and Day, B. and the Solar System Treks: Lunar Mission Planning and Exploration using NASA’s Moon Trek Portal, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-969, https://doi.org/10.5194/egusphere-egu23-969, 2023.

This work studies the remanent magnetization under a weak and a strong magnetic anomaly in Tranquillitatis and in Oceanus Procellarum respectively, which show similar surface ages of 3.6 Ga and 3.3 Ga. A 3D amplitude inversion is used to reconstruct the distributions of magnetization underground. Since there is no globally measured surface magneticeld for the Moon, a crustal magnetic anomaly model with grid resolution of 0.2° is used. The depth to the bottom of the magnetic source is fixed by the boundary identified by a relative criterion, which is 20% of the recovered maximum magnetization. The results show that the two anomalies have different depths to the bottom and different volumes of magnetic sources. The depth to the bottom of the magnetic carriers, which is possibly the Curie depth, is about 30 km and 50 km under Oceanus and Tranquillitatis. The volumes of the two magnetic sources are at the scale of 104 and 105 km3, respectively. The Bouguer gravity anomalies with spherical harmonics reaching 1200 degree in the two studied regions are also checked. The results supports that the magma intrusions containing different abundances of metallic iron are the most possible origins of the magnetic sources in the studied regions. Besides, the thermal states of lunar crust under the two studied maria were probably different during the acquisition process of remanent magnetization.

How to cite: Wang, H. and Yao, S.: Depths to the Bottom and Volumes of Magnetic Sources under a Weak and a Strong Lunar Magnetic Anomaly Revealed by 3D Inversion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3164, https://doi.org/10.5194/egusphere-egu23-3164, 2023.

The planetary magnetic field, caused by convective currents in the cores and linking thermal and interior, is a fundamental way to determine the angular momentum exchange and secular variation in the core motions & core-mantle coupling system. But understanding the high temperature-pressure (e.g., ~5000 °C, 135~330 Gigapascals) rheology fluid flows in planetary cores is a tremendous interdisciplinary challenge. The fine-structure investigation requires understanding the fundamental rheology fluid dynamic involving turbulence and rotation from continuing hydro-dynamo-kinetic coupling scales well beyond the present traditional partial differential equation virtual test.

The lunar magnetic field is believed not currently to possess a feeble global magnetic field and can be ignored when exploring the solar-flare CME-induced solar storm transplant on the lunar surface. The hypothesis holds that the crustal magnetizations were acquired early in lunar history when dynamics were still operating. At that time, the dynamo magnetic fields were generated by the thermochemical convection of electrically conductive alloy metal liquid within lunar cores and reduced with the convection cooling process. The turbulence mechanical stirring of lunar core rheology fluids and perturbations by the tidal effect and orbital precession can contribute to sustaining dynamo fields.

With the supporting observations of China’s lunar and deep space exploration in recent years, it has become possible to re-estimates the past magnetic field by considering combining the tidal heating induced dissipation from viscous friction associated with the differential procession at a different angle and dynamo action (the non-ideal plasma; inner core-outer core-mantle; warm dense matter; liquid iron alloy; chemical-geological properties; density-temperature-pressure) together again.

In this work, based on the newly developed optimization methodology and numerical algorithm of relativistic hybrid particle-in-cell and lattice Boltzmann (RHPIC-LBM version 1.1.2), we establish the 3D lunular magnetic field modeling with combined rheology dynamo thermally and tidal-heating of its lunar cores and investigate the history of magnetic field evolution; And figure out the effect of tidal heating in the deepest lunar mantle,  and offer a possible unprecedented window on this intermediate state of rheology matter and providing a new virtual testing ground for dense rheology plasma theories.

How to cite: Zhu, B.: Exploration of Lunar magnetic fields with dynamo thermally and tidal heating-driven rheology model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3206, https://doi.org/10.5194/egusphere-egu23-3206, 2023.

EGU23-3992 | Posters on site | PS5.3

Lunar secondary crater distributions and ejecta fragment size velocity distributions: implications for regolith redistribution 

Kelsi Singer, Helle Skjetne, Julie Stopar, Mikayla Huffman, Clark Chapman, Lillian Ostrach, Brad Jolliff, and William McKinnon

We have performed an extensive study of secondary craters associated with specific primary craters on the Moon.  These data can be used to understand aspects of both (1) the secondary craters themselves and (2) the ejecta fragments that formed them.  Studying ejecta and secondary craters are a part of understanding the overall contributions of impacts to shaping and redistributing material across the lunar surface. 

We produced secondary crater size-range distributions for a large range of primary crater sizes (~0.8-660 km dimeter primaries).  Our results can be used to make a map of estimated maximum secondary crater sizes across the Moon.  They can also be used to test if a specific secondary crater cluster is likely related to a given primary crater.   

We also produced ejecta fragment size-velocity distributions for all our study sites.  These results can be used to understand the size and velocity of the ejecta fragments that were ejected as part of the primary impact.  This helps us understand the dynamics of the primary impact and the formation of fragments (or clusters of fragments) and how they are ejected during the passage of the shock wave through a planetary surface.  This new empirical data can be used to help constrain analytical and numerical models of dynamic fragmentation, place constraints on the largest ejecta fragments expected be ejected at escape velocity from the Moon, and used as inputs into models of regolith development and impact gardening. 

We will present the most current results on the above topics.  Initial results for 6 primary craters are presented in Singer et al. 2020 where we discovered a previously unrecognized trend where the size velocity distributions are dependent on the size of the impact (i.e., scale dependent).  We now have data on 10 additional primaries and further applications of the study. 

Singer, K. N., Jolliff, B. L., & McKinnon, W. B. (2020). Lunar secondary craters and estimated ejecta block sizes reveal a scale-dependent fragmentation trend. J. Geophys. Res., 125(8), e2019JE006313. doi:10.1029/2019JE006313

How to cite: Singer, K., Skjetne, H., Stopar, J., Huffman, M., Chapman, C., Ostrach, L., Jolliff, B., and McKinnon, W.: Lunar secondary crater distributions and ejecta fragment size velocity distributions: implications for regolith redistribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3992, https://doi.org/10.5194/egusphere-egu23-3992, 2023.

EGU23-5040 | Orals | PS5.3

The ESA/DLR LUNA Habitat as geophysical experimentation facility 

Martin Knapmeyer, Brigitte Knapmeyer-Endrun, Michael Maibaum, Jens Biele, Cinzia Fantinati, Oliver Küchemann, Stephan Ulamec, and Jean-Pierre de Vera

Recently, NASA’s InSight mission has shown the value of geophysical landers by greatly increasing our knowledge of the interior of Mars. Correspondingly, geophysical experiments are also of great relevance to lunar exploration: a number of geophysical experiments were proposed in response to the ESA's 2020 call for ideas for a scientific utilization of the large logistics lander (Argonaut). Geophysical payloads are already planned for the Moon, e.g. the Farside Seismic Suite will land a broad-band seismometer in 2025. We here present how the LUNA Habitat training facility under construction in Cologne, Germany, can contribute to the development and testing of lunar geophysical instrumentation.

The about 700 square meters of the LUNA Habitat will be covered by 60 cm of EAC-1 regolith simulant on most of the area. On an area of 140 square meters, regolith depth increases to 3 m along a sloping bottom (25° and 40°). This part of LUNA provides an invisible, but explorable underground structure suitable for seismic profiling, ground penetrating radar, geoelectrics, geomagnetics and other techniques, as well as sufficient depth for drilling, subsurface sampling, and deployment of heat flow probes. Sculpting craters and even caves in the regolith, as well as cooling small portions of it, is envisioned. Support by the facility will include personnel with experience in geophysical measurements and data analysis, an end-to-end operational environment including a remote control center with standard communication technology, and, last but not least, training of astronauts in co-operation with robotic units to operate the equipment in lunar surface suits and under gravity offloading.

A four-element, Y-shaped array of short period seismometers, based on the layout of the Apollo 17 seismic experiment, will be deployed on the LUNA construction site before erecting the building to record seismic noise sources (car traffic on the DLR campus, the ENVIHAB short arm centrifuge, wind tunnel discharges, air traffic on the nearby CGN international airport etc.). It will also allow for ambient noise analysis aimed at the underground structure, which is expected to consist of Rhine sediments. An active refraction seismic experiment and the deployment of 12 nodal sensors will further aid in site characterization. LUNA will have a concrete floor of up to 60 cm thickness, but with a structured underside for static reasons. The array will be re-deployed on the concrete once the hall is erected to characterize in how far the new high-velocity layer hides the underlying sediments from seismic observation. After completion of LUNA, the effect of the regolith cover on seismic recordings will be characterized by a third array deployment. Documentation of construction details, especially steel enforcing in the concrete, is foreseen.  A broad-band seismometer will be installed in the LUNA Habitat permanently, once construction is finished, to support the identification of artificial noise sources and local seismicity in the recordings of customer instruments, and monitor possible changes in the background e.g. due to new buildings or other large-scale research facilities on the DLR campus.

How to cite: Knapmeyer, M., Knapmeyer-Endrun, B., Maibaum, M., Biele, J., Fantinati, C., Küchemann, O., Ulamec, S., and de Vera, J.-P.: The ESA/DLR LUNA Habitat as geophysical experimentation facility, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5040, https://doi.org/10.5194/egusphere-egu23-5040, 2023.

EGU23-5929 | ECS | Orals | PS5.3

Mafic Mineral Anomaly in the Ohm Crater of the Moon 

Shreekumari Patel, Animireddi V Satyakumar, Paras Solanki, and Mohamed R El-maarry

The 64 km wide Ohm crater is a complex impact crater located on the northern side of the lunar farside. In this study, we generated abundance maps for FeO and TiO2 as well as Spectral Parameter maps to determine the composition. Orthopyroxene and Clinopyroxene, two mafic minerals, are present in the Ohm crater, according to spectral analyses of M3 data. A geostatistical technique is used to optimize the variation trend of diagnostic characteristics across different sites. We noticed that Opx dominates the rest of the crater, while Cpx dominates the western portion of Ohm. Opx denotes sources from above and/or below the crust-mantle boundary, whereas Cpx suggests impact melt crystallization of an anorthositic target crust. The NASA mission GRAIL, which is specifically designed to study gravity anomalies, has found negative anomalies near the Ohm crater that may indicate a thicker crust beneath the crater. Unequal Bouguer gravity anomalies and negative anomalies have been found in the vicinity of the Ohm crater, but they are not clearly connected to the internal morphology. Surface morphological features have no connection to these anomalies of uneven gravity. In addition, the Bouguer gravity signature may be affected by pre-existing subsurface density structure, and post-impact events (such as magmatism), which could account for some of the observed scatter. The regional gravity anomaly also indicates low values in the Ohm crater, suggesting that the thicker crust and the source of the geochemical anomalies are at deeper levels. Strong negative anomalies are seen in the predicted residual gravity data close to the Ohm crater, which suggests low-density bodies at the crustal level. We propose that the pyroxenes are the end product of impact melt crystallization based on regional and residual gravity anomalies, compositional and mineralogical features of the Ohm crater, and geophysical data. Ejecta from the SPA, Orientale, and Mascon Hertzsprung basins, which may or may not have differed from impact melt formed during the Ohm impact event, should also be looked at when analyzing the distribution of mafic minerals throughout the crater. The GRAIL crustal thickness model-1 for the Ohm crater indicates a thicker crust, demonstrating that the mantle upliftment is not the underlying cause of the geochemical anomalies in this area.

Acknowledgement: S. M. Patel and M. R. El-maarry acknowledge support for this work through an internal grant (8474000336-KU-SPSC).

How to cite: Patel, S., Satyakumar, A. V., Solanki, P., and El-maarry, M. R.: Mafic Mineral Anomaly in the Ohm Crater of the Moon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5929, https://doi.org/10.5194/egusphere-egu23-5929, 2023.

Because the Moon is much less flattened than the Earth, most lunar GIS applications use a spherical datum. However, nowadays, with the renaissance of lunar missions approaching, it seems worthwhile to define an ellipsoid of revolution that better fits the lunar gravity potential surface. The main long-term benefit of this might be to make the lunar adaptation of methods already implemented in terrestrial GNSS, gravimetry and GPS applications easier and somewhat more accurate.

In our work, we used a 660th degree and order potential surface called GRGM 1200A Lunar Geoid, developed in the frame of the GRAIL project. Samples were taken from the potential surface along a mesh that represents equal area pieces of the surface. The method of point grid selection was provided by a relatively simple Fibonacci sphere. We tried Fibonacci spheres with 100, 1000, 3000, 5000, 10000 and 100000 points and also separately examined the effect of rotating the network by length for a given number of points on the estimated parameters, but these differences was only noticeable for the lower resolution networks.

We estimated the best-fitting rotation ellipsoid semi-major axis and flatness data for the selenoid undulation values at the network points, which were obtained for a=1,737,576.6 m and f=0.000305. This parameter pair is already obtained for a 10000 point grid, while the case of reducing the points of the equidistant grid to 3000 does not cause a deviation in the axis data of more than 10 centimetres. As expected, the absolute value of the selenoid undulations has decreased compared to the values taken with respect to the spherical basal surface, with maxima exceeding +400 m still being found for Mare Serenitatis and Mare Imbrium, and the largest negative values for South Pole Aitken and Mare Orientale.

Supported by the ÚNKP-22-6 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.

How to cite: Cziráki, K. and Timár, G.: Estimation of the parameters of a lunar ellipsoid of revolution based on GRAIL selenoid data and Fibonacci mesh, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7979, https://doi.org/10.5194/egusphere-egu23-7979, 2023.

EGU23-8116 | Orals | PS5.3

Tungsten isotopes and the early evolution of the Moon 

Thomas Kruijer, Gregory Archer, and Thorsten Kleine

Key events in the early history of the Moon include its formation by a giant impact, the solidification of the lunar magma ocean, and late accretion. The 182Hf-182W system (t1/2 ~9 Ma) constitutes a versatile tool to study each of these processes because they can all result in measurable 182W variations. Here we review the 182W record of lunar rocks and highlight key constraints on the early evolution of the Moon. Tungsten isotope studies on lunar samples demonstrate that there are no resolvable 182W variations within the Moon, implying that lunar magma ocean differentiation later than ~70 Ma after Solar System formation. Nevertheless, the Moon is characterized by a uniform ~25 parts-per-million 182W excess over the present-day bulk silicate Earth (BSE). One possibility is that this 182W difference is radiogenic in origin, in which case the Hf-W system can potentially be used to date the formation of the Moon. However, this interpretation is problematic for two reasons. First, mixing processes during the giant impact very likely modified the 182W composition of the Moon and led to distinct initial 182W compositions of the Moon and Earth. Second, the pre-late accretion 182W compositions of the Moon and BSE overlap within uncertainty, and hence there is no resolved radiogenic 182W difference between the BSE and the Moon. Consequently, the Hf-W system does not provide reliable constraints on the age of the Moon. Instead, the Hf–W systematics are fully consistent with 'young' ages of the Moon, well after the effective lifetime of 182Hf.

How to cite: Kruijer, T., Archer, G., and Kleine, T.: Tungsten isotopes and the early evolution of the Moon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8116, https://doi.org/10.5194/egusphere-egu23-8116, 2023.

EGU23-10526 | ECS | Orals | PS5.3

Lunar Vertex: A PRISM Science Investigation of the Reiner Gamma Lunar Magnetic Anomaly and Swirl 

Sarah Vines, George Ho, David Blewett, Jasper Halekas, Benjamin Greenhagen, Brian Anderson, Dany Waller, Jörg-Micha Jahn, Peter Kollmann, Brett Denevi, Heather Meyer, Rachel Klima, Joshua Cahill, Lon Hood, Sonia Tikoo, Xiao-Duan Zou, Mark Weiczorek, Myriam Lemelin, Shahab Fatemi, and Edward Cloutis

Lunar Vertex is a mission at the intersection of multiple science communities, from planetary geology to space plasma physics. As the first Payloads and Research Investigations on the Surface of the Moon (PRISM1) investigation, scheduled for delivery to the Reiner Gamma (RG) magnetic anomaly in 2024 aboard a commercial lunar lander, Lunar Vertex will unravel the nature of the RG anomaly, the connection to and origin of the associated lunar swirl surface feature, and the structure and impact of the “mini-magnetosphere” in this region. Lunar Vertex includes a suite of magnetometers (Vector Magnetometer – Lander; VML), a fixed-mounted set of cameras (Vertex Camera Array; VCA), and a low-energy ion and electron plasma analyzer (Magnetic Anomaly Plasma Spectrometer; MAPS) on the lander. In addition, a second suite of commercial fluxgate magnetometers (Vector Magnetometer – Rover; VMR) and a multispectral imager (Rover Multispectral Microscope; RMM) are mounted on a dedicated rover that will traverse a distance of at least 500 m from the lander, providing additional multi-point measurements. The combination of magnetic field measurements taken during cruise and descent by VML and during surface operations by both VML and VMR will characterize the surface magnetic field within a strong lunar magnetic anomaly. The combined magnetic field and plasma measurements from VML and MAPS will provide direct observations of plasma populations reaching the lunar surface and the associated local magnetic field configuration. Furthermore, the lunar regolith within the RG magnetic anomaly and over different regions of the associated lunar swirl will be characterized by RMM and VCA to reveal the surface texture, composition, and particle distribution around both the lander and rover locations and the correspondence to potential surface weathering processes.

How to cite: Vines, S., Ho, G., Blewett, D., Halekas, J., Greenhagen, B., Anderson, B., Waller, D., Jahn, J.-M., Kollmann, P., Denevi, B., Meyer, H., Klima, R., Cahill, J., Hood, L., Tikoo, S., Zou, X.-D., Weiczorek, M., Lemelin, M., Fatemi, S., and Cloutis, E.: Lunar Vertex: A PRISM Science Investigation of the Reiner Gamma Lunar Magnetic Anomaly and Swirl, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10526, https://doi.org/10.5194/egusphere-egu23-10526, 2023.

EGU23-10737 | ECS | Orals | PS5.3

An Ultra-Wideband Spectrometer for Lunar Heat-Flow Measurements 

Mehmet Ogut, Shannon Brown, Alan Tanner, Sidharth Misra, Chris Ruf, Chi-Chih Chen, and Matthew Siegler

The lunar heat-flow ultra-wideband spectrometer operates over an extended frequency band from 300 MHz to 6.0 GHz. It is a direct-acquisition single-chain digital spectrometer measuring 1024 spectral channels over 6 GHz bandwidth with each channel bandwidth about 6 MHz. The LHR instrument is intended to characterize the near surface regolith thermal and dielectric properties in order to determine the local geothermal heat flux. It would also reveal subsurface thermal and dielectric property changes due to buried ice, dielectric materials like ilmenite, and bedrock. The wide spectral bandwidth is expected to provide up to 1 m deep brightness temperature measurements from as close as 5 cm penetration depth at higher frequency end of the spectra. Using information obtained at multiple frequency bands, the subsurface temperatures and dielectric properties can be reconstructed.

 

The instrument is currently being developed at Jet Propulsion Laboratory in Pasadena, CA. The design includes a novel receiver architecture allowing a single chain design for the ultra-wideband channelized spectral operation for enabling the science objectives of the instrument. The lab-bench demonstration of the lunar spectro-radiometer has been performed including the calibration testing. The environmental testing will be further conducted before proceeding with the flight model. The final flight version of the spectro-radiometer instrument is expected to have light weight, low-power and small-size suitable for a deployment into a lunar rover or lander.

 

 

How to cite: Ogut, M., Brown, S., Tanner, A., Misra, S., Ruf, C., Chen, C.-C., and Siegler, M.: An Ultra-Wideband Spectrometer for Lunar Heat-Flow Measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10737, https://doi.org/10.5194/egusphere-egu23-10737, 2023.

EGU23-10755 | Posters on site | PS5.3

Radio Instrument Package for Lunar Ionospheric Observation: A Concept Study 

Christopher Watson, Thayyil Jayachandran, Anton Kascheyev, David Themens, Richard Langley, Richard Marchand, and Andrew Yau

The lunar ionosphere is a ~100 km thick layer of electrically charged plasma surrounding the moon.  Despite knowledge of its existence for decades, the structure and dynamics of the lunar plasma remain a mystery due to lack of consistent observational capacity. An enhanced observational picture of the lunar ionosphere and improved understanding of its formation/loss mechanisms is critical for understanding the lunar environment as a whole and assessing potential safety and economic hazards associated with lunar exploration and habitation. To address the high priority need for observations of the electrically charged constituents near the lunar surface, we introduce a concept study for the Radio Instrument Package for Lunar Ionospheric Observation (RIPLIO). RIPLIO would consist of a multi-CubeSat constellation (at least two satellites) in lunar orbit for the purpose of conducting “crosslink” radio occultation measurements of the lunar ionosphere, with at least one satellite carrying a very high frequency (VHF) transmitter broadcasting at multiple frequencies, and at least one satellite flying a broadband receiver to monitor transmitting satellites. Radio occultations intermittently occur when satellite-to-satellite signals cross through the lunar ionosphere, and the resulting phase perturbations of VHF signals may be analyzed to infer the ionosphere electron content and high- resolution vertical electron density profiles. As demonstrated in this study, RIPLIO would provide a novel means for lunar observation, with the potential to provide long-term, high-resolution observations of the lunar ionosphere with unprecedented pan-lunar detail.

How to cite: Watson, C., Jayachandran, T., Kascheyev, A., Themens, D., Langley, R., Marchand, R., and Yau, A.: Radio Instrument Package for Lunar Ionospheric Observation: A Concept Study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10755, https://doi.org/10.5194/egusphere-egu23-10755, 2023.

Boulders are a major surface feature on solid planets and small bodies, including asteroids and comets. Interest in these clasts range from applications relevant for landing site selection to geomechanical parameter characterization of the soil on which they rest [1], to measurements of their size frequency distributions [2] which is relevant for an understanding of their formation and erosion processes. On the Moon boulders are generally found in association with craters, hilltops, rilles, and other steep relief forms. Two main mechanisms of boulder formation are bedrock fragmentation and excavation by impacts, and progressive exposure of pre-existing blocks and fractured bedrock by removal of regolith from steep reliefs by diffusive creep.

An important issue are transport processes which can move the stones on the surface of their parent bodies. On the Moon, one group of boulders, frequently called “rolling stones”, have left tracks on the surface which can cover large distances. Mainly two mechanisms, meteoritic impact and moonquakes [3], have been cited in the literature as drivers of boulder displacements. Much less attention has been given to the hypothesis that other processes like thermal solar-induced rock breakdown [4] could deliver the initial momenta that could initiate the movement of meta stabile rocks.

From an AI -based mapping of the distribution of boulders with tracks on the lunar surface [5] we know that the majority of these boulders are found – not surprisingly - within craters. However, as the AI-based procedure strongly underestimated the number of boulders with tracks, we have conducted a new investigation to map these boulders. However, such a mapping it is only one prerequisite in understanding whether a thermally-induced breakdown could be responsible for an initial triggering of boulder movements. Boulders moving down the slopes disturb the mature regolith and move fresh lunar soil to the surface. This process should remotely be detectable through the stronger spectral features of the fresher optically immature regolith. The number of non-decayed boulders along crater walls should therefore be correlated with the strength of the absorption bands in spectra taken from those crater walls. Spectral characteristics of the refreshed crater walls are measurable through various quantities in the VIS-NIR (e.g. color ratios, etc.)

To start addressing the question to what extent a solar-induced breakdown can trigger rock movements, we have chosen lunar craters for which we have generated new boulder maps. For these craters we determine spectral characteristics and mineralogical composition based on a nonlinear spectral mixing model using M3 hyperspectral imager data from Chandrayaan-1. We are reporting the first results of spectral feature mapping for these craters and discuss the mineralogical interpretation, as well as the existence of a correlation between the number of observable boulders inside craters and identified spectral features of the regolith.

References:

[1] Filice, A., 1967, Science, 1967-06-16 156(3781): 1486-1487. [2] Ruesch, O. et al., 2022 Icarus, 387, 115200. [3] Kumar, S. et al., 2016, J. Geophys. Res. Planets, 121, 147– 179. [4] Molaro, J.L. et al., 2017, Icarus, 294, 247-261. [5] Bickel, V.T. et al., 2020, Nat Commun 11, 2862.

How to cite: Mall, U. and Surkov, Y.: Are day-night heating cycles a trigger for launching the “stones” on tour?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10887, https://doi.org/10.5194/egusphere-egu23-10887, 2023.

EGU23-11166 | ECS | Orals | PS5.3

Polar Ice Accumulation from Volcanically Induced Transient Atmospheres on the Moon 

Andrew Wilcoski, Paul Hayne, and Margaret Landis

Over the last few decades, observations have revealed the presence of water ice at the lunar poles and upended the notion of a completely dry lunar surface. These ice deposits hold information about the history of water on the Moon and in the Earth-Moon system, and are potential resources for future human exploration of the Moon. However, they remain relatively uncharacterized in abundance, distribution, and composition. Foremost among the open questions about lunar ice are: What were the sources of ice on the Moon’s surface, and how much water could have been delivered? The three most likely sources of lunar water ice are: (1) impact delivery from asteroids and/or comets, (2) solar wind ion implantation, and (3) volcanic outgassing of volatiles from the lunar interior. Here, we assess the viability of a volcanic source for water ice accumulated at the lunar poles.

[1] first suggested the occurrence of a volcanically induced transient atmosphere on the ancient Moon that would have been dominated by CO, but with a significant amount of H­2O. Further studies investigated the dynamics [2] and atmospheric escape processes [3] that would have affected such an atmosphere. [4] later suggested that a large number (30,000-100,000) of eruptions would have created less massive atmospheres during the Moon’s most volcanically active period (4-2 Ga).

We model the generation of transient atmospheres from 50,000 eruptions from 4 to 2 Ga, the subsequent escape of these atmospheres to space, and the concurrent accumulation of atmospheric water vapor as ice at the lunar poles [5]. The molecular composition of the modeled atmospheres is determined using estimates of outgassed volatile content for lunar volcanic eruptions derived from analyses of Apollo samples [4,6]. We model three atmospheric escape processes: (1) Jeans escape, (2) sputtering escape, and (3) photodissociative escape [3], and model photodissociative escape separately for both CO and H2O. We use maximum annual surface temperatures [7] measured by the Diviner Lunar Radiometer Experiment on board the Lunar Reconnaissance Orbiter [8] to calculate ice accumulation rates for each Diviner pixel within 30° latitude of the poles [5].

We find that water vapor is removed from a typical transient atmosphere in about 50 years via ice accumulation and photodissociative escape. About 41% of the total water vapor mass outgassed from 4 to 2 Ga is accumulated as ice on the surface. This demonstrates that a significant amount of ice (~8×1015 kg) could have been sourced from volcanic outgassing, though atmospheric escape processes also strongly control the efficacy of this mechanism.

 

[1] Needham, D. H. and Kring, D. A. (2017) EPSL, 478, 175-178. [2] Aleinov, I., et al. (2019) GRL 46, 5107-5116. [3] Tucker, O. J., et al. (2021) Icarus, 359, 114304. [4] Head, J. W., et al. (2020) GRL, 47, e2020GL089509. [5] Wilcoski, A. X., et al. (2022) PSJ 3.5, 99. [6] Rutherford, M. J., et al. (2017) Amer. Mineralogist, 102, 2045-2053. [7] Landis, Margaret E., et al. (2022) PSJ 3.2, 39. [8] Paige, D. A., et al. (2010) Space Sci. Rev., 150, 125- 160.

How to cite: Wilcoski, A., Hayne, P., and Landis, M.: Polar Ice Accumulation from Volcanically Induced Transient Atmospheres on the Moon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11166, https://doi.org/10.5194/egusphere-egu23-11166, 2023.

EGU23-13387 | ECS | Orals | PS5.3

Instrumentation for laser ablation ionisation mass spectrometry on the lunar surface 

Peter Keresztes Schmidt, Matthias Blaukovitsch, Nikita J. Boeren, Marek Tulej, Andreas Riedo, and Peter Wurz

With NASA’s increased focus on exploration of our Moon within the Artemis program, new scientific goals have been formulated to expand our knowledge on the history of our Solar System, including the evolution of the Earth-Moon system. Additionally, establishing a permanent human presence on the Moon has been declared a goal of the Artemis program, the success of which will inevitably depend on in-situ resource utilization (ISRU) of lunar material. In turn, successful ISRU requires methods capable of analysing and selecting suitable materials in place. To support these tasks, sensitive instrumentation capable of determining the elemental and isotope composition of geological samples from the lunar surface is essential. Consequently, defining and determining the technical requirements of such instrumentation, constructing it accordingly, and verifying its performance are all crucial steps in maximising the scientific return of such a mission. Furthermore, NASA’s Artemis program also aims to facilitate future human exploration of Mars, which implies that instrumentation applied successfully on the Moon might find its application on the Martian surface in the future.

 

We present our progress in designing, constructing and testing a prototype miniature laser ablation ionisation mass spectrometer (LIMS) for in-situ measurements on the lunar surface. The finalised instrument will be deployed on the Commercial Lunar Payload Service (CLPS) mission CP-22 scheduled for launch in late 2026 and land in the lunar south pole region. Our miniature reflectron-type time-of-flight mass analyser (160 mm x Ø 60 mm) designed for in-situ space applications was coupled to a pulsed Nd:YAG microchip laser system (SB1 series, Bright Microlaser Srl, Italy) operating at 532 nm (max. laser pulse energy of 40 µJ, pulse repetition rate of 100 Hz). The laser source and the optics were mounted colinearly to the optical axis of the instrument assembly into a cage system. This construction is modelled after the envisioned flight design, and therefore used to determine the required optical and electronic performance characteristics of the future flight instrument. The current flight design will be presented as well. Furthermore, validation of the technical implementation and verification of the scientific requirements will be discussed through the results of laser ablation experiments conducted on lunar regolith simulant.

How to cite: Keresztes Schmidt, P., Blaukovitsch, M., Boeren, N. J., Tulej, M., Riedo, A., and Wurz, P.: Instrumentation for laser ablation ionisation mass spectrometry on the lunar surface, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13387, https://doi.org/10.5194/egusphere-egu23-13387, 2023.

EGU23-13471 | ECS | Posters on site | PS5.3

Statistical Analysis of Lunar 1 Hz Waves Using ARTEMIS Observations 

Yuequn Lou, Xudong Gu, Xing Cao, Mingyu Wu, Sudong Xiao, Guoqiang Wang, Binbin Ni, and Tielong Zhang

Like 1 Hz waves occurring in the upstream of various celestial bodies in the solar system, 1 Hz narrowband whistler-mode waves are often observed around the Moon. However, the wave properties have not been thoroughly investigated, which makes it difficult to proclaim the generation mechanism of the waves. Using 5.5-year wave data from ARTEMIS, we perform a detailed investigation of 1 Hz waves in the near lunar space. The amplitude of lunar 1 Hz waves is generally 0.05-0.1 nT. In the GSE coordinates, the waves show no significant regional differentiation pattern but an absence inside the magnetosphere. Correspondingly, in the SSE coordinates, they can occur extensively at ~1.1-12 RL, while few events observed in the lunar wake due to a lack of interaction with the solar wind. Furthermore, the wave distributions exhibit modest day-night and dawn-dusk asymmetries, but less apparent north-south asymmetry. Compared with nightside, more intense waves with lower peak wave frequency are present on the dayside. The preferential distribution of 1 Hz waves exhibits a moderate correlation with strong magnetic anomalies. The waves propagate primarily at wave normal angles < 60° with an ellipticity of [-0.8, -0.3]. For stronger wave amplitudes and lower latitudes, 1 Hz waves generally have smaller wave normal angles and become more left-hand circularly polarized. Owing to the unique interaction between the Moon and solar wind, our statistical results might provide new insights into the generation mechanism(s) of 1 Hz waves in planetary plasma environments and promote the understanding of lunar plasma dynamics.

How to cite: Lou, Y., Gu, X., Cao, X., Wu, M., Xiao, S., Wang, G., Ni, B., and Zhang, T.: Statistical Analysis of Lunar 1 Hz Waves Using ARTEMIS Observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13471, https://doi.org/10.5194/egusphere-egu23-13471, 2023.

EGU23-13668 | ECS | Posters on site | PS5.3

Urban seismic noise investigation at the site of ESA/DLR’s future LUNA facility at Cologne, Germany 

Stefanie Hempel, Martin Knapmeyer, Jens Biele, and Hans-Herbert Fischer

As international efforts to return humans to the Moon are increasing, ESA's European Astronaut Center (EAC) and the German Aerospace Center (DLR) are expanding their facilities by the LUNA habitat providing a 700m²-wide testbed covered by 60cm lunar regolith simulant (EAC-1) for astronaut training, including deploying and operating geological and seismic regolith characterization experiments, In Site Resource Utilization technologies (ISRU), biological and chemical experiments by both telerobotic and human activity. The LUNA facility will be operated as collaboration between ESA and DLR's Microgravity User Support Center (MUSC, see also the presentation by Knapmeyer et al. at this conference).

Geophysical experiments have proven useful to investigate the subsurface structure at the landing sites of e.g. Apollo and Chang'e missions on the Moon, but also at the InSight landing site on Mars, and a seismometer experiment to the lunar far side is already scheduled (Far Side Seismic suite, in 2025). To support future geophysical investigations on the Moon, a first seismic experiment was conducted in June, 2018 at the previously envisioned site of the LUNA facility between the :envihab, a research facility of the Institute for Aerospace Medicine and the European Astronaut Center (EAC) at Cologne-Porz. This passive seismic experiment consisted of a four-element, Y-shaped array of short period seismometers, based on the layout of the Apollo 17 seismic experiment. It recorded regional seismicity as well as urban noise. These measurements will be repeated and expanded by an active seismic refraction experiment at the new construction site just south of the EAC - before, during and after the construction of the facility, before and after the installment of the regolith cover to investigate the impact of the LUNA facility on the data quality and coupling to the ground.

We present details of the 2018 experiment as well as preliminary results, analyzing ambient noise to map the dominant sources of urban noise such as car traffic and airplane traffic at the nearby CGN international airport, the operational noises of the :envihab centrifuge and the wind tunnel as well as nearby construction and drilling.

How to cite: Hempel, S., Knapmeyer, M., Biele, J., and Fischer, H.-H.: Urban seismic noise investigation at the site of ESA/DLR’s future LUNA facility at Cologne, Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13668, https://doi.org/10.5194/egusphere-egu23-13668, 2023.

EGU23-14255 | ECS | Posters on site | PS5.3

Photometry of rock-rich surfaces on airless bodies. 

Rachael Martina Marshal, Ottaviano Rüsch, Christian Wöhler, Kay Wohlfarth, Sergey Velichko, and Markus Patzek

Introduction and Methods:  Our understanding of the response of boulders to space weathering, micrometeorite abrasion, thermal fatigue, and consequently their evolution into regolith can be improved by characterizing the surface roughness of the uppermost layer of boulders. In the first phase of our study [1] we characterize the surface roughness of boulder fields photometrically by using the phase ratio methodology applied to orbital image data. In the second phase of our study (in-progress) we focus on characterizing the sub-mm scale topography and roughness of naturally fresh surfaces of meteorite samples. The photometric roughness of boulder fields on the lunar surface is studied by employing a normalized logarithmic phase ratio difference (NLPRD) metric, described in [1], to measure and compare the slope of the phase curve (reflectance versus phase angle) of a rock-rich field to a rock-free field . We compare the photometric roughness of rock-rich fields on simulated images, with the photometric roughness of rock-rich fields on Lunar Reconnaissance Orbiter Narrow Angle Camera (LROC NAC) images sampled around an Unnamed crater at Hertzsprung S.


Results and Discussion: The NLPRD is normalized to a rock-free reference surface, assuming the roughness of the regolith within the boulderfield is comparable to the roughness of the regolith at the rock-free reference regions, the higher roughness of the boulder-fields implies the presence of rocks with diverse sub-mm scale roughness and, possibly, variable single scattering albedo. In figure 1b, the spread in NLPRD values for different rock morphologies, is exceeded by the spread in  NLPRD of the NAC-resolved boulderfields. We find spatial clustering of photometrically smooth and rough boulderfields in the downrange and up-range respectively of the Unnamed crater at Hertzsprung S, reflecting ejecta asymmetry (in agreement with [2]) and possibly indicating asymmetric modification of ejecta rock surfaces during impact excavation process. Our results imply that rock physical properties at the start of the surface exposure period are a function of petrology as well as the (shock) effects imparted upon ejecta rock formation and excavation. The work-in progress deals with supplementing our findings with investigation of the sub-mm scale topography and roughness of meteorite and lunar samples. To study the sub-mm scale roughness of these samples we produce high-resolution DTMs at the µm scale using a non-contact optical profilometer. A sample high-resolution DTM of lunar breccia NWA11273 is shown in figure 2.



Figure 3 shows that variations of the mean slope with spatial scale exists within different meteorites types. Next, we will investigate the scale-dependent rock micro-texture of various samples (i.e., ordinary and carbonaceous chondrites, lunar basalts and breccias as well as meteorites from the HED clan), and provide typical values of surface roughness that will inform photometric modelling of rock surfaces.

References: [1] Marshal, R. M., Rüsch, O., Wöhler, C., Wohlfarth, K., & Velichko, S. (2022). Icarus, 115419 [2] Velichko, S., Korokhin, V., Velikodsky, Y., Kaydash, V., Shkuratov, Y., & Videen, G. (2020). PSS, 193.

How to cite: Marshal, R. M., Rüsch, O., Wöhler, C., Wohlfarth, K., Velichko, S., and Patzek, M.: Photometry of rock-rich surfaces on airless bodies., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14255, https://doi.org/10.5194/egusphere-egu23-14255, 2023.

EGU23-15759 | ECS | Posters on site | PS5.3

The MoonLIGHT Pointing Actuator (MPAc) project 

Laura Rubino, Alejandro Remujo Castro, Ubaldo Denni, Marco Muccino, Lorenzo Salvatori, Mattia Tibuzzi, Matteo Petrassi, Michele Montanari, Marco Traini, Luciana Filomena, Lorenza Mauro, Luca Porcelli, and Simone Dell'Agnello

Laser Ranging is a technique used to perform accurate precision distance measurements between a laser ground station and an optical target, a Cube Corner Retroreflector (CCR). Since 1969 it is possible to realize Lunar Laser Ranging (LLR) measurements thanks to Apollo and Luna missions that placed some arrays of CCRs on the lunar surface. LLR outputs include accurate tests of General Relativity, information of the composition of the Moon, its ephemerides and its internal structure or geocentric positions and motions of ground stations: research uniquely enabled by the Moon.

Despite laser ground stations have significantly improved during the years, the current limitation of the lunar optical target is due to lunar librations. In order to achieve more precise LLR measurements, MoonLIGHT project is designed by SCF_Lab joined UMD. The aim of the project is designing a next-generation of retroreflectors, prototyping, manufacturing and qualify them for the Moon’s environment. Moving from a multi small CCRs array to a single large 100 mm CCR, called MoonLIGHT, unaffected by the lunar librations.

The field of view of each CCR is limited: the retroreflector needs to be pointed precisely to the ground station. The Apollo CCR arrays were manually arranged by the astronauts. In 2018 INFN proposed to ESA the MoonLIGHT Pointing Actuators (MPAc) project, able to perform unmanned pointing operation of MoonLIGHT. In 2019 ESA chose MPAc among 135 eligible scientific project proposals. In 2021 ESA agreed with NASA to launch MPAc to the Reiner Gamma region of the Moon, with a Commercial Lunar Payload Services (CLPS), which is part of the Artemis program. The lander on which MPAc will be integrated is designed by Intuitive Machines (IM). The launch expected date is in April 2024.

MPAc must be able to perform two continuous perpendicular rotations to accurately point the frontal face of the CCR towards the Earth. The device is continuously evolving to ensure the success of the mission, that will take place in Ultra High Vacuum space conditions, in a wide operating temperature range. Terrestrial prototypes, with all the characteristics of the final structure, have been developed for the study of mechanical and electronics components. Qualification tests for space are being planned as the components for the Proto Flight Model (PFM) arrived to the LNF. Payload delivery is scheduled for August 2023.

MPAc will contribute to attain lunar orbit range accuracy below few mm. This will improve, in turn, the precision of the Parametrized Post-Newtonian (PPN) parameters and put more stringent constraints on departures from GR predictions with observations.

How to cite: Rubino, L., Remujo Castro, A., Denni, U., Muccino, M., Salvatori, L., Tibuzzi, M., Petrassi, M., Montanari, M., Traini, M., Filomena, L., Mauro, L., Porcelli, L., and Dell'Agnello, S.: The MoonLIGHT Pointing Actuator (MPAc) project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15759, https://doi.org/10.5194/egusphere-egu23-15759, 2023.

EGU23-15933 | ECS | Orals | PS5.3

Orbit Determination and Time Transfer for a Lunar Radio Navigation System 

Andrea Sesta, Mauro Di Benedetto, Daniele Durante, Luciano Iess, Michael Plumaris, Paolo Racioppa, Paolo Cappuccio, Ivan di Stefano, Debora Pastina, Giovanni Boscagli, Serena Molli, Fabrizio De Marchi, Gael Cascioli, Krzysztof Sosnica, Agnes Fienga, Nicola Linty, and Jacopo Belfi

Within the pre-phase A of the Moonlight project proposed and funded by the European Space Agency (ESA), the ATLAS consortium has proposed an architecture to support a Lunar Radio Navigation System (LRNS) capable of providing PNT (Positioning, Navigation, and Timing) services to various lunar users. The Moonlight LRNS will be a powerful tool in support of the lunar exploration endeavors, both human and robotic.

The ESA LRNS will consist of a small constellation of 3-4 satellites put in Elliptical Lunar Frozen Orbits (ELFO) with the aposelene above the southern hemisphere to better cover this region, given its interest for future lunar missions. This LRNS will be supported by a ground station network of small dish antennas (~30 cm), which can establish Multiple Spacecraft Per Aperture (MSPA) tracking at K-band. Any Earth station will be capable of sending a single uplink signal to multiple spacecraft thanks to Code Division Multiplexing modulation, while in the downlink multiple carriers can share the same K-band bandwidth by implementing Code Division Multiple Access (CDMA) on the onboard transponders. This allows the implementation of the Same Beam Interferometry (SBI) technique [1], which adds to spread spectrum ranging and Doppler measurements. In the scope of disseminating accurate PNT services to end users, the constellation will also be capable of maintaining a synchronization to the Earth station clocks to the ns level.

The performances of the proposed architecture have been validated through numerical simulations performed with the ESA GODOT software, enhanced with additional user-defined features and capabilities. For each satellite of the LRNS constellation, the attainable orbital accuracy is at level of a few meters for most orbit mean anomalies and it has been computed considering a setup which includes a perturbed dynamical model (mainly coming from uncertainties in the accelerations induced by the solar radiation pressure and orbital maneuvers) and a realistic error model for Doppler, ranging and SBI measurements.

REFERENCE:

  • Gregnanin, M. et al. (2012). Same beam interferometry as a tool for the investigation of the lunar interior. Planetary and Space Science 74, 194-201

How to cite: Sesta, A., Di Benedetto, M., Durante, D., Iess, L., Plumaris, M., Racioppa, P., Cappuccio, P., di Stefano, I., Pastina, D., Boscagli, G., Molli, S., De Marchi, F., Cascioli, G., Sosnica, K., Fienga, A., Linty, N., and Belfi, J.: Orbit Determination and Time Transfer for a Lunar Radio Navigation System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15933, https://doi.org/10.5194/egusphere-egu23-15933, 2023.

EGU23-16681 | Posters on site | PS5.3

Lunar plasma and electrostatic environment: numerical approach and its future prospects 

Yohei Miyake and Jin Nakazono

Mission preparation for lunar exploration using landers has been rapidly increasing, and strong demand should arise toward precise understanding of the electrostatic environment. The lunar surface, which has neither a dense atmosphere nor a global magnetic field, gets charged electrically by the collection of surrounding charged particles of the solar wind or the Earth's magnetosphere. As a result of the charging processes, the surface regolith particles behave as "charged dust grains". Dust particles have been suggested to have adverse effects on exploration instruments and living organisms during the lunar landing missions, and their safety evaluation is an issue to be solved for the realization of sustainable manned lunar explorations. It is necessary to develop comprehensive and organized understanding of lunar charging phenomena and the electrodynamic characteristics of charged dust particles.

It is widely accepted that the surface potential of the lunar dayside is, "on average" several to 10 V positive due to photoelectron emission in addition to the solar wind plasma precipitation. Recent studies, however, have shown that insulating and rugged surfaces of the Moon tend to make positive and negative charges separated and irregularly distributed, and intense and structured electric fields can be formed around them. This strong electric field lies in the innermost part of the photoelectron sheath and may contribute to mobilizations of the charged dust particles. Since this strong electric field develops on a spatial scale of less than the Debye length and can take various states depending on the lunar surface geometry, it is necessary to update the research approach. In this paper, we will discuss the direction of the near-surface plasma, electrostatic, and dust environment for upcoming lunar landing missions.

How to cite: Miyake, Y. and Nakazono, J.: Lunar plasma and electrostatic environment: numerical approach and its future prospects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16681, https://doi.org/10.5194/egusphere-egu23-16681, 2023.

EGU23-17528 | Posters on site | PS5.3

ILEWG/LUNEX EuroMoonMars & EuroSpaceHub Academy: Recent Highlights 

Bernard Foing, Henk Rogers, Serena Crotti, and Jara Pascual and the ILEWG LUNEX EuroMoonMars Team and EuroSpaceHub Academy

EuroMoonMars programme in Data Analysis, Instrumentation, Field Work and Astronautics: EuroMoonMars is an ILEWG programme [1-226] in collaboration with space agencies, academia, universities and research institutions and industries. The programme includes research activities for data analysis, instruments tests and development, field tests in MoonMars analogue, pilot projects , training and hands-on workshops , and outreach activities. Extreme environments on Earth often provide similar terrain conditions to sites on the Moon and Mars. In order to maximize scientific return it becomes more important to rehearse mission operations in the field and through simulations. EuroMoonMars field campaigns have then been organised in specific locations of technical, scientific and exploration interest. Lunex EuroMoonMars, has been organizing in collaboration with ESA, NASA, European and US universities a programme of data analysis, instrumentation tests, field work and analog missions for students and researchers in different locations worldwide since 2009, including Hawaii HI-SEAs, Utah MDRS, Iceland, Etna/ Vulcano Italy, Atacama, AATC Poland, ESTEC Netherlands, Eifel Germany, etc… Analogue missions provide a practical ground in which students can test the notions learnt at the university in a realistic simulation context. Over the course of these missions, students have access to special Space instrumentation, laboratories, Facilities, Science Operations, Human Robotic partnerships. In 2023 , EuroMoonMars and EuroSpaceHub Academy co-sponsored a series of EMMPOL Moonbase isolation simulation campaigns in Poland.

EuroSpaceHub programme for Space Innovation Workforce Development: The EuroSpaceHub project to facilitate accessibility to the Aerospace sector. EuroSpaceHub is a European-led project with collaborators worldwide, funded by the EIT HEI initiative - Innovation Capacity Building for Higher Education – with Agenda 2021-2027. The project includes six  core partners: Vilnius TU, ISU, U C Madrid,  Sikorsky Kyiv, Collabwith and Lunex. The project was created to foster collaboration, innovation and entrepreneurship in the European Aerospace sector. EuroSpaceHub Academy develops training programme for Space researchers and entrepreneurs.

Space Engineering Workforce Development: we have also developed a semester course of Space System Design Engineering at  EPFL Lausanne sicne 2020.

Interdisciplinary Space Workforce Development: In the frame of ISU International Space University and EuroSpaceHub academy, we performed lectures,  hands-on workshops including the operations of instruments on EuroMoonMars ExoGeoLab lander, workshops on MoonOutpost design performed in the frame of MSS master , or SSP Space Studies Programme. Together with ISU , EuroSpaceHub staff co-supervised various IP Individual Projects of students, and Master Research Projects.

EuroSpaceHub Participation to Congress and Events: We also co-sponsored the participation to conferences such as LPSC, EGU, IAC and the organization of events or workshops connecting the space scientists, engineers, innovators, entrepreneurs to space stakeholders. This included talks and expo booths at IAC International Astronautical Congress and Rome New Space Economy Forum.

How to cite: Foing, B., Rogers, H., Crotti, S., and Pascual, J. and the ILEWG LUNEX EuroMoonMars Team and EuroSpaceHub Academy: ILEWG/LUNEX EuroMoonMars & EuroSpaceHub Academy: Recent Highlights, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17528, https://doi.org/10.5194/egusphere-egu23-17528, 2023.

GI4 – Atmosphere and ocean monitoring

EGU23-135 | ECS | Orals | GI4.2

Deep-Pathfinder: A machine learning algorithm for mixing layer height detection based on lidar remote sensing data 

Jasper Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom

The mixing layer height (MLH) indicates the change between vertical mixing of air near the surface and less turbulent air above. MLH is important for the dispersion of air pollutants and greenhouse gases, and assessing the performance of numerical weather prediction systems. Existing lidar-based MLH detection algorithms typically do not use the full resolution of the ceilometer, require manual feature engineering, and often do not enforce temporal consistency of the MLH profile. Given the large-scale availability of lidar remote sensing data and the high temporal and spatial resolution at which it is recorded, this domain is very suitable for machine learning approaches such as deep learning. This presentation introduces a completely new approach to estimate MLH: the Deep-Pathfinder algorithm, based on deep learning techniques for image segmentation.

The concept of Deep-Pathfinder is to represent the 24-hour MLH profile as a mask (i.e., black indicating the mixing layer, white indicating the non-turbulent atmosphere above) and directly predict the mask from an image with lidar observations. Range-corrected signal (RCS) data at 12-second temporal and 10-meter vertical resolution was obtained from Lufft CHM 15k ceilometers at five locations in the Netherlands (2020–2022). High-resolution annotations were created for 50 days, informed by a visual inspection of the RCS image, the manufacturer's layer detection algorithm, gradient fields, thermodynamic MLH estimates, and humidity profiles of the 213-meter mast at Cabauw.

Our model is based on a customised U-Net architecture with MobileNetV2 encoder to ensure fast inference times. A nighttime variable indicated whether the sample occurred between sunset and sunrise and hence, whether an estimate of the stable or convective boundary layer was required. Model calibration was performed on the Dutch National Supercomputer Snellius. First, input samples were randomly cropped to 224x224 pixels, covering a 45-minute period and maximum altitude of 2240 meters. Then, the model was pre-trained on 19.4 million samples of unlabelled data. Finally, the labelled data was used to fine-tune the model for the task of mask prediction. Performance on a test set was compared to MLH estimates from ceilometer manufacturer Lufft and the STRATfinder algorithm.

Results showed that days with a clear convective boundary layer were captured well by all three methods, with minimal differences between them. The Lufft wavelet covariance transform algorithm contained a slight temporal shift in MLH estimates. Further, it had more missing data in complex atmospheric conditions. STRATfinder estimates for the nocturnal boundary layer were consistently low due to guiding restrictions in the algorithm. In contrast, Deep-Pathfinder followed short-term fluctuations in MLH more closely due to the use of high-resolution input data. Path optimisation algorithms like STRATfinder have good temporal consistency but can only be evaluated after a full day of ceilometer data has been recorded. Deep-Pathfinder retains the advantages of temporal consistency by assessing MLH evolution in 45-minute samples, however, it can also provide real-time estimates. This makes a deep learning approach as presented here valuable for operational use, as real-time MLH detection better meets the requirements of users in aviation, weather forecasting and air quality monitoring.

How to cite: Wijnands, J., Apituley, A., Alves Gouveia, D., and Noteboom, J. W.: Deep-Pathfinder: A machine learning algorithm for mixing layer height detection based on lidar remote sensing data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-135, https://doi.org/10.5194/egusphere-egu23-135, 2023.

EGU23-1387 | ECS | Posters on site | GI4.2

Optical properties of birch pollen using a synergy of three lidar instruments 

Maria Filioglou, Ari Leskinen, Ville Vakkari, Minttu Tuononen, Xiaoxia Shang, and Mika Komppula

Pollen has important implications for health, but also for the climate as it can act as cloud condensation nuclei or ice nuclei in cloud processing. Active remote sensing instruments equipped with polarization capability can extend the detection of pollen from the surface up to several kilometres in the atmosphere maintaining continuous and high time resolution operation. In this study, we use a synergy of three lidars, namely, a multi-wavelength PollyXT lidar, a Vaisala CL61 ceilometer and a Halo Photonics StreamLine Doppler lidar, to investigate the optical properties of birch pollen particles. All three lidars are equipped with polarization channels enabling the investigation of the wavelength dependence at 355, 532, 910 and 1565 nm. Together with pollen observations from a Hirst-type spore sampler and aerosol in situ observations, we were able to characterize the linear particle depolarization ratio (PDR) and backscatter-related Angstrom exponents of the pollen particles. Both optical properties have been extensively used in aerosol classification algorithms and they are therefore highly desired in the lidar community. We found that birch pollen exhibits a spectral dependence in the PDR, and its classification is feasible when, preferably, two or more polarization wavelengths are available.

How to cite: Filioglou, M., Leskinen, A., Vakkari, V., Tuononen, M., Shang, X., and Komppula, M.: Optical properties of birch pollen using a synergy of three lidar instruments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1387, https://doi.org/10.5194/egusphere-egu23-1387, 2023.

Ice clouds in the Arctic are expected to have different radiative properties compared to mid latitude cirrus, because of the different humidity and temperature profile and also the prevalent aerosol loading in northern latitudes which govern their formation. During the late winter and early spring 2022 the HALO-(AC)3 campaign was conducted out of Kiruna (Sweden) to probe artic clouds with an airborne remote sensing payload. For this purpose, the German research aircraft HALO was equipped with a water vapor Differential Absorption Lidar (DIAL), a cloud radar, micro-wave radiometers, radiation measurements in the visible, near infrared and thermal region and a drop-sonde dispenser. A total of 25 flights where performed mainly over the sea between Svalbard and Greenland and up to nearly 90°N.

The primary observable to study ice cloud formation is the relative humidity, which is not directly measurable by lidar, but can only be computed with the aid of additional temperature information. By comparison with a large number of dropsondes launched during flight, we will show that the temperature field from ECMWF IFS analyses and short-term forecasts provides sufficient accuracy to retrieve the relative humidity for ice cloud studies. Using this method we will analyse different scenarios of arctic cirrus formation: under stable artic conditions, during a warm air intrusion and while a cold air outbreak. An interesting special case is the modification of cirrus properties by the presence of an aerosol layer which is most probably composed of long range transported Sharan dust. 

How to cite: Wirth, M. and Groß, S.: Characterisation of Arctic Cirrus by Airborne Water Vapor and High Spectral Resolution Lidar, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2024, https://doi.org/10.5194/egusphere-egu23-2024, 2023.

The atmospheric boundary layer is a layer that directly responds to energy emitted or absorbed from the ground into the atmosphere, and is greatly affected by various meteorological factors, which change the concentration of air pollutants. There is generally an inversion layer above the atmospheric boundary layer, so most of the air pollutants emitted by humans cannot escape to the outside of the atmospheric boundary layer and remain there. Ulsan Metropolitan City in Korea is known as the largest industrial city in Korea. These industrial cities generally emit more air pollutants than other cities. Since these air pollutants are greatly affected by the boundary layer, it is important to accurately calculate the height of the boundary layer. In this study, we compare the height of the atmospheric boundary layer based on LiDAR and the height of the atmospheric boundary layer in the Weather Research and Forecasting numerical model, and examine how the height of the atmospheric boundary layer affects the change in the concentration of air pollutants.

How to cite: Choi, K. and Song, C.: Effect of air pollutant concentration according to the height of the Planetary boundary layer in Ulsan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3042, https://doi.org/10.5194/egusphere-egu23-3042, 2023.

EGU23-3068 | ECS | Posters on site | GI4.2

Improvement of wind vector retrieval method for increasing data acquisition rate of the wind profiler and the wind lidar 

Yujin Kim, Byung Hyuk Kwon, Jiwoo Seo, Geon Myeong Lee, and KyungHun Lee

Representative meteorological instruments that utilize the Doppler effect include Doppler radar, wind profiler, and wind lidar. The latter two instruments produce a vertical profile of winds in high spatio-temporal resolution, in the atmospheric boundary layer. Wind lidar observes with a vertical resolution of 50 m or less and a temporal resolution in minutes, so it fills the observation gap in the lower layer where the wind profiler misses meteorological data. The wind lidar makes the wind vector using DBS (Doppler Beam Swinging) and VAD (Velocity Azimuth Display) methods. It is known that the wind by the VAD method is more accurate than the wind by the DBS method. The DBS method has the advantage of obtaining a wind profile with a fast scan time. On the other hand, there is a restriction that requires at least two beams including vertical beams (one of the east and west beams, and one of the south and north beams), which causes a decrease in the data acquisition rate. The VAD method was improved to produce more wind vector of the wind profiler as well as the wind lidar, which generally uses 5 beams. First, the Fourier series was estimated with the radial velocity by the DBS method. Next, the wind vector was determined by setting the azimuth interval and applying the radial velocity by the Fourier series to the VAD method. The wind vectors were retrieved at the altitude where the wind was not calculated by the DBS method, and the results of the two methods were consistent at the altitude where the wind was calculated by the DBS and the improved VAD method. In this study, we propose a method to increase the data acquisition rate even if the vertical beam or one of the inclined beams is insufficient.

How to cite: Kim, Y., Kwon, B. H., Seo, J., Lee, G. M., and Lee, K.: Improvement of wind vector retrieval method for increasing data acquisition rate of the wind profiler and the wind lidar, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3068, https://doi.org/10.5194/egusphere-egu23-3068, 2023.

EGU23-4339 | Orals | GI4.2

Climatological assessment of the vertically resolved optical aerosol properties by lidar measurements and their influence on radiative budget over the last two decades at UPC Barcelona 

Simone Lolli, Adolfo Comeron, Cristina Gíl-Diaz, Tony Landi, Constantin Munoz-Porcar, Daniel Oliveira, Alejandro Rodriguez-Gomez, Michael Sïcard, Andrés Alastuey, Xavier Querol, and Cristina Reche

In the last two decades, several scientific studies have highlighted the adverse effects, primarily on population health, transportation, and climate, of urban atmospheric particulate due to anthropogenic emissions. For these reasons, aerosols have been monitored through both, remote sensing and in-situ observation platforms, also to establish if the reduction emission policies implemented at the government level have had positive outcomes. In this study, for the first time, we assess how the vertically resolved properties of the atmospheric particulate have changed and consequently their radiative effect during the last twenty years in Barcelona, Spain, one of the largest metropolitan areas of the Mediterranean basin. This study is carried out in the frame of the ACTRIS project through synergy between lidar measurements and the meteorological variables, e.g. wind, temperature, and humidity at the surface. This research, thanks to twenty-year measurements, can shed some light on the meteorological processes and conditions that can lead to haze formation and can help decision-makers to adopt mitigation strategies to preserve large marine Mediterranean metropolitan regions.

How to cite: Lolli, S., Comeron, A., Gíl-Diaz, C., Landi, T., Munoz-Porcar, C., Oliveira, D., Rodriguez-Gomez, A., Sïcard, M., Alastuey, A., Querol, X., and Reche, C.: Climatological assessment of the vertically resolved optical aerosol properties by lidar measurements and their influence on radiative budget over the last two decades at UPC Barcelona, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4339, https://doi.org/10.5194/egusphere-egu23-4339, 2023.

EGU23-5753 | Posters on site | GI4.2

Latent flow measurement by Wind Lidar and Raman Lidar during WaLiNeas campaign 

Donato Summa, Paolo Di Girolamo, Noemi Franco, Ilaria Gandolfi, Marco Di Paolantonio, Marco Rosoldi, Fabio Madonna, Aldo Giunta, and Davide Dionisi

A network of water vapor Raman lidars  WaLiNeas (Lidar Network Assimilation) for improving heavy precipitation forecasting in the Mediterranean Sea has been designed among with the aim of providing water vapor measurements with high spatial-temporal resolution and accuracy, in order to be assimilated into AROME mesoscale models using a four-dimensional ensemble-variational approach with 15-min updates. The CONCERNIG Lidar from University of Basilicata and a Wind Lidar form CNR–IMAA are co-located in the University of Toulone between October 2022 and January 2023 in order to reach the campaign objective. For this scope a of vertical profiles of latent heat flux were obtained  as a  Covariance matrices from vertical wind component (w') and mixing ratio (q') are estimated as a retrieval of a Wind Lidar and Raman Lidar UV respectively.

In this way, a time series of vertical wind profiles from the selected case (31 Oct to 03 Nov) are computed. with temporal resolution Δt = 15 min and vertical resolution Δz = 90 m.  The specific humidity flux < w’ · q’>  [g/kg · m/s] is converted into the flux of latent heat (W/m2) by multiplication with the air density ρ obtained from the radiosonde and the latent heat of vaporization of water Lv. A flux comparison with ground-based water vapour Raman and wind lidar shows agreement within the instruments and the results will be presented during the conference

How to cite: Summa, D., Di Girolamo, P., Franco, N., Gandolfi, I., Di Paolantonio, M., Rosoldi, M., Madonna, F., Giunta, A., and Dionisi, D.: Latent flow measurement by Wind Lidar and Raman Lidar during WaLiNeas campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5753, https://doi.org/10.5194/egusphere-egu23-5753, 2023.

EGU23-7065 | Orals | GI4.2

Nitrous Oxide, N2O: Spectroscopic Investigations for Future Lidar Applications 

Christoph Kiemle, Christian Fruck, and Andreas Fix

Nitrous Oxide, N2O, is the third most important GHG contributing to human-induced global warming, after carbon dioxide and methane. Its growth rate is constantly increasing and its global warming potential is estimated to be 273 times higher than that of CO2 over 100 years. The major anthropogenic source is nitrogen fertilization in croplands. Soil N2O emissions are increasing due to interactions between nitrogen inputs and global warming, constituting an emerging positive N2O-climate feedback. The recent increase in global N2O emissions exceeds even the most pessimistic emission trend scenarios developed by the IPCC, underscoring the urgency of mitigating N2O emissions (Global Carbon Project, 2020). Estimating N2O emissions from agriculture is inherently complex and comes with a high degree of uncertainty, due to variability in weather and soil characteristics, in agricultural management options and in the interaction of field management with environmental variables. Further sources of N2O are processes in the chemical industry and combustion processes. The sink of N2O in the stratosphere increases the NOx concentration which catalytically depletes ozone. Better N2O measurements thus are urgently needed, particularly by means of remote sensing.

Airborne or satellite based N2O lidar remote sensing combines the advantages of high measurement accuracy, large-area coverage and nighttime measurement capability. Past initial feasibility studies revealed that Integrated-Path Differential-Absorption (IPDA) lidar providing vertical column concentrations of N2O would be the method of choice. In this current study we use the latest HITRAN spectroscopic data in order to identify appropriate N2O absorption lines in the wavelength region between 2.9 and 4.6 µm. The infrared spectral region challenges both lidar transmission and detection options. On the transmitter side, the use of optical parametric conversion schemes looks promising, while HgCdTe avalanche photodiode (APD), superconducting nanowire single-photon (SNSPD) or upconversion detectors (UCD) could offer high-efficiency low-noise signal detection. These options are implemented into a lidar simulation model in order to identify the optimal lidar system configuration for measuring N2O from aircraft or satellite using state-of-the-art technology.

How to cite: Kiemle, C., Fruck, C., and Fix, A.: Nitrous Oxide, N2O: Spectroscopic Investigations for Future Lidar Applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7065, https://doi.org/10.5194/egusphere-egu23-7065, 2023.

EGU23-7093 | ECS | Orals | GI4.2

Ceilometer aerosol retrieval and comparison with in-situ tower-measurements 

Marcus Müller, Ulrich Löhnert, and Birger Bohn

In recent years there is a growing interest in real-time aerosol profiling and in this context, the use of automated lidars and ceilometers (ALC) for aerosol remote sensing increased. Ceilometers were originally developed to measure cloud-base height automatically. Apart from this, they also provide vertically resolved backscatter information. Several algorithms have been developed to calibrate this signal and to derive aerosol concentration from it, bringing up new opportunities in air quality monitoring and boundary layer research.

The quality of ALCs is often evaluated by comparing the attenuated backscatter to measurements from high-power lidars. This approach is suitable to validate the backscatter signal. However, for the validation of the aerosol concentration, a direct comparison with an in-situ, optical aerosol measurement is more significant.

In this work, a comparison study was performed using the Jülich Observatory for Cloud Evolution. Data were processed and calibrated with algorithms by E-Profile (https://www.eumetnet.eu/activities/observations-programme/current-activities/e-profile/alc-network/). The aerosol retrieval was performed using a Klett inversion algorithm. Close to the JOYCE site a 120 m meteorological tower is located. This tower was used as a platform for the in-situ aerosol measurement, where an optical particle sizer was mounted 100 m above the ceilometer position.

We will show the setup and data processing of the in-situ measurements as well as an approach how ceilometer raw data can be processed, calibrated and used to retrieve aerosol concentration. First results of the comparison will be presented to evaluate the quality of ALC aerosol-measurement.

How to cite: Müller, M., Löhnert, U., and Bohn, B.: Ceilometer aerosol retrieval and comparison with in-situ tower-measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7093, https://doi.org/10.5194/egusphere-egu23-7093, 2023.

EGU23-7775 | Posters on site | GI4.2

Several months of continuous operation of two thermodynamic Raman lidars in the frame of WaLiNeAs 

Paolo Di Girolamo, Noemi Franco, Marco Di Paolantonio, Donato Summa, Davide Dionisi, Annalisa Di Bernardino, Anna Maria Iannarelli, and Tatiana Di Iorio

The University of Basilicata, in cooperation with ISMAR-CNR, deployed two compact Raman lidars, namely the system CONCERNING and the system MARCO, in Southern France in the frame of the “Water Vapor Lidar Network Assimilation (WaLiNeAs)” experiment. WaLiNeAs, primarily funded by the “French National Research Agency” (ANR), is an international field experiment aimed at studying extreme precipitation events and improving their predictability through the assimilation of water vapour profile measurements from a network of Raman lidar systems into mesoscale numerical models. The experiment has a specific geographical focus on Southern France. The measurement strategy implies the exploitation of seven Raman lidars along the Mediterranean coasts of Spain and France, capable to provide real-time measurements of water vapour mixing ratio profiles over a three-month period starting on October 1st, 2022.

CONCERNING (COmpact RamaN lidar for Atmospheric CO2 and ThERmodyNamic ProfilING), developed in the frame of a cooperation between University of Basilicata, ISMAR-CNR and University of Rome, is a compact and transportable Raman lidar system designed for long-term all-weather continuous operation, capable to perform high-resolution and accurate carbon dioxide and water vapour mixing ratio profile measurements, together with temperature and multi-wavelength (355, 532 and 1064 nm) particle backscattering/extinction/depolarization profile measurements. The system relies on a 45-cm diameter Newtonian telescope and on a diode-pumped Nd:Yag laser source, capable of emitting pulses at the three traditional wavelengths of this laser source(355, 532 and 1064 nm), with a single pulse energy at 355 nm of 110 mJ and an average emitted power of 11 watts, based on a pulse repetition frequency of 100 Hz.

MARCO (Micropulse Atmospheric Optical Radar for Climate Observations) is also a compact and easily transportable Raman lidar system, developed around a high- frequency laser source (20 kHz), capable to perform 24/7 high-resolution and accurate CO2 and water vapour mixing ratio profile measurements, together with temperature and single-wavelength (355 nm) particle backscattering/extinction/depolarization measurements. In the frame of WaLiNeAs, as a result of the restrictions imposed by air traffic authority in the use of the visible and infrared laser radiation, only the 355 wavelength was exploited in CONCERNING, the temperature channel was not available in MARCO, while the CO2 channels, not needed for the purposes of WaLiNeAs, were temporarily deactivated in both systems.

Both systems have been recently designed and developed and WaLiNeAs represents the first international field deployment for both. CONCERNING was deployed at the University of Toulon in La Garde (Lat.: 43.136040 N, Long.: 6.011650 E, Elev.: 65 m, with continuous measurements since 29 September 2022, i.e. over more than 100 days up to now), while MARCO, was deployed at the Direction de Services Techniques in Port-Saint-Louis-du-Rhône, Camargue (Lat.: 43.392570 N, Long.: 4.813480 E, Elev.: 5 m, with continuous measurements since 19 October 2022, i.e. over more than 80 days up to now). At the time of the submission of this abstract, both system are still operational with a tbc date for the stop of the operation of 31 January 2023. Preliminary results from these two systems will be illustrated and discussed during the Conference.

How to cite: Di Girolamo, P., Franco, N., Di Paolantonio, M., Summa, D., Dionisi, D., Di Bernardino, A., Iannarelli, A. M., and Di Iorio, T.: Several months of continuous operation of two thermodynamic Raman lidars in the frame of WaLiNeAs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7775, https://doi.org/10.5194/egusphere-egu23-7775, 2023.

EGU23-8014 | ECS | Posters on site | GI4.2

A compact general-purpose Doppler Lidar for lidar networks 

Jan Froh, Josef Höffner, Alsu Mauer, Thorben Mense, Ronald Eixmann, Gerd Baumgarten, Franz-Josef Lübken, Alexander Munk, Sarah Scheuer, Michael Strotkamp, and Bernd Jungbluth

We present the state of the VAHCOLI (Vertical and Horizontal COverage by Lidar) project for investigating small- to large-scale processes in the atmosphere. In the future, an array of compact lidars with multiple fields of view will allow for measurements of temperatures, winds and aerosols with high temporal and vertical resolution.

Doppler lidars, in particular resonance Doppler lidars, with daylight capability are challenging systems because of the small field of view, spectral filtering and other additional subsystems required compared to observations at night. We developed a universal Doppler lidar platform (~1m3, ~500kg) with all required technologies for automatic operation. The system is capable of studying Mie scattering (aerosols), Rayleigh scattering (air molecules), and resonance fluorescence on free potassium atoms in the middle atmosphere from 5 km to 100 km. Unique spectral methods and narrowband optical components allow precise wind, temperature, and aerosol measurements by studying the Doppler shift and broadening of the scattered signals. The combination of cost-efficient design and fast assembling of such a system allows the construction of a Doppler lidar network with identical units

We will show the latest results and discuss the next scientific and technical steps for network operation and transferring the technology into industry.

How to cite: Froh, J., Höffner, J., Mauer, A., Mense, T., Eixmann, R., Baumgarten, G., Lübken, F.-J., Munk, A., Scheuer, S., Strotkamp, M., and Jungbluth, B.: A compact general-purpose Doppler Lidar for lidar networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8014, https://doi.org/10.5194/egusphere-egu23-8014, 2023.

EGU23-8149 | ECS | Orals | GI4.2

Water vapor retrieval from mini Raman lidar HORUS in the framework of the WaLiNeAs campaign 

Frédéric Laly, Patrick Chazette, Julien Totems, and Jérémy Lagarrigue

The Mediterranean Rim, and more particularly the western Mediterranean area, is one of the most sensitive regions to climate change. The associated environmental changes are already evident through periods of drought and intense rainfall. The predictions of these phenomena are a major societal issue, which led us to use lidar systems to constrain regional modelling. The Raman lidars HORUS-1 and -2 are each composed of two telescopes of 15 cm diameter.  For each telescope N2 and H2O channels are associated. Lidars components have been specifically defined for this task and put into operation during the international Water vapor Lidar Network Assimilation (WaLiNeAs) campaign led by French research teams. Among the three stations managed by the LSCE team, two of them were equipped with HORUS lidar systems at the Port Camargue (43.52 N 4.13 E) and Coursan (43.23 N 3.06 E) sites. The main difference between the two HORUS lidars is the laser used. For HORUS-1 we used an ULTRA laser (optimally pumped by a flash lamp at 30 mJ/20Hz) which showed a good reliability since the beginning of the lidar installation. However, the MERION-C laser (optimally pumped by diodes at 30 mJ/100 Hz) installed in HORUS-2 did not live up to our expectations with several failures, to the point of stopping the measurements in Coursan. We will nevertheless discuss the relative interest of these two lasers in projection of future Raman lidar networks. Observations available from these two lidar systems will be presented and discussed with respect to the meteorological processes encountered during their operating periods.

We give a special acknowledgment to the ANR grant #ANR-20-CE04-0001 for the contribution to the WaLiNeAs program and a special acknowledgment to Meteo France and to the CNRS INSU national LEFE program for their financial contribution for this project. The CEA is acknowledged for the provision of its staff and facilities.

How to cite: Laly, F., Chazette, P., Totems, J., and Lagarrigue, J.: Water vapor retrieval from mini Raman lidar HORUS in the framework of the WaLiNeAs campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8149, https://doi.org/10.5194/egusphere-egu23-8149, 2023.

Since there are only a very few suitable remote sensing measurements, the thermodynamic field of the atmospheric boundary layer and lower free troposphere is largely still Terra Incognita. To close this gap, we developed an automated thermodynamic profiler based on the Raman lidar technique, the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) (Lange et al. 2019).

It uses only the ice-safe 355-nm radiation of an injection-seeded Nd:YAG laser as transmitter. The laser power is about 20 W at 200 Hz. The diameter of the receiving telescope is 40 cm. Four receiving channels (elastic, water vapor, two rotational Raman signals) allow for four independently measured parameters: temperature (T), water vapor mixing ratio (WVMR), particle extinction coefficient, and particle backscatter coefficient.

With these data, ARTHUS resolves, e.g., the strength of the inversion layer at the atmospheric boundary layer (ABL) top, elevated lids in the free troposphere, and turbulent fluctuations. Furthermore, in combination with Doppler lidars, sensible and latent heat flux profiles in the convective ABL and thus flux-gradient relationships can be studied (Behrendt et al. 2020). Consequently, ARTHUS can be applied for process studies of land-atmosphere feedback, weather and climate monitoring, model verification, and data assimilation.

Resolutions of the measurements are a few seconds and meters in the lower troposphere. With the data, also the statistical uncertainties of the measured parameters are derived. Continuous operations over long periods were achieved not only at the Land Atmosphere Feedback Observatory (LAFO) at University of Hohenheim but also during several field campaigns elsewhere covering a large variety of atmospheric conditions.

During the EUREC4A field campaign (Stevens et al, 2020), ARTHUS was deployed onboard the research vessel Maria S Merian between 18 January and 18 February 2020 to study ocean-atmosphere interaction. Here, ARTHUS was collocated with two Doppler lidars: one in vertically pointing mode and one in a 6-beam scanning mode.

Between 15 July and 20 September 2021, ARTHUS was deployed at the Lindenberg Observatory of the German Weather Service (DWD). The objective of the campaign was to investigate the long-term stability of ARTHUS by comparisons with four local radiosondes. Indeed, the very high accuracy during day and night were verified.

ARTHUS participated in WaLiNeAs (Water Vapor Lidar Network Assimilation) between 15 September and 10 December 2022. For this campaign, ARTHUS was deployed at the west coast of Corsica. The objective was to implement an integrated prediction tool to enhance the forecast of heavy precipitation events in southern France, primarily demonstrating the benefit of assimilating vertically resolved WVMR lidar data in the new version of the French operational AROME numerical weather prediction system.

At the conference, highlights of ARTHUS’ measurements during WaLiNeAs will be shown.

References:

Behrendt et al. 2020, https://doi.org/10.5194/amt-13-3221-2020

Lange et al. 2019, https://doi.org/10.1029/2019GL085774

Stevens et. al. 2021, https://doi.org/10.5194/essd-2021-18

How to cite: Lange, D., Behrendt, A., and Wulfmeyer, V.: The Atmospheric Raman Temperature and Humidity Sounder: Highlights of Four Years of Automated Measurements of the Atmospheric Boundary Layer and Free Troposphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10606, https://doi.org/10.5194/egusphere-egu23-10606, 2023.

The increasing atmospheric carbon dioxide (CO2) is the most important factor forcing climate change. However, due to lack of observation data about large-scale range-resolved CO2, there remains substantial uncertainty in current global atmospheric CO2 budget, which hinders giving insight into CO2 cycle and modeling its forcing to climate change. Space-based range-resolved differential absorption lidar (range-resolved DIAL), is a promising and powerful means for obtaining large-scale range-resolved CO2 data, but has been rarely studied. Prior to developing spaceborne range-resolved DIAL, a preliminary study on optimization of on/off-line wavelengths must be performed to ensure high signal-to-noise (SNR), high sensitivity to near surface region and minimize the interference of atmospheric factors. This study aims to find the optimum wavelength scenarios in terms of random errors determined by SNR, weighting functions used to assess sensitivity to near-surface region, and systematic errors affected by atmospheric factors. Firstly, we find the optimal on/off-line wavelengths at 1.57μm and 2.05μm, which are widely used and show good results for measuring CO2 concentration, after estimating on-line and off-line wavenumbers separately using evaluation indexes called  and . Furthermore, we get the optimum wavelength scenarios of spaceborne range-resolved DIAL by comparing the random, systematic errors and weighting functions of optimal on-line and off-line wavelengths at 1.57μm and 2.05μm. Results show that the wavelength scenario at 2.05μm is the optimal for spaceborne range-resolved CO2 detection. To satisfy the requirement that the relative random errors are smaller than 0.01 (<1%), systems at 2.05μm wavelength scenario with vertical resolution of 0.5 km, 0.7 km, 0.8 km, 0.9 km separately require that SNR values of on-line wavelength at 0 km height are larger than 10, 9, 8, 7.

How to cite: Hu, L., Yu, Z., Huang, Y., and Ma, R.: Performance Simulation of Spaceborne Range-resolved Differential Absorption Lidar System For CO2 Profile Detection At 1.57μm and 2.05μm Wavelength Scenarios, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11104, https://doi.org/10.5194/egusphere-egu23-11104, 2023.

Cirrus clouds, forming in the cold upper troposphere, are composed of ice crystals with various sizes and nonspherical shapes. They are observed at all latitudes covering over 30% of the Earth’s surface. Studies reveal that they have a significant impact on the radiation balance of our planet and, consequently, on the climate evolution. The radiative effect of cirrus clouds is strongly determined by the cloud microphysical, thermal, and optical properties. Furthermore, global aviation affects the Earth’s radiation balance by inducing contrails and exerting an indirect effect on the microphysical properties of naturally-formed cirrus clouds. In the last decades, the Arctic surface has been warming faster than other regions of the globe, which is known as Arctic Amplification. The thin and small-coverage cirrus clouds over the Arctic are presumed to largely contribute to it. Unfortunately, however, the optical and microphysical properties of cirrus clouds over the Arctic and the exact role they play in the elevated warming of the Arctic are far from understanding. Compared with the intensive studies of cirrus clouds in the tropics and midlatitude regions, cirrus cloud measurements and model studies at high latitudes are sparse. In this study, we present the comparisons of the particle linear depolarization ratio (PLDR) and occurrence rates of cirrus clouds at midlatitudes (35–60 oN; 30 oW–30 oE) and high latitudes (60–80 oN; 30 oW–30 oE) based on the analysis of lidar measurements of CALIPSO in the years 2018–2021. The results show that cirrus clouds at high latitudes appear at lower altitudes than the midlatitude cirrus clouds. The PLDR and occurrence rates of cirrus clouds at high latitudes are smaller than the midlatitude cirrus clouds. Furthermore, air traffic over Europe was significantly reduced in 2020 (starting from March) and only moderately reduced in 2021 due to the COVID-19 pandemic. Under this condition we are able to study the difference in the aviation impacts on the cirrus cloud properties at high latitudes and midlatitudes.

How to cite: Li, Q. and Groß, S.: CALIPSO observations of cirrus cloud properties: investigation of latitude differences and possible aviation impacts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11893, https://doi.org/10.5194/egusphere-egu23-11893, 2023.

EGU23-12585 | Posters on site | GI4.2

Investigation of 2021 summer wildfires in the Eastern Mediterranean: The ERATOSTHENES Centre of Excellence capabilities for atmospheric studies 

Rodanthi-Elisavet Mamouri, Dragos Ene, Holger Baars, Ronny Engelmann, Argyro Nisantzi, Maria Prodromou, Diofantos Hadjimitsis, and Albert Ansmann

In the summer of 2021, several wildfires were reported in the south of Turkey, fires that are considered one of the worst in the history of Turkey. Due to atmospheric conditions, the smoke plume travelled south between 27 July to 5 August 2021, and smoke layers arrived above Cyprus. 

In this work, the capabilities of the newly established ERATOSTHENES Centre of Excellence (CoE), to study large-scale atmospheric events is presented. The study is based on the synergistic use of different datasets of remote sensing techniques both from ground and space. The EARLINET multiwavelength-Raman-polarization lidar PollyXT-CYP hosted by the ERATOSTHENES CoE is continuously running since October 2020 in Limassol, and during summer 2021, the lidar observed smoke plumes from these extreme wildfires on the south coast of Turkey.  

The PollyXT-CYP is a key research infrastructure of the Cyprus Atmospheric Remote Sensing Observatory (CARO) of the ERATOSTHENES CoE established through the EXCELSIOR H2020 EU Teaming project coordinated by the Cyprus University of Technology. CARO will consist of two high-tech containers housing the PollyXT-CYP lidar and state-of-the art doppler lidar, cloud radar and radiometric equipment which will be used to measure the air quality, the dust transport, and the cloud properties over Cyprus. The CARO is a planning National Facility of the Republic of Cyprus for Aerosol and Cloud Remote Sensing Observations.

Land cover information which shows the type of burned vegetation is used together with satellite products to capture additionally the burned area and to investigate the carbon monoxide of the smoke plume. The study is focusing on the optical characteristics of the plume, as it was detected by the PollyXT-CYP lidar at Limassol. An intense fresh smoke layer was detected on 28-29 July 2021, at an altitude between 2.5 to 4.0 km, having a volume depolarization ratio of ~15% at 355n and ~20% at 532nm, and lidar ratio of 75-80sr at 355nm and 65-70sr at 532nm.

 

Acknowledgements

The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The PollyXT-CYP was funded by the German Federal Ministry of Education and Research (BMBF) via the PoLiCyTa project (grant no. 01LK1603A). The study is supported by “ACCEPT” project (Prot. No: LOCALDEV-0008) co-financed by the Financial Mechanism of Norway (85%) and the Republic of Cyprus (15%) in the framework of the programming period 2014 - 2021.

How to cite: Mamouri, R.-E., Ene, D., Baars, H., Engelmann, R., Nisantzi, A., Prodromou, M., Hadjimitsis, D., and Ansmann, A.: Investigation of 2021 summer wildfires in the Eastern Mediterranean: The ERATOSTHENES Centre of Excellence capabilities for atmospheric studies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12585, https://doi.org/10.5194/egusphere-egu23-12585, 2023.

A newly available Raman lidar (Purple Pulse Lidar Systems) for vertical profiling of atmospheric water vapor, temperature and aerosols was evaluated during the TEAMx pre-campaign (TEAMx-PC22) in summer 2022 in the Inn Valley (Austria). TEAMx (Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment) is an international research program addressing exchange processes in the atmosphere over mountains and their parametrization in numerical weather models and climate models. Prior to the multi disciplinary measurement campaign, planned in 2024/2025, the pre-campaign 2022 was rather performed for testing (new) instruments and measurement sites and finding synergies between certain devices.

The Raman lidar system is capable of profiling water vapor and temperature throughout the entire planetary boundary layer (typically 3 km to 4 km agl. on summer days) continuously with a basic temporal resolution of 10 s and a reasonable vertical resolution of 30 m to 100 m. Depending on conditions and temporal averaging, water vapor profiles could even be obtained up to ~7.5 km agl. during nighttime. The lidar system was located at the University of Innsbruck (downtown). It was operated side by side with a vertically staring Doppler wind lidar and a nearby (50 m) scanning Doppler wind lidar on the rooftop of the university building, which provide vertical profiles of the vertical wind component at a 1-s interval and vertical profiles of the three-dimensional wind vector at a 10-min interval, respectively. During the measurement period (Aug 2022 to Sep 2022), operational radiosondes were launched in close proximity, at Innsbruck Airport, roughly 3 km to the west of the lidar site. In addition to the daily ascent at 2 UTC, radiosondes were launched at about 8, 14 and 20 UTC on selected days with potentially complex meteorological conditions. We present a first assessment of the Raman lidar measurements through comparisons with the radiosonde data. Together with data from the wind lidars, we also present an interpretation for significant meteorological situations and events, such as foehn, a passing front, a thunderstorm and the formation of a convective boundary layer during a warm period.

How to cite: Vogelmann, H., Federer, M., Speidel, J., and Gohm, A.: Assessing the performance of a Combined Water Vapor / Temperature / Aerosol Raman Lidar within the TEAMx pre-campaign in the Inn Valley (Innsbruck, Austria) during Summer 2022, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13101, https://doi.org/10.5194/egusphere-egu23-13101, 2023.

EGU23-13218 | ECS | Orals | GI4.2

ARC and ATLAS: CARS software tools for the data analysis and quality assurance of lidar measurements performed within ACTRIS 

Nikolaos Siomos, Ioannis Binietoglou, Peristera Paschou, Mariana Adam, Giuseppe D'Amico, Benedikt Gast, Moritz Haarig, and Volker Freudenthaler

We present newly developed software for the data analysis and quality assurance of lidar systems operated in the ACTRIS (Aerosol Clouds and Trace Gases Research Infrastructure) research infrastructure. The software development is coordinated by the Meteorological Institute of Munich (MIM), which operates as one of the central facilities of the Center of Aerosol Remote Sensing (CARS) of ACTRIS. In the frame of ACTRIS, a large number of national facilities (NF) are operating lidar systems for aerosol remote sensing. In order to ensure homogeneously high data quality, CARS is developing appropriate common software tools to assist data processing, system intercomparison, and routine quality assurance of lidar data. Here, we present two such software tools, developed and tested using the long experience of the EARLINET (European Aerosol Research Lidar Network) community.

The ARC (Algorithm for Rayleigh Calculations) has been designed to calculate the cross-section and depolarization ratio of molecular back-scattering. The effect of Rotational Raman (RR) scattering is included line-by-line in ARC considering especially the partial blocking of the RR spectrum due to transmission through narrow-band interference filters. The algorithm supports calculation in variable meteorological conditions for an atmosphere that consists of up to five major gas components (N2, O2, CO2, Ar, H2O). Such a tool is needed in order to properly take into account the effect of air temperature in the molecular depolarization ratio measured by the NF lidar systems. It is also crucial for designing lidars that rely on RR scattering such as temperature and RR aerosol lidars and can even be applied for the algorithmic correction of unwanted effects introduced by the interference filter in such systems.

The second software package developed by CARS-MIM is ATLAS (AuTomated Lidar Analysis Software). It has been designed for the operational analysis of the quality assurance tests that should be regularly performed and submitted to CARS by the NF for the ACTRIS labeling process. ATLAS currently supports the analysis of all main CARS test procedures, that is, the Rayleigh fit, the Telecover, and the Polarization Calibration. It can also be used to directly compare signals from two lidar systems; It has already been applied in the first intercomparison campaign of CARS reference systems, organized in September 2022 in Magurele, Romania. The software takes raw lidar data as input so the user can detect otherwise-hidden issues in the preprocessing steps. At the time of writing, ATLAS is compatible with all ACTRIS lidar systems. Future updates will include automated syncing of the system metadata from the handbook of instruments of the network, currently hosted by the Single Calculus Chain (SCC), and a graphical user interface that will facilitate its adoption by the NF users. Both software packages are written in python and are open-source projects.

How to cite: Siomos, N., Binietoglou, I., Paschou, P., Adam, M., D'Amico, G., Gast, B., Haarig, M., and Freudenthaler, V.: ARC and ATLAS: CARS software tools for the data analysis and quality assurance of lidar measurements performed within ACTRIS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13218, https://doi.org/10.5194/egusphere-egu23-13218, 2023.

EGU23-13416 | Orals | GI4.2

Merging clouds retrieved from ALADIN/Aeolus and CALIOP/CALIPSO spaceborne lidars 

Artem Feofilov, Hélène Chepfer, and Vincent Noël

Clouds play an important role for the energy budget of Earth. But, when it comes to predicting the climate's future, their behavior in response to climate change is a major source of uncertainty. To understand and accurately predict the Earth's energy budget and climate, it is necessary to have a thorough understanding of the cloud variability, including their vertical distribution and optical properties.

Satellite observations have been able to provide ongoing monitoring of clouds all around the globe. Among them, active sounders hold a special place thanks to their capability of measuring the vertical position of the cloud with an accuracy of about 100 meters and with a typical horizontal sampling on the order of hundreds of meters. However, clouds retrieved from two spaceborne lidars are different, because the instruments use different wavelengths, pulse energies, pulse repetition frequencies, telescopes, and detectors. In addition, they do not overpass the atmosphere at the same local time.

In this work, we discuss the approach to merging the clouds retrieved from the space-borne lidar ALADIN/Aeolus, which has been orbiting the Earth since August 2018 and operating at 355nm wavelength with the clouds measured since 2006 by CALIPSO lidar, which operates at 532nm.

We demonstrate how to compensate for the existing instrumental differences to get an almost comparable cloud dataset and we discuss the importance of the aforementioned differences between the instruments. The method developed in this study sets the path for adding future lidars (e.g. ATLID/EarthCare) to the global climate lidar cloud record.

How to cite: Feofilov, A., Chepfer, H., and Noël, V.: Merging clouds retrieved from ALADIN/Aeolus and CALIOP/CALIPSO spaceborne lidars, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13416, https://doi.org/10.5194/egusphere-egu23-13416, 2023.

EGU23-13419 | ECS | Orals | GI4.2

Columnar heating rate and  radiative effects of dust aerosols using 20 years of lidar observations. 

Benedetto De Rosa, Lucia Mona, Simone Lolli, Aldo Amodeo, and Michalis Mytilinaios

The uncertainties of the Earth-atmosphere energy budget are associated with a poor understanding of direct and indirect aerosol effects. Dust is a mixture of different minerals, and its chemical and microphysical properties change during transport. Therefore, the influence of dust aerosols on radiative effects is characterized by great uncertainty. Due to meteorological atmospheric patterns, aerosol intrusions are very frequent in the Mediterranean, which is a climatic hot spot and where climate change is much stronger than in other parts of the world. In this study, we analyzed and assessed long-term trends of the surface and columnar heating rate and the radiative effects of dust aerosols using lidar observations. These measurements were taken in the framework of the European Aerosol Research Lidar Network (EARLINET) at Istituto di Metodologie per l'Analisi Ambientale (IMAA) with the Raman/elastic lidar MUSA (40°36′N, 15°44′E). The radiative transfer model Fu–Liou–Gu (FLG) was used to solve aerosol (no clouds) radiative fluxes, with aerosol extinction coefficient profiles from lidar observations as input data. All the cases of dust intrusion that occurred in the last twenty years were selected to understand how they affected the Earth-atmosphere radiative budget, both at the surface and at the top-of-the-atmosphere. In the future, these studies will be important for improving the accuracy of climate predictions.

How to cite: De Rosa, B., Mona, L., Lolli, S., Amodeo, A., and Mytilinaios, M.: Columnar heating rate and  radiative effects of dust aerosols using 20 years of lidar observations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13419, https://doi.org/10.5194/egusphere-egu23-13419, 2023.

EGU23-13643 | ECS | Orals | GI4.2

Is your aerosol backscatter retrieval afflicted by a sign error? 

Johannes Speidel and Hannes Vogelmann

Precise knowledge about the prevailing aerosol content in the atmosphere is very important for several reasons, as aerosols are involved in multiple important processes that not only have a direct impact on air quality, but also influence cloud formation and the earth's radiation budget. Besides that, continuous aerosol observations provide valuable information on atmospheric transport dynamics.
Aerosol backscatter coefficient measurements with elastic backscatter lidars are conducted since multiple decades [1], while the implemented retrieval algorithms predominantly refer to the seminal publications by Klett 1985, Fernald 1984 and Sasano 1985 [2,3,4]. The respective inversion algorithm is often simply called the 'Klett inversion', being a main reason why this algorithm is most often adapted. While more sophisticated aerosol lidars (e.g. Raman lidars, HSRL, ...) have been developed since, simple elastic backscatter lidar measurements are still very frequently conducted as they are technically easy to implement, often as a byproduct. In most cases, the corresponding retrieval algorithms still refer to the 'Klett inversion'.
Unfortunately, the inversion algorithm by Klett 1985 is afflicted by a sign error. In his publication, the sign error is hidden within a substitute, making it very hard to be recognized, representing a major pitfall. A comprehensive literature review revealed, that large parts of the aerosol lidar community are aware of this problem and have tacitly corrected it or, to a much smaller amount, even referred to an erratum which was published by Kaestner in 1986 [5].
However, at the same time and up to this date, a considerable error propagation can be found in literature as well, using and referring to the incorrect algorithm with the sign error included.
Therefore, we want to renew the awareness towards this sign error and show a corrected and slightly improved Klett inversion algorithm. In addition, we present the overall implication resulting from the uncorrected inversion algorithm by using exemplary case studies. Depending on the lidar location and prevailing atmospheric conditions, potential errors reach from marginal to major, often preventing error detection solely based on the magnitude of the calculated results. Simple a posteriori corrections are not possible, as the error magnitude depends on multiple factors.

[1] T. Trickl, H. Giehl, H. Jäger, and H. Vogelmann. 35 yr of stratospheric aerosol measurements at Garmisch-Partenkirchen: From Fuego to Eyjafjalla-   jökull, and beyond. Atmospheric Chemistry and Physics, 13(10):5205–5225, 2013.
[2] James D. Klett. Lidar inversion with variable backscatter/extinction ratios. Appl. Opt., 24(11):1638–1643, June 1985.
[3] Frederick G. Fernald. Analysis of atmospheric lidar observations: Some comments. Appl. Opt., 1984.
[4] Yasuhiro Sasano, Edward V. Browell, and Syed Ismail. Error caused by using a constant extinction/backscattering ratio in the lidar solution. Appl. Opt., 24(22):3929–3932, November 1985.
[5] Martina Kaestner. Lidar inversion with variable backscatter/extinction ratios: Comment. Applied Optics, 25(6):833–835, March 1986.

How to cite: Speidel, J. and Vogelmann, H.: Is your aerosol backscatter retrieval afflicted by a sign error?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13643, https://doi.org/10.5194/egusphere-egu23-13643, 2023.

EGU23-13823 | ECS | Posters on site | GI4.2

Development of a Carbon Dioxide Raman Lidar 

Moritz Schumacher, Andreas Behrendt, Diego Lange, and Volker Wulfmeyer

Carbon dioxide (CO2) is one of the most important greenhouse gases and therefore its detailed measurement is of high interest. As the concentration varies significantly with altitude and time, it is desirable to be able to measure vertical CO2 profiles with high temporal resolution. Profiles of high resolution will improve our understanding of atmospheric systems and the impact of the local environment, e.g., due to natural and anthropogenic sources and sinks. The use of these data in data assimilation provides the potential of improving climate models.

For water vapor and temperature the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) system has proven to be able to provide profiles with high resolution (10-60 s in time and 7.5-100 m vertically) and accuracy in the lower troposphere. Now this successful system will be expanded with a CO2 Raman channel, which is currently in development. After successful integration it will be possible to simultaneously measure CO2, water vapor and temperature profiles. Challenges are the weak signal of the backscattered light due to the low concentration and the small Raman backscatter cross section of CO2.

Further information on the CO2 Raman lidar will be given at the conference.

How to cite: Schumacher, M., Behrendt, A., Lange, D., and Wulfmeyer, V.: Development of a Carbon Dioxide Raman Lidar, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13823, https://doi.org/10.5194/egusphere-egu23-13823, 2023.

Extreme heavy precipitation events (HPEs) pose a threat to human life but, despite regular improvement, remain difficult to predict because of the lack of adequate high frequency and high-resolution water vapor (WV) observations in the low troposphere (below 3 km). To fill this observational gap, The Water vapor Lidar Network Assimilation (WaLiNeAs) initiative aims at implementing an integrated prediction tool (IPT), coupling network measurements of WV profiles, and a numerical weather prediction system to try to improve the  forecasts of  the amount, timing, and location of rainfall associated with HPEs in southern France (struck by ~ 7 HPEs per year on average during the fall).

In the fall/winter of 2022-2023, a network of 6 mobile Raman WV lidars was specifically implemented in Southern France (Aude, Gard, Var and Bouche du Rhone) and in Corsica. The network was complemented by 2 fixed Raman WV lidars in Barcelona and Valencia with the aim to provide measurements with high vertical resolution and accuracy to be assimilated in the French Application of Research to Operations at Mesoscale (AROME-France) model, using a four-dimensional ensemble-variational approach with 15-min updates in addition to the observations operationally assimilated (radar, satellites, …). This innovative IPT is expected to enhance the model capability for kilometer-scale prediction of HPEs over southern France up to 48 h in advance.

The field campaign was conducted from October of 2022 to January 2023, to cover the period most propitious to heavy precipitation events in southern France. A consortium of French, German, Italian, and Spanish research groups operated the Raman WV lidar network

In this presentation, we will provide an overview of the precipitation events in southern France during the WaLiNeAs campaign, as well as an outline of the operations period of the different Raman WV lidars and the lidar data monitoring procedure implemented during the experiment. We will highlight the cases of interest and provide an outlook at next steps towards lidar data assimilation in AROME.

How to cite: Flamant, C. and the WaLiNeAs Team: A network of water vapor Raman lidars for improving heavy precipitation forecasting in southern France: introducing the WaLiNeAs initiative and first highlights from the 2022 field campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14747, https://doi.org/10.5194/egusphere-egu23-14747, 2023.

Each year, during both boreal winter and summer, large amounts of Saharan mineral dust particles get carried westwards over the Atlantic Ocean towards the Caribbean. During their transport, Saharan dust particles can affect the Earth’s radiation budget in different ways. They can either directly scatter, absorb and emit radiation or have an indirect effect by modifying cloud properties through their interactions as cloud condensation nuclei or ice nucleating particles. While during the summer months – the peak season of transatlantic mineral dust transport – the particles are mostly advected in elevated Saharan Air Layers at altitudes of up to 6 km and at latitudes around 15°N, wintertime transport takes place at lower atmospheric levels (<3 km altitude) and lower latitudes. Our recent studies have shown that, during both boreal winter and summer, transported Saharan dust layers are characterized by enhanced concentrations of water vapor compared to the surrounding atmosphere. In this way the dust layers have to potential to modify the radiation budget not only through particle-radiation-interactions, but also through the absorption and emission of radiation by water vapor. This in turn may affect the atmospheric stability and stratification in and around the aerosol layers.

In this study, the turbulent structure as well as the atmospheric stability in and around transported Saharan mineral dust is analyzed and possible differences between summer and wintertime are investigated. Therefore, measurements by both the water vapor and aerosol lidar WALES as well as by dropsondes are studied. They were collected upstream the Caribbean island of Barbados aboard the German research aircraft HALO (High Altitude and Long Range). To identify possible seasonal differences, not only data collected in boreal summer in the framework of the NARVAL-II campaign (August 2016), but also data collected in winter during the EUREC4A research campaign (January & February 2020) are analyzed. During both campaigns several research flights were designed to lead over long-range-transported Saharan mineral dust, thus allowing and in-depth investigation of their properties. The analysis shows that dust layers are highly turbulent and therefore help dust particles to stay airborne for a longer time. Additionally, the dust layers modify the atmospheric stability in a way that the evolution of marine clouds can be affected.

In our presentation, we will give an overview of the performed measurements over long-range-transported Saharan dust layers and present the conducted analyses on atmospheric stability and turbulence from dropsonde measurements and calculated power spectra from lidar data.

How to cite: Gutleben, M. and Groß, S.: Atmospheric turbulence and stability in and around long-range-transported Saharan dust layers as observed by airborne lidar and dropsondes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15538, https://doi.org/10.5194/egusphere-egu23-15538, 2023.

EGU23-15605 | Posters on site | GI4.2

How good are temperature and humidity measurements with lidar? 

Andreas Behrendt, Diego Lange, and Volker Wulfmeyer

In this contribution, we will discuss the performance of state-of-the-art automatic temperature and humidity lidar (e.g., Wulfmeyer and Behrendt 2022). As example, we will investigate ARTHUS (Lange et al., 2019), a lidar system developed at University of Hohenheim. This automatic mobile instrument participated in recent years in a number of field campaigns.

ARTHUS technical configuration is the following: A strong diode-pumped Nd:YAG laser is used as transmitter. It produces 200 Hz laser pulses with up to 20 W average power at 355 nm. Only this UV light is sent after beam expansion into the atmosphere so that the system remains eye safe. The atmospheric backscatter signals are collected with a 40 cm telescope. A polychromator extracts the elastic backscatter signal and three inelastic signals, namely the vibrational Raman signal of water vapor, and two pure rotational Raman signals. The detection resolution of these backscatter signals are 1 to 10 s and 3.75 to 7.5 m. All four signals are simultaneously analyzed and stored in both photon-counting (PC) mode and voltage (so-called “analog” mode) in order to make optimum use of the large intensity range of the backscatter signals covering several orders of magnitude.

From these eight primary signals measured by ARTHUS, four independent atmospheric parameters are calculated merging the PC and analog signals: temperature, water vapor mixing ratio, particle backscatter coefficient, and particle extinction coefficient. The temporal resolution of these data is also 1 to 10 s, allowing studies of boundary layer turbulence (Behrendt et al, 2015) and - in combination with a vertical pointing Doppler lidar - sensible and latent heat fluxes (Behrendt et al, 2020).

From the measured number of photon counts in each range bin, the statistical uncertainty of the measured data due to so-called shot-noise can directly be calculated. This value, however, while determining the major part of the uncertainty, does not cover the total uncertainty because additional noise of the analog signals is not included. So the shot-noise uncertainty alone underestimates the uncertainties in the near range where the analog data is used. To solve with this problem, higher-order analyses of the turbulent fluctuations can be performed which allow to determine the total statistical uncertainty of the measurements (Behrendt et al, 2020).

Finally, to investigate the stability of the calibration and thus the accuracy of the measured data, we decided to compare averaged ARTHUS data with local radiosondes. In order to cope with the unavoidable sampling of different air masses between these different instruments, we are investigating the average of a larger number of profiles.  We found that the performance of the measured data of ARTHUS reaches even the stringent requirements of WMO.

The results will be presented at the conference.

 

References:

Behrendt et al. 2015, https://doi.org/10.5194/acp-15-5485-2015

Behrendt et al. 2020, https://doi.org/10.5194/amt-13-3221-2020

Lange et al. 2019, https://doi.org/10.1029/2019GL085774

Wulfmeyer and Behrendt 2022, https://doi.org/10.1007/978-3-030-52171-4_25

How to cite: Behrendt, A., Lange, D., and Wulfmeyer, V.: How good are temperature and humidity measurements with lidar?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15605, https://doi.org/10.5194/egusphere-egu23-15605, 2023.

EGU23-15696 | Posters on site | GI4.2

A new filtering approach for multiple Doppler Lidar setups 

Kevin Wolz, Christopher Holst, Frank Beyrich, and Matthias Mauder

We compare the wind measurements of a virtual tower triple Doppler Lidar setup to those of a sonic anemometer located at a height of 90 m above ground on an instrumented tower and with those of a single Doppler Lidar. The instruments were set up at the boundary-layer field site of the German Meteorological Service (DWD) in July and August of 2020 during the FESST@MOL (Field Experiment on sub-mesoscale spatio-temporal variability at the Meteorological Observatory Lindenberg) 2020 campaign.  The triple Lidar setup was operated in a stare and in a step/stare mode at six heights between 90 and 500 m above ground, while the single Lidar was operated in a continuous scan Velocity-Azimuth-Display (VAD) mode with an azimuthal resolution of around 1.5 ° and a zenith angle of 55.5 °. Overall, both Lidar methods showed a good agreement for the whole study period for different averaging times and scan modes compared to the sonic anemometer. Additionally, we developed and show a new filtering approach based on a Median Absolute Deviation (MAD) filter for the virtual tower setup and compare it to a filtering approach based on a signal-to-noise ratio SNR threshold. The advantage of the MAD filter is that it is not based on a strict threshold but on the MAD of each 30-second period and can, therefore, better adapt to changing atmospheric conditions. In the comparison the MAD filter leads to a greater data availability while upholding similar comparability and bias values between the triple Lidar and sonic anemometer setups. Our results also show that a single Doppler Lidar is a viable method for measuring wind speed and direction with only small disadvantages, at least for measurement heights similar to our investigation and for comparable heterogeneous but flat landscapes.

How to cite: Wolz, K., Holst, C., Beyrich, F., and Mauder, M.: A new filtering approach for multiple Doppler Lidar setups, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15696, https://doi.org/10.5194/egusphere-egu23-15696, 2023.

EGU23-15942 | ECS | Posters on site | GI4.2

Study of the Atmospheric Boundary Layer and Land-Atmosphere Interaction with Lidars 

Syed Abbas, Andreas Behrendt, Florian Späth, Diego Lange, Osama Alnayef, and Volker Wulfmeyer

Investigating the dynamics of the atmospheric boundary layer (ABL) is essential for studies of air quality, the energy and water cycles and for the improvement of weather and climate models. During daytime in convective conditions, the convective boundary layer (CBL) is formed. Here, we present our approach of how to continuously study CBL characteristics with an improved algorithm including fuzzy logic. The Land-Atmosphere Feedback Observatory (LAFO) of University of Hohenheim consists of two Doppler lidars, a Doppler Cloud Radar, the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS), and Eddy covariance stations. These are excellent tools for observing high resolution atmospheric wind profiles, clouds and precipitation events, as well as thermodynamic profiles and surface fluxes. The data are collected at LAFO by operating continuously two Doppler lidars, one in vertical and one in six-beam scanning mode, to obtain vertical and horizontal wind profiles. Both Doppler lidars are operated with resolutions of 1 s and 30 m. The six-beam staring Doppler lidar is used for obtaining time series of turbulent kinetic energy (TKE), momentum flux, TKE dissipation rate and horizontal wind profiles statistics. The vertically staring Doppler lidar is used to compute statistics of higher-order moments of vertical wind fluctuations, the CBL height, and cloud base height. With these data, the land-atmosphere coupling processes and the associated nonlinear feedbacks are investigated as well as their impact on the turbulent structure of the CBL.

We will present analyses of two three-month periods covering different weather conditions: 1 May to 31 July 2021 and 2022.

How to cite: Abbas, S., Behrendt, A., Späth, F., Lange, D., Alnayef, O., and Wulfmeyer, V.: Study of the Atmospheric Boundary Layer and Land-Atmosphere Interaction with Lidars, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15942, https://doi.org/10.5194/egusphere-egu23-15942, 2023.

EGU23-16149 | ECS | Orals | GI4.2

Performance Simulation and Preliminary Measurements of a Raman Lidar for the Retrieval of CO2 Atmospheric Profiles 

Marco Di Paolantonio, Paolo Di Girolamo, Davide Dionisi, Annalisa Di Bernardino, Tatiana Di Iorio, Noemi Franco, Giovanni Giuliano, Anna Maria Iannarelli, Gian Luigi Liberti, and Donato Summa

Within the frame of the project CONCERNING (COmpact RamaN lidar for Atmospheric CO2 and ThERmodyNamic ProfilING), we investigated the feasibility and the limits of a ground-based Raman lidar system dedicated to the measurement of CO2 profiles. The performance of the lidar system was evaluated through a set of numerical simulations. The possibility of exploiting both CO2 Raman lines of the ν1:2ν2 resonance was explored. An accurate quantification of the contribution of the Raman O2 lines on the signal and other (e.g., aerosol, absorbing gases) disturbance sources was carried out. The signal integration over the vertical and over time required to reach a useful signal to noise ratio both in day-time and night-time needed for a quantitative analysis of carbon dioxide sources and sinks was evaluated. The above objectives were obtained developing an instrument simulator software consisting of a radiative transfer model able to simulate, in a spectrally resolved manner, all laser light interaction mechanisms with atmospheric constituents, a consistent background signal, and all the devices present in the considered Raman lidar experimental setup. The results indicate that the simulated lidar system, provided to have a low overlap height, could perform measurements on the low troposphere (<1 km) gradients (1-5 ppm) with sufficient precision both in day-time and night-time with an integration time of 1-3 h and a vertical resolution of 75 m. The selected Raman lidar setup is currently being tested and we aim to present preliminary results during the conference.

How to cite: Di Paolantonio, M., Di Girolamo, P., Dionisi, D., Di Bernardino, A., Di Iorio, T., Franco, N., Giuliano, G., Iannarelli, A. M., Liberti, G. L., and Summa, D.: Performance Simulation and Preliminary Measurements of a Raman Lidar for the Retrieval of CO2 Atmospheric Profiles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16149, https://doi.org/10.5194/egusphere-egu23-16149, 2023.

EGU23-16192 | ECS | Posters on site | GI4.2

Investigation of Boundary Layer Aerosol Processes with Turbulence-Resolving Lidar 

Osama Alnayef, Andreas Behrendt, Diego Lange, Florian Späth, Volker Wulfmeyer, and Syed Abbas

Our research focuses on the vertical transport of aerosol particles, and the properties of these aerosol particles in dependence on relative humidity. For this, we use the synergy of Raman and Doppler lidar systems operated during the Land-Atmosphere Feedback Experiment (LAFE) (see https://www.arm.gov/research/campaigns/sgp2017lafe).

We will present our first results of investigating the aerosol flux. For this, we use the aerosols backscatter coefficient and vertical wind velocity collected with Raman lidar and Doppler lidar.

The LAFE project was executed at the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) program in August 2017 in the USA.  In addition, data collected at the Land-Atmosphere Feedback Observatory (LAFO) at the University of Hohenheim, Germany is used. Results of the combined aerosol backscatter measurements with water-vapor and temperature lidar measurements to detail insights into the relative humidity dependencies on the growth of aerosols.

How to cite: Alnayef, O., Behrendt, A., Lange, D., Späth, F., Wulfmeyer, V., and Abbas, S.: Investigation of Boundary Layer Aerosol Processes with Turbulence-Resolving Lidar, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16192, https://doi.org/10.5194/egusphere-egu23-16192, 2023.

EGU23-16695 | ECS | Orals | GI4.2

Preliminary Studies and Performance Simulations in support of the mission “CALIGOLA” 

Noemi Franco, Paolo Di Girolamo, Donato Summa, Marco Di Paolantonio, and Davide Dionisi

CALIGOLA (Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land-Atmosphere System) is a mission funded by the Italian Space Agency (ASI), aimed at the development of a space-borne Raman Lidar. A Phase A study to assess the technological feasibility of the laser source and receiver system is currently underway at the Leonardo S.p.A., while scientific studies in support of the mission are conducted by the University of Basilicata. Scientific and technical studies are furthermore supported by other Italian institutions (CNR-ISMAR, CNR-IMAA), with NASA also having expressed an interest in contributing to the mission .

Mission objectives include the observation of the Earth atmosphere, surface (ocean and land). Among the atmospheric objectives, the characterization of the global scale distribution of natural and anthropogenic aerosols, their radiative properties and interactions with clouds, and the measurements of ocean color, suspended particulate matter and marine chlorophyll.

The expected performance of CALIGOLA has been assessed based on the application of an end-to-end lidar simulator. Specifically, sensitivity studies have been carried out to define the technical specifications for the laser source, the telescope, the optics of transceiver, the detectors and the acquisition system. Simulations reveal that the system can measure Rotational Raman echoes from nitrogen and oxygen molecules stimulated at the three lengths wavelength of 355, 532 and 1064 nm. Simulations also reveal that elastic signals are strong enough to meet the requirements under different environmental conditions. As reference signal, several options have been considered. Among others, a temperature-insensitive rotational Raman signal including rotational lines from nitrogen and oxygen molecules.

A careful analysis of different potential orbits is ongoing, with the goal to identify solutions which maximize performance and scientific impact of both atmospheric and oceanic measurements. Near noon-midnight equatorial crossing times are preferable on the ocean side for diel vertical migration and phytoplankton observations, but degrade significantly the performances of atmospheric measurements due to the high solar background. For this reason is essential to find an orbit in which the solar contribution is low enough to obtain acceptable atmospheric results and at the same time the oceanic measurements are far enough from the night-day transitions for as many days a year as possible to assure correct interpretation of phytoplankton physiology. To counterbalance the degraded signal performances also lower obit height are considered, as well as the use of polarized filters to reduce the amount of solar radiation. The estimated performances under different conditions and considering different orbits will be showed during the presentation.

How to cite: Franco, N., Di Girolamo, P., Summa, D., Di Paolantonio, M., and Dionisi, D.: Preliminary Studies and Performance Simulations in support of the mission “CALIGOLA”, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16695, https://doi.org/10.5194/egusphere-egu23-16695, 2023.

EGU23-370 | PICO | NH9.9

A climate based dengue early warning system for Pune, India 

Sophia Yacob and Roxy Mathew Koll

Dengue incidence has grown dramatically in recent decades, with about half of the world’s population now at risk. Climate plays a significant role in the incidence of dengue. However, the climate-dengue association needs to be clearly understood at regional levels due to the high spatial variability in weather conditions and the non-linear relationship between climate and dengue. The current study evaluates the impacts of weather on dengue mortality in the Pune district of India, for a 15-year period, from 2001 to 2015. To effectively resolve the complexity involved in the weather-dengue association, a new dengue metric is defined that includes temperature, relative humidity, and rainfall-dependent variables such as intraseasonal variability of monsoon (wet and dry spells), wet-week counts, flushing events, and weekly cumulative rains. We find that high dengue mortality years in Pune are comparatively dry, with fewer monsoon rains and flush events (rainfall > 150 mm), but they have more wet weeks and optimal humid days (days with relative humidity between 60–78%) than low dengue mortality years. These years also do not have heavy rains during the early monsoon days of June, and the temperatures mostly range between 27–35°C during the summer monsoon season (June–September).  Further, our analysis shows that dengue mortality over Pune occurs with a 2-5 months lag following the occurrence of favourable climatic conditions. Based on these weather-dengue associations, an early warning prediction model is built using the machine learning algorithm random forest regression. It provides a reasonable forecast accuracy with root mean square error (RMSE) = 1.01. To assess the future of dengue mortality over Pune under a global warming scenario, the dengue model is used in conjunction with climate change simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6). Future projections show that dengue mortality over Pune will increase in the future by up to 86 percent (relative to the reference period 1980–2014) by the end of the 21st century under the high emission scenario SSP5-8.5, primarily due to an increase in mean temperature (3°C increase relative to the reference period). The projected increase in dengue mortality due to climate change is a serious concern that necessitates effective prevention strategies and policy-making to control the disease spread.

How to cite: Yacob, S. and Mathew Koll, R.: A climate based dengue early warning system for Pune, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-370, https://doi.org/10.5194/egusphere-egu23-370, 2023.

EGU23-570 | ECS | PICO | NH9.9

Human health as an indicator of climate change. 

Moiz Usmani, Kyle Brumfield, Yusuf Jamal, Mayank Gangwar, Rita Colwell, and Antarpreet Jutla

The association of climatic conditions with human health outcomes has been known for ages; however, the impact of climate on infectious agents in disease transmission is still evolving. Climate change alters the regional weather impacting the emergence, distribution, and prevalence of infectious (vector-, water- or air-borne) diseases. Since the last few decades, the world has experienced an apparent increase in the emergence and re-emergence of infectious diseases, such as Middle East respiratory syndrome coronavirus (MERS-CoV); severe acute respiratory syndrome coronavirus (SARS-CoV); Ebola virus; Zika virus; and recently SARS-CoV-2. With many health agencies recommending handwashing, clean water access, and household cleaning as prevention measures, the threat to water security looms over the world population resulting in a significant public health burden under the lens of the emergence of infectious diseases. Under-resourced regions that lack adequate water supplies are on the verge of an enormous additional burden from such outbreaks. Thus, studying anthropogenic and naturogenic factors involved in the emergence of infectious diseases is crucial to managing and mitigating inequalities. This study aims to determine the impacts of climate variability on infectious diseases, namely water-, air-, and vector-borne diseases, and their association with the distribution and transmission of infectious agents. We also discuss the advancement of built infrastructure globally and its role as a mitigation or adaptation tool when coupled with an early warning system. Our study, therefore, will provide a climate-based platform to adapt and mitigate the impact of climatic variability on the transmission of infectious diseases and water insecurity.

How to cite: Usmani, M., Brumfield, K., Jamal, Y., Gangwar, M., Colwell, R., and Jutla, A.: Human health as an indicator of climate change., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-570, https://doi.org/10.5194/egusphere-egu23-570, 2023.

EGU23-593 | ECS | PICO | NH9.9

Variability and the odds of Total and Pathogenic Vibrio abundance in Chesapeake Bay 

Mayank Gangwar, Kyle Brumfield, Moiz Usmani, Yusuf Jamal, Antar Jutla, Anwar Huq, and Rita Colwell

Vibrio spp. is typically found in salty waters and is indigenous to coastal environments.  V. vulnificus and V. parahaemolyticus frequently causes food-borne and non-food-borne infections in the United States. Vibrio spp. is sensitive to changes in environmental conditions and various studies have explored their relationship with the environment and have identified water temperature as the strongest environmental predictor with salinity also affecting the abundance in some cases. It is unclear how additional environmental factors will affect intra-seasonal variance as well as the seasonal cycle. This study investigated the intra-seasonal variations in total and pathogenic V. parahaemolyticus and V. vulnificus organisms in oysters and surrounding waters from 2009 to 2012 at a few locations in the Chesapeake Bay. V. Vulnificus is always pathogenic, but it has been observed that there was greater sample-to-sample variability in pathogenic V. parahaemolyticus than in total V. parahaemolyticus. To determine the increase in the likelihood of vibrio presence when the value of a certain environmental parameter has changed, the odds ratio is examined for various values of environmental factors. The odds ratio that we employed measures the likelihood that the desired outcome would occur in samples with the vibrio in comparison to the likelihood that the desired outcome will occur in samples without the vibrio. This technique will give us the threshold value of the environmental variable above which the likelihood of vibrio spp. presence has increased drastically. With changing climate and environmental conditions, vibrio is posing increasing risks to human health. The findings of this study will demonstrate the effectiveness of the odds ratio technique in estimating the likelihood that vibrio abundance would increase when environmental conditions change, which can then be incorporated into prediction models to reduce the danger to the public's health.

How to cite: Gangwar, M., Brumfield, K., Usmani, M., Jamal, Y., Jutla, A., Huq, A., and Colwell, R.: Variability and the odds of Total and Pathogenic Vibrio abundance in Chesapeake Bay, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-593, https://doi.org/10.5194/egusphere-egu23-593, 2023.

Some studies suggest atmospheric particulate matter with diameters 2.5 micron and smaller (PM2.5) may possibly play a role in the transmission of influenza and influenza-like illness (ILI) symptoms.  Those studies were predominantly conducted under moderately to highly polluted outdoor atmospheres.  We conducted our study to extend the understanding to include a less polluted atmospheric environment.  A relationship between PM2.5 and ILI activity extended to include lightly to moderately polluted atmospheres could imply a comparatively more complicated transmission mechanism.  We obtained concurrent PM2.5 mass concentration data, meteorological data and reported Influenza and influenza-like illness (ILI) activity for the light to moderately polluted atmospheres over the Tucson, AZ region. We found no relation between PM2.5 mass concentration and ILI activity. There was an expected relation between ILI, activity, temperature, and relative humidity.  There was a possible relation between PM2.5 mass concentration anomalies and ILI activity. These results might be due to the small dataset size and to the technological limitations of the PM measurements. Further study is recommended since it would improve the understanding of ILI transmission and thereby improve ILI activity/outbreak forecasts and transmission model accuracies.

How to cite: DeFelice, PhD, T.: On the Understanding of the transmission route tied to Reported Influenza/Influenza-Like Illness Activity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2467, https://doi.org/10.5194/egusphere-egu23-2467, 2023.

EGU23-5923 | ECS | PICO | NH9.9

Impact of global warming and Greenland ice sheet melting on malaria and Rift Valley Fever 

Alizée Chemison, Dimitri Defrance, Gilles Ramstein, and Cyril Caminade

Mosquitoes are climate-sensitive disease vectors. They need an aquatic environment for the development of their immature stages (egg-larva-nymph). The presence and maintenance of these egg-laying sites depends on rainfall. The development period of mosquitoes is reduced when temperature increases, up to a lethal threshold. Global warming will impact vector’s distribution and the diseases they transmit. The last deglaciation taught us that the melting of the ice sheet is highly non-linear and can include acceleration phases corresponding to sea level rise of more than 4 m per century. In addition, glacial instabilities such as iceberg break-ups (Heinrich events) had significant impacts on the North Atlantic Ocean circulation, causing major global climate changes. These melting processes and their feedbacks on climate are not considered in current climate models and their detailed impacts on health have not yet been studied.

To simulate an accelerated partial melting of the Greenland ice sheet, a freshwater flux corresponding to a sea level rise of +1 and +3 m over a 50-year period is superimposed on the standard RCP8.5 radiative forcing scenario. These scenarios are then used as inputs for the IPSL-CM5A climate model to simulate global climate change for the 21st century. These simulations allow to explore the consequences of such melting on the distribution of two vector-borne diseases which affect the African continent: malaria and Rift Valley Fever (RVF).  Malaria is a parasitic disease that causes more than 200 million cases and more than 600,000 deaths annually worldwide. RVF causes deaths and high abortion rates in herds and poses health risks to humans through contact with infected blood. Former studies have already characterised the evolution of the global distribution of malaria according to standard RCPs. Using the same malaria mathematical models, we study the impact of an accelerated Greenland melting on simulated malaria transmission risk in Africa. Future malaria transmission risk decreases over the Sahel and increases over East African highlands. The decrease over the Sahel is stronger in our simulations with respect to the standard RCP8.5 scenario, while the increase over east Africa is more moderate. Malaria risk strongly increases over southern Africa due to a southern shift of the rain belt which is induced by Greenland ice sheet melting.,. For RVF, the disease model correctly simulates historical epidemics over Somalia, Kenya, Mauritania, Zambia and Senegal.  However, our results show the difficulty to validate continental scale models with available health data. It is essential to develop climate scenarios that consider climate tipping points. Assessing the impact of these tipping point scenarios and the associated uncertainties on critical sectors, such as public health, should be a future research priority.

 

How to cite: Chemison, A., Defrance, D., Ramstein, G., and Caminade, C.: Impact of global warming and Greenland ice sheet melting on malaria and Rift Valley Fever, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5923, https://doi.org/10.5194/egusphere-egu23-5923, 2023.

EGU23-6855 | PICO | NH9.9

An early warning decision support system for disease outbreaks in the livestock sector 

Paola Nassisi, Alessandro D'anca, Marco Mancini, Monia Santini, Marco Milanesi, Cinzia Caroli, Giovanni Aloisio, Giovanni Chillemi, Riccardo Valentini, Riccardo Negrini, and Paolo Ajmone Marsan

New climate regimes, variability and extreme events affect the livestock sector in many aspects, ranging from animal welfare, production, reproduction, diseases and their spread, feed quality and availability. Heat stress, especially when combined with excess or low humidity, exacerbates the perceived temperature or the drought conditions, respectively, increasing hazards for animals. Also, cold extremes, extraordinary windy conditions and altered radiation regimes are detrimental to both animals and fodder.

In this context, the EU-funded SEBASTIEN project aims to provide stakeholders with a Decision Support System (DSS) for more efficient and sustainable management, and consequent valuation, of the livestock sector in Italy. SEBASTIEN DSS will integrate GIS, environmental and biological variables to generate updated risk maps for livestock diseases and zoonoses and their spread, alerting about the expected occurrence of stressing conditions for animals due to abiotic and biotic factors.

The presence of parasites, vectors, and outbreaks will be combined with environmental data, gathered by spatially distributed meteorological and satellite monitoring, to detect conditions that can potentially favor or trigger the spread of related diseases. Sensor-based monitoring data will be integrated with the above information to determine ranges in animal parameters potentially associated with a higher risk of critical pathogen load or density of vectors potential carriers of diseases. Medium to long-term climate forecasts will support predicting possible shifts of favorable conditions that will open up new areas for parasites and pathogens. The vast amounts of data will be integrated and summarized into user-tailored information through a range of techniques, from empirical/statistical indicators to Machine Learning algorithms.

How to cite: Nassisi, P., D'anca, A., Mancini, M., Santini, M., Milanesi, M., Caroli, C., Aloisio, G., Chillemi, G., Valentini, R., Negrini, R., and Ajmone Marsan, P.: An early warning decision support system for disease outbreaks in the livestock sector, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6855, https://doi.org/10.5194/egusphere-egu23-6855, 2023.

EGU23-7652 | PICO | NH9.9

Forecasting the risk of vector-borne diseases at different time scales: an overview of the CLIMate SEnsitive DISease (CLIMSEDIS) Forecasting Tool project for the Horn of Africa 

Cyril Caminade, Andrew P. Morse, Eric M. Fevre, Siobhan Mor, Mathew Baylis, and Louise Kelly-Hope

Vector-borne diseases are transmitted by a range of arthropod insects that are climate sensitive. Arthropods are ectothermic; hence air temperature has a significant impact on their biting and development rates. In addition, higher temperatures shorten the extrinsic incubation period of pathogens, namely the time required for an insect vector to become infectious once it has been infected. Rainfall also creates suitable conditions for breeding sites. The latest IPCC-AR6 report unequivocally concluded that recent climate change already had an impact on the distribution of important human and animal diseases and their vectors. For example, dengue is now transmitted in temperate regions of Europe, and malaria vectors are now found at higher altitudes and latitudes in the Tropics. Different streams of climate forecasts, ranging from short range numerical weather prediction (NWP) models to seasonal forecasting systems, to future climate change ensembles can be used to forecast the risk posed by key vector-borne diseases at different time scales.  

This work will first introduce vector-borne disease forecasting system prototypes developed for different time scales and applications. Three examples will be presented; first a NWP driven model to forecast the risk of the animal disease Bluetongue in the UK, second the skill of the Liverpool malaria model simulations driven by seasonal forecasts in Botswana, and third the impact of RCP-SSP climate change scenarios on the risk posed by dengue and malaria at global scale. In addition, the use of mathematical disease models in anticipating disease risk will be presented, highlighting the limited uptake by policy makers. To bridge the academic/policy making gap, novel participatory approaches which include all actors need to be developed.

The CLIMate SEnsitive DISease Forecasting Tool (CLIMSEDIS) project aims to bridge that gap. The overall aim of CLIMSEDIS is to develop and build capacity in the use of an innovative user-friendly digital tool. CLIMSEDIS will allow end-user stakeholders to utilise forecasts and delineate sub-national risk of multiple climate sensitive diseases to inform timely and targeted intervention strategies in eight countries across the Horn of Africa. Disease prioritization exercise, scoping reviews and interactive workshops with stakeholders will be carried out. The final deliverable will consist in a web-based portal and a phone application that will be used, maintained, and developed further by key African regional partners. A presentation of the CLIMSEDIS project phases and its overall strategy will be presented. 

How to cite: Caminade, C., Morse, A. P., Fevre, E. M., Mor, S., Baylis, M., and Kelly-Hope, L.: Forecasting the risk of vector-borne diseases at different time scales: an overview of the CLIMate SEnsitive DISease (CLIMSEDIS) Forecasting Tool project for the Horn of Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7652, https://doi.org/10.5194/egusphere-egu23-7652, 2023.

EGU23-9509 | PICO | NH9.9 | Highlight

The first continental population dynamics model of the Asian tiger mosquito driven by climate and environment 

Kamil Erguler, Cedric Marsboom, George Zittis, Yiannis Proestos, George Christophides, Jos Lelieveld, and William Wint

The Asian tiger mosquito, Aedes albopictus, is an invasive vector species. It is capable of transmitting more than 20 arboviruses, and is responsible for chikungunya, dengue, and zika transmission. Urbanisation, globalisation, and climate change are expected to expand its habitable range and increase the global vector-borne disease burden in the coming decades. To plan effective control strategies, early-warning and decision support systems are urgently needed.

We developed a climate- and environment-driven population dynamics model of Aedes albopictus with extensive geospatial applicability. The foundation of the model is the age- and stage-structured population dynamics model of Erguler et al. (2016)1. We replaced its rainfall- and human population density-dependent breeding site component with a large-scale mechanistic ecological model. The extension effectively created an ecological-dynamic model hybrid capable of representing niche dependence and response to changing environmental and meteorological conditions over time and under various land characteristics. To the best of our knowledge, this is the first spatiotemporal mechanistic model developed with a capacity to learn from both vector presence and longitudinal abundance data.

We calibrated the model with an extensive field surveillance dataset by combining the data collected through the AIMSurv project, the first pan-European harmonized surveillance of Aedes invasive mosquito species of relevance for human vector-borne diseases, and the global surveillance records available from VectorBase MapVEu. By deriving the model structure and environmental dependencies from the literature and allowing a complete re-configuration of the entire parameter set, we asserted the biological relevance and geospatial applicability, which extends over Europe and North America.

We corroborate that temperate northern territories are becoming increasingly suitable for Aedes albopictus establishment, while neighbouring southern territories become less suitable, as climate continues to change. We identify potential hotspots over Europe and North America by employing the combination of vector abundance and activity as a proxy to pathogen transmission risk.  By investigating routes of introduction to new territories, we demonstrate the significant role of dynamic environmental suitability in the highly efficient spread of this invasive mosquito.

The model is scheduled for integration into the "Climate-driven vector-borne disease risk assessment platform", to predict habitat suitability and dynamic abundance of important disease vectors and the risk of diseases transmitted by them at any location and time up to the end of the century. With the continental model of Aedes albopictus, the platform will reliably inform public health professionals and policy makers and contribute to the global strategies of integrated vector management.

1 Erguler K, Smith-Unna SE, Waldock J, Proestos Y, Christophides GK, Lelieveld J, Parham PE. Large-scale modelling of the environmentally-driven population dynamics of temperate Aedes albopictus (Skuse). PloS one. 2016 Feb 12;11(2):e0149282.

How to cite: Erguler, K., Marsboom, C., Zittis, G., Proestos, Y., Christophides, G., Lelieveld, J., and Wint, W.: The first continental population dynamics model of the Asian tiger mosquito driven by climate and environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9509, https://doi.org/10.5194/egusphere-egu23-9509, 2023.

Vesicular stomatitis (VS) is a multi-vector arboviral disease that affects livestock and has a significant impact on agriculture in both the US and Mexico. Biting midges (Culicoides species) are known vectors of VS. Presence-only species distribution models (SDMs) provide a powerful and versatile tool for estimating both the habitat suitability of biting midges and the distribution of VS, the disease they spread. Such models can improve our understanding of Culicoides ecology, provide opportunities for more efficient VS surveillance and mitigation, and help determine geographical areas where VS is endemic or vulnerable to potential future transmission.

Here, we discuss two case studies related to modeling the distribution of VS and its insect vector. The first focused on predicting the habitat suitability of biting midges, including C. sonorensis and its close relatives (C. variipennis, C. albertensis, and C. occidentalis), based on species presence records collected in the past hundred years from various sources. The second study involved directly estimating the distribution of VS in Mexico, where we used occurrence data in the form of confirmed VS cases in livestock from 2005-2020 in historically endemic regions of Mexico.

SDMs are typically generated using temporally static input data. However, we improved the accuracy of our predictions by applying the Maxent algorithm to time-specific input data, creating dynamic species distribution models and habitat suitability maps. For both case studies, a robust dynamic Maxent distribution modeling workflow was implemented using temporally matched occurrence and environmental data that were carefully selected in collaboration with domain experts.

How to cite: Veron, M.: Dynamic distribution modeling of arboviral vesicular stomatitis and its vector, the biting midge (Culicoides spp.): two case studies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10475, https://doi.org/10.5194/egusphere-egu23-10475, 2023.

EGU23-12513 | PICO | NH9.9 | Highlight

Links between weather and seasonal influenza epidemics 

Jan Kyselý, Hana Hanzlíková, Aleš Urban, Eva Plavcová, and Jan Kynčl

Links between weather variability, influenza/acute respiratory infections (ARI), and human health are extremely complex in the cold season, and their explanation remains uncertain. It is not clear whether the winter mortality peak is related rather to low ambient temperatures or ARI, and how weather variability may modify transmission patterns of ARI and related mortality. This study investigates links between weather characteristics, influenza/ARI epidemics and all-cause mortality in the population of the Czech Republic (Central Europe), by employing long-term epidemiological and meteorological datasets over the 1982/83 to 2019/20 epidemics seasons. The links are analysed with respect to the predominant type of influenza virus in each season (A/H3N2 and A/H1N1 subtypes, and B lineages). We focus on i) identification of meteorological conditions associated with epidemics, ii) how timing of the epidemics and their magnitude are linked to weather characteristics, and iii) whether there are synergetic effects of cold weather and epidemics on the mortality impacts. Preliminary results suggest that high excess mortality during influenza epidemics was associated with low temperatures while above-average temperatures were linked to lower morbidity and mortality impacts. The role of other meteorological characteristics is less clear. Understanding weather conditions that increase the transmission and survival of influenza and respiratory viruses could help to better inform at-risk populations, implement preventive measures, and mitigate the negative impacts of influenza and ARI.

How to cite: Kyselý, J., Hanzlíková, H., Urban, A., Plavcová, E., and Kynčl, J.: Links between weather and seasonal influenza epidemics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12513, https://doi.org/10.5194/egusphere-egu23-12513, 2023.

EGU23-13298 | ECS | PICO | NH9.9

Prognostic epidemiological indices and the fate of ongoing infectious disease outbreaks 

Cristiano Trevisin and Andrea Rinaldo

Prognostic indices, such as the reproduction number or the epidemicity index, help assess the fate of ongoing infectious disease epidemics. While the first is of established importance, the latter focuses on the instantaneous reactivity of the infective compartment to new flare-ups. When subthreshold values of such indices apply (respectively, below the unity for the first and below zero for the latter), they warrant long-term disease-free and unreactive epidemiological conditions. 

These prognostic indicators benefit policymakers during the assessment and implementation of containment measures to reduce the disease burden. They may depend on an array of factors, including environmental forcings and the effect of containment measures on disease transmission.

We showcase a possible implementation of such prognostic indices with reference to the disastrous 2010-2019 Haiti cholera outbreak. To this end, we use a compartmental model that considers rainfalls as an environmental forcing and societal actions tackling the disease's spread. We thus test several scenarios considering a different deployment of intervention measures and we evaluate the outcome of the evolution of the prognostic indices and the epidemiological trajectory in the Haitian regions. We find that subthreshold values of these indices lead to faster waning-disease conditions.
As these indices can recap diverse epidemiological signatures induced by the spatial and temporal deployment of containment measures and potentially by evolving environmental forcings, their implementation could enable policymakers to strategically adopt containment measures in response to both evolving epidemiological and climate forcings.

How to cite: Trevisin, C. and Rinaldo, A.: Prognostic epidemiological indices and the fate of ongoing infectious disease outbreaks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13298, https://doi.org/10.5194/egusphere-egu23-13298, 2023.

EGU23-14214 | ECS | PICO | NH9.9

A Deep Early Warning System of Mosquito Borne Diseases using Earth Observational Data 

Argyro Tsantalidou, Konstantinos Tsaprailis, George Arvanitakis, Diletta Fornasiero, Daniel Wohlgemuth, Dusan Petric, and Charalampos Kontoes

Mosquito-borne diseases (MBDs) have been spreading across many countries including Europe over the past two decades, causing thousands of deaths annually. They are transmitted through the bites of infectious mosquitoes. Environmental, meteorological and other spatio-temporally variables affect the mosquito abundance (MA), and thus affect the circulation of the MBDs in the community. So an early warning system of MA based on these parameters could serve as a warning for the upcoming MBDs incidence. 

We propose Deep-MAMOTH, a data driven, generic and accurate early warning system for predicting MA in the upcoming period, based on earth observational (EO) environmental data and optionally in-situ entomological data. Deep-MAMOTH can be easily replicated and applied to multiple areas of interest without any special parametrization.

The Deep-MAMOTH pipeline collects EO information from various data sources (temperature, rainfall, vegetation, distance from coast, elevation, etc.) and in-situ entomological data for each area of interest. Then, there is a feature extraction phase that combines the previous collected information to more complex features, and finally this data is fed into a Deep Neural Network responsible to capture the relationship between the above mentioned features and the MA, delivering a MA risk class ordered from 0 to 9 for the upcoming period (e.g. 15 days). The pipeline provides a standardized way to predict MA without depending on the area of interest or the mosquito genus and can be modified to predict the actual MA instead of a risk class. However, risk classes help to better propagate the severity of the situation.

Two versions of Deep-MAMOTH were implemented, the first one is using recently collected entomological information in order to produce predictions (i.e. mosquitoes collected 1 week ago). The other version works when there is no recently collected entomological information for the area of interest. The latter version is expected to perform worse than the first one, but gives us the capability to produce predictions anywhere on earth without the need of recently collected entomological data. 

We applied Deep-MAMOTH in Veneto (Italy), in Upper Rhine region (Germany), and the Vojvodina region (Serbia) regarding the Culex spp. genus mosquito. The results are promising as Deep-MAMOTH in Italy achieves a mean absolute error (MAE) of 1.27 classes with the percentage of predictions that deviate at most 3 classes (e3) from the actual one reaching up to 95%. In Serbia MAE is 1.77 classes, with e3 equal to 88% and finally for Germany MAE is 0.92 classes and e3 equal to 94%.  

It’s worth mentioning that prediction performance in the version of Deep-MAMOTH without using entomological information remains promising. MAE in Italy was increased only by 0.02 and in Germany by 0.1, with e3 remaining at the same level in both cases, while in Serbia MAE increased by 0.2 with e3 decreasing by 8%. We conclude that the prediction of MA from EO data can be accurate with or without recently collected entomological data.

Acknowledgment:This research has been co-financed by the ERD Fund of the EU and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, RESEARCH-CREATE-INNOVATE(project code:T2EDK-02070)

How to cite: Tsantalidou, A., Tsaprailis, K., Arvanitakis, G., Fornasiero, D., Wohlgemuth, D., Petric, D., and Kontoes, C.: A Deep Early Warning System of Mosquito Borne Diseases using Earth Observational Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14214, https://doi.org/10.5194/egusphere-egu23-14214, 2023.

EGU23-15398 | PICO | NH9.9

Understanding the Area of Applicability of Data Driven Mosquito Abundance Prediction Models 

Theoktisti Makridou, George Arvanitakis, Konstantinos Tsaprailis, Diletta Fornasiero, and Charalampos Kontoes

An Early Warning System for mosquito abundance is a valuable tool that can alert authorities for potential outbreaks of mosquito populations in a given area for the upcoming period. This information is used to take mitigation actions in order to avoid spread of vector borne diseases such as West-Nile Virus, Malaria, Zika etc. A promising direction of those systems today aims to predict the upcoming mosquito population by following a data driven approach and taking advantage of machine learning (ML) algorithms. The ML algorithms are trained on a limited set of point level data that include the environmental, geomorphological, climatic information and historical in-situ measurements of mosquito population for specific latitude and longitude coordinates. Goal of the ML algorithms is to learn the patents that connect the characteristics (features) of a given area (temperature, humidity, NDVI, rainfall, latitude, longitude, etc) with the upcoming mosquito population.

 

Once the in-situ entomological data are expensive to be collected and limited, one of the key challenge of the aforementioned approach is to understand where those models can generalize with an acceptable accuracy in order to be re-used in areas that prior entomological information do not exist or in other words to understand the area of applicability of those models.

 

In this study we analyze the performance of ML algorithms that have been trained in specific areas and applied to “unseen” areas. Our analysis aims to understand the characteristics of the cases where the algorithms manage to generalize compared with the ones where the performance is poor. Our scope is to establish a systematic approach for determining the area of applicability of the models, thus, to obtain a prior knowledge regarding the areas that we expect models to generalize properly and the areas the predictions of the models are not trustworthy.

 

Our work relied on historical data of Culex pipiens mosquitoes (West Nile virus) collected in the Veneto region of Italy for the decade 2011-2021 and satellite Earth Observation data. For ML regressor we used a feedforward Neural Network with typical mean square error cost function. Initially we conclude that the typical euclidian distance between the coordinates of the trained area and the unseen data is not an informative metric about the model’s area of applicability. Instead, we propose a metric that calculates the distance between the known and the unknown points in the feature space (environmental, geomorphological etc.) and also takes into account the feature importance of trained Neural Network using the SHAP values.

 

The results showed that our proposed metric is informative regarding where the model is expected to have more accurate predictions and manage to capture the cases where the generalization will be poor. This information is useful both to judge if the predictions of a model are trustworthy and also to understand for which areas our prior information is not sufficient and to take actions in future network planning.

How to cite: Makridou, T., Arvanitakis, G., Tsaprailis, K., Fornasiero, D., and Kontoes, C.: Understanding the Area of Applicability of Data Driven Mosquito Abundance Prediction Models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15398, https://doi.org/10.5194/egusphere-egu23-15398, 2023.

EGU23-17226 | ECS | PICO | NH9.9 | Highlight

Identification of thresholds on Sea surface temperature and coastal chlorophyll for understanding environmental suitability of V. vulnificus incidence 

Yusuf Jamal, Moiz Usmani, Mayank Gangwar, and Antarpreet Jutla

Vibrio spp. are pathogenic bacteria native to warm and brackish water. Vibriosis- the disease caused by these pathogens in humans accounts for around 80000 illnesses and 100 deaths annually in the United States. Of all the species, V. vulnificus has the highest mortality rate of all seafood-borne pathogens in the United States. In this context, understanding the environmental conditions that lead to increased V. vulnificus growth and spread can aid in the development of early warning systems and targeted prevention strategies. Besides sea surface temperature (SST), biotic parameters like coastal chlorophyll are also determined to affect V. vulnificus incidence in humans locally. However, the precise role of coastal chlorophyll as a potential confounding variable is understudied. Moreover, the spatial scale to which the data for environmental variables could be obtained also poses characterization constraints for researchers since the commonly employed in-situ sampling-based methods usually work with discrete locations covering a small area. The present study uses the odds ratio analysis to determine SST and chlorophyll-a threshold values critical to V. vulnificus incidence. The analysis reveals a definite positive relationship between remotely derived environmental variables and the odds of V. vulnificus incidence, where a specific statistical value of SST and chlorophyll-a marks a clear distinction between low and high odds of V. vulnificus incidence. This finding translates into a consistent pattern when checked for counties of coastal Florida. We anticipate our methodology to help distinguish between high and low-risk conditions, enabling public health workers to take proactive measures to protect the health and well-being of the public.

How to cite: Jamal, Y., Usmani, M., Gangwar, M., and Jutla, A.: Identification of thresholds on Sea surface temperature and coastal chlorophyll for understanding environmental suitability of V. vulnificus incidence, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17226, https://doi.org/10.5194/egusphere-egu23-17226, 2023.

GI5 – Earth surface and subsurface methods of investigation

EGU23-675 | ECS | Posters on site | GM2.2

Can we monitor shallow groundwater using ambient seismic noise? 

Antonia Kiel, René Steinmann, Eric Larose, and Céline Hadziioannou

Nowadays, the majority of detailed information about groundwater is acquired by wells that provide limited insight in time and especially space. Therefore, it would be interesting to monitor groundwater by continuously measuring seismic velocity changes in the subsurface. The shallow soil is affected by environmental influences like temperature, rainfall or drought, which in turn changes the seismic velocity in the subsurface.

In this study, we use three-component seismometers, which are placed next to an in-situ measurement station of soil conditions (moisture and temperature at different depths) and a meteorological station in the city of Hamburg, Germany. We investigate the sensitivity of high-frequency (> 1 Hz) seismic waves with an anthropogenic origin to ground moisture changes in the uppermost layers of soil. To monitor velocity changes, Passive Image Interferometry is applied. Using the three-component data, we are able to retrieve Rayleigh and Love waves. Relative velocity changes are retrieved using the stretching method. A comparison of seasonal seismic velocity changes and environmental changes shows a positive correlation between velocity and temperature, as well as a negative correlation between velocity and groundwater content. Freezing events are exceptions, as they cause relative velocity increases twice as high as seasonal changes.

The aim of this work is to eliminate temperature effects to work towards inferring water content directly from seismic velocity changes. To eliminate the contribution of temperature, its relation to seismic velocity changes and water content is quantified using regression. Since the relative velocity change is influenced by both temperature and water content, a time period of stable water content is used to quantify the relation between velocity change and temperature. As a result, the residual relative velocity change reproduces the residual water content.

How to cite: Kiel, A., Steinmann, R., Larose, E., and Hadziioannou, C.: Can we monitor shallow groundwater using ambient seismic noise?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-675, https://doi.org/10.5194/egusphere-egu23-675, 2023.

EGU23-714 | ECS | Orals | GM2.2

Seismic imaging of the submarine Kolumbo Volcanic Chain reveals its volcano-tectonic evolution and link to Santorini 

Jonas Preine, Christian Hübscher, Jens Karstens, Gareth Crutchley, and Paraskevi Nomikou

Located in the southern Aegean Sea, the Christiana-Santorini-Kolumbo volcanic field is one of the most hazardous volcanic regions in the world and lies in an active continental rift zone. Northeast of Santorini lies the Kolumbo Volcanic Chain (KVC), which comprises more than 20 submarine volcanic cones, with the Kolumbo volcano representing the most prominent edifice of this chain. However, due to their inaccessibility, little is known about the spatio-temporal evolution and tectonic control of these submarine volcanoes and their link to the volcanic plumbing system of Santorini. We will present multichannel reflection seismic data that allow us to image the internal architecture of the KVC and study its link to Santorini. Using a seismostratigraphic framework, we are able to show the KVC evolved during two episodes, which initiated at approx. 1 Ma with the formation of mainly effusive volcanic edifices along a NE-SW trending zone. Most of the cones of the second episode represent submarine pumice cones that were formed by submarine explosive eruptions between 0.7 and 0.3 Ma and partly developed on top of volcanic edifices from the first episode. Our data show that two prominent normal faults underlie the KVC, indicating a direct link between tectonics and volcanism. In addition, we are able to reveal several buried volcanic centers and a distinct volcanic ridge connecting the KVC with Santorini, suggesting a connection between the two volcanic centers in the past. We argue that this connection was interrupted by a major tectonic event and, as a result, the two volcanic systems now have separate, largely independent plumbing systems despite their proximity.

How to cite: Preine, J., Hübscher, C., Karstens, J., Crutchley, G., and Nomikou, P.: Seismic imaging of the submarine Kolumbo Volcanic Chain reveals its volcano-tectonic evolution and link to Santorini, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-714, https://doi.org/10.5194/egusphere-egu23-714, 2023.

EGU23-900 | ECS | Posters on site | GM2.2

Optimising passive seismic investigations of the ice-bedrock interface zone for the great ice sheets 

Ian Kelly, Anya Reading, Tobias Staal, and Andrew Bassom

The need to better predict how the great ice sheets will respond to continued atmospheric and ocean warming is paramount. Ice deformation and mechanisms for ice sliding across the bedrock underneath are both key considerations. Constraints of this critical ice-bedrock interface zone, particularly over extensive inland areas of Antarctica and Greenland, remain a major hurdle in ice-sheet modeling and estimations of future sea level rise.

Passive seismology offers a logistically-efficient avenue for such investigations, with improvements in sensor technologies, autonomous power solutions and telemetry systems encouraging the deployment of temporary arrays for subglacial mapping and real-time monitoring. Previous experiments have demonstrated the potential of techniques such as receiver functions, horizontal-to-vertical spectral ratios (HVSR) and ambient noise interferometry for characterising the depth and nature of the ice-bedrock zone. This research looks to fully explore the sensitivity range of available passive seismic methods for the ice-bedrock interface, with a view towards optimising data collection and array geometries for future applications. In this contribution, we present an optimised workflow making use of HVSR analysis and the spatial autocorrelation (SPAC) technique using numerical simulations and field data collected from East Antarctica. The results from this study provide a benchmark to guide future deployments in the polar regions.

How to cite: Kelly, I., Reading, A., Staal, T., and Bassom, A.: Optimising passive seismic investigations of the ice-bedrock interface zone for the great ice sheets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-900, https://doi.org/10.5194/egusphere-egu23-900, 2023.

Karst is a landscape with distinctive hydrology and landforms that arise when the underlying rock is soluble. Locating the flowing conduits and pathways in karst is important in terms of water resource management, groundwater flooding, geotechnical and engineering projects. Understanding flow pathways is particularly important for road and railway construction, so as not to adversely affect hydrological networks, in particular those associated with Turloughs.

The aim of this study was to develop methods for directly detecting energetic groundwater flow in sub-surface conduits through passive seismic applications, by detecting the small ground vibrations (seismic microtremor) that flowing water in the sub-surface may generate. This is in contrast to the current ‘traditional’ approach of attempting to actively image the conduits using geophysical and other methods, in order to determine the geometry of flow paths. The imagery of conduits in karst is a very difficult problem and determining if they contain flowing structures is also a very significant challenge using traditional methods, which is the motivation for developing a new approach to the problem.

We undertook experiments at two sites on karst in Ireland; one gently-sloping shallow conduit and one relatively deep and complex-structured conduit. We chose these sites as the caves had previously been dived and we had access to the shapefiles of these caves to ground-truth our findings.

We observed that subterranean flow-related micro-tremor in karst appears as persistent frequency bands on the spectrograms that vary with time and seismic station location with respect to the conduit. This persistent frequency is different than the soil resonating frequency and relates to the subterranean water flow in the conduits. Application of an Amplitude Location Method (ALM)  clearly delineated the conduit as the source of the micro-tremor.

We also conducted an active Airgun experiment at the second site to locate the conduit by tracking a pressure wave, using two arrays of surface seismic stations, as it propagated into the conduit. This combination of detecting and locating seismic microtremor generated by water flow in the conduits and the use of seismic array analysis to track active Airgun source pressure waves propagating at depth in conduits offers a new tool kit for karst hydrology determination. In the next step, we will assess the applicability of Distributed Acoustic Sensing (DAS) using fiber optic cables as sensors for detecting sub-surface water flow, where we expect unrivaled spatial resolution of the flow-induced seismic wavefield. Such a study would be the first attempt to fill the current gap regarding an understanding of karst groundwater dynamics along the entire conduit pathway, at an exceptionally high spatial scale.

How to cite: Karbala Ali, H., Bean, C. J., and Chalari, A.: Detection and source location of the groundwater-induced seismic signal in karst using a combination of passive and active seismic approaches, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1046, https://doi.org/10.5194/egusphere-egu23-1046, 2023.

EGU23-1601 | ECS | Orals | GM2.2

Groundwater Heights Prediction from Seismic Waves with Machine Learning 

Anthony Abi Nader, Julie Albaric, Marc Steinmann, Clément Hibert, Jean-Philippe Malet, Benjamin Pohl, and Christian Sue

Unlike surface water reservoirs, that can be easily quantified and monitored, underground conduits in karst systems are often inaccessible, hence challenging to monitor. Seismic noise analysis was proved to be a reliable tool to monitor ground water storage in a fractured rock aquifer (Lecocq et al. 2017). In underground karstic environments, seismic noise monitoring was able to detect hydrological cycles and monitor the groundwater-content variations (Almagro Vidal et al. 2021). The following approach relies on coupling passive seismic wavefield with hydrological data in a machine learning algorithm in order to monitor underground water heights. The studied site is the Fourbanne karst aquifer (Jura Mountains, Eastern France, Jurassic Karst observatory). The underground conduit is accessible through a drilled shaft and instrumented by two 3-component seismological stations, one located underground and the other one at the surface, and a water height probe. We applied a new approach based on the machine learning random forest (RF) algorithm and continuous seismic records (Hibert et al., 2017), to find characteristic signals to predict the underground river water height. The method consists on the computation on a sliding window of seismic signal features (waveform, spectral and spectrogram features) and using the corresponding water height at the same time window to train the algorithm, and then apply it on new data. The RF algorithm is capable of accurately detecting flooding periods and reproduce the groundwater heights with an efficiency exceeding 95% and 53% using the Nash-Sutcliffe criterion for the seismic stations located in the underground conduit and at the surface respectively. The obtained results are a first promising outcome for the remote study of water circulation in karst aquifers using seismic noise.

How to cite: Abi Nader, A., Albaric, J., Steinmann, M., Hibert, C., Malet, J.-P., Pohl, B., and Sue, C.: Groundwater Heights Prediction from Seismic Waves with Machine Learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1601, https://doi.org/10.5194/egusphere-egu23-1601, 2023.

EGU23-1677 | ECS | Posters virtual | GM2.2

Event Relations and Sources of Icequakes at the Grounding Line of Rutford Ice Stream, West Antarctica 

Ian Lee, Sridhar Anandakrishnan, Richard Alley, Alex Brisbourne, and Andrew Smith

Basal icequakes are generated as a glacier slides over its underlying bedrock, and the stick-slip motion of constant loading and unloading releases shear stresses that produce these very small magnitude (ML < 0) glacial microseisms. Detecting and locating nucleation of these fine-scale icequakes can provide highly useful insights into the deformation processes occurring at the bed and consequently the mechanisms governing glacier flow. We present icequake data derived from a seismic array installed at the grounding line of the Rutford Ice Stream in West Antarctica by Penn State University and the British Antarctic Survey during the 2018/19 austral summer. The region’s natural source seismicity was first processed using the earthquake detection and location software QuakeMigrate and the events were relatively relocated using HypoDD/GrowClust. We then clustered the events into sticky spot clusters using the unsupervised clustering algorithm DBSCAN, and finally from the clusters we selected “model” waveforms to perform template matching on the original seismic traces to create methodically comprehensive high-resolution icequake catalogs at the grounding line of Rutford. We present our methodology including the complete processing pipeline (supplemented by developed supporting open-source scripts) along with key tuning parameters, and describe how our catalogs were used to resolve glacier sliding patterns and key topographical features and characteristics of the bed like sticky spots. We additionally explore the effects of tidal modulation and Rutford ice flow motion on icequake occurrences. Our seismic traces primarily contain icequake signals that derive from stick-slip sliding, but also unique waveforms that might be derived from crevassing and teleseisms that we will also explore. Our results show that stick-slip basal icequakes and these resultant icequake catalogs are valuable data-rich resources that help improve our understanding of glacier flow dynamics and will be important toward improving glacier flow models used for constraining global mean sea level rise.

How to cite: Lee, I., Anandakrishnan, S., Alley, R., Brisbourne, A., and Smith, A.: Event Relations and Sources of Icequakes at the Grounding Line of Rutford Ice Stream, West Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1677, https://doi.org/10.5194/egusphere-egu23-1677, 2023.

EGU23-2707 | Orals | GM2.2

Thermo-Acousto-Elasticity (TAE) of natural rock cliffs: toward better understanding and monitoring damage and erosion process 

Eric Larose, Antoine Guillemot, Laurent Baillet, and Pierre Bottelin

Rainfalls and freeze-thaw cycles are well known to largely contribute to rock slopes erosion, including chemical processes (dissolution, alteration) together with mechanical action (stress change in fractures due to water freezing). The role of heat waves and thermal cycles is less studied in dry conditions. Here we present a thermo-acousto-elastic (TAE) model for rock volumes exposed to cyclic (daily to seasonal) thermal forcings, as an application of environmental seismology (1).

In our model, we assume that the rock temperature is constant at depth (a few meters in general), and that the free surface is exposed to heat fluxes (radiative and convective ones). In practice, these heat fluxes can be respectively derived from solar radiation normal to the rock surface and from the air temperature, both parameters are easily measured in the field. We then develop a numerical model based on a) thermal diffusion (heat propagation in the rock in 2D or 3D models, including complex geometries as cracks, rock columns…), b) thermal expansion relating temperature to strain, and c) acousto-elasticity relating the elastic parameters to the state of stress, (2). Such a model is run, for example, with COMSOL Multiphysics with a finite element scheme. We end up with a 2D or 3D numerical model of stress and deformation of the rock volume evolving over time ranging from sub-daily to yearly time scales.

As an application we test this model on various rock columns and observe that the developed model properly reproduces field observations, including daily and seasonal cycles: the natural resonance frequency of the rock column, a proxy for its rigidity, increases with increasing heat flux (3) and the rear crack closes up. As a result of fitting our numerical model to natural rock columns, we can evaluate the acousto-elastic constant that relates the rigidity to the state of stress, a parameter that is known to mainly depend on the state of damage of the material, opening the route for rockfall risk assessment, monitoring and early warning systems. Our model also allows to shed new light into fatigue and cyclic damage process of rock slopes and cliffs, a key to rock erosion.

 

References:

  • (1) Guillemot, L. Baillet, E. Larose, P. Bottelin : Changes in resonance frequency of rock columns due to thermoelastic effects on a daily scale : observations, modeling and insights to improve monitoring, Geoph. J. Int. 231, 894-906 (2022).
  • (2) Larose, E. & Hall, S.: Monitoring stress related velocity variation in concrete with a 2.10−5 relative resolution using diffuse ultrasound, J. acoust. Soc. Am., 125, 1853–1856 (2009).
  • (3) Bottelin, P., Levy, C., Baillet, L., Jongmans, D. & Gueguen, P.: Modal and thermal analysis of Les Arches unstable rock column (Vercors massif, French Alps), Geophys. J. Int., 194, 849–858 (2013).

How to cite: Larose, E., Guillemot, A., Baillet, L., and Bottelin, P.: Thermo-Acousto-Elasticity (TAE) of natural rock cliffs: toward better understanding and monitoring damage and erosion process, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2707, https://doi.org/10.5194/egusphere-egu23-2707, 2023.

EGU23-3010 | Posters on site | GM2.2

Identification of bedrock depth and blind fault by HVSR analysis along two profiles in Pohang, South Korea considering optimal weather environment and seismometer burial depth 

Su Young Kang, Kwang-Hee Kim, Doyoung Kim, Byungmin Kim, Lanbo Liu, and Youngcheol Lee

Many deep faults do not reach the earth’s surface and thus are not recognized. Such faults are rarely mapped by standard surface geological mapping. This seriously hinders seismic risk mitigation efforts. In this study, we applied the horizontal-to-vertical spectral ratio (HVSR) method to identify blind faults invisible at the surface. Despite its simplicity and low-cost implementation, we noticed that HVSR results were unstable using data collected by exposed seismometers or under higher wind speeds. Therefore, three-component seismic sensors for ambient noise observations were buried at different depths to examine the effects of ground coupling, wind speeds, and precipitations. Results from a series of field tests under diverse conditions guided us to establish data selection criteria. The first required condition is that seismic sensors should be buried (>0.3 meters) to secure ground coupling and to avoid any direct exposure to wind or precipitations. The other is that data should be collected at low wind speeds (< 3 m/s). The requirements were applied to ambient noise data along two profiles traversing unnamed and inferred faults in Pohang, Korea. We initially estimated the resonance frequencies for each site, which varied from 0.41 to 2.52 Hz. They were then converted to bedrock depths using an empirical relationship between the resonance frequency and depth to bedrock observed at boreholes in the area. The estimated depths to bedrock along profiles ranged from 8.0 to -472.0 meters. The resulting depth profiles show significant lateral variations in the bedrock depth, including the one near the Gokgang fault at which the thickness to the major impedance contrasts decreased from 196 to 20 meters. Sudden variations were also observed at unexpected locations along the profile. We examined the details, especially for sites of apparent changes in bedrock depth, and compared their characteristics with other geophysical studies, including Vs30, MASW, Bouguer gravity anomaly, and adjacent stations correlation. Their results are all well correlated to each other and indicate rapid changes in bedrock depth. We attribute the rapid changes to vertical displacements by ancient faulting activity.

How to cite: Kang, S. Y., Kim, K.-H., Kim, D., Kim, B., Liu, L., and Lee, Y.: Identification of bedrock depth and blind fault by HVSR analysis along two profiles in Pohang, South Korea considering optimal weather environment and seismometer burial depth, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3010, https://doi.org/10.5194/egusphere-egu23-3010, 2023.

EGU23-3593 | Posters on site | GM2.2

Meteo-Seismology: Harvesting the Seismic Signals of Weather Dynamics in the Critical Zone 

Michael Dietze, Christian Mohr, Violeta A. Tolorza, Benjamin Sotomayor, and Erwin Gonzalez

Weather conditions are an important driver of Earth surface dynamics, such as gravitational mass wasting, flood propagation, biological activity events and physical interactions within the critical zone. While there are dedicated sensors to capture meteorological parameters, these sensors are comparably expensive, have a small spatial footprint and often lack the temporal resolution needed to constrain high frequency meteorological dynamics. We introduce the concept of meteo-seismology, i.e. the measurement of first-order ground motion signatures of weather conditions by decisively installed seismic sensors. While meteorological manifestations are generally considered seismic noise and it may seem odd to use seismometers instead of weather stations, geophysical sensors circumvent or complement the above caveats and add further important data to a comprehensive picture of the rapidly changing state of the atmosphere and its interaction with the landscape we live in. Based on examples from prototype forested landscapes in Central Europe and Chilean Patagonia, we demonstrate how seismic stations can be used to infer properties of the pressure and wind field and its coupling to the biosphere, constrain rain intensity and drop properties, yield temperature proxies and their propagation into the ground, and survey ground moisture trends and discharge patterns. Understanding the seismic signatures of a meteorological origin also allows to, vice versa, better handle the contaminating side of these seismic sources in records, where high frequency signals are to be used for other than meteo-seismological studies. Our approach offers an alternative and complementary way to non-invasively monitor hydrometeorological energy and matter fluxes at high temporal and spatial resolution.

How to cite: Dietze, M., Mohr, C., Tolorza, V. A., Sotomayor, B., and Gonzalez, E.: Meteo-Seismology: Harvesting the Seismic Signals of Weather Dynamics in the Critical Zone, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3593, https://doi.org/10.5194/egusphere-egu23-3593, 2023.

Large rockfalls often cause huge economic losses and casualties in densely populated mountain areas. Timely acquiring information on a large rockfall can help promptly assess the damage and residual risks and guide the emergency response. Recent works suggest that the seismic signals generated by large rockfalls can provide these key information, but most of them focused on exploring seismic signatures to understand rockfall dynamics, lacking a rapid disaster assessing scheme. Here, we establish a seismic signal-based assessment scheme and demonstrate its capability by taking a large event – the 5 April 2021 Hongya rockfall (Sichuan, China) – as a case study. This scheme consists of three components, which are rockfall identification, detection and location, and characterization. In the rockfall identification module, we show how a rockfall can be distinguished from an earthquake and a rockslide by analyzing its seismic signatures. In the detection and location module, we demonstrate how the kurtosis-based method can be used to rapidly detect the initiation of a rockfall and determine the seismic wave velocity accordingly, and how the arrival-time-based location method can be used to locate a rockfall event. In the rockfall characterization module, we show how rockfall volume can be estimated from the magnitude of radiated seismic energy and how to characterize the dynamic process of a rockfall by the signatures of seismogram, spectrum and recorded seismic energy. Our results show that the seismic signal-based scheme presented here is suitable to characterize large rockfalls and has certain potential for rapid and effective emergency management.

How to cite: Li, W., Wang, D., and Zhang, Z.: Large rockfall detection, location and characterization using broadband seismic records: A case study of Hongya rockfall, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3773, https://doi.org/10.5194/egusphere-egu23-3773, 2023.

EGU23-4500 | Orals | GM2.2

Ambient noise monitoring of the Bayou Corne sinkhole evolution 

Aurelien Mordret, Anais Lavoué, Benjamin Witten, Adam Baig, Sophie Beaupretre, Romeo Courbis, and Chloé Gradon

The collapse at depth of a cavern on the side of the Napoleonville salt dome, Assumption Parish, Louisiana, led to the formation of a large sinkhole at the surface. Besides surficial evidence from direct observations, the precise timeline of the evolution of the sinkhole is poorly known.  Here, we used two years of continuous ambient seismic vibrations recorded at 11 3-component seismic stations located around the Bayou Corne sinkhole to monitor the daily relative seismic velocity changes associated with the sinkhole activity. The sinkhole started to form in 2012 and had several phases of activity. The seismic network was installed in early 2013 and recorded the last major collapses before settling in 2014. Following standard seismic interferometry processing, we computed the full 9-component tensors of ambient vibrations cross-correlations between each pair of sensors. After a drastic quality check of the correlations, we rejected several components for which we did not have enough data or for which the data were corrupted in a way that was difficult to correct. We monitored the relative velocity variations (dv/v) during the studied period using the stretching method in the 0.9-3 Hz frequency band within the early coda of the correlations. We employed a reference-less inversion procedure to obtain a dv/v time series for each component and each pair of stations. The multi-component pairs curves are averaged to get the final time series. The results show significant velocity changes in early 2013 associated with the collapse phases of the sinkhole. The velocity recovers steadily after the second half of 2013 and all of 2014. Two seismically active periods generate smaller velocity drops. In agreement with the spatial extension of the sinkhole toward the southwest seen from the surface, the pairs of stations the most affected by large velocity drops are the ones located along the southwestern shore of the lake.
Our monitoring allows for refining the timeline of the events affecting the sinkhole and its overall activity with a daily temporal resolution. From the analysis of these two years of data, the sinkhole stabilized after intense activity in early 2013. The large velocity variations indicate a strong destructuring of the ground, with potential fracturing and water invasion.

How to cite: Mordret, A., Lavoué, A., Witten, B., Baig, A., Beaupretre, S., Courbis, R., and Gradon, C.: Ambient noise monitoring of the Bayou Corne sinkhole evolution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4500, https://doi.org/10.5194/egusphere-egu23-4500, 2023.

EGU23-5344 | Orals | GM2.2 | Highlight

Tracking storms in the Pyrenees using a dense seismic network 

Jordi Diaz, Mario Ruiz, Mireia Udina, Francesc Polls, Davis Martí, and Joan Bech

Data acquired by a dense seismic network deployed in the Cerdanya basin (Eastern Pyrenees) is used to track the temporal and spatial evolution of meteorological events such as rainfall episodes or thunderstorms. Comparing seismic and meteorological data, we show that for frequencies above 40 Hz, the dominant source of seismic noise is rainfall and hence the amplitude of the seismic data can be used as a proxy of rainfall. The interstation distance of 1.5 km provides an unprecedented spatial resolution of the evolution of rainfall episodes along the basin. Two specific episodes, one dominated by stratiform rain and the second one dominated by convective rain, are analyzed in detail, using high resolution disdrometer data from a meteorological site near one of the seismic instruments.

Seismic amplitude variations follow a similar evolution to radar reflectivity values, but in some stratiform precipitation cases, it differs from the radar-derived precipitation estimates in this region of abrupt topography where radar may suffer antenna beam blockage. Hence, we demonstrate the added value of seismic data to complement other sources of information such as rain-gauge or weather radar observations to describe the evolution of ground-level rainfall fields at high spatial and temporal resolution. The seismic power and the rainfall intensity have and exponential relationship and the periods with larger seismic power are coincident. The time periods with rain drops diameters exceeding 3.5 mm do not result in increased seismic amplitudes, suggesting that there is a threshold value from which seismic data are no longer proportional to the size of the drops.

Thunderstorms can be identified by the recording of the sonic waves generated by thunders. We show that single thunders can be recorded to distances of a few tens of kilometers. As the propagation of these acoustic waves is expected to be strongly affected by parameters as air humidity, temperature variations or wind, the seismic data could provide an excellent tool to investigate atmospheric properties variations during thunderstorms.

How to cite: Diaz, J., Ruiz, M., Udina, M., Polls, F., Martí, D., and Bech, J.: Tracking storms in the Pyrenees using a dense seismic network, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5344, https://doi.org/10.5194/egusphere-egu23-5344, 2023.

EGU23-5610 | ECS | Orals | GM2.2

Evidence of sub-surface water flow dynamics within a karst conduit from ambient noise monitoring 

Axelle Pantiga, Vincent Allègre, Roland Lastennet, Nicolas Houillon, Sylvain Mateo, Fabien Naessens, and Alain Denis

Karst aquifers are characterized by their heterogeneity and complex underground geometry. A great part of the world relies on karst resources for drinkable water and understanding the functioning of karst systems is essential to assess their vulnerability and response to rainfall. Relevant continuous parameters to quantify the underground flow dynamics are still required for these studies as direct underground measurements are not possible. We used surface ambient noise measurements to estimate the seismic signature and amplitude associated with the water flow within an underground karst conduit. We combined geophysical measurements with hydro-chemical and hydrogeological data to build a multidisciplinary approach. The experimental site is the Glane spring, in Dordogne (France). The hydrogeological catchment of this Vauclusian-type spring is 75 km² and consists of upper Jurassic carbonate rocks. The Glane spring shows rapid and intense variations of discharge following rainfall events, ranging from 0.1 to 4 m3/s in 2021. Ambient noise has been continuously recorded since December 2021 using four seismic stations deployed upstream of the source and above the well-known karst terminal conduit. Hydro-chemical parameters and water level have been continuously monitored during a full hydrological cycle and a rain gauge was installed on site to monitor rainfall. During the first year of monitoring, we identified six flooding events. Each event was characterized by an increase in water flow associated with an increase in the seismic signal amplitude. We observed that the seismic amplitude standard level is higher during the high-water period than during the low water period suggesting a larger base water flow. We also observed hysteresis between the seismic power and hydro-chemical parameters. Correlations between the seismic recordings and hydrochemistry might suggest a change in water flow regime within the conduit prior to the flood. Seismic power variations associated with discharge variations are similar to what was already observed for sub-glacial melting flow. Other springs and swallow holes are currently instrumented to validate the approach in the field.

How to cite: Pantiga, A., Allègre, V., Lastennet, R., Houillon, N., Mateo, S., Naessens, F., and Denis, A.: Evidence of sub-surface water flow dynamics within a karst conduit from ambient noise monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5610, https://doi.org/10.5194/egusphere-egu23-5610, 2023.

EGU23-6049 | ECS | Posters on site | GM2.2

Towards quick clay monitoring in the city of Oslo, Norway with urban seismic noise 

Charlotte Bruland, Andreas Köhler, and Volker Oye

Historically, there is one larger quick clay landslide in Norway every year. Since 80 percent of those happen in known quick clay risk areas, it is important to monitor these sites continuously. Alna, a busy, urban area in Oslo, is an example of such a location where a quick clay slide could lead to substantial human and economical losses.

In this study we use ambient noise methods to monitor changes in the subsurface at Alna using a small array of three-component seismic sensors. To retrieve small velocity changes, we apply coda wave interferometry using 12 months of urban seismic noise (above 1 Hz).

We compare the observed day-to-day changes to air temperature, precipitation, and water levels in a nearby river, and observe environmental velocity fluctuations well correlated with air temperature and precipitation. In particular, freezing and thawing produces strong changes in seismic velocity (up to 4 percent). The surface wave-coda used here is sensitive to changes in shear wave velocity, which in turn can be used to detect changes of the sub-surface properties. Therefore, observed velocity variations at Alna could have potential for monitoring and early warning of quick clay instabilities.

How to cite: Bruland, C., Köhler, A., and Oye, V.: Towards quick clay monitoring in the city of Oslo, Norway with urban seismic noise, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6049, https://doi.org/10.5194/egusphere-egu23-6049, 2023.

EGU23-6264 | Orals | GM2.2

Stalagmites' reactions to ground motion studied using modified Raspberry Shake and nodal sensors 

Aurélie Martin, Thomas Lecocq, Ari Lannoy, Yves Quinif, Thierry Camelbeeck, and Nathalie Fagel

Karstic zones are numerous on Earth and offer a particular field of study to evaluate the ground motion levels that occurred in the past in support of regional seismic hazard assessment. Indeed, some fine and slender candlestick stalagmites are intact and therefore indicate that a certain level of ground motion has not been exceeded since they exist. Many parameters must be considered in the behaviour of stalagmites to earthquakes such as their shape, their mechanical properties and their natural frequency. A good way to better understand and characterize the reaction of these stalagmites to earthquakes is to study their reaction to the current permanent ground motion. To do this, a study based on the measurement of ambient seismic noise is underway in the cave of Han-sur-Lesse (Ardenne, Belgium). The ambient seismic noise is measured both at the surface (above the limestone massif and in the nearest village), on the floor of the cave and on the stalagmites themselves. Different three-component seismic sensors are used in parallel: three SmartSolo IGU-16HR 3C and two Raspberry Shake 3D Personal Seismographs, one of which has been adapted to be easily attached to the stalagmites. This parallel configuration during two-week recording periods made it possible to determine the eigenfrequencies and the polarization of the associated movements of 16 stalagmites. In addition, daily and weekly variations in ambient noise and transient events are measured such as earthquakes, quarry explosions or flooding in the cave. The presence of sensors in different places over the same period also makes it possible to study the possible impact of the cave's local characteristics on these measurements.

How to cite: Martin, A., Lecocq, T., Lannoy, A., Quinif, Y., Camelbeeck, T., and Fagel, N.: Stalagmites' reactions to ground motion studied using modified Raspberry Shake and nodal sensors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6264, https://doi.org/10.5194/egusphere-egu23-6264, 2023.

EGU23-6300 | Posters on site | GM2.2

Towards an unsupervised generic seismic detector for hazardous mass-movements: a data-driven approach 

Patrick Paitz, Małgorzata Chmiel, Lena Husmann, Michele Volpi, Francois Kamper, and Fabian Walter

Hazardous mass-movements pose a great danger to the population and critical infrastructure, especially in alpine areas. Monitoring and early-warning systems can potentially save many lives and improve the resilience of mountain communities to catastrophic events. Increasing coverage of seismic networks recording hazardous mass-movements opens up new warning perspectives as long as efficient algorithms screening the seismic data streams in real-time are available.

We propose to combine physical and statistical properties of seismic ground velocity recordings from geophones and seismometers as a foundation for an unsupervised workflow for mass movement detection. We evaluate the performance, consistency, and generalizability of unsupervised clustering algorithms like K-means and Bayesian Gaussian Mixture Models against supervised methods like the Random Forest classifier. Focusing on debris-flow records at the Illgraben torrent in Switzerland, we present a generic mass-movement detector with high accuracy and early-warning capability. We apply this detector to other datasets form other sites to investigate its transferability.

Since our results aim to enable mass-movement monitoring and early-warning worldwide, Open Research Data principles like Findability, Accessibility, Interoperability and Reusability (FAIR) are of high importance for this project. We discuss how using the Renku (renkulab.io) platform of the Swiss Data Science Center ensures FAIR data science principles in our investigation. This is a key step towards our ultimate goal to enable seismology-based early warning of mass-movements wherever it may be required.

How to cite: Paitz, P., Chmiel, M., Husmann, L., Volpi, M., Kamper, F., and Walter, F.: Towards an unsupervised generic seismic detector for hazardous mass-movements: a data-driven approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6300, https://doi.org/10.5194/egusphere-egu23-6300, 2023.

EGU23-6321 | ECS | Posters on site | GM2.2

Can we characterize groundwater reservoirs in central Europe from air-pressure-induced seismic velocity changes? 

Richard Kramer, Yang Lu, and Götz Bokelmann

In this study, we used coda wave interferometry to investigate four years of continuous data from AlpArray and other locations throughout Europe. We estimate the hourly Green’s function by cross-correlating ambient seismic noise recorded at pairs of stations. The results indicate short and long-term variations of the seismic velocities and show the feasibility of large-scale monitoring with ambient seismic noise at high temporal resolution. The relative seismic velocities (dv/v) show temporal variations on the order of 10-3 in a frequency band around 1 Hz. Spectra of the velocity time series contain strong daily and sub-daily behaviour, which are primarily caused by the coupling of atmospheric processes and solid Earth. The explanatory model focuses on depth variations of the groundwater table, linking atmospheric pressure (loading and unloading the Earth's surface) to variations in seismic velocity. This study aims to understand and explain differences in daily and sub-daily behaviour across Europe. This may contribute to the hydrological characterization of the near-subsurface in central Europe. 

How to cite: Kramer, R., Lu, Y., and Bokelmann, G.: Can we characterize groundwater reservoirs in central Europe from air-pressure-induced seismic velocity changes?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6321, https://doi.org/10.5194/egusphere-egu23-6321, 2023.

EGU23-7136 | ECS | Orals | GM2.2

Towards a generic clustering approach for building seismic catalogues from dense sensor networks 

Joachim Rimpot, Clément Hibert, Jean-Philippe Malet, Germain Forestier, and Jonathan Weber

In the context of climate change, the occurrence of geohazards such as landslides or rockfalls might increase. Therefore, it is important to have the ability to characterise their (spatial and temporal) occurrences in order to implement protection measures for the potential impacted populations and infrastructures. Nowadays, several methods including Machine Learning algorithms are used to study landslides-triggered micro-seismicity and the associated seismic sources (eg. rockfalls and  slopequakes). Those innovative algorithms allow the automation of the processing chains used to build micro-seismicity catalogues, leading to the understanding of the landslide deformation pattern and internal structure. Unfortunately, each landslide context has its own seismic signature which requires the use of the most complete and handmade training samples to train a Machine Learning algorithm. This is highly time consuming because it involves an expert that needs to manually check every seismic signal recorded by the seismic network, which can be thousands per day.

The aim of this study is to develop semi-supervised and unsupervised clustering methods to characterise the micro-seismicity of landslides in near real time. Here, we present the preliminary results obtained for creating a landslide micro-seismicity catalogue from the analysis of a dense network of 50 seismic stations deployed temporarily at the Super-Sauze landslide (French Alps). First, we present the performance of supervised Random Forest and XGBoost trained models on the event signals. Then, an approach aimed at processing streams of raw seismic data based on 18s-length windows is explored. Finally, we discuss the clustering results and the transferability possibilities of the approach to other landslides and even environments (glaciers, volcanoes).

How to cite: Rimpot, J., Hibert, C., Malet, J.-P., Forestier, G., and Weber, J.: Towards a generic clustering approach for building seismic catalogues from dense sensor networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7136, https://doi.org/10.5194/egusphere-egu23-7136, 2023.

EGU23-7489 | ECS | Posters on site | GM2.2

Monitoring the cryoseismic activity of the Astrolabe glacier, Terre Adélie, Antarctica 

Tifenn Le Bris, Guilhem Barruol, Emmanuel Le Meur, Florent Gimbert, and Dimitri Zigone

In coastal Antarctica, outlet glaciers exhibit complex dynamics materialized by intense internal deformation, enhanced basal sliding and strong thermo-mechanical interactions with the ocean. Here we aim to use seismic observations to unravel these various processes and their link with glacier and ocean dynamics. As part of the SEIS-ADELICE project (2020-2024) supported by the French Polar Institute IPEV, in January 2022 we deployed four permanent and six temporary (1 month long) broadband seismic stations on and around the Astrolabe Glacier (Terre Adélie, East Antarctica), as well as four ocean-bottom seismometers at sea near the terminus of the floating tongue. In January 2023 we will be supplementing this setup by a temporary network of 50 seismic nodes above the grounding line of the glacier.

Preliminary detection and classification of seismic events reveals a wide variety of cryo-seismic signals. The most pervasive events correspond to icequakes, are located close to the surface, and exhibit clear tidal modulation. We interpret these events as being generated by the brittle fracturing of ice associated with crevasse opening. We also observe numerous short and similar repetitive events of much lower amplitude that are located at few restricted locations near the ice-bedrock interface. These events are likely produced by basal stick-slip over punctual bedrock asperities. Finally, we observe glacial tremors which could result from hydraulic sources at the ice-bedrock interface, although further analysis is required to confirm this hypothesis.

This preliminary work provides useful grounds for deeper analysis to be done in the future on source characteristics and their more quantitative links with glacier dynamics.

How to cite: Le Bris, T., Barruol, G., Le Meur, E., Gimbert, F., and Zigone, D.: Monitoring the cryoseismic activity of the Astrolabe glacier, Terre Adélie, Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7489, https://doi.org/10.5194/egusphere-egu23-7489, 2023.

EGU23-7549 | ECS | Posters on site | GM2.2 | Highlight

Seabed seismometers reveal duration and structure of longest runout sediment flows on Earth 

Megan Baker, Peter Talling, Richard Burnett, Ed Pope, Sean Ruffell, Matthieu Cartigny, Michael Dietze, Morelia Urlaub, Michael Clare, Jeffrey Neasham, Ricardo Silva Jacinto, Pascal Kunath, and Christine Peirce

Seafloor sediment flows (turbidity currents) form some of the largest sediment accumulations on Earth, carry globally significant volumes of organic carbon, and can damage critical seafloor infrastructure. These fast and destructive events are notoriously challenging to measure in action, as they often damage any instruments anchored within the flow. We present the first direct evidence that turbidity currents generate seismic signals which can be remotely sensed (~1-3 km away), revealing the internal structure and remarkably prolonged duration of the longest runout sediment flows on Earth. Passive Ocean Bottom Seismograph (OBS) sensors, located on terraces of the Congo Canyon, offshore West Africa, recorded thirteen turbidity currents over an 8-month period. The occurrence and timing of these turbidity currents was confirmed by nearby moorings with acoustic Doppler current profilers.

Results show that turbidity currents travelling over ~1.5 m/s produce a seismic signal concentrated below 10 Hz with a sudden onset and more gentle decay. Comparison of the seismic signals with information on flow velocities from the acoustic Doppler current profilers demonstrates that the seismic signal is generated by the fast-moving front of the flow (frontal cell), which contains higher sediment concentrations compared to the slower-moving body. Long runout flows travelling >1000 km have a fast (3.7-7.6 m s-1) frontal cell, which can be 14 hours, and ~350 km long, with individual flows lasting >3 weeks. Flows travelling >1000 km eroded >1300 Mt of sediment in one year, yet had near-constant front speeds, contrary to past theory. The seismic dataset allows us to propose a fundamental new model for how turbidity currents self-sustain, where sediment fluxes into and from a dense frontal layer are near-balanced.

Seismic monitoring of turbidity currents provides a new method to record these hazardous submarine flows, safely, over large areas, continuously for years yet at sub-second temporal resolution. Monitoring these processes from land would considerably ease deployment efforts and costs. Thus, work is underway investigating if terrestrial seismic stations can record submarine seafloor processes in Bute Inlet, a fjord in western Canada where independent measurement of delta-lip failures and turbidity currents can be compared to a passive seismic dataset.

How to cite: Baker, M., Talling, P., Burnett, R., Pope, E., Ruffell, S., Cartigny, M., Dietze, M., Urlaub, M., Clare, M., Neasham, J., Silva Jacinto, R., Kunath, P., and Peirce, C.: Seabed seismometers reveal duration and structure of longest runout sediment flows on Earth, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7549, https://doi.org/10.5194/egusphere-egu23-7549, 2023.

EGU23-7727 | Orals | GM2.2

Using Seismic Methods to Monitor Bedload Transport Along a Desert Environment Ephemeral Tributary 

Susan Bilek, J. Mitchell McLaughlin, Daniel Cadol, and Jonathan Laronne

Use of seismic monitoring and data analysis techniques in recent years have allowed for improved understanding of several shallow earth processes, such as glacial motion, subsurface water flow, and bedload transport. Early applications using seismic data collected at high energy alpine rivers suggest that seismic energy within certain frequency bands is linked to bedload discharge.  However, study of other river systems have been more limited, even though some of these systems, such as ephemeral streams in arid environments, transport large quantities of sediment during short-lived flash flood events.  Here we present seismic and hydrologic data collected in a unique sediment observatory within an ephemeral tributary to the Rio Grande River, in the desert southwest of the U.S., combining dense seismic observations with a variety of in-channel bedload and water monitoring measurements. We have seismic records for more than a dozen floods ranging in depth from a few centimeters to over one meter, encompassing bedload flux as high as 12 kg s-1 m-1, two orders of magnitude higher than in most perennial settings. Our efforts to date focus on identifying the noise sources within the seismic record, characterization of the seismic properties of the site, and determining the seismic frequency ranges best correlated with the automatically measured bedload flux. Within the 30-80 Hz frequency range, we find a linear relationship between seismic power and bedload flux. We hypothesize that variations in linear fit statistics between flood events are due to varying bedload grain size distributions and in-channel morphological changes.

How to cite: Bilek, S., McLaughlin, J. M., Cadol, D., and Laronne, J.: Using Seismic Methods to Monitor Bedload Transport Along a Desert Environment Ephemeral Tributary, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7727, https://doi.org/10.5194/egusphere-egu23-7727, 2023.

EGU23-8127 | ECS | Posters on site | GM2.2

Benford's law in detecting rapid mass movements with seismic signals 

Qi Zhou, Hui Tang, Jens M. Turowski, Jean Braun, Michael Dietze, Fabian Walter, Ci-Jian Yang, Sophie Lagarde, and Ahmed Abdelwahab

Rapid mass movements are a major threat in populated landscapes, as they can cause significant loss of life and damage civil infrastructure. Previous work has shown that using environmental seismology methods to monitor such mass movements and establish monitoring systems offers advantages over existing approaches. The first important step in developing an early warning system for rapid mass movements based on seismic signals is automatically detecting events of interest. Though the approach, such as short-term average to long-term average ratio (STA/LTA) and machine learning model, was introduced to detect events (e.g., debris flow and rockfall), it is still challenging to calibrate input parameters and migrate existing methods to other catchments. Detection of debris flows, for instance, is similar to anomaly detection if we consider the seismic stations recording background signals as an overwhelming majority condition. 
Benford's law describes the probability distribution of the first non-zero digits in numerical datasets, which provides a functional, computationally cheap approach to anomaly detection, such as fraud detection in financial data or earthquake detection in seismic signals. In this study, seismic signals generated by rapid mass movements were collected to check the agreement of the distribution of the first digit with Benford's law. Subsequently, we develop a computationally efficient and non-site-specific model to detect events based on Benford's law using debris flows from the Illgraben, a Swiss torrent, as an example. Our results show that seismic signals generated by high-energy mass movements, such as debris flows, landslides, and lahars, follow Benford's law, while those generated by rockfall and background signals do not. Furthermore, our detector performance in picking debris-flow events is comparable to a published random forest and seismic network-based approach. Our method can be applied at other sites to detect debris-flow events without additional calibration and offers the potential for real-time warnings.

How to cite: Zhou, Q., Tang, H., Turowski, J. M., Braun, J., Dietze, M., Walter, F., Yang, C.-J., Lagarde, S., and Abdelwahab, A.: Benford's law in detecting rapid mass movements with seismic signals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8127, https://doi.org/10.5194/egusphere-egu23-8127, 2023.

EGU23-8986 | ECS | Posters on site | GM2.2

Monitoring of an Alpine landslide using dense seismic observations: combining Distributed Acoustic Sensing and 1000 autonomous seismic nodes 

Tjeerd Kiers, Cédric Schmelzbach, Pascal Edme, Patrick Paitz, Florian Amann, Hansruedi Maurer, and Johan Robertsson

Landslides are a major natural hazard that can cause significant loss of life and property damage around the world. As global temperatures rise and weather extremes become more frequent, we can expect an increase in the hazard emanating from landslides too. In order to better understand and mitigate landslide risks, a variety of strategies have been developed to characterize and monitor landslide activity. Many established approaches provide valuable information about surface displacement and surface properties, but are not suited to inspect the subsurface parts of a landslide body. In contrast, seismic imaging and monitoring methods allow us to study subsurface structures, properties, and internal processes that control landslide behaviour.

In our project, we develop novel seismic data acquisition and interpretation approaches to characterize and monitor one of the largest active unstable slopes in the Alps, the Cuolm da Vi landslide, with an unprecedented spatial resolution. We achieve this by combining an array of over 1’000 seismic nodes with fiber-optic based monitoring techniques such as Distributed Acoustic (DAS) and Strain Sensing (DSS).

The deep-seated Cuolm da Vi landslide is located near Sedrun (Central Switzerland) and consists of approximately 100-200 million m3 of unstable rock reaching displacement rates up to 10-20 cm/yr with clear seasonal cycles. In summer 2022, we buried over 6 kilometres of fiber-optic cable in this alpine environment covering the most active part of the landslide with multiple cable orientations. Additionally, we deployed a nodal array of 1046 accelerometers in a hexagonal grid covering around 1km2 with a nominal spacing of 28 meters. Seismic data were acquired with the nodes and the DAS system continuously for four weeks. This time period included the blasting of 163 dynamite shots for calibration and active-source imaging purposes. In 2023, we plan to conduct data acquisition for longer periods using primarily fibre-optic based techniques with a focus on the temporal evolution of the landslide dynamics.

Our first goal is to resolve the internal structure of the landslide based on the controlled-source data acquired in summer 2022 to construct, for example, a seismic velocity model. Based on the models derived from the active-source seismic data, we plan to exploit the continuous seismic recordings of ambient vibrations and potential seismic signals produced by the landslide activity to complement structural models and study the landslide dynamics. We will present our current results and discuss their implications for the next steps towards monitoring this landslide over time.

How to cite: Kiers, T., Schmelzbach, C., Edme, P., Paitz, P., Amann, F., Maurer, H., and Robertsson, J.: Monitoring of an Alpine landslide using dense seismic observations: combining Distributed Acoustic Sensing and 1000 autonomous seismic nodes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8986, https://doi.org/10.5194/egusphere-egu23-8986, 2023.

EGU23-11404 | ECS | Posters on site | GM2.2

Rapid shredding of the subglacial sediment export signal by proglacial forefields 

Davide Mancini, Michael Dietze, Tom Müller, Matthew Jenkin, Floreana Marie Miesen, Matteo Roncoroni, Andrew Nicholas, and Stuart Nicholas Lane

Alpine glaciers have been rapidly retreating and at increasing rates in recent decades due to climate warming. As a consequence, large amounts of suspended- and bed-load flux are being released to proglacial environments, such as proglacial forefields. These regions are among the most unstable geomorphic systems of the Earth because they rapidly respond to changing discharge and sediment conditions. Given this, it might be hypothesized that their intense morphodynamic activity, being a complex and non-linear process, could “shred” the sediment transport signal itself, and especially that related to subglacial sediment export.

To date, our knowledge on subglacial sediment export by subglacial streams is essentially dominated by suspended sediment dynamics recorded in front of shrinking glaciers because of the limitations in measuring bedload transport. The latter is usually monitored far downstream from glacier termini by permanent stations (e.g. water intakes, geophone systems) leaving major uncertainties in the absolute amounts and temporal patterns of transport in both glacial and proglacial environments, as well as the relative importance compared to suspended sediment in case of morphodynamic filtering. Thus, the aim of this project was to investigate the evolution of the both suspended- and bedload subglacial export signals within the proglacial forefield to quantify the extent and the timescale over which proglacial morphodynamics filter them.

This work focuses on a large Alpine glacial forefield, almost 2 km in length, that has formed since the early 1980s at the Glacier d’Otemma (southern-western Swiss Alps, Valais). Data were collected over two entire melt seasons (June-September 2020 and 2021) experiencing different climatic conditions, the first year warm and relatively dry and the second cold and relatively wet. Suspended transport was recorded using conventional turbidity-suspended sediment concentration relationship, bedload transport was monitored seismically, while the morphodynamic filtering was determined using signal post-processing techniques. At present, there are no studies combining continuous measurements of both suspended- and bed-loads in such environments.

Results show that the signal of subglacial bedload export, unlike suspended load export, is rapidly shredded by proglacial stream morphodynamics, which we show is due to a particle-size dependent autogenic sorting of sediment transport at both daily and seasonal time-scales. The result is that over very short distances, the signal of subglacial bedload sediment export is lost and replaced by a signal dominated by morphodynamic reworking of the proglacial braidplain. The suspended signal is less impeded but significant floodplain storage and release of suspended sediment was observed. These results question the reliability of current inferences of glacial erosion rates from sediment transport rates often measured some way downstream of glacier margins.

How to cite: Mancini, D., Dietze, M., Müller, T., Jenkin, M., Miesen, F. M., Roncoroni, M., Nicholas, A., and Lane, S. N.: Rapid shredding of the subglacial sediment export signal by proglacial forefields, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11404, https://doi.org/10.5194/egusphere-egu23-11404, 2023.

EGU23-12107 | ECS | Orals | GM2.2

Seismic Monitoring of Permafrost Dynamics at Mt. Zugspitze (German/Austrian Alps) 

Fabian Lindner, Krystyna Smolinski, Riccardo Scandroglio, Andreas Fichtner, and Joachim Wassermann

As observed elsewhere on a global scale, mountain permafrost at the Zugspitze (German/Austrian Alps) is degrading in response to climate change, which affects the rock slope stability and thus the hazard potential. Recent studies suggest that passive seismology is a promising and emerging tool to monitor permafrost changes as the seismic velocity of rocks strongly decreases/increases upon thawing/freezing. Compared to other, more classical methods like borehole temperature logging or electrical resistivity tomography (ERT), seismology is less laborious and costly, non-invasive and allows continuous monitoring. At Mt. Zugspitze, we exploit these advantages using a permanent seismic station (installed in 2006) as well as three small seismic arrays and Distributed Acoustic Sensing (DAS; both available since summer/fall 2021), to infer permafrost dynamics with high spatio-temporal resolution. The seismic data show repeating diurnal noise generated by the operation of cable cars, which we leverage for cross-correlation analysis. Our results suggest that the dominant signal in the retrieved seismic velocity change time series is caused by the seasonal freeze-thaw cycles associated with permafrost bodies on the northern side of the mountain ridge. On the long-term, the time series show a gradual velocity decrease associated with permafrost degradation due to atmospheric warming and compare well with modeled velocity change time series using rock temperature data from a nearby borehole, which intersects the mountain ridge. We discuss differences in our seismic analysis results obtained from direct and coda waves as well as from single station to station pairs and DAS and interpret the results in the light of other measurements including ERT, rock temperature logging and meteorological parameters.

How to cite: Lindner, F., Smolinski, K., Scandroglio, R., Fichtner, A., and Wassermann, J.: Seismic Monitoring of Permafrost Dynamics at Mt. Zugspitze (German/Austrian Alps), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12107, https://doi.org/10.5194/egusphere-egu23-12107, 2023.

EGU23-12128 | Posters on site | GM2.2

Probing temporal variation of suspended load to bedload ratio using seismic saltation model 

Chao Ting Meng, Wei An Chao, and Yu Shiu Chen

Monitoring temporal and spatial changes in sediment volume in the upstream reservoir is one of the important indicators for evaluating the reservoir project life, especially the information carried by bedload and suspended load. According to field condition, direct bedload monitoring is often difficult. Thus, bedload usually can be estimated by a specific proportion of suspended load depended on the flooding magnitude, which can cause a large uncertainty in estimates of total sediment load. In recent years, riverine micro-seismic signals have been applied to study bedload transport. Our study chose the Da-Pu Dam (location: 23.296500°N, 120.644611°E), located at the upstream of the Zeng-Wen Reservoir and the junction of the Zeng-Wen river and Cao-Lan river, which is the last check dam before entering the reservoir area. Its upstream catchment area is 30,312 hectares that comprise approximately 63% of the Zeng-Wen Reservoir catchment area (48,100 hectares). The length of the monitoring section of the Da Pu Dam is 1,100 meters, with an average width of 121 meters and an average slope of 0.36 degrees. With the available data composed of riverbed cross-section survey, sediment particle size distribution, fluvial measurements (water depth, surface flow velocity), orthoimagery, and suspended load measurement, our study applies seismic saltation model to estimate the bedload flux and compares the results with the measured suspended load. Results showed that there are different ratios between bedload and suspended load under similar hydrological condition during the plum rain season(May-June) and typhoon period(July-September). In a case of flooding event considering the flow stage from medium to high discharge, significant temporal changes in the ratio between bedload and suspended load can also be observed, which imply a complex transition process between the bedload and suspension particles. The temporal changes in sediment ratio obtained in this study can be applied to estimate the total volume of sediment load entering the reservoir. Our estimated results are consistent with the survey of sediment accumulation at the end of each year in the reservoir area.

How to cite: Meng, C. T., Chao, W. A., and Chen, Y. S.: Probing temporal variation of suspended load to bedload ratio using seismic saltation model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12128, https://doi.org/10.5194/egusphere-egu23-12128, 2023.

EGU23-12687 | ECS | Orals | GM2.2

Surprising seismological signals during the October 2015 Skaftá jökulhlaup 

Thoralf Dietrich, Eva P.S. Eibl, Eyjólfur Magnússon, Daniel Binder, Sebastian Heimann, and Sigrid Roessner

Understanding the spatiotemporal details in the occurrence of jökulhlaups, also referred to as glacier lake outburst floods (GLOFs), is important for improving early warning and forecasting future events. Jökulhlaups occur in many different glacier-related settings and differ in their characteristics depending on the natural conditions: From very rapid floods (minutes-hours) originating from moraine dammed lakes in steep valleys to gradual floods (days-weeks) from subglacial lakes such as the ones beneath Vatnajökull ice cap, in Iceland. Previous studies of the October 2015 Skaftá jökulhlaup suggested that several hours of early-warning is possible based on the generated seismic tremor. Here, for the first time, we looked into all three spatial components of GNSS and seismic array data, respectively. Previous studies have already analysed the seismic events (icequakes, tremor, other migrating transient events) in detail, yet only on the z component. We reprocessed all three components of the seismic array data using frequency-wavenumber -analysis (fk-analysis) and match field processing (MFP). Both techniques allow to locate distant signal sources, either by direction only (fk) or actual location (MFP). We specifically focused on the time period when the tremor source is moving with the flood front and found two unexplained seismic signals:

  • A second migrating signal is visible on the lowermost part of the flood path 6 hours later than the passing of the first flood front.

    We compared this with a GNSS observations on top of the subglacial flood path and a hydrometric station 25 km downstream from the glacier margin in the affected Skaftá-river.

    After aligning the time series by the arrival of the pressure wave, the timing of the second seismic signal fits well with a 10 cm uplift of the glacier at the GNSS station; but also with a change in the rate of water level rise at the hydrometric station.

    We discuss this in the context of either explaining GNSS, hydrometric and seismological data individually or giving a hypothetical process that explains all three together. That could be a second intraglacial water lense draining, after the emptying of the lake deformed the overlaying glacier and connected the two water bodies. However, radio echo sounding survey over the source area in spring 2015 did not indicate a significant intraglacal water lense above the subglacial lake. The GNSS data may be cleared as noise artifact and the hydrometric data explained by flow of water out of the river course of Skaftá and onto porous lava fields between Sveinstindur, where the discharge of Skaftá is measured, and the glacier. Yet: The seismic signal then is left unexplained and open for discussion.

  • Finally, 18 hours after the first pulse, we found a sudden deceleration in horizontal motion on the GNSS that coincided with a sudden increase in seismic signals originating at the glacier terminus. We discuss if what we see is actually the glacier stopping, after losing the flood lubrication.

 

How to cite: Dietrich, T., Eibl, E. P. S., Magnússon, E., Binder, D., Heimann, S., and Roessner, S.: Surprising seismological signals during the October 2015 Skaftá jökulhlaup, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12687, https://doi.org/10.5194/egusphere-egu23-12687, 2023.

EGU23-13269 | ECS | Posters on site | GM2.2

Denoising Cryoseismological Distributed Acoustic Sensing Data Using a Deep Neural Network 

Johanna Zitt, Patrick Paitz, Fabian Walter, and Josefine Umlauft

One major challenge in Environmental Seismology is that signals of interest are often buried within the high noise level emitted by a multitude of environmental processes. Those signals potentially stay unnoticed and thus, might not be analyzed further.

Distributed acoustic sensing (DAS) is an emerging technology for measuring strain rate data by using common fiber-optic cables in combination with an interrogation unit. This technology enables researchers to acquire seismic monitoring data on poorly accessible terrain with great spatial and temporal resolution. We utilized a DAS unit in a cryospheric environment on a temperate glacier. The data collection took place in July 2020 on Rhonegletscher, Switzerland, where a 9 km long fiber-optic cable was installed, covering the entire glacier from its accumulation to its ablation zone. During one month 17 TB of data were acquired. Due to the highly active and dynamic cryospheric environment, our collected DAS data are characterized by a low signal to noise ratio compared to classical point sensors. Therefore, new techniques are required to denoise the data efficiently and to unmask the signals of interest. 

Here we propose an autoencoder, which is a deep neural network, as a denoising tool for the analysis of our cryospheric seismic data. An autoencoder can potentially separate the incoherent noise (such as wind or water flow) from the temporally and spatially coherent signals of interest (e.g., stick-slip event or crevasse formation). We test this approach on the continuous microseismic Rhonegletscher DAS records. To investigate the autoencoder’s general suitability and performance, three different types of training data are tested: purely synthetic data, original data from on-site seismometers, and original data from the DAS recordings themselves. Finally, suitability, performance as well as advantages and disadvantages of the different types of training data are discussed.

How to cite: Zitt, J., Paitz, P., Walter, F., and Umlauft, J.: Denoising Cryoseismological Distributed Acoustic Sensing Data Using a Deep Neural Network, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13269, https://doi.org/10.5194/egusphere-egu23-13269, 2023.

EGU23-13334 | Posters on site | GM2.2

Ambient H/V sensitivity to the dynamics of glaciers and ice sheets 

Janneke van Ginkel, Fabian Walter, Ana Nap, Mauro Häusler, and Martin Lüthi

Climate change is causing major shifts in the dynamics of the cryosphere, leading to sea-level rise, glacier break-off events, flooding, and landslides. Geological, thermodynamic and hydraulic processes at the base of an ice mass play a central role in ice flow dynamics, and understanding these is imperative for predicting ice body behavior in a changing climate. To this end, sustained ambient vibrations in glaciated environments can be used to monitor subglacial conditions over significant spatial extent with relatively low-cost acquisition.

In earthquake seismology, a well-established methodology to investigate subsurface properties is the horizontal-to-vertical spectral ratio (H/V) of ambient seismic ground unrest. In cryoseismology, the H/V approach is already used to invert for velocity profiles of ice or firn, to obtain bedrock topography and to identify the presence of basal sediments. To date, only a few hours of seismic vibration records are typically used. Yet in such short time records, biases may arise because of the dynamic character of the glacier. Seismic resonances within the soft ice layer and resulting H/V ratios are expected to vary with changes in subglacial hydraulic conditions.

We propose to leverage temporal variations in H/V spectra to investigate subglacial processes. As a case study, we first focus on the Glacier de la Plaine Morte (Switzerland), where a seismic array was deployed for four months in summer of 2016. During this time, an ice-marginal lake formed and suddenly drained through and under the glacier, making this seismic record ideal for our purposes. This drainage event is well recorded and strongly influences the H/V in terms of amplitude and resonance frequency. We next present ambient H/V measurements of the Sermeq Kujalleq in Kangia (also known as Jakobshavn Isbræ), one of Greenland’s largest outlet glaciers. Here, the H/V spectra show multiple resonances over time, whose origin we discuss in more detail. For both our study cases, separating variations in source and medium properties is pivotal. Tackling this challenge provides glaciologists with a valuable tool to investigate the poorly accessible subglacial environment, which holds the key to our understanding of ice flow and eustatic sea level rise.

How to cite: van Ginkel, J., Walter, F., Nap, A., Häusler, M., and Lüthi, M.: Ambient H/V sensitivity to the dynamics of glaciers and ice sheets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13334, https://doi.org/10.5194/egusphere-egu23-13334, 2023.

EGU23-13383 | ECS | Posters on site | GM2.2

Using a record of bedload transport from Leverett glacier in western Greenland to understand proglacial sediment transport processes from the ice sheet   

Marjolein Gevers, Davide Mancini, Stuart Lane, and Ian Delaney

Increased glacier melt leads to a change in sediment transport capacity below glaciers, which impacts the sediment transport within proglacial areas as well as downstream ecosystems and geomorphology. Previous work on Alpine glaciers shows that strong diurnal discharge variations lead to fluctuations in sediment transport capacity such that deposition and erosion can occur in the proglacial area over the course of the melt season. However, the exact processes controlling sediment transport at the outlet glaciers of ice sheet margins and in their proglacial areas remain uncertain. Data suggest that the diurnal discharge variations are substantially reduced and baseflow discharge is much greater, likely capable of maintaining significant sediment transport throughout the melt season. This difference in the hydrological regime as compared with Alpine glacial systems may drive different rates and variations in sediment transport and, ultimately, in proglacial braid plain morphodynamics.

We measure proglacial sediment transport at Leverett glacier, a land-terminating glacier located at the western margin of the Greenland Ice Sheet. As bedload transport is exceptionally difficult to measure in situ, two seismic stations were installed to evaluate bedload transport in the glacial meltwater stream in the summer of 2022. The first station is located close to the current glacier terminus, and the second one is about 2 km from the current glacier terminus. These two stations allow for the examination of the sediment transport processes within the proglacial area. By using a Fluvial Inversion Model the recorded seismic data is converted into bedload flux. The model is calibrated using active seismic surveys and statistical approaches to evaluate the physical parameters. Outputs of the Fluvial Inversion Model are validated with available water stage data.  The results provide insight as to whether the proglacial area is aggrading or eroding as sediment transport in the two locations at Leverett glacier evolves over the summer season. We discuss the relationship between bedload transport and level of the proglacial river, as well as the seasonal variations in proglacial sediment transport and deposition in Leverett glacier’s proglacial area.

How to cite: Gevers, M., Mancini, D., Lane, S., and Delaney, I.: Using a record of bedload transport from Leverett glacier in western Greenland to understand proglacial sediment transport processes from the ice sheet  , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13383, https://doi.org/10.5194/egusphere-egu23-13383, 2023.

EGU23-16008 | ECS | Orals | GM2.2

Short-term fast ice dynamics derived from passive seismic data at a large Greenland outlet glacier 

Ana Nap, Fabian Walter, Adrien Wehrlé, Andrea Kneib-Walter, Guillaume Jouvet, and Martin P. Lüthi

Outlet glaciers and ice streams are the main channels through which ice sheets transport their mass towards the ocean. One of Greenland’s largest outlet glaciers Sermeq Kujalleq in Kangia (Jakobshavn Isbrae) has been broadly researched after experiencing a rapid retreat of the terminus and accompanying speedup to up to 40 m/day in the early 2000’s. However, such short-term ice dynamic variations remain poorly understood making numerical models difficult to constrain and predictions on future sea-level rise uncertain.

The short-term ice dynamics of Sermeq Kujalleq consists in transient states and can only be captured by in-situ measurements of high spatial and temporal resolution. Glacier seismology has proven to be a valuable tool to study these dynamics, it provides data with a high temporal resolution and can provide information on processes happening below the ice surface. Within the COEBELI project we combine passive glacier seismology with global navigation satellite system (GNSS) receivers, long-range drones, time-lapse cameras and terrestrial radar interferometry to capture processes such as calving and basal sliding at their respective timescales.

Here, we present results from a multi-array seismic deployment at Sermeq Kujalleq in Summer 2022. From May until September two arrays were deployed in the upstream part of the fast-flowing ice stream (>22 km from calving front) and one array on slower moving ice North of the main trunk. For a 3-week period in July, four more arrays were deployed on the fast-flowing ice stream closer to the calving front (<15 km). In the severely crevassed areas near the calving front (<15 km), the arrays consisted of custom-made autonomous seismic boxes whereas at more accessible upstream areas we installed borehole instruments. During the deployment we recorded multiple large calving events, glacier speedups and periodic multi-hour tremors accompanied by bursts of short-term high frequency (>50 Hz) icequakes. By studying these different signals, we are able to better constrain the processes and forces that control fluctuating ice-flow velocity and calving events.

How to cite: Nap, A., Walter, F., Wehrlé, A., Kneib-Walter, A., Jouvet, G., and Lüthi, M. P.: Short-term fast ice dynamics derived from passive seismic data at a large Greenland outlet glacier, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16008, https://doi.org/10.5194/egusphere-egu23-16008, 2023.

High-melt areas of glaciers generate a rich spectrum of ambient seismicity. These signals do not only contain information about the source mechanisms (e.g. englacial fracturing, water flow, iceberg detachment, basal stick-slip motion) but also carry information about seismic wave propagation within the glacier ice and, therefore, the mechanical properties of the ice. In the summer of 2021 two seismic arrays were deployed in Southern Spitsbergen at the vicinity of Hansbreen’s terminus, one being placed directly on the glacial ice, yielding an 8-days long time series of glacial seismicity.

The direct and scattered wave fields from tens of thousands of icequake records (few thousands per day) were used to determine seismic velocities and monitor structural changes within the ice, while the analysis of the ambient noise was leveraged to constrain the ice thickness. The surface icequakes dominate the seismograms due to an abundance of englacial fracturing. Hence, Rayleigh waves and beam-based techniques were employed to characterise the patterns of microseismicity at the transform junction of two glaciers (Tuvbreen and Hansbreen). Several clusters of various-origin seismicity being active at certain times are identified with a majority of them located on stagnant, fast-melting Tuvabreen.

How to cite: Gajek, W.: Rayleigh wave is the coolest – resolving microseismicity of a tidewater glacier in Svalbard, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16346, https://doi.org/10.5194/egusphere-egu23-16346, 2023.

Glaciers or ice-streams have many common points with tectonic faults. Glaciers can move by

stable or unstable slip or by creep within the glacier thickness. Like faults, glacier sliding can

produce “icequake” signals over a huge range of frequencies, rupture length and signal

duration, as well as tremor. But because glaciers are shallower, the sliding interface can be

accessed directly much more easily, by boreholes or cavities. And they move much faster than

tectonic faults, so that deformation is easier to estimate and icequake inter-event times are

much shorter than for earthquakes.

Here I present some observations of high- and low-frequencies repeaters of basal icequakes

in the Mont-Blanc areas. Both types of events occur as bursts lasting for a few days or weeks,

with quasi-regularly inter-events times of the order of a few minutes or hours, and progressive

changes in amplitude and inter-event times. High-frequency events (around 50 Hz) occur all

over the year, with no clear triggering mechanism, and are located on the lower-part of

glaciers, where ice is at the melting point temperature and the glacier mainly moves by stable

sliding. Low frequency events (around 5 Hz) are mainly located at higher elevations (mainly

above 3000 m asl), on steeper slopes, and have larger magnitudes (-2<m<0). They are mainly

observed during or shortly after snowfalls. At these elevations, glaciers are possibly coldbased,

or close to the melting-point temperature, so that they are stuck to their bed and

mainly deform by creep within the ice. We observe progressive changes in waveforms that

suggest slow and evolving rupture velocities. These low-frequency icequakes may be the

analog of low-frequency earthquakes, which also occur near the transition between stable and

unstable slip.

How to cite: helmstetter, A.: Clusters of low- and high-frequency repeating icequakes in the Mont-Blanc massif, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16571, https://doi.org/10.5194/egusphere-egu23-16571, 2023.

EGU23-1568 | ECS | PICO | GM3.2

How is Indira Sagar Dam Altering the Suspended Sediment Transport in Central Indian Region? 

Pragati Prajapati, Gaurav Meena, Somil Swarnkar, and Sanjeev Jha

The hydraulic structures, such as dams and reservoirs, are built for flood mitigation, drinking & irrigation water supply, and hydropower generation. Despite their positive roles, large dams and reservoirs are well known to trap a significant portion of the incoming sediment fluxes. In turn, sedimentation reduces the reservoir's water storage capacity. The Indra Sagar dam, located in the Narmada River Basin, is the largest reservoir in India (total capacity ~ 12.2 Bm3). Therefore, in this study, our objective is to set up a data-driven, i.e., Generalized Additive Model Location Scale and Shape (GAMLSS) to simulate the impact of the Indira Sagar dam on the downstream sediment transport. The daily sediment and water discharge data are used from 1987 to 2019, from June to November, at upstream and downstream gauge stations. Preliminary analysis reveals a significant alteration in downstream sediment discharge after constructing the Indira Sagar dam. However, the pre-dam period doesn't significantly alter sediment transport behavior. In addition, pre-and post-dam water discharge behaviors do not exhibit considerable alteration. The difference between 5-yearly sediment duration curves reveals around 60% to 95% reduction in high and moderate magnitudes sediment load. Further observation suggests an increase in low sediment magnitude flows downstream after the dam construction from the base period 1989-1993. The significance of the study is that it will help water managers in understanding the dam's water storage capacity, which may be affected due to sediment deposition. It is also crucial to understand the geomorphological changes and implications of less sediment supply in the downstream region. The results obtained from this study will further provide additional insights into evolving flood and drought processes and their forecasting around the dam-affected region. This work is in progress, and further results will be presented at the conference.

How to cite: Prajapati, P., Meena, G., Swarnkar, S., and Jha, S.: How is Indira Sagar Dam Altering the Suspended Sediment Transport in Central Indian Region?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1568, https://doi.org/10.5194/egusphere-egu23-1568, 2023.

EGU23-3135 | ECS | PICO | GM3.2

Feldspar luminescence signal of modern fluvial sediments as a proxy for erosion rates? 

Anne Guyez, Stephane Bonnet, Tony Reimann, clare wilkinson, Sebastien Carretier, Kevin Norton, and Jakob Wallinga

Documenting and quantifying sediment transport in natural system, especially over millennial timescale, is still challenging. Among potential new approaches, recent development has shown that luminescence signal could be used to estimate transport parameters in rivers such as virtual velocity of sediments, storage time or sediment sources (McGuire & Rhodes, 2015; Gray et al., 2018; Gray et al., 2019; Sawakuchi et al., 2018; Guyez et al., 2022).

In this study, we focus on the factors controlling post-infrared feldspar luminescence signals (pIRIR) of modern fluvial sediments in upstream areas. The objective is to examine whether pIRIR equivalent dose distributions relate to landscape erosion rates and associated sediment fluxes. To test this hypothesis, we studied catchments in the Southern Alps of New Zealand (SANZ), one of the world’s most active mountain ranges, with extremely high rates of exhumation and erosion.

For eight catchments of the SANZ, we compared the single-grain pIRIR equivalent dose distributions from modern fluvial sediments with catchment-wide erosion rates obtained using measurements of 10Be cosmogenic nuclide concentration in modern fluvial quartz grains. The latter approach is widely used to quantify catchment-wide erosion rates on millennial time scales.

Using the cosmogenic methods, we found catchment-wide erosion rates ranging from 0.2 to 4.0 mm/yr. The rates increased along the mountain range from South-West to North-East, confirming results by Larsen et al. (2014), and may reflect a tectonic uplift gradient related to northward segmentation of the Alpine fault. In addition, erosion rates on the Western side were higher than the Eastern side, which we attribute to the climatic gradient of the SANZ, related to orographic effect.

We measured single-grain pIRIR equivalent dose (De) distributions at the outlet of each catchment. We calculated (1) the fraction of grains whose luminescence signal is saturated (Bonnet et al., 2019; Guyez et al., 2022), (2) the fraction of well-bleached grains. We also characterized the De distribution using (3) the central age model (CAM; Galbraith et al., 1999) and (4) the bootstrapped minimum age model (BS-MAM; Cunningham & Wallinga, 2012). We found a relationship between those four proxies and erosion rates obtained from 10Be, as well as with suspended sediment yield (Adams, 1980; Hicks et al., 2011) and channel steepness index.

Our study shows that single grain pIRIR equivalent dose distributions reflect erosion and sediment fluxes of a catchment. This new property could be further developed with the perspective to use this proxy as a new independent tool to quantify erosion and transport processes in a wide range of fluvial settings on time scales shorter than cosmogenic methods.

How to cite: Guyez, A., Bonnet, S., Reimann, T., wilkinson, C., Carretier, S., Norton, K., and Wallinga, J.: Feldspar luminescence signal of modern fluvial sediments as a proxy for erosion rates?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3135, https://doi.org/10.5194/egusphere-egu23-3135, 2023.

EGU23-3236 | ECS | PICO | GM3.2

Using a hydroacoustic method to establish continuous time series of suspended sand concentration and grain size in the Isère River, France 

Jessica Laible, Benoît Camenen, Jérôme Le Coz, Guillaume Dramais, François Lauters, and Gilles Pierrefeu

High frequency measurements of the concentration and grain size of suspended sand in rivers remain a scientific challenge due to the strong spatio-temporal variability. Applying a hydroacoustic multi-frequency method can improve temporal resolution compared to the classical approach by solid gauging (water sampling) and provides an interesting surrogate for suspended sediment concentration and grain size in rivers characterized by a bimodal suspension. The aim of this study is to establish time series of concentration and grain size of suspended sand in the Isère River (France) using a hydroacoustic method. Measurements with 400 and 1000 kHz Horizontal Acoustic Doppler Current Profilers (HADCP) are used to determine the acoustic attenuation and backscatter. Using frequent isokinetic water samples obtained with a US P-06 sampler close to the ensonified volume, a relation between the acoustic signal and the sediment concentration and grain size can be determined. In a next step, regular solid gaugings help to establish a relation between the concentration and grain size in the ensonified volume and on average in the river cross-section. Finally, time series of concentration and grain size of suspended sand may be established based on this relation. Results show a good correlation between the concentration of fine-grained sediments and acoustic attenuation as well as between the sand concentration and backscatter. While the acoustic signature of fine sediments is mostly driven by concentration changes, the acoustic signature of the sand fraction is impacted by changes not only in concentration but also in grain size distribution (the median diameter  varying between 150 and 400 µm). The homogeneity of concentration and grain size along the acoustic beam seems to be a main factor for successfully establishing concentration time series based on a cell-by-cell analysis.

How to cite: Laible, J., Camenen, B., Le Coz, J., Dramais, G., Lauters, F., and Pierrefeu, G.: Using a hydroacoustic method to establish continuous time series of suspended sand concentration and grain size in the Isère River, France, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3236, https://doi.org/10.5194/egusphere-egu23-3236, 2023.

EGU23-6550 | ECS | PICO | GM3.2

Machine learning assisted delineation and measurement of grains in sediment images – the potential of transfer learning 

David Mair, Ariel Henrique Do Prado, Philippos Garefalakis, Guillaume Witz, and Fritz Schlunegger

The size of coarse sedimentary particles in fluvial systems is key for quantifying sedimentation and transport conditions in both active and ancient fluvial systems. In particular, the grain size of the bed load in gravel-bed rivers allows inferring information on sediment entrainment or deposition mechanisms, and on the hydraulic conditions controlling them. However, collecting data on such coarse-grained sedimentary particles traditionally involved time-intensive and costly fieldwork, leading to the development of image-based techniques for grain size estimation over the last two decades. Nevertheless, despite much progress and the recent deployment of deep learning methods that were trained on large datasets (i.e., > 100 000 manually annotated grains; Lang et al., 2021; Chen et al., 2022), image-based grain size data is limited to single percentile values, often due to a systematic bias and/or a low accuracy (e.g., Chardon et al., 2020; Mair et al., 2022). Specifically, the core challenge for most existing methods is the accurate segmentation, i.e., the identification and delineation of individual grains, across distinctly different types of data.

Here we present a new approach designated to improve the segmentation in images, which is based on the capability of transfer learning of deep learning models. Such a strategy allows us to re-train existing models for new tasks that are similar to their original purpose. In particular, we use the python-based and open-source tool cellpose (Stringer et al., 2021), which is a state-of-the-art machine-learning model based on neural networks and designed to segment cells in biomedical images. We retrained such a cellpose model on several image datasets of fluvial gravel. The rationale for our approach is based on an inferred geometric similarity between cell nuclei and rock pebbles. Our re-trained models outperform existing methods designed for the segmentation of fluvial pebbles in all datasets, despite an order of magnitude smaller number of training data than currently used in machine learning models. Furthermore, our results show that models trained on specialized datasets for a specific sediment setting yield significantly better results than models trained on larger and more diverse datasets. Fortunately, the model’s flexibility, accessibility, and ability for easy and fast training (Pachitariu and Stringer, 2022) enable the training of task- or image-type-specific models. To facilitate the segmentation power of such models, we built an open-source software tool, ImageGrains. This tool allows for easy use of the models we trained, or of other custom models, as well as streamlined grain size and shape measurements. This allows for fast and nearly automated measurements of large numbers of coarse sedimentary particles with high precision and across vastly different image settings.

References

Chardon, V., et al., 2022: River Res. Appl., 38, 358–367, https://doi.org/10.1002/rra.3910.

Chen, X., et al., 2022: Earth Surf. Dyn., 10, 349–366, https://doi.org/10.5194/esurf-10-349-2022.

Lang, N., et al. 2021: Hydrol. Earth Syst. Sci., 25, 2567–2597, https://doi.org/10.5194/hess-25-2567-2021.

Mair, D., et al. 2022: Earth Surf. Dyn., 10, 953–973, https://doi.org/10.5194/esurf-10-953-2022.

Pachitariu, M. and Stringer, C. 2022: Nat. Methods, 19, 1634–1641, https://doi.org/10.1038/s41592-022-01663-4.

Stringer, C., et al. 2021: Nat. Methods, 18, 100–106, https://doi.org/10.1038/s41592-020-01018-x.

How to cite: Mair, D., Do Prado, A. H., Garefalakis, P., Witz, G., and Schlunegger, F.: Machine learning assisted delineation and measurement of grains in sediment images – the potential of transfer learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6550, https://doi.org/10.5194/egusphere-egu23-6550, 2023.

EGU23-10413 | ECS | PICO | GM3.2

A Study on the Bedload Discharge Estimation using CNN 

Minjin Jung, Kyewon Jun, Sunguk Kim, and Changdeok Jang

Localized torrential rain, which has recently increased in frequency due to abnormal climate, accelerates erosion in the river basin and increases sediment transport into the river. The movement of inflowed sediment is one of the most important factors in the development and management of water resources.

Among the mechanisms of sediment transport in rivers, bedload has limitations in direct measurement due to the risk it poses and inaccuracy in the existing measurement methods. Measurement equipment based on new concepts is continuously being developed to overcome these limitations. A representative equipment is a pipe hydrophone, which indirectly measures the bedload discharge by collecting and analyzing acoustic data when soil collides with a metal tube with a built-in microphone.

To estimate the bedload discharge, this study acquired data through indoor experiment and applied them to the learning process of the Convolutional Neural Networks(CNN). First, an indoor hydraulic experiment device was built with a pipe hydrophone installed at the bottom of the water outlet of the indoor waterway. Then, a system for analyzing and displaying graphs for the impact sound of bedload, and data acquisition storage programs therein, was established. Finally, learning for bedload discharge estimation was conducted using CNN, and the accuracy of the estimation was reviewed.

As a result, the F1-score for the accuracy of bedload discharge estimation was 61%, and the accuracy was higher when bedload discharge was 3kg and 10kg, compared to other weight ranges. Considering that the accuracy of 61% is an insufficient level to completely trust the estimated result, more efficient measurement would be possible by combining this method with the previously developed measurement methods in a complementary manner. In future studies, additional experimental data under various conditions will be secured and applied, to increase the accuracy of bedload discharge estimation.

 

"This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(C20017370001)"

How to cite: Jung, M., Jun, K., Kim, S., and Jang, C.: A Study on the Bedload Discharge Estimation using CNN, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10413, https://doi.org/10.5194/egusphere-egu23-10413, 2023.

EGU23-14522 * | PICO | GM3.2 | Highlight

Tracking coarse sediment in an Alpine subglacial channel using radio-tagged particles 

Stuart N. Lane, Matt Jenkin, Margaux Hofmann, Bryn Hubbard, Davide Mancini, Floreana M. Miesen, and Frederic Herman

Temperate Alpine glaciers produce substantial quantities of sediment that are exported via active subglacial meltwater channels to their proglacial environments. Measurements of suspended sediment and bedload in proglacial rivers have been used to estimate glacial erosion rates and downstream sediment yields, assuming that eroded sediment is rapidly evacuated by flowing meltwater; that subglacial sediment storage remains constant and that the measurements are unaffected by proglacial filtering effects. Studies generally focus on the suspended sediment fraction of export, due to the challenges involved in monitoring coarse sediment transport. It is not surprising that subglacial sediment transport dynamics are poorly understood, and a limited amount of field and model-based research indicates that subglacial sediment transport may be attenuated in the rapidly thinning and retreating snout marginal zones of many Alpine glaciers. This is likely due to the existence of non-pressurised subglacial channels with highly variable transport competence related to diurnal discharge variability, leading to cycles of alluviation and deposition. The potential attenuation of sediment and the unknown relationship between suspended load and bedload has important consequences for estimates of glacial erosion based on proglacial export measurements. 

Here, we present results from a proof-of-concept for a method to track radio-tagged bedload particles through meltwater channels under shallow temperate glacier ice (<50 m). Active radio transmitters were inserted into natural pebbles and then deployed directly via boreholes into a 10 m wide snout-marginal subglacial channel at the Glacier d'Otemma, Switzerland. A roving antenna at the surface was used daily to estimate the planimetric point location and downstream transport distance of each tagged particle using Kernel Density Estimation (KDE) as it moved downstream through the subglacial channel. In addition, stationary antennas on the glacier surface monitored the passage of the particles through successive reaches of the subglacial and proglacial channel, constraining the timing of particle transport events. The roving and stationary antenna data were combined to create a transport distance model for each particle, which, when applied at scale, may be used in conjunction with river gauging data to examine the drivers and timescales of coarse subglacial sediment transport. We present results that confirm this method as a highly original means of quantifying subglacial sediment transport using particle tracking.

How to cite: Lane, S. N., Jenkin, M., Hofmann, M., Hubbard, B., Mancini, D., Miesen, F. M., and Herman, F.: Tracking coarse sediment in an Alpine subglacial channel using radio-tagged particles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14522, https://doi.org/10.5194/egusphere-egu23-14522, 2023.

EGU23-14870 | PICO | GM3.2 | Highlight

Smart cobbles and boulders for monitoring movement in rivers and on hillslopes 

Kyle Roskilly, Georgina Bennett, Miles Clark, Aldina Franco, Martina Egedusevic, Robin Curtis, Joshua Jones, Michael Whitworth, Chunbo Luo, and Irene Manzella

Constraining the initiation of bedload sediment transport in rivers is of fundamental importance to understanding a range of geomorphic processes. Likewise, on hillslopes, identifying the initiation of movement is a vital first step towards developing early warning systems for hazards such as landslides. Several studies have previously experimented with embedding sensors within cobbles and boulders to capture and characterise their initiation and subsequent movement in the laboratory and in the field (both for hillslopes and riverbeds). However, these sensors have been limited by their battery life and/or lack of wireless sensor communication in their ability to monitor movement in natural settings over extended time periods. Accelerometers have been most widely applied, e.g. to detect bedload movement on a river bed, but can only measure vibrations and partial changes in orientation between stationary periods, which can occur simply during shaking of a cobble in its pocket on the bed. Gyroscopes, which can assist in continuous orientation tracking and therefore identification of actual transport (e.g. rolling of a cobble along a riverbed), have higher power consumption.

On SENSUM (smart SENSing of landscapes Undergoing hazardous hydrogeomorphic Movement), we have leveraged advances in micro-electronics and Internet of Things technologies to develop a low-power inertial measurement sensor that communicates in near real-time via Long Range Wide Area Network (LoRaWAN). The sensor includes accelerometers, gyroscopes and magnetometers and laboratory experiments have already shown their potential to differentiate between sliding and rolling behaviour. We have embedded sensors in natural and manmade boulders (SlideCubes), cobbles and wood debris within several landslide and flood prone sites across the UK. The sensors form part of Wireless Sensor Networks that also consist of LoRaWAN gateways and other sensors such as discharge gauges.

We present field data captured from smart cobbles installed in upland rivers on Dartmoor and Cumbria that demonstrate the potential of SENSUM sensors to detect initiation of bedload transport, i.e. the transition from shaking of a cobble in its pocket to downstream transport by rolling and/or saltation. We also present preliminary data of landslide movement captured by sensors installed in SlideCubes at Lyme Regis and Isle of Wight. Moving forwards, we will use machine learning methods to analyse sensor data on the server in near real-time in order to characterise and alert of hazardous movement.

How to cite: Roskilly, K., Bennett, G., Clark, M., Franco, A., Egedusevic, M., Curtis, R., Jones, J., Whitworth, M., Luo, C., and Manzella, I.: Smart cobbles and boulders for monitoring movement in rivers and on hillslopes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14870, https://doi.org/10.5194/egusphere-egu23-14870, 2023.

EGU23-14960 | ECS | PICO | GM3.2 | Highlight

The use of optical camera for river turbidity monitoring 

Domenico Miglino, Seifeddine Jomaa, Michael Rode, Francesco Isgro, Khim Cathleen Saddi, and Salvatore Manfreda

Improving river monitoring techniques is critical given the concomitant impact of climate change, population growth, and pollution over the last years. Turbidity is one of the most significant metrics for water quality characteristics. In river basins, high turbidity values can be indicative of both organic and inorganic materials. Turbidity is often used as a proxy for transport of suspended particles and associated fluxes of hydrophobic pollutants in a wide range of hydrological conditions. However, it is demanding to estimate suspended sediment yields in rivers because of the high variability along stream of suspended sediment concentrations. Traditional methods, such as gravimetric analysis, are time-consuming, expensive, often discontinuous in space and time and influenced by human errors or instrumental limitations.

Remote sensing techniques are a suitable alternative to point measurements. Satellite remote sensing allows to study the spatial and temporal variations of water status parameters, but it is limited by the spatial and temporal resolution of the satellites considered. Low range systems can help increase the resolution of the imagery used for this purpose. In particular, the use of optical cameras can significantly reduce the monitoring cost and exponentially increase the information on water bodies health and hydrological dynamics, offering a large amount of data distributed in time and space. Nonetheless, all optical sensing methods are strongly affected by many environmental constraints (light, good optical transmission, visibility, etc.), which make them currently not always suitable for regular long-term monitoring of turbidity in rivers. 

The main goal of the monitoring procedure identified in this work is to avoid all these constraints, by processing the camera image to use it as a real measurement data. In this work, an image processing procedure has been identified by exploiting the water surface reflectance properties to estimate water turbidity spectral indices related to red and green bands of the light visible spectrum (Miglino et al., 2022). This river monitoring system is under development in different cross sections of the Bode River, one of the best-instrumented catchments in Central Germany.managed by UFZ Helmholtz Centre for Environmental Research. They gather a wide range of environmental data including a long-term time series on water quantity and quality. Preliminary results highlighted interesting similarities between the chromatic variation of the water surface captured by the RGB camera and the real data. 

 

Keywords: turbidity, sediment transport, image processing, spectral indices, remote sensing, camera, water quality assessment.

 

References:

Miglino, D., Jomaa, S., Rode, M., Isgro, F., & Manfreda, S. (2022). Monitoring Water Turbidity Using Remote Sensing Techniques. Environmental Sciences Proceedings, 21(1), 63.

How to cite: Miglino, D., Jomaa, S., Rode, M., Isgro, F., Saddi, K. C., and Manfreda, S.: The use of optical camera for river turbidity monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14960, https://doi.org/10.5194/egusphere-egu23-14960, 2023.

EGU23-15456 | ECS | PICO | GM3.2

A Precipiton-Based Approach for Multi Grain-Size Transport Models 

Marine Le Minor, Philippe Davy, Jamie Howarth, and Dimitri Lague

Multi grain-size transport models that simulate transport of various grain sizes along with the bed stratigraphy consider that only the sediment present in an active layer at the top of the substratum participates in sediment transport. The thickness of this well-mixed layer may be fixed but also calculated according to the coarsest grain size it contains or to the shear stress applied at the surface of the substratum. However, this approach puts the emphasis on the conservation of the active layer thickness and on the availability of the various sizes within this layer. This means there is little consideration i) for heterogeneity in grain size distribution when mixing together adjacent stratigraphic layers that differ significantly in composition and ii) for grain sizes that could prevent or slow down removal of the others. To cope with these limitations, we developed an algorithm with the ability to capture the transport of heterogeneous sediments and the related stratigraphic record of erosional and depositional events based on the behavior of the various sizes within the bed layers. We built a multi grain-size module based on the precipiton method: the time spent by a precipiton (volume of water that carries sediment) on a pixel determines the grain-size specific magnitude of deposition and erosion. The newness of our work is that the magnitudes of erosion may be corrected according to the sizes that slow down the erosion of the others (zero or slow erosion rate) and stratigraphic layers with similar composition only may be merged. A few tests were conducted to study the morphological evolution of a 1D-river reach under various conditions (water discharge, sediment source, etc.). A lake was added at the end of the reach to record the various sizes existing the reach over time. At low water discharge when only the threshold of fine grains is exceeded, an armoring layer made of coarse grains develop at the surface of the substrate. At a water discharge when all the grains are in motion, the finer the grains are, the further downstream they are transported. This downstream fining pattern may be associated with changes in the concavity of the river profile. This multi grain-size algorithm not restricted to the precipiton approach has the potential to unravel the role of heterogeneous sediments in the formation of sorting patterns and, therefore, it is to be implemented in the landscape evolution model RiverLab (former Eros). 

How to cite: Le Minor, M., Davy, P., Howarth, J., and Lague, D.: A Precipiton-Based Approach for Multi Grain-Size Transport Models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15456, https://doi.org/10.5194/egusphere-egu23-15456, 2023.

EGU23-16276 | ECS | PICO | GM3.2

Smart sensors to detect movements of cobbles and large woody debris dams. Insights from lab experiments. 

Alessandro Sgarabotto, Irene Manzella, Alison Raby, Kyle Roskilly, Martina Egedusevic, Diego Panici, Miles Clark, Sarah J. Boulton, Aldina M. A. Franco, Georgina L. Bennett, and Chunbo Luo

An increase in population pressure and severe storms under climate change have greatly impacted landslide and flood hazards globally. At the same time, recent advances in Wireless Sensor Network (WSN) and Internet of Things (IoT) technologies, microelectronics and machine learning offer new opportunities to effectively monitor stability of boulder and woody debris on landslides and in flood-prone rivers. In this framework, smart sensors embedded in elements within the landslide body and the river catchment can be potentially used for monitoring purposes and for developing early warning systems. This is because they are small, light-weight, and able to collect different environmental data with low battery consumption and communicate to a server through a wireless connection. However, their reliability still needs to be evaluated. As data from field sites could be fragmented, laboratory experiments are essential to validate sensor data and see their potential in a controlled environment. In the present study, dedicated laboratory experiments were designed to assess the ability of a tag equipped with an accelerometer, a gyroscope, and a magnetometer to detect movements in two different settings. In the first experimental campaign, the tag was installed inside a cobble of 10.0 cm diameter within a borehole of 4.0 cm diameter. The experiments consisted in letting the cobble fall on an experimental table composed of an inclined plane of 1.5 m, followed by a horizontal one of 2.0 m. The inclined plane can be tilted at different angles (18˚- 55˚) and different types of movement have been generated by letting the cobble roll, bounce, or slide. Sliding was generated by embedding the cobble within a layer of sand. The position of the cobble travelling down the slope was derived from camera videos by a tracking algorithm developed within the study. In the second experimental campaign, a simplified analogue model of a woody debris dam was built from a single hollowed dowel with a length of 40 cm and a diameter of 3.8 cm. The sensor tag is installed in the woody dowel within a 2.5 cm longitudinal borehole. Two metal rigs are mounted at both sides of the woody dowel to allow different modes of movement. Specifically, the woody dowel is allowed to move either horizontally or vertically within a range of 20-30 mm, whereas it is always free to complete full rotations. The woody dowel is mounted on a frame within a 20 m long and 0.6 m wide flume. In these two experimental settings, combining data from the accelerometer, gyroscope and magnetometer it was possible to detect movements and differentiate between different type of motions both in a woody dowel and in the cobble under different initial conditions. Data were analysed to understand which type of information could be retrieved. This gives important insights for the assessment of the feasibility and effectiveness of the use of smart sensors in the detection of movements in woody logs within dams and boulders embedded in landslides, thus providing indications for the development of early warning systems using this innovative technology.  

How to cite: Sgarabotto, A., Manzella, I., Raby, A., Roskilly, K., Egedusevic, M., Panici, D., Clark, M., Boulton, S. J., Franco, A. M. A., Bennett, G. L., and Luo, C.: Smart sensors to detect movements of cobbles and large woody debris dams. Insights from lab experiments., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16276, https://doi.org/10.5194/egusphere-egu23-16276, 2023.

EGU23-1884 | ECS | Orals | GI5.4

Comparison of DAS surface waves records at geotechnical scales using telecom fiber optic with different cable and ground coupling 

Ianis Gaudot, Matéo Leroy, Adnand Bitri, and François Bretaudeau

It is now established that existing telecom fiber optic cables (FOC) may be used to record interpretable DAS seismic signals at seismological and reservoir scales, but their use at geotechnical scales remains an active topic of research.

In this work, we present a comparison study of DAS surface waves records on a 600 m long FOC containing both tight and loose standard fiber optics spliced between each other. 2x300 m portion of the FOC are deployed next to each other horizontally at 40 cm depth in a shallow trench located along a road. The first 300 m portion of the FOC lays on the bottom of a PVC pipe (gravity coupling), and the second 300 m portion of the FOC is buried in the soil (soil coupling) ; so that a total of 4 couplings is tested along an optical path totalizing 1200 m: (1) gravity coupling on loose fiber optic, (2) soil coupling of loose fiber optic, (3) gravity coupling on tight fiber optic, and (4) soil coupling on tight fiber optic. We performed hammer shots recorded using DAS with 2.4 m, 4 m, 6 and 10 m gauge length. The resulting DAS data are compared to data from standard vertical and horizontal geophones regularly spaced along the line, as well as data from gimbal mounted vertical geophones towed behind a vehicle along the line.

Our results show that gravity coupling on loose fiber optic using gauge length shorter than 5 m gives interpretable surface waves dispersion image up to 50 Hz for the fundamental Rayleigh wave mode, with a quality which is competitive with results from gimbal data. Therefore, our results suggest that the leveraging of existing telecom FOC for low-cost and fast geotechnical characterization is promising.

How to cite: Gaudot, I., Leroy, M., Bitri, A., and Bretaudeau, F.: Comparison of DAS surface waves records at geotechnical scales using telecom fiber optic with different cable and ground coupling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1884, https://doi.org/10.5194/egusphere-egu23-1884, 2023.

EGU23-2106 | Posters on site | GI5.4

Combined migrations and time-depth conversions: first results 

Raffaele Persico, Gianfranco Morelli, Giuseppe Esposito, and Ilaria Catapano

Commonly exploited migration algorithms or also well-established linear inverse scattering algorithms [1] for the focusing of GPR data are often based on the hypothesis of a homogeneous soil. However, this assumption is not valid always, and it provides deformed results when it is applied to image scenarios where it is not valid. More complex models of the scattering can afford the situation of a stratified medium, but only if the layers are flat and parallel to each other these model assumes analytic forms. In any case, commonly available commercial codes do not allow to implement the reflections and refraction of the waves associated to these cases [2]. More recently, time reverse migration algorithms have been introduced. They can account efficiently of non-homogeneous soils, but their performances in case of large and strong scattering targets are not yet completely established and they make use of forward numerical solvers, not all the times available and user friendly. At the conference, we will describe a strategy based on suitable combination of migration results achieved from different homogeneous media, accompanied by a time-depth conversion accounting for the occurrence of different values of the wave propagation velocity in the investigated domain. We will show how an improvement of the imaging result is achieved even in the lack of a correct mathematical model of the scattering phenomenon. Last but not least, the proposed strategy exploits software routines easy to be implemented.

How to cite: Persico, R., Morelli, G., Esposito, G., and Catapano, I.: Combined migrations and time-depth conversions: first results, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2106, https://doi.org/10.5194/egusphere-egu23-2106, 2023.

EGU23-5339 | Posters virtual | GI5.4

Quantitative inverse scattering analysis for ground penetrating radar imaging 

Alessandro Fedeli, Valentina Schenone, Matteo Pastorino, and Andrea Randazzo

The inspection of underground scenarios is a challenging task required in several applications, from geophysical to archeological and civil areas. The ground penetrating radar (GPR) is a common tool that has been widely adopted to provide qualitative imaging of the underground scenario [1]. Recently, several approaches to process GPR data and retrieve quantitative images to characterize the inspected region have been developed [2-3]. Moreover, to compensate for the loss of information that usually happens in this scenario, GPR systems have been implemented not only in monostatic and bistatic configurations but also in multistatic settings [4].

In this contribution, a quantitative inverse scattering approach is proposed to retrieve the distribution of the complex dielectric permittivity of a buried region, starting from scattering parameters collected through a multistatic GPR configuration. The approach is based on a finite-element (FE) formulation of the electromagnetic inverse scattering problem and, as solving procedure, a reconstruction method in variable exponent Lebesgue spaces is adopted [5]. On the one hand, the FE model embedded in the method is exploited to describe the structure of the measurement configuration without simplifying assumptions (except for the two-dimensional hypotheses and the numerical discretization of the problem). On the other hand, the inversion procedure in variable exponent Lebesgue spaces has been found quite effective to face the ill-posedness and nonlinearity of the problem. A numerical validation of this approach is reported.

 

References

[1] R. Persico, “Introduction to ground penetrating radar: Inverse scattering and data processing.” Hoboken, New Jersey: Wiley, 2014.

[2] M. Pastorino and A. Randazzo, “Microwave imaging methods and applications.” Boston, MA: Artech House, 2018.

[3] V. Schenone, A. Fedeli, C. Estatico, M. Pastorino, and A. Randazzo, “Experimental assessment of a novel hybrid scheme for quantitative GPR imaging”, IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1–5, 2022.

[4] M. Ambrosanio, M. T. Bevacqua, T. Isernia, and V. Pascazio, “Performance analysis of tomographic methods against experimental contactless multistatic ground penetrating radar”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1171–1183, 2021.

[5] V. Schenone, C. Estatico, G. L. Gragnani, M. Pastorino, A. Randazzo, and A. Fedeli, “Microwave-based subsurface characterization through a combined finite element and variable exponent spaces technique”, Sensors, vol. 23, no. 1, p. 167, 2023.

How to cite: Fedeli, A., Schenone, V., Pastorino, M., and Randazzo, A.: Quantitative inverse scattering analysis for ground penetrating radar imaging, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5339, https://doi.org/10.5194/egusphere-egu23-5339, 2023.

EGU23-9597 | Orals | GI5.4

Increasing the sampling density of 3D GPR data using multiple-point geostatistics 

James Irving, Chongmin Zhang, Mathieu Gravey, and Grégoire Mariéthoz

3D GPR data, where measurements are acquired along a series of parallel survey lines, offer much potential for gaining important information about complex subsurface environments. Such data are, however, extremely time consuming to collect, and a typical trade-off is that the survey line spacing is set to be significantly larger than the trace spacing along the lines. This introduces a strong resolution bias in the 3D dataset, and spatial aliasing is commonly present in the across-line direction. Although simple interpolation methods may be considered to address this problem, they generally lead to overly smoothed and unrealistic results.

Here, we present a means of overcoming this issue via multiple-point geostatistics (MPS) simulation. Considering that we have a limited number of sparsely distributed 2D GPR profiles to begin with, we reconstruct the densely spaced 3D GPR data set using a series of separate 2D simulations in both the along-line and across-line directions. Training images, which are necessary for the application of MPS, come from the existing GPR profiles. To deal with the discontinuities in 3D spatial structures caused by performing independent 2D simulations, target profiles are selected randomly but simulations are performed alternately in both directions. Test results show that this methodology provides significantly better reconstructions than standard interpolation, in particular as the spacing between the GPR survey lines increases.

How to cite: Irving, J., Zhang, C., Gravey, M., and Mariéthoz, G.: Increasing the sampling density of 3D GPR data using multiple-point geostatistics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9597, https://doi.org/10.5194/egusphere-egu23-9597, 2023.

EGU23-10974 | Orals | GI5.4 | Highlight

Ground Penetrating Radar for the Detection of Vertebrate Fossils: An Example from the Ica Desert Fossil-Lagerstätte 

Annalisa Ghezzi, Antonio Schettino, Alberto Collareta, Claudio Nicola Di Celma, Pietro Paolo Pierantoni, and Luca Tassi

The Ica Desert of southern Peru presents one of the most important marine Lagerstätten worldwide, characterized by excellent preservation and abundance of outcropping vertebrate fossils of whales, sharks, and dolphins. Even more fossils are potentially buried at shallow depth, which could be exposed by excavation and become the focus of new paleontological research. We investigated a small area at the top of Cerro Los Quesos, one of the most rich fossil-bearing localities in the Ica Desert, formed by sub-horizontal layers of diatomaceous sediments belonging to the Pisco Formation. Although most of these sediments are fine-grained, specific geochemical processes that occured in this area determined the formation of several beds of coarse cemented material, populated by large dolomitic nodules and underlain by two characteristic layers: a black manganese oxyde lamina and a thin reddish dolomite enriched in iron oxyde. Most of the fossils outcropping in the Ica Desert appear to be incapsulated in large dolomitic nodules, which can also be detected at shallow depth by ground penetrating radar (GPR) techniques. Here we describe an approach that can be used to identify the presence of fossils using a GPR system, which requires a detailed analysis of radar profiles and traces. In particular, it is shown that a sequence of distinctive reflected wavelets characterizes the bottom of the dolomitic nodules that wrap the skeletons

How to cite: Ghezzi, A., Schettino, A., Collareta, A., Di Celma, C. N., Pierantoni, P. P., and Tassi, L.: Ground Penetrating Radar for the Detection of Vertebrate Fossils: An Example from the Ica Desert Fossil-Lagerstätte, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10974, https://doi.org/10.5194/egusphere-egu23-10974, 2023.

Endangered burrowing mammals are good indicators of ecosystem quality as they frequently play a crucial role in the functioning of grassland ecosystems, maintaining their diversity, functions, or services. However, the non-destructive estimation of their population size, spatial and temporal population dynamics remains a challenge. The number of burrow openings is a good proxy for estimating actual population sizes if one individual occupies one burrow system and the ratio of openings per burrow system is known. Remote, semi-automated counting of animals’ surface burrows has been successful, and we now focus on detecting subsurface animal burrows. For this purpose, we investigate the applicability of GPR surveys to non-destructively identify and locate artificial burrows of the same size dimensions as burrows of protected ground squirrels.  Based on the results we present an approach to non-invasively map ground squirrel burrows.

A Mala system with 160 and 750MHz antennas was used for the GPR surveys. Artificial burrows (ABs) (5-7cm wide, 1m long) were drilled in the wall of a ditch (depth of 2m, length of 20m). Each burrow location was known and placed between 5 and 160cm depth perpendicular to the direction of the GPR survey. Burrow locations were marked both in the field and radargram. The survey area was a grassland (similar to natural ground squirrel habitats) with short vegetation and even ground surface.

A standard processing of the raw GPR data was used in Reflexw2D, including: compressing original data (deleting every 2nd trace), bandpass filtering, time-zero correction using the automatic correct max phase option, and move-starttime. Processed radargrams were also (fk) migrated and gain adjusted for better display of burrows on images. The last step was the time-depth conversion with constant velocity of 0.1 m/ns. The processing sequence was saved and applied to each raw data file with the same data acquisition parameters.

Preliminary results indicate that although many of ABs can be found through the use of GPR, this method has some drawbacks. Penetration depth was limited to less than 150cms. Since, sousliks dig deeper in the soil, that depth could be one of the limiting factors in mapping entire burrow systems. A general difficulty of locating ABs was that ABs’ reflections were often indistinguishable from unknown subsurface objects despite the prior knowledge of their exact location in the soil. Although reverse polarity of the reflected wave was expected due to the air-filled burrows in the soil, the data did not show this phenomenon clearly. ABs in the upper ~30cm, opposite to ABs deeper, were identifiable more with less plotscale colour intensity.

In summary, while some ABs were detected by GPR, many were not, even though their exact location was known. This experience has indicated a different approach for mapping animal burrows may be necessary. Multiple-point geostatisitcs (MPS) could be a good approach for modelling non-linear burrows. Information about burrows can be obtained from burrow maps used as training images could be combined with GPR data to enable modelling of multiple-point relations and complex zig-zag patterns.

How to cite: Gedeon, C., Szatmari, G., Árvai, M., Sherrod, L., and Meszaros, J.: Preliminary results of the study of using ground-penetrating radar (GPR) as a tool to locate artificial burrows similar to souslik burrows and future directions of mapping burrow systems of sousliks or other burrowing mammals alike, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11627, https://doi.org/10.5194/egusphere-egu23-11627, 2023.

EGU23-12013 | ECS | Posters on site | GI5.4

Benchmark of multiple non-invasive electrodes for a relevant use in urban environments 

Tom Debouny, David Caterina, and Frédéric Nguyen

Over time, urbanized areas have undergone continuous development and growth as they adapt to the changing needs of their residents. This has often involved the construction of new buildings, roads, and infrastructures, as well as the renovation and expansion of existing structures. Subsurface characterization is thus a crucial aspect of urban development, as it is essential for the planning, construction and monitoring of new or existing infrastructures. Urbanized environments may be challenging for conventional subsurface characterization methods such as drilling or excavation due to difficulty of access or the presence of buried networks that are not always properly mapped. Geophysical methods can be seen as an interesting alternative to these traditional characterization approaches but require to be adapted to work properly in such environment. This led to the development of the urban geophysics discipline.

Among the different geophysical methods available, Electrical resistivity tomography (ERT) appears as a useful and robust tool for studying subsurface materials and structures in urban environments. It has already been used to investigate underground utilities such as tunnels, cellars, pipes, tank storages and building foundations as well as natural structures. While ERT minimizes site disturbance, the use of fully non-invasive electrodes is sometimes required for the preservation of investigated sites. The best example remains the investigation of archeological structures. For that purpose, a diversity of non-invasive electrodes such as flat electrodes, bentonite mud or conductive gel has already been used overtime for different purposes but showed different outcomes in terms of contact resistance, measurement uncertainty, durability or signal to noise ratio. To our knowledge, few systematic comparison has been done between the different types of non-invasive electrodes and their impact in terms of imaging/monitoring in specific conditions for urban applications.

The present study proposes an assessment of the use of different non-conventional electrodes on various surfaces often encountered in urban environments at controlled lab-scale. The tested electrodes can be divided into two main categories, the electrolytic and the weight electrodes. The analysis focuses on contact resistance, electrical current transmission, noise measurements, strength and stability of the signal over time. The ease and time of deployment are also taken into account for future uses in larger scale fieldworks. Based on preliminary results, the electrodes based on electrolytic contact demonstrate better performances in highly resistive environments, where a better grounding resistance can globally be achieved compared to weight-based electrodes. However, their implementation are more fastidious slowing the acquisition.

How to cite: Debouny, T., Caterina, D., and Nguyen, F.: Benchmark of multiple non-invasive electrodes for a relevant use in urban environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12013, https://doi.org/10.5194/egusphere-egu23-12013, 2023.

EGU23-12688 | Posters on site | GI5.4

A microwave tomographic approach for contactless Multiple Input Multiple Output GPR systems 

Francesco Soldovieri, Gianluca Gennarelli, Giovanni Ludeno, Giuseppe Esposito, and Ilaria Catapano

Nowadays, Ground Penetrating Radar (GPR) systems working in contactless way deserve huge attention because, if mounted onboard of moving platforms like terrestrial and aerial vehicles, they allow the collection of a large amount of data, while keeping low complexity and time of the measurement step [1,2]. At the same time, multiple input multiple output (MIMO) GPR systems are worth being exploited because, being capable of gathering multiview and multistatic data, they allow an improvement of the reconstruction capabilities [3, 4]. However, the effective use of a contactless MIMO GPR requires the availability of properly designed data processing strategies able to manage the information acquired by this kind of systems and to provide an accurate reconstruction of the scenario under test.

This contribute proposes a microwave tomographic approach, which faces the GPR imaging as a linear inverse scattering problem and it is suitable to process contactless multi-view and multi-static data. The approach is referred to the 2D scalar case, exploits a ray-based model of the scattering phenomenon, and accounts for the presence of the air-soil interface. Specifically, the approach extends to the case of MIMO systems the concept of the Interface Reflection Point (IPR) previously exploited to process contactless data gathered by means of a multi-monostatic GPR [2,5].

At the conference, the approach formulation will be described in detail and results referred to virtual experiments will be provided in order to state the achievable imaging capabilities.

[1] Miccinesi, L., Beni, A., & Pieraccini, M. (2022). UAS-Borne Radar for Remote Sensing: A Review. Electronics, 11(20), 3324.

[2] Catapano, G. Gennarelli, G. Ludeno, C. Noviello, G. Esposito, and F. Soldovieri, "Contactless ground penetrating radar imaging: state of the art, challenges, and microwave tomography-based data processing," IEEE Geosci. Rem. Sens. Mag., vol. 10, no. 1, pp. 251-273, 2022.

[3] García-Fernández, M., López, Y. Á., & Andrés, F. L. H. (2020). Airborne multi-channel ground penetrating radar for improvised explosive devices and landmine detection. IEEE Access, 8, 165927-165943.

[4] Leone, G., & Soldovieri, F. (2003). Analysis of the distorted Born approximation for subsurface reconstruction: Truncation and uncertainties effects. IEEE Transactions on geoscience and remote sensing, 41(1), 66-74.

[5] Catapano, L. Crocco, Y. Krellmann, G. Triltzsch, and F. Soldovieri, “Tomographic airborne ground penetrating radar imaging: achievable spatial resolution and on-field assessment,”, ISPRS J. Photogram. Remote Sens., vol. 92, pp. 69–78, June 2014.

How to cite: Soldovieri, F., Gennarelli, G., Ludeno, G., Esposito, G., and Catapano, I.: A microwave tomographic approach for contactless Multiple Input Multiple Output GPR systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12688, https://doi.org/10.5194/egusphere-egu23-12688, 2023.

EGU23-12812 | Posters on site | GI5.4 | Highlight

Water pipe monitoring via fiber optical sensor and ground penetrating radar: a joint laboratory experiment 

Ilaria Catapano, Giovanni Ludeno, Gianluca Persichetti, Romeo Bernini, and Lorenzo Crocco

Effective usage of water resources is a relevant topic to move towards smart and resilient cities, and it demands technologies aimed at monitoring water distribution networks at avoiding wastefulness and assuring environmental safety.

In this frame, research activities designing technological solutions assuring time-constant monitoring and, simultaneously, providing high spatial resolution images from which infer accurate information about the position and extension of the leakage are carried out.

Being this request difficult to be satisfied by means of a single sensor, the pursued idea is the joint and cooperative use of the distributed optical fiber sensor based on the Brillouin scattering phenomenon [1] and the microwave tomography (MWT) enhanced ground penetrating radar (GPR) [2]. The first technology, if integral to the pipe, is able to detect temperature and/or thermal conductivity variations occurring in the soil hosting the pipe and due to water leakages. Therefore, it appears suitable to assure continuous monitoring and to provide low spatial resolution information about leakage detection. Conversely, GPR allows on-demand non-invasive surveys providing high spatial resolution images of the investigated scenario, if the collected raw data are processed properly. An effective way to do it is the use of MWT approaches, which face GPR imaging as an inverse scattering problem [3].

In order to provide a proof of concept assessing the benefits and limits of the cooperative use of the above technologies, a joint experimentation was carried out. Specifically, an ad-hoc experimental scenario allowing to reproduce a water leakage was built. The scenario is a scaled reproduction of a realistic test case and a plastic pipe filled with fresh water and buried in a river-sand terrain makes it up. The optical fiber sensor was buried in the sand few cm underneath the pipe, while GPR data were collected along and across directions with respect to the pipe.

The achieved results confirmed the expected potentialities and encourage going on this activity.

A detailed presentation of the experimental setup and the achieved results will be provided at the conference.

Acknowledgment: The authors would like to thank the SMART WATERTECH project “Smart Community per lo Sviluppo e l’Applicazione di Tecnologie di Monitoraggio e Sistemi di Controllo Innovativi per il Servizio Idrico Integrato” by which the present work has been financed.

 

[1] Bernini R., Minardo A., Zeni L. (2004) Accuracy enhancement in Brillouin distributed fiber-optic temperature sensors using signal processing techniques, IEEE Photonics Technology Letters 16 (4), pp. 1143-1145.

[2] Catapano, I., Gennarelli, G., Ludeno, G., Persico, R., Soldovieri, F. (2019). Ground Penetrating Radar: Operation Principles and Data, Wiley Encyclopedia of Electrical and Electronics Engineering.

[3] Catapano, I., Palmeri, R., Soldovieri, F., Crocco, L. (2022). GPR Water Pipe Monitoring and Leaks Characterization: A Differential Microwave Tomography Approach. In: Di Mauro, A., Scozzari, A., Soldovieri, F. (eds) Instrumentation and Measurement Technologies for Water Cycle Management. Springer Water. Springer, Cham.

How to cite: Catapano, I., Ludeno, G., Persichetti, G., Bernini, R., and Crocco, L.: Water pipe monitoring via fiber optical sensor and ground penetrating radar: a joint laboratory experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12812, https://doi.org/10.5194/egusphere-egu23-12812, 2023.

EGU23-14265 | Posters virtual | GI5.4

Employment of multiple GPR surveys in urban area, as part of the ERC Rome Transformed project. 

Salvatore Piro, Daniela Zamuner, Daniele Verrecchia, and Tommaso Leti Messina

Important research and technical issues are related to the prospection in urban area to locate subsurface cavities and/or archaeological remains and to produce hazard mapping. In many cases, cavities, voids and collapses represent disruptions to the geometry of an originally near-horizontal layered system. Geophysical techniques can be employed to identify the feature geometries by contrasts in the physical properties, but can be strongly conditioned by cultural features that interfere with instrument measurements (utilities, structures, surficial debris).

The most promising non-destructive geophysical prospection method for use in urban area is GPR. GPR measurements are less affected by the presence of metallic structures compared to magnetometer prospection and they result in the largest amount of data of all commonly employed near-surface geophysical methods, providing detailed three-dimensional information about the subsurface [1], [4]. In thist paper the surveys made with GPR to investigate different sites in the area of S. Giovanni in Laterano and Santa Croce in Gerusalemme in Rome, as part of the ERC funded Rome Transformed project (2019-2024) are presented and discussed. The aim of the GPR survey is to identify Roman and high-medieval age remains which could enhance understanding of the ancient topography and the urban evolution of the study area.

For the surveys a GPR SIR3000 (GSSI), equipped with a 400 MHz (GSSI) bistatic antenna with constant offset, a 70 MHz (Subecho Radar) monostatic antenna and a SIR4000 system equipped with dual frequency antenna with 300/800 MHz were employed.

All the GPR profiles were processed with GPR-SLICE v7.0 Ground Penetrating Radar Imaging Software. The basic radargram signal processing steps included: (i) post processing pulse regaining; (ii) DC drift removal; (iii) data resampling; (iv) band pass filtering; (v) background filter and (vi) migration. With the aim of obtaining a planimetric vision of all possible anomalous bodies, the time-slice representation technique was applied using all processed profiles up to a depth of about 2.5 m, [2], [3]. Ground Penetrating Radar (GPR) survey at the selected areas has produced significant and fruitful results that will be discussed during the presentation.

 

References

1 - I. Trinks, P. Karlsson, A. Biwall and A. Hinterlaitner, Mapping the urban subsoil using ground penetrating radar – challenges and potentials for archaeological prospection, ArchaeoScience, revue d’archeometrié, 2009, suppl. 33,  pp. 237-240.

2 - D. Goodman and S. Piro, GPR Remote sensing in Archaeology, 2013, Springer (Ed), ISBN 978-3-642-31856-6, ISBN 978-3-642-31857-3 (eBook), DOI 10.1007/978-3-642-31857-3. Springer, Berlin, (Germany).

3 - S. Piro S. and D. Goodman, Integrated GPR data processing for archaeological surveys in urban area. The case of Forum (Roma, Italy), 2008, 12th International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK. Proceedings Extanded Abstract Volume.

4 - Piro S., Zamuner D., 2016. Investigating the urban archaeological sites using Ground Penetrating Radar. The cases of Palatino Hill and St John Lateran Basilica (Roma, Italy). Acta IMEKO, Vol. 5, issue 2, pp 80-85. ISSN: 2221-870X. DOI: 10.21014/acta imeko/v5i2.234 .

 

How to cite: Piro, S., Zamuner, D., Verrecchia, D., and Leti Messina, T.: Employment of multiple GPR surveys in urban area, as part of the ERC Rome Transformed project., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14265, https://doi.org/10.5194/egusphere-egu23-14265, 2023.

EGU23-14429 | ECS | Orals | GI5.4

Applied geophysics for regeneration of past metallurgical sites 

Marc Dumont, Itzel Isunza Manrique, Hadrien Michel, Tom Debouny, David Caterina, and Frédéric Nguyen

Ancient metallurgical sites, such as those found in post-industrial cities, present both challenges and opportunities for the development of resilient cities. The legacy of these industries, including mining, smelting, and blast furnace, has left behind vast quantities of residues in the form of unrecorded slag heaps. The challenge of those ancient metallurgical sites is to combine the remediation of the polluted soil while leveraging the valuable resources it contains to support sustainable economic development. This requires a detailed understanding of the structure and composition of the slag heaps in order to safely and effectively extract valuable materials while minimizing environmental impacts.

For decades, the regeneration of past metallurgical sites has relied on extensive drilling surveys and geochemical analysis. However, this approach has proven to be costly, time-consuming, and potentially hazardous for the operators involved. In this context, we present an integrated methodology for characterizing slag heaps using non-invasive geophysics. Developed as part of the NWE-REGENERATIS Interreg project, our approach consists of four main steps: (i) historical studies of the site activities and deposits to identify areas of interest, (ii) electromagnetic induction mapping of the identified areas of interest; (iii) 2D electrical resistivity tomography (ERT) and induced polarization (IP) to image the structure of the slag heap; and (iv) conducting a limited sampling survey to validate the geophysical interpretation and define the bulk composition of the deposit. Our approach is not only less time-consuming and less costly than the traditional method but also safer for the operators.

This study has been applied to a former zinc production site nearby Liège city in Wallonia, Belgium. The application of the NWE-REGENERATIS methodology has allowed the imaging of the 3D structure of the anthropogenic deposits. The combination of ERT and IP measurements has revealed the presence of two types of residues, with the main part of the deposit composed of inert waste, and metallic slag lenses are present on the surface. These insights provide valuable information for assessing the feasibility of urban mining and developing effective regeneration plans for the site. The application of the NWE-REGENERATIS methodology in this study has proven to be a valuable tool for understanding the complexities of ancient metallurgical sites. Our approach is not only less time-consuming and less costly than the traditional method but also safer for the operators.

How to cite: Dumont, M., Isunza Manrique, I., Michel, H., Debouny, T., Caterina, D., and Nguyen, F.: Applied geophysics for regeneration of past metallurgical sites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14429, https://doi.org/10.5194/egusphere-egu23-14429, 2023.

EGU23-14562 | Posters on site | GI5.4 | Highlight

Feasibility study of Neural Networks interpolation applied to Synthetic Aperture Radar Deformations 

Jean Dumoulin, Alexis Renier-Robin, Diego Reale, Thibaud Toullier, Simona Verde, and Francesco Soldovieri

After the collapse of the Genoa Bridge in August 2018, a renewed interest in permanent monitoring of the structural behavior of civil infrastructures [2] was observed. Such monitoring has to encompass the need to survey a very large number of structures that reach critical age but also new structures. In addition, recent technological advances have helped to make the installation and operation of continuous monitoring systems more practical and economical. In parallel, monitoring approaches based on the use of data acquired by satellite Synthetic Aperture Radar (SAR) may complete and enlarge the observation scale of such ground based monitoring systems, to enhance Structural Health Monitoring (SHM) performances.

Monitoring of civil structures is frequently based on vibration analysis. Anyway, one limitation to the use of SHM algorithms based on modal parameter analysis is its sensitivity to environmental effects and not to damage. Among them, the subsidence around and at structure’s foundation level is a factor that has a great influence on natural frequencies.

In this study, we address quasi-periodic monitoring and subsidence characterization using surface deformation measurements achieved through the Differential Interferometric SAR (DInSAR) technology [1]. Peculiarities of DInSAR have to be taken into account with reference to the application to structures monitoring:

  • Robustness of estimated ground deformation obtained throught the combination of the Line-of-sight (LOS) deformation measurements carried out by the processing of complementary ascending and descending orbits data, for which the measurements points and date of acquisition could be different;
  • Sparse, or absence of, measurements points on some areas induced by strong decorrelation phenomena;
  • Limited range of the actual structure deformation that could reach the accuracy of the DInSAR technology.

Bibliographic study showed that it could be difficult to exploit the DInSAR data directly for the SHM because of the problems mentioned above. The proposed procedure aims at reconstructing the deformations over an area of interest using a regularly spaced grid whose deformations would be interpolated on the available sparse measurements dataset. The interpolation is carried out on each orbit trajectory and for each acquisition date. This allows both to:

  • Estimate measurements point on the same, possibly regular, grid for different orbits;
  • Estimate deformation in areas lacking of measurement points;

Inspired from research works of Chen et al. [3] we implemented and studied a neural network (NN) kriging based interpolation (introducing the spatial dimension inside the NN). It allows the modelisation of the points correlation (variograms) directly from the data instead of predefined functions.

An overview of the studied method and developed software applied on 2 use-cases will be presented and analysed. Perspectives towards improvements of such approach will be also discussed.

References

[1] Antonio Pepe and Fabiana Calò. “A Review of Interferometric Synthetic Aperture RADAR (InSAR) Multi-Track Approaches for the Retrieval of Earth’s Surface Displacements”. In: Applied Sciences 7.12 (2017). doi: 10.3390/app7121264. 

[2] Riccardo Lanari et al. “Comment on “Pre-Collapse Space Geodetic Observations of Critical Infrastructure: The Morandi Bridge, Genoa, Italy” by Milillo et al. (2019)”. In: Remote Sensing 12.24 (2020). doi:10.3390/rs12244011.

[3] Wanfang Chen et al. “DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction”. In: arXiv:2007.11972 (May 23, 2022).

How to cite: Dumoulin, J., Renier-Robin, A., Reale, D., Toullier, T., Verde, S., and Soldovieri, F.: Feasibility study of Neural Networks interpolation applied to Synthetic Aperture Radar Deformations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14562, https://doi.org/10.5194/egusphere-egu23-14562, 2023.

EGU23-15344 | Posters on site | GI5.4

Using the Debye parameters of soil for water content and contamination level determination. 

Lourdes Farrugia, Raffaele Persico, Andrea Cataldo, Iman Farhat, and Raissa Schiavoni

The use of time domain reflectometry (TDR) techniques for in-situ, non-destructive measurement of water content has revolutionized soil water management and it is a rapidly growing area of interest. Additionally, monitoring other soil parameters such as levels of contaminants in soil is becoming an active field of research due to increasing environmental pollution and thus enforcement of contamination levels from policy makers. As a result, in recent years there have been advancements of TDR probe capability in terms of operating range, proven design, multiplexing and automated data collection. However, there is still a strong need for systems that are user-friendly and low cost which provide for quasi-real time and in situ monitoring with high sensitivity of soil parameters with adequate accuracy.

In this paper, we present a system consisting of a bifilar TDR probe interfaced with a miniaturized Vector network analyser which enabled measurements of the reflection coefficient in the frequency-domain.   The reflection coefficient is then related to soil parameters, such as soil water content and percentage of diesel oil (as an example of soil contaminant) through an innovative numerical procedure that retrieves the Debye parameters of different soil samples under different conditions.

This numerical procedure consisted of two main steps:

Firstly, the accurate modelling of the bifilar TDR probe in CST Microwave Studio such that the model is an accurate representation of the experimental setup used in the laboratory. This model was also validated using well-characterised materials such as Methanol and Prop-2-ol, utilising Debye parameters as published in [1].

Finally, the bifilar probes were immersed in soil samples having different moisture levels (dry up to 30%, in steps of 5%) and contaminated soil with different percentages of diesel oil (0%, 5%, 7.5% and 10%) and the Debye parameters were retrieved using the validated model in the first step.

Results illustrate that there exists a correlation between the retrieved Debye parameters and the moisture levels and percentage of diesel oil in soil. This proves that the Debye parameters provide the necessary information to differentiate between water or contaminant content and thus can be used for monitoring purposes rather than conducting measurements of the dielectric permittivity.

 

References

[1] Gregory, A.P.; Clarke, R.N. Tables of the Complex Permittivity of Dielectric Reference Liquids at Frequencies up to 5 GHz; National Physical Laboratory Report; 2012. Available online: https://eprintspublications.npl.co.uk/2076/ (accessed on 13 September 2022).

How to cite: Farrugia, L., Persico, R., Cataldo, A., Farhat, I., and Schiavoni, R.: Using the Debye parameters of soil for water content and contamination level determination., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15344, https://doi.org/10.5194/egusphere-egu23-15344, 2023.

EGU23-17111 | Orals | GI5.4

GPR and Ultrasonic investigations to study the degradation of the Auriga statue (Mozia island, Sicily) 

Patrizia Capizzi, Raffaele Martorana, Alessandra Carollo, and Alessandro Canzonieri

The archaeological museum of the Giuseppe Whitaker Foundation (Mozia island, Sicily), exhibits the Greek statue of the Auriga, which has been the subject of geophysical investigations to evaluate the degradation of the marble. In particular, a 3D ultrasonic tomography (UST) and some georadar investigations were performed. For the UST 114 measurement points were used, selected on the surface of the statue. The results of the US tomography show an average velocity of the marble equal to about 4700 m/s, which indicates a good mechanical resistance of the marble. There are widespread areas with lower velocity (around 3000 m/s), which however fall within the range of variability of the material. A comparison was made with ultrasound data acquired in January 2012, during a previous diagnostic campaign. Georadar profiles were performed to highlight any internal discontinuity surfaces, which can be interpreted with the presence of fractures and/or lesions. In all the georadar profiles acquired, the internal signal of the material shows a general homogeneity, which allows to exclude the presence of fracturing surfaces and/or internal lesions.

How to cite: Capizzi, P., Martorana, R., Carollo, A., and Canzonieri, A.: GPR and Ultrasonic investigations to study the degradation of the Auriga statue (Mozia island, Sicily), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17111, https://doi.org/10.5194/egusphere-egu23-17111, 2023.

EGU23-1843 | ECS | Posters virtual | GI5.6 | Highlight

Near surface muography studies at the Gallo-Roman archaeological site of Vienne, France. 

Theodore Avgitas and Jacques Marteau

Archémuons is a collaborative project between the Institute of Physics of the 2 Infinities of Lyon (IP2I Lyon), the Laboratory of Geology of Lyon (LGL) and the ArchéOrient Laboratory. The three laboratories will perform surveys at the Palais du Miroir of the Gallo Roman Museum of Vienne in France. The goal of the project is to evaluate how geology surveys (electric resistivity, gravimetry, seismometry) synergize with muon tomography for near surface underground studies. The foundation of the Palais du Miroir building and the surrounding extensive network of galleries provide a rich yet challenging set of targets to investigate. The controlled/confined environment provides opportunities to test different analysis and imaging techniques as well as new detector geometries, scintillation materials and a new portable prototype compact detector that combines Cherenkov detection with a scintillator based trajectograph which will be deployed and tested on site. In November 2022 the project kickstarted with an electric resistivity survey of the surface above the gallery where the muon detector will be hosted. In parallel a first set of measurements was acquired with a small scintillation detector as a proof of concept and for a first evaluation of the ground overburden. We will present the current status of this project as well as a preliminary result acquired by the time of the EGU2023 General Assembly.

How to cite: Avgitas, T. and Marteau, J.: Near surface muography studies at the Gallo-Roman archaeological site of Vienne, France., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1843, https://doi.org/10.5194/egusphere-egu23-1843, 2023.

EGU23-2339 | ECS | Posters virtual | GI5.6

Close-range methods for muon imaging applications: a case study from Italy 

Tommaso Beni, Diletta Borselli, Lorenzo Bonechi, Luca Lombardi, Sandro Gonzi, Roberto Ciaranfi, Massimo Bongi, Vitaliano Ciulli, Livio Fanò, Catalin Frosin, Andrea Paccagnella, Laura Melelli, Maria Angela Turchetti, Raffaello D'Alessandro, Giovanni Gigli, and Nicola Casagli

The employment of remote sensing (RS) survey methods, in particular of close-range methods, as part of the muon imaging process is becoming a topic of growing interest. Use of light detection and ranging (LiDAR) methodologies, like terrestrial laser scanner (TLS), together with the unmanned aerial vehicles digital photogrammetry (UAV-DP) and satellite data are proving to be fundamental tools to carry out a reliable muographic measurements campaign. The main purpose of this presentation is to show the importance of correctly plan TLS and UAV-DP field surveys for muon radiography applications. To this aim, a real case study is presented: the research of hidden tombs at the Volumni Hypogeum archeo-geosite (Umbria, Italy). A high-resolution digital terrain model (DTM) and three-dimensional models of the surface/sub-surface were created merging different RS survey methods. The muon flux transmission was measured using the MIMA detector prototype (Muon Imaging for Mining and Archaeology). The latter is a small tracker (0.5 x 0.5. x 0.5 m3) developed by the physicists of the National Institute of Nuclear Physics (INFN), unit of Florence, and the Department of Physics and Astronomy of Florence. The measured muon flux was compared to the simulated one, obtained using the three-dimensional created environment, to infer information about the average density of the studied target along the various LoS (line of sight). The study highlights the importance of correctly carrying out the TLS and UAV-DP survey to make reliable hypotheses and decisions throughout the muographic measurement campaign. Furthermore, we pointed out how the precision of the tridimensional data can bias the muon imaging results.

How to cite: Beni, T., Borselli, D., Bonechi, L., Lombardi, L., Gonzi, S., Ciaranfi, R., Bongi, M., Ciulli, V., Fanò, L., Frosin, C., Paccagnella, A., Melelli, L., Turchetti, M. A., D'Alessandro, R., Gigli, G., and Casagli, N.: Close-range methods for muon imaging applications: a case study from Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2339, https://doi.org/10.5194/egusphere-egu23-2339, 2023.

EGU23-2352 | ECS | Posters virtual | GI5.6

Three-dimensional localization of Radon source conduits inside the Temperino mine (Tuscany-Italy) with the muon radiography technique 

Diletta Borselli, Tommaso Beni, Lorenzo Bonechi, Massimo Bongi, Debora Brocchini, Nicola Casagli, Roberto Ciaranfi, Vitaliano Ciulli, Raffaello D'Alessandro, Andrea Dini, Catalin Frosin, Giovanni Gigli, Sandro Gonzi, Silvia Guideri, Luca Lombardi, Andrea Paccagnella, and Simone Vezzoni

Muon radiography, or muography, is a non-invasive technique allowing imaging of the interior of large structures (target) thanks to the study of the absorption of atmospheric muons in materials. The muons absorption effect depends not only on the thickness, but also on the density of the target. Careful comparisons of the muographic results with simulations taking into account a precise description of the target's geometry, allow estimating the two dimensional distribution of the average density of the structure under study as seen from the measurement point of view. In this presentation an application in the geological field for the research and localization of low density anomalies attributable to cavities inside an abandoned mine will be shown. The aim of the study is to identify and locate areas that might be responsible for the production of anomalous concentrations of radon gas inside underground mining sites used for touristic itineraries. Radon is a natural radioactive gas that exposes tourists to ionizing radiation. Radon decay products are the second cause of lung cancer after smoking. It is important therefore to understand where the radon gas comes from before moving through the different galleries. The case study is the Temperino mine near Campiglia Marittima (LI-Italy). Here, the mining activity ended in 1980 and it was primarily focused on the extraction of copper, silver lead and zinc minerals. The area to be explored with muon radiography is part of an area dating back to the Etruscan period that has not yet been completely mapped and that is located above the tourist path of the Temperino mine at a depth of about 40 m from the surface of the hill above. Any nearby cavity could represent a prime conduit that brings radon gas into the tourist trail. The identification and localization in space of these ancient excavations is also interesting from a geological and archaeological point of view. The detector employed for the muographic measurements reported in this presentation, designed in Florence by the National Institute of Nuclear Physics (INFN) and the Department of Physics and Astronomy, is called MIMA (Muon Imaging for Mining and Archaeology) and has cubic shape and approximate dimensions of (50x50x50) cm3. MIMA is equipped with a special protective aluminum mechanism that allows its altazimuth orientation.

How to cite: Borselli, D., Beni, T., Bonechi, L., Bongi, M., Brocchini, D., Casagli, N., Ciaranfi, R., Ciulli, V., D'Alessandro, R., Dini, A., Frosin, C., Gigli, G., Gonzi, S., Guideri, S., Lombardi, L., Paccagnella, A., and Vezzoni, S.: Three-dimensional localization of Radon source conduits inside the Temperino mine (Tuscany-Italy) with the muon radiography technique, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2352, https://doi.org/10.5194/egusphere-egu23-2352, 2023.

EGU23-3567 | Posters virtual | GI5.6

Using a new geophysical tool for improving underground safety in mining and civil engineering: time-sequential muography 

Marko Holma, Jarmo Korteniemi, Pasi Kuusiniemi, and Zongxian Zhang

Tunnelling and underground mining face many risks threatening underground operations. Such hazards include sudden incidents of dangerous and violent rock bursts and cave-ins. The likelihood of these disastrous events increases as operations go deeper and the in-situ stresses increase. Triggers leading to such accidents can be regional seismic events related to faults and tectonically active contacts between rock types (e.g., dyke contacts). Therefore, it is paramount to know the locations of such pre-existing brittle rock structures, understand their 3D extent, and monitor their changes in time. This allows proactive measures to be taken and stresses to be mitigated before disastrous events occur.

Muography is a novel and passive method for imaging rock densities. Muographical techniques can image and distinguish faults and dykes as long as their densities differ from the surrounding rock. Such anomalies are identified by collecting data and statistics on muons - elementary particles which form in the atmosphere and, at near lightspeed, penetrate all matter. The most energetic ones travel over 1 km in rocks. The number of muons coming from each direction reveals the density of the rock column the muons traversed through.

Muography is conceptually akin to X-ray imaging: In both, the formed image relates to the density profile of the target, i.e., a higher-density medium stops more X-rays and muons than a lower-density medium. Images are reconstructed based on the attenuation of natural background radiation flux. Muography can yield both 2D radiography and 3D tomography density images based on the number of survey locations. A third option, time-sequential (time-lapse) muography, allows long-term monitoring of the target rocks and can detect if any changes occur within it as a function of time. This type of imaging works in both radiographical and tomographical modes.

The flux of muons is high at ground level and decreases with depth as bedrock attenuates muons. This means that muon detectors located at shallow observation depths will be faster to record a statistically sound dataset and, as such, quicker in pinpointing any time-varying changes within the target density.

We propose that stationary muography arrays in underground settings could map potentially risky bedrock structures and monitor their density-affecting changes over time. E.g., hidden faults may become visible due to the passing of seasons or after the passing of substantial rainfall as the excess water percolates through the mechanically broken fractures. Another advantage of the time-sequential approach is that it reveals if the studied structure is stable and time-invariant, i.e., no ongoing processes affect its density. Therefore, we propose that applying muography in underground spaces improves understanding of the conditions of the rock body and, hence, increases safety.

We aim to conduct pilots for this application soon.

How to cite: Holma, M., Korteniemi, J., Kuusiniemi, P., and Zhang, Z.: Using a new geophysical tool for improving underground safety in mining and civil engineering: time-sequential muography, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3567, https://doi.org/10.5194/egusphere-egu23-3567, 2023.

EGU23-4756 | ECS | Posters virtual | GI5.6

Muon tomography optimization for dry cask spent nuclear fuel storage imaging 

Jesus Valencia and Adam Hecht

Dry cask spent fuel storage containers currently house much of the world’s spent nuclear fuel stores outside of spent fuel cooling pools. In order to maintain, continuity of knowledge of these containers, seals are applied. When these seals are broken, the containers must be relocated to spent fuel pools for visual inspection.  Large amounts of steel shielding, required for radiation safety, significantly attenuates both radiation emitted from the fuel itself and incoming radiographic probes such as x-ray and neutrons. As a result, the effectiveness of these more traditional radiographic probes is greatly diminished, and no other passive, in situ verification methods are currently in use. While promising results have been demonstrated, long measurement times limit the attractiveness of cosmic-ray muon radiography as a passive verification method. The work presented here compares performance of differing reconstruction techniques to draw recommendations for the optimization of future cosmic-ray muon tomography measurements. For tomographic imaging, the results show that using a plenoptic depth of field reconstruction method, rather than traditional backprojections, results in better imaging resolution for a limited number of views. The depth of field reconstruction method also requires a smaller number of views to reconstruct images useful in the verification of dry cask spent fuel storage containers.

How to cite: Valencia, J. and Hecht, A.: Muon tomography optimization for dry cask spent nuclear fuel storage imaging, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4756, https://doi.org/10.5194/egusphere-egu23-4756, 2023.

EGU23-6638 | ECS | Posters on site | GI5.6

B2G4: A synthetic data pipeline for the integration of Blender models in Geant4 simulation toolkit. 

Angel Bueno, Felix Sattler, Maximilian Perez Prada, Maurice Stephan, and Sarah Barnes

Particle simulation software is essential for the development and validation of theoretical prototypes in a myriad of physical appplications. The Geant4 simulation toolkit provides precise particle transport and matter interaction simulations in a controlled setting. The interpretation of simulated results is intimately linked to the level of detail represented in the simulation itself, including the ability of the simulation framework to create detailed geometries. Yet, rendering such highly detailed geometries is a daunting task in Geant4, where high-variance scenes must often be manually coded. Potential geometrical errors increase the time required for this coding procedure, and thus in-depth knowledge of the underlying simulation engine in Geant4 is needed.

This research proposes Blender2Geant4 (B2G4), a novel framework which transplants 3D scenes from Blender into Geant4 for synthetic data generation. This was achieved by synergizing the descriptive 3D modelling tools in Blender with the simulation capabilities of Geant4. The ability to import, arrange, and manipulate 3D objects in Blender permits the creation of highly detailed and varied scenes: users can easily create sophisticated geometries by using drag-and-drop placement, shape variance randomization, and intuitive material assignments. The suite of functionalities defined in B2G4 lexically translates geometry facets from Blender into a readable format for Geant4, enabling the automated export and import of scenes with minimal manual input. Hence, the B2G4 framework enables automated mass production of corrected 3D scene variations with precise annotations and geometrical consistency checks. The B2G4 framework is designed as an all-purpose geometry creation interface to reduce the complexity of simulation scenes in Geant4 for a variety of physical applications. The applicability of B2G4 in a muon tomography setup is highlighted with a set of procedurally generated 3D scenes.

How to cite: Bueno, A., Sattler, F., Perez Prada, M., Stephan, M., and Barnes, S.: B2G4: A synthetic data pipeline for the integration of Blender models in Geant4 simulation toolkit., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6638, https://doi.org/10.5194/egusphere-egu23-6638, 2023.

EGU23-7336 | Posters virtual | GI5.6

Muon production in the lunar regolith: Opportunities for muon imaging in the Moon 

Pasi Kuusiniemi, Timo Enqvist, Marko Holma, Jarmo Korteniemi, and Teemu Öhman

Muography studies density differences within a medium using muons. They are elementary particles generated by primary cosmic rays as they collide with the matter. On Earth, muons are produced at ca. 15-25 km altitude in the upper atmosphere and penetrate down to ca. 1 km depth in the bedrock (with ever-decreasing numbers by increasing depth due to attenuation). Muons provide a powerful local probe to investigate density variations in any material they pass through (e.g., soils, rock, buildings, magma, or even the atmosphere itself).

Although muography has so far only been applied on Earth, several extra-terrestrial applications have recently been proposed. Many of them focus on possible lunar applications. However, first, we need to understand how muons are formed on the Moon.

As the Moon has no atmosphere the primary cosmic radiation hits the surface unobstructed. Muon production can thus be expected to occur within the lunar regolith, i.e., the ca. 5-10 m thick lunar "soil" layer. Regolith consists of crushed rock dust and shards (bulk density ca. 1.5 g/cm3 with rock fragments, e.g., lunar anorthosite 2.7 g/cm3 [1]).

We simulated lunar muon production using silica (SiO2, density 2.65 g/cm3) as it is easy to construct in a simulation. Silica is a common constituent in silicate minerals, which are abundant also on the Moon, although free quartz itself is rare there. It is also more realistic than water, which we used earlier for testing and developing the simulations' routines and methods [2]. Simulated primary cosmic-ray particles were protons with two energies: 1 PeV and 3 PeV. Protons were chosen since they dominate up to the knee region and are the most relevant primary particles for these studies. The incoming proton zenith angle was selected to be uniform and limited to 75 degrees. Simulations were performed by the Fluka simulation package using the CSC (IT Center For Science Ltd., Finland) supercomputer.

Our preliminary results suggest that about 50% of the muons are generated in the topmost 125 cm. About 90% of the muons are generated in the range of 275 cm. Interestingly, this depth is almost independent of the primary-particle energy. Hence, if these quartz-based simulations are taken as a simplified model for lunar muon production, all muons are generated within just some metres of material.

Consequently, lunar muography should not only work, but it should work for small targets quite close to the surface. Muography could be applied, e.g., to identify H2O ice sources at elevated locations (e.g., crater walls, central peaks, hills, and cliffs), investigate the structural integrity of lunar lava tubes (which are often suggested as possible human habitation sites), and monitoring structural weaknesses of lava tubes or artificial in-situ constructs.

[1] C. Meyer, 2003. The Lunar Petrographic Educational Thin Section Set. https://www-curator.jsc.nasa.gov/education/lpetss/index.cfm.

[2] T. Enqvist, 2021. Exploration of Lunar In Situ Resources Can Be Conducted by Applying Density-Sensitive Cosmic-Ray-Based Geophysical Muon Imaging Method Called Muography. ST.040. SEG 100 Conference.

How to cite: Kuusiniemi, P., Enqvist, T., Holma, M., Korteniemi, J., and Öhman, T.: Muon production in the lunar regolith: Opportunities for muon imaging in the Moon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7336, https://doi.org/10.5194/egusphere-egu23-7336, 2023.

EGU23-8752 | ECS | Posters on site | GI5.6 | Highlight

Status and first results of the MURAVES experiment at Mt. Vesuvius 

Marwa Al Moussawi and the MURAVES Collaboration

The MURAVES experiment, whose acronym stands for MUon RAdiography of VESuvius, aims at the imaging of the internal structure of the summit of Mt. Vesuvius through muography, i.e. the absorption of muons naturally produced by cosmic rays. Though presently quiescent, this volcano carries a dramatic hazard in its highly populated surroundings. The challenging measurement of the rock density distribution in its summit by muography, in conjunction with data from other geophysical techniques, can help the modeling of possible eruptive dynamics. The MURAVES apparatus consists of an array of three independent and identical muon trackers, two pointing towards the volcano and one towards the free sky (to collect reference data), each of them made of four 1m2 active area XY tracking planes made of plastic scintillators. In each muon tracker, a 60 cm thick lead wall between the two downstream planes ensures rejection of background from low energy muons. 

MURAVES has been acquiring data since 2019. We will present a description of the muon trackers, as well as the preliminary results from the analysis of a sub-set of the data samples collected thus far, focusing in particular on an early measurement of density asymmetry.

In addition, we will report on a number of simulation studies that allow us to investigate the effects of the experimental constraints and to compare our simulated data with the actual observations.

How to cite: Al Moussawi, M. and the MURAVES Collaboration: Status and first results of the MURAVES experiment at Mt. Vesuvius, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8752, https://doi.org/10.5194/egusphere-egu23-8752, 2023.

EGU23-8785 | Posters virtual | GI5.6 | Highlight

Cosmic Ray Muon Imaging of the Great Pyramid of Giza 

Ralf Ehrlich

The Exploring the Great Pyramid (EGP) Mission is investigating using cosmic-ray muons to study the interior of the Great Pyramid of Giza with unprecedented resolution. Muon telescopes would collect data over a large angular range at different locations around the pyramid base to produce a tomographic image of the internal structures of the pyramid. The muon telescopes will use scintillator bars with embedded wavelength-shifting fibers read out by silicon photomultipliers, a technology successfully employed in several high-energy physics experiments. We will report on measurements made with a prototype detector at the Fermilab test beam facility and extensive simulation results showing the expected performance of the detectors. 

How to cite: Ehrlich, R.: Cosmic Ray Muon Imaging of the Great Pyramid of Giza, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8785, https://doi.org/10.5194/egusphere-egu23-8785, 2023.

EGU23-11260 | Posters on site | GI5.6

Challenges, best practices and case examples in muon imaging 

Dezső Varga, Gergely Surányi, Gergő Hamar, Gábor Nyitrai, and László Balázs

Muography is an inherently multidisciplinary field, and as such presents a wide range of practical and methodological challenges. Regarding instrumentation, the environment drastically differs from the high energy physics laboratory conditions. In addition, the choice of measurement location and the instrument with the most suitable parameters is far from obvious: one needs to balance between improving detection sensitivity (e.g. moving closer to the target) and local possibilities (accessibility, safety). The presentation gives an overview of successful implementations, with detailed case examples with participation of Wigner Research Centre for Physics. Detectors on the surface need to cope with daily thermal cycling and intermittent high humidity periods, as apparent at the Sakurajima Muography Observatory, or imaging a medieval castle in Sicily. Underground detectors on the other hand require fast and efficient installation, since such environments -- particularly mining -- safety concerns limit personal access. Examples include mines from Finland and Bosnia and Herczegovina. From the point of view of methodology, the presentation will discuss the data quality requirement for three dimensional density map reconstruction (tomography). In case of a complicated karst structure, low density zones identified by muon tomography were confirmed by drilling.

How to cite: Varga, D., Surányi, G., Hamar, G., Nyitrai, G., and Balázs, L.: Challenges, best practices and case examples in muon imaging, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11260, https://doi.org/10.5194/egusphere-egu23-11260, 2023.

EGU23-13175 | Posters virtual | GI5.6 | Highlight

Measuring of water concentration in rock and soil with muon radiography 

Konstantin Borozdin, Tancredi Botto, Nicolás De Beer, Ricardo Repenning, and Claudio Rocha

Dry rock and soil have the capability to absorb and contain water because of their porosity. Measuring water concentration in different materials is important for many applications. For example, in heap leaching the leaching liquid distribution directly affects the metal recovery. The water concentration is the key parameter affecting the slope stability, and its measurement is therefore of a great importance for landslide prevention and tailing dams safety. Measurement of this parameter is however a significant challenge, and is done mostly by measuring rainfall in the field and/or analyzing soil samples in the laboratory. These measurements are model-dependent and require significant extrapolation of the results. 

A direct measurement of the water concentration in-situ is offered by muon radiography - through measuring density distribution based on cosmic-ray muon flux monitoring. By measuring the flux of muons from different directions we can reconstruct density maps of any object they traverse, including large volumes of rock. By monitoring the muon flux, our sensors are sensitive to the density changes in any material above it.  From these density changes we can infer the amount of water contained within the rock or soil.
         
We performed the first in-situ, fully volumetric monitoring of the water concentration in an active leaching heap in Chile.  Here we discuss the results of these pioneering measurements and the potential for muon imaging of the water concentration for different applications.

How to cite: Borozdin, K., Botto, T., De Beer, N., Repenning, R., and Rocha, C.: Measuring of water concentration in rock and soil with muon radiography, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13175, https://doi.org/10.5194/egusphere-egu23-13175, 2023.

EGU23-1225 | Posters on site | GI5.7

Experiments of arsenic (V) adsorption on birnessite: implications on arsenic cycling 

Hao Wei Huang, Huai-Jen Yang, Li-Yun Huang, and Chia-Ju Chieh

Birnessite occurs as a major manganese oxide in sediments. It is characterized by a high adsorption capacity for trace elements, including arsenic. However, the effects of birnessite on arsenic cycling were less intensively investigated than that of goethite, a commonly recognized arsenic host. Therefore, this study utilizes arsenic-bearing solutions containing 0.1–50 ppm arsenic to synthesize birnessite and uses arsenic sequential extraction procedure (SEP) analysis to quantify its arsenic co-precipitation and adsorption capacity.
    SEPs showed that adsorbed/structural arsenic ratio grew from 0:100 to 60:40, with arsenic concentration increasing from 0.1–50 ppm, implying saturation of structural arsenic. SEPs quantify the adsorbed and structural As of birnessite being 0.831 and 1.308 mg/g, respectively. However, the low arsenic concentrations of < 1% in residual solutions indicate nonattainment of the maximum adsorption capacity. Subsequent adsorption experiments using higher initial arsenic concentrations reaching 250 ppm determined the maximum arsenic adsorption capacity to be 19.81 mg/g at pH 7, comparable to the values of 15.3–22.5 mg/g at pH 6.5 (Manning et al., 2002; Singh et al., 2010) and that of 3.79–15.73 mg/g for goethite. It then appears that birnessite adsorption/desorption is more effective than precipitation/dissolution in controlling arsenic cycling. However, the consideration based on the maximum adsorption capacity might overrate the controls of adsorption/desorption relative to precipitation/dissolution because the natural water generally contains less arsenic than that used for the adsorption experiments. Therefore, we conducted adsorption experiments with low arsenic concentrations of 0.5 ppm and a solid/liquid ratio of 0.01 to 0.001. The results showed that adsorption capacity rose abruptly to 1.416 mg/g in two weeks and then slowly increased to 1.523 mg/g after three months. This feature indicated incomplete filling of the adsorption sites on the surface of birnessite at low As concentration despite its large specific surface area. Another controlling factor was the abundance of birnessite in sediments. If 10% of MnO (0.05–0.15%) in the Chianan sediments in southern Taiwan occurred as birnessite, the adsorbed arsenic was calculated to be 0.0005–0.022 mg, corresponding to < 2 % of adsorbed arsenic in 1 g sediments, based on the SEP data of Yang et al. (2016). In the extreme case that all the Mn occurred as birnessite, birnessite could account for up to 25% of the adsorbed arsenic. Apparently, birnessite is not a major contributor to surface arsenic cycling. However, this inference must be evaluated by considering the adsorption and co-precipitation data from goethite and goethite proportions in sediments.

How to cite: Huang, H. W., Yang, H.-J., Huang, L.-Y., and Chieh, C.-J.: Experiments of arsenic (V) adsorption on birnessite: implications on arsenic cycling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1225, https://doi.org/10.5194/egusphere-egu23-1225, 2023.

EGU23-4067 | Orals | GI5.7

Application of ion-exchange resin sachets and XRF-CS in heavy metal pollution sources monitoring 

Yu-Chen Jian, Ludvig Löwemark, and Alice Chien-Yi Liao

For the past decades, scientists have endeavored to develop efficient and suitable approaches to monitor heavy-metal pollution through technological development. Conventional monitoring methods for heavy metals are still complicated, relatively expensive, and time-consuming. This research aims to develop an innovative heavy-metal monitor, the novel approach of ion-exchange resin sachets combined with X-ray fluorescence core scanner (XRF-CS), to achieve an efficient way to effectively monitor vast areas for contamination. The resin sachets, which have a large capacity to quickly take up heavy metals, were deployed in the river weekly to capture heavy metals and then analyzed using the non-destructive, fast, and cost-efficient Itrax XRF core scanner. Two four-week sampling sessions, performed during the dry and wet periods, respectively, were conducted in northeastern Taiwan, where the environment was contaminated by a copper smelter and coal mine activities in the late twentieth century. The results suggest that ion-exchange resins are useful as long-term monitors of heavy metals in a low pollution-level settings (metal concentration <1 mg/L), and that XRF core scanner data truly reflect metal pollution concentrations as measured by inductively coupled plasma-optical emission spectrometry (ICP-OES). This approach allows us to pinpoint pollution sources along the studied river. Especially, Zn, Ni, Mn, Fe, Cu, Ca, and Sr could be detected near pollution sources, where cps values were 1.8 to 3430.6 times higher than in unpolluted areas. Zn shows the largest difference between polluted and non-polluted areas, with the cps values of the samples in polluted areas 3528 times higher than their non-polluted counterparts. Ni, Mn, Fe, Cu, Ca, and Sr’s cps values were 1.8, 29.2, 46.1, 2.4, 6.2, and 5.9 times higher, respectively, than the corresponding counts measured in non-polluted areas. In addition, our results demonstrate that the intensity of precipitation influences the amount of metal adsorption in the resins; resins showed less adsorption in the dry period, and cps values slightly dropped to 81 to 84 percent of the wet period. In summary, ion-exchange resins are a sensitive tool that can be applied in pollution monitoring at various pollution levels due to their high performance in adsorbing heavy metals. Consequently, ion-exchange resin sachets in combination with XRF core scanner analysis is a cost-effective way to monitor large areas of potentially polluted aquatic systems quickly.

How to cite: Jian, Y.-C., Löwemark, L., and Liao, A. C.-Y.: Application of ion-exchange resin sachets and XRF-CS in heavy metal pollution sources monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4067, https://doi.org/10.5194/egusphere-egu23-4067, 2023.

EGU23-6351 | ECS | Orals | GI5.7

Geochemical baseline values of chalcophile and siderophile elements in soils around the former mining area of Abbadia San Salvatore (Mt. Amiata, Southern Tuscany, Italy). 

Federica Meloni, Barbara Nisi, Caterina Gozzi, Jacopo Cabassi, Giordano Montegrossi, Valentina Rimondi, Daniele Rappuoli, and Orlando Vaselli

Determining the background values of chemical components in environmental matrices is a difficult task. This is particularly true in regions where the human impact due to industrial, mining, agricultural and urban activities coexists with a geological (geogenic) anomaly, which influences the concentration of certain elements in soils, waters and air. In these cases, the term geochemical baseline (GB) is preferable, since it considers the actual content of that element in the superficial environment at a given point in time, including both geogenic and anthropogenic contribution. In this study, a total of 102 top- and sub-soil (collected at 10-50 cm and 50-154 cm depth, respectively) samples and seven rocks, onto which the soils developed, were collected for the determination of GBs for selected chalcophile (As, Cu, Hg and Sb) and siderophile (Co, Cr, Ni, and V) elements in 25.6 km2 around the former mining area of Abbadia San Salvatore (Mt. Amiata, Southern Tuscany, Italy). For about one century, cinnabar (HgS) ore deposits have been exploited to produce liquid mercury from the Mt. Amiata volcanic system and its surroundings, which represents a world-class mercury district. The < 2 mm (as required by the national regulamentation) fraction of the samples was pulverized and analysed by ICP-MS (As, Hg and Sb) and ICP-AES (Co, Cr, Ni, and V) after aqua regia digestion. The compositional data analysis of multivariate compositional vectors, based on the log-ratio approach was used to assess the nature of the geochemical . According to our findings, the centred log-ratio (clr) opposed to that of raw/log transformation, enhances the spatial mapping. This also allowed to obtain better-separated variables in the robust Principal Component Analysis (rPCA). Log-ratio geographical maps evidenced that the underlying bedrock geology (parent lithologies), rather than anthropogenic causes, controls the distribution of the  great majority of the elements in the top- and sub-soils. The resulting clr-PCA approach, associated with the geological features, indicates that the geochemical pattern of Hg-As is to be related to the volcanic rocks and ore-deposits, although an anthropogenic influence due to the past mining activity in the topsoils cannot be ruled out. Sb, Co, Cr, Ni, and V distribution patterns are in most cases attributed to calcareous and clay lithologies. The anomalous content of Sb found within the volcanic rocks was likely due to the presence of previously undetected old mining dump. The two data populations (volcanic and calcareus-clay lithologis) were separated into two different databases and the outliers were removed when necessary. By processing the two datasets, the US-EPA’s ProUCL software was used for calculating the GBs for the selected suite of elements. The obtained values are paramount for establishing specific guidelines and quality standards in environmental legislation and policy-making to be applied by the Municipality of Abbadia San Salvatore

How to cite: Meloni, F., Nisi, B., Gozzi, C., Cabassi, J., Montegrossi, G., Rimondi, V., Rappuoli, D., and Vaselli, O.: Geochemical baseline values of chalcophile and siderophile elements in soils around the former mining area of Abbadia San Salvatore (Mt. Amiata, Southern Tuscany, Italy)., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6351, https://doi.org/10.5194/egusphere-egu23-6351, 2023.

EGU23-7980 | ECS | Posters on site | GI5.7

A transect of mercury concentrations in fish (Black bass, Micropterus salmoides) from the Valdeazogues river, Almadén Hg mining district, South Central Spain. 

José Ignacio Barquero, Pablo Higueras, Jesus J. Hidalgo, Jose M. Esbri, Saturnino Lorenzo, and Efren Garcia-Ordiales

The Almadén district has been the World’s largest producer of mercury (Hg), for more than 2000 years. The mining activity in the district ceased some 10 years ago; however, the generalized pollution of soils and stream sediments, as well as the atmospheric emissions from these and other sources, still represent possibilities to toxify the human food chain. The Valdeazogues river crosses completely the district, with some 150 km2 extension, and including a huge mine, three mines of median importance, and up to 60 points where cinnabar (HgS) has been recognized.

Largemouth bass (Micropterus salmoides) is a carnivorous freshwater gamefish, very common along the Valdeazogues river. For years it was fished to complement the diet of the local inhabitants, although nowadays is not so common to consume it. We obtained 28 specimens, with sizes between 69 and 335 mm and weight between 11 and 552 gr, in a transect from the El Entredicho open pit to downstream the district (some 36,3 km). The specimens were analyzed using atomic absorption spectrometry with Zeeman effect.

Results show important variations throughout the transect; the largest fish in terms of weight and length had the highest Hg concentration (5246 ng/g), much higher than the fish with the lowest concentration (473.2 ng/g), which was not the specimen with the lowest size. Besides, as we go downstream the Valdeazogues River, moving away from the Entredicho Mine (considered to be the main source of contamination), Hg concentrations drops considerably until stabilizing at approximately 1200 - 1500 ng/g.

How to cite: Barquero, J. I., Higueras, P., Hidalgo, J. J., Esbri, J. M., Lorenzo, S., and Garcia-Ordiales, E.: A transect of mercury concentrations in fish (Black bass, Micropterus salmoides) from the Valdeazogues river, Almadén Hg mining district, South Central Spain., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7980, https://doi.org/10.5194/egusphere-egu23-7980, 2023.

EGU23-8217 | ECS | Orals | GI5.7

Assessing the impact of both a forest and a waste fire on the soil chemistry of two areas in Campania region 

Lucia Rita Pacifico, Annalise Guarino, Antonio Pizzolante, and Stefano Albanese

In the last decades, intentional illegal burnings increased in the numbers and became a problem of a global interest. As a consequence, human beings can be exposed to potentially toxic elements (PTEs) released during the combustion, dispersed by the wind, and accumulated in the fire’s ashes (Dimitrios, 2020).

Several studies highlighted that PTEs content in the deposited ashes can modify the chemical and the physical characteristics of the soil and, therefore, it can influence the development and growth of local microorganisms and vegetation (Raison, 1979). The geochemical characteristics of ashes depend on the nature of burned material (Dermibas et al. 2003) and on many other variables such as the intensity of combustion, the composition of the underlying soil, the bedrock type, etc.

The aim of the study was to verify at two different sites the environmental impact related with the on-set of two fire events occurred in Campania region (Southern Italy) during the 2017 summer season. One of the fires involved a forest (on the slopes of Mt. Somma-Vesuvius) and one affected a waste disposal site, known as Ilside (close to the city of Caserta). The variation occurred to concentration of PTEs in topsoil was used for the purpose.

Specifically, at both locations, 30 topsoil samples were collected before and right after the fire events. In total 60 samples were collected at the surroundings of Mt. Somma-Vesuvius slopes and 60 at the surroundings of Ilside. The post-fire samples were collected in correspondence of pre-existing sampling sites along the main wind directions recorded at the time of the fires.

To explore the potential elemental contamination occurred in soils due to the fire events, the Enrichment Factor (EFs) of a selection of PTEs was determined and mapped for individual samples. A predominant enrichment of Hg was identified for both areas.

Further, a combined application of multivariate statistics and geospatial analysis was also performed on the calculated EFs.

For the Ilside site (where special waste and e-waste were involved in burning) the association of Hg, Tl, Cu and Co was identified as the main responsible of data variability; for the Vesuvian area, the association of Hg, Cu and Cr was found to be quite strong and possibly associated with forest biomass burning.

This study highlighted how different can be the chemical evidence left by fires occurring in the environment depending on the nature of the burnt materials. At same time, result showed that even the burning of biomasses proceeding from a natural area can input in the environment PTEs which can potentially generate an increase of the pre-existing degree of environmental hazard.

References

Dermibas, A., 2003. Toxic Air Emissions from Biomass Combustion, Energy Sources, 25:5, 419-427.

Dimitrios E. A., 2020. Suburban areas in flames: Dispersion of potentially toxic elements from burned vegetation and buildings. Estimation of the associated ecological and human health risk. Environmental Research, Volume 183, ISSN 0013-9351.

Raison, R.J., 1979. Modification of the soil environment by vegetation fires, with particular reference to nitrogen transformations: a review. Plant Soil 51, 73–108.

How to cite: Pacifico, L. R., Guarino, A., Pizzolante, A., and Albanese, S.: Assessing the impact of both a forest and a waste fire on the soil chemistry of two areas in Campania region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8217, https://doi.org/10.5194/egusphere-egu23-8217, 2023.

EGU23-8374 | Orals | GI5.7

Geochemical transport through the critical zone: Statistics and reconstruction 

Karl Fabian, Clemens Reimann, and Belinda Flem


Detecting and quantifying geochemical transport through the critical zone at the continental to regional scale requires reliable  statistical procedures that can be uniquely interpreted. We present methods that provide different views on the same data sets and  formulate rules for their application and interpretation. The statistical analysis of cumulative distribution functions (CDFs) uses cumulative probability (CP) plots for spatially representative multi-element and multi-media data sets, preferably containing >1000 sites.
Mathematical models demonstrate how contamination can influence elemental CDFs of different  sample media. For example large-scale diffuse soil contamination leads to a distinctive shift of the low-concentration end of the distribution of the studied element in its top-soil CP plot, whereas high local contamination influences the high-concentration end. But also bio-geochemical processes can generate recognizable changes in elemental CDFs.
A related and partly unsolved problem is the correct interpretation of compositional data in terms of their transport through  the critical zone. 

 

How to cite: Fabian, K., Reimann, C., and Flem, B.: Geochemical transport through the critical zone: Statistics and reconstruction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8374, https://doi.org/10.5194/egusphere-egu23-8374, 2023.

In 2015, an environmental monitoring plan (http://www.campaniatrasparente.it) was launched with the aim of assessing the conditions of all environmental compartments (air, water, top and bottom soils, vegetables, biological samples) of the Campania region. A total of 5,333 topsoil samples were collected and analysed to determine the concentration of 52 chemical elements by means of Aqua Regia followed by ICP-MS. The main aim of prospecting campaign was to establish the ranges of the natural geochemical background for a few potentially toxic elements (PTEs) to be used as reference to define the degree of contamination of anthropized areas.

In the study area (about 13,600 km2) four volcanic areas are present and their pyroclastic products are spread across the regional territory due to a common (Plinian) explosive behaviour.

Due to the natural enrichment in some PTEs of soil developed on pyroclastic products, to discriminate the anthropic signals from the natural ones using geochemical data it is not a simple task when dealing with Campania soils. Therefore, as a preparatory work, to precisely identify regional areas mantled by “volcanic” soils we trained five machine learning algorithms (MLAs) to recognize when soil geochemistry is linked with the presence of volcanic products. All MLAs were implemented on centered log-ratio transformed data to reduce the closure and scaling effect commonly affecting geochemical data. In total, 1277 volcanic soils (VS) and 353 non-volcanic soils (NVS), respectively, were selected for the training phase. Data related with VS were selected based on the proximity of the samples with the volcanic centres, excluding highly anthropized areas. Data related with NVS were selected by consulting available detailed geological maps of those areas located faraway from volcanic areas where pyroclastic covers are completely absent. During the training phase, a cross-validation procedure was applied for parameters optimization. In the test phase all the MLAs showed an accuracy greater than 98% and the Random Forest algorithm proved to be the most accurate for the prediction of the remaining 3903 unlabelled soils. Therefore, a total of 1739 samples were classified as NVS and 2164 as VS. A subsequent comparison of the results with the existing distribution models of volcanic products has shown that samples classified as VS mainly fall in areas characterized by a high thickness of the pyroclastic fall deposits normally related to i) eruptions occurred in the last 10 Ky; ii) Campanian Ignimbrite eruption (ca. 39 ky BP); iii) Codola eruption (ca. 25 ky BP).

The MLAs results suggested that the most important chemical variables for the specific classification purpose were Ni, Cs, Ca, Co, Rb, Sc, Mn, U, Na. It is also evident that a first classification could be made by using few of these elements, as well. Our findings could be used as a valuable tool to better discriminate soil nature and geochemical characteristic aiming at a more effective assessment of natural background ranges for those elements sourced by both natural processes and human activities.

How to cite: Ambrosino, M., Albanese, S., Lucadamo, A., and Cicchella, D.: Combining compositional data analysis and machine learning to recognize where soil geochemistry is influenced by the presence of pyroclastic covers in Campania region (Southern Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8484, https://doi.org/10.5194/egusphere-egu23-8484, 2023.

The contamination of groundwater by geogenic sources is a major problem in many nations, especially those in the developing world. Fluoride (F) is one of the most pervasive and well-documented geogenic contaminants because of the severe health risks it poses due to its toxicity. F contamination in groundwater in India has been the subject of intense research over the past many decades. In this article, we describe the underlying geochemical process liable for F contamination as well as the factors controlling its spatiotemporal distribution in the Sedimentary Alluvial Plain (SAP) of Bankura District, West Bengal, India. To achieve the desired objective, representative groundwater samples were collected from tube wells and hand pumps at different locations of the study region during pre- and post-monsoon seasons. Collected samples were subjected to F and other hydrochemical analysis following standard test methods. Analysis shows that 37% of all groundwater samples collected during the pre-monsoon period have fluoride levels over 1.5 ppm (the limit specified by the World Health Organization, Geneva, 2004); however, the contamination level dropped to 30% during the post-monsoon period. The investigation of groundwater level changes indicates that, as water levels rise during the post-monsoon, F concentrations decrease due to the dilution effect. Piper trilinear diagram suggested Na-Ca-HCO3 type of groundwater for both seasons. According to Gibbs diagrams, rock-water interactions (mineral dissolution) are responsible for major ion chemistry in groundwater samples. Factor analysis (FA) of hydrochemical parameters revealed that the occurrence of F in groundwater was due to the weathering and dissolution of fluoride-containing minerals. X-ray diffraction (XRD) analysis of SAP sediments further confirmed the presence of fluoride-bearing minerals (muscovite and fluorite) in the subsurface lithology of the region. A substantial positive loading (> 0.75) of F with pH and bicarbonate for FA demonstrates that F is being leached from the host material by an alkaline-dominated environment. To account for the spatial variability and seasonality to the spatial change of F concentration in groundwater of the SAP, geographical information systems tools and inverse distance weighting interpolation method were used. The results revealed that significant spatiotemporal variability of F contamination was mainly influenced by the recharging rainwater and the average recharge altitude of groundwater in the area under study. The contamination level is significant in the elevated region where replenishing rainwater is more likely to come into contact with fluoride-bearing minerals when it infiltrates and percolates through the vadose zone. This phenomenon increases the F leaching through chemical weathering along groundwater flow pathways. The findings of this study can serve as a scientific foundation for the efficient management of F-contaminated groundwater in the SAP.

 

How to cite: Ghosh, A., Gogoi, N., Kartha, S. A., and Mondal, S.: Geochemical Evaluation and Spatiotemporal Distribution of Fluoride in Groundwater of the Sedimentary Alluvial Plain of Bankura District, West Bengal, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9327, https://doi.org/10.5194/egusphere-egu23-9327, 2023.

Dichlorodiphenyltrichloroethane (DDT) and its metabolites are highly toxic and pose chronic effects to the biosphere. As a natural storage pool, forests have great potential to capture them from the atmosphere and migrate them to the forest soil, which, in turn, influences the safety of the forest ecological environment. In this study, a systematical survey of DDT and its metabolites has been carried out to measure their spatial variations in Chinese forest soils. The main objectives of this study were to (1) investigate the levels, distribution and sources of DDT and its metabolites, and further estimate their mass inventories in Chinese forest soils, (2) explore the impact of soil properties on their distribution, and (III) assess the ecological and health risks of DDT and its metabolites. The research results were as follows. The average concentration of ΣDDTs reached up to 9.75 ng/g, and p,p’-DDT is the main component. Significant difference in the concentration of ΣDDTs was observed between the southeast and northwest regions (p<0.01), which may be related to multiple factors such as pesticide use, rainfall and altitude. The forest soil quality inventory is about 0.58×103 tons, which is lighter than that of domestic farmland soil. 56.1% of soil samples were less than the low value of risk assessment (ERL). The concentration of ΣDDTs in the East and middle is higher than that in the West, and the high value is mainly distributed in the coastal areas. DDTs were mainly from the input of the mixed source composed of industrial DDT and dicofol, of which at least 97% came from industrial DDT and up to 4% from dicofol. ΣDDTs was only positively correlated with precipitation and population density (p<0.05). The degradation of DDT in soil occured from primary stage to high stage. The possible degradation pathways involved in DDTs entering forest soil were preliminarily deduced. Firstly, the surrounding pollution sources volatilize DDTs from soils to the atmosphere through secondary emission. In this process, DDT was continuously transformed into DDE through photodecomposition. The atmosphere rich in DDTs were transported to the forest area and then into the forest surface soil through atmospheric dry and wet deposition. Then, DDT transported continuously accumulated and degraded in forest soil. In the alternation of anaerobic and aerobic process, the main degradation pathways are DDT→DDD→DDMU, DDT→dicofol+DBP, DDT→DDE→DDMU, DDMU→DDNU.

How to cite: Qu, C., Wang, R., and Sun, W.: The occurrence of dichlorodiphenyltrichloroethanes (DDT) and its metabolites in Chinese forest soils: Implications for sources and environmental processes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13317, https://doi.org/10.5194/egusphere-egu23-13317, 2023.

EGU23-15671 | ECS | Posters virtual | GI5.7

Spatio-temporal variations of phosphorus (P) fractions in surface sediments of the southern Caspian Sea 

Pooria Ebrahimi, Mohammad Javad Nematollahi, Hassan Nasrollahzadeh Saravi, Rolf David Vogt, Fariba Vahedi, and Mahdie Baloei

Sediments act as a sink and a secondary source of contaminants, accounting for a central part of coastal and marine biogeochemical cycles. Phosphorus (P) is a macronutrient that governs primary productivity and phytoplankton growth, but excess P influx results in algae bloom and deteriorates aquatic ecosystems. This study assesses seasonal fluctuations, spatial distribution and fractions of P in the sediments of the southern Caspian Sea. In this study, at eight sampling points, composite samples of the surface (from 0 to 10 cm) seabed sediments were collected at 10 and 30 m water depths. The sampling campaigns were carried out in the four seasons and a total of 64 sediment samples were obtained. Total organic matter (TOM), total P (TP) concentration and particle size distribution were determined. Then, P was fractionated using a four-step sequential procedure to quantify the loosely bound P (LP), the reductant soluble P (FeP), the metallic oxide-bound P (AlP) and the calcium carbonate (CaCO3) bound P (CaP). The inorganic P (IP) pool refers to the sum of LP, FeP, AlP and CaP, while the organic P (OP) was calculated by subtracting IP from TP.

The results show that seasonal fluctuations of mean TP were statistically insignificant (p-value > 0.05). Still, the highest levels were recorded in autumn (1555 mg kg-1), followed by winter (1405 mg kg-1), spring (1378 mg kg-1) and summer (1130 mg kg-1). These minor temporal variations in P levels are associated with the seasonal differences in the amount of runoff and the intensity of rivers discharging into the Caspian Sea, and thereby their sediment load and the physicochemical characteristics. The large riverine influx resulted in TP contamination hotspots in the river deltas of Anzali wetland, Babolrood and Sefidrud (northern Iran), where high loadings of suspended particles are discharged into the sea. The spatial TP distribution is thus site-specific and uneven. The main P fraction was CaP, reflecting the phosphate (PO43-) strong affinity for, and association with, calcium-bearing minerals. Only a minor fraction of P was determined as LP. The fraction of the mud-size particles was the main explanatory factor for the spatial distribution of overall low levels of non-residual (or bioavailable) P forms (i.e., LP, FeP and AlP) during spring and summer, while the sand fraction had the greatest explanatory value for the distribution of residual (non-bioavailable) P form (CaP) during autumn and winter. This study demonstrates that P bioavailability in sediments is mostly controlled by the physicochemical characteristics of the sediment material, which again is steered by seawater chemistry. A low content of bioavailable P fractions could therefore be related to the relatively low content of fine-grained (i.e. below 63 µm) particles in sediments of the southern Caspian Sea.

How to cite: Ebrahimi, P., Nematollahi, M. J., Nasrollahzadeh Saravi, H., Vogt, R. D., Vahedi, F., and Baloei, M.: Spatio-temporal variations of phosphorus (P) fractions in surface sediments of the southern Caspian Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15671, https://doi.org/10.5194/egusphere-egu23-15671, 2023.

This study reports on the unique results of the recently concluded Sediment-quality Information, Monitoring and Assessment System to Support Transnational Cooperation for Joint Danube Basin Water Management (SIMONA) project, the largest of its kind in Europe, which was carried out in 2018-2022 as a project of the EU DTP aiming at delivering a ready-to-deploy sediment-quality monitoring system for the effective and comparable measurements and assessment of sediment quality in surface waters in the Danube River Basin in accordance with the EU Water Framework Directive (WFD). The project has developed, tested, demonstrated an innovative environmental geochemical monitoring platform of fluvial (suspended, river bottom and floodplain) sediments using state-of-the-art automated and passive sampling technology for the contamination risk assessment according to the EU WFD in the Danube Basin. Time series analysis and signal processing of one year multi-variate and multi-matrice monitoring data could be used to identify the geochemical background, temporal trends, periodicities and contamination events in the studied EU-defined Hazardous Substances. Since the applied technology, methods and data interpretation is fully consistent with EU legislation risk assessment, results may provide a ‘best solution’ for the spatial and temporal discrimination of contamination. Results of biological contamination assessment of sediments using microbial tests are also presented.

Keywords: data analysis, geochemistry, mobility, speciation, enrichment, time series analysis

How to cite: Kovács, Z., Jordán, G., Szabó, P., and Bálint, M. and the SIMONA Project Team: Development, data modelling of environmental geochemical monitoring of fluvial (suspended, river bottom, floodplain) sediments using unique automated and passive sampling for the contamination risk assessment according to the EU WFD in the Danube Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15997, https://doi.org/10.5194/egusphere-egu23-15997, 2023.

EGU23-16075 | ECS | Orals | GI5.7

Assessing the soil baseline values of a geologically complex territory: the case study of Basilicata region. 

Annalise Guarino, Lucia Rita Pacifico, Antonio Iannone, Andrea Gramazio, and Stefano Albanese

The middle and lower reaches of the Basento river and the whole basin of the Cavone river, in Basilicata region (Italy), underwent to a geochemical prospecting involving soil and stream sediments. Specifically, 190 topsoils were collected within a depth range between 10-15 cm from the ground level and 10 bottom soils were sampled within the depth range between 80-100 cm. 

Samples were analysed at the Life Analytics laboratory (Battipaglia, Italy), by ICP-MS following an aqua regia digestion, to determine the concentrations of 16 potentially toxic inorganic substances (As, Be, Cd, Co, Cr, CrIV, Cu, Hg, Ni, Pb, Sb, Se, Tl, V, Zn, SO4).  

The purpose of the study has been the definition of the upper background limits (UBLs) for the investigation area. An exploratory data analysis (EDA) was conducted on the dataset to outline the main data structural characteristics. Due to the huge number of samples below detection limits (BDL) for Cd, CrIV, Hg, Se, Tl, only As, Be, Co, Cr, Ni, Pb, Cu, V, Zn and SO4 were considered for the UBLs definition. 

The estimate of the above-mentioned values has been conducted following a series of rigorous statistical tests in line with the "Guidelines for the determination of background values for soils and groundwater" released by the Italian National System for Environmental Protection (SNPA).  

In detail, after imputing the few BDL values found in the selected variables by means of K-nearest neighbors (k-NN) algorithm, topsoil and bottom soils data were considered as a whole. Indeed, the dataset was subdivided into 7 subsets according the geopedological units identified based on the local pedological and geological features. 

The BoxCox algorithm was applied to the single subsets to normalize data distribution before any statistical treatment. Outliers were identified by mean of the Dixon’s or Rosner’s Outlier tests depending on the sample size, the observation of boxplots and Q-Q plots and the spatial location of some samples considered as hotspots.  

For each variable and for each subset, two statical indices (i.e.:  95th upper tolerance limit with 95% coverage (95UTL95) and the 95th upper prediction limit (UPL95)) were calculated. The more conservative among them was chosen as representative for the UBLs.

Results showed that the UBLs found are much lower than the guideline values set by the Italian Environmental Law (Legislative Decree 152/2006). Our findings emphasized how the use of guideline values established at a national level is often inadequate to administrate a geologically and pedologically complex territory such as Italy, favoring the chance of running into a wrong identification of local environmental hazards.  

How to cite: Guarino, A., Pacifico, L. R., Iannone, A., Gramazio, A., and Albanese, S.: Assessing the soil baseline values of a geologically complex territory: the case study of Basilicata region., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16075, https://doi.org/10.5194/egusphere-egu23-16075, 2023.

EGU23-16151 | Posters on site | GI5.7

Potentially toxic elements (PTEs) in the soils of a densely populated active volcanic area: the Campi Flegrei case study in Italy. 

Stefano Albanese, Pooria Ebrahimi, Antonio Aruta, Domenico Cicchella, Fabio Matano, Benedetto De Vivo, and Annamaria Lima

The line of research on potentially toxic elements (PTEs) is of growing interest to the scientific community for protecting society against adverse health issues. The Campi Flegrei caldera in southern Italy is an active volcanic area where above two million people live, making it an ideal study area for investigating PTEs of natural and anthropogenic origin through the latest advances in geochemical data analysis. Therefore, a total of 394 topsoil samples (0 to 15 cm) were collected for determining the “pseudo-total” concentrations of elements in the <2 mm fraction using a combination of inductively coupled plasma-atomic emission spectrometry (ICP-AES) and inductively coupled plasma-mass spectrometry (ICP-MS), following aqua regia digestion.

The median values show that concentrations of Zn, Cu, Pb, V and As are greater (>10 mg/kg) than Cr, Co, Ni, Tl, Sb, Se, Cd and Hg. The geochemical maps generated by the Empirical Bayesian Kriging interpolation technique indicate that the higher concentrations of Pb, Zn, Cd, Cr, Hg, Ni and Sb are related to the greater population density (>6500 persons per Km2) in the urban area, but the elevated levels of As, Tl, Co, Cu, Se and V are observed in the other parts. In the context of compositional data analysis, the correlation diagram and robust principal component analysis detected: (1) the Pb–Zn–Hg–Cd–Sb–Cr–Ni association that likely shows anthropogenic activities such as heavy traffic load and fossil fuel combustion in the urban area; (2) the Al–Fe–Mn–Ti–Tl–V–Co–As–U–Th association that mostly represents the contribution of pyroclastic deposits; and (3) the Na–K–B association that probably reveals the weathering degree.

To choose the PTEs with potential health risks for the local inhabitants, the PTE quantities in soil are compared with the corresponding contamination thresholds established by the Italian legislation for residential land use. The Tl, Pb and Zn contents exceed the threshold in more than 15% of the collected samples, but Tl which derives from a natural source (e.g., leucite) is culled before evaluation. Then, children (0-6 years old) are considered for health risk assessment because: (1) Pb has significant adverse health effects in children; and (2) the more frequent hand-to-mouth behavior in children under 6 years old is linked to the higher chance of exposure. The probabilistic health risk modeling for the children <6 years old highlights negligible (hazard quotient below 1) Pb and Zn non-carcinogenic risk and unexpected (cancer risk ≤1E-06) Pb carcinogenic risk for exposure through soil ingestion. However, for the inhalation pathway, the children aged <1 year old have the highest chance (90%) of acceptable (i.e. from 1E-6 to 1E-4) Pb carcinogenic health risk. This should not be overlooked because Naples is under high environmental pressure and previous studies reported increased Pb and Zn quantities in soil between 1974 and 1999. Overall, the results of geostatistical interpolation, compositional data analysis and probabilistic health risk modeling potentially uncover the link between soil geochemistry and human health in densely populated active volcanic areas.

How to cite: Albanese, S., Ebrahimi, P., Aruta, A., Cicchella, D., Matano, F., De Vivo, B., and Lima, A.: Potentially toxic elements (PTEs) in the soils of a densely populated active volcanic area: the Campi Flegrei case study in Italy., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16151, https://doi.org/10.5194/egusphere-egu23-16151, 2023.

EGU23-16341 | ECS | Orals | GI5.7

87Sr/86Sr as an efficient tool to investigate environmental processes in winemaking: a Campania (Italy) case study. 

Piergiorgio Tranfa, Mariano Mercurio, Massimo D'Antonio, Valeria Di Renzo, Carmine Guarino, Rosaria Sciarrillo, Daniela Zuzolo, Francesco Izzo, Alessio Langella, and Piergiulio Cappelletti

In the last few years Sr isotope geochemistry has contributed substantially to environmental and food traceability research. This is achievable because soils, plants and waters all have a peculiar Sr isotopic signature (87Sr/86Sr) inherited from the local geological substratum and affected by geological processes as well as the age and initial rubidium concentration of the rocks. Strontium ions released from the bedrock by weathering processes deriving by the interaction of circulating fluids with rocks, enter the environment and accumulates in water and soils. This reservoir of bioavailable Sr may represent a reliable tracer useful to determine the geographical origin of wines as it is known that strontium is taken first by plant roots, then by grapes, and lastly by wine, with no isotope fractionation when compared to the original 87Sr/86Sr ratio in the soil and rocks. As a result, the study of the Sr isotope ratio in the final product (wine) links directly to its geological origin thus representing a specific geofingerprint for any selected wine. Based on these premises this work aims at confirming the strong link between the product (wine) and its territory, with the final purpose to make it recognizable and distinguishable from similar products and protecting it from possible fraud and adulteration. In this work the 87Sr/86Sr systematics has been used to analyze a total of 39 samples (37 soil samples and 2 wine samples) from Campania (Italy). For a better understanding, both total Sr fraction and bioavailable Sr fraction were analyzed in soil samples (rhizospheric soils, bulk soils and samples collected from different horizons) in order to better investigate the environmental processes involved during the wine production cycle.

How to cite: Tranfa, P., Mercurio, M., D'Antonio, M., Di Renzo, V., Guarino, C., Sciarrillo, R., Zuzolo, D., Izzo, F., Langella, A., and Cappelletti, P.: 87Sr/86Sr as an efficient tool to investigate environmental processes in winemaking: a Campania (Italy) case study., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16341, https://doi.org/10.5194/egusphere-egu23-16341, 2023.

EGU23-123 * | Orals | GMPV1.3 | Highlight

Dating a world-unique Pacific ruin: Nan Madol 

Chuuan-Chou (River) Shen, Felicia Beardsley, Shou-Yeh Gong, Osamu Kataoka, Minoru Yoneda, Yusuke Yokoyama, Leilei Jiang, Albert Yu-Min Lin, James Fox, Jason Barnabas, Gus Kohler, Zoe T. Richards, and Jean-Paul A. Hobbs

Great Holocene civilizations on Pacific islands were created by Homo sapiens. However, most of the construction histories remain uncertain due to the lack of developed writing system and the limitation of dating techniques. Nan Madol (0.7 km in width and 1.5 km in length), an abandoned city called the “Venice of the Pacific” with over 100 artificial islets, is located on the southeastern coast of island Pohnpei in Micronesia. This world-unique ruin, inscribed onto UNESCO’s World Heritage List in 2016, was built with basalt megaliths and scleractinian coral cobbles. Oral histories and previous charcoal 14C ages suggested that the main construction of Nan Madol of Pohnpei could begin in the 13th or 14th century and ceased at the 16th or 17th century, associated with the rise and fall of the Saudeleur Dynasty. However, after 150 years or more of studies, the timing of construction and the dynasty, and the probable influence of environmental factors, remain unresolved. High-precision U-Th dating techniques, developed at the High-Precision Mass Spectrometry and Environment Change Laboratory (HISPEC), Department of Geosciences, National Taiwan University, were used to date the selected pristine coral infills and reveal the construction time of the two ruins. With over 150 coral ages determined, results show a peak of construction activity during the middle 11th century could be related to the rise of the Saudeleur Dynasty. In the early 15th century, construction activities ceased, associated with the dynasty’s downfall. Our study shows that Nan Madol construction and the rise and fall of the dynasty occurred 2-3 centuries earlier than previously estimated. Moreover, the entire development was dominated by El Niño-Southern Oscillation variability and tectonic-related sea level rise.

How to cite: Shen, C.-C. (., Beardsley, F., Gong, S.-Y., Kataoka, O., Yoneda, M., Yokoyama, Y., Jiang, L., Lin, A. Y.-M., Fox, J., Barnabas, J., Kohler, G., Richards, Z. T., and Hobbs, J.-P. A.: Dating a world-unique Pacific ruin: Nan Madol, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-123, https://doi.org/10.5194/egusphere-egu23-123, 2023.

EGU23-265 | Orals | GMPV1.3

Mineral/Fluid interaction as a potential bias in calcite U-Pb dating 

Riccardo Lanari, Anda Buzenchi, Alessandro Bragagni, Bruno Dhuime, Mauro Brilli, Chiara Del Ventisette, Massimo Mattei, Sandro Conticelli, and Riccardo Avanzinelli

The application of U-Pb dating method performed on calcite has exponentially increased over the last years, since constraining the age of the crystallization for such syn-kinematic minerals, would provide a specific timing of faults movement. The potential gain of this approach is evident but the robustness of the U-Pb method performed on calcites has been not yet systematically tested.  Here, we firstly demonstrated that a mineral/fluid interaction indeed affects the regression of the 238U/206Pb and 207Pb/206Pb data-points and therefore the age; and secondly, we propose an innovative application of U-Pb dating method and a new strategy to identify and reject analytically robust isochrons.

We explore 36 samples, combining U-Pb dating performed with different methods along with carbon and oxygen stable isotopes compositions measured on the same fibres of calcite. The extremely high precision 207Pb/206Pb measured by Thermal Ionisation Mass Spectrometry  revealed that every sample experienced a certain degree of fluid interaction. We find no correlation between 238U/206Pb and the spread in δ18O. The higher spread in δ18O is instead coupled with a remarkable scattered data-points that yield U-Pb ages calculated with the different methods on the same samples with a large variability. In conclusion, our study demonstrates that great care must be taken when considering radiometric ages made on calcite since LA-ICP-MS large uncertainties might obscure the isotopic reorganization.

How to cite: Lanari, R., Buzenchi, A., Bragagni, A., Dhuime, B., Brilli, M., Del Ventisette, C., Mattei, M., Conticelli, S., and Avanzinelli, R.: Mineral/Fluid interaction as a potential bias in calcite U-Pb dating, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-265, https://doi.org/10.5194/egusphere-egu23-265, 2023.

EGU23-4234 | Orals | GMPV1.3

Application of carbonate U-Pb geochronology in dating of diagenesis and hydrothermal activity 

Zhongwu Lan, Nick M W Roberts, Shitou Wu, Fangyue Wang, Hao Wang, Rong Cao, Zhensheng Li, Ying Zhou, Kaibo Shi, and Bo Liu

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) U–Pb geochronology of calcite has been an emerging research direction in recent years that has been widely applied to various disciplines, such as dating of brittle deformation, biological biomineralization, oceanic crust alteration, and hydrocarbon migration. The method has the advantage of quickly locating regions of relatively high uranium content and radiogenic lead that avoids the time-consuming procedures traditionally required for isotope dilution methods. Herein, we show how this method is successfully applied to dating of diagenesis and hydrothermal activity in Precambrian-Phanerozoic sedimentary rocks, but with a note of caution that the susceptibility of the calcite U-Pb isotope system to fluid activities means interpretation of calcite U-Pb data and selection of calcite standard should be cautioned. We demonstrate the following case studies: LA-ICP-MS calcite U-Pb geochronology has aided in defining the Mesoproterozoic-Neoproterozoic boundary (ca. 1010 Ma) in North China Craton. It also constrains the timing of calcite infillings in the Ediacaran cap carbonate to be ca. 636 Ma, indicating an early diagenetic origin and thus confirming a methane seepage hypothesis. Two episodes of hydrothermal activity (ca. 290 Ma and ca. 250 Ma) have been recognized from the Cambrian carbonate in the Tarim region, which was induced by the Permian Tarim Large Igneous Province (LIP) and Indosinian orogeny, respectively.

How to cite: Lan, Z., M W Roberts, N., Wu, S., Wang, F., Wang, H., Cao, R., Li, Z., Zhou, Y., Shi, K., and Liu, B.: Application of carbonate U-Pb geochronology in dating of diagenesis and hydrothermal activity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4234, https://doi.org/10.5194/egusphere-egu23-4234, 2023.

The global-scale glacial events recorded by diamictite and cap carbonate couplets occurred in the late Neoproterozoic and has been recognized on at least 15 paleo-continents. Diamictite and cap carbonate couplets play a pivotal role in establishing regional stratigraphic correlations and understanding the extreme climatic conditions and glacial-interglacial cycles of the Neoproterozoic glaciation. Here we report newly discovered Neoproterozoic glaciogenic diamictite and cap carbonate couplet in the Longshoushan area at the southwestern margin of the Alxa Block, NW China. Based on detailed stratigraphic and sedimentologic studies, we identified massive and stratified diamictites at the bottom of the Hanmushan Group, both with poorly sorted and rounded gravels. The presence of glacial striations and ice-rafted dropstones in stratified diamictites supports a glaciogenic origin. The upward transition from massive diamictites to stratified diamictites indicates the process of glacier retreat. The occurrence of thin-bedded phyllites in the stratified diamictites suggests a short-term deglaciation during the glaciation. The 2- to 2.6-m-thick cap carbonates cover the stratified diamictites and consist of thinly laminated microcrystalline dolomites. The basal cap carbonates contain closely linked sheet cracks, cemented breccias, tepee-like structures and cavities. The cap carbonates show high-resolution 13CPDB chemostratigraphy and negative δ13C values (ca. −2.9 to −4.1‰), typical of the Marinoan cap carbonates. Regional sedimentary characteristics and the C-O isotope values suggest that the diamictites and cap carbonate couplet in the Alxa Block likely correspond to the Marinoan glaciation and subsequent deglaciation (ca. 635 Ma), not the previously assumed Ediacaran glaciation. Thus, the diamictite and cap carbonate sequence marks the Cryogenian-Ediacaran boundary in the Alxa Block and provides evidence for further stratigraphic correlation and investigation. This work was financially supported by NSFC projects (grants 42072264, 41730213, 41902229, 41972237) and Hong Kong RGC GRF (17307918).

How to cite: Shao, D., Han, Y., Li, M., Lu, L., Cao, X., and Ju, P.: Discovery of Neoproterozoic glaciogenic diamictites and cap carbonate couplet in the Alxa Block, NW China: Evidence from stratigraphic, sedimentologic and geochemical studies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4758, https://doi.org/10.5194/egusphere-egu23-4758, 2023.

There has been considerable debate as to whether the Korean peninsula has evolved as part of the Sino-Korean Craton since Neoarchean or whether it is a product of the amalgamation of several continental fragments in the early Mesozoic Era. The relationship between the Neoproterozoic Okcheon Metamorphic Belt (OMB) and the Early Paleozoic Tabaeksan Basin (TB) in the central region of the Korean Peninsula has the potential to provide an answer to this question. Various carbonate rocks appear in OMB, showing unique carbon isotope values ​​according to their geologic age.

The Hyangsanni Dolomite is distributed around the Gyemyeongsan Formation with metavolcanics of about 860 Ma. The Hyangsanni Dolomite has δ13C values between +2.9 ‰ and +6.2 ‰, markedly higher than the Cambro-Ordovician values, and are consistent with the Neoproterozoic values. Considering the low values ​​of 86Sr/87Sr, the deposition period of the Hyangsanni Dolomite is judged to be Tonian before the Sturtian Glaciation.

The Geumgang Limestone has a maximum thickness of several tens of meters adjacent to the diamictite layer proposed as a glacial deposit but shows a very extensible distribution. The δ13C values ​​of the Geumgang Limestone range from -12.25 to -7.88 ‰, suggesting that they may be cap carbonates. However, whether their deposition was related to the Sturtian Glaciation or the Marinoan Glaciation is not yet known.

Between the Cryogenian Seochangri Formation of OMB and the Cambrian Jangsan Formation of TB are carbonate rocks previously considered Ordovician. However, carbon and oxygen isotope values analyzed in this study require different interpretations. Zones with δ13C values ​​ranging from -3.4 to +1.3 ‰ agree with Ordovician seawater values. However, over a larger area, δ13C values ​​show mostly positive values ​​from +1.9 to +7.8 ‰. Also, a significant negative excursion of δ13C values ​​down to -6.9 ‰ occurs near the highest values ​​measured. These values correlate with Ediacaran or Early Cambrian carbonates better than Ordovician seawater. It is the first to discover the possible carbonate rocks of Ediacaran or Early Cambrian in South Korea, supporting that the Neoproterozoic OMB and Early Paleozoic TB have a tectonic evolutionary history of continuous deposition rather than an assembly of different continental fragments.

How to cite: Park, K.-H. and Ha, Y.: Carbon Isotopic Composition of Carbonates of the Okcheon Metamorphic Belt in South Korea from Neoproterozoic to Early Cambrian Potential: Geological and Tectonic Significance, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5196, https://doi.org/10.5194/egusphere-egu23-5196, 2023.

EGU23-5345 | ECS | Posters virtual | GMPV1.3

Calcite TLM and LSJ07: two natural reference materials for micro-beam U-Pb geochronology and C, O isotope ratio measurements 

Shitou Wu, Yueheng Yang, Rolf Romer, Nick M W Roberts, and Zhongwu Lan

U-Pb geochronology of calcite using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) is an emerging method, with potential applications to a vast array of geological issues. Accurate LA-ICP-MS calcite U-Pb dating requires matrix-matched RMs for the correction of instrumental mass bias of Pb/U ratios. Several materials are currently being used as RMs, including WC-1, Duff Brown Tank, ASH-15, JT, and AHX-1A. In this study, we will give a brief introduction of LA-ICP-MS lab at IGGCAS for carbonate U-Pb dating. Meanwhile we further characterized two calcite reference materials for micro-beam U-Pb geochronology and and C, O isotope ratio measurements. LA-ICP-MS multiple spot analyses (> 400) at different regions of materials reveal that calcite TLM and LSJ07 are homogeneous for the U-Pb age with 220.72 +/-0.98 Ma and 26.54+/-0.41 Ma respectively. SIMS multiple spot analyses (> 100) reveals calcite TLM is homogeneous for the O isotope ratio at mm special resolution. MAT 253 gives a bulk result of δ18O =-14.20 ‰. LA-MC-ICP-MS multiple spot analyses (> 200) reveals calcite TLM and LSJ07 are homogeneous for the C and O isotope ratio at mm special resolution. MAT 253 gives bulk results of δ13C =-1.53 ‰ andδ13C =-0.33 ‰ for TLM and LSJ07 respectively. These two materials represent a useful addition to the currently distributed WC-1, Duff Brown Tank, ASH-15, JT, and AHX-1A for micro-analytical techniques of U-Pb geochronology and C, O isotope ratio measurements.

How to cite: Wu, S., Yang, Y., Romer, R., Roberts, N. M. W., and Lan, Z.: Calcite TLM and LSJ07: two natural reference materials for micro-beam U-Pb geochronology and C, O isotope ratio measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5345, https://doi.org/10.5194/egusphere-egu23-5345, 2023.

EGU23-5865 | ECS | Posters virtual | GMPV1.3

Dating and characterizing carbonate rocks in Upper Permian reef-dolostone reservoir systems in Sichuan Basin, southwest China: implications for porosity evolution 

Binsong Zheng, Renjie Zhou, Chuanlong Mou, Jianxin Zhao, and Daryl Howard

Large gas fields are hosted in Upper Permian reef-dolostone bodies in Sichuan Basin, southwest China, among which the Puguang gasfield is the largest marine-carbonate gas system in China. The reservoir rocks are mainly composed of intensively dolomitized sponge-reefs constructed within platform margin reef facies in northern Sichuan Basin. Although major reservoir spaces consist of intercrystal pores, dissolved pores and vugs, the knowledge regarding the evolution of porosities is still limited. Using multiple methods, this study focuses on characterising different phases of carbonates (calcite and dolomite) to understand the dolomitization model and porosity evolution of the Upper Permian Panlongdong reef cropped out in northeastern Sichuan Basin. Two-dimensional high-resolution visualization of element contents in reef dolostones was provided by synchrotron-radiation Micro X-ray fluorescence elemental mapping. O and Sr isotope analysis was carried out to trace the nature of fluids during dolomitization. Laser ablation ICP-MS U-Pb dating was performed on dolomite minerals and secondary calcite cements. Our results suggest that: (1) dolomitization of the reef occurred in the early Middle Triassic (~245 Ma) due to the downward reflux of hypersaline seawater rich in Mg2+, accompanied by a significant increase in porosity because of the selective dissolution of low-Mg calcites; (2) in the Late Triassic, continental collision between South and North China plates induced uplifting and formation of a large quantity of (micro)fractures in northern South China, followed by Sr-depleted freshwater passing through the reef, leading to precipitation of secondary calcite cements (~206 Ma).

How to cite: Zheng, B., Zhou, R., Mou, C., Zhao, J., and Howard, D.: Dating and characterizing carbonate rocks in Upper Permian reef-dolostone reservoir systems in Sichuan Basin, southwest China: implications for porosity evolution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5865, https://doi.org/10.5194/egusphere-egu23-5865, 2023.

EGU23-7797 | ECS | Orals | GMPV1.3

H2O-present melting curve of magnesite and trace element distribution during melting of (dry) magnesite and calcite in the upper mantle 

Melanie J. Sieber, HansJosef Reichmann, Robert Farla, Oona Appelt, Marcus Oelze, Christian Lathe, and Monika Koch-Müller

The presence of magnesite (MgCO3) in the Earth’s mantle plays a fundamental role in reducing the melting point of the mantle [1] and forming carbonate‑rich melts such as kimberlites and carbonatites [2]. The melting curve of (dry) magnesite is well constrained [3, 4], but melting of magnesite in the presence of H2O, providing the basis for more complex (natural) systems, is poorly understood from some quenched experiments [5]. Also, the distribution of trace elements such as Li, Sr, Pb, and rare earth elements during melting of magnesite is poorly considered in models that evaluate the trace element budget of carbonate‑rich melts parental to kimberlites [6].

Here we report, first, the H2O‑present melting curve of magnesite between 2 and 12 GPa. The melting curve of magnesite mixed with 16 wt% brucite was established by in ‑ situ X‑ray diffraction measurements using the large volume press at P61B at PETRA III (DESY). Second, we report trace element partitioning data for congruent melting of calcite and incongruent melting of magnesite producing carbonate melt and periclase between 6 and 9 GPa. Those results were obtained from quenched experiments using a rocking multi‑anvil press at the GFZ overcoming equilibrium and quenching problems in previous studies [7].

 

1          Dasgupta and Hirschmann, The deep carbon cycle and melting in Earth's interior. Earth and Planetary Science Letters, 2010. 298(1-2): p. 1-13.

2          Jones, Genge, and Carmody, Carbonate Melts and Carbonatites. Reviews in Mineralogy and Geochemistry, 2013. 75(1): p. 289-322.

3          Solopova, Dubrovinsky, Spivak, Litvin, and Dubrovinskaia, Melting and decomposition of MgCO3 at pressures up to 84 GPa. Physics and Chemistry of Minerals, 2014. 42(1): p. 73-81.

4          Müller, Koch-Müller, Rhede, Wilke, and Wirth, Melting relations in the system CaCO3-MgCO3 at 6 GPa. American Mineralogist, 2017. 102(12): p. 2440-2449.

5          Ellis and Wyllie, Carbonation, hydration, and melting relations in the system MgO-H2O-CO2 at pressures up to 100 kbar. American Mineralogist, 1979. 64(1-2): p. 32-40.

6          Girnis, Bulatov, Brey, Gerdes, and Höfer, Trace element partitioning between mantle minerals and silico-carbonate melts at 6–12GPa and applications to mantle metasomatism and kimberlite genesis. Lithos, 2013. 160-161: p. 183-200.

7          Buob, Experiments on CaCO3-MgCO3 solid solutions at high pressure and temperature. American Mineralogist, 2006. 91(2-3): p. 435-440.

How to cite: Sieber, M. J., Reichmann, H., Farla, R., Appelt, O., Oelze, M., Lathe, C., and Koch-Müller, M.: H2O-present melting curve of magnesite and trace element distribution during melting of (dry) magnesite and calcite in the upper mantle, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7797, https://doi.org/10.5194/egusphere-egu23-7797, 2023.

EGU23-9499 | Orals | GMPV1.3

TILDAS measurement of multiple clumped isotope ratios in carbonates: progress and new horizons 

David Nelson, Scott Herndon, Zhennan Wang, Jay Quade, and David Dettman

Isotopic analysis using high resolution Isotope Ratio Laser Spectroscopy (IRLS) has been shown to be advantageous to multiple geochemical applications during the last decade.  These advances include isotopic analysis of the bulk isotopic compositions of water, carbon dioxide, methane and nitrous oxide.  More recently, laser spectroscopy has been used by several groups to examine the isotopic compositions of methane, carbon dioxide and nitrous oxide when carrying two rare isotopes (so called clumped isotopes).   Our recent work using Tunable Infrared Laser Direct Absorption Spectroscopy (TILDAS) has demonstrated highly accurate (~0.01 ‰) measurements of the clumped (16O13C18O or 638 in HITRAN isotope notation) isotopic composition of carbon dioxide derived from carbonate samples with spectroscopic measurement times of ~30 minutes using a dual laser spectrometer.  That spectrometer is optimized for the measurement of the four isotopologues required to calculate Δ638 (or Δ47).  We present here our parallel project to develop a novel dual laser isotope analyzer capable of measuring multiple carbon dioxide isotopic signatures simultaneously.   Specifically, we simultaneously measure the isotopic abundances of the three most abundant clumped isotopologues (Δ638, Δ637 and Δ828) as well as 17O oxygen excess or Δ17O.  Δ638 and Δ828 correspond to the quantities Δ47 and Δ48 when measured by isotope ratio mass spectroscopy (IRMS).   Δ17O is very difficult to measure with IRMS and Δ637 has not been previously measured with any technique to the best of our knowledge.  The new instrument utilizes carefully chosen spectral windows, operates at low sample pressure and exploits automated laser frequency hopping.  This prototype instrument simultaneously measures seven isotopologues of carbon dioxide: 626, 636, 628, 627, 638, 637 and 828.  Our preliminary results for Δ828 (or Δ48) are displayed as an Allan-Werle plot which shows that the precision in the measurement of Δ828 is ~0.09‰ for a single 3 minute sample measurement referenced to a working reference gas.  The plot shows that instrumental drift is very small over periods of several hours and that the precision can be improved to 0.03‰ by processing 10 sub-samples or to 0.01‰ by processing 100 sub-samples.  These measurements are preliminary and somewhat idealized but show promise for this new technique.

How to cite: Nelson, D., Herndon, S., Wang, Z., Quade, J., and Dettman, D.: TILDAS measurement of multiple clumped isotope ratios in carbonates: progress and new horizons, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9499, https://doi.org/10.5194/egusphere-egu23-9499, 2023.

For fundamental thermodynamic reasons, 13C-18O bonds in carbonate minerals formed under isotopic equilibrium conditions are more abundant than predicted for a random distribution of isotopes, yielding positive Δ47 clumped-isotope signatures which decrease as a function of formation temperature [1]. Although most Earth-surface carbonates are unlikely to achieve complete isotopic equilibrium, Δ47 values of many biogenic and abiotic calcites formed under very different crystallization conditions (and with irreconcilable water-calcite oxygen-18 fractionation laws) appear to follow indistinguishable temperature calibrations, as independently documented by various groups over the years [e.g., 2-4]. That is not to say that all groups agree on a single calibration linking Δ47 and temperature, and a recent comparison of 14 reprocessed calibration studies still found evidence for statistically significant inter-laboratory discrepancies [3]. Rigorous statistical tests aiming to prove or disprove consistency between Δ47 calibrations are particularly challenging because of potentially large and non-independent analytical errors associated with standardization procedures [5], and even in some cases by large correlations in the uncertainties of estimated formation temperatures, making classical least-squares regression approaches ill suited to model these calibration data sets.

Here I propose a new formulation for least-squares regression of data with an arbitrarily complex covariance structure linking all predictor and response observations, generally applicable to all sorts of geochemical data. I use this “Omnivariant Generalized Least-Squares” (OGLS) approach to compare 7 published Δ47 calibration data sets which have been (re)processed according to the newly established InterCarb Carbon Dioxide Equilibrium Scale (I-CDES), supposedly allowing robust comparisons between Δ47 measurements across laboratories [6]. None of these reprocessed calibration data sets are found to deviate significantly from a single, unified regression line, with an overall reduced chi-squared statistic (adjusted for data covariance according to OGLS) of 0.8 consistent with slightly overestimated uncertainties on temperature constraints. This finding marks another milestone in the 17-year-long progress of Δ47 thermometry, which has now solved most of the methodological challenges standing in the way of its widespread application to many scientific issues. In short: carbonate clumped-isotope thermometry is all grown up now.

[1] Schauble et al. (2006) 10.1016/j.gca.2006.02.011
[2] Kele et al. (2015) 10.1016/j.gca.2015.06.032
[3] Petersen et al. (2019) 10.1029/2018GC008127
[4] Anderson et al. (2021) 10.1029/2020GL092069
[5] Daëron (2021) 10.1029/2020GC009592
[6] Bernasconi et al. (2021) 10.1029/2020GC009588

How to cite: Daëron, M.: Making the Case for Reconciled Δ47 Calibrations Using Omnivariant Generalized Least-Squares Regression, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10066, https://doi.org/10.5194/egusphere-egu23-10066, 2023.

EGU23-10706 | ECS | Posters virtual | GMPV1.3

Geochemical and geochronologic investigations into carbonate veins from historical drill cores in undercover Mt Isa, NW Queensland 

Xingyu Chen, Renjie Zhou, David Wood, Daniel Stirling, Kamalendra Jhala, Ira Friedman, Matt Valetich, and Lizzy Philippa

This study investigates carbonate veins in five drill cores archived at Geological Survey of Queensland from NW Queensland, ~100 km south of Mt Isa, with geochemical and geochronologic approaches in order to characterise origins of fluids and their mineralisation potentials. Carbonate veins are mostly hosted in Proterozoic age (approximately 1800-1650 Ma) supra-crustal rocks, which are inferred from geophysics to be covered by 350 to 2,000 m of younger sedimentary rocks of the Eromanga and Georgina basins. Data regarding the nature of fluid activities is important for comparison between the undercover southern Mt Isa and outcropped Mt Isa mineral district, which is a world-class mineral province.

Multiple-phase carbonate veins (mostly calcite and dolomite) are identified, including late formed brittle veins, pyrite/chalcopyrite mineralisation-bearing carbonate veins, and calcite hosted in crackle breccias. Samples are prepared into one-inch polished mounts and studied with SEM-EDS, and in situ laser ablation ICP-MS for geochemical and U-Pb geochronological studies. Relatively pure calcite phases are also prepared with microdrill for stable isotope C and O analysis. Trace element datasets suggest enrichments in rare earth elements and ytterbium (REE+Y) with distinct negative Eu anomalies. Stable isotopes range ~-5 to – 15 (δ13CVPDB‰) and ~10 to 25 (δ18OVSMOW‰). Trace element data, Yb/La and Yb/Ca ratios, and stable isotope signatures imply that these carbonate veins have hydrothermal origins. 206Pb/238U geochronology data has indicated multi-phase calcite formation ranging from the late Neoproterozoic to Cretaceous. Our results provide a novel dataset to demonstrate the use of carbonate veins in revealing fluid activities in a mineral district and help the future exploration of critical mineral deposits in undercover southern Mt Isa when interpreted against regional structural data and well-documented mineralisation events in the northern Mt Isa district.

 

How to cite: Chen, X., Zhou, R., Wood, D., Stirling, D., Jhala, K., Friedman, I., Valetich, M., and Philippa, L.: Geochemical and geochronologic investigations into carbonate veins from historical drill cores in undercover Mt Isa, NW Queensland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10706, https://doi.org/10.5194/egusphere-egu23-10706, 2023.

EGU23-12216 | ECS | Orals | GMPV1.3

Triple oxygen isotope analyses of carbon dioxide, water and carbonates by VCOF-CRDS technique 

Justin Chaillot, Mathieu Daeron, Mathieu Casado, Amaelle Landais, Marie Pesnin, and Samir Kassi

Oxygen-17 excess (Δ17O) in carbonate minerals can provide valuable insights into past continental and marine environments, long-term trends in the temperature and oxygen-isotope composition of ancient oceans, isotopic disequilibrium effects in biogenic and abiotic carbonates, and cryptic diagenesis. Triple oxygen isotope analyses of carbonates and/or CO2 using isotope-ratio mass spectrometers (IRMS) remain challenging, however, because of isobaric interference between 16O13C16O and 16O12C17O. Using spectroscopic methods, the abundance of each CO2 isotopologue may be directly quantified, potentially providing simple, non-destructive measurements of δ13C, δ18O and Δ17O on small samples of CO2.

Here we report new data characterizing the application of VCOF-CRDS (V-shaped Cavity Optical Feedback - Cavity Ring Down Spectroscopy [1]) to the analysis of small samples (<40 μmol) of pure CO2, as typically produced by phosphoric acid digestion of carbonate minerals.

Instrumental drifts from various sources are observed to bias apparent isotopic abundances by a few tens of ppm, but these drifts are slow enough that they may be precisely monitored and corrected for by repeated analyses of a working gas interspersed between other analyses, requiring only ~8 mn per aliquot and 30 mn between consecutive “unkown” analyses. This approach was tested by analyzing repeated aliquots of another CO2 tank with a different isotopic composition, yielding instrumental repeatabilities of 12 ppm, 13 ppm and 7.4 ppm for δ13C, δ18O and Δ17O, respectively (95 % CL, Nf = 66).

The accuracy of our measurements was tested over a wide range of Δ17O values spanning 130 ppm, by analyzing CO2 equilibrated at 25 °C with different waters whose triple oxygen compositions were independently constrained in the SMOW-SLAP scale by IRMS measurements and by simple nonlinear mixing predictions. We find that our Δ17O measurements are well within analytical uncertainties of predicted values (RMSE = 1.2 ppm), with analytical repeatabilities (including isotopic equilibration and gas manipulation) of 8.6 ppm (95 % CL, Nf = 27).

We will also report the results of our ongoing investigation regarding the isotopic fractionation and analytical noise associated with different acid digestion protocols at different reaction temperatures, and the triple oxygen composition of various international reference materials already used for δ13C, δ18O, and clumped-isotope measurements.

Based on these results, we conclude that VCOF-CRDS offers excellent accuracy, along with state-of-the-art levels of analytical precision/linearity, for straightforward analyses of 17O excess in CO2, water, and carbonate minerals.

[1] Stoltmann et al. (2017) 10.1021/acs.analchem.7b02853

How to cite: Chaillot, J., Daeron, M., Casado, M., Landais, A., Pesnin, M., and Kassi, S.: Triple oxygen isotope analyses of carbon dioxide, water and carbonates by VCOF-CRDS technique, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12216, https://doi.org/10.5194/egusphere-egu23-12216, 2023.

EGU23-12645 | Posters on site | GMPV1.3

The onset of the Ediacaran Nama Group sedimentation in Namibia? 

Inigo Andreas Müller, Fabio Messori, Marcel Guillong, Giovan Peyrotti, Michael Schirra, Elias Samankassou, Ulf Linnemann, Mandy Hofmann, Johannes Zieger, Agathe Martignier, Anne-Sophie Bouvier, Torsten Venneman, Kalin Kouzmanov, and Maria Ovtcharova

The final stage of the Proterozoic, the Ediacaran, shields fascinating insights on the development and dispersal of complex metazoans related to dramatic compositional changes in the atmosphere and hydrosphere.  Alternating sequences of siliciclastic and carbonate rocks of the Namibian Nama basin record the final stage of the Ediacaran and contain a vast amount of soft-bodied fauna, as well as some of the first biocalcifying organisms. However, the sparsity of ash beds at the base of the Nama group, preclude accurate and precise constraints on the onset of the Ediacaran biota in Nama group and correlation with chemo stratigraphic records worldwide.  

Due to the scarcity of ash layers, we apply U-Pb dating to carbonate rocks especially from the lower stratigraphic sections of the Nama Group combining the spatial resolution of LA-ICP-MS and the high-precision ID-TIMS U-Pb dating. The combination with mineralogical and geochemical techniques (d13C, d18O, XRD, SEM, EPMA, CL imaging, LA trace element transects, Raman spectroscopy, clumped isotope thermometry, QEMSCAN, SIMS) enables us to better understand the nature of the analyzed carbonates to distinguish between more pristine and diagenetic phases.

This study elaborates on the potential and limitations of carbonate U-Pb dating for improved stratigraphic correlation on these ancient pre-Cambrian marine carbonates from the Nama Group.

How to cite: Müller, I. A., Messori, F., Guillong, M., Peyrotti, G., Schirra, M., Samankassou, E., Linnemann, U., Hofmann, M., Zieger, J., Martignier, A., Bouvier, A.-S., Venneman, T., Kouzmanov, K., and Ovtcharova, M.: The onset of the Ediacaran Nama Group sedimentation in Namibia?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12645, https://doi.org/10.5194/egusphere-egu23-12645, 2023.

Carbonate veins are ubiquitous in many ore deposits and are often interpreted as a late stage or cross cutting fluid flow events in the ore deposit history. Faults accommodate rock displacement and the resulting zones of weakness act as conduits for magma and localised magmatic-hydrothermal fluid flow, leading to the formation of ore deposits. Dating of both low temperature veins and brittle fault material has been notoriously difficult because of a lack of ‘datable’ material. Using innovative techniques, it is now possible to date carbonate with the U-Pb isotopic system.

Here we use in-situ U-Pb carbonate geochronology to date a variety of fault material and mineralised and unmineralised veins within a major fault-controlled Cu-Au-Mo porphyry system in the central Yukon, Canadian Cordillera. Over 50 samples have been dated, revealing a long history of faulting and fluid flow in the deposit spreading over 10s of millions of years between ~75 Ma and <20 Ma. We combine petrography, U-Pb carbonate geochronology, trace element geochemistry, and clumped isotope analysis to interpret the full temperature-time evolution of the fluids within the deposit. Our results show the carbonate veins crystallised during the main ore-forming event at ~75 Ma. Subsequently, there was a prolonged period of fault-controlled fluid pulsing that likely concentrated metallic minerals in the deposit. The findings show that carbonate veins are not always late features within ore deposits and are an underutilised resource for understanding the full temporal and fluid evolution of a system. Carbonate U-Pb geochronology is therefore potentially incredibly useful for telling the previously untold and long history of fluid flow in a variety of deposit types.

How to cite: Mottram, C., Kellett, D., Dennis, P., and Clog, M.: Longevity of fault-controlled fluid flow within a Cu-Au-Mo porphyry (Yukon, Canada) revealed by coupled U-Pb carbonate geochronology and clumped isotope analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13236, https://doi.org/10.5194/egusphere-egu23-13236, 2023.

EGU23-13798 | ECS | Posters virtual | GMPV1.3

Evolution of the hydrothermal fluids of the Yolindi Fe-Cu skarn deposit, Biga peninsula, NW Turkiye: Evidence from carbon-oxygen isotopic variations of calcite minerals 

Mustafa Kaya, Mustafa Kumral, Amr Abdelnasser, Cihan Yalçın, Sercan Öztürk, Hatice Nur Bayram, and Beril Tanç-Kaya

This work deals recently with the carbon (δ13C) and oxygen (δ18O) isotopic variations in the calcite associated with the hydrothermal mineralization to comprehend the nature of the ore fluid and its source and the evolution of the Yolindi Fe-Cu skarn deposit at North of Biga peninsula (NW Turkiye). The Yolindi area is made up of Torasan Formation (marble, hornfels, phyllite, and schist) which was intruded by Oligocene Hallaçlar volcanic rocks and later early Miocene Şaroluk plutonic rocks. The Yolindi Fe-Cu skarn deposit has been formed along the eastern contact of Şaroluk pluton with the Torasan Formation having widespread prograde and/or retrograde skarn, silicic, and carbonate (calcite) alteration. The prograde skarn is less observed and characterized by formation of garnet with subordinate magnetite. While, the retrograde skarn is highly extensive having epidote, actinolite, chlorite, and carbonate including pyrite, magnetite, chalcopyrite, and specular hematite with subordinate sphalerite and galena. Malachite, azurite, goethite, hemimorphite, and cerussite represent the supergene minerals which locally replaced Fe-oxide and Fe-Cu±Zn±Pb sulfide minerals. At the Yolindi Fe-Cu skarn deposit, carbon and oxygen isotope ratios of calcite minerals from the exoskarn zone are -15.5 to -2.0 ‰ relative to PDB and 0.9 to 17.9 ‰relative to V-SMOW, respectively. Furthermore, it was inferred from the calculated carbon isotopic composition of an ore-forming fluid (δ13CCO2 = -12.7 to +0.8 ‰) that the carbon in the fluid is identical to the reduced carbon in sedimentary and metamorphic rocks. However, the calculated fluid's δ18OH2O values—which vary from 0.9 to 17.2 ‰VSMOW—indicate a mixture of metamorphic and magmatic origins for the hydrothermal fluid. This fluid mixing which has high range of C-O isotopic compositions has been due to a temperature effect along with either CO2 outgassing or fluid/rock interactions. Additionally, the mineralizing fluid is most likely derived from the metamorphic dehydration of carbonate rocks in the Torrasan Formation during Yolindi skarn formation.

Keywords: carbon (δ13C) and oxygen (δ18O) isotope; Fe-Cu Yolindi skarn deposit; Biga peninsula; NW Turkiye

How to cite: Kaya, M., Kumral, M., Abdelnasser, A., Yalçın, C., Öztürk, S., Bayram, H. N., and Tanç-Kaya, B.: Evolution of the hydrothermal fluids of the Yolindi Fe-Cu skarn deposit, Biga peninsula, NW Turkiye: Evidence from carbon-oxygen isotopic variations of calcite minerals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13798, https://doi.org/10.5194/egusphere-egu23-13798, 2023.

EGU23-15731 | ECS | Posters on site | GMPV1.3

Variability of (234U/238U) in surface water and tufa deposits: A study in the Mono Basin, California, USA 

Ke Lin, Sidney R. Hemming, Guleed Ali, In-Tian Lin, Chih-Chieh Su, Scott W. Stine, N. Gary Hemming, and Xianfeng Wang

Uranium concentrations and 234U/238U activity ratios (δ234U) of Earth’s surface waters can provide independent and complementary information on changes in weathering regime and hydroclimate. The response of δ234U variation in surface waters in US Great Basin to climate change however remains unclear, which brings ambiguities in interpreting δ234U in aquatic carbonate deposits. Here, we analysed U concentration and δ234U in a suite of surface waters (creeks, springs and lake) as well as tufa deposits from the last glacial lake highstands in the Mono Basin, California, USA to assess the modern uranium budget in the lake water and the controlling factors on its δ234U. We find that U concentrations in groundwater springs are about one order of magnitude higher than those of creek waters. Hence, even though springs only deliver about 15% of annual inflow to the lake, they contribute 70% of U in the lake water. The residence time of U in lake water is calculated to be approximately 15,000 years, on the same order as those of Li, Na, and Cl, but significantly longer than those of alkaline earth elements. The δ234U in Mono Lake water is 180‰, same as in modern-day tufa deposits. The δ234U in lake highstand tufas is ~ 220‰, suggesting much more enhanced physical weathering associated with mountain glacial activities in the basin, even though chemical weathering was also stronger due to increased precipitation. On the other hand, the higher δ234U values (~ 250‰) in modern creeks and springs is consistent with the overall dry environment and stronger physical weathering in the basin. The 40‰ decrease in δ234U of lake water however cannot be explained by radiative decay. We hypothesis that lake water was more frequently stratified in the past, during the last glacial in particular, and the resulted anoxic environment in deep lake water has probably facilitated precipitations more enriched in 234U. 

How to cite: Lin, K., Hemming, S. R., Ali, G., Lin, I.-T., Su, C.-C., Stine, S. W., Hemming, N. G., and Wang, X.: Variability of (234U/238U) in surface water and tufa deposits: A study in the Mono Basin, California, USA, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15731, https://doi.org/10.5194/egusphere-egu23-15731, 2023.

EGU23-15952 | ECS | Posters on site | GMPV1.3

Crack-seal veins: records of 600-million-year complex tectonic and fluid flow evolution in Saudi Arabia 

Adhipa Herlambang, Ardiansyah Koeshidayatullah, Chaojin Lu, Abduljamiu Amao, Abdulwahab Bello, Faisal Al-Ghamdi, Muhammad Malik, and Khalid Al-Ramadan

The Ediacaran Period (635-538 Ma) was marked by considerable tectonic activity, including the end of the Pan-African episode – a long interval of mountain building, rifting, and reorganization spanning most of the Neoproterozoic Era. In Saudi Arabia, the Ediacaran outcrops were developed and preserved in several isolated half-grabens linked to the Ediacaran to early Cambrian Najd strike-slip fault system. This fault system manifested, particularly in the study area, as intensive fractures with a distinctive crack-seal veins morphology. Understanding the mechanism and origin of such fractures could provide unique insights into the structural evolution and paleo fluid flow throughout the history of the Arabian Plate. However, no studies have focused on different structural-controlled diagenetic processes in the Neoproterozoic sequences across the Arabian Plate. Here, we examined precipitated veins along a well-exposed 300 m thick Ediacaran host rock exposure by integrating high-resolution geochemical analyses, carbonate clumped isotopes, fluid inclusions, advanced petrography analysis of Cathodoluminescence microscopy to unravel the structural diagenesis of these Ediacaran strata. The δ18O and δ13C of the carbonate host rocks vary from -11.79 to -7.83‰, and -0.58‰ to 1.1‰, respectively. The estimated paleotemperature of the host rock derived from the clumped isotope is 47-60°C. Furthermore, the current results show that the calcite veins appear in different stages, orientations, geometries, and mineralogy. The δ18O and δ13C of the crack-seal veins vary between -11.2 to -7.8 ‰ and -2.9 to 1.9‰, respectively. The estimated clumped-derived paleotemperature of this vein is 95°C, even higher up to 136°C by utilizing the fluid inclusions. On the other hand, the Mn-rich later phase veins, which cross-cut the crack-seal veins, indicate an isotopic composition of -10.9 to -10.6‰ for δ18O and -18.2 to -15‰ for δ13C, with the estimated paleotemperature of 74-84°C. Hence, we argue that the structural diagenesis history in the study area comprises several distinct tectonic events and fluid circulation members along the fractures associated with different stages of basin evolution. Our findings, for the first time, offer a new understanding of paleo fluid circulation and also highlight the multi-proxy’s potential for investigating the structural diagenesis of calcite veins in the Ediacaran host rock in Arabia.

How to cite: Herlambang, A., Koeshidayatullah, A., Lu, C., Amao, A., Bello, A., Al-Ghamdi, F., Malik, M., and Al-Ramadan, K.: Crack-seal veins: records of 600-million-year complex tectonic and fluid flow evolution in Saudi Arabia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15952, https://doi.org/10.5194/egusphere-egu23-15952, 2023.

EGU23-15974 | ECS | Orals | GMPV1.3 | Highlight

LA-ICP-MS U-Pb carbonate geochronology and its geological applications 

Shitou Wu, Nick Roberts, and Zhongwu Lan

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) U-Pb geochronology for carbonate minerals, calcite in particular, is rapidly gaining popularity as an absolute dating method. In this study, we review the latest technical progress in LA-ICP-MS carbonate geochronology, including the pre-screening strategies (on-line spot selection with a threshold, image-guided approach, and image-based approach), preferred instrumentation (Q-ICP-MS, SF-ICP-MS and MC-ICP-MS), calibration methods, common Pb corrections and the development of reference materials, with the aim of further improving the precision and accuracy of this technique. We emphasized the characterization of two calcite reference materials (TLM and LSJ07) for micro-beam U-Pb geochronology and C, O isotope ratio measurements. The latest geological applications of LA-ICP-MS U-Pb carbonate geochronology in dating of diagenesis and hydrothermal activity were reviewed.

How to cite: Wu, S., Roberts, N., and Lan, Z.: LA-ICP-MS U-Pb carbonate geochronology and its geological applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15974, https://doi.org/10.5194/egusphere-egu23-15974, 2023.

EGU23-16279 | ECS | Posters on site | GMPV1.3

Interpreting hydrothermal clumped isotope temperatures in the Irish Zn-Pb ore field 

Aileen Doran, Steven Hollis, Julian Menuge, Alina Marca, Paul Dennis, and David van Acken

With the introduction of climate action plans by many countries globally, the development of green technologies like electric vehicles and renewable infrastructure is expected to increase. These technologies are resource intensive, meaning we will require increased production of metals to meet the growing demands of society. However, discovery and exploration rates are not increasing at the same rate as demand. Improving understanding of ore system formation and evolution is a crucial step in aiding future exploration, to help supply these critical resources.

In hydrothermal systems, carbonate minerals (e.g., calcite and dolomite) are often associated with all stages of ore formation, with fluid inclusion thermometry and carbon-oxygen (C-O) isotope ratios traditionally used to study fluid temperature and composition. However, there are several challenges still remaining with these techniques, with fluid inclusions often too small, ruptured or deformed for adequate study. In carbonate minerals, the rare, heavy isotopes 13C and 18O bond or clump more frequently at lower temperatures, with the magnitude of clumping inversely temperature-dependent. Measurement of clumped C-O isotope ratios, using gas source isotope spectrometry, simultaneously yields carbonate δ13C and δ18O values and generates mineral precipitation temperatures, allowing fluid δ18O to be directly calculated. While traditionally applied to low temperate environments, recent applications have included hydrothermal ore systems to study fluid temperature and mixing. When combined with other techniques, such as strontium isotopes, new understanding of the sources, movement and compositional evolution of fluids can be deciphered.

Recent clumped C-O and strontium isotope analyses of ore-related carbonates from the Lisheen and Galmoy deposits, southern Irish Zn-Pb ore field, have facilitated the study of fluid sources, temperatures, mixing, and modification. Lisheen and Galmoy are  hosted in a belt of regionally dolomitized Lower Carboniferous (Mississippian) marine limestones, cut by a series of NE-SW-trending ramp-relay normal faults. Study of these deposits reveals that early dolomitizing and later hydrothermal fluids are part of a complex multistage continuum, with phases of fluid mixing, compositional buffering due to dissolution, and isotope resetting. Consequently, studies of carbonates in other deposits may yield new insights into ore formation, ultimately helping exploration for crucial resources.  

How to cite: Doran, A., Hollis, S., Menuge, J., Marca, A., Dennis, P., and van Acken, D.: Interpreting hydrothermal clumped isotope temperatures in the Irish Zn-Pb ore field, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16279, https://doi.org/10.5194/egusphere-egu23-16279, 2023.

The purpose of this abstract is to describe a coupled CFD-MPM model that combines soil mechanics (saturated sediments) with fluid mechanics (seawater or air) as well as solid mechanics (structures) to consider interactions between soil, fluid, and structures. With this formulation, the Material Point Method, which models large deformations in porous media and structures in conjunction with the Implicit Continuous-fluid Eulerian Method, which models complex fluid flows, is combined to model large deformations in porous media and structures. The model has been validated through various benchmarks and then it is used to simulate submarine landslides due to earthquakes. It is shown that this model captures the complicated interactions between saturated sediment, seawater, and offshore structures. This allows us to estimate the impact of potential submarine landslides on offshore structures using the model. 

How to cite: Tran, Q. A.: A hybrid MPM-CFD model for simulating earthquake-induced submarine landslides, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-112, https://doi.org/10.5194/egusphere-egu23-112, 2023.

EGU23-1131 | ECS | Orals | NH3.11

Landsifier: A python library to estimate likely triggers and types of landslides 

Ugur Ozturk, Kamal Rana, Kushanav Bhuyan, and Nishant Malik

The accuracy of landslide hazard models depends on landslide databases for model training and testing. Landslide databases frequently lack information on the underlying triggering mechanism (i.e., earthquake, rainfall), rendering them nearly useless in hazard models.

We created Landsifier, a Python-based unique library with three different machine-Learning frameworks for assessing the likely triggering mechanisms of individual landslides or entire inventories based on landslide 2D platforms and 3D shapes relying on an underlying digital elevation model (DEM). The base method extracts landslide planform properties as a feature space for the shallow learner-random forest (RF). An alternative approach uses 2D landslide images as input for the convolutional neural network deep learning algorithm (CNN). The final framework uses topological data analysis (TDA) to extract features from 3D landslide surfaces, which are then fed into the random forest classifier as a feature space. We tested the developed methods on six inventories spread over Japan. We achieved mean accuracy ranging from 70% to 98%.

Advancing this trigger classifier, we are working on the next generation to classify also the landslide types (i.e., flows, slides, falls, complex) similarly.

How to cite: Ozturk, U., Rana, K., Bhuyan, K., and Malik, N.: Landsifier: A python library to estimate likely triggers and types of landslides, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1131, https://doi.org/10.5194/egusphere-egu23-1131, 2023.

EGU23-1600 | ECS | Orals | NH3.11

Nonsmooth simulations of 3D Drucker-Prager granular flows and validation against experimental column collapses 

Gauthier Rousseau, Thibaut Métivet, Hugo Rousseau, Gilles Daviet, and Florence Bertails-Descoubes

Testing advanced numerical hydro-mechanical models against well-controlled experiments is a critical step in improving our understanding of unsteady granular mass flows, and necessary to provide some domains of validity for any further risk assessment.
To this end, experimental granular collapses were performed to evaluate the sand6 numerical simulator introduced by Daviet & Bertails-Descoubes (2016), which represents the granular medium as an inelastic and dilatable continuum subject to the Drucker-Prager yield criterion in the dense regime, and computes its dynamics using a 3D material point method (MPM). A specificity of this numerical model is to solve such the Drucker-Prager nonsmooth rheology without any regularisation, by leveraging tools from nonsmooth optimisation.
This nonsmooth simulator, which relies on a constant friction coefficient, is able to reproduce with high fidelity various experimental granular collapses over inclined erodible beds, provided the friction coefficient is set to the avalanche angle - and not to the stop angle, as generally done. The results, obtained for two different granular materials and for bed inclinations ranging from 0° to 20°, suggest that a simple constant friction rheology choice remains reasonable for capturing a large variety of granular collapses up to aspect ratios in the order of 10.
Investigating the precise role of the frictional walls by performing experimental and simulated collapses with various channel widths, we find out that, unlike some assumptions formerly made in the literature, the channel width has lower influence than expected on the granular flow and deposit.
The constant coefficient model is extended with a hysteresis model, thereby improving the predictions of the early-stage dynamics of the collapse. This illustrates the potential effects of such phenomenology on transient granular flows, paving the way to more elaborate analysis.

How to cite: Rousseau, G., Métivet, T., Rousseau, H., Daviet, G., and Bertails-Descoubes, F.: Nonsmooth simulations of 3D Drucker-Prager granular flows and validation against experimental column collapses, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1600, https://doi.org/10.5194/egusphere-egu23-1600, 2023.

Abstract: The occurrence time of investigated landslide hazard is not complete, leading to an error in the statistical relationship between rainfall and landslide. And the low accuracy of the critical rainfall threshold model will be built. And further, it will lead to an increase in the false positive rate of meteorological early warning. This study takes rainfall-induced landslides in the Wanzhou District of Chongqing from 1995 to 2015 as the research object. And Henghe Township, where historical disaster data is missing seriously, is the verification area. This study proposes a prediction model of the daily temporal probability of landslides occurrence on a certain day based on Long Short-Term Memory (LSTM) and Temporal Convolutional Network (TCN). The method is used to reconstruct the temporal information of rainfall-induced landslide events by simulating the nonlinear relationship between the occurrence time of landslides and rainfall. The landslide events after the reconstruction of temporal information were verified and selected, and then applied to the reasonable division of the E-D effective rainfall threshold curve, so as to establish the landslide meteorological warning model. The average temporal probability of rainfall-induced landslide occurrence on a certain day predicted by the proposed method reached 90.33%, which is higher than that of ANN (71.17%), LSTM (72.75%), and TCN (86.91%). Based on the temporal probability of landslide occurrence on a certain day which is higher than the 90% probability threshold, 18-time information including 42 landslides in Henghe Township of the verification area is expanded to 201. Compared with only using the historical landslide events, the meteorological warning model based on the expanded time information has a more reasonable warning classification, and the effective warning rate in the severe warning level is increased by 42.86%. The model method in this study is of constructive significance to the daily temporal probability prediction of rainfall-induced landslides on the regional scale and is helpful for the government to accurately model the risk decision of landslide meteorological warning.

How to cite: Zhao, Y. and Chen, L.: Rainfall-induced Landslide temporal probability prediction and meteorological early warning modeling based on LSTM_TCN model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1702, https://doi.org/10.5194/egusphere-egu23-1702, 2023.

The Jurassic red-strata of the Three Gorges Reservoir Area in China is interbedded of thick siltstone and thin sandy-mudstone and contains many clay minerals, such as montmorillonite and illite, which is water sensitive, weak and expansive, and easy to decompose by water weathering. In particular, due to the seasonal rainfall, development of settlements, and large-scale reservoir impoundment, many slow-moving landslides (e.g., deep rotation and planar landslides) often occur. Notwithstanding, the reconnaissance, updating, and mapping of kinematic features of township area landslides lack the appropriate attention of the government and researchers. Landslide susceptibility mapping is necessary prerequisites for landslide hazard and risk assessment. But a certain proportion of unpredictability is always closely related to modeling. The main objective of this work is to introduce deep ensemble learning into landslide susceptibility assessment to improve the performance of maximum likelihood models. Therefore, the current model construction has focused on three basic classifiers: decision tree, support vector machine, multi-layer perceptron neural network model, and two homogeneous ensemble models: random forest and extreme gradient boosting. Two prominent ensemble techniques—homogeneous/heterogeneous model ensemble and bagging, boosting, stacking ensemble strategy—were applied to implement the deep ensemble learning. Then, thirteen influencing factors were prepared as predictors and dependent variables. The landslide susceptibility maps were validated by the area under the receiver operating characteristic curve. The results of validation showed that the ensemble model shows that the ROC/AUC value is higher than 0.9, which is improved compared with the basic classifiers. Deep ensemble learning focuses more on detecting the landslide susceptibility area with the highest probability of occurrence. The Stacking based RF-XGBoost model obtained the best verification score (AUC=0.955). The comparison between the susceptibility map and landslide inventory data is encouraging as most of the recorded landslide pixels (about 83.3%) are at a high susceptibility level. Besides, from the information gain rate, we found that the Yangtze River and human engineering activities mainly affect the results, which is consistent with the current situation in the study area. The research results in the township-level landslide susceptibility map can also be extended to other urban and rural areas affected by landslides to reduce the landslide disaster risk and formulate further development strategies.

How to cite: Zeng, T., Yin, K., and Wu, L.: Uncertainty research of landslide susceptibility mapping based deep ensemble learning: different basic classifier and ensemble strategy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2445, https://doi.org/10.5194/egusphere-egu23-2445, 2023.

EGU23-4428 | Orals | NH3.11

From Dense Flows to Powder Cloud Simulations: The OpenFOAM Avalanche Module 

Matthias Rauter, Julia Kowalski, and Wolfgang Fellin

OpenFOAM [1] is a well-known and widely used framework for physical simulations. Its Finite Area Framework allows the depth-integrated simulation of flows on nearly arbitrary surfaces. It was shown that this framework can be applied to snow avalanche simulations in natural terrain [2].

We will present the latest updates to the framework and the implementation of the avalanche module. The module provides not only a model for dense flow avalanches [2], but was lately extended to simulate powder snow avalanches and mixed snow avalanches. Various well-known friction and snow entrainment models are available for use, as well as unique models for deposition and coupling of dense flow and powder cloud layer in mixed snow avalanches. For practical applications, the module provides interfaces and methods for the integration of geographic information systems (GIS) and is fully capable of using raster and shape files for in- and output.

The avalanche module is built to integrate well in the OpenFOAM structure and follows the common user concepts of OpenFOAM. Therefore, users familiar with OpenFOAM should be able to accommodate quickly to the module and to run simulations after a short time. The module is provided as open source and its structure enables and encourages the implementation and experimenting with new ideas. One mayor goal of the module is to reduce the time from model development to model evaluation and application.

The module is hosted and developed collaboratively on develop.openfoam.com/Community/avalanche. We will provide an introduction into the framework and development process and provide interested people pointers on how to get started with the module and how to implement their own ideas.

[1] Weller, H. G., Tabor, G., Jasak, H., & Fureby, C. (1998). A tensorial approach to computational continuum mechanics using object-oriented techniques. Computers in physics, 12(6), 620-631.

[2] Rauter, M., Kofler, A., Huber, A., & Fellin, W. (2018). faSavageHutterFOAM 1.0: depth-integrated simulation of dense snow avalanches on natural terrain with OpenFOAM. Geoscientific Model Development, 11(7), 2923-2939.

How to cite: Rauter, M., Kowalski, J., and Fellin, W.: From Dense Flows to Powder Cloud Simulations: The OpenFOAM Avalanche Module, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4428, https://doi.org/10.5194/egusphere-egu23-4428, 2023.

EGU23-4715 | Posters on site | NH3.11

MultiResUNet, VGG16, and U-Net applications for landslide detection 

Saro Lee, Fatemeh Rezaie, and Mahdi Panahi

The frequent occurrence of disastrous landslides can lead to significant infrastructure damages, loss of life, and the relocation of populations. Early detection of landslides is crucial for mitigating the consequences. Today, deep learning algorithms, particularly fully convolutional networks (FCNs) and their variants such as the ResU-Net, have been utilized to rapidly and automatically detecting landslides. In the current study, a novel method using three new deep learning models: MultiResUNet, VGG16, and U-Net was used to detect landslides in Hokkaido Island, Japan. Our dataset is comprised of Sentinel-2 images and a mask layer, which includes "landslide" or "non-landslide" labels. The suggested framework was based on the analysis of satellite images of landslide-prone locations using bands 2 (blue), 3 (green), 4 (red), and 5 (visible and near-infrared) of Sentinel 2, slope and elevation factors. We trained each model on the dataset and evaluated their performance using a variety of statistical indexes, including precision, recall, and F1 score. The results showed that the MultiResUNet model outperformed the other two models, achieving an accuracy of 82.7%. The VGG16 and U-Net models achieved accuracies of 65.5% and 67.2%, respectively. The results indicated the capability of deep learning algorithms to process satellite images for early landslide detection and provide the opportunity of implementing efficient and effective disaster management strategies.

How to cite: Lee, S., Rezaie, F., and Panahi, M.: MultiResUNet, VGG16, and U-Net applications for landslide detection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4715, https://doi.org/10.5194/egusphere-egu23-4715, 2023.

Gravity-driven geophysical granular flows, such as rock avalanches, landslides, debris flows, etc., interact with obstacles (e.g. bridge piers and buildings) as they flow down the slope, causing rapid changes in flow velocity and height in the vicinity to form a granular shock wave in front of the object. The interaction between shock waves will affect the granular-flow field near the obstacles. However, the complex physical processes make some challenges in understanding how the granular material behaves in the influencing area of shock-shock interaction.

In this study, systematic chute experiments were performed with glass particles to investigate the dynamic interaction between granular flow and two circular cylinders with variable spacing distances. The pressure sensors were used to measure the impact pressure of the granular flow on the upstream cylindrical surfaces and a plate equipped flush with the chute bed. The accelerometers were mounted at the bottom of the plate to record seismic signals generated by the granular flow impacting on the bed as well as the cylinders. Flow velocities and depths were determined using an image processing method. The discrete element method (DEM) was utilized to construct a virtual model of the chute system and particles and to simulate the dynamic processes of granular flow interacting with the cylinders. The experimental and the DEM simulated results showed that bow shock waves were generated just upstream of the two cylinders and a granular vacuum zone was formed on the lee side of each cylinder, with the incoming flow velocity being significantly reduced in the granular-shock influencing area. As the spacing decreases, the two shock waves change from being independent to mutual interference. In addition, the effects of spacing distances on the shapes of the granular vacuum and bow shock waves were investigated by experiments and compared to the DEM results, showing a strong interaction between granular shocks. The pinch-off distance which is determined by the length of the granular vacuum also showed a dependence on the spacing distance of the cylinders, indicating a decreasing pinch-off distance with decreasing value of spacing. The impact pressures and acoustic signals generated by granular flow impacting on the chute bed and the surfaces of the cylinders in the shock influencing area for varying Froude numbers were also analyzed.

In summary, the DEM simulations and the recorded signals are helpful to analyze the interaction between granular shock waves. The finding in present study may contribute to better understanding granular shock dynamics and may eventually in improving the design of the protective structure in hazard-prone area.

How to cite: Wang, J., Chen, Z., and Wang, D.: Effects of Spacing Distance between Cylindrical Obstacles on Granular Shock Interactions in Gravity-Driven Experimental Flows, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5177, https://doi.org/10.5194/egusphere-egu23-5177, 2023.

EGU23-5309 | ECS | Orals | NH3.11

Impacts of flow path water-saturation for debris-flow erosion modelling at Illgraben (Switzerland) 

Anna Lena Könz, Jacob Hirschberg, Brian McArdell, Perry Bartelt, and Peter Molnar

Debris flows can significantly grow along their flow path by entraining sediments stored in the channel bed and banks. This entrainment process is influenced by various factors such as flow properties (e.g., flow momentum, basal shear stress) and environmental conditions (e.g., soil water saturation, sediment availability). In recent years, different attempts to include the entrainment process in runout models have improved modelled flow properties and runout behavior by empirically linking entrainment volumes to individual modelled flow properties. Linking entrainment to environmental factors, however, has remained challenging.

Here, we aim at implementing and testing the influence of flow path water-saturated conditions in debris-flow runout modelling in a Swiss debris-flow basin (Illgraben). To this end, the modified RAMMS runout model, which includes an empirical algorithm to describe entrainment as a function of basal shear stress (Frank et al., 2015), is coupled with a simple hydrological model to predict soil water saturation. In a first step, the RAMMS model was calibrated for the Illgraben site for seven events with detailed data on erosion/deposition along the fan as well as flow properties at the outflow of the simulation domain (de Haas et al., 2022). In the calibration procedure, the focus was placed on the erosion proportionality factor dz/dtau [m/kPa] (which links the maximum potential erosion depth to the basal shear stress) as it is assumed to be the driving saturation-induced increase of entrained volume. Preliminary results show that in most cases, including the entrainment process improves the reproduction of the flow properties, especially the ‘hydrograph’ front, and that the erosion proportionality factor dz/dt shows a significant degree of variation for different events. In a second step, the relationship between soil moisture conditions and maximum erosion depth expected along the flow path was investigated. The hydrologic conditions are simulated with a conceptual model solving the water balance for the basin’s headwaters. The headwater discharge serves as the water input for the channel on the fan, where an infiltration model is applied, and entrainment is investigated. The presented framework, which could be incorporated into other runout models, is expected to be useful for debris-flow entrainment modelling, as well as for assessing climate change impacts on debris-flow runout.

References

de Haas, T., McArdell, B.W., Nijland, W., Åberg, A.S., Hirschberg, J., Huguenin, P., 2022. Flow and Bed Conditions Jointly Control Debris‐Flow Erosion and Bulking. Geophysical Research Letters 49. https://doi.org/10.1029/2021GL097611

Frank, F., McArdell, B.W., Huggel, C., Vieli, A., 2015. The importance of entrainment and bulking on debris flow runout modeling: examples from the Swiss Alps. Nat. Hazards Earth Syst. Sci. 15, 2569–2583. https://doi.org/10.5194/nhess-15-2569-2015

How to cite: Könz, A. L., Hirschberg, J., McArdell, B., Bartelt, P., and Molnar, P.: Impacts of flow path water-saturation for debris-flow erosion modelling at Illgraben (Switzerland), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5309, https://doi.org/10.5194/egusphere-egu23-5309, 2023.

EGU23-6411 | ECS | Posters virtual | NH3.11 | Highlight

Importance of water and water producing processes in cascading events in mountainous regions 

Jessica Munch and Perry Bartelt

Over the last years, several multiphase avalanches have been observed, some of them leading to a cascade of events, such as in Chamoli, India, 2021, where a mixture of ice and rock fell down Ronti Peak, and transitioned to a debris flow with large amounts of water being involved. Another example is the event that occurred at Pizzo Cengalo, Switzerland, in 2017, where the rock face collapsed on the underlying glacier, entraining part of it, and also transitioning to a debris flow. When such a mass movement occurs, and leads to a cascade of events, the runout distances are much longer, and the consequences, both for humans and infrastructure, are much more important. 

When a multiphase avalanche turns into a cascade of events, the amount of water present in the flow seems to be a determining factor for the runout distance. The sources of water, for both of the events aforementioned remain debated, and the amounts of water that can be generated by the melting of the ice in the flow or by entrainment are poorly constrained. Indeed, from the moment that ice and snow are involved in a multi-material gravitational flow, they have the potential to melt due to friction between the different components of the flow and with the ground, and hence generate water. Material entrainment on the way also has the potential to either directly incorporate water in the flow, or bring in material with a high water content (i.e. hydrated sediments) or ice, that has the ability to melt while the flow propagates. An accurate modelling the thermal aspect of the flow as well as its ability to entrain material on the way is necessary to quantify the amount of water present in the flow.

Here, using a multiphase depth-average model specifically designed to handle gravitational flows made of rocks/ice/water/snow or any single components of these, we want to assess 1) the impact of heat transfers between the materials and 2) entrainment of multiphase ground material on the flow behaviour and more specifically on the water content in the flow and the consequences it has in term of runout distances and potential for cascading events. 

First results show that both entrainment and heat transfer within the flow play a major role in water production. Our experiments suggest that heat transfer between rocks and ice leads to the most efficient water production. Material entrainment also plays a major role in incorporating water in the flow, or producing it by melting entrained ice. Better constrains regarding material thermal properties, ground composition and potential for entrainment are however necessary to accurately quantify the amounts of water that can join the flow and influence the runout distances.

How to cite: Munch, J. and Bartelt, P.: Importance of water and water producing processes in cascading events in mountainous regions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6411, https://doi.org/10.5194/egusphere-egu23-6411, 2023.

EGU23-6718 | ECS | Posters on site | NH3.11 | Highlight

Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data 

Kushanav Bhuyan, Hakan Tanyas, Lorenzo Nava, Silvia Puliero, Sansar Raj Meena, Mario Floris, Cees van Westen, and Filippo Catani

Mapping landslides in space has gained a lot of attention over the past decade with good results. Current methods are primarily used to generate event inventories, but multi-temporal (MT) inventories are rare, even with manual landslide mapping. Here, we present an innovative deep learning strategy employing transfer learning. This allows our Attention Deep Supervision multi-scale U-Net model to be adapted to landslide detection tasks in new regions. This method also provides the flexibility to retrain a pretrained model to detect both rain and seismic landslides in new regions of interest. For mapping, archived Planet Lab remote sensing imagery from 2009 to 2021 at spatial resolutions of 3–5 m was used to systematically generate MT landslide inventories. Examining all cases, our approach provided an average F1 value of 0.8, indicating that it successfully identified the spatiotemporal occurrence of landslides. To examine the size distribution of mapped landslides, we compared the frequency distribution of predicted co-seismic landslides with manually mapped products from the literature. The results showed good agreement between the calculated exponents of the power law, with differences ranging from 0.04 to 0.21. Overall, this study demonstrated that the proposed algorithm can be applied to large areas to construct a polygon-based MT landslide inventory.

How to cite: Bhuyan, K., Tanyas, H., Nava, L., Puliero, S., Meena, S. R., Floris, M., Westen, C. V., and Catani, F.: Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6718, https://doi.org/10.5194/egusphere-egu23-6718, 2023.

EGU23-6884 | ECS | Orals | NH3.11

Using Deep Learning for Sentinel-1-based Landslide Mapping 

Aiym Orynbaikyzy, Frauke Albrecht, Wei Yao, Simon Plank, Andres Camero, and Sandro Martinis

Every year, landslides kill or injure thousands of people worldwide and substantially impact human livelihood. With the increasing number of extreme weather events due to the changing climate, urban sprawl and intensification of human activities, the amount of deadly landslide events is expected to grow. Landslides often occur unexpectedly due to the difficulty of predicting their location and timing. In such cases, providing information on the spatial extent of the landslide hazard is essential for organising and executing first-response actions on the ground.

This study explores the advantages and limitations of using high-resolution Synthetic Aperture Radar (SAR) data from Sentinel-1 within a deep learning framework for rapidly mapping landslide events. The objectives of the research are four-fold: 1) to investigate how Sentinel-1 landslide mapping can be improved using deep learning; 2) to explore if the addition of up to three pre-event scenes could improve the SAR-based classification accuracies; 3) to test if and how much the addition of polarimetric decomposition features and interferometric coherence help to improve classification accuracies; 4) to test if performing data augmentation affects the final results.

We adopt a semantic segmentation model – U-Net, and a novel deep network - U2-Net, to map landslides based on limited but globally distributed landslide inventory data. In total, 306 image patches with 128x128 pixels size were split into 80% for training/validation of the model and 20% for testing it. We calculate radar backscatter information (gamma nought VV and VH), polarimetric decomposition features (alpha angle, entropy, anisotropy) and interferometric coherence between temporally adjacent scenes. The features are calculated for three pre-event scenes and one post-event scene. Copernicus Digital Elevation Model (DEM) data are used to integrate land surface elevation and slope information into the classification process.

Using all Sentinel-1 features, the best result of deep learning model obtained 0.96 for the Dice coefficient on validation data. The landslide detection based on U2-Net gave slightly better results than the U-Net-based approach. The accuracies of models based on one, two or three pre-event scenes did not substantially differ, indicating no added values of increasing pre-event SAR features. Higher accuracies were reached when polarimetric decomposition features were combined with interferometric coherence compared to runs with only radar backscatter. Increasing the sample size using image augmentation methods such as four-directional rotation and flipping helped advance the accuracy.

Future research is directed towards (i) increasing and diversifying the landslide examples, (ii) performing landslide-events-based resampling and (iii) adding pre- and post-event optical data from Sentinel-2.  

How to cite: Orynbaikyzy, A., Albrecht, F., Yao, W., Plank, S., Camero, A., and Martinis, S.: Using Deep Learning for Sentinel-1-based Landslide Mapping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6884, https://doi.org/10.5194/egusphere-egu23-6884, 2023.

EGU23-8446 | ECS | Orals | NH3.11 | Highlight

Automatic detection of landslides from satellite images using a range of training events 

Kathryn Leeming, Itahisa Gonzalez Alvarez, Alessandro Novellino, and Sophie Taylor

Landslides in remote or uninhabited regions can be undocumented, leaving gaps in landslide inventories which are a key input for hazard and risk assessments. This can lead to landslide events being missing from research studies, and contribute to a bias in the events used for training of machine learning models.

In this work we use satellite images, terrain information, and labelled examples of landslides to train a convolutional neural network (U-Net), for the purpose of adding previously undocumented and new landslides to inventories. This model segments the input images and highlights the pixels it labels as landslides.

Our work focusses on landslides with a range of types and triggers, so that the model is exposed to a variety of training data. We describe the key properties of the landslides in the training set, and discuss the implications for future uses of the trained model.

How to cite: Leeming, K., Gonzalez Alvarez, I., Novellino, A., and Taylor, S.: Automatic detection of landslides from satellite images using a range of training events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8446, https://doi.org/10.5194/egusphere-egu23-8446, 2023.

EGU23-8596 | ECS | Posters virtual | NH3.11 | Highlight

Evaluating effects of topographies on explicit hydromechanical solvers using procedural generation 

Saoirse Robin Goodwin

A key problem for landslide research is evaluating hydromechanical solvers on a suitable variety of terrain types. There currently exists a large gulf between studies using hydromechanical solvers on highly idealised terrain, and those on real topographies. This makes it difficult to properly evaluate (i) the sensitivity of the output from the solver to specific terrain features, and (ii) potential numerical artifacts. One way to bridge the gap is to use procedural generation -- which has been used extensively in the videogame and animation industries for three decades -- to generate hillsides with controlled properties. Indeed, the size and frequency of topographical features can be set using procedural generation algorithms, so the spatial distribution of topographical features can be varied in isolation. This study uses a depth-averaged SPH solver to model single-surge flows on a variety of procedurally generated terrains. We investigate the effects of the spatial distribution and magnitude of features on the deposition patterns from the flows. We also discuss other potential applications for these approaches, including hazard mapping for cases where topographical uncertainty is likely (e.g. for modelling snow avalanches).

How to cite: Goodwin, S. R.: Evaluating effects of topographies on explicit hydromechanical solvers using procedural generation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8596, https://doi.org/10.5194/egusphere-egu23-8596, 2023.

EGU23-8895 | ECS | Orals | NH3.11

Application of SOSlope to shallow landslide triggering in Rüdlingen (Switzerland) 

Ilenia Murgia, Filippo Giadrossich, Denis Cohen, Gian Franco Capra, and Massimiliano Schwarz

The development and application of deterministic models for vegetated slope stability analysis at a local scale is a pivotal issue in international research. Such tools identify mitigation and risk management techniques during increasingly frequent critical rainfall events. In this sense, the SOSlope software, developed by ecorisQ international association (www.ecorisq.org), allows the simulation of hydro-mechanical dynamics that may influence shallow landslides' occurrence, focusing on the progressive activation of root reinforcement in space and time to counteract soil movement. 

This study presents a reconstruction of an artificially triggered landslide in Rüdlingen (Switzerland), carried out during the Triggering Rapid Mass Movements project, aiming for a back-analysis of the hydro-mechanical conditions leading to its triggering. This experiment allows comparing real-scale data on triggering dynamics of shallow landslides with modeling assumptions and results. Detailed measurements during the investigation and following slope failure were used to calibrate the hydro-mechanical input parameters used in SOSlope and evaluate the modeling capability to reproduce the landslide-triggering conditions and behaviors. 

Results show a reasonable reconstruction of the complex dynamics leading to the loss of soil stability. In particular, considering the water effect and the force redistribution dynamics during the triggering. SOSlope can quantify the effect of the root reinforcement spatial distribution and passive earth pressure. In addition to quantifying the maximum value of root reinforcement achieved to counteract soil movement, SOSlope enables observing its progressive activation in space and time. Pore water pressure dynamics show a distinctive trend regarding preferential flows in soil fractures and macropores; the decrease of suction stress due to increased water content in the soil matrix was also observed. SOSlope allows for systemic analysis of the landslide event by evaluating the different phases of change in slope stability and identifying the causes that favored their failure. These results are challenging to understand the shallow landslide triggering dynamics on vegetated slopes, given simplified assumptions through simpler models. This tool could support risk management strategies, including green-based solutions, nearby structures and infrastructure, or reforestation activities for slope stabilization. In the latter case, through the software, the structure, composition, and efficiency of the plantation can be checked. 

Future developments in SOSlope will include the implementation of a triangulated grid mesh to improve computational limitations associated with the raster input data square grid resolution and the inclusion of new tree species for root reinforcement estimation.

How to cite: Murgia, I., Giadrossich, F., Cohen, D., Capra, G. F., and Schwarz, M.: Application of SOSlope to shallow landslide triggering in Rüdlingen (Switzerland), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8895, https://doi.org/10.5194/egusphere-egu23-8895, 2023.

EGU23-9956 | ECS | Orals | NH3.11

A surrogate model for depth-averaged erosion and deposition closures using deep learning 

Mohammad Nikooei and Clarence Edward Choi

Geophysical mass flows are commonly modelled using depth-averaged (DA) numerical models, which rely on closure relations to account for erosion and deposition. While erosion and deposition are grain scale phenomena, their physics is overlooked due to simplifications required in DA models. In this study, a framework is proposed to transfer the grain-scale physics of erosion and deposition to the continuum scale of DA models. A long short-term memory (LSTM) neural network is coupled with a DA model to incorporate the grain-scale physics of erosion and deposition. As a surrogate model for the closure relation, the LSTM model is trained using computed results from grain-scale Discrete Element Method (DEM) simulations. The surrogate model is evaluated by studying the deposition of an initially flowing granular mass over slope. The effective flow depth h and DA velocity u calculated by the DA-LSTM model are compared with DEM simulation results. The DA-LSTM model is demonstrated to provide more computational efficiency compared to DEM simulations. The newly proposed surrogate model offers a promising approach to calculating more complex closures using deep learning techniques.

How to cite: Nikooei, M. and Edward Choi, C.: A surrogate model for depth-averaged erosion and deposition closures using deep learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9956, https://doi.org/10.5194/egusphere-egu23-9956, 2023.

EGU23-10159 | ECS | Posters on site | NH3.11

Unravelling the complex dynamic of slow-moving landslides in the Flysch zone region, Lower Austria. A case study of the Hofermühle catchment. 

Yenny Alejandra Jiménez Donato, Edoardo Carraro, Philipp Marr, Robert Kanta, and Thomas Glade

Slow-moving landslides are complex processes that represent a significant challenge for landslide dynamic analysis and disaster risk reduction. In some cases, they have been considered as early signals of potential destructive events as they can accelerate under specific climatic conditions, causing significant damage.  However, slow-moving landslides have been constantly neglected as the require significant time, human resources, and specific numerical models to assess their non-uniformity. Considering the existing gaps and the lack of data of slow-moving landslides in Austria, a long-term monitoring project has been carried out by the ENGAGE group of the University of Vienna. Several investigation techniques for hydro-geo monitoring have been installed in Lower Austria for multi-temporal landslide investigation in several landslides, using them as living laboratories. Therefore, the present study aims to integrate the valuable hydro-mechanical data to bring light on potential acceleration conditions of slow-moving landslides, frequency and intensity relationships and cascading hazards initiated from within the slow-moving landslide mass.  

The geographical and geological conditions of the province of Lower Austria place it as a very susceptible region to the occurrence of landslides. The predominant geology correspond to the units of the Flysch Zone and the Klippen Zone, which are mechanically weak units composed by intercalation of limestones and deeply weathered materials. These conditions, along with the hydrological conditions, land use changes and other anthropogenic impacts contribute to the instability of the region. Consequently, in order to understand landslide processes and mechanisms, we attempt to integrate the hydro-mechanical data compiled from the monitoring sites to model a complex event triggered in 2013, in the Hofermühle catchment, district of Waidhofen an der Ybbs, in order to improve our understanding of landslide conditioning factors and triggering mechanisms of potential cascading hazards in the region.

How to cite: Jiménez Donato, Y. A., Carraro, E., Marr, P., Kanta, R., and Glade, T.: Unravelling the complex dynamic of slow-moving landslides in the Flysch zone region, Lower Austria. A case study of the Hofermühle catchment., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10159, https://doi.org/10.5194/egusphere-egu23-10159, 2023.

EGU23-10269 | Posters on site | NH3.11

Detecting Landslide Affected Areas Using Deep Learning of Bi-Temporal Satellite Imagery Datasets 

Fuan Tsai, Elisabeth Dippold, Po-Jui Huang, and Chi-Chuan Lo

Landslide is one of the most frequently occurred and destructive natural hazards in Taiwan and many other places around the world. Using satellite images to help identify landslide affected regions can be an effective and economic alternative comparing to conventional ground-based measures. However, utilizing remotely sensed images for the investigation and analysis of landslides still faces challenges. In a long-term monitoring of landslide affected areas, it is common to observe landslides occur repeatedly at or around the same region, thus requiring change-detection analysis of multi-temporal image datasets to identify this type (repeatedly occurred) landslides, especially to monitor its expansion. In recent years, machine learning techniques are extensively adopted for image analysis, including satellite images. Therefore, integrating change-detection with machine learning algorithms should be helpful for identifying and mapping incremental landslides from multi-temporal satellite images. This research developed a systematic deep learning framework for detecting landslides with bi-temporal satellite image pairs as the training datasets. The training datasets are extracted and labelled from multi-temporal high-resolution multi-spectral satellite images covering two watershed regions where landslides occurred frequently. Experimental results indicate that the developed machine learning algorithms can achieve high accuracies and perform better than conventional methods for detecting landslide affected areas from time-series satellite images, especially in the places where landslides may occur repeatedly.

How to cite: Tsai, F., Dippold, E., Huang, P.-J., and Lo, C.-C.: Detecting Landslide Affected Areas Using Deep Learning of Bi-Temporal Satellite Imagery Datasets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10269, https://doi.org/10.5194/egusphere-egu23-10269, 2023.

Western Ghats (WG) of India is experiencing frequent landslides during every Indian summer monsoon. Due to the unique blend of topography and tropical humid climate, accelerates chemical weathering, forming a layer of unconsolidated soil unconformably overlies the Precambrian crystalline rock. Lack of cohesion or bonding in these contrasting geologic materials, makes WG vulnerable to various forms of landslides during the peak of Indian summer monsoon. Hence detailed information about soil thickness has a predominant role in identifying the landslide prone area and understanding the landslides in WG. However, soil thickness maps are not available for WG area and steep rugged terrain makes it difficult to collect detailed soil thickness data. This study used a random forest (RF) machine-learning model to predict the soil depth with a limited number of sparse samples in the Panniar river basin of WG. The model was combined using 70 soil depth observations with eleven covariates such as normalized difference vegetation index, topographic wetness index, valley depth, solar radiance, elevation, slope length, slope angle, slope aspect, convergence index, profile curvature and plan curvature. The results show that the RF model has good predictive accuracy with coefficient of determination (R2) of 0.822 and root mean square error (RMSE) of 2.968, i.e., almost 80% of soil depth variation explained. The spatially predicted soil depth map clearly shows regional patterns with local details. Both geomorphological processes and vegetation contributed to shaping the soil depth in the study area. The resulting map can be used for understating the soil characteristics and  modelling  the landslide susceptibility in the study area.

How to cite: Asokan Laila, A. and Gopinath, G.: Soil depth Prediction in a landslide prone tropical river basin under data-sparse conditions using machine-learning technique, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11135, https://doi.org/10.5194/egusphere-egu23-11135, 2023.

EGU23-13292 | Orals | NH3.11

Advances in landslide analysis by using remote sensing and artificial intelligence (AI): Results from MultiSat4SLOWS project 

Mahdi Motagh, Simon Plank, Wandi Wang, Aiym Orynbaikyzy, Magdalena Vassileva, and Mike Sips

Landslides are a major type of natural hazard that cause significant human and economic losses in mountainous regions worldwide. Optical and synthetic aperture radar (SAR) satellite data are increasingly being used to support landslide investigation due to their multi-spectral and textural characteristics, multi-temporal revisit rates, and large area coverage. Understanding landslide occurrence, kinematics and correlation to external triggering factors is essential for landslide hazard assessment. Landslides are usually triggered by rainfall and thus, are often covered by clouds, which limits the use of optical images only. Exploiting SAR data, and their cloud penetration and all weather measurement capability, provides more precise temporal characterization of landslide kinematics and its occurrence. However, except for a few research studies, the full potential of SAR data for operational landslide analysis are not fully exploited yet. This is a very demanding task, considering the availability of a vast amount of Sentinel-1 data that have been globally available since October 2014.

In this presentation we summarise all the achievements that were made within the framework of MultiSat4SLOWS project (Multi-Satellite imaging for Space-based Landslide Occurrence and Warning Service), financed within the Helmholtz Imaging 2020 call. The project aims on developing a multi-sensor approach for detection and analysis of the landslide occurrence time and its spatial extent using freely available SAR data from Sentinel-1. Within this project,  we generated a reference database based on Sentinel-1 and -2 data for training, testing and validation of deep learning algorithms. The reference database contains various landslide examples that occurred worldwide and include pre- and post-event polarimetric, coherence and backscatter features. Also, we investigated the applicability of SAR/InSAR time-series data for landslide time detection. Finally, we introduce a prototype of a Visual Analytics platform for rapid landslide analysis of spatial and temporal ground deformation patterns and correlation with external triggering factors.

 

How to cite: Motagh, M., Plank, S., Wang, W., Orynbaikyzy, A., Vassileva, M., and Sips, M.: Advances in landslide analysis by using remote sensing and artificial intelligence (AI): Results from MultiSat4SLOWS project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13292, https://doi.org/10.5194/egusphere-egu23-13292, 2023.

EGU23-13333 | ECS | Orals | NH3.11

Geophysical mass flow over complex micro-topography: from grain-scale mechanics to continuum modeling 

Lu Jing, Shuocheng Yang, and Fiona C. Y. Kwok

Geophysical mass flows involve granular earth materials surging down natural slopes, one of the major threats to mountainous regions worldwide. Accurate modeling of geophysical mass flows requires closure relations both within the flow (rheology) and at the flow-substrate interface (boundary conditions). However, although recent years have seen significant advances in the modeling of granular flow rheology, our understanding of how flowing granular materials interact with the substrate remains largely elusive. Here, we focus on micro-topography, i.e., geometric base roughness that is about the same size as the grain size, and investigate its effects on the granular flow dynamics as well as the associated closure relations. To systematically vary the base roughness from smooth to rough, we generate the base using immobile particles with varying particle size and spatial arrangement in laboratory experiments (with particle image velocimetry for flow kinematics extraction) and discrete element method simulations. Two granular flow scenarios are considered, including steady-state flow down inclines and granular column collapse. In the first scenario, it is found that basal slip occurs when the base roughness is below a range of intermediate values and a general slip law connecting the slip velocity, the mean flow velocity, and the base roughness is developed. In the second, transient flow scenario, basal slip inevitably occurs even for very rough bases due to inertial effects and a transient basal slip law is proposed to correlate the slip velocity with local flow properties based on kinetic theory arguments. The basal slip laws developed in this work can be readily incorporated as a dynamic boundary condition in continuum modeling of granular flows. In future work, grain-scale mechanisms relevant to more realistic geophysical flows will be investigated, including the feedback effects of pore fluid pressure on the flow mobility during basal sliding and the role of irregular particle shapes in hydro-mechanical modeling of geophysical mass flows.

How to cite: Jing, L., Yang, S., and Kwok, F. C. Y.: Geophysical mass flow over complex micro-topography: from grain-scale mechanics to continuum modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13333, https://doi.org/10.5194/egusphere-egu23-13333, 2023.

EGU23-13523 | ECS | Posters on site | NH3.11

Automatic landslide detection using Sentinel-1 and -2 images - a glacial case study 

Alexandra Jarna Ganerød, Erin Lindsay, Ola Fredin, Tor-Andre Myrvoll, Steinar Nordal, Martina Calovi, and Jan Ketil Rød

Although Norway is a country with rough terrain and a high frequency instable steep slopes, there is a scarcity of landslide data available. This limits the accuracy of thresholds for early warning systems, and hazard maps, both of which rely on historic event data. There is great potential to supplement existing ground-based observations with automated landslide detection, using satellite imagery and deep learning. In working towards an automated system for landslide detection in Norway, we investigated which imagery types and machine-learning models performed best for detecting landslides in a formerly glaciated landscape.

We locally trained a deep learning model with the use of Keras, TensorFlow 2 and U-net architecture. As input data, we used multi temporal composites with Sentinel-1 and -2 image stacks of all available images from one month pre- and post-event. Processed bands included: dNDVI (difference in maximum normalised difference vegetation index) from Sentinel-2, and pre- and post-event Synthetic Aperture Radar (SAR) data (terrain-corrected, mean of multi-temporal ascending descending images, in VV polarisation) from Sentinel-1. Training and evaluation were performed with a well-verified landslide inventory of 120 manually mapped rainfall-triggered landslides from Jølster (30-July-2019), in Western Norway. We tested the model with four input data settings using different bands and various polarization for the pre- and post-event SAR data, including: 1) full version (all 13 bands) 2) dNDVI (Sentinel-2), preVV, postVV (Sentinel-1), 3) preVV, postVV (Sentinel-1), and 4) post-R, post-G, post-B, post-NIR, dNDVI (Sentinel-2). The results were compared to the results of a pixel-based conventional machine learning model (Classification and Regression Tree) using the same input data. The second input data setting provides the best results. The performance scores show precision results for all four input data settings between 80-85%, with Matthews corelation coefficient values from 51-89%. Moreover, the deep-learning model significantly outperforms the conventional machine learning model in the input data setting #3. We see that the patch-based classification method far out-performs the pixel-classification due to the ability to differentiate the landslide signal from random noise produced from speckle in undisturbed areas. In addition, this represents one of the first attempts to fuse SAR and optical data for landslide detection, and we show there is an advantage in doing so in this case.

 

How to cite: Ganerød, A. J., Lindsay, E., Fredin, O., Myrvoll, T.-A., Nordal, S., Calovi, M., and Rød, J. K.: Automatic landslide detection using Sentinel-1 and -2 images - a glacial case study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13523, https://doi.org/10.5194/egusphere-egu23-13523, 2023.

Geophysical mass flows typically consist of a granular solid phase having a broad grain size distribution and an interstitial fluid phase. During the flow, particles of larger sizes tend to segregate in the flow and thereby accumulate in the flow surface and front, resulting in dramatic changes in the flow and deposition characteristics, such as enhanced runout distances and stratified deposit patterns. However, current hydro-mechanical modeling of geophysical mass flows often does not consider grain size segregation and the resulting internal heterogeneity of the flow, which can largely compromise the predictability of existing hydro-mechanical models. A major challenge lies in the multiscale nature of grain segregation and its effects on the flow mobility, which requires detailed characterization of segregation mechanics at both the particle and flow levels. Here, we first review recent advances in a multiscale framework in which the driving and resistive forces of segregation on a single intruder particle or a collection of large particles have been formulated based on discrete element method simulations and theoretical analysis. Then, we discuss how these particle-scale forces can be derived toward a continuum formulation for segregation flux modeling and be connected with the flow dynamics in a two-way coupling manner. These physics-based force formulations reflect the micromechanics of segregation and lead to enhanced predictive modeling of particle size dynamics in the granular flow. Finally, we discuss the potential of extending the proposed framework to consider the effects of interstitial fluids and other mechanisms in upscaled hydro-mechanical modelling for more realistic geophysical mass flows.

How to cite: Liu, M. and Jing, L.: Modelling grain size segregation in geophysical mass flows: bridging particle-level forces and continuum models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14147, https://doi.org/10.5194/egusphere-egu23-14147, 2023.

EGU23-14199 | Orals | NH3.11

“Fusion network with attention for landslide detection. Application to Bijie landslide open dataset” 

Candide Lissak, Thomas Corpetti, and Mathilde Letard

Remote sensing techniques are now widely spread for the early detection of ground deformation, implementation of warning systems in case of imminent landslide triggering, and medium- and long-term slope instability monitoring. The large breadth of data available to the scientific community, associated with processing techniques improved as the data volume was increasing, has led to noticeable developments in the field of remote sensing data processing, using machine learning algorithms and more particularly deep neural networks.

 

This arsenal of data and techniques is necessary for the present scientific challenges the community of researchers on landslides still have to meet. As landslides can be complex, for risk management and disaster mitigation strategies, it is necessary to have a precise idea of their location, shape, and size to be studied and monitored. The challenge aims to automate landslide detection and mapping, especially through learning methods. Machine learning methods based on Deep Neural Networks have recently been employed for landslide studies and provide promising efficient results for landslide detection [1].

 

In this study, we propose an original neural network for landslide detection. More precisely, we exploit a fusion network [1] dealing with optical images on the one hand and Digital Elevation Models on the other hand. To improve the results, attention layers [3] (able to stabilize the training and more precise results) as well as mix up techniques [4] (able to generalize more efficiently) are exploited.

The model was trained and tested on the open Bijie landslide dataset.

 

Keywords: Remote sensing for landslide monitoring and detection, landslide detection, deep neural networks, attention

 

[1] Ji, S., Yu, D., Shen, C., Li, W., & Xu, Q. (2020). Landslide detection from an open satellite imagery and digital elevation model dataset using attention-boosted convolutional neural networks. Landslides, 17(6), 1337-1352.

[2] Song, W., Li, S., Fang, L., & Lu, T. (2018). Hyperspectral image classification with deep feature fusion network. IEEE Transactions on Geoscience and Remote Sensing, 56(6), 3173-3184.

[3] Niu, Z., Zhong, G., & Yu, H. (2021). A review on the attention mechanism of deep learning. Neurocomputing, 452, 48-62.

[4] Thulasidasan, S., Chennupati, G., Bilmes, J. A., Bhattacharya, T., & Michalak, S. (2019). On mixup training: Improved calibration and predictive uncertainty for deep neural networks. Advances in Neural Information Processing Systems, 32.

How to cite: Lissak, C., Corpetti, T., and Letard, M.: “Fusion network with attention for landslide detection. Application to Bijie landslide open dataset”, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14199, https://doi.org/10.5194/egusphere-egu23-14199, 2023.

EGU23-14546 | ECS | Orals | NH3.11

ML-based characterization of PS-InSAR multi-mission point clouds for ground deformation classification 

Claudia Masciulli, Michele Gaeta, Giorgia Berardo, Gianmarco Pantozzi, Carlo Alberto Stefanini, and Paolo Mazzanti

Persistent Scatterer Interferometry (PSI) is a powerful multitemporal A-DInSAR (Advanced Differential Synthetic Aperture Radar Interferometry) technique widely used for monitoring and measuring Earth’s surface displacements over large areas with sub-centimetric precision. The capability to detect ground deformation processes relies on the available PSI spatial density, strictly related to the resolution of the considered sensor and the presence of stable natural and artificial reflectors. A new data fusion approach, developed as part of the “MUSAR” project funded by ASI (Italian Space Agency), integrates multi-band SAR sensors to improve data coverage of PSI data by synthesizing multi-sensor displacement information. The integration of multi-mission PSI generates synthetic measurement points, named Ground Deformation Markers (GD-Markers), featuring vertical (Up-Down) and horizontal (Est-West) components of the displacements. The fusion of PSI data extracted by C-band Sentinel-1 images from the Copernicus initiative and the COSMO-SkyMed constellation in the X-band from ASI contributed to creating a dataset with high information content.

Each GD-Markers cluster with displacement measurements identifies a specific deformation process in the region of interest. After selecting the relevant cluster of points, the deformation processes were classified into different categories (e.g., landslide, subsidence) to improve their understanding and evaluation for mitigating natural-related hazards. This study aimed to develop a machine learning-based classification system, starting from GD-Markers point clouds, which support the automatization of ground displacement identification and characterization. The synthetic points were characterized as individual entities or point clouds, formed by a discrete cluster of points in space, to evaluate the advantage of treating each point independently or incorporating local neighborhood information. The structured point data were analyzed using a supervised Random Forest (RF) approach to evaluate the performance of point cloud classification and categorization for identifying the best initial setting. Each point was assigned a label representing a deformation process in point cloud classification, while one label is provided for the entire point cloud dataset with categorization.

Comparing models’ performances allowed the definition of the best possible approach for classifying the deformation processes observed by GD-Markers point clouds. The analysis assessed the effectiveness of the classification of single points or clusters to identify the optimal setup that achieves an accurate segmentation between adjacent deformation processes. Identifying this initial setting was essential for selecting and developing advanced deep-learning approaches.

How to cite: Masciulli, C., Gaeta, M., Berardo, G., Pantozzi, G., Stefanini, C. A., and Mazzanti, P.: ML-based characterization of PS-InSAR multi-mission point clouds for ground deformation classification, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14546, https://doi.org/10.5194/egusphere-egu23-14546, 2023.

EGU23-14639 | ECS | Posters on site | NH3.11

Performance analysis of a U-Net landslide detection model 

Itahisa Gonzalez Alvarez, Kathryn Leeming, Alessandro Novellino, and Sophie Taylor

Image segmentation algorithms are a type of image classifier that assigns a label to each individual pixel in an image. U-Nets, initially developed for the analysis of biomedical images and now widely used in a variety of fields, are an example of such algorithms. It has been shown that U-Nets are specially interesting when working with small training datasets and combined with data augmentation techniques.

In this study, we used satellite images with labelled landslide masks from known events to train a U-Net to identify areas of potential landslide. These landslide masks are time-consuming to create, resulting in a small initial training set. Even when working with U-Nets, the success of machine learning and AI tools depends on the availability and quality of training data, as well as the algorithm settings during the training process. Tuning machine learning models to achieve the best performance possible from limited amounts of data is important to generate trustworthy results that can be used to advance the knowledge of landslide events around the world.

Here, we show the differences in algorithm performance as we use different types of data augmentation and model parameters. We also explore and assess the effects on performance of options such as including different satellite bands, terrain information and alternative colour band representations.

How to cite: Gonzalez Alvarez, I., Leeming, K., Novellino, A., and Taylor, S.: Performance analysis of a U-Net landslide detection model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14639, https://doi.org/10.5194/egusphere-egu23-14639, 2023.

Steep slopes, deforestation, unconsolidated deposits, high annual rainfall, and a highly dissected landscape facilitate the occurrence of landslides in one of the most important Colombian highways “Via al Llano”, frequently causing traffic interruptions. Prior to a susceptibility assessment of the area, a multitemporal inventory is required. Usually, landslides are identified and mapped by visual interpretation of satellite optical and/or aerial images. However, in study areas located in tropical areas such as that of Via al Llano, due to the frequent presence of clouds, a number of images are needed to identify the landslides and estimate the period of their occurrence. Therefore, an automatic detection procedure is indispensable for large tropical areas and multitemporal event inventories. The cloud-based Google Earth Engine (GEE) allows geospatial processing of freely available multi-temporal data. In this work, we perform automatic detection of landslides using the Normalized Difference Vegetation Index (NDVI) from Sentinel-2 (optical images) and the SAR-backscatter change from Sentinel-1 (radar images) over a sector of the Buenavista area, extending for 53km2 in the south portion of the “Via al Llano”. Considering a period during which the occurrence of some landslides blocked the highway, images before and after this event were selected for automatic detection, and the results were compared with landslide inventory previously prepared by an expert operator by visual analysis of images available on Google Earth (optical-natural color images). To assess the ability of each method to discriminate between landslides and stable slopes, confusion matrices were calculated. The NDVI-based approach demonstrated an acceptable ability to identify the landslides, although generating a high number of false positives. On the other hand, the SAR-based method exhibits a lower ability to correctly detect the landslide polygons, even if generating a lower number of false positives. This is maybe due to the pattern of predicted positives which mostly consists of isolated pixels; conversely, the NDVI-based approach provides groups of adjacent pixels predicted as positives which better reproduce the shapes of the landslide polygons. Finally, by combining the two approaches and using topographic masks, better accuracy in the automatic mapping of our multitemporal landslide inventories was achieved.

How to cite: Calderon-Cucunuba, L. P. and Conoscenti, C.: Automatic mapping of multitemporal landslide inventories by using open-access Synthetic Aperture Radar and NDVI imagery in Google Earth Engine: a case study of the “Via al Llano” highway (Colombia), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15954, https://doi.org/10.5194/egusphere-egu23-15954, 2023.

EGU23-16166 | Posters on site | NH3.11 | Highlight

Numerical modelling of mudflows impacting settlements: a case study 

Alessandro Leonardi, Giulia La Porta, and Marina Pirulli

Mudflows are common natural hazards, often originating from the liquefaction of shallow landslides triggered by rainfall. The numerical back-analysis of past events is key in projecting the application of numerical models towards forward analysis. However, the complex multi-physics nature of the problem hampers the development of comprehensive frameworks. Notwithstanding, calibrated numerical models, able to simulate all aspects of the problem (triggering and runout) can still be valuable tools for aiding the design of countermeasures. This can currently only happen if calibration is performed on the specific site, or on sites with very similar geomorphological and geological characteristics.

In this presentation, the application of a coupled triggering and runout model is explored. Two study cases of well-known events occurring in Southern Italy are presented. A pseudo-plastic model is used for the post-triggering rheology. The resolution of the runout simulation is down to the level of the specific exposed element (houses, roads). This allows for an ad-hoc assessment of risk on key pieces of infrastructure. The results reveal interesting aspects related to how the complex topographic features of settlements challenge the traditional workflow for back-analysis. In particular, the channelization of flows within the settlement itself leads to an overestimation of hazard, unless care is placed to resolve the triggering phase down to the sub-basin scale.  

 

REFERENCES

Ng, C. W. W., Leonardi, A., Majeed, U., Pirulli, M., & Choi, C. E. (2023). A Physical and Numerical Investigation of Flow–Barrier Interaction for the Design of a Multiple-Barrier System. Journal of Geotechnical and Geoenvironmental Engineering, 149(1). https://doi.org/10.1061/(asce)gt.1943-5606.0002932

Pasqua, A., Leonardi, A., & Pirulli, M. (2022). Coupling Depth-Averaged and 3D numerical models for the simulation of granular flows. Computers and Geotechnics, January, 104879. https://doi.org/10.1016/j.compgeo.2022.104879

How to cite: Leonardi, A., La Porta, G., and Pirulli, M.: Numerical modelling of mudflows impacting settlements: a case study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16166, https://doi.org/10.5194/egusphere-egu23-16166, 2023.

EGU23-16501 | Posters on site | NH3.11

Assessment of landslide susceptibility in the rocky coast subsystem of Essaouira, Morocco 

Sergio C. Oliveira, Abdellah Khouz, Jorge Trindade, Fatima ElBchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud

Several researchers have developed landslide susceptibility maps in recent years using a variety of methods and models. The Information Value method has frequently been used to assess landslide susceptibility in a variety of coastal environments. In this study we used these bivariate statistical techniques to assess the coastal region of Essaouira's susceptibility to landslides. 588 different landslides were found, classified, and mapped along the rocky coast of this coastal stretch. The observation and interpretation of many data sources, such as high-resolution satellite images, aerial photographs, topographic maps, and extensive field surveys, are employed to understand terrain predisposing conditions and to predict landslides. Essaouira's rocky coastal system is situated in the centre of Morocco's Atlantic coast. The study region was divided into 1534 (50 m wide) cliff terrain units. The landslide inventory was randomly split into two separate groups for training and validation purposes: 70% of the landslides were used for training the susceptibility model and 30% for independent validation. Elevation, slope angle, slope aspect, plan curvature, profile curvature, cliff height, topographic wetness index, topographic position index, slope over area ratio, solar radiation, presence of faulting, lithological units, toe lithology, presence and type of cliff toe protection, layer tilt, rainfall, streams, land-use patterns, normalized difference vegetation index, and lithological material granulometry were the twenty-two layers of landslide conditioning factors that were prepared. Using a pixel-based model (12.5 m x 12.5 m) and an elementary terrain unit-based model, the bivariate Information Value approach was used to determine the statistical link between the conditioning factors and the various landslide types and to produce the coastal landside susceptibility maps. The multiple coastal landslide susceptibility models were evaluated for accuracy and predictive power using the receiver operating characteristic curve and area under the curve. The findings allowed for the designation of 38% of the rocky coast subsystem as having a high susceptibility to landslides, with the majority of these areas being found in the southern part of the coastal region of Essaouira. Both future planned development operations and environmental conservation can benefit from these susceptibility maps.

Acknowledgements: The work has been financed by national funds through FCT (Foundation for Science and Technology, I. P.), in the framework of the project “HighWaters – Assessing sea level rise exposure and social vulnerability scenarios for sustainable land use planning” (EXPL/GES-AMB/1246/2021).

How to cite: Oliveira, S. C., Khouz, A., Trindade, J., ElBchari, F., Bougadir, B., Garcia, R. A. C., and Jadoud, M.: Assessment of landslide susceptibility in the rocky coast subsystem of Essaouira, Morocco, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16501, https://doi.org/10.5194/egusphere-egu23-16501, 2023.

EGU23-17563 | Orals | NH3.11 | Highlight

Impact of a debris flow surge on a vertical wall oblique with respect to flow direction 

Aronne Armanini, Alessia Fontanari, and Fabio Sartori

Debris flows are rapid to very rapid flows, made up of a high concentrated mixture of water and sediments. These types of flow are catastrophic natural phenomena affecting mountain areas and causing several property damages and loss of lives every year. The mitigation of these phenomena is then fundamental:  check dams and longitudinal protection walls are among the main structural passive countermeasures. A crucial aspect in the definition of the design criteria for these structures is the analysis of the impact force exerted by a debris flow on them.
From a scientific point of view, the state of the art in this field is quite lacking, despite the relevance of the topic. In the case of impact of a debris surge on a vertical plane normal to the flow direction, according to Armanini and Scotton (1992), two main types of impact may occur. The first type consists of a complete deviation of the flow along the vertical obstacle, assuming a jet-like behavior (Figure 1).  The second type is characterized by the formation of a reflected wave after the impact, which propagates upstream (Figure 2). The analytical solution based on momentum and mass balances in both case is already known (see Armanini 2009 and Armanini et al. 2020) and the comparison between theoretical results and experimental data are quite satisfactory. 
Much less studied is the case of the impact of a debris flow surge on a vertical wall, arranged in an oblique direction with respect to the flow direction, as in the case of lateral protection walls. 
In order to better understand its kinematic characteristics, the phenomenon  has been studied in the Hydraulic Laboratory of the University of Trento. The phenomenon has been reproduced in a channel of variable slope, by releasing a certain volume of fluid and measuring its impact force on a gate situated at the end of the channel at different oblique orientation with respect to flow direction. Several slopes of the channel and concentration of the solid fraction have been investigated. 
When the flow crash into the gate, it is deviated in the vertical direction along the obstacle and forms initially a vertical jet, which is soon deviated in the direction parallel to the gate.
The phenomenon has been theoretically investigated both in the light of the one-dimensional theory of fluid impacts already adopted for the case of impact on a vertical wall arranged orthogonally to the flow, and using a simplified approach derived from the classical two-dimensional theory of Ippen (1951) of the deviations of supercritical currents. The comparison between the predictions of the theory and the experimental data turns out to be quite good.

How to cite: Armanini, A., Fontanari, A., and Sartori, F.: Impact of a debris flow surge on a vertical wall oblique with respect to flow direction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17563, https://doi.org/10.5194/egusphere-egu23-17563, 2023.

EGU23-787 | ECS | PICO | CR2.3

Mapping stagnant ice and age in the Dome Fuji region, Antarctica, by combining radar internal layer stratigraphy and flow modeling 

Zhuo Wang, Olaf Eisen, Ailsa Chung, Daniel Steinhage, Frédéric Parrenin, and Johannes Freitag

The Dome Fuji (DF) region in Antarctica is a potential site for holding an ice record older than one million years. Here, we combine the internal airborne radar stratigraphy with a 1-D inverse model to reconstruct the age field of ice in the DF region. As part of the Beyond EPICA - Oldest Ice reconnaissance (OIR), the region around DF was surveyed with a total of 19000 km of radar lines in the 2016/17 Antarctic summer. Internal stratigraphy in this region has now been traced. Through these tracked radar isochrones, we transfer the age-depth scale from DF ice core to the adjacent 500 km2 region. A 1-D inverse model has been applied at each point of the survey to extend the age estimates to deeper regions of the ice sheet where no direct or continuous link of internal stratigraphy to the ice cores is possible, and to construct basal thermal state and accumulation rates. Through the reliability index of each model, we can evaluate the reliability of the 1-D assumption. Mapped age of basal ice and age density imply there might exist promising sites with ice older than 1.5 million years in the DF region. Moreover, the deduced basal state, i.e., melting rates and stagnant ice provide constraints for finding old-ice sites with a cold base. The accumulation rate ranges from 0.014 to 0.038 m a-1 (in ice equivalent) in the DF region, which is also an important criterion for potential old ice.

How to cite: Wang, Z., Eisen, O., Chung, A., Steinhage, D., Parrenin, F., and Freitag, J.: Mapping stagnant ice and age in the Dome Fuji region, Antarctica, by combining radar internal layer stratigraphy and flow modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-787, https://doi.org/10.5194/egusphere-egu23-787, 2023.

EGU23-792 | ECS | PICO | CR2.3

What to watch out for when assimilating ice-cores as regional SMB proxies? 

Marie G. P. Cavitte, Hugues Goosse, Kenichi Matsuoka, Sarah Wauthy, Rahul Dey, Vikram Goel, Jean-Louis Tison, Brice Van Liefferinge, and Thamban Meloth

Ice cores remain the highest resolution proxy for measuring past surface mass balance (SMB) that can be used for model-data comparison. However, there is a clear difference in the spatial resolution of the ice cores, with a surface sample on the order of cm2, and the spatial resolution of models, with at best a surface footprint on the order of a few km2. Comparing ice core SMB records and model SMB outputs directly is therefore not a one-to-one comparison. In addition, it is well known that ice cores, as point measurements, sample very local SMB conditions which can be affected by local wind redistribution of the SMB at the surface.

We set out to answer the question: how representative are ice-cores of regional SMB? For this, we use several ground-penetrating radar (GPR) surveys in East Antarctica, which have co-located ice core drill sites. Most of our sites share a relatively similar climatology, as they are all coastal ice promontories/rises along the Dronning Maud Land coast, with the exception of the Dome Fuji survey on the high plateau in the interior of the continent.

We will show that the comparison of the SMB signals of the GPR and the ice core records allows us to estimate the spatial footprint of the ice cores, and that this spatial footprint varies widely from site to site. We will provide a summary of the spatial and temporal characteristics for each location.

How to cite: Cavitte, M. G. P., Goosse, H., Matsuoka, K., Wauthy, S., Dey, R., Goel, V., Tison, J.-L., Van Liefferinge, B., and Meloth, T.: What to watch out for when assimilating ice-cores as regional SMB proxies?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-792, https://doi.org/10.5194/egusphere-egu23-792, 2023.

EGU23-2178 | ECS | PICO | CR2.3

Radar-derived ice fabric anisotropy and implications on flow enhancement along the Thwaites Glacier Eastern Shear Margin 

Tun Jan Young, Carlos Martin, Thomas Jordan, Ole Zeising, Olaf Eisen, Poul Christoffersen, David Lilien, and Nicholas Rathmann

Glaciers and ice streams account for the majority of ice mass discharge to the ocean from the Antarctic Ice Sheet, and are bounded by intense bands of shear that separate fast-flowing from slow or stagnant ice, called shear margins. The anisotropy of glacier ice (i.e. a preferred crystal orientation) stemming from high rates of shear at these margins can greatly facilitate fast streaming ice flow, however it is still poorly understood due to a lack of in-situ measurements. If anisotropy is incorporated into numerical ice sheet models at all, it is usually as a simple scalar enhancement factor that represents the "flow law" that governs the model's rheology. Ground-based and airborne radar observations along two transects fully crossing the Eastern Shear Margin of Thwaites Glacier reveal rapid development of highly anisotropic fabric tightly concentrated around a lateral maximum in surface shear strain. These measurements of fabric strength at the centre of the shear margin are indicative of a horizontal pole configuration, which potentially represents ice that is “softened” to shearing in some directions and hardened in others. The resulting flow enhancement revealed by our results suggest that the viscosity of ice is highly variable and regime-dependent, and supports the importance of considering anisotropic flow laws to model the rheology of ice sheets.

How to cite: Young, T. J., Martin, C., Jordan, T., Zeising, O., Eisen, O., Christoffersen, P., Lilien, D., and Rathmann, N.: Radar-derived ice fabric anisotropy and implications on flow enhancement along the Thwaites Glacier Eastern Shear Margin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2178, https://doi.org/10.5194/egusphere-egu23-2178, 2023.

Permafrost, the frozen layer beneath a freezing and thawing active layer, is an impermeable frozen soil that persists for multiple years. The gradual thawing of permafrost and thickening of the active layer allows a glimpse into the evolution of the hydraulic processes that shape the periglacial landscape. One question in understanding the governing mechanics within the rapidly evolving periglacial landscape is how water retains within or segregates through the active layer to eventually feed rivers. 

In this exploratory study, we analyze data from multiple periglacial hydraulic catchments over time and characterize their hydraulic response rate to stressors. We test whether deconvolution and demixing of noisy time series can isolate precipitation from thawing permafrost signals in river discharge. We use the Ensemble Rainfall-Runoff (ERRA) script, which is effective in inferring nonstationary and nonlinear responses to precipitation using Runoff Response Distribution (RRD), to further test temperature signatures. Using this tool, we measure the RRD for the same catchments both over the years and over the summer months. We hypothesize that an increase in active layer thickness over years and over summer months will delay the RRD due to an increase in water storage.

By analyzing the parameters that change the RRD of periglacial systems with time, soil moisture content, average seasonal and yearly temperatures, and precipitation, we can begin a systematic understanding of how the active layer modulates hydraulic responses and how the responses may be different from other hydraulic systems.

How to cite: Culha, C. and Kirchner, J.: Characterizing melt water properties in the periglacial active layer through seasonal and yearly variations in catchment hydrology., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4291, https://doi.org/10.5194/egusphere-egu23-4291, 2023.

EGU23-5504 | PICO | CR2.3

Sensitivity of the mass conservation method to the regularisation scheme 

Fabien Gillet-Chaulet, Eliot Jager, and Mathieu Morlighem

While being one of the most important variables for predicting the future of the ice sheets, observations of ice thickness are only available along flight tracks, separated by a few to a few tens of kilometres. For many applications, these observations need to be interpolated on grids at a much higher resolution than the actual average spacing between tracks.

The mass conservation method is an inverse method that combines the sparse ice thickness data with high resolution surface velocity observations to obtain a high-resolution map of ice thickness that conserves mass and minimizes the departure from observations.  As with any inverse method, the problem is ill-posed and requires some regularisation. The classical approach is to use a Tikhonov regularisation that penalizes the spatial derivatives of the ice thickness and therefore favours smooth solutions with implicit spatial correlation structures. In a Bayesian framework, regularization can be seen as an implicit assumption for the prior probability distribution of the inverted parameter. Other popular geostatistical interpolation algorithms, such as kriging, usually require to parameterize the spatial correlation of the interpolated field using standard correlation functions (e.g., gaussian, exponential, Matèrn).

Here we replace the Tikhonov regularisation term in the mass conservation method  by a term that penalises the departure from a prior, where the error statistics are parametrized with the same standard correlation functions. This makes the regularisation independent from grid spacing and regularisation weights do not need to be adjusted. We present and discuss the sensitivity of the mass conservation method to the regularisation scheme using a suite of synthetic and “true” bed from deglaciated areas and show that prescribing the correct regularisation always provides the most accurate solution.

How to cite: Gillet-Chaulet, F., Jager, E., and Morlighem, M.: Sensitivity of the mass conservation method to the regularisation scheme, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5504, https://doi.org/10.5194/egusphere-egu23-5504, 2023.

EGU23-6770 | PICO | CR2.3

Greenland ice-stream dynamics: short-lived and agile? 

Olaf Eisen, Steven Franke, Paul D. Bons, Julien Westhoff, Ilka Weikusat, Tobias Binder, Kyra Streng, Daniel Steinhage, Veit Helm, John D. Paden, Graeme Eagles, and Daniela Jansen

Reliable knowledge of ice discharge dynamics for the Greenland ice sheet via its ice streams is essential if we are to understand its stability under future climate scenarios as well as their dynamics in the past, especially when using numerical models for diagnosis and prediction. Currently active ice streams in Greenland have been well mapped using remote-sensing data while past ice-stream paths in what are now deglaciated regions can be reconstructed from the landforms they left behind. However, little is known about possible former and now defunct ice streams in areas still covered by ice. Here we use radio-echo sounding data to decipher the regional ice-flow history of the northeastern Greenland ice sheet on the basis of its internal stratigraphy. By creating a three-dimensional reconstruction of time-equivalent horizons, we map folds deep below the surface that we then attribute to the deformation caused by now-extinct ice streams. We propose that locally this ancient ice-!ow regime was much more focused and reached much farther inland than today’s and was deactivated when the main drainage system was reconfigured and relocated southwards. The insight that major ice streams in Greenland might start, shift or abruptly disappear will affect our approaches to understanding and modelling the past or future response of Earth’s ice sheets to global warming. Such behaviour has to be sufficiently reproduced by numerical models operating on the mid- to longer-term timescales to be considered adequate physical representations of the naturally occuring dynamic behaviour of ice streams.

How to cite: Eisen, O., Franke, S., Bons, P. D., Westhoff, J., Weikusat, I., Binder, T., Streng, K., Steinhage, D., Helm, V., Paden, J. D., Eagles, G., and Jansen, D.: Greenland ice-stream dynamics: short-lived and agile?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6770, https://doi.org/10.5194/egusphere-egu23-6770, 2023.

EGU23-6900 | ECS | PICO | CR2.3

Determining Basal Mass Balance of Ice Shelves Using Simulation-Based Inference 

Guy Moss, Vjeran Višnjević, Cornelius Schröder, Jakob Macke, and Reinhard Drews

The ice shelves buttressing the Antarctic ice sheet determine its stability. Over half of all mass loss in Antarctica occurs due to ice melting at the water-ice boundary at the base of ice shelves. Different contemporary methods of estimating the spatial distribution of the melting rates do not produce consistent results, and provide no information about decadal to centennial timescales. We explore a new method to infer the spatial distribution of the basal mass balance (BMB) using the internal stratigraphy which may contain additional information not present in other sources such as ice thickness and surface velocities alone. The method estimates the Bayesian posterior distribution of the BMB,  and provides us with a principled measure of uncertainty in our estimates. 

 

Our inference procedure is based on simulation-based inference (SBI) [1], a novel machine learning inference method. SBI utilizes artificial neural networks to approximate probability distributions which characterize those parameters that yield data-compatible simulations, without the need of an explicit likelihood function. We demonstrate the validity of our method on a synthetic ice shelf example, and then apply it to Ekström ice shelf, East Antarctica, where we have radar measurements of the internal stratigraphy. The inference procedure relies on a simulator of the dynamics of the ice shelves. For this we use the Shallow Shelf Approximation (SSA) implemented in the Python library Icepack [2], and a time-discretized layer tracing scheme [3].  These detailed simulations, along with available stratigraphic data and the SBI methodology, allows us to compute a spatially-varying posterior distribution of the melting rate. This distribution corroborates existing estimates and extends upon them by quantifying the uncertainty in our inference. This uncertainty should be incorporated in future forecasting of ice shelf dynamics and stability analysis.

 

[1] Lueckmann et al.: Benchmarking simulation-based inference (2020).

[2] Shapero et al.: icepack: a new glacier flow modeling package in Python, version 1.0. (2021).

[3] Born: Tracer transport in an isochronal ice-sheet model (2017).



How to cite: Moss, G., Višnjević, V., Schröder, C., Macke, J., and Drews, R.: Determining Basal Mass Balance of Ice Shelves Using Simulation-Based Inference, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6900, https://doi.org/10.5194/egusphere-egu23-6900, 2023.

EGU23-8775 | PICO | CR2.3

Advancements in RUC Snow Model for Implementation in the Regional Application of the Unified Forecasting System (UFS) 

Tatiana Smirnova, Anton Kliewer, Siwei He, and Stan Benjamin

RUC land surface model (LSM) was designed for short-range weather predictions with an emphasis on severe weather. The model has been operational at NCEP since 1998. Currently it is utilized in the operational WRF-based Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) regional models. Being available to the world WRF community, RUC LSM is also used as a land-surface component in operational weather prediction models in Austria, New Zealand and Switzerland.

At present time, RUC LSM is being tested in the regional application of the UFS-based Rapid Refresh FV3 Standalone (RRFS) model to replace operational RAP and HRRR at NCEP.

RUC LSM has improved and matured over the years. The unique feature of this land-surface model is continuous evolution of soil/snow states within moderately coupled land data assimilation (MCLDA). To avoid possible drifts, this feature requires high skill from RUC LSM as well as accurate atmospheric forcing. Continuous snow cycling includes the following snow state variables: snow cover fraction, snow depth, snow water equivalent and snow temperature. To avoid possible inaccuracies in the location of cycled snow on the ground, snow depth is corrected daily using 4-km IMS snow cover information. Work is also underway to further improve RUC snow model for better surface predictions over snow-covered areas. RUC snow model uses “mosaic” approach to account for subgrid variability of snow cover. Within this approach, snow-covered and snow-free portions of the grid cells are treated separately in the solution of energy and moisture budgets. Thus, snow cover fraction becomes a critical parameter, and modifications to its computation have been developed and tested in the RRFS retrospective experiments. Results from these validation experiments will be presented at the meeting.

How to cite: Smirnova, T., Kliewer, A., He, S., and Benjamin, S.: Advancements in RUC Snow Model for Implementation in the Regional Application of the Unified Forecasting System (UFS), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8775, https://doi.org/10.5194/egusphere-egu23-8775, 2023.

EGU23-9080 | ECS | PICO | CR2.3

Historical snow and ice temperature compilation documents the recent warming of the Greenland ice sheet 

Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Asa Rennermalm, Achim Heilig, Jakob Abermann, Dirk Van As, Anja Løkkegaard, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel Van Den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm

The Greenland ice sheet mass loss is one of the main sources of contemporary sea-level rise. The mass loss is primarily caused by surface melt and the resulting runoff. During the melt season, the ice sheet’s surface receives energy from sunlight absorption and sensible heating, which subsequently heats the subsurface snow and ice. The energy from the previous melt season can also enhance melting in the following summer as less heating is required to bring the snow and ice to the melting point. Subsurface temperatures are therefore both a result and a driver of the timing and magnitude of surface melt on the ice sheet. We present a dataset of more than 3900 measurements of ice, snow and firn temperature at 10 m depth across the Greenland ice sheet spanning the years from 1912 to 2022. We construct an artificial neural network (ANN) model that takes as input the ERA5 reanalysis monthly near-surface air temperature and snowfall for the 1954-2022 period and train it on our compilation of observed 10-meter temperature. We use our dataset and the ANN to evaluate three broadly used regional climate models (RACMO, MAR and HIRHAM). Our ANN model provides an unprecedented and observation-based description of the recent warming of the ice sheet’s near-surface and our evaluation of the three climate models highlights future development for the models. Overall, these findings improve our understanding of the ice sheet’s response to recent atmospheric warming and will help reduce uncertainties of ice sheet surface mass balance estimates.

How to cite: Vandecrux, B., Fausto, R. S., Box, J. E., Covi, F., Hock, R., Rennermalm, A., Heilig, A., Abermann, J., Van As, D., Løkkegaard, A., Fettweis, X., Smeets, P. C. J. P., Kuipers Munneke, P., Van Den Broeke, M., Brils, M., Langen, P. L., Mottram, R., and Ahlstrøm, A. P.: Historical snow and ice temperature compilation documents the recent warming of the Greenland ice sheet, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9080, https://doi.org/10.5194/egusphere-egu23-9080, 2023.

EGU23-12495 | ECS | PICO | CR2.3

Radar forward modelling as a precursor for statistical inference 

Leah Sophie Muhle, Guy Moss, A. Clara J. Henry, and Reinhard Drews

Projections of the future development of the Antarctic Ice Sheet still exhibit a large degree of uncertainty due to difficulties in constraining parameters of ice-flow models such as basal boundary conditions. Deriving better estimates of these parameters from radargrams could greatly improve model accuracy, but integration of inferred radar attributes into ice-flow models is not yet widespread.

Here, we develop a radar forward modeling framework that is geared to train a machine learning workflow (likely simulation-based inference) to extract radar attributes such as the internal stratigraphy and basal boundary conditions (e.g., frozen vs. wet) from radar data. The workflow starts with ice-dynamic forward models predicting physically sound stratigraphies and internal/basal temperatures for synthetic flow settings using shallow ice, shallow shelf and higher order ice-flow models. This is then used as input to the radar simulator (here gprMax), which calculates the radar image produced by such a stratigraphy. To do so, we match the synthetic permittivities of the modeled stratigraphy with statistical properties known from ice-core logging data and prescribe temperature dependent attenuation via an Arrhenius relation. gprMax is optimized for acceleration using GPUs which can be efficiently employed when solving the FDTD discretized Maxwell equations. Currently, 200 m wide and 500 m deep sections can be simulated on a single NVIDIA GeForce RTX 2070 Super graphics card within 390 minutes. The runtime can be substantially improved in a HPC environment. In order to obtain radar simulations comparable with observations, we also add system specific noise and contributions from volume scattering with variable surface roughness. Here, we focus on 50 MHz pulse radar for which we have many observational counterparts. However, the workflow is designed to encompass multiple ice-dynamic settings and different radar frequencies.

The application of physical forward models will result in physically meaningful radargrams which are indistinguishable from observations. This provides a tool to create datasets for training machine learning workflows for inference without the limitations of hand-labeled data.

How to cite: Muhle, L. S., Moss, G., Henry, A. C. J., and Drews, R.: Radar forward modelling as a precursor for statistical inference, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12495, https://doi.org/10.5194/egusphere-egu23-12495, 2023.

EGU23-12553 | ECS | PICO | CR2.3

At the bottom of ice streams: unraveling the physics of sliding onset through a glacier-scale field experiment 

Elisa Mantelli, Reinhard Drews, Olaf Eisen, Daniel Farinotti, Martin Luethi, Laurent Mingo, Dustin Schroeder, and Andreas Vieli

Fast ice stream flow at speeds of hundreds to thousands of meters per year is sustained by sliding at the ice sheet base, whereas slow flow outside of ice streams is characterized by limited-to-no basal sliding. In this sense, the transition from no sliding to significant sliding exerts a key control on ice stream flow. The detailed physical processes that enable the onset of basal sliding are somewhat debated, but laboratory experiments, recent theoretical work, and a handful of direct observations support the notion of sliding initiating below the melting point as a result of regelation and premelting. 

In this contribution we describe a recently funded glacier-scale field experiment that has been designed to advance the understanding of sliding onset physics by testing the hypothesis that sliding starts below the melting point. The experiment will take place at the Grenzgletscher (Swiss Alps), which is known to have a cold-based accumulation region and a temperate-based ablation region. Our work will involve extensive surface geophysics (radio echo sounding, terrestrial radar interferometry, radar thermal tomography) aimed at identifying the sliding onset region. This work will guide the site selection for a subsequent borehole study of englacial deformation that is meant illuminate the relation between sliding velocity and basal temperature. The borehole work will allow us to test systematically the hypothesis that sliding starts below the melting point through an extended region of temperature-dependent sliding, and possibly to advance the formulation of temperature-dependent friction laws that are used to describe the onset of sliding in ice flow models.

The focus of this contribution will be specifically on the experimental design - how it is informed by existing theory and observations, and how it will support theoretical and ice flow modeling advances, at the glacier scale and beyond.

How to cite: Mantelli, E., Drews, R., Eisen, O., Farinotti, D., Luethi, M., Mingo, L., Schroeder, D., and Vieli, A.: At the bottom of ice streams: unraveling the physics of sliding onset through a glacier-scale field experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12553, https://doi.org/10.5194/egusphere-egu23-12553, 2023.

EGU23-14292 | ECS | PICO | CR2.3

Bias correction of climate models using observations over Antarctica. 

Jeremy Carter, Erick Chacón Montalván, and Amber Leeson

Regional Climate Models (RCM) are the primary source of climate data available for impact studies over Antarctica. These climate-models experience significant, large-scale biases over Antarctica for variables such as snowfall, surface temperature and melt. Correcting for these biases is desirable for impact models being driven by meteorological data that aim to produce optimal estimates of for example surface run-off and ice discharge. Typical approaches to bias correction often neglect the handling of uncertainties in parameter estimates and don’t account for the different supports of climate-model and observed data. Here a fully Bayesian approach using latent Gaussian processes is proposed for bias correction, where parameter uncertainties are propagated through the model. Advantages of this approach are demonstrated by bias-correcting RCM output for near-surface air temperature over Antarctica.

How to cite: Carter, J., Chacón Montalván, E., and Leeson, A.: Bias correction of climate models using observations over Antarctica., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14292, https://doi.org/10.5194/egusphere-egu23-14292, 2023.

EGU23-15374 | ECS | PICO | CR2.3

Reconstructing accumulation rates of the Greenland ice sheet using dated radiostratigraphy 

Philipp Immanuel Voigt and Andreas Born

The stability of the Greenland ice sheet is poorly constrained even for benchmark periods such as the mid-Holocene or Eemian. Since ice stratigraphy holds a record of both surface mass balance (SMB) and ice dynamics, dated radiostratigraphy offer a potential route to improved reconstructions. Here we explicitly simulate isochrones and employ inverse methods to optimize the solution. The Englacial Layer Simulation Architecture (ELSA) coupled with a thermomechanical ice sheet model computes the isochrones or ice layers, which enable the direct comparison with the radiostratigraphy data. The accumulation rates force ELSA, and are adjusted until the model reproduces the observations within their uncertainties. We deploy the Ensemble Kalman Smoother for the data assimilation. This results in not only the reconstruction of the SMB; an optimized simulation of the ice sheet is obtained by solving the corresponding forward problem. Hence, the contribution to sea level change by Greenland over the same period can also be constrained.

Here we present our initial approach and preliminary results of SMB reconstruction. Future plans and expansions of the work are also presented, involving the study of several model parameters such as basal traction.

How to cite: Voigt, P. I. and Born, A.: Reconstructing accumulation rates of the Greenland ice sheet using dated radiostratigraphy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15374, https://doi.org/10.5194/egusphere-egu23-15374, 2023.

EGU23-40 | PICO | CR2.2

Investigating firn and ice anisotropy around the EastGRIP Camp, North East Greenland Ice Stream, from ambient noise surface waves 

Emma Pearce, Dimitri Zigone, Charlie Schoonman, Steven Franke, Olaf Eisen, and Joachim Rimpot

We use cross-correlations of ambient seismic noise data between pairs of 9 broadband three component seismometers to investigate variations in velocity structure and anisotropy in the vicinity of the EastGRIP camp along and across flow of the Northeast Greenland Ice Stream (NEGIS).

From the 9-component correlation tensors associated with all station pairs we derive dispersion curves of Rayleigh and Love wave group velocities between station pairs at frequencies from 1 to 25 Hz. The distributions of the Rayleigh and Love group velocities exhibit anisotropy variations for the along and across flow component. To better assess those variations, we invert the dispersions curves to shear wave velocities in the horizontal (Vsh) and vertical (Vsv) direction for the top 300 m of the NEGIS using a Markov Chain Monte Carlo approach.

The reconstructed 1-D shear velocity model revels radial anisotropy in the NEGIS. Along and across flow vertical shear wave velocities (Vsv) identify comparable velocity profiles for all depths. However, horizontal shear wave velocities (Vsh) are faster by approximately 250 m/s in the along flow direction below a depth of 100 m, i.e. below the firn-ice transition.

This type of anisotropy seems to arise from the alignment of a crystallographic preferred orientation, due to deformation associated with shear zones. The role of anisotropy as e.g. created by air bubbles in the firn and ice matrix, is yet unclear.

Faster Vsh velocities in the along flow direction support that the NEGIS has crystal orientation alignment normal to the plane of shear compression (i.e. ice crystals orientated across flow) within the upper 300 m of the ice stream and are in alignment with the results from other methods. We demonstrate that simple, short duration (2-3 weeks), passive seismic deployment and environmental noise-based analysis can be used to determine the anisotropy of the upper part of ice masses.

How to cite: Pearce, E., Zigone, D., Schoonman, C., Franke, S., Eisen, O., and Rimpot, J.: Investigating firn and ice anisotropy around the EastGRIP Camp, North East Greenland Ice Stream, from ambient noise surface waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-40, https://doi.org/10.5194/egusphere-egu23-40, 2023.

EGU23-92 | ECS | PICO | CR2.2

Improving identification of glacier bed materials using converted-wave seismics 

Ronan Agnew, Adam Booth, Alex Brisbourne, Roger Clark, and Andy Smith

When modelling ice sheet and glacier dynamics, a consideration of basal conditions is essential. Bed topography, hydrology and materials provide important controls on ice flow; however, the materials underlying large sections of the polar ice sheets are unknown. Seismic amplitude-versus-offset (AVO) analysis provides a means of inferring glacier bed properties, namely acoustic impedance and Poisson's ratio, by measuring bed reflectivity as a function of incidence angle.

However, existing methods of applying AVO to glaciology only consider the compressional-wave component of the wavefield and solutions suffer from non-uniqueness. This can be addressed using multi-component seismic datasets, in which a strong converted-wave arrival (downgoing compressional-wave energy converted to shear-wave energy upon reflection at the glacier bed) is often present. We present a method of jointly inverting compressional (PP) and converted-wave (PS) seismic data to improve constraint of glacier bed properties.

Using synthetic data, we demonstrate that for typical survey geometries, joint inversion of PP- and PS-wave AVO data delivers better-constrained bed acoustic impedance and Poisson’s ratio estimates compared with PP-only inversion. Furthermore, joint inversion can produce comparably constrained results to PP inversion when using input data with a smaller range of incidence angles/offsets (0-30 degree incidence for joint inversion, versus 0-60 degrees for PP- only). This could simplify future field acquisitions on very thick ice, where obtaining data at large incidence angles is difficult.

Joint AVO inversion therefore has the potential to improve identification of glacier bed materials and simplify field acquisitions of glacial AVO data. We also present preliminary results from Korff Ice Rise, West Antarctica, where better constraints on bed conditions can help improve our knowledge of ice sheet history in the Weddell Sea sector. Routine measurements of this kind will help constrain ice-sheet model inputs and reduce uncertainty in predictions of sea-level rise.

How to cite: Agnew, R., Booth, A., Brisbourne, A., Clark, R., and Smith, A.: Improving identification of glacier bed materials using converted-wave seismics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-92, https://doi.org/10.5194/egusphere-egu23-92, 2023.

EGU23-93 | ECS | PICO | CR2.2

Efficient neural network-based detection of seismicity in fibre optic data from Store Glacier, West Greenland 

Andrew Pretorius, Adam Booth, Emma Smith, Andy Nowacki, Sjoerd de Ridder, Poul Christoffersen, and Bryn Hubbard

Seismic surveys are widely used to characterise the properties of glaciers, their basal material and conditions, and ice dynamics. The emerging technology of Distributed Acoustic Sensing (DAS) uses fibre optic cables as seismic sensors, allowing observations to be made at higher spatial resolution than possible using traditional geophone deployments. Passive DAS surveys generate large data volumes from which the rate of occurrence and failure mechanism of ice quakes can be constrained, but such large datasets are computationally expensive and time consuming to analyse. Machine learning tools can provide an effective means of automatically identifying seismic events within the data set, avoiding a bottleneck in the data analysis process.

Here, we present a novel approach to machine learning for a borehole-deployed DAS system on Store Glacier, West Greenland. Data were acquired in July 2019, as part of the RESPONDER project, using a Silixa iDAS interrogator and a BRUsens fibre optic cable installed in a 1043 m-deep borehole. The data set includes controlled-source vertical seismic profiles (VSPs) and a 3-day passive record of cryoseismicity.  To identify seismic events in this record, we used a convolutional neural network (CNN). A CNN is a deep learning algorithm and a powerful classification tool, widely applied to the analysis of images and time series data, i.e. to recognise seismic phases for long-range earthquake detection.

For the Store Glacier data set, a CNN was trained on hand-labelled, uniformly-sized time-windows of data, focusing initially on the high-signal-to-noise-ratio seismic arrivals in the VSPs. The trained CNN achieved an accuracy of 90% in recognising seismic energy in new windows. However, the computational time taken for training proved impractical. Training a CNN instead to identify events in the frequency-wavenumber (f-k) domain both reduced the size of each data sample by a factor of 340, yet still provided accurate classification. This decrease in input data volume yields a dramatic decrease in the time required for detection. The CNN required only 1.2 s, with an additional 5.6 s to implement the f-k transform, to process 30 s of data, compared with 129 s to process the same data in the time domain. This suggests that f-k approaches have potential for real-time DAS applications.

Continuing analysis will assess the temporal distribution of passively recorded seismicity over the 3 days of data. Beyond this current phase of work, estimated source locations and focal mechanisms of detected events could be used to provide information on basal conditions, internal deformation and crevasse formation. These new seismic observations will help further constrain the ice dynamics and hydrological properties of Store Glacier that have been observed in previous studies of the area.

The efficiency of training a CNN for event identification in the f-k domain allows detailed insight to be made into the origins and style of glacier seismicity, facilitating further development to passive DAS instrumentation and its applications.

How to cite: Pretorius, A., Booth, A., Smith, E., Nowacki, A., de Ridder, S., Christoffersen, P., and Hubbard, B.: Efficient neural network-based detection of seismicity in fibre optic data from Store Glacier, West Greenland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-93, https://doi.org/10.5194/egusphere-egu23-93, 2023.

EGU23-952 | PICO | CR2.2

Variability of surface density at Dotson Ice Shelf, West Antarctica 

Clare Eayrs, Lucas Beem, Choon-Ki Lee, Won Sang Lee, Jiwoong Chung, Christopher Pierce, Jamey Stutz, and David Holland

The ice mass balance of Antarctica has been steadily and strongly decreasing over recent decades, with major ramifications for global sea levels. Satellite remote sensing offers global, daily coverage of ice mass changes, which is essential for understanding land ice changes and their effects on global climate. However, we need to correct for processes including firn densification, glacial isostatic adjustment, elastic compensation of the Earth’s surface, ocean tides, and inverse barometer effect. Of these corrections, understanding the changes to the firn layer constitutes one of the largest uncertainties in making estimates of the surface mass balance from space. Furthermore, the development of firn models that aid our understanding of firn densification processes is hampered by a lack of observations.

Radar sounder reflections contain information about the roughness and permittivity of the reflecting interface, allowing us to map the spatial variability of the ice surface characteristics. In 2022, a helicopter-mounted ice-penetrating radar system developed by the University of Texas Institute for Geophysics collected high-quality radar observations over the Dotson Ice Shelf, West Antarctica. These surveys obtained clearly defined surface and bed reflections. We derived near-surface density along these survey flight lines using the radar statistical reconnaissance method developed by Grima, 2014. We calibrated our estimates with contemporary observations, including ground penetrating radar, a shallow ice core, an Autonomous phase-sensitive Radio Echo-sounder (ApRES), and radar soundings of well-defined surfaces from a calibration flight.

How to cite: Eayrs, C., Beem, L., Lee, C.-K., Lee, W. S., Chung, J., Pierce, C., Stutz, J., and Holland, D.: Variability of surface density at Dotson Ice Shelf, West Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-952, https://doi.org/10.5194/egusphere-egu23-952, 2023.

EGU23-1137 | ECS | PICO | CR2.2

Hydraulic behaviour of a mountain permafrost subsoil revealed by an infiltration experiment and ERT time-lapse measurements 

Mirko Pavoni, Jacopo Boaga, Alberto Carrera, Giulia Zuecco, Luca Carturan, and Matteo Zumiani

Although rock glaciers represent a common periglacial landform in the alpine environment, and have a significant contribution to the hydrological regime of the related areas, their hydrodynamic is relatively less defined if compared to moraines, talus, and hillslope deposits. So far, the hydraulic behaviour of frozen layers that may be found inside rock glaciers has been investigated only with geochemical analysis of their spring water. These previous studies observed that the frozen layer acts as an aquiclude (or aquitard) and separates a supra-permafrost flow component, originating from snow-ice melting and rainwater, and a deeper aquifer at the bottom of the rock glacier systems.

In this work we verified, for the first time with a geophysical monitoring method, the low-permeability hydraulic behaviour associated to the frozen layer of mountain permafrost subsoils. In the inactive rock glacier of Sadole Valley (Southern Alps, Trento Province, Italy) we performed an infiltration experiment combined with 2D electrical resistivity tomography (ERT) measurements in time-lapse configuration. Considering the same ERT transect, a time zero dataset (t0) has been collected before the water injection, subsequently about 800 liters of salt water have been spilled (approximately in a point) on the surface of the rock glacier in the middle of the electrodes array, and 10 ERT datasets have been collected periodically in the following 24 hours. To highlight the variations of electrical resistivity in the frozen subsoil, related to the injected salt water flow, only the inverted resistivity model derived from t0 dataset has been represented in terms of absolute resistivities, while the other time steps results have been evaluated in terms of percentage changes of resistivity with respect to the t0 initial model.

Our results clearly agree with the assumption that a frozen layer acts as an aquiclude (or aquitard) in a mountain permafrost aquifer, since during the infiltration experiment the injected salt water was not able to infiltrate into the underlying permafrost layer. The positive outcome of this test, fronting impervious environment and logistic constraints, opens up interesting future scenarios regarding the application of this geophysical monitoring method for the hydraulic characterization of rock glaciers. The experiment, used in this work to evaluate the permeability of the frozen layer, could be adapted in future to evaluate (in a quantitative way) the hydraulic conductivity of the active layer in rock glacier aquifers.

How to cite: Pavoni, M., Boaga, J., Carrera, A., Zuecco, G., Carturan, L., and Zumiani, M.: Hydraulic behaviour of a mountain permafrost subsoil revealed by an infiltration experiment and ERT time-lapse measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1137, https://doi.org/10.5194/egusphere-egu23-1137, 2023.

EGU23-2250 | ECS | PICO | CR2.2

Ice slab thickening drives surface runoff expansion from the Greenland Ice Sheet’s percolation zone - and vice versa 

Nicolas Jullien, Andrew Tedstone, and Horst Machguth

On the Greenland Ice Sheet, the firn layer holds the potential to trap and refreeze surface meltwater within its pore space. Acting as a buffer, it prevents meltwater from leaving the ice sheet. However, several meter-thick ice slabs have developed in the firn during the last two decades, reducing subsurface permeability and inhibiting vertical meltwater percolation. Ice slabs are located above the long-term equilibrium line along the west, north and northeast coasts of the ice sheet. Through time, ice slabs have thickened while new ones have developed at higher elevations. Concomitantly, the area of the ice sheet drained by surface rivers has increased by 29% from 1985 to 2020. Nowadays, 5-10% of surface losses through meltwater runoff originates from these newly drained areas, which correspond strongly with where ice slabs are located.

Here, we demonstrate that the highest elevation which is drained by surface rivers – termed the maximum visible runoff limit – is controlled by the ice content in the subsurface firn. Using ice slab thickness derived from the accumulation radar and annual maximum visible limit retrievals from Landsat imagery from 2002 to 2018, we show that a sub-surface ice content threshold triggers the shift from a ‘firn deep percolation regime’ to a ‘firn runoff regime’. Although ice slabs act as an aquitard, vertical meltwater percolation can still take place where visible meltwater ponds at the surface. We show that once the firn runoff regime is underway, ice slabs are thicker in locations with active surface hydrology compared to locations where no meltwater is visible at the surface. Spatial heterogeneity in ice slab thickness is therefore predominantly controlled by surface hydrology features.

How to cite: Jullien, N., Tedstone, A., and Machguth, H.: Ice slab thickening drives surface runoff expansion from the Greenland Ice Sheet’s percolation zone - and vice versa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2250, https://doi.org/10.5194/egusphere-egu23-2250, 2023.

EGU23-2856 | ECS | PICO | CR2.2

New Representation of Synthetic Aperture Radar Images for Enhanced Ice-Sounding Interpretation 

Álvaro Arenas-Pingarrón, Hugh F.J. Corr, Paul V. Brennan, Carl Robinson, Tom A. Jordan, Alex Brisbourne, and Carlos Martín

The processing of Synthetic Aperture Radar (SAR) images is based on the coherent integration of Doppler frequencies. The associated Doppler spectrum is generated from the variation of the relative location between the radar and the scatterer. In geometries where the moving radar-platform follows a straight trajectory at constant velocity, the Doppler frequency depends on the angle of elevation from the radar to the scatterer, according to the electromagnetic (EM) propagation. In ice-sounding by airborne SAR, the EM path depends on the air-ice interface and the firn ice properties. For any of the scatterers under test, after integrating the received radar echoes from the multiple radar locations into a single pixel, the resulting amplitude image forgets which is the backscattering angle from each of the radar locations. However, this information is still within the Doppler spectrum of the image. We decompose the Doppler spectrum of the SAR image into three non-overlapping sub-bands; assign to each sub-band one of the primary colours red, green or blue, forming three sub-images; and finally merge the sub-images into a single one. Rather than a single full-beamwidth averaged amplitude value, the new composition now includes angular backscattering information, coded by one of the primary colours. Blue colour is assigned to scattering received from forwards, when the scatterer is ahead of the radar (positive Doppler frequencies); green approximately from the vertical (near zero-Doppler geometries); and red to scattering received from backwards (negative Doppler). Thus, heterogeneous scattering will be represented by one or two colours, whereas homogeneous scattering will be grey, with all the primary colours uniformly weighted. Features like internal layering, crevasses, SAR focussing quality and discrimination of multiple reflections from surface and bottom, can now be better interpreted. We present and discuss the results from the British Antarctic Survey (BAS) airborne radar PASIN2 for deep-ice sounding, in Recovery and Rutford ice streams, respectively in East and West Antarctica during seasons 2016/17 and 2019/20.

How to cite: Arenas-Pingarrón, Á., Corr, H. F. J., Brennan, P. V., Robinson, C., Jordan, T. A., Brisbourne, A., and Martín, C.: New Representation of Synthetic Aperture Radar Images for Enhanced Ice-Sounding Interpretation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2856, https://doi.org/10.5194/egusphere-egu23-2856, 2023.

In many regions of the Northern Hemisphere, permafrost is thawing due to climate change. In steep terrain, this permafrost degradation can affect slope stability. In one of Iceland's eastern fjords, Seyðisfjörður, nine major landslide cycles have occurred in the last century, originating from the lower parts (< 500 m a.s.l.) of the Strandartindur slopes, with the largest landslide event ever recorded in Iceland occurring in December 2020. Its triggering mechanism is being intensively studied and its development is being monitored. In addition to these instabilities, slow movements are also observed in the upper part (> 500 - 1010 m a.s.l.) of these slopes. In these upper areas, it is not known whether permafrost is present in the subsurface or what is causing it to creep downward. To further investigate the stability of these slopes, it is important to know and map the distribution and condition of possible permafrost layers. Therefore, electrical resistivity tomography (ERT) and ground penetrating radar (GPR) measurements were performed to study the presence and distribution of permafrost in the mountain, Strandartindur, above Seyðisfjörður. A combination of measurements is used as ERT responds primarily to the electrical resistivity of the subsurface, but this can depend strongly on other factors such as porosity, water content, etc., and GPR can help map the presence of different interfaces in the soil determined by their different physical properties, such as relative electrical permittivity, but also conductivity, which is the reciprocal of resistivity. Combining the two methods allows us to get a clearer picture of the subsurface. As a benchmark for ERT measurements in the field, a laboratory setup was performed with soil and rock samples at different temperatures and water saturations to study the behavior of frozen and non-frozen conditions in our geologic environment. With all of these measurements, we aim to answer the questions of whether permafrost is present in the selected area, what the distribution of permafrost is, whether we can use laboratory ERT to establish reference resistivity values, and if these methods are appropriate for this area.

How to cite: von der Esch, A., Piispa, E. J., and Sæmundsson, Þ.: Electrical Resistivity Tomography and Ground-Penetrating Radar Measurements for Permafrost Detection on a Mountain Slope at Strandartindur, Seyðisfjörður - East Iceland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4135, https://doi.org/10.5194/egusphere-egu23-4135, 2023.

EGU23-4895 | ECS | PICO | CR2.2

Detecting permafrost freeze-thaw front propagation using time-laps ERT observations in a large column experiment 

Jelte de Bruin, Victor Bense, and Martine van der Ploeg

Cold regions are increasingly subjected to higher air temperatures, causing warming of permafrost and a deepening of the active layer. This activates hydrogeological groundwater flow and new groundwater pathways to emerge. Monitoring of the active layer depth occurs mainly with the use of temperature observations, but a more flexible and non-invasive method to study transient subsurface processes is with the use of Electrical Resistivity Tomography (ERT) observations. 

Automated time-laps ERT arrays are used to monitor the frozen ground evolution during various seasons, observing resistivity variations during freezing and thawing. Similarly, the leaching of meltwater into the ground under freezing/thawing conditions can be observed. Not only geophysical changes such as fluctuations in water content and water table, but also temperature variations affect the electrical resistivity field. In order to track the development of permafrost active-layer freeze-thaw fronts using ERT observations, it is thus essential that the effect of temperature on the resistivity is clearly defined at realistic scales representing field conditions. Our aim is to determine fluid resistivity at various stages during freezing and thawing and validate current temperature–resistivity relations for partly frozen soils.

This study used a soil column (0.4 m diameter, 1 m heigh) equipped with 96 stainless steel electrodes placed at 8 horizontal rings of 12 electrodes each at various heights around the circumference of the column alongside with temperature sensors. The column was fully insulated on the sides and top except for the bottom, creating a 1D heat transfer system. The soil column was filled with quartzite sand with a D50 of 350 (μm) and organic matter content of 5 (wgt %). The experimental setup was placed within a climate chamber where the column was frozen to -4 °C and thawed to 3 °C over a 3-month period. During the freezing and thawing phase, a full 3D resistivity image was collected using the ERT at a weekly interval. Initial results show that the setup is capable of simulating permafrost freezing and thawing dynamics and ongoing work focuses on the relation between the temperature and time lapse ERT resistivity observations.

How to cite: de Bruin, J., Bense, V., and van der Ploeg, M.: Detecting permafrost freeze-thaw front propagation using time-laps ERT observations in a large column experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4895, https://doi.org/10.5194/egusphere-egu23-4895, 2023.

EGU23-5545 | ECS | PICO | CR2.2

High resolution maps of the sub-ice platelet layer in Atka Bay from electromagnetic induction sounding 

Mara Neudert, Stefanie Arndt, Markus Schulze, Stefan Hendricks, and Christian Haas

We present maps of the sub-ice platelet layer (SIPL) thickness and ice volume fraction beneath the land-fast sea ice in Atka Bay adjacent to the Ekström Ice Shelf (southeastern Weddell Sea, Antarctica). The widespread SIPL beneath Antarctic fast ice is indicative of basal melt of nearby ice shelves, contributes to the sea ice mass balance and provides a unique ecological habitat. Where plumes of supercooled Ice Shelf Water (ISW) rise to the surface rapid formation of platelet ice can lead to the presence of a semi-consolidated SIPL beneath consolidated fast ice.

Here we present data from extensive electromagnetic (EM) induction surveying with the multi-frequency EM sounder GEM-2 between May and December, 2022. It includes monthly survey data along a fixed transect line across Atka Bay between May and October, as well as comprehensive mapping across the entire bay in November and December. The GEM-2 surveys were supplemented by drill hole thickness measurements, ice coring and CTD profiles. A new data processing and inversion scheme was successfully applied to over 1000 km of EM profiles with a horizontal resolution of one meter. We obtained layer thicknesses of the consolidated ice plus snow layer, the SIPL, and the respective layer conductivities. The latter were used to derive SIPL ice volume fraction and an indicator for flooding at the snow-ice interface. The robustness of the method was validated by drill hole transects and CTD profiles.

Our results support conclusions about the spatial variability of the ocean heat flux linked to outflow of ISW from beneath the ice shelf cavity. Temporally, we found that the end of SIPL growth and the onset of its thinning in summer can be linked to the disappearance of supercooled water in the upper water column.

How to cite: Neudert, M., Arndt, S., Schulze, M., Hendricks, S., and Haas, C.: High resolution maps of the sub-ice platelet layer in Atka Bay from electromagnetic induction sounding, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5545, https://doi.org/10.5194/egusphere-egu23-5545, 2023.

EGU23-5851 | PICO | CR2.2

Measuring snow and avalanche properties using acoustic and seismic distributed fiber optic sensing 

Alexander Prokop, Nicola P. Agostinetti, and Bernhard Graseman

Since 2012 we monitor avalanche activity using distributed acoustic and seismic fiber optic sensing at our avalanche test area at Lech am Arlberg, Austria. The method is based on an optical time domain reflectometer system that detects seismic vibrations and acoustic signals on a fiber optic cable that can have a length of up to 30 km in 80 cm resolution. While in the first years we focused on successfully developing an operational avalanche detection system that is able to tell in real time reliably when an avalanche was triggered and what the size of the avalanche is, we now present our investigations of the seismic signals to measure snow properties such as snow depth and avalanche properties such as flow behavior. Our test in winter 2022 recorded by blasting triggered avalanches and during data post processing we extracted seismic guided waves. We discuss methods for extracting information from guided waves for measuring snow depth, which was verified against spatial snow depth measurements from terrestrial laser scanning. Analyzing the seismic signals of avalanches with run-out distances ranging from a few metres to approximately 250 m allows us to differentiate between wet and snow avalanches, which is discussed in the context of avalanche dynamics.

How to cite: Prokop, A., Agostinetti, N. P., and Graseman, B.: Measuring snow and avalanche properties using acoustic and seismic distributed fiber optic sensing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5851, https://doi.org/10.5194/egusphere-egu23-5851, 2023.

EGU23-6935 | PICO | CR2.2

A new view of a 1970s radar dataset from Greenland 

Nanna Bjørnholt Karlsson, Dustin Schroeder, Louise S. Sørensen, Winnie Chu, Thomas Teisberg, Angelo Tarzano, Niels Skou, and Jørgen Dall

The short observational record is one of the main obstacles to improving the present understanding of the future of the Polar ice sheets. While the quantity and quality of observations presently are increasing observations from before the 1990s are scarce. Here, we present the first results from a newly digitized ice-penetrating radar dataset acquired over the Greenland Ice Sheet in the 1970s. The data consist of more than 170,000 km of radar flight lines. While the ice thickness information from the data has been digitized by previous studies, the data itself (notably the z-scopes) were until recently only available as 35-mm films, microfiche copies of the films, and enlarged positives: Formats that are not usable for digital analysis.

In 2019, the film rolls were scanned by a digital scanner and subsequently, a large effort has been directed at carrying out quality control of the data with the view of making them publicly available.  Here we present the first results from this digitization. The overall data quality is good, and we are able to retrieve valuable information on layer stratigraphy and ice-flow dynamics.

How to cite: Karlsson, N. B., Schroeder, D., Sørensen, L. S., Chu, W., Teisberg, T., Tarzano, A., Skou, N., and Dall, J.: A new view of a 1970s radar dataset from Greenland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6935, https://doi.org/10.5194/egusphere-egu23-6935, 2023.

EGU23-7198 | PICO | CR2.2

Climatic imprint in the mechanical properties of ice sheets and its effect on ice flow: Observations fromSouth Pole and EPICA Dome C ice cores 

Carlos Martin, Robert Mulvaney, Howard Conway, Michelle Koutnik, C. Max Stevens, Hugh Corr, Catherine Ritz, Keith Nicholls, Reinhard Drews, and M. Reza Ershadi

The climatic conditions over ice sheets at the time of snow deposition and compaction imprint distinctive crystallographic properties to the resulting ice. As it gets buried, its macroscopic structure evolves due to vertical compression but retains traces of the climatic imprint that generate distinctive mechanical, thermal and optical properties. Because climate alternates between glacial periods, that are colder and dustier, and interglacial periods, the ice sheets are composed from layers with alternating mechanical properties. Here we compare ice core dust content, crystal orientation fabrics and englacial vertical strain-rates, measured with a phase-sensitive radar (ApRES), at the South Pole and EPICA Dome C ice cores. In agreement with previous observations, we show that ice deposited during glacial periods develops stronger crystal orientation fabrics. In addition, we show that ice deposited during glacial periods is harder in vertical compression and horizontal extension, up to about three times, but softer in shear. These variations in mechanical properties are ignored in ice-flow models but they could be critical for the interpretation of ice core records. Also, we show that the changes in crystal orientation fabrics due to transitions from interglacial to glacial conditions can be detected by radar. This information can be used to constrain age-depth at future ice-core locations.

How to cite: Martin, C., Mulvaney, R., Conway, H., Koutnik, M., Stevens, C. M., Corr, H., Ritz, C., Nicholls, K., Drews, R., and Ershadi, M. R.: Climatic imprint in the mechanical properties of ice sheets and its effect on ice flow: Observations fromSouth Pole and EPICA Dome C ice cores, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7198, https://doi.org/10.5194/egusphere-egu23-7198, 2023.

EGU23-7695 | ECS | PICO | CR2.2

Spatial variation of ice crystal fabric and implications of anisotropic flow in the Northeast Greenland Ice Stream 

Tamara Gerber and Olaf Eisen and the NEGIS community

Anisotropic crystal fabrics in ice sheets develop as a consequence of deformation and hence record information of past ice flow. Simultaneously, the fabric affects the present-day bulk mechanical properties of glacier ice because the susceptibility of ice crystals to deformation is highly anisotropic. This is particularly relevant in dynamic areas such as fast-flowing glaciers and ice streams, where the formation of strong fabrics might play a critical role in facilitating ice flow. Anisotropy is ignored in most state-of-the-art ice sheet models, and while its importance has long been recognized, accounting for fabric evolution and its impact on the ice viscosity has only recently become feasible. Both the application of such models to ice streams and their verification through in-situ observations are still rare. We present an extensive dataset of fabric anisotropy derived from ground-based and air-borne radar data, covering approximately 24,000 km2 of the Northeast Greenland Ice Stream onset region. Our methods yield the horizontal anisotropy and are based on travel time anisotropy as well as birefringence-induced power modulation of radar signals. These methods complement each other and show good agreement. We compare the in-situ observations with the results obtained from a fabric-evolution model employed along flow line bundles in the ice stream onset to discuss the fabric in light of past flow history and its significance for the current flow mechanics of the ice stream.

 

How to cite: Gerber, T. and Eisen, O. and the NEGIS community: Spatial variation of ice crystal fabric and implications of anisotropic flow in the Northeast Greenland Ice Stream, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7695, https://doi.org/10.5194/egusphere-egu23-7695, 2023.

EGU23-8197 | ECS | PICO | CR2.2

Ice rise evolution derived from radar investigations at a promontory triple junction, Dronning Maud Land, East Antarctica 

M. Reza Ershadi, Reinhard Drews, Veronica Tsibulskaya, Sainan Sun, Clara Henry, Falk Oraschewski, Inka Koch, Carlos Martin, Jean-Louis Tison, Sarah Wauthy, Paul Bons, Olaf Eisen, and Frank Pattyn

Promontory ice rises are locally grounded features adjacent to ice shelves that are still connected to the ice sheet. Ice rises are an archive for the atmospheric and ice dynamic history of the respective outflow regions where the presence, absence, or migration of Raymond arches in radar stratigraphy represents a memory of the ice-rise evolution. However, ice rises and their inferred dynamic history are not yet used to constrain large-scale ice flow model spin-ups because matching the arch amplitudes includes many unknown parameters, e.g., those pertaining to ice rheology. In particular, anisotropic ice flow models predict gradients in ice fabric anisotropy on either side of an ice divide. However, this has thus far not been validated with observations.

 

The ground-based phase-sensitive Radio Echo Sounder (pRES) has previously been used to infer ice fabric types for various flow regimes using the co-polarized polarimetric coherence phase as a metric to extract information from the birefringent radar backscatter. Here, we apply this technique using quad-polarimetric radar data along a 5 km transect across a ridge near the triple junction of Hammarryggen Ice Rise at the Princess Ragnhild Coast. A comparison with ice core data collected at the dome shows that the magnitude of ice fabric anisotropy can reliably be reconstructed from the quad-polarimetric data. We use the combined dataset also to infer the spatial variation of ice fabric orientations in the vicinity of the triple junction. The observations are integrated with airborne radar profiles and strain rates based on the shallow ice approximation. We then discuss whether estimated anisotropy from radar polarimetry on ice rises, in general, can be another observational constraint to better ice rises as an archive of ice dynamics.

How to cite: Ershadi, M. R., Drews, R., Tsibulskaya, V., Sun, S., Henry, C., Oraschewski, F., Koch, I., Martin, C., Tison, J.-L., Wauthy, S., Bons, P., Eisen, O., and Pattyn, F.: Ice rise evolution derived from radar investigations at a promontory triple junction, Dronning Maud Land, East Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8197, https://doi.org/10.5194/egusphere-egu23-8197, 2023.

EGU23-9273 | ECS | PICO | CR2.2

Layer-optimized SAR processing with a mobile pRES to illuminate the internal layering of an alpine glacier 

Falk M. Oraschewski, Inka Koch, Mohammadreza Ershadi, Jonathan Hawkins, Olaf Eisen, and Reinhard Drews

The internal, isochronous layering of glaciers is shaped by accumulation and ice deformation. Information about these processes can be inferred from observing the layers using radar sounding. The reflectivity of the layers depends on density (permittivity) and acidity (conductivity) contrasts which tend to decrease with depth. At places like alpine glaciers where logistic limitations often only allow the deployment of lightweight and power-constrained ground-penetrating radar systems, it can therefore be challenging to illuminate the deeper radio-stratigraphy.

The phase-sensitive Radio Echo Sounder (pRES) is a lightweight frequency modulated continuous wave radar which allows the use of coherent Synthetic Aperture Radar (SAR) processing techniques to improve the signal-to-noise ratio of internal reflection horizons. Using a mobile pRES we collected a radar profile on an alpine glacier (Colle Gnifetti, Italy/Switzerland). Here, we demonstrate how to apply layer-optimized SAR techniques to make deep internal layers visible, which could not be seen by a conventional pulsed radar. We evaluate the requirements on spatial resolution and positioning accuracy during data acquisition, necessary for applying layer-optimized SAR processing, as they constrain the feasibility of the method. We further discuss implications on how density and acidity contribute to decreasing dielectric contrasts.

How to cite: Oraschewski, F. M., Koch, I., Ershadi, M., Hawkins, J., Eisen, O., and Drews, R.: Layer-optimized SAR processing with a mobile pRES to illuminate the internal layering of an alpine glacier, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9273, https://doi.org/10.5194/egusphere-egu23-9273, 2023.

EGU23-9619 | ECS | PICO | CR2.2

High-density 3D and 4D GPR data acquisitions over alpine glaciers using a newly developed drone-based system. 

Bastien Ruols, Ludovic Baron, and James Irving

We have developed a drone-based GPR system at the University of Lausanne that allows for the safe and efficient acquisition of large, high-density, 3D and 4D datasets over alpine glaciers. The system is able to record approximately 4 line-km of high-quality GPR data per set of drone batteries in less than 30 minutes of operation which, combined with multiple sets of batteries and/or the possibility of charging at the field site, means that 3D datasets over a large area can be acquired with unprecedented efficiency. The latter performance is possible thanks to (i) a custom-made real-time-sampling GPR controller that has been specifically designed for glaciers studies, (ii) minimization of the total payload weight using custom-built antennas and carbon-fiber components, and (iii) development of an optimized survey methodology. Further, because the drone is equipped with real-time kinematic GPS positioning, survey paths can be repeated with great precision, which opens new opportunities in term of 4D data acquisitions.

In the summer of 2022, we acquired both 3D and 4D data over two Swiss glaciers. On the Otemma glacier, we surveyed a grid of 462 profiles representing a total length of 112 line-km of data in only four days. After 3D binning, the trace spacing intervals in the in-line and crossline directions were respectively 0.4 m and 1 m, making this arguably the largest 3D GPR dataset of such density ever recorded over ice. The interface between the ice and the bedrock, visible on all profiles, extends to 1000 ns which translates into a depth of approximately 80 m. In addition, internal englacial and subglacial 3D structures are clearly detectable.

In parallel, we visited the Rhône glacier on a monthly basis between June and September 2022. A collapse feature, identified by the presence of large circular crevasses, had formed and was evolving close to the snout of the glacier. This represented a great opportunity to test the 4D acquisition capabilities of our system. We collected four high-density 3D datasets on the same survey grid. The repeatability of the trajectories was excellent as the paths differ only by a few centimeters between occurrences. Clear variations in the internal structure of the glacier are visible which will be investigated in the upcoming months.

How to cite: Ruols, B., Baron, L., and Irving, J.: High-density 3D and 4D GPR data acquisitions over alpine glaciers using a newly developed drone-based system., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9619, https://doi.org/10.5194/egusphere-egu23-9619, 2023.

The Whillans Ice Stream (WIS) is a major outlet of the West Antarctic Ice Sheet. Significantly, the downstream portion of the WIS is presently decelerating, possibly stagnating by the end of this century. Additionally, this downstream region of WIS is unique in that it moves primarily by stick-slip motion. However, both the rate of deceleration as well as the percent of motion accommodated by stick-slip motion is spatially variable. Such spatial variability is potentially linked to associated variability in basal conditions. Active source seismic measurement are capable of providing high-resolution insights into basal conditions, however, they are time-consuming to collect, limiting the spatial extent over which they can be acquired. In this presentation, we will use passive seismic measurements collected at over 50 seismic stations to map sediment thickness and ice-bed conditions across the region. This will be done using the receiver function method which images the depth and physical properties of sediments by modeling the arrival times and amplitudes of seismic waves that interact with subglacial sedimentary structures. We will first map conditions at the ice-bed interface by using relatively high-frequency waveforms (> 2 Hz) as they are sensitive to the physical properties of the shallow (< 20m ) subglacial sediments layers. Across the entirety of the study region, we find that this uppermost layer of sediments is characterized by relatively high porosity sediments.  Second, we will utilize lower frequencies (< 2 Hz) to map the depth basement, finding that the entire region is underlain 100’s of meters of sediments (Gustafson et al., Science, 2022). We will use our maps of sediment properties and thickness to investigate potential mechanisms for the observed variability in deceleration and stick-slip behavior of the WIS.  

How to cite: Winberry, J. P.: Basal Conditions and Sedimentary Structure of the Whillans Ice Stream., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9621, https://doi.org/10.5194/egusphere-egu23-9621, 2023.

Englacial temperature and water content play critical roles in glacier dynamics, both within ice sheets and mountain glaciers. As radio wave attenuation is sensitive to both of these properties, radio-echo sounding (RES) serves as a useful tool for mapping out their distributions within glaciers. Ground-based bistatic surveys, in which multi-offset measurements are taken, provide a large diversity in bed incidence angles and travel-path lengths. Provided the anomaly of interest is sufficiently sampled, these measurements can be exploited to perform attenuation tomography, thereby recovering the distribution of englacial radio wave attenuation from which englacial temperature can be estimated. Extensive RES surveys have been carried out over Antarctica using airborne radar; however, due to the monostatic geometry, methods for estimation of englacial radio wave attenuation and basal roughness have relied primarily on nadir returns. These estimates are often derived from 2D spatial correlation of basal return power and ice thickness or by employing layer-tracking methods. These techniques are limited in that the former uses echoes from a large spatial footprint, preventing the detection of small-scale anomalies, while the latter assumes a known, spatially invariant reflectivity for tracked layers. However, by considering returns from off-nadir in airborne surveys, techniques from multi-offset surface surveys can be modified and extended to perform airborne attenuation tomography. While not reaching the range of path diversity achievable in surface-based surveys due to limitations imposed by total internal reflection at the ice-air interface, airborne off-nadir returns contain valuable information about subglacial and englacial conditions that is often ignored. Thus, we propose a method for estimating englacial attenuation and basal roughness using the drop in power from the peak to tail of hyperbolic scattering events in unfocussed radargrams associated with the rough bed surface. The travel-paths of the bed returns across a given hyperbolic event vary in both length and bed incidence angle. Thus, the drop in return power across a hyperbolic event gives insight into both the integrated attenuation along a travel-path, as well as the scattering function at the bed. Specular reflections from internal layers with varying dips similarly provide diversity in travel-path lengths, allowing the derivation of a relationship between path length and return power without the complications brought about by diffuse scattering at rough surfaces. Using the diverse path lengths and angles through the ice, a tomographic inversion to map the spatial distribution englacial attenuation anomalies can be implemented. This technique is applied to synthetic data, as well as data collected using the British Antarctic Survey’s Polarimetric-radar Airborne Science Instrument (PASIN), specifically to lines collected over the Eastern Shear Margin of Thwaites Glacier. This location was chosen as constraining bed conditions and identifying expected englacial thermal anomalies are critical to understanding the history and modelling the future of Thwaites.

How to cite: May, D., Schroeder, D., and Young, T. J.: Radar Attenuation Tomography for Mapping Englacial Temperature Distributions Using Off-Nadir Airborne Radio-Echo Sounding, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9833, https://doi.org/10.5194/egusphere-egu23-9833, 2023.

EGU23-10127 | ECS | PICO | CR2.2

Monitoring lake ice with acoustic sensors 

Christoph Wetter, Cédric Schmelzbach, and Simon C. Stähler

Monitoring of the thickness and elastic parameters of floating ice on lakes and the sea is of interest in understanding the climate change impact on Alpine and Arctic environments, assessing ice safety for recreational and engineering purposes, studying ice shelves as well as exploring possibilities for the future exploration of the icy crusts of ocean worlds in our solar system. A multitude of geophysical methods exist today to monitor sea and lake ice thickness as well as elastic parameters. Mostly, seismic and radar measurements are used. Both methods have in common that they come with significant logistical effort and expensive equipment. In this study, we present a novel low cost approach using acoustic sensors for ice monitoring.

We explored the possibility of using microphones deployed on frozen lakes in the Swiss Alps to monitor the lake ice-thickness using acoustic signals originating from frequently occurring ice quakes. Data were obtained during a three-month-long field campaign at Lake St. Moritz in Switzerland in winter 2021/2022. Three microphone stations were placed on the lake in addition to five conventional seismometers. These seismometers were used to compare the acoustic signals with the seismic ice quake recordings. Additionally, also active-source experiments were conducted using hammer strokes as source, which were used to constrain elastic parameters of the ice.

The acoustic recordings of ice quakes allowed us to exploit the unique characteristics of so-called air-coupled waves to determine time-dependent ice thickness curves of Lake St. Moritz for winter 2021/2022 using acoustic data only. Furthermore, the acoustic data allowed us to gain new insights into the ice/air coupling of seismic waves in ice. 

How to cite: Wetter, C., Schmelzbach, C., and Stähler, S. C.: Monitoring lake ice with acoustic sensors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10127, https://doi.org/10.5194/egusphere-egu23-10127, 2023.

EGU23-11787 | ECS | PICO | CR2.2

Validating manual measurements of snow water equivalent against a reference standard 

Alexander Radlherr and Michael Winkler

The snowpack is a key component in several fields like climatology, hydrology, or natural hazards research and mitigation, not least in mountainous regions. One of the most considerable snowpack features is the snow water equivalent (SWE), representing the mass of water stored in the snowpack and – in another perspective – the weight straining objects the snow is settling on (snow load). In comparison to snow depth, measuring SWE is rather complex and prone to errors. Consecutive observations of SWE do not have a long tradition in many regions.

Despite various recent developments in measuring SWE by means of remote sensing or other noninvasive methods, e.g. with scales, GNSS reflectometry, signal attenuation and time delay techniques, cosmic-ray neutron sensing, etc. the standard measuring technique still are snow tubes or gauging cylinders, often in combination with digging pits. Tubing-technique is commonly used as reference for the validation of named modern methods, although studies addressing its accuracy, precision and repeatability are very rare.

This contribution provides results from comparing different types of SWE measurement tubes with reference standard oberservation. Several field tests were executed at different sites in the Austrian Alps covering a great variety of snow conditions (e.g. dry and wet), snow depths and SWEs. For the reference observation 3x4 m rectangular fields were dug snow-free and the respective snow masses have been weighted stepwise using ca. 50-liter-buckets. Due to the large total mass of snow of typically around two tons per rectangular, relative uncertainties are extremely small and the results highly accurate. Additionally, different snow tubes were compared to each other. The cylinder or tube designs vary a lot: from meters long metal coring tubes of typical inner diameters of ca. 4-7 cm (without the need of pits) or PVC cylinders with typical lengths of 0.5 to 1.5 m and diameters ranging from about 5-20 cm to small aluminum tubes holding a maximum of 0.5 liter of snow.  

Many statistical measures like variance and bias vary quite a lot primarily depending on the equipment used, but also on the different snow conditions. A synopsis on the suitability of the various methods depending on the questioning or objective of the observation is provided.

How to cite: Radlherr, A. and Winkler, M.: Validating manual measurements of snow water equivalent against a reference standard, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11787, https://doi.org/10.5194/egusphere-egu23-11787, 2023.

EGU23-13127 | PICO | CR2.2

Snow depth sensitivity to mean temperature and elevation in the European Alps 

Matthew Switanek, Wolfgang Schöner, and Gernot Resch

Many of the gauged snow depth measurements in the European Alps began in the late 19th and early 20th centuries. We leverage this reasonably long period of record to investigate the historical sensitivity of snow depths as a function of precipitation, mean temperature, and elevation. By controlling for changes in precipitation, we can isolate the influence that different temperature changes have on snow depths at varying elevation bands. This simple, yet effective, approach to defining our historical sensitivity can provide a robust observational framework to evaluate the impact that a range of different future warming scenarios would have on snow depths across the Alps. As a result, adaptation and mitigation measures can be put in place for a variety of end users, such as ski tourism and water resource management. Furthermore, this provides an observational reference by which to evaluate the performance of climate model simulations.

How to cite: Switanek, M., Schöner, W., and Resch, G.: Snow depth sensitivity to mean temperature and elevation in the European Alps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13127, https://doi.org/10.5194/egusphere-egu23-13127, 2023.

EGU23-14390 | ECS | PICO | CR2.2

Long-time permafrost evolution in alpine bedrock: quantifying climate change effects with geoelectrical monitoring 

Riccardo Scandroglio, Maike Offer, and Michael Krautblatter

While climate change driven increase in air temperature has been correctly modeled in recent decades, the extent of its consequences is still uncertain. In high alpine environments, especially in steep rock walls, permafrost degradation reduces slope stability with critical consequences for people and infrastructures: to properly assess the risk, the rate of these changes must be monitored. In the last decades, electrical resistivity tomography (ERT) has been used in more than hundred studies to detect permafrost, but there are only limited long-term monitoring cases that mostly do not provide quantitative information. 

Here we compare ERT measurements from two alpine landforms with different altitude and lithology: Steintälli ridge (3160m asl, CH) and Mt. Zugspitze rock wall (2750 m asl, DE/AT). Standard procedures and permanently installed electrodes allow the collection of a unique dataset of consistent measurements since 2006. Supporting information like resistivity-temperature calibration from former studies, rock surface and borehole temperatures as well as active seismic refraction measurements enable an advanced quantitative interpretation of the results. 

Permafrost at both sites is close to disappearing and in both cases resistivity changes are evident and in good agreement with air temperature increase, although with different magnitudes according to the landform. The yearly 3D measurements of the Steintälli ridge show a sudden and conspicuous degradation (~40% of the volume in 15 years), while the monthly 2D monitoring of the north face of Mt. Zugspitze shows slow constant decrease in summer (~15% of the surface in 15 years) and a strong variation in winter in correlation with snow-height. 

For the first time we provide a quantification of alpine permafrost degradation rates in different landforms over 15 years. These datasets help to better understand the different characteristics of the thermal responses to the climate change induced stress on alpine permafrost environments.

How to cite: Scandroglio, R., Offer, M., and Krautblatter, M.: Long-time permafrost evolution in alpine bedrock: quantifying climate change effects with geoelectrical monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14390, https://doi.org/10.5194/egusphere-egu23-14390, 2023.

EGU23-16308 | ECS | PICO | CR2.2

Thwaites Glacier Eastern Shear Margin: Insights from two broadband seismic arrays 

Emma C. Smith, Marianne Karplus, Jake Walter, Nori Nakata, Adam D. Booth, Lucia Gonzalez, Andrew Pretorius, Ronan Agnew, Stephen Veitch, Eliza J. Dawson, Daniel May, Paul Summers, Tun Jan Young, Poul Christoffersen, and Slawek Tulaczyk

The stability of Thwaites Glacier, the second largest marine ice stream in West Antarctica, is a major source of uncertainty in future predictions of global sea level rise. Critical to understanding the stability of Thwaites Glacier, is understanding the dynamics of the shear margins, which provide important lateral resistance that counters basal weakening associated with ice flow acceleration and forcing at the grounding line. The eastern shear margin is of interest, as it is poorly topographically constrained, meaning it could migrate rapidly, causing further ice flow acceleration and drawing a larger volume of ice into the fast-flowing ice stream. 

We present initial insights from a 2-year-long seismic record, from two broadband seismic arrays each with 7 stations, deployed across the eastern shear margin of Thwaites Glacier. We have applied a variety of processing methods to these data to detect and locate icequakes from different origins and analyse them in the context of shear-margin dynamics. Preliminary results suggest there is basal seismicity concentrated near the ice-bed interface on the slow-moving side of the margin, as opposed to within the ice-stream itself. Some of the identified seismic events appear to exhibit clear shear-wave splitting, suggesting a strong anisotropy in the ice, which would be consistent with polarization observed in recently published radar studies from the field site. Further analysis of the split shear-waves will allow us to better constrain the region's ice-fabric, infer past shear-margin location, and assess the future stability of this ice rheology.  

With such a large quantity of data, manual event identification is unpractical, and hence we are employing machine-learning approaches to identify and locate icequakes of interest in these data. Our results and forthcoming results from upcoming active-seismic field seasons have important implications for better understanding the stability of glacier and ice stream shear margins. 

How to cite: Smith, E. C., Karplus, M., Walter, J., Nakata, N., Booth, A. D., Gonzalez, L., Pretorius, A., Agnew, R., Veitch, S., Dawson, E. J., May, D., Summers, P., Young, T. J., Christoffersen, P., and Tulaczyk, S.: Thwaites Glacier Eastern Shear Margin: Insights from two broadband seismic arrays, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16308, https://doi.org/10.5194/egusphere-egu23-16308, 2023.

EGU23-16342 | PICO | CR2.2

Intercomparison of quantification methods for snow microstructure during the SnowAPP experiment 

Anna Kontu, Leena Leppänen, Roberta Pirazzini, Henna-Reetta Hannula, Juha Lemmetyinen, Petri Räisänen, Amy McFarlane, Pedro Espin Lopez, Kati Anttila, Aleksi Rimali, Hanne Suokanerva, Jianwei Yang, Teruo Aoki, Masashi Niwano, Ghislain Picard, Ines Ollivier, Laurent Arnaud, Margaret Matzl, Ioanna Merkouriad, and Martin Schneebeli

Snow microstructure defines the physical, mechanical and electromagnetic properties of snow. Accurate information of snow structure is needed by many applications, including avalanche forecasting (Hirashima et al., 2008) and numerical weather prediction (de Rosnay et al., 2014). The interaction of electromagnetic waves with snow properties can be applied in satellite remote sensing to retrieve, for example, global information of snow mass (Pulliainen et al., 2020). Objective in-situ observations of snow microstructure are needed to validate and develop both physical models and satellite snow retrieval algorithms. Conventional measurements of snow grain size are unsatisfactory in this regard, as the parameter is difficult to measure objectively, and even its definition is ambiguous (Mätzler, 2002). Hence, recent efforts have focused on developing forward models of microwave interactions and snow specific surface area (SSA), which can be objectively measured in field and laboratory conditions using various methods. A recently proposed approach links SSA to microwave scattering properties through another physically defined parameter (Picard et al., 2022).

In the SnowAPP project, three field campaigns were carried out at the Finnish Meteorological Institute Arctic Research Centre in Sodankylä, with the goal of collecting data on snow microstructural properties and establishing the relation of microstructure to both optical reflectance and microwave emission and scattering from snow.  During the spring 2019 campaign, six different methods were used for measuring SSA; and several methods were used for measuring snow density, another important factor affecting especially the extinction of microwave energy. Furthermore, multi-frequency radiometry and a wide-band, high resolution spectrometer were used to measure microwave emission and reflectance. In this study, we compare objectively the SSA and density values obtained by the different methods in a round-robin exercise. The relation of measured snow microstructures to measured spectral properties of snow are discussed.

SnowAPP was funded by the Academy of Finland, with contributions from WSL Institute for Snow and Avalanche Research SLF, Centre Tecnològic de Telecomunicacions de Catalunya, Beijing Normal University, National Institute for Polar Research, Meteorological Research Institute (Japan), and Université Grenoble Alpes.

 

de Rosnay, P., Balsamo, G., Albergel, C., Muñoz-Sabater, J., & Isaksen, L. (2014). Initialisation of land surface variables for numerical weather prediction. Surveys in Geophysics, 35(3), 607–621. https://doi.org/10.1007/s10712-012-9207-x

Hirashima, H., Nishimura, K., Yamaguchi, S., Sato, A., & Lehning, M. (2008). Avalanche forecasting in a heavy snowfall area using the snowpack model. Cold Regions Science and Technology, 51(2–3), 191–203. https://doi.org/10.1016/j.coldregions.2007.05.013

Mätzler, C., 2002. Relation between grain-size and correlation length of snow. J. Glaciol., (48)162: 461-466.

Picard, G., Löwe, H., Domine, F., Arnaud, L., Larue, F., Favier, V., & Meur, E. le. (2022). The Microwave Snow Grain Size: A New Concept to Predict Satellite Observations Over Snow-Covered Regions. https://doi.org/10.1029/2021AV000630

Pulliainen, J., Luojus, K., Derksen, C., Mudryk, L., Lemmetyinen, J., Salminen, M., Ikonen, J., Takala, M., Cohen, J., Smolander, T., & Norberg, J. (2020). Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018. Nature, 581(7808), 294–298. https://doi.org/10.1038/s41586-020-2258-0

 

How to cite: Kontu, A., Leppänen, L., Pirazzini, R., Hannula, H.-R., Lemmetyinen, J., Räisänen, P., McFarlane, A., Espin Lopez, P., Anttila, K., Rimali, A., Suokanerva, H., Yang, J., Aoki, T., Niwano, M., Picard, G., Ollivier, I., Arnaud, L., Matzl, M., Merkouriad, I., and Schneebeli, M.: Intercomparison of quantification methods for snow microstructure during the SnowAPP experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16342, https://doi.org/10.5194/egusphere-egu23-16342, 2023.

EGU23-16522 | ECS | PICO | CR2.2

Resolving ice content heterogeneity within permafrost peatlands using high-frequency induced polarisation. 

Madhuri Gopaldas Sugand, Andreas Hördt, and Andrew Binley

Permafrost peatlands are highly vulnerable ecosystems in a warming climate; their thaw greatly impacts carbon storage capacity and endangers existing landscape morphology. Due to their remoteness and, in some cases, protected status, it is difficult to characterise and monitor the subsurface using invasive methods. Geophysical investigations are useful in such cases allowing relatively rapid and extensive subsurface mapping. We focus here on the emerging high-frequency induced polarisation (HFIP) method, which can be effective in permafrost hydrology research as the geoelectrical properties of frozen water display a characteristic frequency-dependence between ranges of 100 Hz and 100 kHz.

HFIP field measurements were conducted using the Chameleon-II equipment (Radic Research) on two peat permafrost sites located in Abisko, Northern Sweden: Storflaket mire and Heliport mire. The sites have been subject to routine permafrost monitoring since 1978 and are known to have an upper peat layer underlain by a silt-rich subsoil. We present the results of 2D surveys measuring frequencies ranging from 1 Hz to 57 kHz, which capture a high-frequency phase shift peak. Field data are inverted for each measured frequency separately with ResIPy, using an appropriate data error quantification model. The spectral data analysis captures heterogeneity within the subsurface, i.e., layered medium, permafrost mire boundary and ice-rich versus ice-poor regions. Identification of spectrally distinct regions allows the application of an appropriate relaxation model. For this study, we apply a two-component mixture model for ice-content estimation. Our results extend the existing knowledge at this site by quantifying ice content in a 2D plane, thus improving the foundation for further modelling studies.

How to cite: Sugand, M. G., Hördt, A., and Binley, A.: Resolving ice content heterogeneity within permafrost peatlands using high-frequency induced polarisation., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16522, https://doi.org/10.5194/egusphere-egu23-16522, 2023.

EGU23-798 | ECS | Posters on site | ST2.4

Investigating the acceleration efficiency of VLF and ULF waves on different electron populations in the outer radiation belt through multi-point observations and modeling 

Afroditi Nasi, Christos Katsavrias, Sigiava Aminalragia-Giamini, Nour Dahmen, Antoine Brunet, Constantinos Papadimitriou, Ingmar Sandberg, Sébastien Bourdarie, Viviane Pierrard, Edith Botek, Fabien Darrouzet, Ondrej Santolik, Benjamin Grison, Ivana Kolmasova, David Pisa, Yoshizumi Miyoshi, Wen Li, Hugh Evans, and Ioannis A. Daglis and the Arase Team

During the second half of 2019, the Earth’s magnetosphere was impacted by a sequence of Corotating Interaction Regions (CIRs) during four consecutive solar rotations. Based on the solar wind properties, the CIRs can be divided in four groups, with the 3rd group, which arrived on August-September 2019, resulting in significant multi-MeV electron enhancements, up to ultra-relativistic energies of 9.9 MeV.

Each CIR group has a different effect on the outer radiation belt electron populations; we investigate them by exploiting combined measurements from the Van Allen Probes, THEMIS, and Arase satellites. We produce Phase Space Density (PSD) radial profiles and inspect their dependence on the values of the first and second adiabatic invariants (μ,K), ranging from seed to ultra-relativistic electrons and from near-equatorial to off equatorial mirroring populations, respectively.

Focusing on the 3rd CIR group, and in order to assess the relative contribution of radial diffusion and gyro-resonant acceleration, we perform numerical simulations of the radiation belt environment, combining several relevant models: EMERALD (NKUA), GEO model (NKUA), Salammbô (ONERA), VLF model (IAP), Plasmaspheric model (BIRA-IASB), FARWEST (ONERA). We further compare the temporal evolution of the simulated electron PSD with the above observations.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 for the SafeSpace project.

How to cite: Nasi, A., Katsavrias, C., Aminalragia-Giamini, S., Dahmen, N., Brunet, A., Papadimitriou, C., Sandberg, I., Bourdarie, S., Pierrard, V., Botek, E., Darrouzet, F., Santolik, O., Grison, B., Kolmasova, I., Pisa, D., Miyoshi, Y., Li, W., Evans, H., and Daglis, I. A. and the Arase Team: Investigating the acceleration efficiency of VLF and ULF waves on different electron populations in the outer radiation belt through multi-point observations and modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-798, https://doi.org/10.5194/egusphere-egu23-798, 2023.

Atmospheric precipitation of radiation belt electrons plays an important role in the magnetosphere-ionosphere-atmosphere coupling system, which can trigger chemical and electric effects in the upper atmosphere and meanwhile generate aurorae of various types. In the regime of the quasi-linear theory, it is commonly accepted that the population of trapped electrons is no smaller than the precipitated population. However, such a concept has been proved to break down due to the nonlinear wave-particle interactions, which can drive the superfast electron precipitation. Therefore, on basis of the long-term MEPED datasets of POES satellites, we perform a comprehensive analysis of the spatiotemporal characteristics and geomagnetic dependence of superfast radiation belt electron precipitation. Our results demonstrate that superfast atmospheric precipitation of energetic electrons occurs with a non-negligible percentage with respect to the overall electron precipitation observations, and has the geomagnetic dependence similar to that of whistler-mode chorus waves.

How to cite: Guo, D., Xiang, Z., and Ni, B.: A statistical study of superfast atmospheric precipitation of radiation belt electrons observed by POES satellites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3069, https://doi.org/10.5194/egusphere-egu23-3069, 2023.

EGU23-3134 | ECS | Posters on site | ST2.4

Simultaneous observations of whistler mode waves by the DEMETER spacecraft and the Kannuslehto station 

Kristyna Drastichova, František Němec, Jyrki Manninen, and Michel Parrot

We use conjugate observations of magnetospheric whistler mode electromagnetic waves at frequencies up to 16 kHz to determine their typical spatial scales and propagation to the ground. For this purpose, we use data obtained by the DEMETER spacecraft at an altitude of about 700 km and by the ground-based Kannuslehto station in Finland. The overlap between the two data sets corresponds to more than 500 DEMETER half-orbits between November 2006 and March 2008. Two different approaches are used. First, specific wave events observed simultaneously by both the spacecraft and the ground station are analyzed in detail. Second, the correlations of the power spectral densities of measured signals are calculated as a function of the frequency and geomagnetic longitude/L-shell separation. These are used to determine typical longitudinal/L-shell correlation lengths and to discuss wave propagation to the ground.

How to cite: Drastichova, K., Němec, F., Manninen, J., and Parrot, M.: Simultaneous observations of whistler mode waves by the DEMETER spacecraft and the Kannuslehto station, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3134, https://doi.org/10.5194/egusphere-egu23-3134, 2023.

EGU23-3188 | Orals | ST2.4

Line radiation events: Properties, generation, and propagation 

Frantisek Nemec, Ondřej Santolík, Jyrki Manninen, George B. Hospodarsky, and William S. Kurth

Whistler-mode waves propagating in the Earth’s inner magnetosphere sometimes appear as a set of nearly constant frequency elements separated by a fixed frequency. Such events are typically called line radiation, and they can have two distinct origins. First, events with narrow spectral lines and the frequency spacing corresponding to the base power system frequency (50/100 or 60/120 Hz) are generated by electromagnetic radiation from electric power systems on the ground (power line harmonic radiation, PLHR). Second, waves with broader spectral lines, whose frequency spacing does not correspond to the power system frequency, are believed to be generated by plasma instabilities in the magnetosphere (magnetospheric line radiation, MLR).

Frequencies of line radiation events are typically on the order of a few kHz, while their frequency spacing is on the order of a hundred Hz. Relevant spacecraft observations at larger radial distances are thus very sparse due to the typically low frequency resolution of available measurements, not sufficient to distinguish the line structure. We use high-resolution multicomponent wave measurements performed by the EMFISIS instrument on board the Van Allen Probes during the burst mode to fill this observational gap. We systematically identify the line radiation events and analyze their occurrence and properties. Detailed wave propagation analysis allows us to reveal wave propagation throughout the magnetosphere. We further show that the frequency spacing of MLR events appears to be related to an electrostatic wave observed at the corresponding frequency (≈100 Hz). Finally, conjugate observations performed by the Kannuslehto station in Finland are used to estimate the spatial extent of the events.

How to cite: Nemec, F., Santolík, O., Manninen, J., Hospodarsky, G. B., and Kurth, W. S.: Line radiation events: Properties, generation, and propagation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3188, https://doi.org/10.5194/egusphere-egu23-3188, 2023.

Whistler-Mode Chorus (WMC) waves are an important contributor to the dynamics of the magnetosphere, not only for their prevalence in measured observations of near-Earth space but also for their dominant role in transporting energy and particles throughout it. It is therefore of key importance to space weather modelling that we understand how WMC waves are generated, how they subsequently evolve and how they interact with the particle populations that they transport. There are also fundamental physics question to answer as WMC waves display nonlinear phenomena rarely seen in other fields, including their ability to raise and lower their frequency repeatedly and rapidly leading to rising and falling tone waves respectively. Are the interactions between the wave and the particles driving such phenomena, and if so to what degree are they doing so?

 

In this talk, we revisit the nonlinear evolution of WMC waves from a theoretical perspective.  Wave-particle interactions are shown to be a key driver of the modulational instabilities that lead to element and subelement formation which are well represented by an extension of the well-known Nonlinear Schrodinger equation. Simulations of this yields power spectrum reminiscent of the rising and falling tone emissions observed in mission data from the Van Allen probes, THEMIS, MMS and Cluster and determines that that wave-particle interactions are the primary cause of this effect. As a result, this nonlinear theory indicates regimes in which these frequency sweeps can be enhanced or dampened, and suggests why the WMC band gap at half the gyrofrequency exists.

How to cite: Ratliff, D. and Allanson, O.: Nonlinear wave-particle interactions in Whistler-Mode Chorus waves: modulation as a route to rising and falling tones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3375, https://doi.org/10.5194/egusphere-egu23-3375, 2023.

EGU23-3445 | Orals | ST2.4

Global modeling of the mesoscale buildup of the ring current and its role in magnetosphere-ionosphere coupling 

Kareem Sorathia, Adam Michael, Anthony Sciola, Shanshan Bao, Dong Lin, Slava Merkin, Sasha Ukhorskiy, Constanze Roedig, and Jeffrey Garretson

During geomagnetically active periods plasma is transported from the magnetotail into the inner magnetosphere to become the ring current. The transpot of plasma into the ring current occurs at different spatial and temporal scales, from global quasi-steady convection to bursty bulk flows (BBFs), with typical cross-tail extents of 1-3 Earth radii. During its enhancement, the ring current plays a critical role in magnetosphere-ionosphere coupling. Ring current ions build up plasma pressure in the inner magnetosphere and will drive field-aligned currents which must close in the ionosphere, while electrons will lead to diffuse precipitation and enhanced ionospheric conductance which shape the ionospheric path of current closure. Current closure in the ionosphere will couple to the thermospheric neutral population, via Joule heating, and alter the dynamics of the plasmasphere, via the penetration electric field in the inner magnetosphere. 

Understanding the relative role of convection at different spatial scales in both the buildup of the ring current and its broader effects on geospace coupling is an area of active interest and one of the core science questions of the Center for Geospace Storms. In this talk I will describe how addressing this question has informed the development of the Multiscale Atmosphere Geospace Environment (MAGE) model and highlight several recent modeling studies which illustrate the central role of mesoscale processes.

How to cite: Sorathia, K., Michael, A., Sciola, A., Bao, S., Lin, D., Merkin, S., Ukhorskiy, S., Roedig, C., and Garretson, J.: Global modeling of the mesoscale buildup of the ring current and its role in magnetosphere-ionosphere coupling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3445, https://doi.org/10.5194/egusphere-egu23-3445, 2023.

EGU23-3482 | Orals | ST2.4

The controlling effect of the cold plasma density over the acceleration and loss of ultra‐relativistic electrons 

Yuri Shprits, Hayley Allison, Alexander Drozdov, and Dedong Wang

Novel analysis of phase space densities at multiple energies allows for differentiation between various acceleration mechanisms at ultra‐relativistic energies. This method allows us to trace how particles are being accelerated at different energies and show how long it takes for acceleration to reach particular energy. This method clearly demonstrates the importance of local acceleration and also demonstrates the importance of outward radial diffusion in transporting electrons to GEO.

Acceleration to such high energies occurs only when cold plasma in the trough region is extremely depleted, down to the values typical for the plasma sheet. We perform event and statistical analysis of these depletions and show that the ultra‐relativistic energies are reached for each such depletion that is accompanied by the intensification of ~2MeV. VERB‐2D simulations are then used to explain these observations. There is also a clear difference between the loss mechanisms at MeV and multi‐MeV energies due to EMIC waves that can very efficiently scatter ultra‐relativistic electrons but leave MeV electrons unaffected.

Modelling and observations clearly show that cold plasma has a controlling effect over the ultra‐ relativistic electrons that are 10^6‐10^7 times more energetic. We also present how the new understanding gained from the Van Allen Probes mission can be used to produce the most accurate data assimilative forecast. Under the recently funded EU Horizon 2020 Project Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) we study how ensemble forecasting from the Sun can produce long‐term probabilistic forecasts of the radiation environment in the inner magnetosphere.

How to cite: Shprits, Y., Allison, H., Drozdov, A., and Wang, D.: The controlling effect of the cold plasma density over the acceleration and loss of ultra‐relativistic electrons, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3482, https://doi.org/10.5194/egusphere-egu23-3482, 2023.

EGU23-4064 | ECS | Orals | ST2.4

Archimedean Spiral Distribution of Electrons in Earth Inner Magnetosphere 

Weiqin Sun, Jian Yang, Wenrui Wang, and Jun Cui

We present an analytic theory to demonstrate that electrons with an initially asymmetric spatial distribution would form an Archimedean spiral distribution in the inner magnetosphere. Such evolution is a result of the gradient/curvature drift, whose angular velocity decreases with radial distance. It has been known for a long time that spectrograms of energetic electrons in Earth's inner radiation belt exhibit time-varying organized peaks and valleys. Recent observations from Van Allen Probes have shown that such regular patterns are ubiquitous and are referred to as “zebra stripes”. Our theory can predict zebra stripes accurately. We also use the Rice Convection Model (RCM) to simulate zebra stripes. For the simplest situation with the dipolar magnetic field model, the analytic theory perfectly matches with the RCM simulation. In a realistic simulation, the RCM reproduces the time-dependent structures and evolution of the zebra stripes, which are in good consistency with Van Allen Probes observations.

How to cite: Sun, W., Yang, J., Wang, W., and Cui, J.: Archimedean Spiral Distribution of Electrons in Earth Inner Magnetosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4064, https://doi.org/10.5194/egusphere-egu23-4064, 2023.

EGU23-4471 | Orals | ST2.4

Quantifying the Contribution of Nonlinear Resonant Effects to Diffusion Rates 

Dmitri Vainchtein, Anton Artemyev, Didier Mourenas, and Xiaojia Zhang

The wave-particle resonant interaction is a key process controlling energetic electron flux dynamics in the Earth’s radiation belts. All existing radiation belt codes are Fokker-Planck models relying on the quasi-linear diffusion theory to describe the impact of wave-particle interactions. However, in the outer radiation belt, spacecraft often detect waves sufficiently intense to interact resonantly with electrons in the nonlinear regime.

We propose an approach to (1) estimate the contribution of such nonlinear resonant interactions, and (2) include them into diffusion-based radiation belt models. Using statistics of chorus wave-packet amplitudes and sizes (number of wave periods within one packet), we provide a rescaling factor for the quasi-linear diffusion rates to account for the contribution of nonlinear interactions in long-term electron flux dynamics. Such nonlinear effects may speed up 0.1-1 MeV electron diffusive acceleration by a factor of x2-3 during disturbed periods.

How to cite: Vainchtein, D., Artemyev, A., Mourenas, D., and Zhang, X.: Quantifying the Contribution of Nonlinear Resonant Effects to Diffusion Rates, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4471, https://doi.org/10.5194/egusphere-egu23-4471, 2023.

Space plasmas are often characterized by non-thermal particle distributions that are generally characterized by a high-energy tail that follows a power law for large velocity arguments. For modelling purposes, these are often described by kappa-type distributions (Livadiotis, 2017). Over the past few decades, the kappa distribution has been adopted in interpretations of observations in various space plasma contexts including the solar wind (Chotoo et al., 2000), planetary magnetospheres (Collier and Hamilton, 1995), the outer heliosphere (Decker and Krimigis, 2003) and the inner heliosheath (Livadiotis and McComas, 2012) and also in theoretical models (Hellberg et al., 2009). An abundance of data from the Cassini and Voyager missions has established in Saturn's magnetosphere the coexistence of non-thermal electron populations (of different characteristics). Schippers et al. (2008) analysed the radial distribution of electron populations in Saturn's magnetosphere by using an ad hoc two-kappa model, thus establishing the relevance of multi-kappa models with respect to electron populations in Saturn's magnetosphere. This coexistence of electron clouds (at distinct temperatures) is a key element in our work.

Electrostatic Solitary Waves (ESWs), generally associated with bipolar electric field waveforms observed alongside propagating density disturbances, are known to occur in Saturn's magnetosphere (Pickett et al., 2015). In this study, we have relied on a multi-fluid plasma model to investigate the significance of suprathermal electron populations in determining the characteristics of different types of solitary wave solutions. Our investigation reveals that the spectral index (i.e. the  parameter value related to the cold electron population mainly) is crucial in explaining the difference among different types of nonlinear structures. A comparison with spacecraft observations suggests that our theoretical estimations may be relevant in the interpretation of ESW observations in Saturn's magnetosphere.

References

Chotoo, K., Schwadron, N.A., Mason, G.M., Zurbuchen, T.H., Gloeckler, G., Posner, A., Fisk, L.A., Galvin, A.B., Hamilton, D.C., Collier, M.R., 2000. J. Geophys. Res. Space Phys. 105, 23107–23122. https://doi.org/10.1029/1998JA000015

 

Collier, M.R., Hamilton, D.C., 1995. Geophys. Res. Lett. 22, 303–306. https://doi.org/10.1029/94GL02997

 

Decker, R.B., Krimigis, S.M., 2003. Adv. Space Res. 32, 597–602. https://doi.org/10.1016/S0273-1177(03)00356-9

 

Hellberg, M.A., Mace, R.L., Baluku, T.K., Kourakis, I. and Saini, N.S., 2009. Physics of Plasmas, 16(9), p.094701

 

Livadiotis, G., 2017. Kappa Distributions - Theory and Applications in Plasmas (Elsevier).

 

Livadiotis, G., McComas, D.J., 2012. Astrophys. J. 749, 11. https://doi.org/10.1088/0004-637X/749/1/11

 

Pickett, J.S., Kurth, W.S., Gurnett, D.A., Huff, R.L., Faden, J.B., Averkamp, T.F., Píša, D. and Jones, G.H., 2015. Journal of Geophysical Research: Space Physics120(8), pp.6569-6580.

 

Schippers, P., Blanc, M., André, N., Dandouras, I., Lewis, G.R., Gilbert, L.K., Persoon, A.M., Krupp, N., Gurnett, D.A., Coates, A.J., Krimigis, S.M., Young, D.T., Dougherty, M.K., 2008. J. Geophys. Res. Space Phys. 113, https://doi.org/10.1029/2008JA013098

 

 

How to cite: Varghese, S. S. and Kourakis, I.: On the role of suprathermal electrons on the characteristics of electrostatic solitary waves in Saturn’s magnetosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4797, https://doi.org/10.5194/egusphere-egu23-4797, 2023.

EGU23-5059 | ECS | Orals | ST2.4

Nightside plasmaspheric plume-to-core migration of whistler-mode hiss waves 

Zhiyong Wu, Zhenpeng Su, Jerry Goldstein, Nigang Liu, Zhaoguo He, Huinan Zheng, and Yuming Wang

Whistler-mode hiss waves play an important role in the radiation belt electron depletion. Whether the hiss waves with significant differences in amplitude and propagation direction within the plasmaspheric core and plume are related to each other remains unclear. We here show that the plasmaspheric plume facilitates the energy conversion from energetic electrons to hiss waves and then guides hiss waves into the plasmaspheric core. Three ground and space missions captured the initial formation and subsequent rotation of the plasmaspheric plume in the noon-dusk-midnight sector following a strong substorm. The observed hiss waves in the nightside plasmaspheric plume and core propagated oppositely but highly correlated with each other at a time lag of 4-10 s. The linear instability of energetic electrons in the plasmaspheric plume qualitatively explains the frequency-dependence of hiss waves, and the ray-tracing modeling reproduces the propagation direction and timing of hiss waves.

How to cite: Wu, Z., Su, Z., Goldstein, J., Liu, N., He, Z., Zheng, H., and Wang, Y.: Nightside plasmaspheric plume-to-core migration of whistler-mode hiss waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5059, https://doi.org/10.5194/egusphere-egu23-5059, 2023.

EGU23-7338 | ECS | Posters on site | ST2.4

A number density/temperature description of the Earth’s outer radiation belt 

Dovile Rasinskaite

Substorms can inject electrons of energies ranging from 10s to 100s keV (often called source and seed populations) into the magnetosphere which can be accelerated to relativistic energies and be harmful to space-based infrastructure. Here we present a number density/temperature description of the Earths outer radiation belt obtained by using omni-directional flux and energy measurements from the HOPE and MagEIS instruments from the Van Allen Probe mission. This dataset provides a comprehensive statistical study of the whole Van Allen probe era. Values of number density and temperature are extracted by fitting energy and phase space density in log space to find the distribution function. Zeroth and second moments are taken respectively of the distribution function to find the number density and temperature. A number density/ temperature description is advantageous over an energy/flux description as it allows to differentiate between the transport and heating of electrons. The shape and variation of plasma distributions is also discussed, and general statistical properties presented. The relative importance of transport and heating is also discussed. We will explore the classification of substorm injections (i.e., is the injection a heating or transport of electrons, or a combination of both) and this technique can be extended across more energy ranges. 

How to cite: Rasinskaite, D.: A number density/temperature description of the Earth’s outer radiation belt, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7338, https://doi.org/10.5194/egusphere-egu23-7338, 2023.

EGU23-7524 | Orals | ST2.4

An Empirical Model of Whistler Mode Waves in the Radiation Belt Region 

Ondrej Santolik, Ivana Kolmasova, Ulrich Taubenschuss, Marie Turcicova, and Miroslav Hanzelka

Whistler mode waves interact with different magnetospheric particle populations in the inner magnetosphere and significantly influence particle fluxes in the Earth's radiation belts. Using recently acquired large databases of spacecraft measurements from the Van Allen Probes and Cluster missions we construct new empirical models of whistler mode waves in the inner magnetosphere. We pay special attention to the off-equatorial region, which is often under-sampled in the currently existing models, and to the inter-calibration of data from different spacecraft missions. We take into account the effects of instrumental noise and other artifacts which influence the quality of data at the input of the modeling procedure. Our results show that dawn chorus occurs most often around noon, while its peak average amplitudes are observed during the local night. We also show that off-equatorial plasmaspheric hiss has a strong obliquely propagating component. We further confirm the influence of low plasma density regions on the intensity of chorus.

How to cite: Santolik, O., Kolmasova, I., Taubenschuss, U., Turcicova, M., and Hanzelka, M.: An Empirical Model of Whistler Mode Waves in the Radiation Belt Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7524, https://doi.org/10.5194/egusphere-egu23-7524, 2023.

EGU23-7785 | Orals | ST2.4

The Angular Distribution of Whistler-Mode Chorus Wave Vector Directions from Van Allen Probes and MMS Observations 

David P. Hartley, Ivar Christopher, Lunjin Chen, Ondrej Santolik, Craig Kletzing, Matthew Argall, and Narges Ahmadi

The dynamics of Earth's outer electron radiation belt is, in part, driven by interactions with whistler-mode chorus waves.  Chorus can cause rapid acceleration of electrons up to relativistic energies, as well as drive precipitation of particles into the atmosphere causing both microbursts and diffuse aurora.  Chorus can propagate in such a way that it crosses the plasmapause boundary and may contribute to the possible sources of plasmaspheric hiss, which itself can cause atmospheric losses of particles and the formation of the slot region between the inner and outer radiation belts.  The direction of the wave vector relative to the background magnetic field is a key parameter for quantifying these processes, since it determines the propagation trajectory of the wave, and is required for calculating the resonance condition of the wave-particle interaction.

The orientation of the wave vector is investigated using both survey mode data and high-resolution burst mode observations from the EMFISIS Waves instrument on the Van Allen Probes spacecraft.  Spatial coverage beyond the Van Allen Probes orbit is provided by burst-mode observations from the FIELDS instrument suite on Magnetospheric Multiscale (MMS).  The polar and azimuthal wave vector angles are considered using both spectral analysis, where the frequency-time structure can be resolved, and instantaneous values, which can be used to identify variations within individual chorus subpackets.  We compare the results from each of these different timescales.  Near strong plasma density gradients, such as those which occur on the boundaries of plasmaspheric plumes, we identify that the wave vector becomes more oblique than the general case where no density gradients are present.  The obliquity of the wave vector is shown to directly relate to both the magnitude of the density gradient, and its proximity to the spacecraft.  

How to cite: Hartley, D. P., Christopher, I., Chen, L., Santolik, O., Kletzing, C., Argall, M., and Ahmadi, N.: The Angular Distribution of Whistler-Mode Chorus Wave Vector Directions from Van Allen Probes and MMS Observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7785, https://doi.org/10.5194/egusphere-egu23-7785, 2023.

EGU23-8042 | ECS | Posters on site | ST2.4

Impact of interplanetary shocks on the radiation belt environment measured by a low altitude satellite 

Stefan Gohl and František Němec

We use electron flux data measured by the Energetic Particle Telescope (EPT) onboard the Proba-V satellite in a Low Earth Orbit (LEO) to investigate the radiation belt response to the interplanetary shock arrival. Altogether, as many as 31 interplanetary shocks selected from the OMNI data during 2013-2018 are investigated. While the radiation belt fluxes are nearly unaffected by the shock arrival in some cases, other events reveal a sudden drop of energetic electron fluxes spanning over a broad range of L-shells. Electron flux changes at various L-shells and energies are evaluated and compared with the solar wind dynamic pressure change across the shock front, magnetopause location, and z-component of the interplanetary magnetic field. The aim is to identify parameters governing the radiation belt response to the interplanetary shock passage and to understand the strikingly different responses to the seemingly similar solar wind variations.

How to cite: Gohl, S. and Němec, F.: Impact of interplanetary shocks on the radiation belt environment measured by a low altitude satellite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8042, https://doi.org/10.5194/egusphere-egu23-8042, 2023.

EGU23-8693 | Orals | ST2.4

Observations and Analysis of Deep Penetrations of MeV Electrons from REPT PHA Data 

Xinlin Li, Declan O'Brien, and Daniel Baker

The Relativistic Electron and Proton Telescope (REPT), consisting of a stack of nine aligned silicon detectors onboard Van Allen Probes, has contributed a great number of discoveries based its nominal data. However, the REPT Pulse Height Analysis (PHA) data set, which was taken every 12 milliseconds (ms), including the pulse height that is proportional to the energy deposit of each individual particle from all nine REPT detectors, has been seldom-tapped. Here we show that this data set actually provides higher energy resolution particle measurements than the typical binned data from REPT. Geant4 simulations are used to extend and improve the electron detecting capabilities of REPT using the PHA data. After replicating the nominal characteristics of REPT in the Geant4 toolbox, new channels for REPT, going from 12 electron channels to 47 and lowering the minimum energy to ~1 MeV, have been formulated. The deep storm-time penetration of MeV electrons into the slot region (2<L<3) and inner belt (L<2) has been investigated. Clear dynamic variations of MeV electrons in these regions are revealed and substantiated by quantitative analysis. This is only an example of how the REPT PHA data will enable us to quantitatively address many more various science questions.

How to cite: Li, X., O'Brien, D., and Baker, D.: Observations and Analysis of Deep Penetrations of MeV Electrons from REPT PHA Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8693, https://doi.org/10.5194/egusphere-egu23-8693, 2023.

EGU23-8906 | ECS | Orals | ST2.4

Impact of the solar activity on the non-linearity of the statistical dependency between solar wind and the inner magnetosphere 

Sanni Hoilijoki, Veera Lipsanen, Adnane Osmane, Milla Kalliokoski, Harriet George, Lucile Turc, and Emilia Kilpua

Solar wind variations and transients are the main driver of the dynamics of the Earth’s magnetosphere. Interplanetary coronal mass ejections (ICME) cause the largest variations in the near-Earth space, but significant geomagnetic activity can also be driven by high-speed streams (HSSs) and stream interaction regions (SIRs). Solar wind – magnetosphere interactions drive fluctuations in the inner magnetosphere and impact the electrons in the outer radiation belt. Ultra low frequency (ULF) waves in the Pc5 range (2-7mHz) can accelerate electrons in the inner magnetosphere via drift resonance and cause changes in the electron flux up to several orders of magnitude. The different solar wind structures, ICMEs and HSSs/SIRs have been found to have different impact on the ULF waves and electrons in the inner magnetosphere. In this study we use mutual information from information theory to study the statistical dependency of the ULF waves and radiation belt electrons on the solar wind parameters and fluctuations over the solar cycle 23. Unlike Pearson correlation coefficient mutual information can also be used to investigate non-linear statistical dependencies between different parameters. We calculate correlation coefficients separately for each year and find that the non-linearity between the solar wind parameters and some magnetospheric parameters is higher during solar maximum when most of the geomagnetic activity is driven by ICMEs, while the non-linearity decreases during the declining phase, as larger portion of the geomagnetic activity is driven by HSSs and SIRs. To investigate further if the change of the ratio of ICMEs and HSSs is the possible cause of the changes in the non-linearity during the solar cycle, we calculate the correlation coefficients separately during ICMEs, HSSs/SIRs and quiet solar wind.

How to cite: Hoilijoki, S., Lipsanen, V., Osmane, A., Kalliokoski, M., George, H., Turc, L., and Kilpua, E.: Impact of the solar activity on the non-linearity of the statistical dependency between solar wind and the inner magnetosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8906, https://doi.org/10.5194/egusphere-egu23-8906, 2023.

EGU23-8925 | ECS | Orals | ST2.4

Radiation belt particle diffusion, drift and advection via cyclotron interactions 

Oliver Allanson, Jacob Bortnik, Donglai Ma, Adnane Osmane, and Jay Albert

There is a growing body of observational, theoretical and experimental evidence to indicate that a proper description of radiation belt charged particle transport will require new mathematical models, i.e. new partial differential equations. One leading candidate is to extend the ‘standard diffusion equation’ to a more general Fokker-Planck equation in order to include advection coefficients. Ideally, these advection (first-order transport) coefficients should be parameterized by plasma and VLF/ELF electromagnetic wave parameters in a similar manner to that used for the diffusion coefficients. To the authors' knowledge, this goal has not yet been achieved - at least not to obtain an equation that can be/has been implemented into operational global scale numerical models.

In general, advection coefficients are in fact a combination of both ‘drift coefficients’ and derivatives of the diffusion coefficients. In the standard quasilinear formalism, this combination produces advection coefficients that are identically zero because of specific constraints imposed via the Hamiltonian structure, with a derivation often attributed to Landau/Lichtenberg & Lieberman [1].

In this paper [2] we present a new theory that incorporates and builds upon the ‘weak turbulence/quasilinear results’ of [3,4] and demonstrates the breaking of the ‘Landau-Lichtenberg-Liebermann condition’ for the case of high wave amplitudes, or equivalently small timescales.

We therefore obtain:
(i) the standard quasilinear results for small wave amplitudes and long timescales;
(ii) and non-zero advection coefficients - as well as diffusion coefficients - that are valid for short timescales (high wave amplitudes).

These limiting timescales are determined by the electromagnetic wave amplitude. This also demonstrates that one can use what may be considered ‘quasilinear methods’ to obtain interesting new results for ‘nonlinear/high-amplitude’ waves in radiation belt modelling. We verify the results using high-performance test-particle experiments.

References

[1] A.J. Lichtenberg, and M.A. Lieberman, “Regular and Chaotic Dynamics”, 2nd Ed., Springer, 1991

[2] O. Allanson et al (in prep)

[3] D.S. Lemons, PoP, 19, 012306, 2012

[4] O. Allanson, T. Elsden, C. Watt, and T. Neukirch, Frontiers Aston. Space Sci., 8:805699, 2022

How to cite: Allanson, O., Bortnik, J., Ma, D., Osmane, A., and Albert, J.: Radiation belt particle diffusion, drift and advection via cyclotron interactions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8925, https://doi.org/10.5194/egusphere-egu23-8925, 2023.

EGU23-9976 | ECS | Orals | ST2.4

Using pitch angle index to quantify anisotropies in the outer radiation belt 

Ashley Greeley, Shrikanth Kanekal, and Quintin Schiller

Changes in pitch angle distributions can be a useful indicator of various changes in the radiation belts. Many methods of observing pitch angle distributions are qualitative. We present a method of studying pitch angle distributions that allows for a quantitative analysis of pitch angle distributions over time and energy channels, which allows for closer monitoring of spatial and temporal changes in the radiation belts. We use Van Allen Probes data from both spacecraft in fit pitch angle distributions with the form J0sinnα, tracking ‘n’ over time. We use this method of tracking pitch angle distributions to establish a connection between very localized wave particle interactions and particle scattering.

How to cite: Greeley, A., Kanekal, S., and Schiller, Q.: Using pitch angle index to quantify anisotropies in the outer radiation belt, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9976, https://doi.org/10.5194/egusphere-egu23-9976, 2023.

EGU23-10180 | Orals | ST2.4

Characteristic Times for Radiation Belt Drift Phase Mixing 

Solène Lejosne and Jay M. Albert

One of the key assumptions of radiation belt modeling based on a three-dimensional Fokker-Planck equation is that trapped particle fluxes do not depend on the drift phase (i.e., the azimuthal angle, or magnetic local time, MLT). It is usually considered that MLT-dependent structures (such as particle injection signatures and subsequent drift echoes) are rapidly smoothed out by drift phase mixing. Yet, the characteristic times for radiation belt drift phase mixing are not well known.

In this presentation, we show the existence of a naturally occurring phase mixing process in the presence of field fluctuations. This process complements the observational phase mixing due to the finite resolution of the measuring instrument.

We present a first quantification for the characteristic time of natural phase mixing and we discuss the implications in terms of radiation belt modeling.

How to cite: Lejosne, S. and Albert, J. M.: Characteristic Times for Radiation Belt Drift Phase Mixing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10180, https://doi.org/10.5194/egusphere-egu23-10180, 2023.

EGU23-10216 | Orals | ST2.4

Study of Ion Injection into the Inner Magnetosphere Using an Implicit Particle in Cell Simulation Driven by A Global MHD simulation 

Mostafa El Alaoui, Giovanni Lapenta, Liutauras Rusaitis, and Raymond Walker

Observations and magnetohydrodynamic simulations show that not all plasma injections from reconnection in the tail reach the inner magnetosphere to populate the ring current. We have used a self-consistent three-dimension particle-in-cell (PIC) simulation one way coupled to a global magnetohydrodynamic (MHD) simulation of the solar wind-magnetosphere-ionosphere system to investigate the population of the ring current during storm time substorms. This model includes a large fraction of the inner magnetosphere and the near-Earth tail. It allows us to study of the injection of particles from the tail and the interaction of the particles with plasma waves. The calculation begins with electrons and ions propagating earthward from the tail reconnection region. The particle distributions that enter the inner magnetosphere (R < 10 RE) from the magnetotail have a suprathermal component which acts as a seed population for the ring current. We imposed a steady southward IMF with a magnitude of 8 nT at the upstream boundary of the MHD simulation domain for more than three hours. The solar wind number density was 6 cm-3, the thermal pressure was 16 pPa, and the velocity was 530 km/s in the X direction toward Earth.  After we ran the MHD simulation, we chose an interval to examine during which there were several earthward flow channels and dipolarization fronts. Then, we used the output from this time to populate a large PIC simulation domain in the inner magnetosphere. In GSM coordinates, this domain extends over -22 RE <X < 12.5 RE, -13 RE < Y <13 RE, -5 RE < Z < 5 RE. The mass ratio was 256 with realistic ions and more massive electrons. In an initial simulation, we ran the code for 16,000 cycles and found that a ring current developed. We will discuss the reasons why some particles from the tail reach the inner magnetosphere, and some do not by examining how the particles are accelerated and lost.    

How to cite: El Alaoui, M., Lapenta, G., Rusaitis, L., and Walker, R.: Study of Ion Injection into the Inner Magnetosphere Using an Implicit Particle in Cell Simulation Driven by A Global MHD simulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10216, https://doi.org/10.5194/egusphere-egu23-10216, 2023.

EGU23-10513 | ECS | Posters virtual | ST2.4

EMIC wave induced proton precipitation during the 27-28 May 2017 storm:Comparison of BATSRUS+RAM-SCB simulations with ground/space based observations 

Shreedevi Porunakatu Radhakrishna, Yiqun Yu, Yoshizumi Miyoshi, Xingbin Tian, Minghui Zhu, Sandeep Kumar, Satoko Nakamura, Chae-Woo Jun, Masafumi Shoji, Kazuo Shiokawa, Vania Jordanova, Tomoaki Hori, Kazushi Asamura, Iku Shinohara, Shoichiro Yokota, Satoshi Kasahara, Kunihiro Keika, Ayako Matsuoka, Martin Connors, and Akira Kadokura

Recent studies have shown that the ion precipitation induced by EMIC waves can contribute significantly to the total energy flux deposited into the ionosphere and severely affect the magnetosphere-ionosphere coupling. During the geomagnetic storm of 27-28 May 2017, the ARASE and the RBSPa satellites observed typical signatures of EMIC waves in the inner magnetosphere. The DMSP and MetOp satellites observed enhanced proton precipitation during the main phase of the storm. In order to understand the evolution of proton precipitation into the ionosphere, its correspondence to the time and location of excitation of the EMIC waves and its relation to the source and distribution of proton temperature anisotropy, we conducted two simulations of the BATSRUS+RAMSCBE model with and without EMIC waves included. Simulation results suggest that the H- and He-band EMIC waves are excited within regions of strong temperature anisotropy of protons in the vicinity of the plasmapause. In regions where the Arase/RBSPa satellite measurements recorded EMIC wave activity, an increase in the simulated growth rates of H- and He-band EMIC waves is observed indicating that the model is able to capture the EMIC wave activity. The RAM-SCBE simulation with EMIC waves reproduces the precipitating fluxes in the premidnight sector fairly well, and is found to be in good agreement with the DMSP and MetOp satellite observations. The results suggest that the EMIC wave scattering of ring current ions gives rise to the proton precipitation in the premidnight sector at subauroral latitudes during the main phase of the 27 May 2017 storm.

How to cite: Porunakatu Radhakrishna, S., Yu, Y., Miyoshi, Y., Tian, X., Zhu, M., Kumar, S., Nakamura, S., Jun, C.-W., Shoji, M., Shiokawa, K., Jordanova, V., Hori, T., Asamura, K., Shinohara, I., Yokota, S., Kasahara, S., Keika, K., Matsuoka, A., Connors, M., and Kadokura, A.: EMIC wave induced proton precipitation during the 27-28 May 2017 storm:Comparison of BATSRUS+RAM-SCB simulations with ground/space based observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10513, https://doi.org/10.5194/egusphere-egu23-10513, 2023.

EGU23-10543 | ECS | Posters on site | ST2.4

Outer radiation belt electron flux and phase space density changes during sheath regions of coronal mass ejections from Van Allen Probes and GPS data 

Milla Kalliokoski, Michael Henderson, Steven Morley, Emilia Kilpua, Adnane Osmane, Leonid Olifer, Drew Turner, Allison Jaynes, Harriet George, Sanni Hoilijoki, Lucile Turc, and Minna Palmroth

Turbulent and compressed sheath regions ahead of interplanetary coronal mass ejections are key drivers of dramatic changes in the electron fluxes in the Earth’s outer radiation belt. They are also associated with elevated wave activity in the inner magnetosphere. These changes in electron fluxes can occur on timescales of tens of minutes that are not readily captured by a two-satellite mission such as the Van Allen Probes due to long revisit times. The recently released Global Positioning System (GPS) data set, on the other hand, provides a larger number of measurements at a given location within a given amount of time, owing to the many satellites in the constellation. In our statistical study on the impact of sheath regions on the outer radiation belt, we investigated events in 2012-2018 at timescales of 6 hours (Van Allen Probes data) and 30 minutes (GPS data). The study showed that the flux response to sheaths as reported from Van Allen Probes observations is reproduced by GPS data.  We highlight that the shorter timescale allowed by GPS data further confirms that the energy and L-shell dependent flux changes are associated with the sheaths rather than the following ejecta. Additionally, we studied the electron phase space density, which is a key quantity for identifying non-adiabatic electron dynamics. This showed that electrons are effectively accelerated only during geoeffective sheaths (SYM-H < -30 nT). Outer belt losses are common for all sheaths, and the lost electrons are replenished during the early ejecta.

How to cite: Kalliokoski, M., Henderson, M., Morley, S., Kilpua, E., Osmane, A., Olifer, L., Turner, D., Jaynes, A., George, H., Hoilijoki, S., Turc, L., and Palmroth, M.: Outer radiation belt electron flux and phase space density changes during sheath regions of coronal mass ejections from Van Allen Probes and GPS data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10543, https://doi.org/10.5194/egusphere-egu23-10543, 2023.

EGU23-10778 | ECS | Posters virtual | ST2.4

Plasma pressure distribution of ions and electrons in the inner magnetosphere during CIR driven storms observed during Arase satellite era 

Sandeep Kumar, Yoshizumi Miyoshi, Vania Koleva Jordanova, Lynn M Kistler, Inchun Park, Porunakatu Radhakrishna Shreedevi, Kazushi Asamura, Shoichiro Yokota, Satoshi Kasahara, Yoichi Kazama, Shiang -Yu Wang, Sunny W. Y. Tam, Takefumi Mitani, Nana Higashio, Kunihiro Keika, Tomo Hori, Chae-Woo Jun, Ayako Matsuoka, Shun Imajo, and Iku Shinohara

Geomagnetic storms are the main component of space weather. Enhancement of the ring current is a typical feature of the geomagnetic storm and a global decrease in the H component of the geomagnetic field is observed during the main phase of the geomagnetic storm.  The ring current represents a diamagnetic current driven by the plasma pressure in the inner magnetosphere. The plasma pressure is mainly dominated by protons in an energy range of a few to a few hundred keVs during quiet times. The O+ contribution is also important, and sometimes dominates more than H+ during intense geomagnetic storms. However, electron contribution to the ring current is not studied well. Recently, we showed that the electron pressure also contributes to the depression of ground magnetic field during the November 2017 CIR-driven storm by comparing Ring current Atmosphere interactions Model with Self Consistent magnetic field (RAM-SCB) simulation, Arase in-situ plasma/particle data, and ground-based magnetometer data [Kumar et al., 2021]. Arase satellite observed 26 geomagnetic storms driven by Corotating Interaction Regions (CIR) during 2017-2021. In this study, we examine statistically the spatial and temporal distribution of ions (H+, He+, O+) and electrons pressure as a function of magnetic local time, L shell and wide range of energies during prestorm, main phase, early recovery and late recovery phase for 26 CIR storms using in situ plasma/particle data obtained by Arase. The results indicate that the electrons (20-50 keV) contribution to the ring current pressure is non-negligible.

How to cite: Kumar, S., Miyoshi, Y., Jordanova, V. K., Kistler, L. M., Park, I., Shreedevi, P. R., Asamura, K., Yokota, S., Kasahara, S., Kazama, Y., Wang, S.-Y., Tam, S. W. Y., Mitani, T., Higashio, N., Keika, K., Hori, T., Jun, C.-W., Matsuoka, A., Imajo, S., and Shinohara, I.: Plasma pressure distribution of ions and electrons in the inner magnetosphere during CIR driven storms observed during Arase satellite era, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10778, https://doi.org/10.5194/egusphere-egu23-10778, 2023.

The polar wind, consisting of low-energy ions and electrons, is an outflow along the open magnetic field lines from the polar cap ionosphere to the magnetosphere. Previous studies found that both solar radiation and solar wind electromagnetic energy are the two main energy sources for the polar wind. The polar rain, being field-aligned precipitating electrons from the solar wind to the polar cap, may provide additional energies for the polar wind. This scenario is complicated as simulation studies show that polar rain changes the electric potential structures over the polar cap ionosphere. It is unclear how the polar rain affects the polar wind ion outflow. In this study, we show a positive correlation between the polar wind and the polar rain. Meanwhile, the polar wind is generally diminished in regions with strong Earth’s magnetic field, suggesting the B modulates the penetration depth of the polar rain through the magnetic mirror force and thus the energy dissipation of the polar rain. Therefore, the polar rain can be an additional energy source for the polar wind although the polar rain has generally smaller energies and intensities than the particle precipitations in the auroral regions.

How to cite: Li, K.: The effects of the polar rain on the polar wind ion outflow from the nightside ionosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11056, https://doi.org/10.5194/egusphere-egu23-11056, 2023.

EGU23-11084 | ECS | Posters on site | ST2.4

A Missing Dusk-side Loss Process in the Electron Ring Current 

Bernhard Haas, Yuri Y. Shprits, Michael Wutzig, Dedong Wang, and Mátyás Szabó-Roberts

The Earth’s magnetic field traps charged particles which are transported longitudinally around Earth, generating a near-circular current, known as the ring current. While the ring current has been measured on the ground and space for many decades, the enhancement of the ring current during geomagnetic storms is still not well understood, due to many processes contributing to its dynamics on different time scales. The low energy part of the ring current of 10-50 keV is responsible for surface charging effects on spacecraft, potentially causing satellite anomalies.

Here, we show that existing ring current models systematically overestimate the in-situ satellite measurements of the Earth’s night side electron ring current during geomagnetic storms. By analyzing electron drift trajectories during the storm onset, we show that this systematic overestimation of flux can be explained through a missing loss process which operates in the pre-midnight sector. Quantifying this loss reveals that the theoretical upper limit of strong diffusion has to be reached in a broad region of space in order to reproduce the observed flux. We include this missing loss process and show that predictions of electron flux can be significantly improved. Identifying missing loss processes in ring current models is vital to accurately predict storm time dynamics and the associated hazards, that result from a delicate balance of source and loss processes.

How to cite: Haas, B., Shprits, Y. Y., Wutzig, M., Wang, D., and Szabó-Roberts, M.: A Missing Dusk-side Loss Process in the Electron Ring Current, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11084, https://doi.org/10.5194/egusphere-egu23-11084, 2023.

EGU23-12704 | ECS | Posters on site | ST2.4

Studying the South Atlantic Anomaly temporal evolutionfrom 1998 to 2022 using the SEM-2 proton flux 

François Ginisty, Frédéric Wrobel, Robert Ecoffet, Mioara Mandea, Alain Michez, Nicolas Balcon, Marine Ruffenach, and Julien Mekki

The SEM-2 (Space Environment Monitor-2) instrument embedded on the NOAA-15 Low Earth Orbit satellite provides measurements of trapped protons in the Van Allen inner belt from 1998 to nowadays. This continuous amount of measurements enables us to study the temporal evolution of the dynamics of the South Atlantic Anomaly (SAA) over more than two solar cycles.
In particular, we study the temporal evolution of the area of the SAA. We observe that the area of the SAA is anti-correlated with the solar activity. Two physical process explain this anticorrelation.
First, the more the Sun is active the more it disables the cosmic rays to reach the Earth Magnetosphere and to fill the inner radiation belt with protons. Then, when the Sun in more active, the upper atmosphere is warmer and therefore absorbs more protons from the radiation belt.
Then, we investigate the protons flux centroid of the SAA. The temporal evolution of its position, latitude and, longitude is studied over the same time interval (1998-2022). We notice the latitude of the centroid is also anti-correlated with the solar activity whereas the longitude seems absolutely
independent. Some explanations are given for these observations.
The temporal evolution of the position of the centroid shows a drift of the SAA. Indeed from 1998 to 2022 the SAA drifted of about 7 degrees West.
The SEM-2 instrument measures flux for protons of different energies (16, 36, 70 and, 140 MeV). For each energy, the SAA dynamic has a similar trend but with different values. These differences are investigated and the results discussed.

How to cite: Ginisty, F., Wrobel, F., Ecoffet, R., Mandea, M., Michez, A., Balcon, N., Ruffenach, M., and Mekki, J.: Studying the South Atlantic Anomaly temporal evolutionfrom 1998 to 2022 using the SEM-2 proton flux, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12704, https://doi.org/10.5194/egusphere-egu23-12704, 2023.

EGU23-13125 | ECS | Posters on site | ST2.4

Investigating Solar Wind Drivers of Ultrarelativistic Electron Enhancements in the Outer Radiation Belt 

Matyas Szabo-Roberts, Yuri Shprits, and Hayley Allison

A distinct population of ultrarelativistic electrons has been observed in the outer radiation belt after several geomagnetic storms, and recent modeling results indicate that an existing seed population, and depletions in plasmasphere electron density, are a necessary condition for the appearance of this electron population. In order to similarly deepen our understanding of the solar wind drivers behind the appearance of these electrons with extreme energy, we catalog storms corresponding to ultrarelativistic enhancements by origin, and begin to establish necessary and sufficient solar wind conditions for these enhancement events. To do so, we perform superposed epoch analysis on a 6 year period from 2012 to 2018, using solar wind data from the Omniweb service, as well as electron flux and electron density data products from the Van Allen Probes mission. We also provide an overview of further modeling objectives and open questions for continued investigation of this electron population.

How to cite: Szabo-Roberts, M., Shprits, Y., and Allison, H.: Investigating Solar Wind Drivers of Ultrarelativistic Electron Enhancements in the Outer Radiation Belt, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13125, https://doi.org/10.5194/egusphere-egu23-13125, 2023.

EGU23-13189 | ECS | Posters virtual | ST2.4

Impact of Interplanetary Coronal Mass Ejections and High Speed Streams on the dynamic variations of the electron population in the outer Van Allen belt 

Adamantia Dimitrakoula, Alexandra Triantopoulou, Afroditi Nasi, Christos Katsavrias, Ioannis A. Daglis, and Ingmar Sandberg

The outer Van Allen radiation belt stands out for its intense variability, due to the complex mechanisms that take place due to the Sun – Earth coupling. One fundamentally important effect is the acceleration of seed electrons to relativistic and ultra – relativistic energies, through different mechanisms, namely radial diffusion and local acceleration.

In our work, we examine 46 events from the Van Allen Probes era (2012 – 2018), which we categorize according to the interplanetary driver of the geomagnetic disturbance. In particular, we study 16 events caused by Interplanetary Coronal Mass Ejections (ICMEs) and 30 events caused by High Speed Streams (HSS), following Stream Interaction Regions (SIRs), for which we calculate the electron Phase Space Density (PSD) for distinct values of the first adiabatic invariant (μ = 100, 1000, 5000 MeV/G) corresponding to seed, relativistic and ultra – relativistic electrons in the outer radiation belt. Furthermore, we perform a Superposed Epoch Analysis (SEA) of the geomagnetic disturbance events, which lead to either enhancements or depletions of the electron PSD, taking into consideration the parameters of solar wind activity, the state of the magnetosphere and the values of the second adiabatic invariant (K = 0.03, 0.09, 0.15 G1/2RE). We discuss the effects of the drivers on the variability of the outer radiation belt and how the different electron populations are affected, by comparing the time and radial profiles of the PSD. Our results lead to a clear difference between the two drivers, as far as it concerns the acceleration mechanisms.

How to cite: Dimitrakoula, A., Triantopoulou, A., Nasi, A., Katsavrias, C., Daglis, I. A., and Sandberg, I.: Impact of Interplanetary Coronal Mass Ejections and High Speed Streams on the dynamic variations of the electron population in the outer Van Allen belt, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13189, https://doi.org/10.5194/egusphere-egu23-13189, 2023.

EGU23-14289 | Posters on site | ST2.4

Developing Chorus Wave Model Using Van Allen Probe and Arase Data 

Dedong Wang, Yuri Shprits, Ting Feng, Thea Lepage, Ingo Michaelis, Yoshizumi Miyoshi, Yoshiya Kasahara, Atsushi Kumamoto, Shoya Matsud, Ayako Matsuoka, Satoko Nakamura, Iku Shinohara, and Fuminori Tsuchiiya

Chorus waves play an important role in the dynamic evolution of energetic electrons in the Earth’s radiation belts and ring current. Due to the orbit limitation of Van Allen Probes, our previous chorus wave model developed using Van Allen Probe data is limited to low latitude. In this study, we extend the chorus wave model to higher latitudes by combining measurements from the Van Allen Probes and Arase satellite. As a first step, we intercalibrate chorus wave measurements by comparing statistical features of chorus wave observations from Van Allen Probes and Arase missions. We first investigate the measurements in the same latitude range during the two years of overlap between the Van Allen Probe data and the Arase data. We find that the statistical intensity of chorus waves from Van Allen Probes is stronger than those from Arase observations. After the intercalibration, we combine the chorus wave measurements from the two satellite missions and develop an analytical chorus wave model which covers all magnetic local time and extends to higher latitudes. This chorus wave model will be further used in radiation belt and ring current simulations.

How to cite: Wang, D., Shprits, Y., Feng, T., Lepage, T., Michaelis, I., Miyoshi, Y., Kasahara, Y., Kumamoto, A., Matsud, S., Matsuoka, A., Nakamura, S., Shinohara, I., and Tsuchiiya, F.: Developing Chorus Wave Model Using Van Allen Probe and Arase Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14289, https://doi.org/10.5194/egusphere-egu23-14289, 2023.

EGU23-15611 | Orals | ST2.4

Observations of Off-Equatorial ULF Waves and Simulations of their effects on Radial Diffusion in the Radiation Belts 

Theodore Sarris, Xinlin Li, Hong Zhao, Kostis Papadakis, Wenlong Liu, Weichao Tu, Vassilis Angelopoulos, Karl-Heinz Glassmeier, Yoshizumi Miyoshi, Ayako Matsuoka, Iku Shinohara, and Shun Imajo

Magnetospheric ultra-low frequency (ULF) waves are known to cause radial diffusion and transport of hundreds-keV to few-MeV electrons in the radiation belts, as the range of drift frequencies of such electrons overlaps with the frequencies of the waves, leading to resonant interactions. Numerous expressions have been derived to quantitatively describe radial diffusion, so that they can be incorporated in global models of radiation belt electrons; however, most expressions of the radial diffusion rates are derived only for equatorially mirroring electrons, and are based on estimates of the power of ULF waves that are obtained either from spacecraft close to the equatorial plane or from the ground. Recent studies using the Van Allen Probes and Arase have shown that the wave power in magnetic fluctuations is significantly enhanced away from the magnetic equator, consistent with models simulating the natural modes of oscillation of magnetospheric field lines. This has significant implications for the estimation of radial diffusion rates, as higher pitch angle electrons will experience considerably higher ULF wave fluctuations than equatorial electrons. In this talk, we present recent results on the distribution of the magnetic field wave power as a function of magnetic latitude in different local time sectors and under different solar and geomagnetic conditions. Furthermore, using analytic functions of wave amplitudes in 3D test particle simulations, we simulate the change in L over time for particles of different pitch angles; this change in L can be translated to novel analytic diffusion coefficients with pitch-angle, L and energy dependence. In this talk we discuss the potential implications for the radial diffusion rates as currently estimated.

How to cite: Sarris, T., Li, X., Zhao, H., Papadakis, K., Liu, W., Tu, W., Angelopoulos, V., Glassmeier, K.-H., Miyoshi, Y., Matsuoka, A., Shinohara, I., and Imajo, S.: Observations of Off-Equatorial ULF Waves and Simulations of their effects on Radial Diffusion in the Radiation Belts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15611, https://doi.org/10.5194/egusphere-egu23-15611, 2023.

EGU23-15928 | Posters on site | ST2.4

Proton precipitation from EMIC waves at high latitudes: A casestudy from 29 March 2021 

Patrizia Francia, Marcello DE Lauretis, Mirko Piersanti, Giulia D'Angelo, and Alexandra Parmentier

Electron precipitation driven by electromagnetic ion cyclotron (EMIC) waves in the Pc1 range (0.1–5Hz) has been suggested as a significant loss mechanism for outer radiation belt fluxes of electrons in the 1–5 MeV energy range. Moreover, EMIC waves have been also observed to cause significant precipitation of ring current protons during geomagnetic storms.
In this study we report the concurrent observations of electromagnetic ion cyclotron Pc1 waves in both ionospheric F-region and at ground. Key event on March 29, 2021 shows that high latitude ground magnetometers in Antarctica and CSES LEO satellite detected concurrent Pc1 wave and energetic proton precipitation. In the ionospheric F-layer above the Auroral zone, the CSES satellites observed transverse Pc1 waves and localized plasma density enhancement, which is occasionally surrounded by wide/shallow depletion. This might indicate that EMIC wave-induced proton precipitation contributes to the energy transfer from the magnetosphere to the ionosphere and to the ionization of the F-layer.

How to cite: Francia, P., DE Lauretis, M., Piersanti, M., D'Angelo, G., and Parmentier, A.: Proton precipitation from EMIC waves at high latitudes: A casestudy from 29 March 2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15928, https://doi.org/10.5194/egusphere-egu23-15928, 2023.

EGU23-15979 | ECS | Posters on site | ST2.4

Auroral oval identification based on Swarm magnetometer data 

Margot Decotte, Spencer Hatch, Karl Laundal, and Jone Reistad

Following the work done with the DMSP spectrometer data to derive the auroral occurrence probability in all covered MLat-MLT sectors above 50 degrees MLat (Decotte et al. 2023), here we use the Swarm magnetometer data to extract the probability to detect magnetic field perturbations in the East--West direction. We derive the integrated spectral density from the magnetic field data in a given frequency band, and we define a minimum power threshold above which fluctuations would indicate field-aligned currents. We obtain MLat-MLT distributions of magnetic field fluctuations for various geomagnetic conditions. We find strong similarities between the preferred region of magnetic perturbations and the Xiong and Lühr auroral boundaries (2014), suggesting that the auroral oval morphology could be investigated through magnetic field spectral power estimates. We compare the magnetic field fluctuation probability with the auroral occurrence probability (DMSP particle data) and we find a recurrent dawn-dusk asymmetric pattern in both distributions.  

How to cite: Decotte, M., Hatch, S., Laundal, K., and Reistad, J.: Auroral oval identification based on Swarm magnetometer data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15979, https://doi.org/10.5194/egusphere-egu23-15979, 2023.

EGU23-16056 | ECS | Posters on site | ST2.4

VLF banded structured events observed in the 5–39 kHz frequency range in Finland 

Liliana Macotela, Jyrki Manninen, and Martin Fullekrug

Analysis of very low frequency (VLF) radio waves provides us the remarkable possibility of investigating the response of both the lower ionosphere and magnetosphere to a diversity of transient and long-term physical phenomena originating on Earth (e.g., atmospheric waves) or in space (e.g., CMEs). In this work, broadband VLF data measured at Kannuslehto, in northern Finland, is used to characterize a new type of VLF emissions displaying a strip-like structure observed in the 5–39 kHz frequency range. Analyzing campaigns from 2006 to 2022, we found that this emission can be observed either in the high VLF frequency ranges or spanning from low to high frequency ranges. We also found that the events last usually less than 1 hour, occur during evening hours, and during quiet geomagnetic conditions. We discuss the seasonal dependence of this kind of events by analyzing a complete year during 2022. We also discuss whether their origin might be due to plasma instabilities in the magnetosphere, as in the case of auroral hiss.

How to cite: Macotela, L., Manninen, J., and Fullekrug, M.: VLF banded structured events observed in the 5–39 kHz frequency range in Finland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16056, https://doi.org/10.5194/egusphere-egu23-16056, 2023.

EGU23-16202 | ECS | Posters virtual | ST2.4

Observation of VLF transmitter induced electron precipitation of up to 400keV 

Coralie Neubüser, Roberto Battiston, Francesco Maria Follega, William Jerome Burger, Mirko Piersanti, and Dario Recchiuti

Ground-based very low frequency (VLF; 10-30kHz) transmitters have been found in previous studies to emit whistler waves that can re- sonate with high-energy particles (>100keV) in the radiation belt, causing energetic electron precipitation via pitch angle scattering. In the attempt to find a similar mechanism responsible for electron precipitation due to EM waves emitted during seismic events, we ha- ve analysed three years of data (2019-2021) from the China Seismo- Electromagnetic Satellite (CSES) and the NOAA POES satellites. We found enhanced electron fluxes due to the 19.8kHz waves of the NWC transmitter in Australia at L-shell values of about 1.5 and 1.8 at energies up to 400keV in the data of the CSES and NOAA POES-19 sa- tellite, respectively. The enhanced fluxes can be followed along the drift shells from Australia eastwards, and are observed to be lost in the the South Atlantic Anomaly (SAA) due to the interaction with the atmosphere. The high energy resolution of the HEPP-L detector on board CSES of 11keV from 0.1 to 3MeV allows a detailed study of the signal and we will present the expected energy-dispersed wisp struc- ture in L-shell. Finally, we will present our latest results on the identification of isolated electron bursts and the assignment to dif- ferent VLF transmitters, which includes the correlation of VLF wave measurements from ground and space-based instruments to determined on/off periods of the transmitters.

How to cite: Neubüser, C., Battiston, R., Follega, F. M., Burger, W. J., Piersanti, M., and Recchiuti, D.: Observation of VLF transmitter induced electron precipitation of up to 400keV, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16202, https://doi.org/10.5194/egusphere-egu23-16202, 2023.

EGU23-17001 | Orals | ST2.4

A new mechanism for early time plasmaspheric refilling 

Raluca Ilie, Jianghuai Liu, Michael Liemohn, and Joseph Borovky

We present a robust assessment of the formation and evolution of the cold H+ population produced via charge-exchange processes between ring current ions and exospheric neutral hydrogen in the inner magnetosphere, inferred via numerical simulations of the near-Earth plasma using a drift kinetic model of the ring current-plasmasphere system.

We evaluate the flow of mass and energy through the inner magnetospheric system and show that the production and evolution of the cold H+ population can be primarily driven by the plasma sheet conditions and dynamics and has the potential to reshape the plasmasphere and enhance the early-stage plasmaspheric refilling. We present evidence that the plasma sheet heavy ion composition is the primary controlling factor in the formation of the cold H+ via charge exchange with the geocorona, while the neutral density plays a much smaller role.

How to cite: Ilie, R., Liu, J., Liemohn, M., and Borovky, J.: A new mechanism for early time plasmaspheric refilling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17001, https://doi.org/10.5194/egusphere-egu23-17001, 2023.

EGU23-17213 | Orals | ST2.4

New pathways for EMIC wave propagation within the ionosphere: SWARM observations and modelling 

Robert Rankin, Dmytro Sydorenko, and Ian R Mann

Electromagnetic ion cyclotron (EMIC) waves are important because of their essential role in reducing the amount of radiation in the Earth's radiation belts under geomagnetic storm conditions. In this presentation, we show results from a new simulation model of EMIC waves and compare them with SWARM satellite data and ground-based observations [I. P. Pakhotin et al., Geophys. Res. Lett., 2022, doi:10.1029/2022GL098249]. The EMIC wave model is a first-of-a-kind in accounting for wave propagation in the magnetosphere and a realistic ionosphere specified using the IRI and MSIS empirical models. The inclusion of a realistic ionosphere in the model enables new pathways to the upper atmosphere to be identified, which is crucial for understanding the waves detected on the ground. We show using a model-data comparison that EMIC wave energy is reflected at different locations in the ionosphere toward the equator to form standing waves. This is a new resonance phenomenoncreated by interference of waves that produces an amplitude peak in the upper atmosphere at lower latitudes, far from the location of the initial source. Understanding such pathways is crucial for correctly diagnosing the location of EMIC wave populations in space, and assessing their role in radiation belt loss.

How to cite: Rankin, R., Sydorenko, D., and Mann, I. R.: New pathways for EMIC wave propagation within the ionosphere: SWARM observations and modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17213, https://doi.org/10.5194/egusphere-egu23-17213, 2023.

EGU23-17286 | ECS | Orals | ST2.4

Nonlinear Scattering of Relativistic Electrons by Oblique EMIC Waves 

Miroslav Hanzelka, Wen Li, Qianli Ma, and Luisa Capannolo

Electrons in the Earth’s outer radiation belt can experience rapid energization and pitch angle scattering through interactions with naturally generated electromagnetic waves. Cyclotron resonant interactions with large amplitude electromagnetic ion cyclotron (EMIC) emissions cause scattering and major atmospheric losses of relativistic electrons in the sub-MeV and MeV energy range. While theory and simulations in the past focused mostly on parallel propagating waves, in-situ spacecraft observations of EMIC waves commonly show quasi-parallel or moderately oblique propagation.

Here we present the results of test-particle analysis of electron interaction with helium band and hydrogen band EMIC waves parametrized by wave normal angle (WNA) and wave amplitude. It is shown that nonlinear phase trapping and the associated transport of electrons to low-pitch angles become efficient only at very large amplitudes (> 1% of the background magnetic field), especially in the helium band frequency range, making the nonlinear effects less important than in the whistler-electron interaction case. Harmonic resonant interactions with oblique waves further increase the probability of detrapping, pushing the pitch angle evolution closer to pure diffusion. We also analyze the pitch angle behavior near the loss cone and study the evolution of phase space density (PSD) through the Liouville mapping method. Despite the significant advection effects caused by force-bunching of resonant electrons at low pitch angles, the PSD in the loss cone exhibits behavior similar to strong diffusion. We argue that this is expected to be the case for any bursty precipitation caused by cyclotron resonant interactions.

The wave normal angle has only minor impact on the precipitation rate in the energy range affected by the off-equatorial fundamental resonance, except for the case of very oblique waves (WNA > 70 deg). However, since oblique EMIC waves are elliptically polarized and interact with both co-streaming and counter-streaming electrons, they can enhance the changes in the pitch angle of mirrored (trapped) relativistic electrons. The scattering efficiency for counter-streaming electrons strongly depends on the wave ellipticity, and in turn, on wave frequency, wave normal angle, and ion composition. Our simulation results support the need for accurate wave normal angle and amplitude distribution to quantify the relativistic electron precipitation to the Earth’s atmosphere.

How to cite: Hanzelka, M., Li, W., Ma, Q., and Capannolo, L.: Nonlinear Scattering of Relativistic Electrons by Oblique EMIC Waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17286, https://doi.org/10.5194/egusphere-egu23-17286, 2023.

GI6 – Multidisciplinary sessions on geoscience instrumentation, data networks, and analysis

Geomorphological mapping is one of the primary research methods used to collect data on glacial landforms and reconstruct glaciological processes. The most common approach is a combination of field-based and remote mapping using data obtained from various sensors. However, one of the crucial methodical problems is collecting remote sensing data in the appropriate spatial resolution for the analyzed landform, which directly affects the data collection time and costs. This study aims to find the optimal resolution of digital elevation models (DEMs) to map subtle glacial landforms: kame terraces, eskers, flutes, and push moraine. Such landforms contain valuable information about the glacial process–form relationships, however, are often too subtle to be recognized on satellite data, and therefore more detailed data (e.g., UAV-based) are required. By “optimal”, we mean the resolution high enough to enable recognition of the landforms mentioned above, and at the same time, as low as possible to minimize the time spent on data collection during the fieldwork.

To find out the optimal resolution, we used detailed (0.02 – 0.04 m ground sampling distance [GSD]) DEMs of the glacier forelands in Iceland (Kvíárjökull, Fjallsjökull and Svinafellsjökull), created based high-resolution images from an unmanned aerial vehicle (UAV). The DEMs were resampled to 0.05, 0.10, 0.15, 0.20, 0.30, 0.40, 0.50, 1.00 and 2.00 m GSD and selected glacial landforms were mapped independently by two operators and cross-checked. The results indicate that 2.0 m resolution is insufficient to properly recognize landforms such as pushed moraines or flutes; however, it can be sufficient to detect kame terraces and major glacifluvial channels. For general mapping of locations of forms such as annual pushed moraines or fluting, the 0.5 m resolution is required. However, to obtain geomorphometric characteristics of the landforms (e.g., height, width, volume) resolution between 0.1 and 0.2 m is necessary. Finer resolution (better than 0.05 m GSD) does not increase the ability to detect landforms or better characterize their geometric properties; however, in some cases might be useful to obtain information about clast characteristics. The experiment proved that decimeter-scale spatial resolution is sufficient for mapping of some geomorphological forms (annual pushed moraines, flutes), which allows for planning UAV missions at a higher elevation above the ground and, therefore, minmizing the duration of field surveys. Moreover, some of the more prominent landforms (e.g., kame terraces, larger moraines) can be successfully detected from aerial or satellite-based DEMs (e.g. freely available ArcticDEM) with a resolution of 2.00 m, the use of which reduces the costs of field research to a minimum.

This research was funded by the National Science Centre, Poland, Grant Number 2019/35/B/ST10/03928.

How to cite: Śledź, S. and Ewertowski, M.: Optimal resolution of UAV-based digital elevation models (DEMs) for mapping of selected subtle glacial landforms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-151, https://doi.org/10.5194/egusphere-egu23-151, 2023.

EGU23-3292 | Posters on site | GI6.1

CO2 concentration and stable isotope surveys in the ambient air of populated areas of La Palma (Canary Islands) by means of mobile Delta Ray measurements using an electrical car 

Nemesio M. Pérez, María Asensio-Ramos, José Barrancos, Eleazar Padrón, Gladys V. Melián, Fátima Rodríguez, Germán D. Padilla, Violeta T. Albertos, Pedro A. Hernández, Antonio J. Álvarez Díaz, Héctor de los Ríos Díaz, David Afonso Falcón, and Juan Cutillas

Anomalous CO2 degassing of volcanic origin was observed by the end of November 2021 in the neighborhoods of La Bombilla and Puerto Naos, located in the western flank of La Palma, about 5 km distance southwestern of the 2021 Tajogaite eruption vents (Hernández et al., 2021). In this study zone, continuous monitoring of CO2 concentration in the outdoors ambient air at 200 cm from the surface has reached a daily average of maximum and mean values about 28,000 and 10,000 ppm, respectively. We started recently to perform CO2 concentration and stable isotope surveys in the outdoors ambient air of Puerto Naos at 140 cm from the surface by means of a Delta Ray analyzer installed in an electrical car which was driving through the streets of Puerto Naos. This instrument is a high performance, mid-infrared laser-based, isotope ratio infrared spectrometer (IRIS) which offers the possibility of performing simultaneous determination of δ13C and δ18O in CO2 at ambient concentrations with a precision as low as 0.05‰. One major advantage of IRIS techniques with respect to more traditional ones (e.g., isotopic ratio mass spectrometry -IRMS-) is the possibility to perform (semi)continuous measurements at high temporal resolution. Since October 2022, seven surveys have been performed at Puerto Naos making up a total of about 600 measurements. The observed CO2 concentrations and the δ13C-CO2 values in the outdoors ambient air ranged from 420 to 3,500 ppm and from -9.0 to -3.2 ‰ vs. VPDB, respectively. Survey data analysis showed a good spatial correlation between relatively high CO2 concentrations with δ13C-CO2 values less 13C-depleted (i.e., volcanic CO2). These observations highlight that stable isotope surveys allow to evaluate the impact of volcanic degassing on the air CO2 concentration and provide valuable results to identify the volcanic CO2 gas hazard zones.

Hernández, P. A., Padrón, E., Melián, G. V., Pérez, N. M., Padilla, G., Asensio-Ramos, M., Di Nardo, D., Barrancos, J., Pacheco, J. M., and Smit, M.: Gas hazard assessment at Puerto Naos and La Bombilla inhabited areas, Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7705, https://doi.org/10.5194/egusphere-egu22-7705, 2022.

How to cite: Pérez, N. M., Asensio-Ramos, M., Barrancos, J., Padrón, E., Melián, G. V., Rodríguez, F., Padilla, G. D., Albertos, V. T., Hernández, P. A., Álvarez Díaz, A. J., de los Ríos Díaz, H., Afonso Falcón, D., and Cutillas, J.: CO2 concentration and stable isotope surveys in the ambient air of populated areas of La Palma (Canary Islands) by means of mobile Delta Ray measurements using an electrical car, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3292, https://doi.org/10.5194/egusphere-egu23-3292, 2023.

EGU23-3620 | ECS | Posters on site | GI6.1

SO2 emissions during the post-eruptive phase of the Tajogaite eruption (La Palma, Canary Islands) by means of ground-based miniDOAS measurements in transverse mode using a car and UAV 

Oscar Rodríguez, José Barrancos, Juan Cutillas, Victor Ortega, Pedro A. Hernández, Iván Cabrera, and Nemesio M. Pérez

Throughout the 85 days that lasted the Tajogaite eruption at Cumbre Vieja volcano (La Palma, Canary Islands, Spain), observations of SO2 emissions were made using ground-based instruments, in transverse mode, static scanners and on-board drones, as well as by numerous satellite instruments. The initial estimates of the total SO2 emission from the eruption were 2.4 Mt from TROPOMI and 1.2 Mt from the traverse data. These measurements formed part of the official monitoring effort, providing insights into the eruption’s evolution and informing the civil defence response throughout the eruption (Hayer C. et al., 2022; Albertos V. T. et al., 2022). Once the Tajogaite eruption was over, we continued performing a SO2 monitoring release to the atmosphere by the Tajogaite volcanic vent since the low ambient concentrations of SO2 make it an ideal volcanic gas monitoring candidate even during the post-eruptive phase. SO2 measurements had been carried out a using a car-mounted and UAV-mounted ground-based miniDOAS measurements throughout this post-eruptive phase. About 80 measurements of SO2 emission rates were performed from December 15, 2021 to December 17, 2022. The standard deviation of the estimated values obtained daily was ~ 20%. The range of estimated SO2 emission values has been from 670 to 17 tons per day, observing a clear decreasing trend of SO2 emissions during the post-eruptive phase. During the first month of the post-eruptive phase, it was observed that the average value of the estimated SO2 emission was about 219 tons/day, while it dropped to 107 tons/day during the second and third month after the end of the Tajogaite eruption. This average value continued decreasing during the fourth month of the post-eruptive phase, about 67 tons/day, and recently measurements provide an average SO2 emission value of 13 tons/day. These relatively low observed SO2 emissions during the post eruptive of the Tajogaite eruption phase seems to be clearly related to shallow magma cooling processes within the Tajogaite volcanic edificie.

Hayer, C., Barrancos, J., Burton, M., Rodríguez, F., Esse, B., Hernández, P., Melián, G., Padrón, E., Asensio-Ramos, M., and Pérez, N.: From up above to down below: Comparison of satellite- and ground-based observations of SO2 emissions from the 2021 eruption of Cumbre Vieja, La Palma, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12201, https://doi.org/10.5194/egusphere-egu22-12201, 2022.

Albertos, V. T., Recio, G., Alonso, M., Amonte, C., Rodríguez, F., Rodríguez, C., Pitti, L., Leal, V., Cervigón, G., González, J., Przeor, M., Santana-León, J. M., Barrancos, J., Hernández, P. A., Padilla, G. D., Melián, G. V., Padrón, E., Asensio-Ramos, M., and Pérez, N. M.: Sulphur dioxide (SO2) emissions by means of miniDOAS measurements during the 2021 eruption of Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5603, https://doi.org/10.5194/egusphere-egu22-5603, 2022.

How to cite: Rodríguez, O., Barrancos, J., Cutillas, J., Ortega, V., Hernández, P. A., Cabrera, I., and Pérez, N. M.: SO2 emissions during the post-eruptive phase of the Tajogaite eruption (La Palma, Canary Islands) by means of ground-based miniDOAS measurements in transverse mode using a car and UAV, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3620, https://doi.org/10.5194/egusphere-egu23-3620, 2023.

EGU23-3819 | Posters virtual | GI6.1

Using tunable diode laser (TDL) system in urban environments to measure anomalous CO2 concentrations: the case of Puerto Naos, La Palma, Canary Islands 

José Barrancos, Germán D. Padilla, Gladys V. Melián, Fátima Rodríguez, María Asensio-Ramos, Eleazar Padrón, Pedro A. Hernández, Jon Vilches Sarasate, and Nemesio M. Pérez

Carbon dioxide (CO2) is a colourless and odourless gas. It is non-flammable, chemically non-reactive and 1.5 times as heavy as air; therefore, may accumulate at low elevations. CO2 is a toxic gas at high concentration, as well as an asphyxiant gas (due to reduction in oxygen). Irritation of the eyes, nose and throat occurs only at high concentrations. Since the Tajogaite eruption ended on December 13, 2021, high concentrations of CO2 up to 20% (200.000 ppmv) have been observed inside of buildings of the neighborhoods of La Bombilla and Puerto Naos (La Palma, Canary Islands), which are located about 5 km distance from the Tajogaite eruption vent. Anomalous concentrations of CO2 are manily detected in the ground-floor and basement of the buildings in Puerto Naos, and the distribution of relatively high CO2 concentrations  is not homogeneous or uniform throughout the Puerto Naos area (Hernández P.A. et al, 2022).

The purpose of this study was to use the Tunable Laser Diode (TDL) absorption spectroscopy method to monitor the indoor CO2 concentration of the ground-floor of one of the buildings of Puerto Naos. A CO2-TDL was installed on 9 January 2022 and continues measuring the CO2 concentration along an optical path of about 6 meters. During the period January-March 2022, daily averages of CO2 concentrations from fifteen-minute data ranged from 5000 to 25000 ppmv reaching values up to 40000 ppmv (4%). Over time, a clear decreasing trend of the indoor CO2 concentration has been observed at this observation site and the daily CO2 averages from fifteen-minute data during the last 3 months (October-December 2022) ranged from 1000 to 2500 ppmv. This clear decreasing trend over time has not been observed at other observation sites where the concentration of CO2 inside buildings is being monitored. This observation indicates the complexity of the problem and the need to install a dense network of sensors to monitor CO2 for civil protection purposes.

 

Hernández, P. A., Padrón, E., Melián, G. V., Pérez, N. M., Padilla, G., Asensio-Ramos, M., Di Nardo, D., Barrancos, J., Pacheco, J. M., and Smit, M.: Gas hazard assessment at Puerto Naos and La Bombilla inhabited areas, Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7705, https://doi.org/10.5194/egusphere-egu22-7705, 2022.

How to cite: Barrancos, J., Padilla, G. D., Melián, G. V., Rodríguez, F., Asensio-Ramos, M., Padrón, E., Hernández, P. A., Vilches Sarasate, J., and Pérez, N. M.: Using tunable diode laser (TDL) system in urban environments to measure anomalous CO2 concentrations: the case of Puerto Naos, La Palma, Canary Islands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3819, https://doi.org/10.5194/egusphere-egu23-3819, 2023.

EGU23-3834 | Posters on site | GI6.1

Modeling outdoor dispersion of CO2 at Puerto Naos (La Palma, Canary Islands) 

Luca D Auria, Alba Santos, Pedro A. Hernández, Gladys V. Melián, Antonio J. Álvarez Díaz, María Asensio-Ramos, Alexis M. González Pérez, and Nemesio M. Pérez

The 2021 Tajogaite eruption in Cumbre Vieja volcano (La Palma, Canary Islands), which started on Sep. 19, 2021, and lasted 85 days, caused extensive damages because of the lava flows and ash fall. However, since the middle of Nov. 2021, some areas located about 5 km SW of the eruptive center started to be affected by intense diffuse CO2 emission. Among them are the urban centers of La Bombilla and Puerto Naos (Hernández et al., 2022). These emissions prevented the population of these two centers from returning to their houses because of high  concentrations of CO2 in indoor and outdoor environments.

In this work, we model the CO2 dispersion process in Puerto Naos to obtain hazard maps with the maximum CO2 concentrations which can be reached in the town in the outdoor environment. To achieve these results, we combined field observations with numerical modelling. Field surveys were realized in low wind conditions, measuring the CO2 concentration with portable sensors  at 15 and 150 cm from the ground at measurement points spaced approximately 10 m from each other along the streets of Puerto Naos.

We realized numerical modelling using the software TWODEE-2, a code for modeling the dispersion of heavy gases based on the solution of shallow water equations (Folch et al., 2009). For this purpose, we used a detailed digital topographic model, including the edifices of Puerto Naos. Using a trial-and-error approach, we determined the gas emission rates from a set of discrete source points in no-wind conditions. Subsequently, we repeated the numerical modelling, keeping the same sources and simulating all the realistic wind conditions in terms of direction and intensity. For each simulation, we determined the maximum CO2 concentration at different elevations from the ground. This allowed obtaining a hazard map with the maximum CO2 outdoor concentrations for each part of the town

The main results highlight that the outdoor environment is affected by a dense layer of CO2, whose flow is strongly conditioned by the urban infrastructures. Furthermore, we evidenced how even light winds can change the gas concentration pattern radically in a few minutes, evidencing the possibility of sudden changes in the CO2 concentration outdoors with no warning.

Folch A., Costa A., Hankin R.K.S., 2009. TWODEE-2: A shallow layer model for dense gas dispersion on complex topography, Comput. Geosci., doi:10.1016/j.cageo.2007.12.017

Hernández, P. A., Padrón, E., Melián, G. V., Pérez, N. M., Padilla, G., Asensio-Ramos, M., Di Nardo, D., Barrancos, J., Pacheco, J. M., and Smit, M.: Gas hazard assessment at Puerto Naos and La Bombilla inhabited areas, Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7705, https://doi.org/10.5194/egusphere-egu22-7705, 2022.

How to cite: D Auria, L., Santos, A., Hernández, P. A., Melián, G. V., Álvarez Díaz, A. J., Asensio-Ramos, M., González Pérez, A. M., and Pérez, N. M.: Modeling outdoor dispersion of CO2 at Puerto Naos (La Palma, Canary Islands), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3834, https://doi.org/10.5194/egusphere-egu23-3834, 2023.

EGU23-5223 | Orals | GI6.1

Event-oriented observation across scales and environmental systems: MOSES started operation. 

Ute Weber and Claudia Schuetze and the MOSES-Team

The novel observing system „Modular Observation Solutions for Earth Systems (MOSES)“, is an initiative of the Helmholtz Association of German Research Centers that aims at investigating the interactions of short-term events and long-term trends across environmental systems. MOSES is a mobile and modular infrastructure and its component measuring systems are managed by the participating research centers. By quantifying energy, water, nutrient and greenhouse gas states and fluxes during events such as heat waves, droughts, heavy precipitation, floods, rapid thaw of permafrost or of ocean eddies, and subsequently along the related event chains, the system delivers data to examine potential long-term impacts of these events and to gain a better understanding of extreme events that are expected to increase in frequency and intensity in a changing climate. In order to obtain comprehensive data sets, a cross-system approach is followed, covering the atmosphere, land surface and hydrosphere. These event-related data sets complement long-term and/or large scale data sets of established national and international monitoring programs and satellite data such as TERENO, ICOS, eLTER, SENTINEL, etc. After a 5-year setup period, MOSES was successfully put into operation in 2022 (Weber et al., 2022, https://doi.org/10.1175/BAMS-D-20-0158.1).

While long-term trends are typically assessed with stationary observation networks and platforms specifically designed for long-term monitoring, proven event-oriented observation systems and strategies are still missing. Event-oriented observation campaigns require a combination of a) measuring systems that can be rapidly deployed at “hot spots” and in “hot moments”, b) mobile equipment to monitor spatial dynamics in high-resolution, c) in situ measuring systems to record temporal dynamics in high-resolution, and d) interoperable measuring systems to monitor the interactions between atmosphere, land surface and hydrosphere. We will present the observation system and the observing strategy on examples from two past test campaigns: 1) The “Swabian MOSES campaign” of 2021 that captured the formation and evolution of supercells, hail and heavy precipitation and the resulting local flash floods (Kunz et al., 2022, https://doi.org/10.3389/feart.2022.999593). 2) The MOSES campaign of 2019 that captured the historical low flow situation along the Elbe River and into the German Bight (e.g., Kamjunke et al., 2021, https://doi.org/10.1002/lno.11778). As an outlook, upcoming national and international campaigns and potential future deployments will be presented.

How to cite: Weber, U. and Schuetze, C. and the MOSES-Team: Event-oriented observation across scales and environmental systems: MOSES started operation., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5223, https://doi.org/10.5194/egusphere-egu23-5223, 2023.

EGU23-5684 | ECS | Posters on site | GI6.1

Random Forest Classification of Proterozoic and Paleozoic rock types of Tsagaan-uul area, Mongolia 

Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, and Gáspár Albert

The Tsagaan-uul area of the Khatanbulag ancient massif in the Central Asian Orogenic Belt is located in the southern part of Mongolia, which belongs to the Gobi Desert. It has a low vegetation cover, and because of this, remotely sensed data can be used without difficulty for geological investigations. Factors such as sparse population and underdeveloped infrastructure in the region further create a need for combining traditional geological mapping with remote sensing technologies. In existing geology maps of the area, the formations are lithologically very diverse and their boundaries were mapped variously, so a need for a more precise lithology-based map arouse.

This study investigated combinations of fieldwork, multispectral data, and petrography for the rock type classification. A random forest classification method using multispectral Sentinel-2A data was employed in order to distinguish different rocks within Proterozoic Khulstai (NP1hl) metamorphic complex, which is dominated by gneiss, andesite, sandstone, limestone, amphibolite, as well as the Silurian terrigenous-carbonate Khukh morit (S1hm) formation, Tsagaan-uul area. Based on the ground samples collected from field surveys, ten kinds of rock units plus Quaternary sediments were chosen as training areas. In addition, morphometric parameters derived from SRTM data and band ratios used for iron-bearing minerals from Sentinel 2 bands are selected as variables in the accuracy of classification. The result showed that gneisses were recognized with the highest accuracy in the Khulstai complex, and limestones and Quaternary sediments were also well predicted. Moreover, the tectonic pattern was also well recognized from the results and compared to the existing maps provided a more detailed geological image of the area. This study emphasized the need for samples as baseline data to improve the machine learning methods, and the method provides an appropriate basis for fieldwork.

 

How to cite: Badrakh, M., Tserendash, N., Choindonjamts, E., and Albert, G.: Random Forest Classification of Proterozoic and Paleozoic rock types of Tsagaan-uul area, Mongolia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5684, https://doi.org/10.5194/egusphere-egu23-5684, 2023.

EGU23-5689 | Posters on site | GI6.1

Post-earthquake geoenvironmental changes in landslide-affected watersheds in Atsuma, Hokkaido (Japan) 

Yuichi S. Hayakawa, Tennyson Lo, Azim Zulhilmi, Xinyue Yu, and Xiaoxiao Wang

Following drastic changes in geoenvironmental components by coseismic landslides in mountainous watersheds, more gradual changes can be observed in the elements, including bare-land surface conditions, sediment connectivity, and vegetation recovery on sloping terrains. Such geoenvironmental changes may continue for years to decades, with complex interrelationships among various geomorphological and ecological factors. Their assessments are also crucial for local to regional environmental management. After the occurrence of numerous coseismic landslides triggered by the 2018 Hokkaido Eastern Iburi Earthquake in northern Japan, geomorphological and geoecological changes were explored using optical and laser sensors on uncrewed aerial systems. Morphological characteristics of the landslide-affected slopes in the watersheds were assessed with structure-from-motion multi-view stereo photogrammetry and light detection and ranging topographic datasets, while vegetation recovery on the slopes was examined with visible-light and near-infrared images. Although spatial relationships among morphological developments, sediment mobility, and vegetation recovery were not clearly observed, their general temporal trends may be correspondent. Dominant processes affecting the morphological developments are supposed to be frost heave in the cold climate and non-frequent high-intensity rainfalls, and these can be conditioning vegetation growth. Such local changes will be further examined on a wider, regional scale. 

How to cite: Hayakawa, Y. S., Lo, T., Zulhilmi, A., Yu, X., and Wang, X.: Post-earthquake geoenvironmental changes in landslide-affected watersheds in Atsuma, Hokkaido (Japan), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5689, https://doi.org/10.5194/egusphere-egu23-5689, 2023.

EGU23-5750 | Posters on site | GI6.1

Aseismic creep and coseismic dislocation at an active fault in volcanic area: the case of Ischia Island 

Stefano Carlino, Nicola Alessandro Pino, Lisa Beccaro, and Prospero De Martino

Understanding the fault dynamics in volcanic areas is not a simple task, mainly due to both the heterogeneity of volcanic structures and the local stress distribution. The presence of high temperature-high pressure geothermal fluids and relative high strain rates, and the occurrence of viscous processes in the deeper part of the volcano further contribute to generate complex patterns of strain load and release, possibly with aseismic creep and differential movements along the faults.

We present the case of an active fault located Casamicciola Terme town – in northern area of the volcanic caldera of Ischia Island (Southern Italy) – where repeated destructive earthquakes occurred at least since 1769, even causing thousands of victims in a single event, with the last one striking in 2017. To assess a possible mechanism leading to the activation of the Ischia main seismogenic fault, its cyclic nature and the related hazard, we performed a joined analysis of the ground vertical movements, obtained from cGPS (2001-present), DInSAR (2015-2018) time-series, and levelling data of the island (1987-2010). The geodetic data indicate that Casamicciola seismogenic fault is characterized by a complex dynamic, with some pre- and post-seismic aseismic dislocation, along sectors that move differentially, in response to the long-term subsidence of the island. Based on the ground deformation rate and on the distribution of degassing areas, we speculate that fluid pressure variations may have a major role in modulating the apparent non-stationarity of the Ischia stronger earthquakes. Furthermore, we suggest that a punctual monitoring of the distribution in space and time of the aseismic creep could provide clues on the state of strain of the seismogenic fault.

How to cite: Carlino, S., Pino, N. A., Beccaro, L., and De Martino, P.: Aseismic creep and coseismic dislocation at an active fault in volcanic area: the case of Ischia Island, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5750, https://doi.org/10.5194/egusphere-egu23-5750, 2023.

EGU23-6832 | ECS | Orals | GI6.1

Quantifying karstic geomorphologies using Minkowski tensors and graph theory: Applications to SLAM Lidar data from carbonate caves in Northern Bavaria (Germany) 

Rahul Prabhakaran, Ruaridh Smith, Daniel Koehn, Pierre-Olivier Bruna, and Giovanni Bertotti

Karstification is a ubiquitous feature in carbonate rocks. The origins can be hypogenic or epigenic based on the source of the reacting fluids. The presence of karstified lithologies and their spatial heterogeneity poses a major risk in subsurface energy utilization goals (hydrocarbons, geothermal etc). Such dissolution features tend to organize as spatial networks, with their evolution controlled by a complex interplay of several factors, including natural mineralogical variations in host rocks, effects of pre-existing structures, directional history of palaeo-flow paths, and competition between convective transport and dissolution. Accurate quantification of the spatial distribution of karst is difficult owing to resolution issues in 3D data such as seismic and ground penetrating radar. Recent advances in Simultaneous Location and Mapping (SLAM) Lidar technology have made possible to acquire karst cave passage geometries at very high-resolution with relative ease compared to conventional terrestrial lidar. In this contribution, we present a unique dataset of more than 80 caves, scanned using SLAM lidar, in Jurassic carbonates from northern Bavaria, Germany. We introduce a methodology for robustly deriving morphometrics of karstic caves using Minkowski tensors and spatial graph theory. The method is based on a combination representation of cave passage skeletons as spatial graphs and 2D passage cross-sections using Minkowski functionals. The enriched topological representation enables detailed analysis of internal spatial variation within a single cave and also comparison with cave geometries from other caves. We derive a typology of cave systems based on the degree of structural control on karstification using the database.

How to cite: Prabhakaran, R., Smith, R., Koehn, D., Bruna, P.-O., and Bertotti, G.: Quantifying karstic geomorphologies using Minkowski tensors and graph theory: Applications to SLAM Lidar data from carbonate caves in Northern Bavaria (Germany), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6832, https://doi.org/10.5194/egusphere-egu23-6832, 2023.

EGU23-7265 | Posters on site | GI6.1

Low Power, Rugged Edge Computing provides a low cost, powerful solution for on the ground remote sensing in extreme environments 

Nicholas Frearson, Terry Plank, Einat Lev, LingLing Dong, and Conor Bacon

Ground based remote sensing devices increasingly incorporate low cost single board computers such as a Raspberry Pi to capture and analyze images and data from the environment. Useful and cheap as these devices are, they are not designed for use in extreme conditions and as a consequence often suffer from early failure. Here we describe a system that incorporates a commercially available rugged Edge Computer running embedded Linux that is designed to operate in remote and extreme environments. The AVERT system  (Anticipating Volcanic Eruptions in  Real Time) developed at Columbia University in New York and funded by the Moore Foundation uses solar and wind powered Sensor nodes configured in a spoke and hub architecture currently operating on two volcanoes overseen by the Alaska Volcano Observatory in the Aleutian Islands, Alaska. Multiple Nodes distributed around the volcanoes are each controlled by an Edge Computer which manages and monitors local sensors, processes and parses their data via radio link to a central Hub and schedules system components to wake and sleep to conserve power. The Hub Edge Computer collects and assembles data from multiple Nodes and passes it via satellite, cellular modem or radio links to servers located elsewhere in the world or cloud for near real-time analysis. The local computer enables us to minimize local power demand to just a few watts in part due to the extremely low power sleep modes that are incorporated into these devices. For instance, a Node incorporating a webcam, IRCam, weather station, Edge Computer, network switch, communications radio and power management relays draws only 4.5W on average. In addition, this level of local computing power and a mature Linux operating environment enables us to run AI algorithms at source that process image and other data to flag precursory indicators of an impending eruption. This also helps to reduce data volume passed across the network at times of low network connectivity. We can also remotely interrogate any part of the system and implement new data schemes to best monitor and react to ongoing events. Future work on the AI algorithm development will incorporate local multisensor data analytics to enhance our anticipatory capability.

How to cite: Frearson, N., Plank, T., Lev, E., Dong, L., and Bacon, C.: Low Power, Rugged Edge Computing provides a low cost, powerful solution for on the ground remote sensing in extreme environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7265, https://doi.org/10.5194/egusphere-egu23-7265, 2023.

EGU23-8673 | Orals | GI6.1

Are they radon or random signals? Analysis of time series of 222Rn activity concentrations in populated areas of La Palma (Canary Islands, Spain) 

Antonio Eff-Darwich, Germán D. Padilla, José Barrancos, José A. Rodríguez-Losada, Pedro A. Hernández, Nemesio M. Pérez, Antonio J. Álvarez Díaz, Alexis M. González Pérez, Jesús García, José M. Santana, and Eleazar Padrón

Radon, 222Rn, is a radioactive constituent of the surface layer of the atmosphere. The analysis of the temporal and spatial variations in the flux of radon across the soil–air interface is a promising tool to study geo-dynamical processes. However, many of these variations are induced by external variables, such as temperature, barometric pressure, rainfall, or the location of the instrumentation, among others.

Anomalous CO2 degassing has been observed since the end of November 2021 in the neighborhoods of La Bombilla and Puerto Naos, located in the western flank of La Palma, about 5 km distance southwestern of the 2021 Tajogaite eruption vents (Hernández et al. 2022). In order to complement these observations with other independent parameters, a set of radon monitoring stations have been deployed in that area. In an attempt to filter out non-endogenous variations in the radon signal, we have implemented time-series numerical filtering techniques based on multi-variate and frequency domain analysis. A background level for radon emissions at various locations could therefore be defined, by which correlations between radon concentration, gaseous emissions and dynamical processes could be carried out. Some preliminary results corresponding to the first 3 months of data (october-december 2022) are presented.

Hernández, P. A., Padrón, E., Melián, G. V., Pérez, N. M., Padilla, G., Asensio-Ramos, M., Di Nardo, D., Barrancos, J., Pacheco, J. M., and Smit, M.: Gas hazard assessment at Puerto Naos and La Bombilla inhabited areas, Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7705, https://doi.org/10.5194/egusphere-egu22-7705, 2022.

How to cite: Eff-Darwich, A., Padilla, G. D., Barrancos, J., Rodríguez-Losada, J. A., Hernández, P. A., Pérez, N. M., Álvarez Díaz, A. J., González Pérez, A. M., García, J., Santana, J. M., and Padrón, E.: Are they radon or random signals? Analysis of time series of 222Rn activity concentrations in populated areas of La Palma (Canary Islands, Spain), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8673, https://doi.org/10.5194/egusphere-egu23-8673, 2023.

EGU23-8795 | ECS | Orals | GI6.1

Integration of Seismic and Quasi-Static Signals for Improved Volcanic Monitoring 

Joe Carthy, Alejandra Vásquez Castillo, Manuel Titos, Luciano Zuccarello, Flavio Cannavò, and M. Carmen Benitez

The time scale of ground displacement at volcanoes varies between short, sub second seismic events, to days, months or even years. This study is focused on data from seismic and GNSS stations located around Mount Etna. The GNSS and seismic stations operate at different time scales. Data from these different time scales is extracted and combined in order to better understand the subsurface dynamics. The overall aim of this research is to improve volcanic forecasting and monitoring. It does this in a novel way by applying signal processing and machine learning techniques to the rich dataset.

Mount Etna offers an interesting case study as it is a widely monitored volcano with a variety of sensors and with a rich pool of data to analyse. Additionally the volcanic dynamics at Mount Etna are complex. This is a volcano where there is a variety of different sub-surface dynamics due to the movement of both deep and shallow magma. This allows for rich insights to be drawn through the combination of different signal types.

This study looks at combining the information obtained from the seismic array at Mount Etna, with the information obtained from various GNSS stations on the volcano. The seismic array has been able to capture ground velocity data in the frequency range 0.025 Hz to 50 Hz from a range of stations at different locations across the volcano. The GNSS stations measure ground displacement with a sampling frequency of 1 Hz, and they allow for longer term ground dynamic analysis.

We analyse different seismic events, and relate the type and number of the seismic events to the long term ground deformation that we see in the recorded GNSS data. Where links between the two signal types have been identified, research is ongoing to establish a direct connection with known volcanic activity on Mount Etna. This will help establish what the relationship that we are seeing signifies. This integration of data from different types of sensors is a significant step into bridging the gap between seismic and quasi-static ground displacement at active volcanoes and should open the path toward more in depth volcanic monitoring and forecasting.

How to cite: Carthy, J., Vásquez Castillo, A., Titos, M., Zuccarello, L., Cannavò, F., and Benitez, M. C.: Integration of Seismic and Quasi-Static Signals for Improved Volcanic Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8795, https://doi.org/10.5194/egusphere-egu23-8795, 2023.

EGU23-10069 | ECS | Orals | GI6.1

Vredefort impact site modelling through inhomogeneous depth weighted inversion. 

Andrea Vitale and Maurizio Fedi

We are showing an application of the 3D self-constrained depth weighted inversion of the inhomogeneous gravity field (Vitale and Fedi, 2020) of the Vredefort impact site.

This method is based on two steps, the first being the search in the 3D domain of the homogenous degree of the field, and the second being the inversion of the data using a power-law weighting function with a 3D variable exponent. It does not involve directly data at different altitudes, but it is heavily conditioned by a multiscale search of the homogeneity degree.

The main difference between this inversion approach and the one proposed by Li and Oldenburg algorithm (1996) and Cella and Fedi (2012) is therefore about the depth weighting function, whose exponent is a constant through the whole space in the original Li and Oldenburg and Cella and Fedi approaches, while it is a 3D function in the method which we will discuss here.

The model volume of the area reaches 20 km in depth, while along x and y its extension is respectively 41 by 63 km. The trend at low and middle altitudes of the estimated β related to the main structures is fitting the expectations because the results relate to two main structures, which are geometrically different: the core is like a spheroid body (β ≈ 3) and the distal rings are like horizontal pipes or dykes (1 < β < 2).

With a homogeneous depth weighting function, we recover a smooth solution and both the main sources, the main core and the rings of the impact, are still visible at the bottom of the model (20 km). This is not in agreement with the result by Henkel and Reimold (1996, 1998), which, based on gravity and magnetic inversion supported by seismic data, proposed a model where the bottom of the rings is around 10 km and the density contrast effect due to the core structure loses its effectiveness around 15 km.

Instead, using an inhomogeneous depth weighting function (figure 28) we can retrieve information regarding the position at depth of both core and distal ring structures that better fits the above model. In fact, the bottom of the distal ring structure, that should be around 10 km according to Henkel and Reimold (1996, 1998), is recovered very well using an inhomogeneous depth weighting function, while in the homogeneous case we saw that the interpreted structure was still visible at large depths.

In addition, also the core structure is shallower compared to the homogeneous approach and seems more reliable if we compare it with the model of Henkel and Reimold (1996, 1998).

Instead, the inhomogeneous approach presented in this paper leads naturally us to a better solution because it takes into account during the same inversion process of the inhomogeneous nature of the structural index within the entire domain.

How to cite: Vitale, A. and Fedi, M.: Vredefort impact site modelling through inhomogeneous depth weighted inversion., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10069, https://doi.org/10.5194/egusphere-egu23-10069, 2023.

EGU23-11065 | ECS | Posters on site | GI6.1

The Dynamics of Climate Change Science and Policy in Panama: A Review 

Gustavo Cárdenas-Castillero, Steve Paton, Rodrigo Noriega, and Adriana Calderón

The local studies and reports indicate that the temperature of Panama has increased by approximately 1°C since the 1970s. More evidence shows a constantly rising sea level in the Guna Yala archipelago, coral bleaching on both coasts, and increasingly more frequent and extreme precipitation events throughout Panama. This study includes an analysis of over 400 scientific publications made by researchers from multiple centres and more than 20 Panamanian official reports due to Panama's mandate and duties under the international climate accords. To summarise the results, the studies were gathered according to the climate change effects by Panamanian locations and analysed posteriorly using Rstudio and ArcMAP. The results indicate a significant increase in climate change research beginning in 2007.

This study identified and examined the essential findings per hydroclimatic region, showing the trends, limitations, collaborations, and international contributions. Climate change research in Panama includes some of the longest-term meteorological, hydrological, oceanographic, and biological studies in the neotropics. The most significant number of identified climate change-related studies were conducted, at least in part, in the Barro Colorado Natural Monument located in central Panama. Other frequently used sites include Metropolitan Natural Park, Soberania Park, the Panama Canal Watershed and the Caribbean coast of Colón and Bocas del Toro, primarily due to research conducted by Smithsonian Tropical Research-affiliated investigators. The tropical forests of Panama are some of the bests studied in the world; however, research has been concentrated in a relatively small number of locations and should be expanded to include additional areas to achieve a more complete and comprehensive understanding of climate change will impact Panama in the future.

How to cite: Cárdenas-Castillero, G., Paton, S., Noriega, R., and Calderón, A.: The Dynamics of Climate Change Science and Policy in Panama: A Review, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11065, https://doi.org/10.5194/egusphere-egu23-11065, 2023.

EGU23-12050 | Orals | GI6.1

Stress field analysis from induced earthquakes caused by deep fluid injection: the 2013 St. Gallen (Switzerland) seismic sequence. 

Bruno Massa, Guido Maria Adinolfi, Vincenzo Convertito, and Raffaella De Matteis

The city of St. Gallen is located in the Molasse Basin of northeast Switzerland. Mesozoic units of the substratum are affected by a fault system hosting a hydrothermal reservoir. In 2013 a deep geothermal drilling project started in an area close to the city. During a phase of reservoir stimulation, a sequence of more than 340 earthquakes was induced with a maximum magnitude ML 3.5. Stress inversion of seismological datasets became an essential tool to retrieve the stress field of active tectonics areas. With this aim, a dataset of the best constrained Fault Plane Solutions (FPSs) was processed in order to qualitatively retrieve stress-fields active in the investigated volume. FPSs were obtained by jointly inverting the long-period spectral-level P/S ratios and the P-wave polarities following a Bayesian approach (BISTROP). Data were preliminarily processed by the Multiple Inverse Method to evaluate the possible dataset heterogeneity and separate homogeneous FPS populations. The resulting dataset was then processed using the Bayesian Right Trihedra Method (BRTM). Considering that hypocentral depths range between 4.1 and 4.6 km b.s.l., in order to emphasize depth-related stresses, we performed a first step of raw stress inversion procedure splitting the data into five subsets, grouping events located inside 100-m depth ranges. Once the presence of stress variations with depth has been excluded, the second step of fine stress inversion procedure was performed on the entire dataset. The stress-inversion procedure highlights an active stress field dominated by a well-constrained NE low-plunging σ3 and a corresponding NW low-plunging σ1. The corresponding Bishop ratio confirms the stability of the retrieved attitudes. Results are in good accordance with the regional stress field derived from regional natural seismicity. Additionally, the retrieved, dominant, stress field is coherent with the regional tectonic setting.

This research has been supported by PRIN-2017 MATISSE project (No. 20177EPPN2).

How to cite: Massa, B., Adinolfi, G. M., Convertito, V., and De Matteis, R.: Stress field analysis from induced earthquakes caused by deep fluid injection: the 2013 St. Gallen (Switzerland) seismic sequence., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12050, https://doi.org/10.5194/egusphere-egu23-12050, 2023.

EGU23-13693 | ECS | Orals | GI6.1

Assessing the transfer factors (TFs) of contaminants from soil to plants: the case study of Campania region (Southern Italy) 

Lucia Rita Pacifico, Annalise Guarino, Gianfranco Brambilla, Antonio Pizzolante, and Stefano Albanese

The presence of potentially toxic elements (PTEs) derived from anthropogenic sources in soil represents a serious issue for animal and human health. These elements can easily move from the geological compartment to the biological compartment through to the food chain. (Jarup, 2003).

The geochemical knowledge of a territory allows to assess the degree of contamination of the environment, to locate the sources of environmental hazard and, possibly, to manage the anomalous concentrations of the PTEs in environmental matrices with the purpose of eliminating or minimizing their negative impact on the health of living beings. (Reimann et al. 2005).

Several studies have been already carried out to determine the distribution patterns of PTEs in the soil of Campania region (Southern Italy) (De Vivo et al., 2022) but little is known about the transfer processes of contaminants from soils to agricultural products.

In light of above, we present the results of a new study whose purpose was to determine the Transfer Factors (TFs) of PTEs from soil to a series of agricultural products commonly grown in Campania.

Considering the complex geological and geomorphological settings of the region and the diffuse presence of an historical anthropization related to the industry, agriculture, and urbanization, TFs were calculated for a relevant number of fruit and vegetable samples (3731 specimens). They were collected across the whole regional territory to detect differences between analysed species and to highlight the spatial changes in TFs occurring for individual species.

The TFs were calculated starting from the quasi-total (based on Aqua Regia leaching) and bioavailable (based on Ammonium Nitrate leaching) concentrations of PTEs in 7000 and 1500 soil samples, respectively.

Preliminary results show that TFs determined for the various agricultural species vary in space and in amount independently from the original elemental concentrations in soils. High values of TFs are found in areas where PTE concentrations in soil are low and vice versa, thus suggesting that multiple regression and multivariate analyses could be performed to investigate if some additional chemical and physical characteristics of soil (pH, grainsize, OM, etc.) could have a relevant weight on the transfer processes of contaminant from the soil to the plant life.

 

References

Järup L. 2003. Hazards of heavy metal contamination. Br. Med. Bull. 68, 167–182.

Reimann C., de Caritat P. 2005. Distinguishing between natural and anthropogenic sources for elements in the environment: regional geochemical surveys versus enrichment factors. Science of The Total Environment, Volume 337, Issues 1–3, pages 91-107.

De Vivo B. et al. 2022. Monitoraggio geochimico-ambientale dei suoli e dell'aria della Regione Campania. Piano Campania trasparente. Volume 4. Aracne Editore, Genzano di Roma.

How to cite: Pacifico, L. R., Guarino, A., Brambilla, G., Pizzolante, A., and Albanese, S.: Assessing the transfer factors (TFs) of contaminants from soil to plants: the case study of Campania region (Southern Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13693, https://doi.org/10.5194/egusphere-egu23-13693, 2023.

EGU23-13853 | Posters on site | GI6.1

Analysis and Modelling of 2009-2013 vs. 2019-2022 Unrest Episodes at Campi Flegrei Caldera 

Raffaele Castaldo, Andrea Barone, De Novellis Vincenzo, Pepe Antonio, Pepe Susi, Solaro Giuseppe, Tizzani Pietro, and Tramelli Anna

Geodetic modelling is a significant procedure for detecting and characterizing unrest and eruption episodes and it represents a valuable tool to infer volume and geometry of volcanic source system.

In this study, we analyse the 2009–2013 and the ongoing 2019-2022 uplift phenomena at Campi Flegrei (CF) caldera in terms of spatial and temporal variations of the stress/strain field. In particular, we investigate the characteristics of the inflating sources responsible of these main deformation unrests occurred in the last twenty years. We separately perform for the two considered periods a 3D stationary Finite Element (FE) modelling of geodetic datasets to retrieve the geometry and location of the deformation sources. The geometry of FE domain takes into account both the topography and the bathymetry of the whole caldera. For what concern the definition of domain elastic parameters, we take into account the Vp/Vs distribution from seismic tomography. In order to optimize the nine model parameters (center coordinates, sferoid axes, dip, strike and over-pressure), we use the statistical random sampling Monte Carlo method by exploiting both geodetic datasets: the DInSAR measurements obtained from the processing of COSMO-SkyMed and Sentinel-1 satellite images. The modelling results for the two analysed period are compared revealing that the best-fit source is a three-axis oblate spheroid ~3.5 km deep, similar to a sill-like body. Furthermore, in order to verify the reliability of the geometry model results, we calculate the Total Horizontal Derivative (THD) of the vertical velocity component and compare it with those performed directly on the two DInSAR dataset.

Finally, we compare the modelled shear stress with the natural seismicity recorded during the 2000-2022 period, highlighting high values of modelled shear stress at depths of about 3.5 km, where high-magnitude earthquakes nucleate.

How to cite: Castaldo, R., Barone, A., Vincenzo, D. N., Antonio, P., Susi, P., Giuseppe, S., Pietro, T., and Anna, T.: Analysis and Modelling of 2009-2013 vs. 2019-2022 Unrest Episodes at Campi Flegrei Caldera, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13853, https://doi.org/10.5194/egusphere-egu23-13853, 2023.

EGU23-15127 | ECS | Orals | GI6.1

Multiscale magnetic modelling in the ancient abbey of San Pietro in Crapolla 

Luigi Bianco, Maurizio Fedi, and Mauro La Manna

We present a multiscale analysis of magnetic data in the archaeological site of San Pietro in Crapolla (Massa Lubrense, near Naples, Italy). The site consists of the ruins of an ancient abbey. We computed the Wavelet Transform of the Gradiometric measurements and decomposed the data at different scales and positions by a multiresolution analysis, allowing an effective extraction of local anomalies. Modelling of the filtered anomalies was performed by multiscale methods known as “Multiridge analysis” and “DEpth from eXtreme Points (DEXP)”.  The first method analyses a multiscale dataset at the zeroes of the first horizontal and vertical derivatives besides the potential field data themselves (ridges).  The Wavelet Transform Modulus Maxima  lines converged to buried remains. The field, scaled by a power law of the altitude (DEXP transformation) allowed estimates of source depths at its extreme points. The depth estimations for the buried structures obtained from the two methods are very close each other and fairly agree with those from the modelling of GPR anomalies. On the basis of these results, an archaeological excavation followed our indications and brought to light ancient walls.

How to cite: Bianco, L., Fedi, M., and La Manna, M.: Multiscale magnetic modelling in the ancient abbey of San Pietro in Crapolla, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15127, https://doi.org/10.5194/egusphere-egu23-15127, 2023.

EGU23-15190 | Orals | GI6.1

Synthetic aperture radar burst overlapped interferometry for the analysis of large ground instabilities: Experiments in volcanic regions. 

Antonio Pepe, Andrea Barone, Pietro Mastro, Pietro Tizzani, and Raffaele Castaldo

This work presents an overview of some applications of synthetic aperture radar (SAR) interferometry technology for the detection and analysis of large ground displacements occurring in volcanic areas, with the aim to retrieve the three-dimensional (3-D) ground displacement field (up-down, east-west, north-south). Specifically, the work summarizes and investigates the potential of Bursted Overlapped Interferometry (BOI) that properly combined can allow the retrieval, at different scales of resolution and accuracies, of the north-south components of the ground deformations, which are usually not available considering conventional SAR interferometry techniques. In this context, the almost global coverage and the weekly revisit times of the European Copernicus Sentinel-1 SAR sensors permit nowadays to perform extensive analyses with the aim to assess the accuracy of the BOI techniques. More recently, Spectral Diversity (SD) methods have been exploited for the fine co-registration of SAR data acquired with the Terrain Observation with Progressive Scans (TOPS) mode. In this case, considering that TOPS acquires images in a burst mode, there is an overlap region between consecutive bursts where the Doppler frequency variations is large enough to allow estimating and compensating for, with great accuracy, potential bursts co-registration errors. Additionally, and more importantly, in the case of non-stationary scenarios, it allows detecting the ground displacements occurring along the azimuthal directions (almost aligned along north-south) with centimeter accuracy. This is done by computing the difference between the right and left interferograms, i.e., the burst overlapped interferogram, and relating it to the ongoing deformation signals.

This work aims to apply the BOI technique in selected volcanic and seismic areas to evaluate the impact of this novel technology for the analysis of quantifying, over small, covered regions, the accumulated ground displacements in volcanic areas. In such regions, the interest is on quantifying the accuracy of integrated BOI systems for the retrieval of 3-D displacements. To this aim, we selected as a test site the Galapagos Island and we analyze with BOI the north-south ground displacements. At the next EGU symposium, the results of the BOI analyses will be presented, thus also providing comparative analyses with the results obtained from the use of potential field method applied on the ground displacements in volcanic areas. More specifically, by adopting this technique, we are able to estimate independently the north-south components of the ground displacement by exploiting the harmonic properties of the elasticity field.

How to cite: Pepe, A., Barone, A., Mastro, P., Tizzani, P., and Castaldo, R.: Synthetic aperture radar burst overlapped interferometry for the analysis of large ground instabilities: Experiments in volcanic regions., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15190, https://doi.org/10.5194/egusphere-egu23-15190, 2023.

EGU23-16132 | ECS | Orals | GI6.1

Multiscale imaging of low-enthalpy geothermal reservoir of the Phlegraean Fields caldera from gravity and resistivity data. 

Maurizio Milano, Giuseppe Cavuoto, Alfonso Corniello, Vincenzo Di Fiore, Maurizio Fedi, Nicola Massarotti, Nicola Pelosi, Michele Punzo, Daniela Tarallo, Gian Paolo Donnarumma, and Marina Iorio

The central‐eastern sector of the Phlegraean Fields caldera, southern Italy, is one of the most intensely studied and monitored volcanic active area of the word. This area reveals typical characters of a high‐ enthalpy geothermal systems. However, recently the presence of two different geothermal reservoirs has been outlined: one located in the central sector dominated by highly active vapours generated by episodic arrival of CO2‐rich magmatic fluids and the other one located in the eastern sector (Agnano zone) characterized by a shallow (400-500 m b.s.l.) still hot reservoir, heated by the upward circulation of deep no magmatic hot vapor.

In this study we present preliminary results deriving from the integration of different geophysical surveys carried out in the Agnano plain area, in the frame of the GEOGRID research project. We acquired high-resolution gravity data along two parallel profiles and we investigated the depth, shape and density contrast of the subsurface structures by the CompactDEXP (CDEXP) method, a multiscale iterative imaging technique based on the DEXP method. The resulting density models, together with DC resistivity and stratigraphic data, outlines the presence of a complex morphology of the Agnano subsoil characterized by a horst-graben structure. The importance of the structural lines identified by geophysical data, is also confirmed by the alignment of correlate outcropping thermal waters.

How to cite: Milano, M., Cavuoto, G., Corniello, A., Di Fiore, V., Fedi, M., Massarotti, N., Pelosi, N., Punzo, M., Tarallo, D., Donnarumma, G. P., and Iorio, M.: Multiscale imaging of low-enthalpy geothermal reservoir of the Phlegraean Fields caldera from gravity and resistivity data., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16132, https://doi.org/10.5194/egusphere-egu23-16132, 2023.

EGU23-4057 | ECS | Orals | GI6.2

Mapping of Soils Salinity with Landsat 8 OLI Imagery and Random Forest Algorithm 

Teng Zhang, Zhongjing Wang, Yingfu Tang, and Yujia Shi

Soil salinity mapping is essential for sustainable land development and water resources management. In situ sampling is time-consuming, laborious, and restricted by geographical conditions. Therefore, an efficient and accurate model is necessary to monitor and assess the spatio-temporal dynamic salinization at regional a scale. In this study, Shule River Basin (SLRB) is taken as an example to develop the soil salinity mapping model based on Landsat 8 OLI images using random forest (RF) algorithms. A series of extended soil salinity indexes (ESSIs) were generated by combining any two, three, or four spectral bands were combined in expressions that include one or more of the arithmetic operations: addition, subtraction, multiplication, division, square and rooting form. The features selected from ESSIs outperformed the features selected from soil salinity indexes (SSIs) used in references. The best selected indexes are (B7^2-B5^2)^0.5, (B4^2+B5^2-B6^2)^0.5, (B1*B5-B4*B6/(B1*B5+B4*B6))^0.5,(B2*B6-B3*B7/( B2*B6+B3*B7))^0.5. In addition, three partition sampling methods of the training set and validation set for long-tail distribution problems are compared. The results showed that the resampling method considering the long-tail distribution performs better than systematic resampling and random k-fold cross-validation. The regional soil salinity mapping results showed that most areas are seriously salt-affected in the whole basin, especially along the river and the southeast mountainous area, where the soil salinity classes are highly and even over-extremely saline. This study could have implications for agricultural schemes planning and salinization control.

How to cite: Zhang, T., Wang, Z., Tang, Y., and Shi, Y.: Mapping of Soils Salinity with Landsat 8 OLI Imagery and Random Forest Algorithm, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4057, https://doi.org/10.5194/egusphere-egu23-4057, 2023.

EGU23-4412 | ECS | Orals | GI6.2

An Application of UAV in Open-pit Gold Deposit Geological Field Mapping 

Jiayi Wang, Kunfeng Qiu, and Jianan Fu

Unmanned Aerial Vehicle (UAV) can greatly improve the geological field mapping. However, applications of UAV in the investigations of the deposit still remain to be explored. The Liba gold deposit, located at the Li-Min gold belt to the western Qinling orogenic belt, is a typical open-pit gold deposit. The associated (local) landscape and geomorphology provide an excellent natural laboratory to explore the UAV in deposit field mapping. Here, UAV-based photogrammetry was performed to get the aerial photos across the mining area, as well asoutcrop information from the Liba gold mine. In the combination with a detailed field work, alteration zones with the regional faults can be efficiently interpreted and evaluated, both from the macro- to micro scale. According to the work, we established a general working flow of the usage of UAV deposit field exploration to improves the field work. By demonstrating the UAV-based technical applied in Liba, this work can strongly promote the understanding and interpretation of regional geology during the field work.

Key words: Open-pit Gold Deposit, Liba gold deposit, UAV-drone photogrammetry, Geological field mapping

How to cite: Wang, J., Qiu, K., and Fu, J.: An Application of UAV in Open-pit Gold Deposit Geological Field Mapping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4412, https://doi.org/10.5194/egusphere-egu23-4412, 2023.

EGU23-4516 | Posters on site | GI6.2

Drones Paired with Hyperspectral Imaging Paired with LiDAR to Locate Explosive Ordnance 

Alexandra Restrepo, Aya Labnine, Rocco DiMatteo, Colin Edwards, Jamali Hamilton, Luis Quinto, Madison Tuohy, Alex Nikulin, and Timothy S. de Smet

Anti-personal/tank landmines, improvised explosive devices (IED), unexploded ordinances (UXO), and other abandoned explosive ordinances (EO) all pose long-lasting threats that are detrimental to areas of conflict. From 2015 to 2021, a total of 49,050 deaths/injuries were caused by EOs, and this number is only increasing. Current demining methods heavily rely on ground-based electromagnetic-induction (EMI); however, this method is costly, time consuming and puts personnel at risk. Recent advances in drone and remote sensing technology have allowed for the development of alternative remote methods to improve the efficiency in locating EOs. We used a Velodyne VLP-16 light detection and ranging (LiDAR) sensor attached to a DJI Matrice 600 drone platform to remotely identify EOs, specifically PFM-1 and VPMA-3 anti-personnel mines, TM-62M anti-vehicle mines, and 3 meter long 122 mm multibarrel rockets (MBRL). LiDAR data was acquired in dual return acquisition mode at 300 rpm and a flight speed of 1 m/s. Several of these EOs are being used in the current Russo-Ukrainian war, including: TM-62 anti-vehicle mines, PFM-1 landmines, and the MBRL rockets. Our LiDAR sensor was calibrated with a 18 m swath width to acquire 4630 points/m2  density and a 1.7 cm footprint resolution. The LiDAR data that was collected was post-processed to produce various derivative data such as: 3D point clouds, digital elevation models (DEM), digital surface models (DSMs), and derivative data products such as the total horizontal derivative (THD) filter. Processed data highlighted lateral spatial heterogeneity, which identified vertical and horizontal MBRLs, as well as surficial TM-62M anti-vehicle, TM62P anti-personnel mines and VPMA-3 landmines. PFM-1 landmines, the smallest of all EOs used, were not located, as the footprint resolution of the data collected was too small (1.7 cm) to clearly differentiate the ordinance from the environment. This pilot study allowed us to better understand the strengths and weaknesses of this method. We plan to further develop this technology by exploring the use of streamlined algorithms, applying alternative data processing workflows, and using sub-pixel techniques to improve the accuracy and efficiency of location. Refining data acquisition parameters, such as the speed and height of drone flight may also lead to further improvements in efficiency. In addition to location, a focus could also be placed on looking at intensity to identify material properties of EOs. 

How to cite: Restrepo, A., Labnine, A., DiMatteo, R., Edwards, C., Hamilton, J., Quinto, L., Tuohy, M., Nikulin, A., and de Smet, T. S.: Drones Paired with Hyperspectral Imaging Paired with LiDAR to Locate Explosive Ordnance, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4516, https://doi.org/10.5194/egusphere-egu23-4516, 2023.

EGU23-7272 | Posters on site | GI6.2

Automatic Detection of UAV GCP Targets Using Line-Based Approach 

Junho Yeom, Aisha Javed, Taeheon Kim, and Youkyung Han

With the advent and development of UAV technologies, UAV images are widely used in various fields since UAV photogrammetry has many advantages in terms of cost and accessibility. In addition, UAV photogrammetry has the advantage of enabling precise 3D surveying because it acquires images of higher spatial resolution with higher overlap compared to traditional aerial photogrammetry. UAV photogrammetry requires ground control points (GCPs) that are dense and evenly distributed throughout the study area. GCP surveying is generally conducted on-site, unlike automated UAV flight and image acquisition, which is a primary factor hindering time and labor cost reduction. In addition, pre-processing, such as UAV orthophoto, point cloud data, and digital elevation model (DEM) production, is performed automatically according to designated parameters, whereas matching GCP survey information with the images involves the intervention of an analyst. Therefore, in this study, the automatic extraction of UAV GCP targets and their centroids was investigated to increase the utilization of UAV photogrammetry and reduce the cost. Sequential steps of image thresholding, boundary detection, and buffered labeling detected a candidate area where ground targets exist. Then, the Hough transform was applied to the target candidates to extract two dominant lines and their intersection point representing the target center. The proposed method extracts the GCP targets from the images with high accuracy, and it was confirmed that it could be applied to complex urban areas. In addition, the GCP targets and their centroid points were successfully extracted from various land covers.

How to cite: Yeom, J., Javed, A., Kim, T., and Han, Y.: Automatic Detection of UAV GCP Targets Using Line-Based Approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7272, https://doi.org/10.5194/egusphere-egu23-7272, 2023.

EGU23-7531 | Orals | GI6.2

Assessment of the Faidherbia albida effect on millet yield using UAV images analysis and geostatistical techniques 

Serigne Mansour Diene, Romain Fernandez, Eric Goze, Ibrahima Diack, Marième Faye, Al Housseynou Dabo, Pape Oumar Ba Bousso, Alain Audebert, Olivier Roupsard, Louise Leroux, Modou Mbaye, Abdou Aziz Diouf, Moussa Diallo, and Idrissa Sarr

Agroforestry, the association between trees/shrubs and crops, a widespread practice in West Africa, is presented as a lever for ecological intensification to optimize cereal yields in the face of strong population growth and the fight against climate change. Within the framework of the EU-DESIRA SustainSAHEL project, we aim to develop techniques to spatially assess the effect of trees on millet yields on an intra-field scale using imagery from an UAV equipped with a multispectral camera combined with geostatistical approaches. Indeed, recent advances in earth observation technologies position the UAV as an effective tool for evaluating the agronomic performance of agroforestry systems and for taking into account the intra-field variability of yields caused by environmental conditions, agricultural practices or the presence of trees (Roupsard and al., 2020 ; Leroux and al., 2022). The objective of this study was to estimate millet yields intra-field variability using UAV and up-to-date geostatistical approaches.

The study was carried out over the 2018-2022 cropping seasons in one representative Faidherbia parkland of the groundnut basin of Senegal. To that end, a Random Forest (RF) algorithm was first calibrated to estimate millet yield at sub-plot scale using a thresholding classification to eliminate non-vegetation elements and also to integrate texture data, in order to take into account the spatial relationships between pairs of pixels. Millet yields data and vegetation and textural index from aerial images at a flight height of 25 meters acquired in farmers’ plots were used to calibrate the RF model. The RF model was used to upscale yield at the whole field scale thus allowing to obtain a map of millet yield. Then Voronoï diagram, with Faidherbia as a reference, was applied to each yield map, considering each Voronoï region as a zone of influence of its included Faidherbia. We then applied a transformation and rotation matrix to overlay all the zones of influence of a population of 50 Faidherbia by putting all the trees at the same geographical position. Finally, we build an atlas, which is an average structure representative of a population and which makes possible to detect the patterns and properties of the evolution of the population considered, to evaluate the distance and directional effect of Faidherbia on vegetation index of the population and then on millet yield.

The RF model is able to explain between 70 and 90 % of the millet yield variability. Then the analysis has shown that the tree has an influence on the millet stand density with a distance-decay effect from the tree. This stand density is about 60 % around the tree and 30 % at 15m from the tree.

Key words : Agroforestry, Uav, Machine learning, Image analysis, Geostatistics, Atlas

How to cite: Diene, S. M., Fernandez, R., Goze, E., Diack, I., Faye, M., Dabo, A. H., Bousso, P. O. B., Audebert, A., Roupsard, O., Leroux, L., Mbaye, M., Diouf, A. A., Diallo, M., and Sarr, I.: Assessment of the Faidherbia albida effect on millet yield using UAV images analysis and geostatistical techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7531, https://doi.org/10.5194/egusphere-egu23-7531, 2023.

EGU23-8617 | Orals | GI6.2 | Highlight

Ultra High-Resolution terrestrial and marine DEMs drive Relative Sea Level Rise projections and flooding scenario for 2100 A.D. for the Island of Panarea (Southern Tyrrhenian Sea, Italy) 

Marco Anzidei, Fawzi Doumaz, Alessandra Esposito, Daniele Trippanera, Antonio Vecchio, Massimo Fabris, Alessandro Bosman, and Tommaso Alberti

In the Aeolian Archipelago (southern Tyrrhenian Sea), Panarea Island and the islets of Bottaro, Lisca Bianca, Lisca Nera and Dattilo, is undergoing sea level rise, land subsidence, coastal erosion and beach retreat that are posing continuous threats to coastal stability and infrastructures built along the coastal zone. With the aim to assess the coastal changes by the end of 2100 according to the IPCC climatic scenarios, that predict a global sea level rise even more than 1 m, a detailed evaluation of the potential coastal flooding has been estimated in the frame of the PANDCOAST project, funded by the INGV.

This work focuses on the use of Unmanned Aerial Vehicles (UAVs) imagery combined with multibeam bathymetry data collected in different years for the generation of the very  high-resolution Digital Terrain and Marine Model (DTMM) of the Panarea Island and its archipelago. Scenarios are based on the determination of the current coastline position, high resolution Digital Terrain and Marine Models, vertical land movements and climatic projections.  The data fusion of detailed topographic data, up to 2 cm/pixel for the subaerial sector with sea level rise projections released by the Intergovernmental Panel on Climate Change (IPCC) for the SSP2.6 and SSP5 climatic scenarios for this area, are used to map the expected multi-temporal sea level rise scenarios for 2050 and 2100.

In the analysis have been incorporated the effects of the vertical land movements (VLM) as estimated by the Global Navigation Satellite System (GNSS) network located in the archipelago. Assuming constant rates of VLM for the next 80 years, relative sea level rise projections provide values between 31±11 cm by 2050 and 104±27 cm by 2100 for the IPCC AR6 SSP8.5 scenarios and at 27±10 cm by 2050 and 73±24 cm by 2100, for the IPCC AR6 SSP2.6 scenario, with small variations in the individual islets of the archipelago. With these scenarios, the lowest elevated coasts of the islands are exposed to increasing marine flooding, especially during storm surges and high water levels particularly heavy from the north-western sectors.

How to cite: Anzidei, M., Doumaz, F., Esposito, A., Trippanera, D., Vecchio, A., Fabris, M., Bosman, A., and Alberti, T.: Ultra High-Resolution terrestrial and marine DEMs drive Relative Sea Level Rise projections and flooding scenario for 2100 A.D. for the Island of Panarea (Southern Tyrrhenian Sea, Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8617, https://doi.org/10.5194/egusphere-egu23-8617, 2023.

EGU23-10468 | Orals | GI6.2 | Highlight

UAS applications in high-resolution topographic change, land use classification, and sub-surface geophysical mapping 

Mel Rodgers, Rocco Malservisi, Robert Van Alphen, Taha Sadeghi Chorsi, Timothy Dixon, and Charles Connor

The use of unoccupied aerial systems (UAS) in geoscience has dramatically improved our ability to collect data at high resolution, minimal cost, and in rapid response to sudden events. The wide range of sensor and platform configurations gives scientists great flexibility in survey design and data collection. Satellite remote sensing data has exceptional spatial coverage and continues to increase its data acquisition to meter-level resolution. UAS data can image to the cm-level resolution but lacks the same spatial coverage as satellite. By combining and comparing UAS data with satellite and ground-based remote sensing data we can utilize the different strengths of these systems. Here we demonstrate various UAS applications in high-resolution topographic change, land use classification, and sub-surface geological mapping. We use UAS payloads such as RTK georeferenced RGB and multispectral images, lidar, and magnetic sensors to image surface changes and sub-surface structures. We demonstrate the need for post-processing (PPK) high precision GNSS rover locations over utilizing only RTK position information.

Florida, USA, is home to rapidly changing beaches and wetlands, which are highly susceptible to our changing climate and destructive storm events. We show examples from beaches and wetlands in Pinellas County, Florida, USA where we have a) imaged the emergence and development of a barrier island, b) developed automated land use classification using photogrammetry and multispectral data, c) evaluated the impacts of a major hurricane event on a recently renourished beach. Pacaya Volcano, Guatemala, is an active volcano with frequent lava flows and historical flank collapse events. Using a combination of satellite DEMs, ground-based Terrestrial Radar Interferometry data, and UAS RGB SfM-photogrammetry, we have imaged recent lava flows in high-resolution showing details of lava flow levees and other structures. By comparing our data to pre-eruption satellite DEMs we can evaluate the volume and morphology of recently emplaced lava flows. In addition, we have collected magnetic data over recent lava flows that allows us to image the sub-surface structure of the lava flows and model lava flow properties. UASs are a powerful tool for remote sensing, geodetic, and geophysical data collection. They augment satellite and ground-based methodologies and by combining multidisciplinary data from these platforms we can image the earth in greater spatial and temporal detail than ever before.  

How to cite: Rodgers, M., Malservisi, R., Van Alphen, R., Sadeghi Chorsi, T., Dixon, T., and Connor, C.: UAS applications in high-resolution topographic change, land use classification, and sub-surface geophysical mapping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10468, https://doi.org/10.5194/egusphere-egu23-10468, 2023.

EGU23-11014 | ECS | Posters on site | GI6.2

A study on classification and monitoring of marine debris using multi-spectral images and deep learning 

You Chul Jeong, Jong-Seok Lee, Jisun Shin, and Young-Heon Jo

Marine environmental issues due to marine debris are worldwide phenomena. According to a press release from the Ministry of Oceans and Fisheries of Korea, marine waste collection from the coastal area increased yearly. In 2020, it collected 1.38 million tons, about 45% more than in 2018. To remove them, they were collected and monitored through field monitoring systems. However, it is very inefficient in terms of time and cost. Therefore, the remote sensing approach can be suited for classifying and investigating marine waste dumped in coastal areas. Previous studies have classified marine waste by combining remote sensing based on RGB images and artificial intelligence. However, actual marine waste is often damaged, or its shape is difficult to recognize through RGB images. This study was conducted to classify various wastes using multi-spectral camera and a convolution neural network (CNN) model. We first trained and tested CNN model using three wastes, such as a brown paper box, an orange-colored buoy, and a blue plastic basket with different spectral characteristics in the land environment. Then, we conducted the classification of marine waste using CNN model and multi-spectral images taken with Uncrewed Aerial Systems (UAS) in the marine environment around Socheongcho-Ocean Research Station (S-ORS). The CNN model were trained using 1,452 seawater and 1,319 clear plastic images around the S-ORS with 128 x 128-pixel size. We calculated precision, recall, f1-score, and accuracy, suggesting that the CNN model could be used to classify various marine wastes in the various ocean environment. Overall, these results can provide useful information for marine waste monitoring.

How to cite: Jeong, Y. C., Lee, J.-S., Shin, J., and Jo, Y.-H.: A study on classification and monitoring of marine debris using multi-spectral images and deep learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11014, https://doi.org/10.5194/egusphere-egu23-11014, 2023.

EGU23-11869 | ECS | Posters on site | GI6.2

How UAV improve past metallurgical deposits characterization for landfill regeneration 

Hadrien Michel, Marc Dumont, David Caterina, François Jonard, Itzel Isunza Manrique, Tom Debouny, and Frédéric Nguyen

Ancient metallurgical industries produced large amounts of residues, which were typically deposited in heaps or tailing ponds. The presence of such wastes could represent a potential source of pollution that may prevent the reuse of the sites. The NWE-REGENERATIS project aims to characterize different types of metallurgical deposits in order to improve their management and rehabilitation. The understanding of these sites is made difficult by their heterogeneous composition, complex morphology and dense vegetation.

Here, we explore the interest of integrating UAV surveys in geophysical characterization of NWE-REGENERATIS sites. First, our approach uses photogrammetry to build the digital surface model. Such models can be used to approach deposit volume and improve modelling of the sites. Those are crucial to carry accurate inversion of land-based geophysical data. Secondly, the multi-spectral measurements allow characterizing surface geochemical composition in order to define surface waste characteristics. These data could be used to explain surface electrical resistivity variation. Finally, areas with high metallurgical contents are highlighted with magnetic mapping. There, the ability of UAV to cover areas previously unattainable by land (dense vegetation and/or steep inclines) is key for a better understanding of the site.

This methodology is applied to multiple sites, including old iron and zinc factories or uncharacterized industrial landfill. We thus present strengths and weaknesses of each UAV mapping used to characterize metallurgical landfills.

How to cite: Michel, H., Dumont, M., Caterina, D., Jonard, F., Isunza Manrique, I., Debouny, T., and Nguyen, F.: How UAV improve past metallurgical deposits characterization for landfill regeneration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11869, https://doi.org/10.5194/egusphere-egu23-11869, 2023.

EGU23-12229 | ECS | Posters on site | GI6.2

Real surface vegetation functioning and early stress detection using visible-NIR-thermal sensor synergies: from UAS to future satellite applications 

Adrián Moncholi, Shari Van Wittenberghe, Maria Pilar Cendrero-Mateo, Luis Alonso, Marcos Jiménez, Katja Berger, Alasdair Mac Arthur, and José Moreno

Under the current climate change conditions, the early stress detection of crops and worldwide vegetation are crucial to promote sustainable agriculture and ecosystem management. With the upcoming European Space Agency’s Fluorescence Explorer-Sentinel 3 (FLEX-S3) tandem mission, vegetation fluorescence and the auxiliary parameters/traits needed to interpret solar-induced vegetation fluorescence (SIF) will become available at 300x300 m spatial resolution. Today, a variety of SIF-specialized UAS systems exist to retrieve the canopy-emitted SIF over larger areas, e.g., as a reference for airborne imaging SIF sensors. However, they lack the complementary sensors needed for a correct interpretation of the highly dynamic fluorescence emission.  In this study we present the FluoCat system, a unique UAS system which can be mounted either in a UAV or cable-suspended mobile platform. On board the FluoCat are mounted: a high-spectral resolution Piccolo Doppio dual spectrometer system, a MAIA-S2 multispectral camera and a TeAx Thermal Capture Fusion camera, which can be triggered simultaneously according to a pre-set protocol. The FluoCat system mimics the FLEX-S3 sensor configuration, by using a multi-sensor system integrating the visible, NIR and thermal spectral regions providing complete datasets to assess the actual vegetation stress. In this context a field campaign was conducted in the experimental site ‘Las Tiesas’ in Barrax, Spain, with the aim to (1) apply sampling protocols to obtain spatially representative canopy reflectance and SIF measurements, and (2) provide accurate ground truth measurements for real (i.e., leaf) surface reflectance and effective surface fluorescence measurements, linkable to the real photosynthetic performance. Further we demonstrate the development of a sensor synergy product, combining canopy physiological and structural information to reveal real surface physiological stress-related energy emission. The ‘sunlit green fluorescence’ is a synergy product combining the top-of-canopy fluorescence and the fractional vegetation cover of the sunlit vegetation. This synergy product improved the estimation of the effective surface fluorescence flux, using the leaf fluorescence emission as reference, by reducing the errors from 36 % to 18 % (band 687 nm); and from 24 % to 6 % (band 760 nm). Real surface properties and products referring to the actual photosynthetic surface behavior are promising quantitative proxies to assess the impact of climate change and/or management practices on crop lands or even whole ecosystems. With this study we show how innovative proximal sensing platforms can help to develop new data processing schemes combining all required information for the quantitative assessment of vegetation health, even before visible damage occurs. The further processing and normalization of first-derived stress proxies such as SIF can generate further in-depth early stress detection, directly related to the photosynthetic light reactions, and further global carbon assessment. These developments are in direct support for the global monitoring of early vegetation stress under a changing global climate.

How to cite: Moncholi, A., Van Wittenberghe, S., Cendrero-Mateo, M. P., Alonso, L., Jiménez, M., Berger, K., Mac Arthur, A., and Moreno, J.: Real surface vegetation functioning and early stress detection using visible-NIR-thermal sensor synergies: from UAS to future satellite applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12229, https://doi.org/10.5194/egusphere-egu23-12229, 2023.

EGU23-12890 | Orals | GI6.2 | Highlight

Stromboli surface changes from Pleiades high-resolution space data 

Claudia Spinetti, Marina Bisson, and Monica Palaseanu-Lovejoy

Stromboli is one of the most visited volcanoes in the world due to its persistent activity consisting in mild strombolian explosions with a frequency up to 25-30 events per hour. This activity is punctuated by more energetic explosions named major explosions, paroxysms and lava flow. These types of eruption can change drastically the morphology of the affected areas and cause volcanic phenomena highly impacting for the island, including heavy fallout of blocks and bombs on the flanks of the volcano, pyroclastic flows and tsunami waves. Paroxysms are highly dangerous phenomena for the tourists that climb the volcano and can cause serious problems also to the local people living on the two villages on the coast of the island. In order to map the areas affected by morphological changes, the thickness of deposits and the associate volume estimation of erupted products, we propose a study based on two techniques of remote sensing. First, we reconstruct the Stromboli topography, before and after an event, elaborating stereo pairs of Pleiades satellite and using as base an airborne LiDAR data at spatial resolution of 50 cm. Then we map the morphological changes giving an estimation of the relative areas and volumes. These results, discussed and compared with available field data, can help to better understand the impact of the event and provide indications useful in a territory planning aimed to mitigate the effects of such calamitous events.

How to cite: Spinetti, C., Bisson, M., and Palaseanu-Lovejoy, M.: Stromboli surface changes from Pleiades high-resolution space data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12890, https://doi.org/10.5194/egusphere-egu23-12890, 2023.

EGU23-13115 | ECS | Posters on site | GI6.2

Surface temperature variations observed from a thermal infrared camera mounted on a hovering UAV platform 

Jamal Elfarkh, Kasper Johansen, Victor Angulo-Morales, Omar Lopez Camargo, and Matthew F. McCabe

Land surface temperature (LST) is crucial information that helps to understand and assess the interactions between the surface and the atmosphere. LST is a key parameter used in various applications including studies of irrigation, water use, vegetation health, urban heat island effects, and building insulation. In addition to several satellites that provide periodic images of surface temperature, unmanned aerial vehicle (UAV) platforms have been adapted to obtain higher spatio-temporal resolution thermal infrared (TIR) data. In fact, numerous research studies have investigated the accuracy and the processing method of UAV-based TIR images given its complexity and sensitivity to ambient conditions. However, the surface temperature is characterized by continuous and rapid variation over time, which is difficult to take into consideration in the processing of UAV-based orthomosaics. Here, we quantify this variation and discuss the environmental factors that lead to its amplification. Thermal images were collected over a fixed hovering position during periods of 15-20 min, representing the common duration of UAV flights. At different times of the day, we flew at different altitudes over sand, water, grass and olive trees. Before the quantification of the surface temperature variation, the thermal infrared data were evaluated against field-based measurements using calibrated Apogee sensors. The evaluation showed a significant error in the UAV-based thermal infrared data linked to wind speed, which increased the bias from -1.02 to 3.86 °C for 0.8 to 8.5 m/s winds, respectively. The assessment of the LST values collected over the different surfaces showed a temperature variation while hovering ranging between 1.4 and 5 °C. In addition to wind effects, temperature variations while hovering were strongly linked to solar radiation, specifically radiation fluctuations occurring after sunrise and before sunset. This research provides insights into the LST variation expected for standard UAV flights of 15-20 min under different environmental conditions, which should be taken into account during UAV-based thermal infrared data processing and may help interpret and quantify inconsistencies in UAV-based orthomosaics of LST.

How to cite: Elfarkh, J., Johansen, K., Angulo-Morales, V., Lopez Camargo, O., and F. McCabe, M.: Surface temperature variations observed from a thermal infrared camera mounted on a hovering UAV platform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13115, https://doi.org/10.5194/egusphere-egu23-13115, 2023.

EGU23-14035 | Orals | GI6.2

Up-scaling approach to monitor pests in Alpine forests: A case study in Vinschgau, South Tyrol, Italy. 

Abraham Mejia-Aguilar, Alexandros Theofanidis, Emilio Dorigatti, Ruth Sonnenschein, Ekaterina Chuprikova, and Liqiu Meng

Endemic pests are a fundamental part of forest ecosystems, they provide key ecosystem services such as nutrient cycling and support biodiversity. Still, massive outbreaks of these pests, triggered by events such as drought, windthrows, and snow breaks, can limit the provisioning of ecosystem services that are key for human populations such as water cycle regulation and, which can eventually trigger natural hazard events (e.g. landslides).

Unmanned Aerial Vehicles (UAVs) and miniaturized optical sensors can be used to support foresters in detecting, identifying, and quantifying pests and their diffusion by exploiting multispectral imagery at high resolution. Such platforms are especially suited for monitoring areas in mountain regions that are difficult to access.

This study focus on the pine processionary (Thaumetopoea pityocampa) and European bark beetle (Ips typographus) that affect many forests in the Province of South Tyrol, Italy. Here, we present an up-scale strategy that first identifies the presence of a pest at the centimeter level (ground and close-range scale) based on UAV-derived products on a plot level. We conducted three UAV-flight campaigns during the year corresponding to the insect-life cycle. Then, on the one hand, using simple RGB and NDVI mosaics the system delineates the trees, identifies nests (processionary) and quantifies their impact. On the other, using the NDVI time series collection the system classify healthy, infested or dead tree linked to the presence of bark beetle. The system classifies and quantifies its presence by presenting graduated symbol maps widely used by foresters. Then, we scale up to meter resolution (remote sensing scale) to detect changes due to certain conditions of stress that can link to the presence of the studied pests. The final aim is to create high-quality training datasets that will be exploited by remote sensing products (Sentinel) to study and cover wider areas.

How to cite: Mejia-Aguilar, A., Theofanidis, A., Dorigatti, E., Sonnenschein, R., Chuprikova, E., and Meng, L.: Up-scaling approach to monitor pests in Alpine forests: A case study in Vinschgau, South Tyrol, Italy., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14035, https://doi.org/10.5194/egusphere-egu23-14035, 2023.

EGU23-14165 | Posters on site | GI6.2 | Highlight

The integrated use of LiDAR and photogrammetric techniques by the UAS platform for the mapping of rockfall processes in Ischia Island (Italy) 

Vincenzo De Novellis, Massimiliano Alvioli, Andrea Barone, Antonello Bonfante, Maurizio Buonanno, Raffaele Castaldo, Ada De Matteo, Federica Fiorucci, Susi Pepe, Paola Reichenbach, Michele Santangelo, Giuseppe Solaro, Pietro Tizzani, and Andrea Vitale

The following work focuses on the surveys that were carried out using optical sensors (photogrammetry) and LiDAR mounted on UAS platforms. The processing of the acquired images provided the necessary information for the development of high-precision digital terrain models that can be used as a basis for the subsequent modeling of the stability analysis of collapse phenomena with STONE, a three-dimensional rockfall simulation model. These surveys allowed us to localize the possible detachment sources and the inclusion of scenario-based seismic shaking as a trigger for rockfalls.

The areas filmed fall almost exclusively along the north-western slope of Mt. Epomeo and more precisely in the areas identified as locality Falanga (32 ha) and locality Frassitelli (123 ha) in the territory of the Municipality of Forio (Napoli) and only marginally in the Municipality of Serrara Fontana (Napoli). The slope surveyed has two distinct morphologies: 1) the north-west oriented sector (Falanga) delimited by extremely steep walls and by cliffs with variable vertical development, at the base of which there is a large sub-flat area delimited to the north by a new sudden jump in slope; 2) in the west sector (Frassitelli) the slope is instead more rounded, even if in various points there are areas with steep slopes and strongly fractured cliffs; this side is characterized by the presence of numerous tuff blocks, even of large dimensions, which have stopped at various altitudes after having detached themselves from the overlying sub-vertical walls.

We also used data from the Geoportale Nazionale Italiano managed by the Ministry of Environment and provided different kinds of spatial data. In particular, the archive contains an extensive LiDAR survey covering a substantial portion of Italy, with data stored at the intermediate processing level. For this research, we selected point clouds covering the Ischia island and we interpolated separately the two point clouds, using the module specifically designed to perform surface interpolation from vector points mapped by splines, within the GIS platform.

In conclusion, we interpreted the point-to-point difference between DSM and DTM as due to vegetation and exploited this information to infer modifications of ground parameters relevant to the simulations with Stone. We partially took into account disturbances due to the presence of anthropic structures and buildings using additional land cover data, which we correlated with point-to-point DSM – DTM differences.

How to cite: De Novellis, V., Alvioli, M., Barone, A., Bonfante, A., Buonanno, M., Castaldo, R., De Matteo, A., Fiorucci, F., Pepe, S., Reichenbach, P., Santangelo, M., Solaro, G., Tizzani, P., and Vitale, A.: The integrated use of LiDAR and photogrammetric techniques by the UAS platform for the mapping of rockfall processes in Ischia Island (Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14165, https://doi.org/10.5194/egusphere-egu23-14165, 2023.

EGU23-15267 | ECS | Orals | GI6.2

The NERC Field Spectroscopy Facility UAV Suite 

Robbie Ramsay, Alex Merrington, Jack Gillespie, and Steven Hancock

The Field Spectroscopy Facility (Edinburgh, UK) is a Natural Environment Research Council public funded body which maintains and provides cutting edge spectroscopy instrumentation and expertise to UK and international researchers. The facility primarily focuses on the provision of ground based spectroscopic instrumentation, often in support of airborne spectroscopic surveys, but was awarded a UKRI capital fund in 2019 for the development of a UAV spectroscopic sensor suite to fill the spatial resolution gap between airborne and ground measurements.

Developed as the “NERC Field Spectroscopy Facility UAV Suite”, the new instrument pool consists of various UAV platforms and spectroscopic sensors which can be loaned to UK and international researchers. Instruments include multispectral cameras with sensors matched to Sentinel-2 and WorldView-3 centre wavelengths; thermal cameras covering the SWIR to MIR region; a custom designed UV-VIS spectrometer for measurements of solar induced fluorescence; and the flagship sensor of the suite, a lightweight hyperspectral imager with LIDAR attachment covering the UV-VIS-SWIR region (350 to 2500 nm range).

In this presentation, we discuss the development of the FSF UAV suite, discussing our “chain” concept of development – calibration of sensors at our optical laboratory; integration of sensors onto UAVs; logistical planning of flights with associated ground-based data acquisition; and the development of custom processing chains of UAV acquired data. We will highlight select campaigns on which the UAV suite has been used, including macro plastic detection as part of ESA HyperDrone, ecological surveying of large peatlands in Northern Scotland, and support for the ESA-FLEX (solar induced fluorescence sensing) mission. We will also discuss the challenges involved in sensor integration, and provide insight into the novel solutions which we have employed during the development of the UAV suite.  

How to cite: Ramsay, R., Merrington, A., Gillespie, J., and Hancock, S.: The NERC Field Spectroscopy Facility UAV Suite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15267, https://doi.org/10.5194/egusphere-egu23-15267, 2023.

EGU23-15546 | ECS | Posters virtual | GI6.2

Assessment of transpiration in different almond production systems with two-source energy balance models using high-resolution aerial imagery. 

Manuel Quintanilla-Albornoz, Joaquim Bellvert, Ana Pelechá, Jaume Casadesus, Omar García-Tejera, and Xavier Miarnau

The almond production has increased by doubling their hectares under irrigation treatments in Spain. In a context of water scarcity, the estimation of Evapotranspiration (ET) and its components, Transpiration (T) and Evaporation (E), are key variables to monitor and manage the water resources. High-resolution ET can be retrieved from surface energy flux modeling, such as a Two-Source Energy Balance (TSEB) model, using an Unmanned Aerial System (sUAS). sUAS equipped with Thermal and Multispectral cameras allows us to obtain the main parameters required in TSEB. Currently, there are no studies that evaluate the T obtained with TSEB Priestley Taylor (TSEB-PT) and TSEB-2T models in tree-scale almonds under different irrigation treatments (IR) and production systems (PS). In this context, we evaluated the T retrieved with TSEB-PT and TSEB-2T models using Sap Flows sensor in trees with three PS, Open Vase with Minimal Pruning (OVMP), Central Axis (CA) and Hedgerow (HGR), and three levels IR, Full Irrigation (FI), Mild Stressed (MS) and Stressed (SS). Five flights were conducted from March 2021 to July 2021 to analyze the almond growing season with an aircraft equipped with a thermal and multispectral camera. Leaf area index (LAI), stem water potential (Ψstem) and Fractional Intercepted Photosynthetically Active Radiation (fIPAR) was also measured concomitant to image acquisition. PS presents significant differences in fractional canopy cover (F_C), tree height (H_C), LAI and Sap Flow transpiration (Tsf). The two TSEB models show a generalized overestimation with a BIAS of 0.99 and 1.22 for TSEB-2T and TSEB-PT respectively. TSEB-PT presented worse statistics and R2 decreases in the more intensive production system. HGR has equal or greater LAI but lower F_C, which would imply an overestimation of canopy temperature (T_C) by the PT method. This is in addition to the difficulty of setting the PT coefficient according to the context of the crop. The overestimation in both models could be associated with an error in Campbell (1998) Radiative Transfer Model used to estimate transmittance, which has an error of 0.14 RMSE and 0.12 BIAS compared with fIPAR. Our results suggest the use of TSEB-2T with high resolution images considering the current available technology that allows us to estimate T_C and T_S separately, especially in intensive or super-intensive almond crops. To improve the T estimation, it is recommended to use in situ PAR measurement to decrease the influence of LAI measurements on the models.

How to cite: Quintanilla-Albornoz, M., Bellvert, J., Pelechá, A., Casadesus, J., García-Tejera, O., and Miarnau, X.: Assessment of transpiration in different almond production systems with two-source energy balance models using high-resolution aerial imagery., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15546, https://doi.org/10.5194/egusphere-egu23-15546, 2023.

EGU23-16009 | Orals | GI6.2

Common mission planning and situation awareness model for UxS Command and Control systems 

Teodor Hanchevici, Piotr Zaborowski, Donald V. Sullivan, and Alex Robin

Multi-vendor operations of uncrewed vehicles as part of the observations, surveillance and surveying are already daily practice in many fields. The popularity of the integration platforms that manage multiple, sometimes simultaneously, systems is also already proven by the integration platforms' popularity. With new European regulations for the drone industry and the growing popularity of various (ground, water surface, underwater, aerial) systems exploitations, the need for situation awareness and planning that will be flexible and vendor lock-in free is leveraged. However, despite several recent efforts and some popular specifications that aim at becoming de-facto standards, civil operations' interoperability challenge is unsolved. To assess whether a shared data model is suitable for multi-domain, multi-heterogeneous vehicle use, and challenge it with real applications and demonstrate the exchange of command and control information, OGC members started an Interoperability Experiment in 2022. IE is based on a data model developed by Kongsberg Geospatial and partners under the Standards-based UxS Interoperability Test-bed (SUIT). The IE considers those other standards and specifications which were used in the SUIT work as well as other Command and Control practices from the aviation and marine communities. The presentation depicts selected use cases and scenarios and outlines the information model of the localized situation awareness and mission planning and operations. Being specific for autonomous vehicle operations, they extend the needs of generic geospatial representations. Authors will explain relations to other similar models like (LSTS, MavLink, UMAA, STANAG 4586, JAUS, C2INav) and modern geospatial data exchange standards like OGC SensorThings, Features, Moving Features, GeoPose.

How to cite: Hanchevici, T., Zaborowski, P., Sullivan, D. V., and Robin, A.: Common mission planning and situation awareness model for UxS Command and Control systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16009, https://doi.org/10.5194/egusphere-egu23-16009, 2023.

EGU23-16685 | Posters on site | GI6.2

In - season progressive crop type mapping in war affected Ukraine 

Josef Wagner, Inbal Becker-Reshef, Shabarinath Nair, Sergii Skakun, Yuval Sadeh, Sheila Baber, Blake Munshel, Andrew Zolli, and Françoise Nerry

The invasion of Ukraine by Russian forces was expected to have global impact on food trade and security, since Ukraine is a breadbasket cereals and oil seeds producer. The NASA Harvest « Rapid Agricultural Assessment for Policy Support » (RAAPS) team was triggered early in the conflict to provide answers to the following questions : 

(i) How much winter cereals, winter oil seeds and summer crops were planted in Ukraine during the 2021-2022 cropping season?

(ii) What proportion of those crops fell under the Russian occupied area? 

(iii) How much cropland was left unplanted in 2022 due to the war?

As insights had to be produced within season, the NASA Harvest RAAPS team produced the first ever, Ukraine scale in-season crop type map based on Planet Labs 3 meter spatial -, 4 bands spectral -, and daily  temporal – resolution data.  Since   no   labeled   datasets   were   available   early   enough   in-season  for applying supervised machine learning techniques, cropland was progressively mapped   into   four   classes   (winter   cereals,   rapeseed,   summer   crops   and barren/non cultivated plots), using semi-supervised clustering techniques and heuristical thresholdings. Expert domain  knowledge  allowed to cope  with missing ground truth training data. First, active cropland was separated into winter crops and potential summer crops. K-means clustering of April and May Planet images, followed by visual cluster assignment, allowed to efficiently separate green crops (winter crops) from barren soils (potential summer crops). Then, another K-means clustering allowed to split winter crops into winter cereals and rapeseed as of end of May, based  on the intense yellow flowering signal of the latter. Finally a set of NDVI based heuristics was applied on potential summer crops in order to assess if green-up happened or not. Crops which   did   not   green   up   as   of   the   11th   of   July   2022   were   considered barren/non-planted. 

Road side ground surveyed crop type information collected in free Ukraine has been provided by Kussul & al. (2022) in August 2022. Validation against this data provided an overall accuracy of 94 % and a mean F1-score of 91 % for winter cereals, rapeseed and summer crops. No unplanted fields  were collected as part of the ground campaign. Several assessments of proportional area per crop type and occupation status were performed throughout the growing season, as occupation boundaries kept moving. As of the 11th of July 2022, 23.03 % of Ukraines cropland was occupied. 55.29 % of all detected barren fields were located within occupied territories, mainly scattered around the front line. 33.9 % of all winter crops were under occupied territory when harvest ready (mid July). 

This crop type map was used for computing harvested area, estimating yield and   for   production computation. Following NASA EarthObservatory articles were published,   providing   information   to   the   public   and   private   sector :   (i) https://earthobservatory.nasa.gov/images/150025/measuring-wars-effect-on-a-global-breadbasket    (ii) https://earthobservatory.nasa.gov/images/150590/larger-wheat-harvest-in-ukraine-than-expected 

How to cite: Wagner, J., Becker-Reshef, I., Nair, S., Skakun, S., Sadeh, Y., Baber, S., Munshel, B., Zolli, A., and Nerry, F.: In - season progressive crop type mapping in war affected Ukraine, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16685, https://doi.org/10.5194/egusphere-egu23-16685, 2023.

EGU23-16686 | Orals | GI6.2 | Highlight

An automated GIS procedure for mapping ballistic projectiles by using UAVs imagery: the case of the 3rd July, 2019 paroxysm at Stromboli 

Marina Bisson, Claudia Spinetti, Roberto Gianardi, Karen Strehlow, Emanuela De Beni, and Patrizia Landi

This study presents an application based on UAS optical data for mapping at very high spatial resolution the ballistic projectiles erupted during an explosive volcanic eruption. The novelty consists in the development of a GIS-based automate procedure that, elaborating high spatial resolution UAV optical imagery (RGB) acquired within few days from the explosive event, is able to reproduce the boundary of each ballistic projectile as georeferenced polygon feature. This procedure, applied for the first time at Stromboli volcano (Aeolian Archipelago, Italy), has reconstructed in 2D digital format the shape of the ballistic spatter clasts emplaced on the East flank of the volcano during the paroxysm of the 3rd July, 2019. The dimensions of the clasts, reproduced as polygon features stored in WGS 84 UTM 33 metric coordinates, range from 0.03 m2 (16 cm x 16 cm) to 4.23 m2 (~2 m x 2 m). Respect to the classic field survey, the application here presented is able to generate, in efficient and rapid way, a large amount of data and information on ballistic deposits, covering also the areas inaccessible and/or dangerous as particularly affected by ballistic fallout. Such application allowed  to better understand the dynamic of ballistics emplacement, providing a useful contribution to volcanic hazard mitigation.

How to cite: Bisson, M., Spinetti, C., Gianardi, R., Strehlow, K., De Beni, E., and Landi, P.: An automated GIS procedure for mapping ballistic projectiles by using UAVs imagery: the case of the 3rd July, 2019 paroxysm at Stromboli, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16686, https://doi.org/10.5194/egusphere-egu23-16686, 2023.

EGU23-17308 | Posters on site | GI6.2

Transfer learning from citizen science photos enables plantspecies identification in UAV imagery 

Salim Soltani, Hannes Feilhauer, Robbert Duker, and Teja Kattenborn

Accurate information on the spatial distribution of plant species and communities is in high demand for various fields of application, such as nature conservation, forestry, and agriculture. A series of studies has shown that CNNs accurately predict plant species and communities in high-resolution remote sensing data, in particular with data at the centimeter scale acquired with Unoccupied aerial vehicles (UAV). However, such tasks require ample training data to generate transferable CNN models. Reference data are commonly generated via geocoded in-situ observations or labeling of remote sensing data through visual interpretation. Both approaches are commonly laborious and can present a critical bottleneck for CNN applications. An alternative source of training data is given by using knowledge on the appearance of plants in the form of plant photographs from citizen science projects such as the iNaturalist database. Such crowd-sourced plant photos are expected to be very heterogeneous, and often show a different perspective compared to the typical bird-perspective of remote sensing data. Still, crowd-sourced plant photos could be a valuable source to overcome the challenge of limited training data and reduce the efforts for field data collection and data labeling. Here, we explore the potential of transfer learning from such a crowd-sourced data treasure to the remote sensing context. Therefore, we investigate firstly, if we can use crowd-sourced plant photos for CNN training and subsequent mapping of plant species in high-resolution remote sensing imagery. Secondly, we test if the predictive performance can be increased by a priori selecting photos that share a more similar perspective to the remote sensing data. Therefore, we used three case studies to test our proposed approach using multiple RGB orthoimages acquired from UAV for the target plant species Fallopia japonica (F. japonica), Portulacaria Afra (P. afra), and 10 different tree species, respectively. For training the CNN models, we queried the iNaturalist database for photos of the target species and the surrounding species that are expected in the areas of each case study. We trained CNN models with an EfficientNet-B07 backbone. For applying these models based on the crowd-sourced data to the remote sensing imagery, we used a sliding window approach with a 10 percent overlap. The individual sliding-window-based predictions were spatially aggregated in order to create a high-resolution classification map. Our results demonstrate that CNN models trained with heterogeneous, crowd-sourced plant photos can indeed predict the target species in UAV orthoimages with surprising accuracy. Filtering the crowd-sourced photos used for training by acquisition properties increased the predictive performance. This study demonstrates that citizen science data can effectively anticipate a common bottleneck for vegetation assessments and provides an example on how we can effectively harness the ever-increasing availability of crowd-sourced and big data for remote sensing applications.

How to cite: Soltani, S., Feilhauer, H., Duker, R., and Kattenborn, T.: Transfer learning from citizen science photos enables plantspecies identification in UAV imagery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17308, https://doi.org/10.5194/egusphere-egu23-17308, 2023.

EGU23-1083 | ECS | Orals | GI6.3

Exploring the ‘Individual Treatment Effects’ (ITE) of Vegetation with Causal Inference on Soil Organic Carbon Prediction in Germany 

Nafiseh Kakhani, Thomas Gläßle, Ruhollah Taghizadeh-Mehrjardi, Ndiye Michael Kebonye, and Thomas Scholten

Carbon is an essential element and contributor to healthy soil conditions as well as ecological soil function and productivity. Additionally, carbon is a component of all plants and animals on the planet and is a necessary component of life. Natural vegetation serves as a significant but highly dynamic carbon sink. When vegetation is removed quicker than it can regenerate, for example by harvesting crops or timber, soil carbon is depleted. Thus, understanding the environmental effects and dynamics of loss of vegetation is a crucial prerequisite to turning our natural resource management from a carbon emitter to a carbon sink to avoid that and achieve sustainability. At the same time, the spatial distribution of soil organic carbon is also highly heterogeneous, with variations in climate, other soil characteristics, and land use/land cover affecting how our ecosystem reacts to the loss of vegetation. Thus, to effectively improve green metrics and contribute to the creation of future policies, it is required to conduct research on the changes in vegetation and their effect on soil organic carbon and provide regionally appropriate management advice. Here, in this research, our goal is to examine the "individual treatment effects" (ITE), which are a personalized or individualized effect estimation of one variable on the output, and utilize causal inference to address them.  Using the LUCAS dataset, we explore the heterogeneous treatment effect of percent tree coverage (PTC), as a parameter of the density of trees on the ground, on the soil organic carbon content in Germany. We do this by leveraging some parameters, such as climate data, land use/land cover information, and other information from the soil. We thus offer a data-driven viewpoint for focusing on sustainable behaviors and effectively increasing soil organic carbon content levels.

How to cite: Kakhani, N., Gläßle, T., Taghizadeh-Mehrjardi, R., Kebonye, N. M., and Scholten, T.: Exploring the ‘Individual Treatment Effects’ (ITE) of Vegetation with Causal Inference on Soil Organic Carbon Prediction in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1083, https://doi.org/10.5194/egusphere-egu23-1083, 2023.

EGU23-1444 | ECS | Posters on site | GI6.3

Lava flow mapping using Sentinel-1 SAR time series data: a case study of the Fagradalsfjall eruptions 

Zahra Dabiri, Daniel Hölbling, Sofia Margarita Delgado-Balaguera, Gro Birkefeldt Møller Pedersen, and Jan Brus

Lava flows can threaten populated areas, cause casualties and considerable economic damage. Therefore, understanding lava flows and their evolution is important because they can be linked to lava transport systems and eruption parameters. However, timely and accurate lava flow mapping in the field can be time-consuming and dangerous. Earth observation (EO) data plays an important role in improving lava flow mapping and monitoring. Synthetic Aperture Radar (SAR) data provide a unique opportunity to study lava flows, especially in areas with high cloud coverage during the year. Moreover, smoke and ash clouds can be partially penetrated by SAR. The freely available Sentinel-1 SAR data (C-band), with its high temporal and spatial resolution, opens new opportunities for studying lava flow evolution and lava morphology. However, Sentinel-1 data have mainly been used to study surface deformation using Differential Interferometric SAR (DInSAR) techniques, and the utilisation of SAR backscatter information for lava flow characterisation has not been thoroughly exploited.

The Fagradalsfjall volcanic system is located on the Reykjanes Peninsula in southwest Iceland. The eruption began on the 19th of March and lasted until the 18th of September 2021. The resulting lava flows cover an area of 4.8 km2 (Pedersen et al., 2022). Another eruption occurred in August 2022. We used time series of dual-polarisation, including VH (antenna sends vertical pulses and receives horizontal backscatter) and VV (antenna sends vertical pulses and receives horizontal backscatter), Sentinel-1 data to study the changes in lava flow extent and morphology during the 2021 and 2022 Fagradalsfjall eruption phases. The pre-processing of Sentinel-1 data included orbit state vector correction, radiometric calibration to reduce the radiometric biases caused by topographic variations, co-registration, and range doppler terrain correction. In addition to backscatter polarisations, we calculated the image texture using the grey-level co-occurrence matrix (GLCM) algorithm, including several measures such as contrast, homogeneity, and entropy. We used object-based segmentation and classification algorithms to delineate the lava extent and evaluated the applicability of different polarisations. To validate the mapping results, we used reference layers derived from high-resolution optical images available from Pedersen et al. (2022). The results showed that cross-polarisation was the most suitable for mapping the extent of lava. Additionally, the integration of texture information allowed us to distinguish lava types to some extent.

The results demonstrate the potential and challenges of utilising SAR backscatter information from Sentinel-1 data for studying the spatio-temporal lava flow evolution and mapping lava flow morphology, especially when the applicability of optical EO data is limited. 

Pedersen, G. B. M., Belart, J. M. C., Óskarsson, B. V., Gudmundsson, M. T., Gies, N., Högnadóttir, T., et al. (2022). Volume, Effusion Rate, and Lava Transport During the 2021 Fagradalsfjall Eruption: Results From Near Real-Time Photogrammetric Monitoring. Geophysical Research Letters, 49, 13, e2021GL097125. https://doi.org/10.1029/2021GL097125

How to cite: Dabiri, Z., Hölbling, D., Delgado-Balaguera, S. M., Pedersen, G. B. M., and Brus, J.: Lava flow mapping using Sentinel-1 SAR time series data: a case study of the Fagradalsfjall eruptions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1444, https://doi.org/10.5194/egusphere-egu23-1444, 2023.

High spatial resolution land surface temperature (LST) (<= 100 m) has a considerable significance for small scale studies like agricultural applications and urban heat island studies. Originally developed for optical data, spatiotemporal fusion methods, such as the widely used Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), are gradually becoming promising approaches to generate high resolution thermal variables but still have shortcomings, such as an invalid assumption in thermal fields and the accumulation of systematic biases. Hence, we proposed a variant of the ESTARFM algorithm, referred as the unbiased ESTARFM (ubESTARFM), aiming to better accommodate the spatiotemporal approach to thermal studies. We evaluated the results derived from our method and the typical ESTARFM against both in-situ LST and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) LST over a continental scale of Australia. The results show that the ubESTARFM has a bias of 2.55 K, unbiased RMSE (ubRMSE) of 2.57 K, and Pearson correlation coefficient (R) of 0.95 against the in-situ LST over 11290 samples at 12 sites, all of which are significantly better than that of the ESTARFM, with a bias of 4.73 K, ubRMSE of 3.80 K and R of 0.92. In the cross-satellite comparison, the ubESTARFM LST has a bias of -1.69 K, ubRMSE of 2.00 K, and R of 0.70 over 43 near clear-sky scenes, while the ESTARFM LST has a bias of 1.79 K, ubRMSE of 2.68 K, and R of 0.59. Overall, the ubESTARFM is able to avoid the accumulation of systematic bias, considerably reduce the deviation of uncertainty, and maintain a good level of correlation with validation datasets compared to the typical ESTARFM algorithm. It is a promising method to integrate reliable numeric values from coarse resolution LST and spatial heterogeneity from fine resolution LST, and may be further coupled with energy balance or radiative transfer models to better enable farm- or regional-scale water management strategy or decision making.

How to cite: Yu, Y., Renzullo, L., Tian, S., and Malone, B.: An unbiased spatiotemporal fusion approach to generate daily 100 m spatial resolution land surface temperature over a continental scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1501, https://doi.org/10.5194/egusphere-egu23-1501, 2023.

EGU23-2114 | Orals | GI6.3 | Highlight

Tracking tillage practices across European croplands using multi-scale remote sensing and machine learning. 

Nathan Torbick, Aoife Whelan, Nick Synes, Xiaodong Huang, and Vincent Cornwell

The adoption of regenerative agricultural practices is gaining traction as an approach to enhance soil health and sequester carbon to combat climate change. Several sustainability frameworks and programmes are now incentivizing producers to transition to regenerative farming. These evolving initiatives have created a need to build and operate Measurement, Reporting and Verification (MRV) platforms to track cropland practices and impacts. To help scale initiatives, we have developed an automated approach that leverages multi-source remote sensing, data science and machine learning for cost-effective, robust and transparent tracking of tillage practices. Our approach leverages time-series satellite observations from Sentinel-1 and Sentinel-2 constellations, along with ancillary data from SMAP, soils and weather. Within a hierarchical classification, these inputs are blended with dense, independent training data (i.e., “ground truth”) collected across Europe with tens of thousands of samples gathered across France, Belgium, Denmark and the UK. Training data includes observations of crop types and rotations, residue, soil disturbance and field conditions. Together, these multi-source data feed into gradient boosting and Convolutional Neural Networks to ultimately help seasonally classify tillage practices into conventional, reduced or no till at field scale for all major row crops. Withheld independent observations and data science best practices are used to tune model performance and class accuracy depending on regional schemes, residue categories and landscape practice variability. F1 score and Overall Accuracy achieve > 80% with some crop and tillage practice combinations (i.e. corn, soy, wheat conventional) > 0.9. In addition, we share lessons learnt and next challenges. With this approach, the Community of Practice can robustly track every field wall-to-wall over seasons and feed downstream applications, such as estimating Soil Organic Carbon and emissions process modelling. With these tools, and open operational data streams such as Copernucis, we can support scaling regenerative agriculture impacts and grow carbon farming initiatives and ecosystem service markets across Europe. 

How to cite: Torbick, N., Whelan, A., Synes, N., Huang, X., and Cornwell, V.: Tracking tillage practices across European croplands using multi-scale remote sensing and machine learning., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2114, https://doi.org/10.5194/egusphere-egu23-2114, 2023.

EGU23-2199 | Posters on site | GI6.3

The Operation and Service of National Land Satellite 1 

Hyewon Yun, Yun-Soo Choi, and Sunghee Joo and the National Geographic Information Institute Korea Land Satellite Center

Korean National Land Satellite 1 has been launched with a mission to map national geospatial information and to monitor land resource and disasters on March 22, 2021. The satellite has a precise optical payload of 5 multi-spectral bands (Pan, R, G, B, and NIR). It observes the ground of 12 kilometers width at a 0.5m GSD (Ground Sample Distance) mainly over the Korean Peninsula and global areas of interest during at least four years.

The product of National Land Satellite is classified to 4 levels: Basic geometry image based on initial satellite position (Level 1); Precise Ortho-rectified image (Level 2);

Reproduced 2D/3D information only with Level 2 (Level 3); and Reproduced 2D/3D information with Precise image(Level 2/3) and other spatial information (Level 4). As the first 0.5m-scale satellite, Level 1 and Level 2 products are open and accessible to the Korean public. In case of Level 2 product, the average location accuracy shows about 1~4m in Korea, depending on the number of available Ground Control Points (GCP) and Level 2 product will produce North Korea Digital Map at 1:5,000 scale. The level 3 and level 4 will be serviced to the public in stage from 2023. The Korea national land satellite can be used to monitor disaster damage, especially for monitoring climate change caused by increasing greenhouse gas emissions through increasing plastic waste. In addition, it is expected that it can be used to generate high value-added spatial information such as 3D spatial information through convergence between various spatial information and land satellite information.

 

Acknowledgment: This work was supported by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government and Korea Environment Industry & Technology Institute (KEITI) through Plastic-Free Specialized Graduate School funded by Korea Ministry of Environment (MOE).

Keywords : #National Land Satellite, #CAS500, #High resolution, #0.5m, #Diaster #plastic waste #climate change

How to cite: Yun, H., Choi, Y.-S., and Joo, S. and the National Geographic Information Institute Korea Land Satellite Center: The Operation and Service of National Land Satellite 1, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2199, https://doi.org/10.5194/egusphere-egu23-2199, 2023.

EGU23-3070 | ECS | Posters on site | GI6.3

A Study on Fine Particle Emission Characteristics in Dangjin Port Using High Resolution Scanning LiDAR 

Yuseon Lee, Jaewon Kim, and Youngmin Noh

As emissions from ships and marine sources account for a high proportion of fine particle emissions, interest in air pollutants generated in port areas and the need to prepare countermeasures are increasing. For port air pollutants, it is necessary to consider substances emitted from ships and various emission sources from the yard around ports. This study uses a scanning LiDAR system capable of observing PM10 and PM2.5 in a radius of up to 5 km at a high resolution of 30 m horizontally and left and right to check high-concentration pollutants generated around Dangjin Port(36.985476°N, 126.745613°E) in real time and corresponding substances tried to distinguish. The scanning LiDAR used in this study provides the Ångström exponent calculated from the extinction coefficient at both wavelengths of 1064 and 532 nm and the depolarization ratio at 532 nm. First, the Ångström exponent can confirm information about the particle size. In addition, the depolarization ratio is a parameter representing information on the asphericity of particles. It provides information on the classification of aerosol types depending on whether the particles are spherical or non-spherical. The concentration of fine particle generated was identified using the extinction coefficient, and the kind of particle was determined using the Ångström exponent and the depolarization ratio. The primary source of fine particle in the vicinity of Dangjin Port was an industrial complex, such as a steel mill located on the west side of Dangjin Port, and fine particle was also generated from the port's coal yard and moving ships. The diffusion direction of fine particle was closely related to the wind direction. The type of fine particle confirmed by a low Ångström exponent between 0 and 1 and a high depolarization ratio degree between 0.1 and 0.2 was confirmed as non-spherical scattering dust. Through this study, it was confirmed that it was possible to identify the generation and movement of fine particle in a wide area and to distinguish the types of particles using scanning lidar.

Acknowledgement

This work was supported by the “Graduate school of Particulate matter specialization.” of Korea Environment Industry & Technology Institute grant funded by the Ministry of Environment. Republic of Korea.

How to cite: Lee, Y., Kim, J., and Noh, Y.: A Study on Fine Particle Emission Characteristics in Dangjin Port Using High Resolution Scanning LiDAR, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3070, https://doi.org/10.5194/egusphere-egu23-3070, 2023.

EGU23-3071 | Posters on site | GI6.3

A Study on analysis of fine particle Distribution in Busan Port Area Using Scanning LiDAR 

Jaewon Kim, Juseon Shin, Shohee Joo, and Youngmin Noh

Busan is Korea's largest port city. Considering the large size of the port, measurement through a single monitoring station has limitations in expressing the spatial distribution of fine particles. In this study, a Scanning LiDAR system was used to overcome the limitations of existing observations. Scanning LiDAR is a remote sensing device that uses a laser as a light source to calculate distance information. It can calculate fine particle mass concentration and distance information through signal analysis of collected light from laser light scattered backward by fine particles. It is possible to observe the fine particle concentration in real-time and continuously for 24 hours at a resolution of 30 m within a radius of 5 km and to check the spatial distribution of particulate matter using this. Scanning LiDAR is located on the rooftop of the 9th Engineering Building, Yongdang Campus, Pukyong National University, Korea (latitude: 35.11, longitude: 129.09, about 10m above ground), and was observed from March 2nd to April 28th, 2022. Residential areas, ports, industrial facilities, etc., are included in the observation range, and the average fine particle concentration by area was obtained by dividing it into six areas. ( (A) residential area, (B) steel mill, (C) Gamman Port, (D) redevelopment area, (E) shipyard, (F) berth ). Areas A, B, and C are located to the northeast of the port area, while Areas D, E, and F are located to the west and southwest. As a result of observation, the average concentration of PM2.5 and PM10 in the A, B, and C areas tended to be higher than those in D, E, and F. In the case of Area A, despite being residential, it has a high average concentration. This is because the fine particle is emitted from Area C, where ships and loading equipment are located, and Area B, where steel mills are located. This can be attributed to the diffusion and movement of fine particles discharged from the port area to the downwind side due to the influence of the south wind series, which is the main wind during the observation period.

Acknowledgement

This work was supported by the "Graduate school of Particulate matter specialization"of Korea Environment Industry & Technology Institute grant funded by the Ministry of Environment, Republic of Korea.

How to cite: Kim, J., Shin, J., Joo, S., and Noh, Y.: A Study on analysis of fine particle Distribution in Busan Port Area Using Scanning LiDAR, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3071, https://doi.org/10.5194/egusphere-egu23-3071, 2023.

EGU23-3687 | Posters on site | GI6.3

Crop type mapping in Central and South Asia using Sentinel-1 and Sentinel-2 remote sensing data 

Christoph Raab and Viet Duc Nguyen

Crop type information derived from satellite remote sensing are of pivotal importance for quantifying crop growth and health status. However, such spatial information are not readily available for countries in Central and South Asia, where smallholder farmers play a dominant role in agricultural practice, and food security. In this study, we provide insights into crop type mapping for three study sites in the region: 1) Panfilov District in Kazakhstan, 2) Jaloliddin Balkhi District in Tajikistan, and 3) Multan District in Pakistan. A collection of Sentinel-2 and Sentinel-1 satellite data was used along with the random forest classification algorithm. To train and validate the classification model, field data were collected between May and October 2022 in each of the study areas. Our main objective was to evaluate the performance of a combined Sentinel-2 and Sentinel-1 mapping approach in comparison to a single source result. In addition, this contribution will provide insights into the performance with regard to crop type mapping accuracy of different temporal data aggregation intervals. Preliminary results indicate a small increase in overall accuracy for a combined Sentinel-2 and Sentinel-1 mapping approach. However, Sentinel-2 data might be sufficient for reliable crop type mapping, in case cloud coverage is not a constraint. Future studies might consider evaluating the potential benefit of using a full Sentinel-1 data set without temporal aggregation for mapping crop types.

How to cite: Raab, C. and Nguyen, V. D.: Crop type mapping in Central and South Asia using Sentinel-1 and Sentinel-2 remote sensing data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3687, https://doi.org/10.5194/egusphere-egu23-3687, 2023.

To track global environmental change and evaluate the risk to sustainable development, analysts and decision-makers in government, civil society, finance, and industry need the fundamental geospatial data products known as Land Use and Land Cover Change (LULCC) maps. Our research studied LULCC variations in a timeframe of 5 years in the Gabala district. Sentinel 2 open-source products were used to compare and categorize the procedure over one-year time intervals. For this investigation, the discrete indexing method was developed and used. The approach we used was focused on obtaining multiple indices and using them to improve classification performance. The Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Bare Soil Index (BSI), Normalized Difference Tillage Index (NDTI), and Salinity Index (SI) are the indices evaluated. The most crucial variables were determined and classified using the random forest classifier in LULCC. The Sentinel Application Platform of the European Space Agency (SNAP ESA) algorithm was used to analyze the process and performed over 90% accurate predictions when applied to the testing dataset. Results revealed that using the RS technique, time and cost-efficient analyses are possible and reliable for developing socioeconomic and ecological growth strategies.

How to cite: Ahadov, B. and Karimli, N.: Analyzing Land Use/Land Cover Changes and its Dynamics Using Remote Sensing Data: A case study of Gabala, Azerbaijan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3777, https://doi.org/10.5194/egusphere-egu23-3777, 2023.

EGU23-4049 | ECS | Orals | GI6.3

Comparison of coverage obtained by land use classification using landsat and RapidEye. Case study: Tenosique, Tabasco, Mexico. 

Jacob Nieto, Nelly Lucero Ramírez Serrato, Mariana Patricia Jácome Paz, and Tania Ximena Ruiz Santos

Land use classification studies help to quantify the changes in forest cover that may occur at a given site over time. This quantification helps us understand the effect of the natural and anthropogenic processes over the study site. Activities such as agriculture, cattle ranching and illegal logging, which in turn are related to the evolution of the site's public policies, can be evaluated through classification studies. Tenosique area, in the southeast of Mexico, is a clear example of the consequences of these programs, being largely benefited by economic consent for agriculture and more for cattle ranching, and, suffering,  in 1974, a complete  turn in productivity activities because it was given full support in exploration and obtainment of hydrocarbons. This led to a crisis that left the area devastated and later became a protected area in 2008, which resulted in illegal logging, and land use for agriculture within the tropical forest, among others. With remote sensing, the task of quantifying the effect of public policies has become increasingly influential and many studies are being carried out to evaluate the current state of Tenosique. However, the results are known to depend directly on the images and methodologies used for this task.Because of this, this project, proposes, in a practical exercise, to determine how much these results may vary with respect to the images used as input for the supervised classification, and if this variation is significant enough to establish rules of operation on methodologies and determine ranges of the parameters of the images to perform a better land use classification. The aim of this project is to determine the margin of variability in the classification result over a given study area, using images from different satellite platforms, Landsat and RapidEye, together with the analysis of the properties of each image, when acquired by the satellite. In addition, the degree of affectation in the image by meteorological changes such as tropical haze in the source image and its respective corrected image was evaluated. The main results are:  individualization of complications and advantages derived from the resolution of the images, identification of the main steps for the possible corrections that can be needed for the images, advantages that are used for analyzing the metadata before doing some process to the images and finally, presenting a decision tree based on this information. It is important to emphasize that this study allows us to delimit the scope and limitations of the land use classifications made in the study area. Acknowledgments: Tania Ximena for the Planet images and Humberto Abaffy-Castillo, Ulises Gracía-Martínez and Mario Seinos-Jiménez for technical help in the project.

How to cite: Nieto, J., Ramírez Serrato, N. L., Jácome Paz, M. P., and Ruiz Santos, T. X.: Comparison of coverage obtained by land use classification using landsat and RapidEye. Case study: Tenosique, Tabasco, Mexico., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4049, https://doi.org/10.5194/egusphere-egu23-4049, 2023.

EGU23-5481 | ECS | Posters on site | GI6.3

A Study on the background surface reflectance retrieval of near-UV wavelength using GK-2B/GEMS data 

Suyoung Sim, Kyung-soo Han, Sungwon Choi, Noh-hun Seong, Daeseong Jung, Jongho Woo, and Nayeon Kim

 Surface reflectance is the product of removing atmospheric scattering and absorption effects from the Top-Of-Atmosphere (TOA) radiation using the Radiative Transfer Model (RTM), and it refers to the reflectance according to the solar and satellite zenith angles at the time of observation. Surface reflectance is an essential input data for other Level-2 calculation algorithms such as aerosol, cloud, ozone, gas tracers, etc. Therefore, if the surface reflectance data has missing value, it will lead to missing other products that use it. However, when there are clouds in the satellite image, there is a problem with that blank pixels are generated because the surface reflectance cannot be calculated. Therefore, in this study, we conducted an algorithm to calculate background surface reflectance (BSR) without missing values with high accuracy using GK-2B/Geostationary Environment Monitoring Spectrometer (GEMS) data. The BSR is an estimate of the surface reflectance under specific observation conditions (solar and satellite zenith angles) and is a product that avoids the calculation precedence dilemma between AOD and surface reflectance. In many studies, the BSR is mainly calculated using the minimum reflectance method, but it has limitations in not considering the angular conditions at the time of observation and the reflectance characteristics of the ground surface. To overcome these limitations, a realistic BSR calculation was performed considering the anisotropic reflectance characteristics of the surface according to the observation conditions through bi-directional reflectance distribution function (BRDF) modeling.

 Surface reflectance, which is an input variable for BRDF modeling, was calculated based on the Look-Up Table (LUT) generated using the Second Simulation of Satellite Signal in the Solar Spectrum (6SV) RTM. At this time, LUT interpolation was additionally performed through the 6d-interploation technique to resolve discontinuities that may occur in LUT-based atmospheric correction. For BRDF modeling, the kernel-based Roujean model was used, and the optimal synthesis period for BRDF modeling considering the characteristics of the GEMS satellite was selected. To evaluate the accuracy of BSR, the simulated BSR through the BRDF model and the observed surface reflectance were compared, and it was confirmed that the BSR showed higher accuracy than the minimum reflectance method. In the future, the BSR produced through this study is expected to have a great impact on improving the calculation accuracy of aerosol and atmospheric products of GEMS satellites.

How to cite: Sim, S., Han, K., Choi, S., Seong, N., Jung, D., Woo, J., and Kim, N.: A Study on the background surface reflectance retrieval of near-UV wavelength using GK-2B/GEMS data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5481, https://doi.org/10.5194/egusphere-egu23-5481, 2023.

EGU23-5697 | ECS | Posters on site | GI6.3

Applicability evaluation of Spectral Band Adjustment Factor for Cross-Calibration using high resolution optical satellite 

NaYeon Kim, Kyung-soo Han, Sungwon Choi, Noh-hun Seong, Daeseong Jung, Suyoung Sim, and Jongho Woo

Currently, research such as time-series vegetation index analysis, disaster monitoring, and aerosol monitoring are being conducted using high-resolution optical satellites. However, since each high spatial resolution satellite has differences in the spectral response of the two sensors, there is a limit of time-series monitoring when using satellite data fusion. In this study, the Spectral Band Adjustment Factor (SBAF) was calculated for Sentinel-2A and Landsat-8, which are high-resolution satellites, and cross-calibration was performed. When combining data from two satellites, it is necessary to overcome the difference in radiometric sensor characteristics of each satellite. The bias due to the difference in the spectral response of the two satellites was corrected through an adjustment factor derived from the EO-1 Hyperion data. As a result of applying SBAF, the difference in value was within 5%. In the future, based on the results derived from this study, it is expected to make a great contribution to continuous monitoring and time series analysis of aerosols including PM2.5.

※ This work was supported by the "Graduate school of Particulate matter specialization." of Korea Environmental Industry & Technology Institute grant funded by the Ministry of Environment, Republic of Korea.

How to cite: Kim, N., Han, K., Choi, S., Seong, N., Jung, D., Sim, S., and Woo, J.: Applicability evaluation of Spectral Band Adjustment Factor for Cross-Calibration using high resolution optical satellite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5697, https://doi.org/10.5194/egusphere-egu23-5697, 2023.

The Yellow Sea (YS) and East China Sea (ECS) have the world’s largest supply of floating algae. The golden tides (Sargassum horneri) appear mainly in the YS and ECS, but become entangled as they drift. The floating harmful macroalgae blooms (HMBs) obstructs navigation and is a huge socioeconomic problem in the vicinity of coastal areas. To determine the origin and movement trend of the golden tide in the YS and ECS, the multi-satellite sensor data (e.g. Sentinel-2 and GOCI) was used to detect the floating macroalgae which was determined by the Alternative Floating Algae Index (AFAI, Wang and Hu, 2016) and mapped over the study area using a 15-year data. 

The occurrence period of the golden tide from 2008 to 2019 determined that they were found between January and March in the China coast, and the patches of floating macroalgae in Jeju Island and the west coast of Korea were observed between March and May. The macroalgae was detached from the waters near the Yangtze River and Zhejiang Province, China and then floating into the east and north-east ward influenced by the Tsushima warm current or Kuroshio. The build-up of the gold tide was occurred in the middle of the ECS and pile-up of them was in the coast of Korea from March to May. Recently, changes have begun to appear in movement trend of the golden tide. During 2020 and 2021, the golden tide was found in the western coast of Korea on January and in the northern waters of Jeju Island, Korea on February, and at the same time, another large-scale patch was found in the waters near the mouth of the Yangtze River and Zhejiang Province, China. From the results, the golden tide outbreak occurred that first flowed in west coast of Korea and northern Jeju Island in the winter, and then another outbreak occurred in southern Jeju Island in spring. It was analyzed that the movement trend of the golden tide has changed in recent years that the golden tide presented in the YS and ECS have different origins such as Bohai Bay and near the Yangtze River and Zhejiang Province, China.

How to cite: Son, Y. B. and Choi, J.-K.: Tracing the golden tide outbreak in the Yellow Sea and East China Sea over a 15-year period using multi-satellite sensor data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6085, https://doi.org/10.5194/egusphere-egu23-6085, 2023.

EGU23-6520 | ECS | Orals | GI6.3

Mapping Cambodian Wetlands with Satellite Imagery and Google Earth Engine’s Machine Learning Algorithm. 

Vasudha Darbari, Hackney Christopher, Vasilopoulos Grigorios, Forsters Rodney, and Parsons Dan

The wetlands and lakes that make up more than 30% of Cambodia's terrain are home to a diverse range of resources and biodiversity. More than 46% of the population lives and works in these wetlands while 80% of the local population relies on their vital resources for sustenance such as fish, food, water and vegetables. This makes Cambodia one of the nations with the highest reliance on wetland and lake ecosystems in the world. On-going development in the region has boosted the rates of  urbanization. Urban expansion has deteriorated wetland ecosystems through land reclamation and infilling projects as well as hydrological and sediment cycle disruptions. It has also increased the demand for mined sand from the Mekong River. Mapping and monitoring the extent and distribution of wetland ecosystems in order to quantify the impact of human activities on these vital areas is critical for maintaining the ecological balance and promoting the sustainable development of an extensively eco-service dependent country such as Cambodia. In this study we combine spaceborne multispectral and radar remote sensing datasets with machine learning classification models and algorithms within the Google Earth Engine to monitor the changes observed in Cambodian wetlands through time. Our classifier is trained by comparing Sentinel 1 Synthetic Aperture Radar data to corresponding multispectral images captured from Landsat. We then use the classifier to monitor wetland extent through time from 1989 to present using merged Landsat 5 and 8 databases. With our maps and areal statistics, we identify the spatio-temporal trends and changes in wetland cover linked to climatic patterns and local anthropogenic influence connected to sand mining from the Mekong River and land infilling. In the last 15 years, about half the country’s wetlands have disappeared, with 15 out of 25 lakes near the capital completely infilled with sand that can be clearly observed with analysis of satellite data.

How to cite: Darbari, V., Christopher, H., Grigorios, V., Rodney, F., and Dan, P.: Mapping Cambodian Wetlands with Satellite Imagery and Google Earth Engine’s Machine Learning Algorithm., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6520, https://doi.org/10.5194/egusphere-egu23-6520, 2023.

EGU23-6548 | ECS | Posters on site | GI6.3 | Highlight

Using LiDAR on a Ground-based Agile Robot to Map Tree Structural Properties  

Omar Andres Lopez Camargo, Kasper Johansen, Victor Angulo, Samer Almashharawi, and Matthew McCabe

The widespread use of diameter at breast height (DBH) and tree height attributes as a non-destructive indirect estimation of tree parameters (e.g., above-ground biomass, volume, age, and carbon stock) demands efficient and accurate surveying methods. However, traditional surveys, which are primarily manual, are often time-consuming, inaccurate, inconsistent, and might suffer from observer-bias. This study applies an agile quadruped robot, Spot from Boston Dynamics, and a mounted LiDAR system for mapping and measuring tree height, diameter at breast height (DBH), and tree volume. This project uses the Spot Enhanced Autonomy Payload (EAP) navigation module as the source of LiDAR data. The use of this module has two main advantages. First, Spot EAP's VLP-16 sensor is a low-beam LiDAR that, as demonstrated in previous research, is capable of estimating tree structural parameters while consuming less time and data than robust systems such as Terrestrial Laser Scanning (TLS). Second, using an existing payload as the primary source of data without disabling its default function results in more efficient payload capacity utilization and, as a result, lower energy consumption, in addition to making room for additional payloads. The experiment was conducted for 41 trees (23 Erythrina variegata and 18 Ficus altissima) in a park on the campus of King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. TLS data were used to compute the height and volume reference data, while manual measurements were used to obtain DBH reference data. The robot-derived point cloud generation methodology was based on a multiway registration approach in which a total of 76 scans were acquired from 4 different locations using multiple poses of the robot to overcome the short field of view of the LiDAR sensor. As a result of processing the scans, a point cloud for each of the trees was obtained. The height estimations, which consist of a difference within Z coordinates, obtained a mean absolute error (MAE) and a mean percentage error (MPE) of 6.71 cm and 1.31% respectively. The DBH estimation based on circle-fitting algorithms obtained an MAE and an MPE of 2.55 and 12.99% respectively. The volume estimation obtained a coefficient of determination of 0.93. When compared to the most recent approaches available in the literature, the results for height and volume were satisfactory, yielding higher accuracy than other studies in some cases. The results for DBH estimation were also comparable to those in the literature. The main sources of error were tree occlusion and inclined trees, both of which are solvable by including more scanning locations and increasing the robustness of software estimation. Consequently, the acquisition system is not a barrier to future improvements. This work successfully introduced one of the first methods for using agile robots in high throughput field phenotyping. The use of agile robots addresses some of the major challenges for deploying ground-based robotics in high throughput field phenotyping, allowing for a higher assessment frequency without causing soil compaction and damage, as well as bringing unprecedented adaptation to difficult terrains.

 

How to cite: Lopez Camargo, O. A., Johansen, K., Angulo, V., Almashharawi, S., and McCabe, M.: Using LiDAR on a Ground-based Agile Robot to Map Tree Structural Properties , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6548, https://doi.org/10.5194/egusphere-egu23-6548, 2023.

The detection of hydromorphological structures gained more attention during the last decades. Many approaches of different scopes, scales and purposes have been developed. They can either be classified as stand-alone methods, like the German River Habitat Survey, which evaluates the hydromorphological integrity on a catchment scale or as methods being part of an ecological assessment, which includes the estimation of hydromorphological characteristics on the scale of respective study sites. The main purposes of detecting hydromorphological structures are to investigate the spatial characteristics and temporal scale of change to collect reliable and comparable data in a sampling setup of an ecological multi habitat sampling. Especially river restoration projects often lack the detection of positive effects on aquatic biota induced by missing or wrong development of physical river habitat structures (PRHS).

Most methods available for determining PRHS are insufficient for this task as they lack sufficient temporal and spatial resolution. Examples thereof include overview methods based on topographic maps and remote sensing. On the other hand, visual assessment methods do not reach the required accuracy and objectiveness or are too general if too few hydromorphological structures are assessed. Therefore, this research proposes the combination of Unmanned Areal Vehicle (UAV) and high-resolution sensors. This combination creates high-resolution imagery or point clouds by using multispectral sensors or Lidar scanner.

In a case study of the river Lippe, the methods for detecting PRHS on Structure from Motion (SfM) high-resolution imagery with deep learning, based classification methods are applied. Results indicate the potential from different deep learning classification approaches to identify physical river habitat structures being able to assess the development over time.

How to cite: Dacheneder, F.: Detecting hydromorphological structures using an AI-based analysis of high-resolution drone imagery to access physical river habitat development, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6995, https://doi.org/10.5194/egusphere-egu23-6995, 2023.

EGU23-7538 | Posters on site | GI6.3

Surface temperature retrieval at mid-infrared band using a combination of low-orbit and geostationary orbit satellite imagery 

Kwonho Lee, Heeseob Kim, Seonghun Pyo, and Seunghan Park

Infrared remote sensing technique has been widely used for the characteristics of objects since it
has the advantage of higher atmospheric transmittance than visible wavelengths. However, the
Mid-Wave InfraRed (MWIR) region close to the visible band can be partially affected by solar
radiation, so the solar radiation and attenuation in the atmosphere cause errors in the target
detecting. In this study, an algorithm for retrieval of the mid-infrared surface temperature was
developed by using a combination of the GEO-KOMPSAT-2A (GK-2A) satellite and Landsat data.
Through the comparison with ground observations, it was found that the surface temperatures at
MWIR band retrieved are less than 3K, and a statistically significant level of mutual comparison
was obtained. Therefore, despite the limitations of the MWIR band, the new methodology can be
applied to determine the surface-level temperature through the coupling between the two
different orbit satellites.

Acknowledgement
This research was supported by the Korea Aerospace Research Institute (FR22H00W01) in
2022-2023.

How to cite: Lee, K., Kim, H., Pyo, S., and Park, S.: Surface temperature retrieval at mid-infrared band using a combination of low-orbit and geostationary orbit satellite imagery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7538, https://doi.org/10.5194/egusphere-egu23-7538, 2023.

EGU23-8857 | ECS | Orals | GI6.3

Identification and remediation-related monitoring of potential toxic elements (PTE) in the hyperaccumulator plant Brassica juncea with hyperspectral imaging. 

Friederike Kästner, Theres Küster, Hannes Feilhauer, and Magdalena Sut-Lohmann

Across Europe there are 2.5 million potentially contaminated sites due to natural and anthropogenic activities. In this regard, phytoremediation approaches are need as a cost-effective and ecosystem-friendly technique to rehabilitate soil compared to conventional methods. Hyperspectral imaging provides an ideal method to improve and monitor existing bioremediation methods, using hyperaccumulator plants. In our study, the hyperaccumulator plant Brassica juncea showed a high tolerance to the accumulation of Cu, Zn and Ni. Hyperspectral measurements were conducted with a HySpex VNIR-SWIR hyperspectral sensor (408-2500 nm) in-situ and in the laboratory. To monitor and optimize the process of accumulation with hyperspectral imaging, we calculated different vegetation indices, related to metal-induced plant stress, such as TCARI/OSAVI, Chlorophyll Vegetation Index (CVI), Red-Edge Stress Vegetation Index (RSVI), Normalized Pigments Chlorophyll Index (NPCI), Red-Edge Inflection Point (REIP) and Disease Water Stress Index (DWSI), using various pre-processing steps (raw, smoothed and brightness corrected data). In addition, the relation between the different indices and the measured heavy metal content in the samples were tested with a multivariate technique using Partial Least Squares Regression (PLSR). Our results revealed, even with no pre-processed image data, changes in chlorophyll- and red-egde-related indices with increasing PTE concentration. With hyperspectral imaging we are already able to monitor differences of the PTE accumulation within the hyperaccumulator plant Brassica juncea.

How to cite: Kästner, F., Küster, T., Feilhauer, H., and Sut-Lohmann, M.: Identification and remediation-related monitoring of potential toxic elements (PTE) in the hyperaccumulator plant Brassica juncea with hyperspectral imaging., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8857, https://doi.org/10.5194/egusphere-egu23-8857, 2023.

EGU23-8888 | ECS | Posters on site | GI6.3

Monitoring the environmental conditions in landfill sites: a case study of Fyli - Ano Liosia, Attica Region, Greece 

Eirini Efstathiou and Vassilia Karathanassi

Landfills constitute a major environmental issue that needs to be handled, especially when they are located near large urban areas. In landfills, end up most of the city non-hazardous solid waste (mainly household waste), which are not appropriate for recovery/recycling and thus they are disposed in the ground for decomposition process. Monitoring of such sites is significantly important, due to the fact that the decomposition process - which includes the release of hot gases - is harmful to the environment and to the human health.  The increase of Land Surface Temperature (LST) in landfill sites and the methane gas emissions, which contribute to the greenhouse effect, can be monitored using remote sensing methods and techniques. This type of monitoring is very important for safeguarding the surrounding environment, especially in environmentally sensitive areas, as are those located close to densely populated areas, and therefore, many studies have been carried out focusing on the monitoring of the environmental impacts of landfills through remote sensing. In relevance with previous literature, the current study aims at monitoring the environmental impact of the active landfill site of Fyli – Ano Liosia, Attica, Greece. For the needs of the study, time series of Land Surface Temperature (LST) have been processed as extracted from Landsat 8-9 satellite imagery. The analyzed time period is from January 2021 to December 2022. LST data have been extracted from two areas within the landfill, one in the active landfill area and the second one in an area that has been rehabilitated and is no longer active. Furthermore, we selected to study LST data from a bare soil area which is located at a short distance from the landfill in order to find temperature deviation caused by the decomposition processes. The land surface temperatures inside the landfill have been compared with those of the bare soil as well as with the air temperature, which is provided by the weather station of Ano Liosia of METEO (infrastructure of National Observatory of Athens for weather forecasting). It has been observed that the LST in the active area of ​​the landfill is higher by 1°C-2°C compared to that in the inactive area of ​​the landfill, and by 2°C-3°C compared to the bare soil LST. A reversal of this phenomenon has been observed during the snowy winter months due to different snowmelt rates and possibly due to a slowdown of the decomposition process. The air temperature was found to be significantly lower than the LST, as expected.

How to cite: Efstathiou, E. and Karathanassi, V.: Monitoring the environmental conditions in landfill sites: a case study of Fyli - Ano Liosia, Attica Region, Greece, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8888, https://doi.org/10.5194/egusphere-egu23-8888, 2023.

EGU23-9489 | ECS | Posters on site | GI6.3 | Highlight

Resolution-enhanced Hyperspectral EnMAP data: CubeSat-based high resolution data fusion approach 

Victor Angulo, Kasper Johansen, Jorge Rodriguez, Omar Lopez, Jamal Elfarkh, and Matthew McCabe

Hyperspectral (HS) images obtained from space are useful for monitoring different natural phenomena on regional to global scales. The Environmental Mapping and Analysis Program (EnMAP) is a satellite recently launched by Germany to monitor the environment and explore the capabilities of hyperspectral sensors in the 420 and 2450 nm range of the spectrum. However, the data captured by the EnMAP mission have a ground sampling distance (GSD) of 30 m. This limits the use of the data for some applications that require higher spatial resolution (<10 m). This study examines the potential for improving the resolution of hyperspectral data using high resolution multispectral (MS) data obtained by Cubesats. Specifically, this work uses the data captured by the PlanetScope constellation, which has more than 150 CubeSats in low Earth orbit, with a high spatial and temporal resolution. The approach adopted leverages (1) the spectral capability of the hyperspectral EnMAP sensor, with a bandwidth of 6.5 nm in the visible and near infrared (VNIR) range (420–1000 nm) and 10 nm in the SWIR range (900–2450 nm), and (2) the spatial capability of the multispectral PlanetScope data, with a GSD of 3 meters, to enable significant spatial improvements due to its high spatial resolution. The main components of this work include: (i) area of interest clipping (ii) data co-registration, (iii) HS-MS data fusion, and (iv) quality assessments using the Jointly Spectral and Spatial Quality Index (QNR). In this study, a 2 km x 2 km area of interest was selected in the Malaucene region of France, where six state-of-the-art HS-MS fusion methods were evaluated: (1) fast multi-band image fusion algorithm (FUSE), (2) coupled nonnegative matrix factorization (CNMF), (3) smoothing filtered-based intensity modulation (SFIMHS), (4) maximum a posteriori stochastic mixing model (MAPSMM), (5) Hyperspectral Superresolution (HySure), and (6) generalized laplacian pyramid hypersharpening (GLPHS). Quality assessments of the enhanced data showed that high spectral and spatial fidelity are maintained, with the best performing fusion method being FUSE with a QNR of 0.625 followed by the MAPSMM method with a QNR of 0.604. Overall, this study advocates the benefits associated with the fusion of hyperspectral and multispectral data to obtain enhanced EnMAP data at 3 m GSD. 

How to cite: Angulo, V., Johansen, K., Rodriguez, J., Lopez, O., Elfarkh, J., and McCabe, M.: Resolution-enhanced Hyperspectral EnMAP data: CubeSat-based high resolution data fusion approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9489, https://doi.org/10.5194/egusphere-egu23-9489, 2023.

EGU23-10320 | ECS | Posters on site | GI6.3

Sensitivity analysis and discontinuity removal of 6SV LUT-based surface reflectance for each channel: based on GEO-KOMPSAT-2A 

Daeseong Jung, Kyung-soo Han, Noh-hun Seong, Suyoung Sim, Jongho Woo, Nayeon Kim, and Sungwon Choi

To monitor the surface based on Earth observation optical satellites, accurate atmospheric correction of satellite images is required. Surface reflectance is calculated using a look-up table (LUT) based on a radiative transfer model. In addition, atmospheric gas components and geometric information of solar and satellite observations used in LUT construction are applied to each channel at equal intervals. However, the atmospheric gas components are sensitive to the atmospheric effect in a specific wavelength range of the satellite sensor. The higher the geometric information appears in the satellite observation area, the greater the variability of the atmospheric effect occurs because the moving distance of light increases. Because of this, LUT-based atmospheric correction at equal intervals generates discontinuities in surface reflectance in satellite images. In this study, to improve the quality of the surface reflectance applied with atmospheric correction, a Second Simulation of a Satellite Signal in the Solar Spectrum Vector (6SV) radiation transfer model was used to analyze the sensitivity of the surface reflectance for each channel according to the GEO-KOMPSAT-2A-based atmospheric gas component and the geometric information of the solar and satellite observations. After figuring out the variability of surface reflectance for each channel according to the intervals of variables used in LUT construction, an error analysis of surface reflectance was performed for the optimal LUT interval considering the interpolation technique. In the future, it is considered that the results of this study can be used to identify LUT-based surface reflectance characteristics for removing discontinuities in surface reflectance, including increasing the utilization of geostationary satellite images.

How to cite: Jung, D., Han, K., Seong, N., Sim, S., Woo, J., Kim, N., and Choi, S.: Sensitivity analysis and discontinuity removal of 6SV LUT-based surface reflectance for each channel: based on GEO-KOMPSAT-2A, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10320, https://doi.org/10.5194/egusphere-egu23-10320, 2023.

EGU23-10586 | Posters on site | GI6.3

Application cases of remote sensing-integrated crop model to simulate and predict crop yield with satellite images 

Seungtaek Jeong, Jong-min Yeom, Jonghan Ko, Daewon Chung, and Sun-Gu Lee

The remote sensing-integrated crop model (RSCM) was designed to simulate crop growth processes and yield using remote sensing data. The RSCM is based on the radiation use efficiency (RUE) model and employs a within-season calibration procedure recalibrating the daily crop leaf area index (LAI) using satellite images. And it has functions to calculate daily biomass, evapotranspiration (ET), gross primary productivity (GPP), and net primary productivity from the LAI in addition to crop yield. In previous studies, the essential crop growth parameters required in the model, such as RUE, light extinction coefficient, specific leaf area, base temperature, etc., were determined through field experiments. And its performances were validated using various remote sensing data, including proximity sensing data, drone images, and satellite images. Among them, this study presented the application results with satellite images in the RSCM. The target crop is rice (Oryza Sativa), one of the world's major crops, and the study areas range from South Korea to Northeast Asia. Satellite images and meteorological data were used differently depending on the study sites. The types of satellite images used in this study are the RapidEye, the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Terra/Aqua satellite, and the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) of Communication, Ocean and the Meteorological (COMS) satellite. And gridded data for air temperature and solar radiation was acquired from the Korea Local Analysis and Prediction System (KLAPS) and the European Centre for Medium-Range Weather Forecasts (ECMFW). The primary application of the RSMC is to simulate rice yield, but some results showed crop growth factors such as biomass, LAI, GPP, and ET. In addition, the most recent study performed the early prediction of crop yield by combining deep learning with crop models. Through this study, it is possible to know the future utilization of the RSCM model in the agriculture and satellite application fields.

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (RS-2022-00165154, "Development of Application Support System for Satellite Information Big Data").

How to cite: Jeong, S., Yeom, J., Ko, J., Chung, D., and Lee, S.-G.: Application cases of remote sensing-integrated crop model to simulate and predict crop yield with satellite images, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10586, https://doi.org/10.5194/egusphere-egu23-10586, 2023.

EGU23-11414 | ECS | Orals | GI6.3

Temporal variations of United Arab Emirates coastline from 1991 to 2021 

Justine Sarrau and Abdelgadir Abuelgasim

In the context of global sea level rising, coasts are directly impacted. The retreat to coastlines and submersion of anthropic installations are among the major impacts. It is thus imperative to continuously monitor the coastlines status and devise the means and techniques to effectively assess their status. The United Arab Emirates (UAE) for example is a country which has a long sandy coastline. In this research, an algorithm was developed that makes use of remote sensing temporal data to assess the variability of the coastline in the UAE. The algorithm is used to automatically extract the whole coastline between 1991 and 2021 from Landsat 5 and 8 satellite images. They were selected for 1991, 2001, 2013 and 2021 because of the availability of data, and the significant changes that have been done in coastal areas due to urban development during this period.

Only the Landsat spectral bands of green and near-infrared were utilized to calculate the spectral index of detection of the coast DDWI (Direct Difference Water Index). It is the first step of the algorithm developed. Then is used an automatic threshold Otsu to differentiate the land from water. The result is filled to remove the main artifacts and a canny edge detector is used to detect the coastline. At the end of the algorithm, the result is georeferenced because it lost it during the process. The georeferenced layer is polygonised so that the remaining artifacts are easier to remove. Then, a mask layer was created including boats, clouds, etc… and it is removed from the polygonised layer to get the final extracted coastline.

The preliminary findings of this study show that the sandbanks have increased during the period of the study along the Arabian Gulf waters, suggesting that the coastline is retreating. The results showed a development of the sandbanks towards the Arabian Gulf in several places along the northern coastline but also their general retreat on the north-western one. This can be explained by the sediment settlement or the backfills that have been done to create new islands especially around Abu Dhabi city and Dubai. The creation of mangroves plantations or port infrastructures in the same place has completely changed the coastline layout of the UAE.

On the other side of the UAE, along the sea of Oman, the sandbanks have retreated, suggesting either soil erosion by water currents or advancement of the coastline. The results show no significant change at all and no sandbanks. The only changes observed are linked to the anthropic modification of the coast. While the coastline did not change, the developed algorithm detected scattered sandbanks as the coastline. This confusion likely comes from the similar reflectance of sandbanks in shallow water with the sand of the coast. A further improvement for the developed algorithm will be pursued in the future to reduce such confusions.
This methodology is applicable worldwide, but it is necessary to monitor the results for sandy areas such as the Middle East.

How to cite: Sarrau, J. and Abuelgasim, A.: Temporal variations of United Arab Emirates coastline from 1991 to 2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11414, https://doi.org/10.5194/egusphere-egu23-11414, 2023.

EGU23-12111 | Orals | GI6.3

Multi-source UAV remote sensing and AI for crop growth monitoring 

Zhigang Sun, Wanxue Zhu, Ehsan Eyshi Rezaei, Jinbang Peng, Danyang Yu, and Stefan Siebert

Accurate and in-time monitoring of cropping systems is critical to precision farming in order to facilitate decision-making for agronomic management and enhancing crop yield under changing climate. In this study, multi-source unmanned aerial vehicle (UAV) remote sensing observations were conducted at several key growing stages of crops at a standard wheat-maize cropping system field trials in the North China Plain from 2018 to 2020. Crop leaf area index, above-ground biomass, chlorophyll content, grain yield, and plant density were estimated using multi-source UAV remote sensing observations (including RGB, multi/hyperspectral, LiDAR, and thermal sensors) processed by machine/deep learning approaches.

In this study, we will give a comprehensive research introduction focusing on how to improve the estimation accuracy of the above crop growth variables via UAV remote sensing and machine/deep learning approaches, including three aspects:

(1) Data source and fusion, including the integration of multi-source UAV information for comprehensive maize growth monitoring, comparison of UAV-based point clouds with different densities for crop biomass estimation, and crop chlorophyll content estimation using multi-scale hyperspectral information.

(2) Optimization of UAV observation management: we will answer when is the most relevant phenological stage for maize yield estimation via high-frequent UAV observations; investigate extrapolation artefacts, validate the suitability and discuss the uncertainty of the UAV-based strategies for 'model calibration at a small site while applying these models at a large extent' for crop monitoring.

(3) Modeling improvement will give two cases to introduce improving crop biomass estimation accuracyand realize the plant density counting during the vigorous growing period employing deep learning.

How to cite: Sun, Z., Zhu, W., Eyshi Rezaei, E., Peng, J., Yu, D., and Siebert, S.: Multi-source UAV remote sensing and AI for crop growth monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12111, https://doi.org/10.5194/egusphere-egu23-12111, 2023.

EGU23-12310 | Orals | GI6.3 | Highlight

Integration between space- and ground-based observations in areas prone to volcanic hazard: the experience of Mt. Etna Supersite 

Giuseppe Puglisi, Alessandro Bonforte, Maria Fabriza Buongiorno, Lucia Cacciola, Francesco Guglielmino, Gaetana Ganci, Massimo Musacchio, Simona Scollo, Danilo Reitano, Malvina Silvestri, and Letizia Spampinato

The Geohazard Supersites and Natural Laboratories (GSNL) is an initiative of the Group of Earth Observation (GEO) that has started in 2007 with the Frascati declaration, in which the GeoHazards Community of Practice recommended to: “... stimulate international and intergovernmental effort to monitor and study selected reference (geologic hazards) sites, by establishing open access to relevant datasets according to GEO principles, to foster collaboration between various partners and end users”. Since the beginning the main idea has been the improvement of the hazard assessment by combining space- and ground-based datasets provided by the Space Agencies and the research institutions managing the in-situ observation systems, respectively.

According to the definition of Supersite, since the early stage of the GSLN initiative, Mt. Etna has been identified as one of the Supersites due to its almost continuous eruptive activity, the great amount of satellite and in-situ data available, and the advanced in-situ multi-parametric observing systems. Officially, Mt. Etna is a Permanent Supersite since 2014. The Space Agencies provide quotas of SAR and high-spatial resolution optical multispectral satellite data and INGV offers geophysical, geochemical, and volcanological data. The data are accessible via an open access platform implemented in the framework of the EC FP7 MED-SUV project, and is going to be integrated in the EPOS research infrastructure.

During the past few decades, Mt. Etna has erupted almost every year offering the optimal conditions to apply the Supersite concept; thus here we report some relevant examples of the integrated use of the space-and ground-based data applied to Mt. Etna’s eruptions, highlighting how such complementarity improved the monitoring of the eruptive events and the assessment of the associated hazards.

How to cite: Puglisi, G., Bonforte, A., Buongiorno, M. F., Cacciola, L., Guglielmino, F., Ganci, G., Musacchio, M., Scollo, S., Reitano, D., Silvestri, M., and Spampinato, L.: Integration between space- and ground-based observations in areas prone to volcanic hazard: the experience of Mt. Etna Supersite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12310, https://doi.org/10.5194/egusphere-egu23-12310, 2023.

Acid mine drainage (AMD) is considered as one of the main factors causing water pollution in regions with historic or current mining activities. Its generation, release, mobility, and attenuation involves complex processes governed by a combination of physical, chemical, and biological factors. Clearly this phenomenon is highly dynamic depending on other external factors such as precipitations and ground water table fluctuations and conventional monitoring is time and resource-demanding. Recent research studies proved that imaging spectroscopy represents an alternative to conventional methods and an efficient way to characterize mines and assess the potential for AMD discharge while focusing on mapping those minerals serving as indicators of sub-aerial oxidation of pyrite (‘hot spots’) and the subsequent formation of AMD. In this study a potential of new PRISMA hyperspectral satellite sensor for multi-temporal AMD mappng was evaluated. The PRISMA AMD mineral mapping results were compared with existing ground truth data and other validated AMD maps derived using aerial high-resolution hyperspectral imaging data (e.g., CASI/SASI). To conclude, a spectral and spatial resolution of the PRISMA satellite data is sufficient to map this phenomenon at multi-temporal scale and PRISMA data has a potential to be operationally used in remediation projects and other environmental applications.

How to cite: Kopackova-Strnadova, V.: Mapping mining environmental impacts using PRISMA hyperspectral imagery: Acid mine drainage (AMD) example, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12364, https://doi.org/10.5194/egusphere-egu23-12364, 2023.

EGU23-12461 | Posters on site | GI6.3

Machine learning based two-step urban tree carbon storage estimation fusing airborne LiDAR, and Sentinel-2 

Yeonsu Lee, Bokyung Son, and Jungho Im

Urban trees are important carbon sink in human settlements by absorbing carbon dioxide and storing them as biomass. As urban areas continue to expand, quantification of carbon storage (CS) in human settlements is becoming important. Usually, urban tree CS is extrapolated using total tree area statistics and carbon stocks per unit area. However, since urban trees show large variability due to diverse growing conditions, additional information such as vegetation vitality or three-dimensional structures should be considered in CS estimation. This study suggests a new two-step approach to estimate urban tree CS using forest tree carbon stocks and then correcting it to human settlements via machine learning (ML) regression models and remote sensing data. First, urban tree CS was estimated using a high-resolution urban tree canopy cover map which classified by deep-learning approach and forest tree carbon stocks which were calculated using merchantable growing stocks and biomass expansion factor (Step 1 CS). Second, urban tree CS was estimated via ML models using Step 1 CS, Sentinel-2 images, and airborne light detection and ranging (LiDAR) measurement as independent variables. As dependent variable, the field-measured CS values calculated using allometric equations and field-measured diameter at breast height using terrestrial LiDAR were utilized. Step 2 CS using random forest showed the best performance with a correlation coefficient of 0.90 and a root-mean-squared-error of 0.48. Tree height and normalized difference vegetation index appeared as important variables in estimating urban tree CS. Suggested model can estimate urban tree CS more sophisticatedly and spatially explicitly. The output, high-resolution urban tree CS map, can be used in urban planning to achieve carbon neutrality and pleasant urban environment.

 

How to cite: Lee, Y., Son, B., and Im, J.: Machine learning based two-step urban tree carbon storage estimation fusing airborne LiDAR, and Sentinel-2, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12461, https://doi.org/10.5194/egusphere-egu23-12461, 2023.

Dryland forests are highly climate-sensitive are facing more frequent droughts and, consequently, increasing tree mortality, extreme wildfire events, and outbreaks of forest insects and pathogens. These changes, associated with climate change, are leading to biodiversity loss and the deterioration of related ecosystem services. Understanding the relationships between forest structure and function is essential for managing dryland forests to adapt to these changes. We studied the structure-function relationships in four dryland conifer forests distributed along a semiarid to sub-humid climatic aridity gradient. Forest structure was represented by leaf area index (LAI) and function by gross primary productivity (GPP), evapotranspiration (ET), and the derived efficiencies of water use (WUE= GPP/ET) and leaf area (LAE = GPP/LAI). The water and carbon fluxes at the ecosystem level were estimated by an empirical approach in which regression models were developed to relate multiple spectral data (VIs) derived from VENμS and Sentinel-2A satellites, combined with meteorological data, to local eddy covariance measurements from flux tower records available at three of the four study sites. The red-edge-based MERIS Terrestrial Chlorophyll Index (MTCI) from VENμS and Sentinel-2A showed strong correlations to flux tower GPP and ET measurements (R2cal >0.91, R2val >0.84). Using our approach, we showed that as LAI decreased with decreasing AI (dryer conditions), estimated GPP and ET decreased (R2>0.8 to LAI), while WUE (R2=0.68 to LAI) and LAE increased with decreasing AI. We propose that the higher WUE and LAE reflect an increased proportion of sun vs. shade leaves as LAI decreases. The results demonstrate the importance of high-resolution spectral and spatial data in low-density dry forests and the intricate structure-function interactions in the forests’ response to drying conditions.

How to cite: Dubinin, M. (., Osem, Y., Yakir, D., and Paz-Kagan, T.: Investigating the relationships between the leaf area index and forest functions of dryland conifer forests along an aridity gradient using VENµS and Sentinel-2 satellites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12505, https://doi.org/10.5194/egusphere-egu23-12505, 2023.

EGU23-12720 | ECS | Orals | GI6.3

Volcanic cloud detection and retrieval by micro-millimetre-waves and thermal-infrared satellite observations 

Francesco Romeo, Luigi Mereu, Stefano Corradini, Luca Merucci, and Simona Scollo

The characterization of the eruption source parameters (EPS) of explosive eruptions is of vital importance to prevent damages, mitigate environmental impact and reduce aviation risks.  We consider highly explosive eruptions with a Volcanic Explosive Index (VEI) greater than 3. During these eruptions, a great number of volcanic particles are ejected into the atmosphere where they can remain suspended for several weeks. Satellite passive sensors can be adopted to monitor volcanoes due to their high spatial and temporal resolution. 

In this work we combine the Microwave (MW) and Millimetre-wave (MMW) observations with Thermal-InfraRed (TIR) radiometric data from Low Earth Orbit (LEO) satellites to have a complete characterization of the volcanic clouds. MW-MMW passive sensors are adopted to detect larger volcanic particles (i.e. size bigger than 20 µm) by working at lower frequencies. TIR observations are employed to study smaller particles due to the sensor settings which work at smaller wavelengths. We describe new physical-statistical methods together with machine learning techniques aiming at detecting and retrieving volcanic clouds masses of 2015 Calbuco, 2014 Kelud as well as other eruptions having high explosive activities worldwide. Concerning the detection, we compare the well-known split-window methods with a machine learning algorithm named Random Forest (RF). This work highlights how the machine learning model is suitable to automatically identify tephra contaminated pixels by combining different spectral information (i.e. MW-MMW and TIR) coming from different satellite platforms. Indeed, we used data coming from: Advanced Technology Microwave Sounder (ATMS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors on board the Suomi-NPP LEO satellite; Microwave Humidity Sounder (MHS) and Advanced Very High Resolution Radiometer (AVHRR) sensors on board the Metop series.  In terms of retrieval, the new developed Radiative Transfer Model Algorithm (RTMA) is designed to estimate the total columnar content (TCC) and in turn the mass, for both MW-MMW and TIR observations. The synthetic BTs (simulated by RTMA) are linked with the observed BTs to retrieve the volcanic clouds features. In this respect, two minimization techniques, the Maximum Likelihood Estimation (MLE) and the Neural Network (NN) architecture, are also compared and discussed. Results show a good comparison of the mass obtained using the MLE and NN methods for all the analysed bands but also with previous studies on the deposit as well as other validated satellite retrieval methods. 

In conclusion, this work shows how the machine learning model can be an effective tool for volcanic cloud detection and how the synergic use of the TIR and MW-MMW observations can give more accurate estimates of the near source volcanic cloud.

How to cite: Romeo, F., Mereu, L., Corradini, S., Merucci, L., and Scollo, S.: Volcanic cloud detection and retrieval by micro-millimetre-waves and thermal-infrared satellite observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12720, https://doi.org/10.5194/egusphere-egu23-12720, 2023.

EGU23-13477 | ECS | Posters on site | GI6.3

Assessing the atmospheric correction algorithms for improving the retrieval data accuracy in the remote sensing technique 

Mir Talas Mahammad Diganta, Md Galal Uddin, and Agnieszka I. Olbert

For the purposes of cost-effective and rapid surface water quality monitoring, the utilization of the cutting-edge satellite remote sensing (RS) technique has increased over the years. Recently, several studies have revealed that the RS technique severely suffers from particles present in the atmosphere, especially from aerosol particles. This interference significantly influences the quality of the information extracted from remote sensing measurements and produces much more uncertainty in retrieving optically active water quality indicators (e.g., chlorophyll-a, coloured dissolved organic matter, total suspended matter) from optically complex water bodies. Therefore, it is required to minimize the uncertainty within the remotely sensed data by reducing the impact of atmospheric interference through the atmospheric correction (AC) process. Currently, a series of algorithms have been utilized in the literature for treating the AC in the RS technique, among which ACIX-Aqua, ACOLITE, BAC, C2RCC, FLAASH, iCOR, l2gen, LaSRC, POLYMER, GRS, Sen2Cor, and 6SV are widely used. Since the development of the AC algorithms, its applications have increased in handling of big data, like as remote sensing data. Recently, several studies have revealed that the existing algorithms have produced a considerable uncertainty in the retrieval data due to the architectural complexity of algorithms. Although, the application of cutting-edge machine learning and artificial intelligence techniques is increasing for atmospheric correction process. Therefore, the aim of the research is to develop an efficient algorithm utilizing the publicly available AC algorithms and incorporating machine learning and artificial intelligence approaches in order to reduce atmospheric interference from the RS data. The results of the research could be helpful for retrieving various optically active water quality indicators most efficiently in terms of reducing the uncertainty in monitoring water quality.

Keywords: surface water quality; remote sensing; atmospheric correction, artificial intelligence; optically active water quality indicators.

How to cite: Diganta, M. T. M., Uddin, M. G., and Olbert, A. I.: Assessing the atmospheric correction algorithms for improving the retrieval data accuracy in the remote sensing technique, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13477, https://doi.org/10.5194/egusphere-egu23-13477, 2023.

EGU23-13492 | ECS | Posters on site | GI6.3

Automated mapping of grain size distributions from UAV imagery using the CNN-based GRAInet model 

Theodora Lendzioch, Jakub Langhammer, and Veethahavya Kootanoor Sheshadrivasan

The grain size distribution of gravel riverbed material is an essential parameter to estimate the sediment transportation, groundwater-river flow interaction, river ecosystem, and fluvial geomorphology. Conventional and present methods of obtaining grain size distribution analysis of more extensive areas are time-consuming and remain challenging in effectively modeling sediment load. On this account, this paper appraised the role of employing the end-to-end data-driven GRAINet approach, a convolutional neural network (CNN) application, to predict and map the grain size distribution at particular locations over an entire gravel bar based on georeferenced drone-based orthoimagery. We conducted multiple drone surveys after post-flood events in the Javoří Brook Šumava National Park (Šumava NP) in Czechia over a small unregulated montane stream with an exposed gravel bar and frequently changed fluvial dynamics. The GRAINet model performances between the predicted mean diameter (dm) and ground truth diameter dm (human performance) produce the result of different loss functions, i.e., the mean absolute errors (MAEs), the mean squared errors (MSEs), and the root-mean-square errors (RMSEs). Corresponding averages of MAEs varied between 3 cm to  4.8 cm with standard deviations (STDs) of 1.7 cm and 3.8 cm, respectively. The averages of MSE ranged between 13 cm to 14.5 cm with  STDs of 12.7 cm and 12.8 cm, and RMSE of 3.2 cm to  5.6 cm with STDs of 1.6 cm and 4.6 cm, respectively. With high to moderate accuracies and lower computational costs than other deep learning approaches, the tested ensemble model shows that the integration of UAV remote sensing and machine learning (ML) provides a promising tool to help make decisions using timely mapped high-resolution grain size maps without access to direct object counts or locations.   

How to cite: Lendzioch, T., Langhammer, J., and Kootanoor Sheshadrivasan, V.: Automated mapping of grain size distributions from UAV imagery using the CNN-based GRAInet model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13492, https://doi.org/10.5194/egusphere-egu23-13492, 2023.

EGU23-14315 | ECS | Orals | GI6.3 | Highlight

European Ground Motion Service: production status and validation 

Lorenzo Solari, Joanna Balasis-Levinsen, and Henrik Steen Andersen

The European Ground Motion Service (EGMS) allows a wide spectrum of users to access ground motion data over 30 European countries for free, under the Copernicus data policy. The EGMS aims to serve for various applications, of which geohazards are probably the primary target. Also, the Service establishes a baseline for studies dedicated to localised deformation affecting buildings and infrastructure in general.

The EGMS is the result of a massive computational effort to process thousands of Sentinel-1 images and derive three levels of products: (a) basic, i.e. line of sight (LOS) velocity maps in ascending and descending orbits referred to a local reference point; (b) calibrated, i.e. LOS velocity maps calibrated with a geodetic reference network and (c) ortho, i.e. components of motion (horizontal and vertical) anchored to the reference geodetic network. The EGMS is implemented under the responsibility of the European Environment Agency in the frame of the Copernicus Programme.

The EGMS baseline (2016-2020) and the first annual update (2016-2021) were made available to users in the summer of 2022 and in the first quarter of 2023, respectively. The EGMS products are displayed in the EGMS Explorer (https://egms.land.copernicus.eu/), where users can investigate the data in a 3D web interface, explore the temporal behaviour of ground motion through time series and download one or multiple data tiles. External web map services can be imported in the EGMS Explorer to ease the interpretation of the interferometric measurements.

The strategy to update satellite interferometric time series is a hot topic for wide area processing services. So that, one of the goals of this presentation is to show the EGMS update strategy, which should guarantee the best trade-off between the identification of new coherent targets and motion areas and the continuity of the Service in terms of technical implementation and noise level.

The expected wide usage of the EGMS products required to setup a validation system that has two goals: verify the usability of the data for the expected range of applications and assess the quality of the products with respect to service requirements. Validation is based on seven activities performed in sixteen different countries and in several validation sites, which are representative for thematic applications (e.g. mining-induced ground motion) in different environments of Europe. To guarantee reproducibility of results, the validation data (e.g. levelling or corner reflectors time series, landslide databases) will be made available to users according to licensing conditions. The results of the validation exercise will be available to users in Q3 2023.

How to cite: Solari, L., Balasis-Levinsen, J., and Andersen, H. S.: European Ground Motion Service: production status and validation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14315, https://doi.org/10.5194/egusphere-egu23-14315, 2023.

EGU23-14746 | ECS | Orals | GI6.3

i-φ-MaLe: a novel AI-phasor based method for a fast and accurate retrieval of multiple Solar-Induced Fluorescence metrics and biophysical parameters 

Riccardo Scodellaro, Ilaria Cesana, Laura D'Alfonso, Margaux Bouzin, Maddalena Collini, Giuseppe Chirico, Roberto Colombo, Franco Miglietta, Marco Celesti, Dirk Schuettemeyer, Sergio Cogliati, and Laura Sironi

The accurate retrieval of Solar-Induced chlorophyll Fluorescence (SIF) is a pivotal target for Earth Observation since SIF can be easily monitored through optical remote sensing and provides unique information concerning the vegetation health status. Here, we propose i-φ-MaLe (metti il nome per esteso), a novel algorithm, which couples the Fourier analysis with a supervised machine learning-based procedure trained with the atmosphere-canopy radiative transfer (RT) SCOPE model.  i-φ-MaLe is the first method able to simultaneously retrieve, from the vegetation reflectance spectra, the Top Of Canopy SIF spectrum, the SIF spectrum corrected for leaf/canopy reabsorption (i.e. at photosystem level), the quantum efficiency (Fqe) and three canopy-related biophysical parameters (Leaf Area Index - LAI, Chlorophyll content - Cab and APAR) in few milliseconds. Validation procedures, based on the analysis of RT simulations, demonstrated that i-φ-MaLe, in experimental conditions (signal to noise ratio – SNR >= 500), estimates each biophysical parameter and SIF spectrum with a relative root mean square error (RRMSE) lower than 5%. In order to investigate the seasonal and daily dynamics of SIF, LAI, Cab, Fqe and APAR, the method has been also applied to field experimental data collected in the context of the AtmoFLEX and FLEXSense ESA campaigns, both at top-of-canopy (TOC) and tower (~100 meters) levels. Concerning the TOC scenario, the retrieved annual dynamic for SIF spectra has been compared with the results obtained by inversion-based methods, showing a good consistency amongthe different approaches (RRMSE ~ 10%). Moreover, SIF daily and annual dynamics, retrieved by excluding the oxygen spectral bands affected by the atmospheric reabsorption,  have been investigated for  high tower measurements. . In this context, i-φ-MaLe provided  promising results that can integrate and possibly overcome complex and computationally expensive atmospheric compensation techniques actually needed to retrieve fluorescence from oxygen absorptions bands. This study demonstrates a promising potential to exploit ground and tower spectral measurements with advanced processing algorithms, for improving our understanding on the link between canopy structure and physiological functioning of plants. Moreover, i-φ-MaLe can be straightforwardly employed to process reflectance spectra and open new perspectives in fluorescence retrieval at different scales.

How to cite: Scodellaro, R., Cesana, I., D'Alfonso, L., Bouzin, M., Collini, M., Chirico, G., Colombo, R., Miglietta, F., Celesti, M., Schuettemeyer, D., Cogliati, S., and Sironi, L.: i-φ-MaLe: a novel AI-phasor based method for a fast and accurate retrieval of multiple Solar-Induced Fluorescence metrics and biophysical parameters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14746, https://doi.org/10.5194/egusphere-egu23-14746, 2023.

EGU23-14908 | Orals | GI6.3

New method for retrieval surface UV albedo from Lidar Surface Returns (LSR) of Aeolus 

Lev Labzovskii, Gerd-Jan van Zadelhoff, Gijsbert Tilstra, Jos De Kloe, and David Donovan

Here, we report results paving the way toward a new method for retrieving surface albedo at 355 nm from lidar surface returns (LSR) of Aeolus. We found that averaged monthly LSR estimates at 2.5 x 2.5 grid clearly varied depending on the land type with the signal strength descending as follows: snow, arid areas, vegetation, water surfaces. Most importantly, given the difference in the instrumental setup, Aeolus LSR exhibited unexpectedly high agreement with Lambertian Equivalent Reflectance from TROPOMI and GOME-2 with correlation coefficients (r) of ~0.87 at global scales for median estimates at the study period (r = 0.91 for TROPOMI-GOME-2) and regional estimates for 37 selected areas (r > 0.90) where the agreement is driven by land surfaces with lower agreement over water due to inherently different physics of Aeolus LSR. Aeolus LSR showed superior sensitivity to the change of land type from vegetation to arid, compared to GOME-2 or TROPOMI as indicated by the highest negative agreement between Aeolus LSR, compared to GOME-2 or TROPOMI. We anticipate that our results will lay the foundation for the multiyear surface UV albedo climatology during the entire Aeolus lifetime.

 

How to cite: Labzovskii, L., van Zadelhoff, G.-J., Tilstra, G., De Kloe, J., and Donovan, D.: New method for retrieval surface UV albedo from Lidar Surface Returns (LSR) of Aeolus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14908, https://doi.org/10.5194/egusphere-egu23-14908, 2023.

Coastal aquaculture has become one of the main sources of animal protein and plays an important role in food and nutrition supplies and security around the world. Accurately mapping aquaculture areas is the basis for its sustainable management and use, and provides important support to policy development and implementation at regional, national, and global levels. Considering the concentrated and densely distributed characteristics of aquacultures, it is difficult to distinguish the dikes between aquacultures and identify small-scale aquacultures using medium-and low-resolution SAR images. GaoFen-3 (GF-3) is the first launched full-polarimetric C-band SAR satellite of China at metre-level resolution. This study aims to use a novel combination model to extract coastal aquacultures in the Yancheng coastal wetland, China on the basis of GF-3 Fully Polarimetric SAR Imagery. Polarimetric decomposition algorithms were applied to extract polarimetric scattering features and feature optimization was applied based on the separability index. To separate adjacent and even adhering ponds into individual aquaculture objects, we proposed a novel model that integrated two UNet++ subnetworks with the marker-controlled watershed (MCW) segmentation strategy to obtain more refined coastal aquaculture results. The accuracy assessment results demonstrated a considerable performance, with F1 greater than 95%, IoU greater than 90%, and insF1 higher than 85%. The experimental results indicate that the proposed algorithm achieved fairly high accuracy in aquaculture extraction and can effectively improve the boundary quality of individual aquacultures.

How to cite: Yu, J., He, X., Motagh, M., Yang, P., and Xu, J.: Coastal Aquaculture mapping using a novel combination model of GF-3 Fully Polarimetric SAR Imagery: A case study of Yancheng coastal wetland, China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14979, https://doi.org/10.5194/egusphere-egu23-14979, 2023.

EGU23-15311 | Orals | GI6.3

Timely mapping and quantification of volcanological parameters: the 2021-2022 Etna lava flows 

Cristina Proietti, Emanuela De Beni, Massimo Cantarero, and Tullio Ricci

The 2021 eruptive activity at Mt Etna was characterized by 57 paroxysmal events at the South-East Crater, the most active among its four summit craters. These episodes of Strombolian activity and high lava fountains fed lava flows towards East, South, and South-West and caused ashfall in the surroundings of the volcano. In 2022 the SEC gave rise to only two paroxysms in February and effusive activity in May-June and since November (still ongoing). Although the impacted area does not include permanent infrastructures it is of high tourist attraction. Hence, timely mapping of each lava flow field was mandatory for hazard mitigation. The high frequency of the 2021 paroxysms, up to two events in 24 hours, forced us to implement a multidisciplinary approach based on various remote sensing techniques, with different spatial resolutions and revisiting time. In particular, several satellite images were processed, depending on data availability and weather conditions. Data acquired by Sentinel-2 MSI, Skysat, Landsat-8 OLI, and TIRS allowed us to map the lava flow fields at a spatial resolution ranging from 0.5 to 90 meters. High-spatial resolution (from 4.5 up to 55 cm) DEMs and orthomosaics were also realized elaborating the visible and thermal images acquired through Unmanned Aerial Systems (UASs) surveys. Moreover, data acquired by the thermal cameras of the Istituto Nazionale di Geofisica e Vulcanologia permanent network were re-projected into the topography for analyzing the lava flow field evolution at 5-meter spatial resolution. These multi-platform remote sensing data allowed for mapping the lava flows and compiling a geodatabase reporting the main geometrical parameters (e.g. length, area, average thickness, and volume). The resulting multi-sensor methodology enabled, for the first time on Etna, to timely and accurately characterize frequently occurring effusive events.

How to cite: Proietti, C., De Beni, E., Cantarero, M., and Ricci, T.: Timely mapping and quantification of volcanological parameters: the 2021-2022 Etna lava flows, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15311, https://doi.org/10.5194/egusphere-egu23-15311, 2023.

EGU23-15349 | Posters on site | GI6.3

Satellite Investigation to study POcket BEach Dynamics in Malta. The SIPOBED project 

Luciano Galone, Emanuele Colica, Peter Iregbeyen, Luca Piroddi, Adam Gauci, Alan Deidun, Gianluca Valentino, and Sebastiano D'Amico

Pocket Beaches are small beaches limited by natural headlands, strongly jutting into the sea, free from direct sedimentary contributions that are not eroded from back-shore cliffs. Malta’s pocket beaches are one of the most significant geomorphologic features of the archipelago. They play an important role for a variety of ecological and economic reasons. In this sense, sediment (mostly sand) dynamics is the most relevant factor to consider in the beach system. Sediment movement can be driven by a variety of factors, including wave action, currents, wind and direct and indirect anthropic action, leading to extreme morphological modifications in some cases.

The SIPOBED (Satellite Investigation to study POcket BEach Dynamics) project seeks to develop a reliable and cost-effective tool capable of monitoring sediment dynamics using satellite and other remote sensing data in several selected Maltase Pocket Beach systems, by reconstructing the volume and distribution of sediment of the beaches system through time.

The monitoring of sandy coastal zones requires the analysis of sediment dynamics in the entire beach system, from the coastal dunes to the closure depth, where the influence of sea waves on the seabed is low. SIPOBED uses Interferometric SAR and Light Detection and Ranging (LIDAR) derived Digital Elevation Models (DEMs) to study the inland system dynamics. The DEMs are used to improve the co-registration of temporal SAR imagery and detect subtle changes between acquisitions. The underwater sediment dynamics monitoring is approached by tracking bathymetric changes using multispectral satellite and unmanned aerial vehicle (UAV) images. In situ bathymetric data is essential for calibrating and validating the model. This methodology allows for more frequent and cost-effective monitoring of changes in both the dune-beach system and the ocean floor compared to classical approaches, such as in situ topographic surveys and ship-based sonar surveys. The project also aims to determine the bedrock depth and geometry at the lower limit of the pocket beach system using near-surface geophysical techniques.

The monitoring of Maltese sandy coastal beaches can provide insights into the factors influencing sediment dynamics and improve our understanding of the processes that shape and reshape pocket beaches over time. The results of the SIPOBED project will contribute to developing a risk assessment and monitoring tool that combines the sediment dynamics process with their potential local impacts, resulting in a powerful instrument for decision-makers.

The SIPOBED project is financed by the Malta Council for Science and Technology (MCST, https://mcst.gov.mt/) through the Space Research Fund (Building capacity in the downstream Earth Observation Sector), a programme supported by the European Space Agency.

How to cite: Galone, L., Colica, E., Iregbeyen, P., Piroddi, L., Gauci, A., Deidun, A., Valentino, G., and D'Amico, S.: Satellite Investigation to study POcket BEach Dynamics in Malta. The SIPOBED project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15349, https://doi.org/10.5194/egusphere-egu23-15349, 2023.

EGU23-15413 | Orals | GI6.3

SAR localization of passive RFID tags under snow and vegetation using a mobile reader antenna 

Mathieu Le Breton, Arthur Charléty, Nicolas Grunbaum, Éric Larose, and Laurent Baillet

Passive RFID tags are opening new capabilities of monitoring in geoscience [1], applied to landslide [2-3], snowpack [4] or riverine pebble monitoring. This study investigate the ability to localize passive RFID tags (working at 868 MHz) from the air in harsh conditions met in natural areas outdoors. The tags are localized with the synthetic aperture radar method (SAR)  with a mobile reader from above, installed on a rail and equiped with a differential GNSS. The tags are localized either directly on the ground, under a vegetal cover, or under a snow cover, and the localization accuracy is evaluated in each case. This technique opens the possibility to monitor ground displacement even under snow or vegetal coverage, that challenge most of existing displacement measurement techniques.

 

 

Related studies on the topic :

[1] Le Breton, M., Liébault, F., Baillet, L., Charléty, A., Larose, É., Tedjini, S., 2022. Dense and long-term monitoring of earth surface processes with passive RFID—a review. Earth-Science Reviews 234, 104 225. https://doi.org/10.1016/j.earscirev.2022.104225

[2] Charléty, A., Le Breton, M., Larose, E., Baillet, L., 2022. 2D Phase-Based RFID Localization for On-Site Landslide Monitoring. Remote Sensing 14, 3 577. https://doi.org/10.3390/rs14153577

[3] Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D., Guyoton, F., Jaboyedoff, M., 2019. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Engineering Geology 250, 1–10. https://doi.org/10.1016/j.enggeo.2018.12.027

[4] Le Breton, M., Larose, É., Baillet, L., Lejeune, Y., van Herwijnen, A., 2022. Monitoring snowpack SWE and temperature using RFID tags as wireless sensors. https://doi.org/10.5194/egusphere-2022-761

How to cite: Le Breton, M., Charléty, A., Grunbaum, N., Larose, É., and Baillet, L.: SAR localization of passive RFID tags under snow and vegetation using a mobile reader antenna, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15413, https://doi.org/10.5194/egusphere-egu23-15413, 2023.

EGU23-16434 | Orals | GI6.3 | Highlight

The Student-Led Design and Testing of an Imaging CubeSat Payload 

Matthew Watson and Thomas Hunter and the PROVE Team

Volcanic ash presents a challenge for the aviation industry. 3D information is needed to be able to back-calculate dose – this is a key parameter in managing airspace. To recreate the ash cloud, multiangle observations are required – deal to perform visual and infrared observations. Other mission objectives using the can also be realised, for example, as volcanic ash clouds are the primary target, there is the possibility to map new magma extrusions, lava and pyroclastic flow movements. Thermal infrared data has also previously been used to observe volcanic cycles and better understand their behaviour. The visual images required for 3D construction of ash clouds can be used to create digital elevation models of terrain around volcanos which have application in disaster management and planning, and forest fires may also be included as targets of opportunity.

A CubeSat mission - Pointable Radiometer for Observing Volcanic Emissions (PROVE) Pathfinder - is proposed to monitor the ash cloud using both thermal infrared and visual cameras. The resulting 2U payload consists of a thermal infrared camera (FLIR Tau 2 with a 50mm lens) and a visual camera (a narrow field of view Basler ace ac5472-5gc with a Kowa LM75HC lens). Alongside this, a payload computer to communicate with the cameras and store data was selected (the BeagleBone Black Enhanced Industrial) with a custom PCB providing connections to the instruments and bus. The software to operate the payload takes the form of a custom scheduler for an imaging pass, sending commands to the camera systems (and to the bus) to take the required multiangle images for ash cloud reconstruction.

The engineering model of the payload is currently being tested at the European Space Agency’s CubeSat Support Facility with the support of the Education Office of the European Space Agency under the educational Fly Your Satellite! Test Opportunities programme. The team are undertaking a month of environmental testing including vibration and thermal vacuum tests. The aim of the testing campaign is to qualify the payload for launch.

How to cite: Watson, M. and Hunter, T. and the PROVE Team: The Student-Led Design and Testing of an Imaging CubeSat Payload, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16434, https://doi.org/10.5194/egusphere-egu23-16434, 2023.

EGU23-17455 | Orals | GI6.3

Are Southeast Asian lakes impacted by changes in climate and land-use? A historical and future scenario analysis. 

Salvatore G.P. Virdis, Siwat Kongwarakom, Sangam Shrestha, Liew Ju Neng, Bachisio M. Padedda, Tatsaneewan Phoesri, and Aung Chit Moe

Southeast Asian lakes provide several ecosystem services and are an important natural resource for water supplies, industry, agriculture, shipping, fishing, and recreation. It has been demonstrated that they are highly vulnerable to anthropogenic and climate threats. Recent scientific findings clearly demonstrated that climate change has already significantly affected the SEA region and that these impacts will continue and expand as the pace of climate change accelerates. However, a deep understanding of "if" and "how" climate change as well as intensification of land uses may exacerbate those impacts on such vulnerable ecosystems across the whole region is lacking.

To contribute towards filling some of the existing knowledge gaps, in a renowned data scarce region, we present the results of a 3-year-long interdisciplinary research project entitled Climate Change Risk Assessment for Southeast Asian Lakes (CCRASEAL), led by the Asian Institute of Technology and funded by the Asia Pacific Network for Global Research (APN).

We present new insights on: i) historical, remote sensing derived, yearly land use changes from 1992 to 2021 estimated at basin scale across whole mainland SEA; ii) historical and future changes in climate respectively for the periods 1970-2006 and 2007-2100 using different downscaled CORDEX-SEA climate data at lake level; iii) detected and assessed climate and land use long-term trends and their coupled impacts on both monthly runoff at multi-basin scale level and lake surface areas of more than 700 water bodies. Finally, we detected and assessed the satellite-derived Lake Surface Water Temperature (LSWT) trends, an essential climate variable (ECV), within defined historical and future scenarios and across whole mainland SEA.

To achieve our results, we used and integrated multi-source and multi-resolution datasets made of satellite derived water and land products along with available climatic CORDEX-SEA climate datasets. Furthermore, we used a combination of conventional remote sensing, GIS, machine- and deep learning based processing approaches. In our studies we analysis possible spatial and temporal linkages between observed alterations to multiple-threats, to understand “if”, “when”, “how” and “where” climate and land use changes had affected and will affect SEA lakes.

Results have been validated using, when available, ground-based observation collected at national and regional scales.

How to cite: Virdis, S. G. P., Kongwarakom, S., Shrestha, S., Neng, L. J., Padedda, B. M., Phoesri, T., and Moe, A. C.: Are Southeast Asian lakes impacted by changes in climate and land-use? A historical and future scenario analysis., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17455, https://doi.org/10.5194/egusphere-egu23-17455, 2023.

EGU23-17477 | Orals | GI6.3

Thermal features and heat budget of Campi Flegrei unrest caldera from fast, high-resolution airborne mapping 

Carmine Gambardella, Roberto Moretti, Giuseppe Ciaburro, Dario Martimucci, Francesco Marconi, and Rosaria Parente

Campi Flegrei caldera (CFc; Southern Italy) is the archetype for volcanic risk occurring within a highly anthropized area. CFc was mostly shaped by the collapse following the Neapolitan Yellow Tuff eruption (NYT) ~15 ky BP, which generated about 50 km3 of volcanic products mainly deposited via huge pyroclastic flows. More than 50 eruptions from several volcanic centers were generated within the caldera after the NYT, with last eruption occurring in 1538 (Monte Nuovo eruption). Since the 1950s, CFc experiences a long-term unrest in the Pozzuoli area. After the 1969-72 and 1982-84 episode, uplift started again in 2004, raising serious concern to population and authorities also because of the recurrent seismic activity and the persistence of fumarolic emissions fed by the underlying hydrothermal system.

In this context, thermal monitoring of the caldera is a strategic issue for volcanic forecasting, considering that several areas are prone to the opening of volcanic vents. The large size of the onshore portion of the CFc (90 km2), the difficulties to access several anomalous sites and the huge degree of anthropization make the direct assessment of ground-thermal anomalies and the realization of periodic measurement campaigns very difficult, time-consuming and unsafe.

Here we report on a detailed airborne thermal mapping from a flight made on 15 April 2022 at ~6.30 am (local time). Thermal acquisition was performed with a wide-array broadband thermal sensor in conjunction with optical imagery in Red-Green-Blue bands via a 150 MP camera. The sensor platform and the aircraft ¾  including logistic facilities, agreements with military airports and authorizations to fly ¾  are a strategic asset of the BENECON. The high resolution of thermal mapping (instrumental accuracy: 0.05 °C on temperature; pixel size: 0.45m x 0.45m) in conjunction with real-time acquisition of optical images allows a straightforward discrimination of natural ground anomalies from thermal emissions and spots due to anthropic activities. Ground thermal anomalies related to volcanic-hydrothermal activity and associated with the caldera unrest are concentrated in the well-known Solfatara and Pisciarelli sites, whereas minor features are detected on the relief bordering the western side of Agnano plain, inside the Astroni crater and on the southern flank of Monte Nuovo, in line with results from existing ground surveys. At Solfatara and Pisciarelli, the shape of measured thermal anomalies matches that of CO2 fluxes interpolated from literature data. The consistency between heat fluxes computed from airborne-detected ground temperatures and soil CO2 fluxes (e.g., in the order of 100 MW for the Solfatara crater) confirms that steam condensation from hydrothermal activity is presently the dominant engine responsible for endogenous heat release at CFc.

The fast execution of the airborne survey, the rapid data processing and post-processing and the capability of detecting the most subtle anomaly prompt for periodic surveys of the CFc thermal flux aimed at 1) the tracking of existing anomalies 2) the rapid detection of new thermal features and 3) the building of time-series. Integration with optical and, in perspective, hyperspectral VNIR images foster an unprecedented capability to monitor the ongoing volcanic unrest.

How to cite: Gambardella, C., Moretti, R., Ciaburro, G., Martimucci, D., Marconi, F., and Parente, R.: Thermal features and heat budget of Campi Flegrei unrest caldera from fast, high-resolution airborne mapping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17477, https://doi.org/10.5194/egusphere-egu23-17477, 2023.

EGU23-393 | ECS | Orals | GI6.5

Using environmental radioactivity to create a national scale peatlands map: a case study from Ireland 

David O Leary, John Connolly, Louis Gilet, Jim Hodgson, Colin Brown, and Eve Daly

Historically, peatlands have acted as globally important carbon sequestration habitats via the storage of organic material. Modern degraded/drained peatlands emit this carbon as CO2 via decomposition of the stored organic material. Through restoration projects, in which the water table is raised, peatlands may become carbon neutral or possibly carbon negative. National restoration plans require a knowledge of peatland extent and spatial distribution across large geographic areas.

Globally, current peatland maps are created in a variety of ways including the use of optical satellite remote sensing or combinations of legacy soil/quaternary maps. However, optical remote sensing cannot detect peatlands under landcover such as forest or grassland. Legacy maps are often created from sparse in-situ augur, borehole, or trial pit data. These types of measurements do not allow for accurate measurement of peatland boundaries.

Radiometrics, a geophysical method that measures radiation emitted from geological materials, is particularly suited to peatland studies. Modelling of radiometric attenuation shows that a statistical difference is present in recorded potassium, equivalent uranium and equivalent thorium counts acquired over peat, compared to those acquired over a non-peat/mineral soil. Mineral soils contain geological material which acts as a source of gamma radiation. Peat, being a mostly organic material, is generally not considered a source of radiation. Peat also tends to be saturated and water acts to attenuate the recorded gamma signature. These effects combined means that peatlands are represented as a “low” radiometric signal in the landscape.

In Ireland, the Tellus survey, acquired by the Geological Survey, Ireland (GSI) aims to acquire airborne data including electromagnetic, magnetic, and radiometric data, consistently across the country (flight line spacing of 200m). This study uses Tellus airborne radiometric data in combination with machine learning classification techniques, to identify peatlands under modified landcover, such as forestry and grasslands and to increase the spatial resolution of existing peatland map to 50 x 50 m. The methodology is robust and can be applied in all areas where these data exist. The results may update national and international carbon inventories of peatlands area and geographic distribution and inform European policy.

How to cite: O Leary, D., Connolly, J., Gilet, L., Hodgson, J., Brown, C., and Daly, E.: Using environmental radioactivity to create a national scale peatlands map: a case study from Ireland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-393, https://doi.org/10.5194/egusphere-egu23-393, 2023.

EGU23-537 | ECS | Posters virtual | GI6.5

Impact of radon exposures on non cancer outcomes and future perspectives  

Carolina L Zilli Vieira and Petros Koutrakis

Radon is a naturally occurring radioactive gas formed from the decay of primordial radionuclides (Uranium and Thorium) in the Earth's crust. It infiltrates into homes from soil, water, and construction materials. Indoor radon is one of the leading cause of lung cancer. Our recent studies have showed short- and middle-term exposures to indoor radon are also related to increased risk of cardiovascular, pregnancy and respiratory morbidity and mortality. These findings bring a new direction for radon exposures and health outcomes studies.  In this overview, we will present our most recent studies on radon exposures and non-cancer outcomes, describing from biological mechanisms to future directions for public health policies.

How to cite: Zilli Vieira, C. L. and Koutrakis, P.: Impact of radon exposures on non cancer outcomes and future perspectives , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-537, https://doi.org/10.5194/egusphere-egu23-537, 2023.

EGU23-549 | ECS | Posters on site | GI6.5 | Highlight

Mapping of radioactivity levels in and around the gold mine tailing dams of Gauteng Province, South Africa 

Paballo Moshupya, Seeke Mohuba, Tamiru Abiye, and Ian Korir

Naturally occurring radionuclides arises mainly from natural sources and anthropogenic activities such as mining. In South Africa, gold mining in the goldfields of the Witwatersrand Basin has resulted in numerous tailing dams that have high concentrations of NORM bearing residue. The aim of this study was to evaluate the surface radioactivity levels in and around the gold tailing dams of Gauteng Province in South Africa and further determine the consequential radiological exposure to the public. The portable BGO SUPER-SPEC (RS-230) spectrometer, with a 6.3 cubic inches Bismuth Germanate Oxide (BGO) detector was used to measure the activity concentrations for 238U, 232Th and 40K in mine tailings, soils and underlying rocks. This work was conducted on a regional scale and covered the West Rand, East Rand and Central Rand Districts of the Gauteng Province, which are dominated by the abandoned gold tailings dams. Of the three radionuclides that were studied, 238U was found to be the most significant radioactive contaminant of radiological concern. High 238U concentrations (209.95 to 2578.68 Bq/kg) were found in the mine tailings than in the surrounding soils (9.88 to 941.07 Bq/kg) and rocks (11.12 to 71.63 Bq/kg). In surface soil, the radionuclides show significant spatial variability with high activities recorded in soils located in close proximity to tailings thus signifying the adverse environmental impacts of mining in the study area. The annual effective dose estimations indicate that the mine tailings found in the area and soils impacted by tailings significantly contribute to the external gamma radiation received by members of the public. This therefore highlight the need for further monitoring and regulatory control measures targeting these affected areas, in order to ensure the protection of persons and the environment within the areas.

Keywords: activity concentration; gold mine tailings; in situ gamma ray spectrometry; radiological

exposures; South Africa

 

How to cite: Moshupya, P., Mohuba, S., Abiye, T., and Korir, I.: Mapping of radioactivity levels in and around the gold mine tailing dams of Gauteng Province, South Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-549, https://doi.org/10.5194/egusphere-egu23-549, 2023.

EGU23-2800 | ECS | Posters on site | GI6.5

BlueSky: a system for in-situ identification of 137Cs in industrial waste 

Virginia Strati, Matteo Albéri, Enrico Chiarelli, Tommaso Colonna, Enrico Guastaldi, Andrea Iannarone, Nicola Lopane, Alice Magnoni, Andrea Maino, Fabio Mantovani, Dario Petrone, Kassandra Giulia Cristina Raptis, Filippo Semenza, Mattia Taroni, and Giacomo Zambelli

In industrial waste management the on-site and real-time automatic radiological characterization represents a significant improvement in disposal procedures, minimizing processing times and operators exposure. In a steel mill the accidental fusion of radioactive sources in contaminated metals is an event with a non-negligible extent. In these radiological emergency situations, significant issues arise for the environment protection with negative consequences on the mill’s production. The contamination of the separate structures (e.g., furnaces, filtering systems) force a stop on the production and a complex management of the storage and disposal of the contaminated materials. In these situations, a representative sampling is an extremely time-consuming and expensive operation which increases the risks of further radiological contamination both to the environment and the involved personnel.

BlueSky is an innovative measurement system developed and validated in a steel mill for the in-situ characterization of filtering and dust suppression systems contaminated with Cs-137 which were stocked in about 400 containers with an approximate mass of 100 kg each. BlueSky was conceived with the goal of identifying, in-situ and with a 95% confidence level, the containers with an activity concentration lower than 100 Bq/kg, the clearance level which determines their disposal without radiological relevance. A single 20-minute measurement, realized positioning the detector on the top of each container, permits to achieve this objective with a Minimum Detection Activity of 22 Bq/kg.

The BlueSky system includes a 2 x 2 inches cerium bromide (CeBr3) detector partially collimated with a lead shielding to decrease by 60% the signal contribution from the surrounding environment. The in-situ measurement process has been streamlined by the development of an Android App that, thanks to the Bluetooth module coupled to the detector, manages the data taking process, analyzes the acquired spectrum, displays the results and sends them to the Cloud Storage Platform.

How to cite: Strati, V., Albéri, M., Chiarelli, E., Colonna, T., Guastaldi, E., Iannarone, A., Lopane, N., Magnoni, A., Maino, A., Mantovani, F., Petrone, D., Raptis, K. G. C., Semenza, F., Taroni, M., and Zambelli, G.: BlueSky: a system for in-situ identification of 137Cs in industrial waste, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2800, https://doi.org/10.5194/egusphere-egu23-2800, 2023.

EGU23-3353 | Posters virtual | GI6.5

Temporal variability of gamma radiation and aerosol concentration over the North Atlantic ocean 

Nuno Dias, Guilherme Amaral, Carlos Almeida, António Ferreira, António Camilo, Eduardo Silva, and Susana Barbosa

Gamma radiation measured over the ocean is mainly due to airborne radionuclides, as gamma emission by radon degassing from the ocean is negligible. Airborne gamma-emitting elements include radon progeny (Pb-2114, Bi-214, Pb-210) and cosmogenic radionuclides such as Be-7. Radon progeny attaches readily to aerosols, thus the fate of gamma-emitting radon progeny, after its formation by radioactive decay from radon, is expected to be closely linked to that of aerosols.

Gamma radiation measurements over the Atlantic Ocean were made on board the ship-rigged sailing ship NRP Sagres in the framework of project SAIL (Space-Atmosphere-Ocean Interactions in the marine boundary Layer). The measurements were performed continuously with a NaI(Tl) scintillator counting all gamma rays from 475 keV to 3 MeV.  

The counts from the sensor were recorded every 1 second into a computer system which had his time reference corrected by a GNSS pulse per second (PPS) signal. The GNSS was also used to precisely position the ship. The measurements were performed over the Atlantic ocean from January to May 2020, along the ship’s round trip from Lisboa - Cape Verde – Rio de Janeiro – Buenos Aires – Cape Town – Cape Verde - Lisboa.

The results show that the gamma radiation time series displays considerable higher counts and larger variability in January compared to the remaining period. Reanalysis data also indicate higher aerosol concentration. This work investigates in detail the association between the temporal evolution of the gamma radiation measurements obtained from the SAIL campaign over the Atlantic Ocean and co-located total aerosol concentration at 550 nm obtained every 3 hours from EAC4(ECMWF Atmospheric Composition Reanalysis 4) data.

How to cite: Dias, N., Amaral, G., Almeida, C., Ferreira, A., Camilo, A., Silva, E., and Barbosa, S.: Temporal variability of gamma radiation and aerosol concentration over the North Atlantic ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3353, https://doi.org/10.5194/egusphere-egu23-3353, 2023.

The characterization of NORM/TENORM materials must be performed using different nuclear techniques, able to show the complete scheme of the equilibrium of the radionuclides in the different natural chains. The characterization must be done in order to be able to determine the levels of radionuclides present in them, in order to verify the clearance levels for the correct management of the material, of the area management in which they are located and determine any breakage of the natural chains to identify NORM/TENORM pollution phenomena in the environment where these materials are stored. All this is particularly important in order to organize the remediation of polluted sites.

In the site of national interest of Tito Scalo (South Italy), "ex Liquichimica" Area, following specific samplings, characterizations were carried out for the determination of Uranium, 226Ra, 210Pb and 210Po as well as the gamma emitters with various analytical techniques and through specific radiochemical procedures.

The above determinations were performed on various matrices, including surface and groundwater, soils, silt-sediments and plants, for a total of 257 soil samples, 47 groundwater samples, 8 surface water samples, 8 silt-sediment and 10 plant samples.

The analyzes were conducted using radiochemical procedures, such as the IAEA/AQ/34:2014 procedure, accredited according to the UNI EN ISO 17025 standard, specific for the determination of U, Ra, Pb and Po in phosphogypsum.

The analytical techniques used are complex and involve multiple steps for the treatment of the sample and the sequential separation of the radionuclides for their determination: in particular, the above procedure involves the use of liquid scintillation, alpha and gamma spectrometry after radiochemical treatment of the starting matrix. Processes of this type require, in addition to specific skills, a qualitative process that guarantees the goodness of the entire process.

This work shows in detail the IAEA/AQ/34 procedure for the radiological characterization of the phosphogypsum basin of the "ex Liquichimica" area of Tito Scalo, as well as analytical data for each group of analyzed matrices.

 

How to cite: Taroni, M., Iannarone, A., and Zambelli, G.: NORM-TENORM: Characterization of Uranium, Radium, Lead and Polonium levels in the area of the phosphogypsum basin in South Italy. Radiochemical measurement techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3918, https://doi.org/10.5194/egusphere-egu23-3918, 2023.

EGU23-4703 | Posters on site | GI6.5

A refined chronology and spatial distribution of artificial radionuclide fallout (239,240Pu, 137Cs) in South America 

Pierre-Alexis Chaboche, Olivier Evrard, Anthony Foucher, Pierre Sabatier, and Marcos Tassano

Sedimentary sequences have received a growing interest as a support for conducting climatic and environmental reconstructions covering the 20th century period, which has been highly impacted by socio-environmental changes. South-America is one of the regions of the world the most impacted by these changes (e.g. agricultural expansion, extreme climatic events) which induce many deleterious consequences (e.g. increase of soil erosion, transfer of contaminants). However, quantitative information regarding soil erosion and sediment accumulation processes at the catchment scale is currently lacking to determine the magnitude of these phenomena and promote effective policies to mitigate their environmental and economic impacts.

Fallout of anthropogenic radionuclides (137Cs, 239Pu and 240Pu) emitted by atmospheric nuclear weapon tests conducted between 1945 and 1980 provides an opportunity to overcome this lack of information. Indeed, artificial radionuclides bound to fine-grained sediment have been increasingly recognized as powerful tools to conduct environmental, climatic and soil redistribution rate reconstructions during the Anthropocene. Although spatial and temporal reconstructions of this fallout have been conducted worldwide, this information remains scarce in South America. In addition, scientific controversies emerged regarding the contribution of French atmospheric nuclear tests to the deposition of artificial radionuclides in this region of the world, requiring further investigation.

Based on a compilation of 137Cs inventories in undisturbed soil profiles (n=96) and a digital soil mapping approach, an open-access baseline map of 137Cs fallout at the subcontinental scale of South America was created. The results showed that the 137Cs inventory technique should be appropriate to reconstruct soil erosion in intensive agricultural landscapes of Chile, Argentina, Uruguay and southern Brazil and theoretically applicable in Paraguay, Bolivia and Peru. Compared to previous estimations, higher levels of 137Cs fallout were observed between 20 and 60° South latitude. Additional measurements were therefore conducted in undisturbed soils and lake sediment cores collected at these latitudes by analyzing the 240Pu/239Pu atomic ratios, which is a powerful tool to determine the sources and their respective contributions to the deposition of anthropogenic radionuclides. Significantly lower plutonium atom ratios were found and attributed to the higher contribution (up to 60% in Uruguay) of the fallout following French atmospheric nuclear tests between 1966 and 1974.

This refined chronology and spatial distribution of bomb-derived fallout will undoubtedly be useful to avoid misinterpretations of sediment core dating and reconstruct soil redistribution rates during the Anthropocene in South America.

How to cite: Chaboche, P.-A., Evrard, O., Foucher, A., Sabatier, P., and Tassano, M.: A refined chronology and spatial distribution of artificial radionuclide fallout (239,240Pu, 137Cs) in South America, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4703, https://doi.org/10.5194/egusphere-egu23-4703, 2023.

EGU23-5501 | ECS | Posters virtual | GI6.5

Prediction of caesium dynamics in soil using Mid-Infrared Spectroscopy (MIRS) 

Ayane Kan, Maria Heiling, Arsenio Toloza, Franck Albinet, Takuro Shinano, and Gerd Dercon

The release of radiocaesium radionuclides (RCs) has affected food safety after the accidents at Chernobyl and Fukushima Daiichi nuclear power plants. 137Cs, in particular, is of major concern in terms of agriculture due to its relatively long half-life (30.2 years for 137Cs), its strong fixation by the soil, and easy absorption by plants. Therefore, several countermeasures have been undertaken. For instance, topsoil removal and potassium fertilizer successfully reduced the level of RCs contamination in agricultural products. However, the relation between the transfer factor and exchangeable potassium (Kex) differs depending on the soil, meaning that there are several parameters including Kex that influences caesium (Cs) uptake by plants. The reason remains unclear, but a previous studies suggested that exchangeable 137Cs could be a crucial factor in explaining the variation. Also, some factors such as solid/liquid distribution coefficient (Kd) of Cs, or the ratio of exchangeable 137Cs versus total 137Cs (137Csex / 137Cstotal) in the soil could be involved in the determination of the risk of 137Cs uptake by plants. Furthermore, a rapid risk assessment is needed while these parameters can take a huge amount of time to be determined. Hence, Mid-Infrared Spectroscopy (MIRS), being faster, more cost-effective, and non-destructive, may be utilized for the determination of these parameters. However, the prediction of these parameters using MIRS has yet to be assessed. In this study, we aimed to assess whether MIRS can predict Cs-related parameters in the soil such as Kd, 137Csex / 137Cstotal, Kex and other parameters that may be of influence on the behaviour of RCs in the soil, such as CEC, pH, and soil organic carbon.

In total about 1700 soil samples were collected from agricultural fields in the Fukushima Prefecture in Japan. The soil samples were air-dried and ground. The MIRS data were obtained using a Thermo Scientific Nicolet iS20 spectrometer. Using Partial Least Squares Regression as a baseline, the spectra data and the wet chemistry data including Kd, 137Csex / 137Cstotal, and Kex, among other soil parameters, were used for modelling and prediction. Even though until present (at submission of this abstract) only 176 samples have been measured, we found that balancing the range of values between training and validation sets enabled Partial Least Regression Estimation methods to provide a relatively high R2 valid score for the prediction of each wet chemistry data, especially soil organic carbon, CEC, Mgex and Caex, ranging between 0.73 and 0.88. Using less than 200 samples, however, the validation scores of Cs -related parameters were less than 0.5. Further MIRS data are expected for up to about 1600 soil samples, for 137Csex / 137Cstotal in the soil. Additional processing and modelling techniques will be tested aiming at further improving the validation scores, and results will be shown at EGU.

How to cite: Kan, A., Heiling, M., Toloza, A., Albinet, F., Shinano, T., and Dercon, G.: Prediction of caesium dynamics in soil using Mid-Infrared Spectroscopy (MIRS), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5501, https://doi.org/10.5194/egusphere-egu23-5501, 2023.

EGU23-6130 | ECS | Orals | GI6.5

Validation of a High-Fidelity Monte Carlo Model for Airborne Gamma-Ray Spectrometry with Field Measurements 

David Breitenmoser, Gernot Butterweck, Malgorzata M. Kasprzak, and Sabine Mayer

The objective of the present study is to simulate the spectral gamma-ray response of the Swiss Airborne Gamma-Ray Spectrometry system (SAGRS) using Monte Carlo radiation transport codes. The SAGRS is mounted in the cargo bay of a AS-332M1 Super Puma helicopter from the Swiss Air Force and consists of four prismatic NaI(Tl) scintillation crystals with a total volume of 16.8 l. We developed a high-fidelity Monte Carlo model of the SAGRS including the detector system and the helicopter using the multi-purpose radiation transport code FLUKA. As part of the measurement campaign ARM22c organized by the National Emergency Operations Centre (NEOC), we performed hover and line flights in combination with ground measurements using certified 133Ba and 137Cs point sources to validate our model. The performed measurements revealed a significant impact of the helicopter fuel on the detector response for various solid angles. In general, we found an excellent agreement between the measured and simulated detector response with relative errors in the full energy peak <10%. The validated model presented herein offers a novel way to simulate the spectral detector response of the SAGRS for the generation of fundamental spectra in a full spectrum analysis framework.

How to cite: Breitenmoser, D., Butterweck, G., Kasprzak, M. M., and Mayer, S.: Validation of a High-Fidelity Monte Carlo Model for Airborne Gamma-Ray Spectrometry with Field Measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6130, https://doi.org/10.5194/egusphere-egu23-6130, 2023.

EGU23-6207 | ECS | Posters virtual | GI6.5

VARIATIONS OF AIR QUALITY RADIO-INDICATORS 40K AND 137Cs IN ATMOSPHERIC AEROSOLS IN SEVERAL LOCATIONS IN SPAIN. 

María López Pérez, Elisa Gordo, Francisco Javier Hernández Suárez, Gabriel Castelló, Pedro Ángel Salazar Carballo, Cristina González, Francisco Javier Expósito, Juan Pedro Díaz, and Esperanza Liger

Understanding the mechanisms for transport and deposition of pollutants in the atmosphere is essential for the modelling of air quality. Air quality Radio-indicators (or radio-tracers) such as 40K and 137Cs may be useful to identify and differentiate natural and anthropogenic inputs of pollutants as well as forcing mechanisms (such as dust plumes, nuclear accidents, etc…).  

Spain, due to its proximity to the African continent, is especially affected by African dust plumes which have a remarkable impact on air quality. These events, in addition to large amounts of aerosols, bacteria, virus, seeds, etc.., are usually accompanied by relatively high concentration of 40K (t1/2 = 1.25·109 years) and 137Cs, a fission product with a half-live of 30.2 years. The deterioration of the air quality during such events often has large socio-economical and medical implications to the population.

In this work we analyse and discuss the variations of these two radio-indicators in aerosol samples collected at 7 different monitoring stations over a period of 10 years (2009-2018). The monitoring stations were all located in Spain and operated by the Spanish Nuclear Safety Council. These stations were: Tenerife (28º27′18′′N; 16º17′29′′W), Málaga (36º43’40’’N; 4º28’80’’W), Sevilla (37°22′51″N; 5°59′28″O), Cáceres (39°28'36"N; 6°22'06"O), Madrid (40°27′16″N; 3°43′42″W), Barcelona (41°23′12″N; 2°09′50″E) and Bilbao (43°16′07″N; 2°56′16″O).

40K and 137Cs activity concentrations in atmospheric aerosols were recorded from January 2006 to July 2018. Sampling was carried out weekly using high-flow collectors that operate at about 600 m3/h.  Polypropylene square filters were used to collect atmospheric aerosols. These filters have an efficiency of approximately 96% for the collection of radionuclides.

40K activity concentrations were detected between 39% (Tenerife) and 100% (Bilbao and Madrid) of the samples measured. However, 137Cs activity concentrations appeared in between 3% (Sevilla) and 19% (Bilbao) of the aerosol samples. The simultaneous detection of both radio-indicators in the monitoring stations located in the south of Spain were mostly linked to African dust plumes.

During the weeks after the Fukushima nuclear power plant accident in 2011, 137Cs was detected between 70% (Málaga) and 100% (Madrid, Barcelona and Bilbao) of the samples analyzed. Other fission products such as 131I and 134Cs were also recorded in the same samples during this period.

This work highlights the proper functioning of the Spanish environmental radiological monitoring network but also its usefulness for the study of atmospheric processes impacting air quality such as African dust plumes.

Acknowledgements

This study was supported by the Spanish Nuclear Safety Council (CSN).

How to cite: López Pérez, M., Gordo, E., Hernández Suárez, F. J., Castelló, G., Salazar Carballo, P. Á., González, C., Expósito, F. J., Díaz, J. P., and Liger, E.: VARIATIONS OF AIR QUALITY RADIO-INDICATORS 40K AND 137Cs IN ATMOSPHERIC AEROSOLS IN SEVERAL LOCATIONS IN SPAIN., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6207, https://doi.org/10.5194/egusphere-egu23-6207, 2023.

EGU23-6491 | Posters virtual | GI6.5 | Highlight

Radon gas emissions during the 2021 Tajogaite eruption at Cumbre Vieja Volcano (La Palma, Canary Islands) 

M. Candelaria Martin-Luis, Pedro A. Salazar-Carballo, María López-Pérez, Xiomara Duarte-Rodríguez, José L. Rodríguez-Marrero, José M. Lorenzo-Salazar, and Antonio Catalán-Acosta

On 19 September 2021, the largest historic eruption of La Palma began, named the Tajogaite volcano. It was active for 85 days, ending on 13 December 2021. During eruptions, the exposure to natural pollutants rises above background levels due to gas emissions and particulate matter (ash and aerosols) into the atmosphere. Moreover, rock fracturing due to magma injection and seismic activity associated with the eruptive phenomena can increase the ground permeability, having a potential effect on radon (222Rn) emissions. During the eruptive and post-eruptive period of the Tajogaite volcano, 222Rn measurements were performed across the affected areas to assess the possible radiological impact of this volcanic episode on La Palma inhabitants.

During the first weeks of the eruption, 88 Solid State Nuclear Track (CR-39-SSNT) detectors were deployed at workplaces and dwellings, mainly located in the vicinity of the eruption, though several detectors were also placed in more distant areas for comparison. These detectors were exposed for ca. 90 days, from September 2021 to January 2022, though only 77 detectors could be retrieved as the rest were buried by the lavas. In addition, 3 portable RadonScout devices (SARAD GmbH) were used for continuous monitoring (1 h integration time) of radon and environmental parameters (air temperature, humidity and barometric pressure). They were installed inside 3 buildings located 2.8-5 km from the volcano.

Eighty percent of the CR-39-SSNT radon data were below the reference level of 300 Bq/m3 (Directive 2013/59/Euratom). Of the remaining detectors, a large percentage of radon levels were above 300 Bq/m3 in the Aridane valley, an area close to the volcano, and with a clear spatial pattern showing higher levels of 222Rn at shorter distances to the eruptive centre. Continuous monitoring of radon showed low 222Rn levels (< 300 Bq/m3) at the two sites furthest from the volcano, with fluctuations highly correlated with environmental variables. Several anomalies of 222Rn reaching up to 4000 Bq/m3 were detected during the eruptive period in the monitoring station located closer to the eruptive centre, unrelated to the observed environmental variables. These anomalies were synchronous with the occurrence of large explosive events and phreatomagmatic pulses during the eruption.

The computed effective dose due to the contribution of 222Rn during the 3 months of eruption was 0.3 mSv, which, extrapolated to the annual reference value, provides an estimated effective dose of 0.9 mSv/year. This value is 50% lower than the estimated worldwide annual average dose from natural and artificial radiation sources (2.4 mSv/year) (UNSCEAR 2000). Thus, radon levels during the Tajogaite eruption did not lead to a significant increase in exposure level to this radioactive gas. However, transient radon bursts have been recorded associated with several phases of the volcanic activity.

 Acknowledgments

This study was supported by the Spanish Ministry of Science and Innovation (BOE-A-2021-20262).

References:

Council Directive 2013/59/Euratom laying down basic safety standards for protection against the dangers arising from exposure to ionising radiation, and repealing Directives 89/618/Euratom, 90/641/Euratom, 96/29/Euratom, 97/43/Euratom and 2003/122/Euratom.

UNSCEAR (2000), Sources and effects of ionizing radiation. UNITED NATIONS, New York.

How to cite: Martin-Luis, M. C., Salazar-Carballo, P. A., López-Pérez, M., Duarte-Rodríguez, X., Rodríguez-Marrero, J. L., Lorenzo-Salazar, J. M., and Catalán-Acosta, A.: Radon gas emissions during the 2021 Tajogaite eruption at Cumbre Vieja Volcano (La Palma, Canary Islands), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6491, https://doi.org/10.5194/egusphere-egu23-6491, 2023.

EGU23-7900 | ECS | Orals | GI6.5

A fast algorithm for real-time monitoring of artificial radioisotopes in presence of variable natural radioactivity 

Agustín Cerezo, Elena Prieto, Ignasi Reichardt, Ramón Casanovas, and Marçal Salvadó

The Catalan Environmental Radiological Surveillance Network consists of different types of scintillation gamma spectrometry detectors for the continuous and real-time automatic measurement of environmental radiation. The Network has a total of 35 monitors that obtain spectra every 10 minutes: 23 direct measurement monitors (13 with LaBr3(Ce), 5 SrI2(Eu) and 5 NaI (Tl) detectors), 10 particulate filter monitors (9 with LaBr3(Ce) detectors and 1 with SrI2(Eu)) and 2 river water monitors.

A method for the automatic and real-time quantification of the activity concentration of artificial, natural and NORM isotopes was developed and tested in the laboratory. The uncertainties in the activity concentrations, as well as the corresponding detection limits, were calculated applying the ISO-11929 standard. The developed and validated method that is exposed in the present study will be implemented shortly in all the stations of the Network.

The method is based on the analysis by spectral regions or ROIs (Regions of Interest). The method eliminates from the ROIs of the artificial (or NORM) isotopes of study the contributions due to emissions of natural isotopes (overlapping and Compton radiation), the ambient background, the possible intrinsic background of the detector and the contributions of other possible isotopes. As a result, an equation is generated for each isotope that allows us to obtain its net activity concentration (Bq/m3). This procedure is applied to determine the activity concentration of isotopes of natural origin (212Pb, 214Pb and 214Bi), artificial (131I, 137Cs and 60Co) and NORM (234Th).

The method successfully eliminates the contribution of natural elements, intrinsic background and Compton contribution, both in situations with high and low activity of natural isotopes. Therefore, it allows obtaining the net activity concentration of the artificial isotopes of interest and eliminates the presence of false positives that could be produced by the presence of natural isotopes.

How to cite: Cerezo, A., Prieto, E., Reichardt, I., Casanovas, R., and Salvadó, M.: A fast algorithm for real-time monitoring of artificial radioisotopes in presence of variable natural radioactivity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7900, https://doi.org/10.5194/egusphere-egu23-7900, 2023.

Detection of gamma-rays emitted by K-40 decay demonstrates potential for reliable soil moisture estimation for agricultural and hydrological applications. With a circular footprint of roughly 20 m radius, gamma-ray spectroscopy (GRS) provides a continuous, non-invasive average measurement that fills the scale gap between point and satellite data. GRS sensors have also been successfully integrated with Unmanned Aerial Systems opening the potential for soil moisture mapping.  Current theoretical models of gamma-ray spectra and soil moisture have not been extensively tested with empirical data. An existing soil moisture model for NaI gamma-ray spectra includes a method for biomass water content correction and was tested with five sampling campaigns in a tomato field, while another soil moisture model was tested with a single sampling campaign in a sugar beet field using CsI gamma-ray spectra. We hypothesize that testing existing theoretical models with thorough empirical data over a range of soil moisture and vegetative conditions will increase our understanding of the relationship between gamma-ray spectra, soil moisture, and biomass, and will allow us to validate and/or improve the soil moisture calibration function.

In this study we conduct a robust calibration of a stationary CsI gamma-ray soil moisture sensor (gSMS, Medusa Radiometrics) against gravimetric water content samples at a long term agricultural experimental field in eastern Nebraska, United States. Additional measurements include an Eddy Covariance tower, a Cosmic-Ray Neutron Sensor, in-situ soil moisture sensors, and destructive vegetation sampling every 10 days during the growing season. In total, 18 sampling campaigns were conducted between June 2021 and October 2022 under bare soil, maize, and soybean conditions. Soil samples were collected in a radial pattern at 0, 2, 5, and 12 m from the sensor, every 60 degrees following the expected spatial sensitivity of the gSMS. Samples from the 19 locations surrounding the sensor were aggregated in 5 cm intervals from 0 to 35 cm depth. Both a depth-weighting function and the arithmetic mean were used to calculate the average gravimetric water content within the sensing volume.

We then leverage the relatively large experimental data set of gravimetric water content and K-40 counts to test current theoretical approaches to soil moisture estimation with GRS. Data from both bare soil and vegetated conditions allow us to investigate and potentially remove the biomass water content signal from the soil moisture estimation. Comparison with the existing theoretical calibration functions shows large deviations with the empirical data.  Cosmic-ray Neutron Sensor data recorded at the site shows a high degree of correlation (R > 0.7 for hourly data) between the K-40 counts and neutron counts under changing biomass conditions. Lastly, comparison of the GRS derived soil moisture data with the in-situ soil moisture sensors, rainfall, and evapotranspiration result in good correspondence with soil moisture state and water fluxes at the study site.

How to cite: Becker, S. M. and Franz, T. E.: Theoretical vs experimental relationship between K-40 counts and gravimetric water content at a well instrumented agricultural research station in Nebraska, USA, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7988, https://doi.org/10.5194/egusphere-egu23-7988, 2023.

EGU23-12074 | Orals | GI6.5

Atmospheric radon measurements to assess the relative representativeness of radon flux models 

Dafina Kikaj, Edward Chung, Mareya Saba, Ute Karstens, Alistair Manning, Chris Rennick, Anita Ganesan, Grant Foster, Simon O’Doherty, Angelina Wenger, and Tim Arnold

The unique physical and chemical characteristics of radon make it an excellent tracer of atmospheric mixing and transport processes. As such, it has long been a species of interest to the climate change research communities. However, reliable, high resolution radon flux maps are essential for the use of atmospheric radon in climate studies.

Validation of the existing radon flux maps and inventories is currently limited by the availability of systematic measurements of radon fluxes and other process-relevant parameters (e.g., physical characteristics and moisture content of soil). Localised measurements of radon flux, soil moisture and soil physical properties can provide some information to validate and improve flux maps.  On the other hand, high sensitivity atmospheric radon measurements in conjunction with atmospheric transport models would determine the relative representativeness of radon flux models over larger scales.

To tackle the validation of radon flux maps, atmospheric radon measurements were compared to the results of modelled radon concentrations calculated using the Lagrangian particle model, the Met Office Numerical Atmospheric Modelling Environment (NAME) and two available versions of European radon flux maps1. For this purpose, radon data from three UK greenhouse gases atmospheric monitoring stations located in Heathfield (an inland, 100 m tall tower), Tacolneston (an inland, 185 m tall tower), and Weybourne (a coastal site, 10 m tower) were used. The differences between measured and modelled radon concentrations on diurnal and monthly scales will be presented and discussed. The ratio of measured-modelled radon concentrations shows the potential to objectively assess the reliability of radon flux maps under different wind directions and atmospheric mixing conditions.

 

 

1 2015: doi:10.1594/PANGAEA.854715 and 2022: ICOS data search (icos-cp.eu).

How to cite: Kikaj, D., Chung, E., Saba, M., Karstens, U., Manning, A., Rennick, C., Ganesan, A., Foster, G., O’Doherty, S., Wenger, A., and Arnold, T.: Atmospheric radon measurements to assess the relative representativeness of radon flux models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12074, https://doi.org/10.5194/egusphere-egu23-12074, 2023.

EGU23-12151 | ECS | Orals | GI6.5

Can radon measurements at tall towers provide information on atmospheric vertical mixing states? 

Mareya Saba, Dafina Kikaj, Edward Chung, Alistair Manning, Ute Karstens, Chris Rennick, Anita Ganesan, Grant Forster, Simon O'Doherty, Angelina Wenger, and Tim Arnold

The vertical mixing state of the atmosphere, as well as the atmospheric boundary layer (ABL) height, are important atmospheric transport model parameters for the accurate simulation of greenhouse gas concentrations. In order to use tall tower greenhouse gas measurements to quantify regional scale emissions (top-down, inverse estimates) an estimate of the atmospheric transport model uncertainty across the time series of study is needed. Several methods have been used to estimate this, often relying on arbitrary thresholds or a combination of parameters (such as vertical gradients if a gas is measured at multiple points). Here we study if radon has potential as an independent measurement to assess model uncertainty.

Radon is a radioactive noble gas present in our atmosphere and is a good tracer of mixing processes in the ABL due to its properties. Hence, measurements of atmospheric radon concentration can provide useful insights into the vertical mixing state of the atmosphere, and in turn may help to calibrate and validate atmospheric dispersion models.

In this study, we use high temporal resolution atmospheric measurements of radon and CH4 from four tall tower sites in the UK, which are part of the Deriving Emissions linked to Climate Change (DECC) network: Heathfield (HFD), Ridge Hill (RGH), Tacolneston (TAC) and Weybourne (WAO). At each site, CH4 is measured at two or three different heights, while radon is measured at one height.

To determine a metric whereby single-height measurements of radon can provide a proxy for vertical mixing states, we compare the diurnal cycle of the measured radon concentration with the modelled radon (calculated by the Met Office Numerical Atmospheric Modelling Environment (NAME) dispersion model and radon flux maps). The largest uncertainties are shown to be before sunrise and after sunset right before the inversion layer was formed/destroyed. The diurnal CH4 vertical gradient at these times is also compared with the modelled CH4 vertical gradient.

How to cite: Saba, M., Kikaj, D., Chung, E., Manning, A., Karstens, U., Rennick, C., Ganesan, A., Forster, G., O'Doherty, S., Wenger, A., and Arnold, T.: Can radon measurements at tall towers provide information on atmospheric vertical mixing states?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12151, https://doi.org/10.5194/egusphere-egu23-12151, 2023.

EGU23-12190 | ECS | Orals | GI6.5

Mapping the environmental radioactivity in Catalonia using a mobile unit with LaBr3 scintillation detectors. 

Elena Prieto, Agustin Cerezo, Ignasi Reichardt, and Marçal Salvadó

This study describes the equipment implementation of a mobile gamma spectrometry unit using LaBr3 detectors and the process followed to obtain a radiological map of Catalonia (Spain). The mobile unit consists of two 2”x2” LaBr3 scintillation detectors mounted on the top of a 4x4 car. To obtain the preliminary map, the extension of Catalonia was divided in 1425 cells of 5x5 km2. Before starting the measurements, we planned a route to ensure a proper distribution and a minimum quantity of spectra within each cell. The car is equipped with a portable computer to control spectra acquisition and a GPS system that associates a position to each spectrum. Each spectrum is stabilised and calibrated. During the acquisition, the computer placed inside the car shows, in real-time, the value of the ambient dose equivalent and the exact location. Therefore, when the software obtains an unexpected high value, the driver of the car can modify the route to acquire more spectra of the area. The first data set of measurements included 70000 spectra obtained during stable weather conditions and represent the preliminary results of the radiological map, as other data campaigns are currently under preparation. In this study, we present the ambient dose equivalent map of Catalonia and isotopic information of interest, such as punctual detections of 137Cs and 131I and other radionuclides. The origin of these detections is analysed and explained in detail.

How to cite: Prieto, E., Cerezo, A., Reichardt, I., and Salvadó, M.: Mapping the environmental radioactivity in Catalonia using a mobile unit with LaBr3 scintillation detectors., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12190, https://doi.org/10.5194/egusphere-egu23-12190, 2023.

EGU23-14656 | Orals | GI6.5

Atmospheric transport modelling of radon-222 at European scale: description and validation against ICOS observations. 

Arnaud Quérel, Tanina Hached, Denis Quélo, Michel Ramonet, Camille Yver Kwok, and Ute Karstens

Atmospheric transport models used for nuclear emergency purposes are dedicated to simulating the atmospheric transport of radionuclides released from a damaged nuclear facility. The quality of this response is crucial and must be constantly improved. However, long-range measurement campaigns for validation are scarce, especially for radioactive pollutants. An effective way to do so is by simulating the radon-222 which is a non-reacting atmospheric tracer species with quite well-known exhalation rate and well-known nuclear transitions.

Radon-222 is naturally emitted. Its flux spatial variation is mainly due to the type of soil and rocks, rather than the vegetation or land use. Temporal variations are mainly led by soil humidity, leading to a monthly variation. The monthly surface radon flux map of Karstens and Levin, 2022 is used in this study.

The availability of the observations at suitable temporal and spatial scales is achieved in this study thanks to the Integrated Carbon Observation System, ICOS (Heiskanen et al. 2021). ICOS provides standardized and open data from more than 39 atmosphere stations that measures greenhouse gases concentrations in the atmosphere. Some stations also provide radon-222 concentrations measurements. Among them, some also include measurements at different heights - from ground level up to 200 meters – which is valuable to validate the vertical atmospheric transport modelling. The limited set of radon-222 stations is not a substitute for performing the comprehensive validation against a large variety of observations but gives valuable information on the performance of air concentration predictions. A previous study using the dose rate measurements network (Quérel et al. 2022), required in addition the need of an accurate deposition modelling to assess gamma dose rates at ground level due to wet deposition of radon-222 decay products.

We evaluate here the overall performance of an air concentration modelling chain: Karstens radon-222 fluxes, Météo-France ARPEGE numerical weather predictions and IRSN LdX operational atmospheric transport model. Simulated radon-222 air concentrations are compared with observations from the ICOS monitoring network over Europe, on an hourly frequency basis over one year. On initial examination, the model appears to under-predict radon-222 concentrations and some possible explanations and sources of improvement are identified.

 

References:

Heiskanen, J., C. Brümmer, N. Buchmann, C. Calfapietra, H. Chen, B. Gielen, T. Gkritzalis, S. Hammer, S. Hartman, M. Herbst, et al. (2021), The Integrated Carbon Observation System in Europe, Bulletin of the American Meteorological Society, 1 - 54, doi:10.1175/bams-d-19-0364.1.

Karstens, U. and Levin, I. (2022). traceRadon monthly radon flux map for Europe 2006-2022 (based on GLDAS-Noah v2.1 soil moisture), https://hdl.handle.net/11676/ge5vMeklvG_Qz43rzcS2wx0-

Quérel, A., Meddouni, K., Quélo, D., Doursout, T., and Chuzel, S. (2022). Statistical approach to assess radon-222 long-range atmospheric transport modelling and its associated gamma dose rate peaks. Advances in Geosciences. 57. 109-124. 10.5194/adgeo-57-109-2022.

How to cite: Quérel, A., Hached, T., Quélo, D., Ramonet, M., Yver Kwok, C., and Karstens, U.: Atmospheric transport modelling of radon-222 at European scale: description and validation against ICOS observations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14656, https://doi.org/10.5194/egusphere-egu23-14656, 2023.

EGU23-15199 | Posters on site | GI6.5

Water preparation methods of dissolved organic fraction determination for C-14 AMS measurements 

Anita Molnár, Róbert Janovics, Mihály Veres, and Mihály Molnár

The determination of 14C in dissolved inorganic carbon (DIC) fraction has important task in nuclear environmental monitoring and water base protection. The aim of my research is to develop a preparation method for the 14C determination of dissolved organic carbon (DOC) and to develop sample preparation of total carbon containing both organic and inorganic fractions. In practice, the measurement of dissolved inorganic carbon (DIC) 14C is of essencial importance for example in environmental studies, as the amount of DIC is usually more than 100 times the amount of DOC and there is an easy, rapid preparation method. However, it is often difficult to interpret water dating and water residence time by measurement of dissolved inorganic fraction, because DIC dissolved in water can come from several sources: deep CO2 uptake and bedrock dissolution, not only from the surface biogenic environment at the time of seepage. Therefore, the measurement of dissolved organic carbon (DOC) component gets more importance around nuclear facilities because of its efficiency in detection of anthropogenic effect. To this aim, preparation methods have been developed that are suitable to determine the specific 14C activity concentration of the total dissolved carbon (TD14C) as well as of the dissolved organic form (non-purgeable organic fraction). The measurement of 14C in organic form is a difficult task, the amount of material is usually very small (only a few µg) and samples are difficult to handle furthermore the necessary sample volume usually is more than 500 mL. One of the solutions for DO14C sample preparation is an application of wet oxidation method. In this case the organic components are oxidized by acid and CO2 is extracted. This type of sample preparation technique is basically very sensitive about modern and fossil carbon contamination. However, the method has the additional disadvantage of high chemical demand (hence the contamination introduced) and a complicated and long sample preparation process. These disadvantages can be overcome by testing the total dissolved fraction 14C, which contains both fraction: inorganic and organic forms. Sample preparation can be performed in a significantly shorter time and at lower cost and can be used effectively alongside DI14C for the detection and monitoring of organic forms, for example in environmental monitoring of nuclear facilities. By determining DI14C and TD14C and carbon concentrations, DO14C can be estimated with a good approximation (±10% rel. error).

 

,,Prepared with the professional support of the Doctoral Student Scholarship Program of the Co-operative Doctoral Program of the Ministry of Innovation and Technology financed from the National Research, Development and Innovation Fund.”

The research was supported by the European Union and the State of Hungary, co-financed by the European Regional Development Fund in the project of GINOP-2.3.4-15-2020-00007 “INTERACT”.

How to cite: Molnár, A., Janovics, R., Veres, M., and Molnár, M.: Water preparation methods of dissolved organic fraction determination for C-14 AMS measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15199, https://doi.org/10.5194/egusphere-egu23-15199, 2023.

EGU23-15860 | Orals | GI6.5

On the trail of Cs-137 and Sr-90 – Trace analysis to monitor radioactivity in air 

Sandra Baur, Sabine Schmid, Jacqueline Bieringer, and Andreas Bollhöfer

The German Federal Office for Radiation Protection (Bundesamt für Strahlenschutz, BfS) is legally obliged to continuously monitor radioactivity in the environment in Germany. The Atmospheric Radioactivity and Trace Analysis Section of the BfS is operating four different measurement facilities/laboratories in Southern Germany: gamma spectrometry, radiochemistry and noble gas laboratories in Freiburg i.Br. and the Comprehensive Nuclear-Test-Ban Treaty Organisation (CTBTO) monitoring station RN33 on Mt. Schauinsland. The three laboratories provide data of radioactive aerosol bound particulates such as Cs, U, Pu or Sr and noble gases (Kr and Xe) for the German Integrated Measurement and Information System (IMIS). The radionuclide station RN33 is monitoring radioactive particulates and Xe for the International Monitoring System (IMS) of the CTBTO. The variation of radioactivity on aerosol bound particles over time and the analysis of their origin, distribution and transport in the environment will be presented.

To collect aerosol bound particles, ground-level air sampling is carried out by high volume air samplers located in Freiburg i.Br. and on Mt. Schauinsland. The high volume air sampler is operated with two filter layers: an upper polypropylene layer with a collection efficiency of about 85% to 95% and a bottom fibre glass layer with a collection efficiency of almost 100%. The fibre glass filter is used as a control for collection efficiency of the polypropylene filter. As required by the German IMIS monitoring programmes, the routine sampling period is seven days, which can be reduced to daily cycles in case of (un)expected enhanced activity concentrations. The filters are separately pressed to pellets and analysed by high resolution γ-spectrometry. In addition, the polypropylene-filters are processed radioanalytically and analysed with a low level α/β-counting system and α-spectrometry.

The applied methods together with atmospheric transport modelling allow to detect smallest amounts of radioactive substances as well as to investigate their origin, distribution and transport in the environment. In addition, the Cs-137/Sr-90 ratios can be used as a geochemical fingerprint for source identification. Current (2022) median activity concentrations in ground-level air for Cs-137 and Sr-90 (2021) are 0.42 µBq m-³ and 0.06 µBq m-³, respectively. Detection limit (LOD) for Cs-137 is on average 0.14 µBq m-³ in weekly samples and 0.01 µBq m-³ in monthly samples for Sr-90. In March 2022 dust blown in from the Sahara towards Southern Germany resulted in slightly higher airborne Cs-137 activity concentrations while Sr-90 did not markedly change. Other sources for increased Cs-137 activity concentrations include past above ground nuclear weapons tests or resuspension of fallout from the Chernobyl accident. Thus, trace analysis is used to track short- and long-term changes in radioactivity in the environment at lowest activity levels.

How to cite: Baur, S., Schmid, S., Bieringer, J., and Bollhöfer, A.: On the trail of Cs-137 and Sr-90 – Trace analysis to monitor radioactivity in air, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15860, https://doi.org/10.5194/egusphere-egu23-15860, 2023.

EGU23-16827 | Orals | GI6.5

Testing mobile ground-based gamma-ray spectroscopy for measuring 40K in an agricultural field (Spain) 

Leticia Gaspar, Iván Lizaga, Arturo Catalá, and Ana Navas

Proximal gamma-ray spectroscopy is an effective technique for monitoring the spatial and temporal distribution of terrestrial radioelements like 40K, which is inversely proportional to the volumetric soil water content SWC (m3/m3). In recent years, PGRS has become a promising sensor to infer topsoil water content at an intermediate field scale supported by adequate calibration and corrections, but to date, it has not yet been used in Spain. The aim of this contribution is to test the response of mobile ground-based gamma measurements conducted while walking over an agricultural plot of 400 m2 of bare soil. Two surveys were conducted, a day before and a day after a 16-liter rain episode, allowing us to i) evaluate the information obtained when using the mobile mode, ii) test the response of the PGRS to dry and wet soil conditions, and iii) compare mobile measurements with stationary records taken during one hour at the 4 vertices of the study plot. A scintillator detector of 0.3 L sodium iodide (NaI) crystal was used to evaluate the region of interest for total counts of 40Potassium (1461 KeV). The mobile measurements were conducted 0.5 m above the soil surface and taken in stop-and-go mode (instead on-the-go mode) with two sets of 5 transects spaced 5 m apart placed in a perpendicular direction to cover the study plot. While walking we stopped every 1m for 10 sec. to collect a total of 21 measurements per transect, obtaining 210 data for geostatistical interpolation. These preliminary results show higher content of 40K (cps) during the dry compared to the wet survey, and some differences in the spatial distribution of 40K for both surveys. Similarities and parallel trends were observed when comparing mobile and stationary measurements, supporting the promising use of PGRS technique.

How to cite: Gaspar, L., Lizaga, I., Catalá, A., and Navas, A.: Testing mobile ground-based gamma-ray spectroscopy for measuring 40K in an agricultural field (Spain), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16827, https://doi.org/10.5194/egusphere-egu23-16827, 2023.

EGU23-2574 | ECS | Posters virtual | GI6.7

2D mineral prospectivity mapping of hand specimen and outcrop walls using AHS and pXRF data in Bockau 

Martin Köhler, Nailia Rizatdinova, Andreas Knobloch, and Roberto de la Rosa

The Goldeneye project combines different sensing technologies with proximal sensing to produce reference calibrated mineralogical maps through data fusion. In order to develop mineral detection applications, rock specimens, taken from an outcrop in Bockau (Erzgebirge, Germany), are analyzed with active hyperspectral scanning (AHS) as well as portable X-ray fluorescence (pXRF) devices. The received data is analyzed by means of artificial intelligence in order to develop an approach to automatically map the minerals with the samples. The analysis is carried out in advangeo® 2D Prediction, developed by Beak Consultants GmbH. Tin concentrations derived from pXRF measurements and AHS data from 2/3 of the specimen surface serve as training and validation data of the artificial intelligence algorithm (artificial neural networks). As a result, we developed a prediction model for the distribution of tin and its associated mineral cassiterite throughout the rock specimen, which allows to detect the mineral potential of hand specimens and larger outcrops in a fast and reliable manner.

The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the Grant Agreement 869398.

How to cite: Köhler, M., Rizatdinova, N., Knobloch, A., and de la Rosa, R.: 2D mineral prospectivity mapping of hand specimen and outcrop walls using AHS and pXRF data in Bockau, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2574, https://doi.org/10.5194/egusphere-egu23-2574, 2023.

EGU23-2597 | Orals | GI6.7

AMD Monitoring using multispectral imaging from Worldview-3, Sentinel-2 and drone-based data 

Delira Hanelli, Andreas Knobloch, Jari Joutsenvaara, Julia Puputti, Ossi Kotavaara, Korab Tmava, Azem Rexhaj, and Ana Bautista Gascuena

The sulfidic sulfur contained in the host rocks and mining waste leads to strong acid mine drainage processes in the mining landscapes of Trepca, Kosovo and Pyhasalmi, Finnland. In the present, the water quality is usually monitored by discrete sampling and analysis of dissolved metal particles and other chemical parameters. Not only is this a cost- and time-consuming process, but the assessment takes place only on discrete locations.

The main aim of this application is to elaborate the suitability of multispectral remote sensing (R/S) data from different sensors for area-wide identification and quantitative mapping of Acid Mine Drainage (AMD) constituents such as dissolved iron concentration (Fe3+), pH value etc. in water bodies. The potential for mining waste to be subject to AMD processes is also being investigated through area-wide quantitative mapping of the sulfate content (SO₄2-) in solid ground.

In this framework, water and solid ground samples were collected to calibrate and validate the supervised machine learning algorithm of Artificial Neural networks (ANN), used for the identification of dependencies between the multispectral R/S data and the ground measurements. The ANNs of multilayer perceptron type (MLP) is implemented in the advangeo® 2D Prediction software from Beak Consultants GmbH (www.advangeo.com). The modelling and prediction software analyses complex non-linear relationships between a wide variety of spatial controlling parameters and natural complex processes or occurrences, by using methods of artificial intelligence within a Geographic Information System (GIS) environment.

In the mining landscapes of Artana 1 & 2 and Kelmend, AKG has allocated and analysed about 20 water samples and 15 soil samples between May – August 2022 in two field campaigns, whereas low pH values (3 – 4), dissolved iron concentrations up to 25 mg/L and sulfate contents up to 28474 mg/kg have been recorded. Because of the small-scale features in the mining landscapes, high-resolution multispectral images from Worldview-3 and time-series of drone-based acquisitions are used as controlling parameters for the modelling process.

In the tailing pond of Pyhasalmi and the surrounding water environment, the Oulu University has allocated and analysed about 60 water samples between June – October 2022 in two field campaigns. Low pH values (3 – 4), dissolved iron concentrations up to 1800 mg/L and sulfate contents up to 2200 mg/l have been recorded. In this case, medium-resolution multispectral images from Sentinel-2 (Level-1C TOA and Level-2A BOA products) and high-resolution images from Worldview-3 are used as controlling parameters for the modelling process.

In all scenarios, the imagery was acquired during similar time frames as the sampling, to ensure that the measured water / soil grounds parameters correspond to the surface reflectance information.

In the study, advantages and limitations of different multispectral imaging sensors are elaborated. The newly established dependencies from the ANN models can be used to perform area-wide monitoring of AMD processes in time-series, drastically reducing the need for terrestrial measurements in the future.

The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the Grant Agreement 869398.

How to cite: Hanelli, D., Knobloch, A., Joutsenvaara, J., Puputti, J., Kotavaara, O., Tmava, K., Rexhaj, A., and Bautista Gascuena, A.: AMD Monitoring using multispectral imaging from Worldview-3, Sentinel-2 and drone-based data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2597, https://doi.org/10.5194/egusphere-egu23-2597, 2023.

EGU23-2625 | Posters virtual | GI6.7

Detection of mining relics (Pingen) using LiDAR technology 

Enis Sterjo, Andreas Knobloch, Martin Köhler, and Andreas Brosig

From the middle of the 17th to the beginning of the 19th century, tin mining was carried out near Bockau and Aue in the Westerzgebirge. The object of the mining was stratiform mineralization. Near Bockau, (underground) tin mining was first mentioned in documents in 1663 and was active, with interruptions, until the beginning of the 19th century. On an area of more than 2 km², hundreds of dumps and pits, numerous abandoned mines, and historically very remarkable underground objects are known. Mining was preferably carried out near the surface. Despite favourable morphological conditions, hardly any deep adits were built and depths of more than 20 m were rarely reached. In this context, Pingen are abandoned ore pits or prospecting sites, where ores and other mineral resources were mined. Geometrically Pingen resemble round depressions created by the collapse of a mine workings (shaft, adit, underground drift), collapsed due to its age, leaving this relic usually funnel-shaped (down-facing cone), often surrounded by an annular dump (0.5 to 3 m) caused by the lowered surface.

The main aim of this application is to identify mining relics (Pingen) using a UAV equipped with LiDAR technology. The LiDAR technology allows to obtain a high-resolution Digital Elevation Model (DEM) and Point cloud of the surveyed area. The DEM is the digital representation of topographic and manmade features located on the surface of the earth.

In this framework, a LiDAR survey was conducted in a flight area of about 1,6 km² within the “Bockau” area during August 2022. The surveyed features include the elevations, colorized Point Cloud (RGB values), transparency levels, reflectance values, and number of returns (significant for the penetration of the vegetation). This information was used to derive the final products: DEM and classified Point cloud. Various spatial analyses were conducted and tested on the DEM and Point Cloud to automatically identify the mining relics. Hydrogeological analysis showed to be the best approach for the automatic identification of Pingen. As a result, the ground depressions were identified and nested surfaces were delineated.

The automatically identified features were validated by examination of randomly selected samples on the surveyed point cloud, comparison to identified features based on the National dataset of the LiDAR Database and field verification. The validation revealed, that around 90% of the Pingen in the study area were successfully identified with the developed workflow. Other features of interests couldn’t be identified due to the similarity of geometric properties with other topographical features, dense vegetation, erosion etc.

The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the Grant Agreement 869398.

How to cite: Sterjo, E., Knobloch, A., Köhler, M., and Brosig, A.: Detection of mining relics (Pingen) using LiDAR technology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2625, https://doi.org/10.5194/egusphere-egu23-2625, 2023.

Remote sensing UAV based technology combined with modern alteration mapping tools (SWIR, XRD Raman and XRF) for mineral detection has experienced great advances in the Cu-Au epithermal exploration targeting. We demonstrate quick and cost-efficient approach for epithermal gold exploration mapping and evaluation on examples of high-sulphidation epithermal Cu-Au deposits and prospects in the Panagyurishte ore district, Bulgaria.

The Panagyurishte ore district is part of the global Tethyan-Eurasian Cu-Au belt that developed during the Mesozoic as a copper-rich, andesite-dominated magmatic arc system characterized by obvious affiliation of porphyry-copper (PCD) and epithermal Cu-Au ore deposits with granodiorite and andesite dominated magmatic complexes. The target mapping has lacked high-resolution data to identify and prove the geometry of the alteration mineral assemblages and ore controlling fault structures. When distal sensing is combined with field mapping and proximal modern mineral detection methods such as SWIR (1300-2500nm) and Raman spectroscopy, XRD and ore petrography is more efficient tool for detection of hydrothermally altered minerals and zones by their diagnostic spectral signatures.

Drone based photogrammetry approach was applied for hydrothermal alterations mapping and targeting for Cu-Au epithermal deposits exploration in the Panagyurishte ore district, Bulgaria. Mineral alterations maps for Pesovets, Petelovo and Krassen Au-epithermal deposits was assembled using orthophoto model and TIR- 3D mapping to utilize the time and cost efficiency of the subsequent geological exploration field work. For classification and verification of drone orthophoto mosaic geological mapping and rock sampling was carried out in addition to XRF and XRD mapping and stream sediments sampling. UAV- based mapping with selected light bands was used to recognize different hydrothermal alterations styles such as advanced argillic (AAA), argillic (AA) propylitic (Prop) and phyllic (Phy) alteration styles that are overprinting andesitic volcanic sequences in the central part of Panagyurishte ore district. Radial and concentric fault structures and regional strike-slip fault zones have also been proved by UAV-based mapping. Domains of proximal hypogene AAA and AA and more distal propylitic halo as possible host of HS gold mineralization were clearly outlined. XRF mapping of the Pesovets lithocap indicate increasing of As (20-50ppm) and Ti (570-2400ppm) concentrations when approaching AA and AAA alteration domains and could also provide effective vectoring tool for targeting of epithermal Cu-Au mineralization.

 The recent study demonstrates UAV-based mineral mapping approach that will help to improve the exploration targeting and decision making in and eestimation of the Cu-Au mineral potential in cost-efficient manner.

The study is supported by the Horizon 2020 co-funded GOLDENEYE project, which has received funds through the Grant Agreement 869398.

How to cite: Bogdanov, K., Velev, S., and Krumov, I.: Remote-sensing applications for Au-epithermal deposits mapping and exploration targeting in Panagyurishte ore district, Bulgaria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2669, https://doi.org/10.5194/egusphere-egu23-2669, 2023.

EGU23-2781 | ECS | Posters on site | GI6.7

3D mineral prospectivity mapping of the Bockau tin deposit 

Paul Bohlender, Andreas Brosig, Roberto De La Rosa, Andreas Knobloch, and Andreas Barth

To ensure Europe increases its domestic production of high quality and responsibly produced raw materials, the development of innovative technologies for 3D geological modeling in mineral exploration is paramount. The Erzgebirge in Germany provides an excellent framework to showcase the application of artificial intelligence and in particular Artificial Neural Networks (ANN) for 3D mineral prospectivity mapping. The Erzgebirge belongs to the Variscan Belt, withholding 800 years of mining history and it is also famous for Ag, Sn, W, Fe, Cu, Li mineralizations among others. The Bockau deposit is located at the western section of the Erzgebirge. The target area is a Paleozoic metasediment body that was formed during the Variscan orogeny. The metasediment body consists primarily of alternating micaschist, phyllite and quartzite and dips mostly 25° to 240° SW. The metasediment is surrounded by Late Variscan plutons which partly led to contact metamorphic zones. In addition there is a large Quartzite body which was mined near to the surface in the 17th century for Sn, following a stratiform tin anomaly which can reach up to 4000 ppm Sn.

Thanks to the long mining history, the Bockau deposit condenses a large amount of geological, geochemical, geophysical and mineral data. To increase mineralogical knowledge of the deposit and to help identify drilling targets, a hybrid approach for 3D mineral predictivity mapping is implemented. Potentially mineralisation-controlling factors are identified in knowledge-driven genetic exploration models, taking into account the borehole data, major faults, electromagnetic data, intrusive bodies, contact metamorphic zones and lithological borders, followed by data-driven weighted ANN predictive modelling implemented in the in-house developed advangeo® 3D Prediction Software. The predictive model is guided by structural variables such as the euclidean distance to fault planes, lithological surfaces and to metamorphic contact zones. The model is also constrained by geophysical data by a magnetic susceptibility model obtained from an airborne magnetic data inversion. Finally, Sn anomaly data from boreholes is implemented as training data for the prediction.

The results show the probability distribution of Sn mineralisation occurrence in 3D over a voxel model formed by blocks of approximately 684 m3 13(x), 13.5(y) and 4(z), increasing the mineralogical knowledge of the deposit and guiding exploration efforts complementing the decision making process for drilling new targets. The results are validated by iteratively implementing the jackknife method, splitting the training data into validation and training subsets. The first prediction iteration is performed with a subset containing 77 % of the Sn content data from boreholes as training data, followed by 50 and 30 % subsets. Thus, allowing at each iteration to perform a quantitative evaluation of the prediction by comparing the validation subset with the Sn content of the borehole that was not used for the prediction.

The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the Grant Agreement 869398.

How to cite: Bohlender, P., Brosig, A., De La Rosa, R., Knobloch, A., and Barth, A.: 3D mineral prospectivity mapping of the Bockau tin deposit, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2781, https://doi.org/10.5194/egusphere-egu23-2781, 2023.

The Panagyurishte ore district, Bulgaria is situated in the Srednogorie zone situated in the western part of the global Cu-Au dominant Tethyan-Eurasian Cu-Au metallogenic belt. Significant examples of Late Cretaceous volcano-plutonic structures with porphyry-copper deposits (Elatsite, Medet, Asarel, Tsar Assen, Vlaykov Vruh), connected to subvolcanic granodiorite porphyry intrusions occur in the Panagyurishte ore region, Bulgaria. The PSD are closely associated with high-sulphidation type Cu-Au epithermal deposits (Chelopech, Krasen, Radka, Elshitsa) that are related to andesite - dacite magmatic activity. 3D UAV-supported alteration mapping of Vlaykov Vruh and Tsar Assen PCD have been performed to identify and prove the geometry of the alteration mineral assemblages and ore controlling structures. Domains consisting of phyllic, argillic, propylitic and K-silicate alteration zones associated with and porphyry-copper style of mineralization in Vlaykov Vruh and Tsar Assen deposits were outlined. 3D modelling of Popovo Dere PCD by means of Leapfrog Geo and mineral alteration mapping study outlined fault controlled proximal K-silicate domain and more distal propylitic domain as a potential Cu-porphyry deposit target for further mineral exploration and evaluation

Two types of K-silicate alterations, one with magnetite and another without magnetite that hosted Cu-porphyry mineralization have been distinguished within the proximal Cu-rich zone. More distal propylitic domain has also been outlined by 3D modelling. Strike-slip fault control within the K-silicate alteration domain outlined the cone shaped Cu-porphyry ore body. The UAV-Multispectral and TIR mapping in addition to XRD study confirmed the geometry of phyllic alteration domain hosted in andesitic and dacitic volcanic rocks. The propylitic alteration zone is developed in the granodiorite porphyry intrusion in Vlaykov Vruh PCD and with K-silicate domains hosts Cu-Mo mineralization. Fe-oxide and malachite rich domains have been traced in Tsar Assen PCD in addition to Cu-rich zone in the western part of the open pit.

The recent study demonstrates that combined UAV-supported remote sensing and mineral alteration field and XRD mapping could provide an effective vectoring and exploration targeting tool toward PCD mineralization

This study is supported by the Horizon 2020 co-funded GOLDENEYE project through the Grant Agreement 869398.

How to cite: Velev, S., Bogdanov, K., and Krumov, I.: 3D alteration mapping and remote-sensing applications for porphyry -copper deposits (PCD) exploration, in Panagyurishte ore district, Bulgaria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3168, https://doi.org/10.5194/egusphere-egu23-3168, 2023.

EGU23-4901 | ECS | Orals | GI6.7

Development of time-gated Raman proximal sensing for an earth observation platform 

Jari Havisto, Martin Köhler, Sanna Uusitalo, Marko Paavola, Andreas Knobloch, and Katariina Rahkamaa-Tolonen

The Goldeneye project combines remote sensing and positioning technologies with proximal sensing to produce reference calibrated mineralogical maps through data fusion. The project brings together optical satellite sensor data, drone sensor aerial data both optical and electromagnetic as well as spectral ground sensor data. Satellite data can offer spectral signatures of large areas but suffers from limited spatial resolution and blind spots where the higher resolution satellite data is not available. Drone data can offer more variety in spectral wavelengths with higher resolution but there are some drawbacks as well. Namely, NIR vibrational spectroscopy requires background information for successful mineralogical analysis. In addition, the most interesting SWIR range is challenging due to large and very expensive sensors. To cope with these challenges of aerial data, proximal sensing can be applied in locations where satellite imagery is not available, and it can also produce reference information for the calibration of the spaceborne and airborne instruments. The conventionally used analyses for producing mineralogical information from field collected samples are the mineral liberation analysis (MLA) and X-Ray diffraction (XRD) which require extensive sample preparations and are laborious and slow. Goldeneye-project has studied the use of time-gated Raman for easier and more practical production of reference data at the field sites as well as from field collected rock samples. The benefit of Raman is an accurate characteristic spectral fingerprint and an ability to distinguish small mineralogical features as the detection spot is in the range of hundreds of microns. There are continuous wave Raman spectrometers, which are already field deployable. However, conventional Raman suffers from the auto-fluorescence emission triggered by the laser illumination, especially in light-colored rock samples. Time-gated (TG) Raman has the benefit of time-resolved sensing, where the Raman scattering is recorded before the fluorescence signal is over-powering the weaker scattered signal. TG-Raman can thus offer information from a wider variety of geological specimen than the conventional Raman. In Goldeneye-project, TG-Raman spectra were collected with custom sampling solution from mineral samples and drill cores from Erzgebirge exploration site in Germany. The data was analysed together with pXRF reference data to assess the benefit of the data fusion.

The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the Grant Agreement 869398.

How to cite: Havisto, J., Köhler, M., Uusitalo, S., Paavola, M., Knobloch, A., and Rahkamaa-Tolonen, K.: Development of time-gated Raman proximal sensing for an earth observation platform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4901, https://doi.org/10.5194/egusphere-egu23-4901, 2023.

EGU23-5181 | Posters on site | GI6.7

Monitoring Active Mining Areas in Operation using Sentinel-1 Coherence Time Series 

Kateryna Sergieieva, Olena Kavats, and Dmitriy Khramov

Monitoring and mapping open-pit mining activity is essential to identify operation sites and unaffected surfaces of mining areas. Vertical displacements of the earth's surface associated with open pit mining can be detected using high spatial resolution Digital Surface Model (DSM) data or based on all-weather Synthetic Aperture Radar (SAR) Single Look Complex (SLC) satellite images using Differential Interferometry Synthetic Aperture Radar (DInSAR) technique. In some cases, activity in an open pit may not be accompanied by changes in terrain heights but cause violations of land cover integrity accompanied by earth's surface texture changes (for example, deforestation or recultivation, violation of quarries and dump slope integrity, changes in surface conditions, hydrological disturbances, etc.) and can be detected using coherence maps generated from SAR SLC data.

Coherence is the modulus of the complex correlation coefficient between two SLC images containing information about the amplitude and phase of the radar signal. If there is no surface change between the two survey dates, the coherence values are close to 1. Mining activities change the surface texture, so the coherence decreases to values close to 0. The frequency approach estimates the total changes in coherence over the season. For example, the Temporal Activity Index (TAI) is a relative coherence frequency below a given threshold across the time series of SAR images. In the case of monitoring open pit mining, activity areas with consistently low coherence over a time series of observations are of primary interest.

The study area is an open-pit mining area of the Pyhäsalmi Mine located in the Pohjois-Pohjanmaa region, Finland. It includes an old open pit, a backfill open pit, and several waste dumps [1]. Time series of Sentinel-1 SLC Interferometric Wide (IW) images were used to detect active areas in operation for the study area. Images were collected every 12 days from May to  September 2020-2022 and provided by the GOLDEN-AI platform [2].

For each observation year, a time series of Sentinel-1 SLC coherence was generated for the Pyhäsalmi mine. Active areas in operation were identified for open pits and waste dumps based on TAI maps (Fig. 1), providing information about the intensity of surface changes during the observation periods.

Figure 1. Temporal Activity Index maps for the Pyhäsalmi Mine area.

Funding. This work was funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 869398 “Earth observation and Earth GNSS data acquisition and processing platform for safe, sustainable and cost-efficient mining operations” (Goldeneye).

Acknowledgments. The authors gratefully acknowledge Maria Hänninen, Environmental Manager at Pyhäsalmi Mine Oy for specification locations for measurements and study planning, and the OPT/NET BV company (opt-net.eu) and GOLDEN-AI platform for supplying Sentinel-1 data. The authors would like to thank the European Commission, the European Space Agency, and the Copernicus Program for providing Sentinel-1 data.

References:

[1] Siikanen, S., Savolainen, M., Karinen, A., Puputti, J., Kauppinen, T., Uusitalo, S., & Paavola, M., 2022. Drone-based near-infrared multispectral and hyperspectral imaging in monitoring structural changes in mine tailing ponds. Thermal Infrared Applications XLIV, Vol. 12109, pp. 58-64). https://doi.org/10.1117/12.2618294

[2] Havisto, J., Matselyukh, T., Paavola, M., Uusitalo, S., Savolainen, M., González, A. S., Knobloch, A. & Bogdanov, K., 2021. Golden AI Data Acquisition and Processing Platform for Safe, Sustainable and Cost-Efficient Mining Operations. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, pp. 5775-5778. https://ieeexplore.ieee.org/document/9554181

 

How to cite: Sergieieva, K., Kavats, O., and Khramov, D.: Monitoring Active Mining Areas in Operation using Sentinel-1 Coherence Time Series, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5181, https://doi.org/10.5194/egusphere-egu23-5181, 2023.

EGU23-6208 | Posters on site | GI6.7

Interferometric Synthetic Aperture Radar (InSAR)-based measurements of displacements due to geomorphologic changes in northern mining environments – testing and validating InSAR in open pit and tailings of Pyhäsalmi Mine, Finland 

Ossi Kotavaara, Guillem Domenech, Sandra Mingot, Jari Joutsenvaara, Julia Puputti, Daniel Nieto Yll, Zarina Acero, and Terhi Ala-Hulkko

Monitoring the stability of mine structures, such as tailing ponds and open-pits, is crucial for ensuring the safety of personnel on-site and for preventing environmental accidents. This must be done, not only during the active operation of a mine, but also during possible reuse phases, and even after closure. Currently, monitoring the structural stability of the mining area relies heavily on manually conducted RTK-GNSS-based measurements of established control points. While this is a precise and relatively simple technique, it does pose a limit to how many control points can feasibly be monitored, as using tens or even hundreds of control points is time-intensive and laborious. Consequently, monitoring larger areas and areas requiring frequent measuring can be challenging. A remote monitoring option would also remove the element of danger that comes from having to reach control points in possibly unstable areas. InSAR appears to be an alternative for measuring terrain displacements in large, mining areas. Some limitations remain, as terrain coverage and weather conditions in northern latitudes can hinder InSAR analysis. 

 

The Callio Lab research centre at the Pyhäsalmi mine in Finland has been chosen as a test site for InSAR measurements conducted during the EU H2020-funded GoldenEye project. InSAR is used to measure terrain displacement as a result of geomorphologic changes during the summer and autumn of 2022. Additionally, InSAR analysis will be carried out using a network of corner reflectors during winter 2023. InSAR measurements will be evaluated and compared to drone imagery-based photogrammetric Digital Elevation Models (DEM) and field observations. Supplementary RTK-GNSS measurements are planned to be used to control the stability of selected control points. Results will provide valuable insight about InSAR usability for long-term monitoring in northern latitudes in mine environments, as well as, knowledge related to weather and terrain conditions required for obtaining reliable InSAR. Results will also touch on the main challenges faced when using InSAR in such an environment.

 

This work has been supported by project Earth observation and Earth GNSS data acquisition and processing platform for safe, sustainable and cost-efficient mining operations (Goldeneye) ID: 869398, Horizon 2020.

How to cite: Kotavaara, O., Domenech, G., Mingot, S., Joutsenvaara, J., Puputti, J., Nieto Yll, D., Acero, Z., and Ala-Hulkko, T.: Interferometric Synthetic Aperture Radar (InSAR)-based measurements of displacements due to geomorphologic changes in northern mining environments – testing and validating InSAR in open pit and tailings of Pyhäsalmi Mine, Finland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6208, https://doi.org/10.5194/egusphere-egu23-6208, 2023.

EGU23-8355 | ECS | Posters on site | GI6.7

Callio Lab – a GoldenEye field trial site at the Pyhäsalmi mine in Finland 

Julia Puputti, Marko Holma, Ossi Kotavaara, Jari Joutsenvaara, and Marton Magyar

Callio Lab is a multidisciplinary research centre operating at the Pyhäsalmi mine in Finland and it is coordinated by the Kerttu Saalasti Institute of the University of Oulu.  The Callio Lab team is responsible for hosting, facilitating, and supporting field trials conducted at the Pyhäsalmi site during the EU funded H2020 project GoldenEye. They are also involved in evaluating the piloted techniques, which includes providing ground truths and other comparative data that can be used for validation. The field trials include pilots such as monitoring the stability of tailing ponds and the deployment of an underground simulated GNSS system. 

The Pyhäsalmi mine is a prime location for testing remote sensing and positioning technologies in a real-world mining setting, as the environment encompasses many key elements that can be found in mines around the world: active and closed open pits of various steepness, ore and waste rock piles, tailing ponds in various states of use, and a multifaceted landscape. Callio Lab and its predecessor CUPP (the Centre for Underground Physics in Pyhäsalmi) have a long-standing history of cooperation with the mining company, which affords easy access to the area and the possibility of using historical datasets spanning decades. We will be presenting how the Callio Lab environment at the Pyhäsalmi mine can serve as a field trial site in projects such as GoldenEye.  

This work has been supported by the project Earth observation and Earth GNSS data acquisition and processing platform for safe, sustainable and cost-efficient mining operations (Goldeneye) ID: 869398, Horizon 2020.

How to cite: Puputti, J., Holma, M., Kotavaara, O., Joutsenvaara, J., and Magyar, M.: Callio Lab – a GoldenEye field trial site at the Pyhäsalmi mine in Finland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8355, https://doi.org/10.5194/egusphere-egu23-8355, 2023.

Interferometric Synthetic Aperture Radar (InSAR) has been applied using SAR images from the European Space Agency (ESA) Sentinel-1 constellation, in descending orbit, to obtain the terrain displacement by means of the Coherent Pixel Technique (CPT). This Persistent Scatter Interferometry (PSI) technique was developed in 2002 by the Remote Sensing Laboratory (RSLab) of the Universitat Politècnica de Catalunya, UPC (Lanari et al., 2004; Mora et al. 2002), and recently updated by the Dares Technology team.

ESA Sentinel-1 satellite constellation images were used with Single Look Complex (SLC) images and Interferometric Wide Swath (IW) acquisition mode to detect terrain displacements at Vlaykov Vruh and Tsar Assen porphyry-copper deposits (PCD) in the southern part of Panagyurishte ore district in Bulgaria.

The detected displacement magnitude in Vlaykov Vruh was from 500 to 4,000 m2 while for Tsar Assen PCD it ranges from 500 to 2,500 m2 where several spots of displacement were detected.

We conclude that in the waste pile area east of the Vlaykov Vruh slope instabilities occurred with a displacement of 3.5 cm. Due to a landslide along the fault structure, a slope displacement of about 4.0 cm for Tsar Assen PCD was detected.

The study is supported by the Horizon 2020 co-funded GOLDENEYE project, which has received funds through Grant Agreement 869398.

 

References:

Lanari, R.; Mora, O.; Manunta, M.; Mallorqui, J.J.; Berardino, P.; Sansosti, E. 2004. A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms.’ IEEE Trans. Geosci. Remote Sens., 42, 1377–1386.

Mora, O.; Mallorqui, J.J.; Duro, J. 2002.Generation of deformation maps at low resolution using differential interferometric SAR data.’ Proceedings of 2002 IEEE International Geoscience and Remote Sensing Symposium, IGARSS ’02, Toronto, ON, Canada.

 

How to cite: Domenech, G., Bogdanov, K., Nieto-Yll, D., and Faridi, A.: Interferometric Synthetic Aperture Radar (InSAR) mapping in Vlaykov Vruh and Tsar Assen Cu-porphyry deposits, Panagyurishte ore region, Bulgaria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8364, https://doi.org/10.5194/egusphere-egu23-8364, 2023.

To accomplish strategic objectives on zero-pollution, the entire mining life cycle (exploration, extraction, closure, mine- site rehabilitation) needs to develop minimal impact exploration and monitoring technologies and applications which are open to the broadest groups of stakeholders. In this respect Earth Observation (EO), Drone & Proximal Sensing and relevant in-situ data bring significant contribution for both, sustainable management of mineral resources and efficient multi-scale monitoring of mining impacts. In this sense, the purpose of the GEOMIN activity, part of the Group on Earth Observations (GEO) Work Programme [1] [2], is to increase awareness and use of state-of-the-art EO data and methods which represent a novel means for sustainable monitoring and management of mineral resources and efficient multi-scale monitoring mining impacts. 

How is GoldenEye project through AI-driven tools and applications enhances the GEOMIN community?

In the scope of the GoldenEye project, OPT/NET delivered the next generation of AI exploitation system: a hybrid platform which combines the processing & automation capabilities of AI with the natural problem-solving abilities of humans. We have developed dedicated applications with our novel approach based on the Artificial Intelligence Knowledge Packs (AI KPs), integrated in GOLDENAI Engine, to rapidly interpret the geographical patterns and environmental impacts caused by the mining activity.

What is the role of the GEO Knowledge Hub (GKH) as the Digital portal in promoting the replicability and re-usability of AI KP in the mining sector and how it relates to Goldeneye ?

The GEO Knowledge Hub (GKH) is a central cloud-based digital library providing access to Earth Observations applications developed by GEO. The GEO Knowledge Hub is part of the GEOSS Infrastructure and helps the  GEO to advance Open Knowledge. The scope of the GKH is to promote the replicability and re-usability of EO Applications by sharing with the end users, all the Knowledge Resources essential to fully understand and re-use them. All the Knowledge Resources are directly shared, curated and organized by the Knowledge Provider to ensure replicability with proper documentation.

Therefore, several Knowledge Packages (KPs) related to the technological solutions of the GoldenEye project can be found in the GKH. In this paper, the KP related to the GOLDENAI platform will be presented, including the description of the integrated AIKPs, such as:

  • AI KP for mineral mapping - Band-ratios based on WorldView-3 
  • AI KP for mineral mapping - SPCA based on WorldView-3
  • AI KP for UML clustering based on Copernicus Satellite imagery (Sentinel-1 SLC)

The paper has been prepared in the frame of the Horizon 2020 co-funded project GOLDENEYE, which has received funds through the GA 869398.

 

References:

[1] GEO (2023a). GEO Work Programme 2023-2025. Access 09 Jan. 2023. url:

 https://earthobservations.org/geo_wp_23_25.php 

[2] GEO (2023b). GEO WEEK 2022. Access 09 Jan. 2023. url: https://earthobservations.org 

How to cite: Gutierres, F., Matselyukh, T., Paavola, M., Franziskakis, F., De Salvo, P., and Carlos, F.: Discover the new approach to applications development with ‘Artificial Intelligence Knowledge Packs (AI KPs)’ in the GEO Knowledge Hub: Towards the Open and Reproducible Knowledge application for mine site monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9595, https://doi.org/10.5194/egusphere-egu23-9595, 2023.

EGU23-11469 | Orals | GI6.7

Drone-based electromagnetic survey system for environmental applications 

Markku Pirttijärvi and Pekka Korkeakangas

During the last few years, the number of applications utilizing unoccupied aerial vehicles (UAVs), or drones, has increased rapidly in geophysics. The main benefits of airborne surveys are the ability to avoid terrain obstacles such as lakes, rivers, swamps, and ravines and the ability to collect evenly sampled data over large areas quickly. Drone surveys are safer and more cost-effective than ground surveys, especially in rough terrain. Compared to manned aircrafts, drones are cheaper to acquire and to operate. Drones are also versatile, fast to deploy, and ecologically more friendly.

Presently, drones are commonly used for magnetic surveying, and in addition to normal photogrammetry, drones are also used for multispectral and thermal imaging. Electromagnetic (EM), radiometric and gravity applications have been scarce, because the instruments are heavy compared to the modest payload of reasonable priced drones. Special adaptation or completely new instrumentation is needed to enable more drone applications.

Radai is a private Finnish company specialized in drone-based geophysical and environmental surveys. For the last five years Radai have been developing Louhi – a frequency-domain electro­magnetic (EM) system that is lightweight enough to be operated by drones. Presently, Louhi is operated using a large (Ø 100 m) ground loop as the EM source and a standalone 3-component EM receiver is towed by a VTOL (vertical take-off and landing) drone. Radai also develops a fully airborne system where a smaller transmitter loop (Ø 1 m) is fixed to the drone and receiver is towed either by the same drone or by a second drone that flies in tandem with the first one. The applications of the new EM system include geological mapping, mineral exploration, groundwater and geotechnical investigations and environmental monitoring. This paper gives details of the drone-based Louhi EM system and shows results from the first environmental survey made over a tailings pond dam of closed Pyhäsalmi Zn-Cu mine in Finland. The work is made as a part of EU Horizon 2020 funded Goldeneye project.

How to cite: Pirttijärvi, M. and Korkeakangas, P.: Drone-based electromagnetic survey system for environmental applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11469, https://doi.org/10.5194/egusphere-egu23-11469, 2023.

EGU23-11816 | ECS | Orals | GI6.7

Piloting Simulated GNSS in Underground Spaces 

Marton Magyar, Julia Puputti, Ossi Kotavaara, Jari Joutsenvaara, Eli Ariel, and Tuomas Koivurova

Global navigation satellite systems (GNSS)-based navigation services are widely used above ground in open-pit mining operations for safety management, process optimalization and fleet management. Extending these location-based services (LBS) to underground operations may increase efficiency and safety in mining, underground research and development, as well as, in mine reuse projects. Numerous different methods and technologies have been proposed and utilized for positioning and navigation in indoor areas and underground tunnels. Depending on the detection technology, there have been four main categories of LBS with varying levels of complexity and accuracy: 1) inertial navigation systems, 2) radio frequency (RF) based positioning, 3) multi-sensor (hybrid) navigation and 4) pseudolite-based positioning. The main motivation for deploying GNSS technology in underground conditions is to utilize the already existing, robust infrastructure, with simple off-the-shelf receiver devices. The tested system has high potential to enable high accuracy positioning in traditional GNSS-denied areas. 

The simulated underground GNSS approach is tested in a 400-meter-deep tunnel section in the Pyhäsalmi mine located in Northern Finland. At the test site, 17 signal emulators have been installed in a 200-meter-long mine tunnel to provide GNSS access. The goal is to test the simulated underground GNSS and its ability to support a wide range of common above-ground GNSS end-user devices and services. These may include applications for worker safety, mine environment monitoring and operational efficiency. The accuracy, reliability and coverage of the tested system will affect its usability significantly. In this paper, we measure positioning accuracy in different underground conditions and environments, assess applicability of a hybrid positioning approach using WLAN supported services, and test functionality of the system with common GNSS devices. The collected positioning data is analyzed with spatial analyses and statistics in geographic information systems. Results of the study will indicate how GNSS emulation techniques could be adopted to deep underground spaces and what are the possible development needs of the technology. 

This project received funding from the European Union's Horizon 2020 innovation programme under grant agreement number: 839398.

How to cite: Magyar, M., Puputti, J., Kotavaara, O., Joutsenvaara, J., Ariel, E., and Koivurova, T.: Piloting Simulated GNSS in Underground Spaces, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11816, https://doi.org/10.5194/egusphere-egu23-11816, 2023.

The Goldeneye project has implemented a unique combination of remote sensing and positioning technologies, exploiting Earth observation and Earth GNSS data, together with data fusion and processing powered by data analytics and machine-learning algorithms. The platform allows satellites, drones and in-situ sensors to collect high-resolution data, which can be processed and converted into actionable intelligence for safety, environmental monitoring and overall productivity, allowing more efficient exploration, extraction and closure. These tools have been demonstrated in 5 field trials in Germany, Bulgaria, Romania, Kosovo and Finland, and the initial results show significant time and cost savings, even up to 80%, for example, in exploration and mine safety, environmental and operations reporting. The project has a duration of 3,5 years and an EC funding of €8.36M. The multidisciplinary consortium includes industrial partners, SMEs, academic/research centres and end-users.

The project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No [869398].

How to cite: Paavola, M.: Goldeneye –a multisource AI-enabled earth observation platform for mining applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17075, https://doi.org/10.5194/egusphere-egu23-17075, 2023.

EGU23-185 | Orals | GI6.8

Space weather during extreme SEPs: new assessment of worst case scenario 

Alexander Mishev, Sanja Panovska, and Ilya Usoskin

An important topic in the field of space physics is the quantification of the cosmic-ray-induced effects in the atmosphere and the corresponding space weather effects. Space weather effects, specifically the exposure to radiation at aviation altitudes, represent an important threat. Here, we focus on a specific class of events due to solar energetic particles (SEPs), viz. events that can be registered at ground level: ground-level enhancements and more particularly extreme events with cosmogenic imprints,i.e. that have been registered by 14C records.

Naturally, for assessment of space weather effects during extreme SEP events, it is necessary to possess precise information on their spectra. Here we present results and application of an analysis of SEPs using neutron monitor (NM) records, that is derivation of their spectra, and application of numerical models. Using reconstructed spectra during the strongest directly recorded event, that is GLE # 5, occurred on 23 February 1956, and employing a convenient rescaling,  we assessed the space weather effect during the strongest indirectly reconstructed historical extreme SEP event, that is, 774 AD. Subseqeuntly, employing a state-of-the-art reconstruction of the magnetic field we study the worst-case scenario representing a combination of a geomagnetic excursion, that is the Laschamp excursion ca. 42 kyr ago and a 774 AD-like event. The possible implications are discussed.

How to cite: Mishev, A., Panovska, S., and Usoskin, I.: Space weather during extreme SEPs: new assessment of worst case scenario, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-185, https://doi.org/10.5194/egusphere-egu23-185, 2023.

EGU23-287 | ECS | Orals | GI6.8

A New Open-Source Geomagnetosphere Propagation Tool (OTSO) and its Applications 

Nicholas Larsen, Alexander Mishev, and Ilya Usoskin

We present a new open-source tool for magnetospheric computations, that is modelling of cosmic ray propagation in the geomagnetosphere, named "Oulu - Open-source geomagneToSphere prOpagation tool" (OTSO). A tool of this nature is required to interpret experiments and study phenomena within the cosmic ray research field.  Here, we demonstrate several applications of OTSO, namely the computation of asymptotic directions of selected cosmic ray stations, effective rigidity cut-off across the globe at various conditions within the design, and general properties, including the magnetospheric models employed. OTSO was applied to the investigation of several ground-level enhancement events after which comparison and validation of OTSO with older widely used tools such as MAGNETOCOSMICS was performed, and good agreement was achieved. The necessary background for the analysis of two notable ground-level enhancements was produced using OTSO and their spectral and angular characteristics show good agreement with prior studies and spacecraft data. This validation of OTSO's current abilities reveals its usefulness to the cosmic ray research field and its open-source nature further allows for the tool to be developed beyond its current capabilities by users to meet the needs of the research community.

How to cite: Larsen, N., Mishev, A., and Usoskin, I.: A New Open-Source Geomagnetosphere Propagation Tool (OTSO) and its Applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-287, https://doi.org/10.5194/egusphere-egu23-287, 2023.

EGU23-3095 | Posters on site | GI6.8

Effects of heterogeneous soil moisture distributions in cosmic-ray neutron sensing - the case of irrigation monitoring 

Heye Bogena, Cosimo Brogi, Markus Köhli, Harrie-Jan Hendricks Franssen, Olga Dombrowski, and Johan Alexander Huisman

Soil moisture (SM) sensors are widely used to monitor soil water dynamics and support irrigation management with the aim of achieving better yields while reducing water consumption. Unfortunately, due to the small measuring volume of point-scale sensors, their soil moisture readings are often not representative for heterogeneous agricultural fields. Therefore, in such cases, sensors with larger sensing volume are needed to address spatially variable SM. A suitable technique is the cosmic ray neutron sensor (CRNS) as it integrates SM over a large volume with a radius of ~130-210 m and a penetration depth of ~15-85 cm. The CRNS method is based on the inverse relationship between measured environmental neutron density and the presence of hydrogen pools (e.g., SM) in the instrument surroundings. However, the ability of CRNS to accurately monitor areas with complex SM heterogeneities (e.g., small irrigated fields) and the influence of detector design were not yet investigated. In this study, we used the neutron transport model URANOS to simulate the effect of SM variations on a CRNS placed in the centre of squared irrigated fields (0.5 to 8 ha dimensions). For this, SM in the irrigated field and in the surrounding was altered between 0.05 and 0.50 cm3 cm-3 (500 simulations in total). In addition, we investigated the effect of employing high-density polyethylene (HDPE) moderators with different thickness (5 to 35 mm) as well as a 25 mm HDPE moderator with an additional gadolinium oxide thermal shielding. Results showed that, in heterogeneous SM scenarios, the 2 e-folding lengths footprint (R86) can become smaller or larger than what previous studies showed in homogeneous SM distributions. In addition, a thin HDPE moderator will result in relatively smaller R86 whereas thicker moderators and the addition of a thermal shielding will result in relatively larger R86. However, we found that a relatively small footprint is not directly related to a better monitoring of SM nearby the instrument. In fact, in all the investigated field dimensions, the 25mm HDPE moderator with gadolinium shielding showed the largest values of R86 but also the largest variations of detected neutrons with changing SM. In addition, such moderator showed the highest chances of detecting irrigation events that increase SM by 0.05 or 0.10 cm3 cm-3 in the irrigated area. Generally, detection was uncertain only for SM variations of 0.05 cm3 cm-3 in fields of 0.5 ha when initial SM was 0.02 cm3 cm-3 or higher. Although the results of this study suggest the feasibility of monitoring and informing irrigation with CRNS, we found that SM variations outside the irrigated field have a considerable influence on CRNS measurements. Especially in fields of 0.5 and 1 ha dimension, it can be impossible to distinguish whether a relative change in detected neutrons is due to irrigation or to SM variations in the surroundings. These results are relevant for irrigation monitoring and the combination of neutron transport simulations and real-world installations has the potential to establish CRNS as a decision support system for irrigation management.

How to cite: Bogena, H., Brogi, C., Köhli, M., Hendricks Franssen, H.-J., Dombrowski, O., and Huisman, J. A.: Effects of heterogeneous soil moisture distributions in cosmic-ray neutron sensing - the case of irrigation monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3095, https://doi.org/10.5194/egusphere-egu23-3095, 2023.

EGU23-4506 | Orals | GI6.8

ORCA (Observatorio de Rayos Cósmicos Antártico), current status and future perspectives 

Juan José Blanco, Juan Ignacio García Tejedor, Sindulfo Ayuso de Gregorio, Óscar García Población, Alejandro López-Comazzi, Diego Sanz Martín, Ivan Vrublevskyy, Laura Gonzalvo Ballano, and Alberto Regadío

ORCA (2.37 GV) is a suit of two neutron monitors and a muon telescope. It was installed at Juan Carlos I Antarctic Base on January 2019 being in operation since. Because the low level of the solar activity, only a few of solar events have been detected. The GLE 73 and three Forbush decreases. A new ORCA like detector (ICaRO, 11.5 GV) is being installed at 2200 m a.s.l in Izaña Atmospheric Observatory (Tenerife Island, Spain). On the other hand, CaLMa neutron monitor (6.95 GV) will be updated with a muon telescope made by eight 1 m2 scintillators arranged in two layers of four scintillators at some point during the next two years. These three detector will measure muons and neutrons from cosmic ray interaction with atmosphere at three different locations allowing to study the solar activity from a new perspective

How to cite: Blanco, J. J., García Tejedor, J. I., Ayuso de Gregorio, S., García Población, Ó., López-Comazzi, A., Sanz Martín, D., Vrublevskyy, I., Gonzalvo Ballano, L., and Regadío, A.: ORCA (Observatorio de Rayos Cósmicos Antártico), current status and future perspectives, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4506, https://doi.org/10.5194/egusphere-egu23-4506, 2023.

EGU23-6045 | Posters on site | GI6.8

The concentration of cosmogenic radionuclide 7Be from the perspective of space weather and long-term trends in the stratospheric temperature and wind 

Kateřina Podolská, Michal Kozubek, Miroslav Hýža, and Tereza Šindelářová

Cosmogenic radionuclide Beryllium 7Be concentration is primarily determined by the solar activity level and space weather conditions. The 7Be is generated by cosmic ray reactions in the stratosphere and in the upper troposphere, binds to atmospheric aerosols and is transported horizontally and vertically by wind and gravity. The highest values of cosmic radiation are observed during the solar minima because, at that time the penetrability of the Earth’s and Sun magnetosphere is greatest.

The concentrations of the radionuclide 7Be are reliable indicators of various atmospheric processes. In our work, we try to contribute to better understanding of the dynamics of processes by associating them with long-term trends of stratospheric temperature dynamics. We investigate the coupling of concentrations of the cosmogenic radionuclide 7Be in the longitudinal view during the years 1986–2022 (time series of activity concentration of 7Be in aerosols evaluated by the corresponding activity in aerosols on a weekly basis at the National Radiation Protection Institute Monitoring Section in Prague) to space weather parameters (Kp planetary index, disturbance storm time Dst, proton density, proton flux), and stratospheric dynamics parameters (temperature, zonal component of wind, O3). On short timescales the intensity of cosmic radiation decreases by few percent in several days. On a longer timescale the intensity of galactic cosmic rays is strongly influenced by the degree of solar activity and by variations in the geomagnetic field. This corresponds with findings that the zonal wind climatology differences were largest in the decades of 2000–2010 than between others observed decades.

How to cite: Podolská, K., Kozubek, M., Hýža, M., and Šindelářová, T.: The concentration of cosmogenic radionuclide 7Be from the perspective of space weather and long-term trends in the stratospheric temperature and wind, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6045, https://doi.org/10.5194/egusphere-egu23-6045, 2023.

EGU23-6789 | Posters on site | GI6.8

Sensitivity of the Cosmic Ray Neutron Sensor (CRNS) to Seasonal Biomass Dynamics in Cherry and Olive Orchards 

Samir K. Al-Mashharawi, Marcel M. El Hajj, Kasper Johansen, Matthew F. McCabe, and Susan Steele-Dunne

Biomass estimation is important in many applications, such as carbon sequestration and precision agriculture. Developing a reliable method for biomass estimation from satellite, airborne and near-surface remote sensing sensors is an ongoing task due to the large uncertainty in current methods, which are often related to sensor limitations. Indeed, signals from optical sensors and synthetic aperture radar at high and medium frequencies suffer from saturation issues at high biomass levels. The Cosmic-Ray Neutron Sensor (CRNS) is a new non-invasive near-surface sensor used primarily to estimate soil water content (SWC), but it has also shown potential for retrieving other hydrological and environmental parameters such as biomass water equivalent and snow depth. The CRNS detects and counts the number of neutrons controlled by hydrogen atoms in the soil, air just above the ground, and vegetation. Biomass attenuates the intensity of cosmic ray neutrons, hence the ability to estimate biomass from a CRNS. Recent studies have used CRNS measurements to estimate biomass changes in crop areas and forest stands, while the use of CRNSs in orchards is limited. The objective of this study is to explore the potential of two CRNSs to estimate the biomass variation in irrigated cherry and olive tree orchards. The olive tree orchard is located in an arid region in northern Saudi Arabia (plantation density of 1667 trees/hectare) with an average tree height of 3 m and canopy diameter of 2 m. The cherry field is located in southern France (plantation density of 260 trees/hectare) with an average tree height of 3.5 m and canopy diameter of 5.5 m. Several soil moisture probes recording soil water content (SWC) at 15-min intervals at both sites were installed at different depths within the CRNS footprint. SWC measurements were used to assess the variations in the sensitivity of CRNS to soil moisture with increasing biomass. Tree parameters (height, canopy width, canopy length, leaf area index, and diameter at breast height) were measured in situ to estimate biomass using allometric equations. In addition, repetitive Light Detection and Ranging (LiDAR) scanning was performed over the cherry field to detect canopy volume changes over time. The results showed that the CRNS is sensitive to SWC variation, and this sensitivity is controlled by biomass evolution, indicating that CNRS measurements can also be used to estimate biomass. The sensitivity of CRNS neutron counts to SWC in the early season (before blooming) was twice as high as that during the mid- and late growing seasons (maximum leaf cover). The Cornish Pasdy model­, which models the measured neutron counts as a function of SWC and biomass contribution, was calibrated and then inverted to estimate the biomass in the cherry and olive tree orchards. 

How to cite: Al-Mashharawi, S. K., El Hajj, M. M., Johansen, K., McCabe, M. F., and Steele-Dunne, S.: Sensitivity of the Cosmic Ray Neutron Sensor (CRNS) to Seasonal Biomass Dynamics in Cherry and Olive Orchards, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6789, https://doi.org/10.5194/egusphere-egu23-6789, 2023.

EGU23-11071 | ECS | Posters on site | GI6.8

Updated heliospheric modulation potential of cosmic rays and station-specific scaling factors for 1964-2021 

Pauli Väisänen, Ilya Usoskin, Riikka Kähkönen, Sergey Koldobskiy, and Kalevi Mursula

Galactic cosmic rays (GCR) are energetic particles originating from galactic or extra-galactic sources. When they arrive inside our heliosphere, they are modulated by the magnetic irregularities in the solar wind flow from the Sun, deflecting and slowing down the GCR particles. The level of this modulation varies according to solar activity, especially the 11-year solar cycle. The heliospheric modulation potential, denoted by ϕ, describes the average energy loss of particle in MV and quantifies the level of modulation. It can be determined using ground-based neutron monitor (NM) measurements of GCRs by multiple stations. Here we use the most recent version of the NM yield function and a RMSE-minimization method to compute a new and more accurate version of the modulation potential ϕ and station-specific scaling factors κ, which can be used to scale the level of count rates to the theoretical NM count rate given by the model. The new version offers daily resolution of ϕ and can be conveniently updated with new measurements, stations, or updates to datasets whenever they might occur. The scaling factors and their variation can be used to scale the data for physical analyses or to identify outliers, errors or physical phenomena which do not match with the model.

How to cite: Väisänen, P., Usoskin, I., Kähkönen, R., Koldobskiy, S., and Mursula, K.: Updated heliospheric modulation potential of cosmic rays and station-specific scaling factors for 1964-2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11071, https://doi.org/10.5194/egusphere-egu23-11071, 2023.

EGU23-11326 | ECS | Posters on site | GI6.8

Monitoring soil moisture in the deeper vadose zone: A new approach using groundwater observation wells and cosmic ray neutrons 

Daniel Rasche, Jannis Weimar, Martin Schrön, Markus Köhli, Markus Morgner, Andreas Güntner, and Theresa Blume

Monitoring soil moisture at depths greater than one meter is generally challenging and often highly invasive as it requires opening large soil pits. As a result, this deeper vadose zone is often not monitored at all. On top of that, conventional soil moisture sensors usually have only a small measurement volume. On the other hand, soil moisture estimates derived from above-ground Cosmic-Ray Neutron Sensing (CRNS) are a representative average over an area of several hectares but only of the upper half meter of the soil. To this day, it is commonly believed that cosmic radiation cannot be used to monitor soil water content below this depth. As a consequence, large parts of the root-zone and deeper unsaturated zone have remained outside the observational window of the method. The estimation of soil moisture in greater depths typically requires additional invasive measurements, other active geophysical methods, or mathematical models which extrapolate surface soil moisture observations.

Against this background, we investigated the possibility of using passive detection of cosmogenic neutrons in existing monitoring infrastructure (e.g. groundwater wells). We hypothesized that this method provides a larger measurement volume than traditional techniques based on active neutron probes while requiring less safety restrictions.

Our neutron transport simulations demonstrated that this downhole-CRNS technique would be sensitive enough to detect changes of water content in depths down to 5 meters and above, depending on the temporal resolution of measurements. The simulations also revealed a large measurement radius of several tens of cm depending on the soil moisture content and soil bulk density.

From the theoretical results we derived a functional relationship between soil moisture and detectable neutrons and tested it in a groundwater observation well. Additional installations of supporting soil moisture sensors have been used to validate the model predictions as well as the neutron signals monitored by the CRNS detector. The study demonstrated the general applicability of downhole Cosmic-Ray Neutron Sensing for the estimation of soil moisture in greater depths and at temporal resolution of two days.

How to cite: Rasche, D., Weimar, J., Schrön, M., Köhli, M., Morgner, M., Güntner, A., and Blume, T.: Monitoring soil moisture in the deeper vadose zone: A new approach using groundwater observation wells and cosmic ray neutrons, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11326, https://doi.org/10.5194/egusphere-egu23-11326, 2023.

EGU23-11905 | Posters virtual | GI6.8

SEVAN European particle detector network for the atmospheric, solar and space weather studies 

Tigran Karapetyan, Ashot Chilingarian, and Balabek Sargsyan

Experiments during recent years with SEVAN detectors on mountain tops in Armenia, Slovakia, and Bulgaria reveal the broad potential of SEVAN detectors; The SEVAN detector on Lomnicky Stit (Slovakia) measured the largest thunderstorm ground enhancements (TGE), with particle fluxes exceeding the background 100-times. With muon and gamma ray fluxes, the maximum values of the potential difference in thunderclouds were measured, equal to 350 MV at Mt. Aragats, and 500 MV at the sharp peak of Lomnicky Stit. In Nov 2019, SEVAN detectors were installed at DESY (Hamburg and Zeuthen sites). Fluxes of electrons, photons, and muons and weather parameters are continuously monitored at all sites (at different latitudes, longitudes, and altitudes). To fully exploit the scientific potential of the SEVAN detectors, in 2023 is planned to install a new detector in the Umwelt-Forschungs-Station (UFS, Schneefernerhaus, 2650 m asl) near the top of the Zugspitze (2962 m), a site with a long history of atmospheric research. The new SEVAN module will be compact (SEVAN-light), and will enable the energy spectra measurements in the range from 0.3 to 50 MeV, allowing unambiguously separating Radon progeny gamma radiation from runaway electron-photon avalanches.

How to cite: Karapetyan, T., Chilingarian, A., and Sargsyan, B.: SEVAN European particle detector network for the atmospheric, solar and space weather studies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11905, https://doi.org/10.5194/egusphere-egu23-11905, 2023.

Neutron monitor counting rates show, among others, a  $\sim$ 1.6--2.2-year period. This period has been associated with a solar origin affecting the cosmic ray propagation conditions through the heliosphere. The duration of this period varies from one Solar Cycle to another.
\cite{Comazzi_Blanco_2022} found the duration of the $\sim$ 1.6--2.2-year period ($\tau$) is linearly related to the averaged sunspot number ($SSN_a$) in each Solar Cycle.
In this piece of research, we have analyzed this relationship. This equation shows that shorter $\sim$1.6--2.2-year periods occur during stronger cycles when $SSN_a$ is higher. Drawing on this relationship given by $SSN_a = (-130 \pm 10) \: \tau + (330 \pm 30)$, we computed $\tau$ for the cycles previous to the existence of neutron monitors (Solar Cycles 7--19). 
By means of the Huancayo neutron monitor spectrum we checked the validity of this equation along the Solar Cycle 19. 
Once the previous relationship is checked, $\tau$ for the current Solar Cycle 25 is computed giving $\sim$ 2.22 years.

An internal mechanism of the solar dynamo called Rossby waves could produce these variations in the solar magnetic field  and, indirectly, in neutron monitor counting rates.
The harmonic of fast Rossby waves with $m=1$ and $n=8$ fit with the detected periodicity and the variation of the solar magnetic field strength from weaker to stronger Solar Cycles could explain the different periods detected in each cycle.
Finally, a solar magnetic field strength of $\sim$ 7--25 kG in the tachocline have been estimated based on the detected periodicities using the dispersion relation for fast Rossby waves. 

How to cite: López-Comazzi, A. and Blanco-Ávalos, J. J.: Study of the relationship between Sunspot number and the duration of the $\sim$1.6--2.2-year period in neutron monitor counting rates, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11981, https://doi.org/10.5194/egusphere-egu23-11981, 2023.

EGU23-12576 | ECS | Posters on site | GI6.8

Cosmic rays on snow: A combined analysis of fractional snow cover derived from Sentinel-2, MODIS and Cosmic Ray Neutron Sensors across Europe 

Nora Krebs, Paul Schattan, Sascha Oswald, Martin Schrön, Martin Rutzinger, and Johann Stötter

Epithermal neutrons from cosmic ray showers are slowed by hydrogen atoms in snow. The drop in the fast neutron abundance in the atmosphere can be measured with above-ground Cosmic Ray Neutron Sensing (CRNS), allowing for an estimation of the Snow Water Equivalent (SWE). SWE is an important variable that has a substantial role in hydrological modelling and forecasts. However, up to now, SWE is conventionally measured at point-scale, which holds only little information about the average SWE in areas of heterogeneous terrain and where snow drift is a predominant process. CRNS offers the prospect of closing this gap by sensing neutrons within a footprint of 10–20 hectares. Currently, further investigations are needed to reduce the uncertainties in the signal conversion from neutron counts to SWE. In this study, we compare the daily signals of 65 CRNS stations across Europe with the corresponding Fractional Snow Cover (FSC) products from Sentinel-2 and MODIS (Moderate-resolution Imaging Spectroradiometer) with a 20 m and 500 m spatial resolution, respectively. By analysing the FSC products, we were able to identify characteristic ranges of neutron counts at snow presence (winter signals) and absence (summer signals). Comparing these ranges and their overlap among stations, we were able to distinguish typical signal properties of lowland, pre-Alpine and Alpine sites. We found that altitude-related properties, such as soil and vegetation characteristics govern the general neutron level at the study sites. Snowfall typically leads to a major drop in the neutron count rate that is superimposed on the summer neutron count level. High-altitude stations are generally characterized by low ranges of count rates in summer and by high ranges in winter, while low-altitude stations show a reversed trend. Our results demonstrate that the suitability of a station for SWE measurements with CRNS depends highly on the site-specific hydrogen pool fluctuations that can be linked to altitude. Especially in heterogeneous mountain terrain with low soil formation, the advantages of CRNS come into play and can provide a spatial average of SWE with low uncertainties.

How to cite: Krebs, N., Schattan, P., Oswald, S., Schrön, M., Rutzinger, M., and Stötter, J.: Cosmic rays on snow: A combined analysis of fractional snow cover derived from Sentinel-2, MODIS and Cosmic Ray Neutron Sensors across Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12576, https://doi.org/10.5194/egusphere-egu23-12576, 2023.

EGU23-15343 | Posters on site | GI6.8

Measurements of cosmic rays by a mini neutron monitor aboard the German research vessel Polarstern 

Bernd Heber, Sönke Burmeister, Hanna Giese, Konstantin Herbst, Lisa Romaneehsen, Carolin Schwerdt, Du Toit Strauss, and Michael Walter

Neutron monitors are ground-based devices that measure the secondary particle population, i.e., neutrons produced by, e.g., galactic cosmic rays (GCRs). Due to their functionality, they are integral counters whose flux is proportional to the variation of the input spectrum. However, the measured flux also depends on the geomagnetic position and the static pressure at the monitor's location. To better understand the instrument response, the Christian-Albrechts-Universität zu Kiel, DESY Zeuthen, and the North-West University in Potchefstroom, South Africa, agreed on regular monitoring of the GCR intensity as a function of latitude, by installing a portable device aboard the German research vessel Polarstern in 2012. The vessel is ideally suited for this research campaign because it covers extensive geomagnetic latitudes (i.e., goes from the Arctic to the Antarctic) at least once per year. Since the installation aboard the vessel, 12 latitude scans were performed, allowing us to compute the so-called yield function by experimental means presented in this contribution.

The Kiel team received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 870405. The team would like to thank the crew of the Polarstern and the AWI for supporting our research campaign.

How to cite: Heber, B., Burmeister, S., Giese, H., Herbst, K., Romaneehsen, L., Schwerdt, C., Strauss, D. T., and Walter, M.: Measurements of cosmic rays by a mini neutron monitor aboard the German research vessel Polarstern, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15343, https://doi.org/10.5194/egusphere-egu23-15343, 2023.

EGU23-15523 | Posters on site | GI6.8

Buoy-based detection of low-energy cosmic-ray neutrons to monitor the influence of atmospheric effects 

Martin Schrön, Daniel Rasche, Jannis Weimar, Markus Köhli, Bertram Boehrer, Peter Dietrich, and Steffen Zacharias

Neutron monitors on the Earth’s surface are usually used to observe the dynamics of highly energetic cosmic-ray particles, assuming that local environmental conditions do not influence the measurement. In another young research field, low-energy cosmic-ray neutrons are used to monitor local dynamics of environmental water content. Water in soil, air, snow and vegetation determines the amount of ground albedo neutrons in the sensitive energy range from 1 eV to 100 keV. Plenty of small neutron detectors are operated on natural or agricultural sites all around the world. 

A major issue is the modulation of the neutron flux by the dynamics of incoming high-energy cosmogenic particles. Conventionally, independent data from neutron monitors are consulted to serve as a reference for the correction of the local detectors. However, the performance of this comparative correction approach is unreliable, because it does not account for geographical displacement, different energy windows of the detectors, or potential influence of atmospheric conditions on the referenced neutron monitor.

To test the traditional correction approaches for incoming cosmic radiation, air pressure, and air humidity, an experimental setup should avoid any influence of changes due to soil moisture. Therefore, a set of neutron detectors have been deployed in a buoy at the center of a lake for six months. The measurement period also included a Forbush Decrease in September, 2014. 

We found that the neutron signals correlated with air pressure, air humidity, and secondary cosmic radiation. The thermal neutron response to air humidity has been revealed to be different from the epithermal neutron response, while air pressure and incoming radiation similarly   influenced the thermal and epithermal signals. The results have been used to evaluate different existing strategies for air humidity correction of low-energy neutron data. Additionally, the potential effect of lake temperature on the thermal neutron count rate has been investigated. We have also analyzed the performance of the buoy  signal together with different neutron monitors in their capability to correct for the changes of incoming radiation and for the Forbush Decrease during the measurement period.

Overall, the study demonstrates how low-energy neutron detectors on a buoy  could be used to assess the influence of atmospheric and cosmogenic factors on the signal without the influence of soils. Despite the low count rate over water, the general principle could also serve as an alternative to remote neutron monitors as a more local reference signal at more comparable energies.

How to cite: Schrön, M., Rasche, D., Weimar, J., Köhli, M., Boehrer, B., Dietrich, P., and Zacharias, S.: Buoy-based detection of low-energy cosmic-ray neutrons to monitor the influence of atmospheric effects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15523, https://doi.org/10.5194/egusphere-egu23-15523, 2023.

EGU23-15741 | ECS | Orals | GI6.8

Rigidity dependence of cosmic ray diurnal anisotropy using 22 years of GRAPES-3 muon telescope data 

Meeran Zuberi and the The GRAPES-3 Collaboration

The GRAPES-3 muon telescope (G3MT) has been recording high statistics of muons at a rate of ~50000 per second for the past two decades allowing us to probe the tiny variations in the muon flux caused by solar phenomena. The directional capabilities of G3MT enable us to look into 169 independent directions with a large median rigidity ranging from 64 to 141 GV. We have examined the 22 years (2000-2021) of G3MT data using the Fourier series technique to obtain the daily SDA amplitude and phase. The measured SDA amplitude and phase show a strong rigidity dependence. We found that the phase dominantly has the 22-year variation controlled by the drift effect due to solar polar magnetic field reversal, regardless of their rigidity. However, the higher rigidity bin phase variation shows an additional component of the 11 years controlled by the diffusion. The details of this work will be discussed during the talk.

How to cite: Zuberi, M. and the The GRAPES-3 Collaboration: Rigidity dependence of cosmic ray diurnal anisotropy using 22 years of GRAPES-3 muon telescope data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15741, https://doi.org/10.5194/egusphere-egu23-15741, 2023.

EGU23-15980 | ECS | Orals | GI6.8

Yield function of the DOSimetry TELescope (DOSTEL) count and dose rates aboard an aircraft 

Lisa Romaneehsen, Sönke Burmeister, Hanna Giese, Bernd Heber, and Konstantin Herbst

The Earth is continuously exposed to galactic cosmic rays. The magnetized solar wind in the heliosphere and the Earth's magnetic field alters the flux of these particles. If cosmic rays hit the atmosphere, they can form secondary particles. The total flux measured within the atmosphere depends on the atmospheric density above the observer. Therefore, the ability of a particle to approach an aircraft depends on its energy, the altitude, and the position of the plane. The cutoff rigidity describes the latter.
The radiation detector of the detector system NAVIDOS (NAVIgation DOSimetry) is the DOSimetry Telescope (DOSTEL), measuring the count and dose rates in two semiconductor detectors. From 2008 to 2011, two instruments were installed in two aircraft. First, we corrected the data for pressure variation by normalizing them to one flight level and determined their dependence on the cutoff rigidity by fitting a Dorman function to the observation. The latter was used to compute the yield function, which describes the ratio of incoming primary cosmic rays, approximated by a force field solution, to the measured count and dose rate for a particular instrument. As for neutron monitors, the sensitivity increases substantially above a rigidity of about 1 GV.
We received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 870405. 

How to cite: Romaneehsen, L., Burmeister, S., Giese, H., Heber, B., and Herbst, K.: Yield function of the DOSimetry TELescope (DOSTEL) count and dose rates aboard an aircraft, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15980, https://doi.org/10.5194/egusphere-egu23-15980, 2023.

EGU23-16004 | ECS | Posters on site | GI6.8

Impact and relevance of soil density changes on cosmic-ray neutron sensing for soil water estimation 

Katya Dimitrova Petrova, Lena Scheiffele, Lucile Verrot, Martin Schrön, and Josie Geris

Cosmic ray neutron sensor (CRNS) technology is becoming increasingly popular for monitoring volumetric soil water content (SWC) at the field (hectare) scale in a variety of environments. Applications include permanently installed (stationary) or the use of mobile (rover, trains, etc.) platforms. In agricultural settings, permanently installed CRNS have proven particularly useful for providing time series of footprint average SWC estimates. To derive the SWC product at a site, CRNS needs to be calibrated using gravimetric SWC, soil organic matter and bulk density (BD). Those variables may in the best case be derived from a large number of soil samples, collected ideally on multiple occasions and under a range of hydrometeorological conditions. Most CRNS applications use an average site-specific value of bulk density derived for a site from ≥1 field calibration and it is considered static over time.

However, while this is a safe assumption for many environments, in agricultural settings, management activities (e.g. tillage) may introduce substantial changes in BD over time. This may affect the accuracy of the CRNS SWC estimates, which in turn could affect management decisions (e.g. on irrigation) or modelling efforts, relying on these SWC inputs.

The importance of BD as a source of uncertainty in CRNS SWC estimation has been recognized with dedicated laboratory and neutron simulation experiments quantifying the effects. However, field-based studies are lacking. Therefore, the objective of this work is to quantify the impact and relevance of temporal variability in soil bulk density on the estimation of CRNS SWC in a variety of environments with different level of agricultural land use management. We used data from three sites (Scotland, Germany and China) with stationary CRNS, where BD was sampled on ≥3 or more occasions for sensor calibration. The sites display a varying intensity of land use management, cover different soil types and contrasting weather conditions. We quantify the differences in estimates of SWC by using the range of average BD values at a site and compare these differences to other sources of uncertainty (e.g. the integration time of neutron counts). We additionally consider existing theories on the interaction of neutrons and soil bulk density to evaluate the impact of BD changes. Finally, we make recommendations on when BD variability and thus its sampling over time may become important for the derivation of CRNS SWC outputs.

How to cite: Dimitrova Petrova, K., Scheiffele, L., Verrot, L., Schrön, M., and Geris, J.: Impact and relevance of soil density changes on cosmic-ray neutron sensing for soil water estimation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16004, https://doi.org/10.5194/egusphere-egu23-16004, 2023.

EGU23-17336 | ECS | Orals | GI6.8

Cosmic Ray Soil Moisture Sensors as an Asset to Space Weather Monitoring Activities 

Fraser Baird and Keith Ryden

Cosmic Ray Sensors (CRS) are used worldwide to measure soil moisture at intermediate scales, exploiting the neutrons produced in the air showers created by cosmic ray particles interacting with the atmosphere. Neutron Monitors also exploit these atmospheric neutrons, but they are shielded from local soil moisture variations so that information about the cosmic ray flux near Earth can be deduced from their observations. Neutron monitors remain the state of the art for observing variations in high-energy cosmic rays and are critically important to understanding ground-level enhancements of atmospheric radiation caused by high energy solar energetic particles.

This contribution explores how the UK CRS network (COSMOS-UK) can complement the neutron monitor network in monitoring these ground-level enhancements, as well as other space weather-driven variations in the ground-level neutron flux. Observations of such variations using COSMOS-UK are presented and discussed, and the sensitivity of COSMOS-UK to ground-level enhancements is also shown. Finally, the prospects and challenges of improving the space weather utility of CRS networks are discussed.

How to cite: Baird, F. and Ryden, K.: Cosmic Ray Soil Moisture Sensors as an Asset to Space Weather Monitoring Activities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17336, https://doi.org/10.5194/egusphere-egu23-17336, 2023.

EGU23-17421 | Orals | GI6.8

Cosmic ray muons as a proxy for in-cruise galactic cosmic ray protons in 3He gas proportional counters 

Jack T. Wilson, Patrick N. Peplowski, Zachary W. Yokley, David J. Lawrence, and Richard C. Elphic

3He gas proportional counters have an extensive history in planetary neutron spectroscopy and several upcoming missions including Psyche, VIPER, MMX and Dragonfly will include this technology. In space, Galactic Cosmic Ray (GCR) protons deposit energy in the 3He gas in these detectors via ionization. This energy deposition constitutes a background on top of the neutron capture pulse-height spectrum that is particularly prominent at low energies. As planetary nuclear spectroscopy experiments are often count-rate limited using the full pulse height spectrum, including the proton and triton wall effect regions, has significant value. This will be particularly true for the upcoming VIPER mission that will explore the permanently shaded regions at the Moon’s south pole using the Neutron Spectrometer System (NSS).  The NSS does not include a neutron generator, so the count rates are low, and the rover will not spend long at any location.  However, using lower-energy parts of the spectrum requires understanding the GCR-originating background, which none of the previous missions were able to measure due to their low-energy cutoffs. GCR protons with mean energy around 400 MeV deposit similar amounts of energy to the 4 GeV mean-energy muons present at ground level as both represent minimum ionizing particles within the 3He sensors.  We therefore developed an experiment using a pair of plastic scintillators in coincidence with a 3He tube to measure energy deposition from muons while excluding room background gamma rays.  Here we will present results of this experiment to characterize the angular response to cosmic ray muons of a 3He flight spare detector from the VIPER NSS and explore the implications of these results for analysis of planetary neutron data sets.

How to cite: Wilson, J. T., Peplowski, P. N., Yokley, Z. W., Lawrence, D. J., and Elphic, R. C.: Cosmic ray muons as a proxy for in-cruise galactic cosmic ray protons in 3He gas proportional counters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17421, https://doi.org/10.5194/egusphere-egu23-17421, 2023.

EGU23-17487 | ECS | Posters on site | GI6.8

Cosmic-ray neutron production and propagation inside snow packs characterized by multi-particle Monte Carlo simulations 

Jannis Weimar, Paul Schattan, Rebecca Gugerli, Benjamin Fersch, Darin Desilets, Martin Schrön, Markus Köhli, and Ulrich Schmidt

Cosmic-ray neutron sensors buried below a snow pack provide a passive and autonomous monitoring technique of snow water equivalent (SWE). The effective neutron flux is attenuated inside the snow volume resulting in an inverse relationship between neutron intensity and the water equivalent of the snow column above the sensor. Neutrons are moderated and absorbed within the snow. Simultaneously, highly energetic cosmic rays produce further neutrons via spallation and evaporation processes. A comprehensive assessment of the neutron flux therefore requires multi-particle simulations which involve all relevant incoming particle species and transient particles from cosmic-ray showers which play a crucial role in neutron production.

In our study, we used the Monte Carlo toolkit MCNP6 and validated its high-energy evaporation and spallation models against a measured data set of a neutron intensity profile in water. Based on that we fitted analytical functions to a large variety of simulation setups that describe the neutron intensity as a function of SWE and the moisture content of the soil below the sensor. Moreover, single-particle tracking revealed that the radial footprint of the method does not exceed few meters for detectors below thick snow layers. In the case of shallow snow, however, the diffusive long-range neutron flux in the atmosphere may penetrate through the snow pack to the buried sensor and thereby increases the influence of distant objects. Since the diffusive flux is further sensitive to the atmospheric water content, we developed an air humidity correction tailored to snow-buried neutron detectors.

In general, the study aims at a holistic understanding of neutron production and transport processes in snow and the adjacent soil and air volumes in order to improve SWE monitoring by buried cosmic-ray neutron sensors and compares the simulation results to field data.

How to cite: Weimar, J., Schattan, P., Gugerli, R., Fersch, B., Desilets, D., Schrön, M., Köhli, M., and Schmidt, U.: Cosmic-ray neutron production and propagation inside snow packs characterized by multi-particle Monte Carlo simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17487, https://doi.org/10.5194/egusphere-egu23-17487, 2023.

EGU23-852 | ECS | Posters virtual | NH4.1

A suitable time-dependent conditional probability for Pacific strong earthquakes 

Cristiano Fidani

Statistical analyses of NOAA POES data have recently evidenced electron burst losses 1.5-3.5 h before strong earthquakes in the West Pacific and 55-59 h before strong earthquakes in East Pacific. The conditional probability of a strong seismic event after an ionospheric loss event was calculated depicting possible scenarios in both areas. It presented a geohazard risk reduction initiative that can gain valuable preparation time by adopting a probabilistic short-term warning a few hours prior, especially for tsunamis in those dangerous areas. As electron losses were detected in the same region both for West and East Pacific earthquakes, the probability of a strong event in the West Pacific would be first considered and vanish in less than 4 h. Then, after considering the seismic activity, a statistical evaluation of a disastrous event for the East Pacific coast is generated, so defining a time-dependent increase in conditional probability.

How to cite: Fidani, C.: A suitable time-dependent conditional probability for Pacific strong earthquakes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-852, https://doi.org/10.5194/egusphere-egu23-852, 2023.

EGU23-1592 | Posters virtual | NH4.1 | Highlight

Lower  Ionospheric  variation over Europe during the  tectonic activity in the area of Thessaly, Greece on March of 2021. 

Michael E. Contadakis, Demeter N. Arabelos, Pikridas Christos, Stylianos Bitharis, and Emmanuel Scordilis

This is one of a series of papers in which  we investigate the Lower ionospheric variation on the occasion of intense tectonic activity.In the present paper, we investigate the TEC variations during the intense seismic activity in Thessaly, on March 2021 over Europe. The Total Electron Content (TEC) data are been provided by the  Hermes GNSS Network managed by GNSS_QC, AUTH Greece, the HxGN/SmartNet-Greece of Metrica S.A, and the EUREF Network. These data were analysed using Discrete Fourier Analysis in order to investigate the TEC turbulence. The results of this investigation indicate that the High-Frequency limit fo of the ionospheric turbulence content, increases as aproaching the occurrence time of the earthquake, pointing to the earthquake epicenter, in accordane to our previous investigations. We conclude that the Lithosphere Atmosphere Ionosphere Coupling, LAIC, mechanism through acoustic or gravity waves could explain this phenomenology.

 

Keywords: Seismicity, Lower Ionosphere, Ionospheric Turbulence, Brownian Walk, Aegean area.

How to cite: Contadakis, M. E., Arabelos, D. N., Christos, P., Bitharis, S., and Scordilis, E.: Lower  Ionospheric  variation over Europe during the  tectonic activity in the area of Thessaly, Greece on March of 2021., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1592, https://doi.org/10.5194/egusphere-egu23-1592, 2023.

EGU23-2087 | Orals | NH4.1

Double resonance before earthquakes 

Chieh-Hung Chen, Kai Lin, Xuemin Zhang, and Yongxin Gao

An instrumental array was established in southwest China for Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere and Ionosphere (MVP-LAI).  We retrieved multiple-geophysical data from the array to investigate common characteristics in LAI before earthquakes.  Broadband seismometers are utilized to monitor ground vibrations in the lithosphere.  Barometers record changes in air pressure near the Earth’s surface.  Magnetometers monitor variations in the ionospheric currents ~100 km above the Earth’s surface.  Instead of GPSTEC (Global Positioning System Total Electron Content), electromagnetic signals transmitted from the BDS (BeiDou navigation system) geostationary satellites are received by ground-based GNSS (Global Navigation Satellite System) receivers to compute TEC data.  The BDSTEC from the geostationary satellites continuously monitor changes in TECs ~350 km in altitude right over the array.  We transferred these data into the frequency domain and found that ground vibrations, air pressure, the magnetic field, and BDSTEC data share the frequency ~5×10-3 Hz before major earthquakes.  Ground vibrations exhibit frequency characteristics of ~5×10-3 Hz due to resonance of nature frequencies before failure of materials (i.e., dislocations of faults, and earthquakes).  Ground vibrations with frequency of ~5×10-3 Hz persistently hit the bottom of the atmosphere that can trigger atmospheric resonance before earthquakes.  Double resonance (i.e., crustal and atmospheric resonance) provides the new way to reveal the seismo-anomalies of multiple geophysical parameters in LAI.  Double resonance would shed a light in earthquake prediction in practice once we face the major issue for efficiently retrieving resonance signals from multiple observation data. 

 

How to cite: Chen, C.-H., Lin, K., Zhang, X., and Gao, Y.: Double resonance before earthquakes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2087, https://doi.org/10.5194/egusphere-egu23-2087, 2023.

EGU23-2126 | Posters virtual | NH4.1

New features of the ELSEM-Net electromagnetic monitoring stations network and analysis of recent data associated with strong earthquakes. 

Dimitrios Z. Politis, Stelios M. Potirakis, Philopimin Malkotsis, Nikolaos Papadopoulos, Dionysios Dimakos, Michael Exarchos, Efstratios Liadopoulos, Yiannis F. Contoyiannis, Angelos Charitopoulos, Kyriakos Kontakos, Dimitrios Doukakis, Grigorios Koulouras, Nikolaos Melis, and Konstantinos Eftaxias

The ELSEM-Net (hELlenic Seismo-ElectroMagnetics Network, http://elsem-net.uniwa.gr) is a telemetric network of ground-based monitoring stations for the study of fracture-induced electromagnetic emissions. It comprises 11 telemetric stations, spanning all over Greece, and has continuously been operated for almost 30 years. In this paper we present the new, custom designed, instrumentation of the telemetric stations. Specifically, we present both the hardware and the firmware/software used, from antennae to data acquisition and data management. Finally, we present recent recordings prior to significant strong earthquakes (EQs) that have happened in Greece, as well as the obtained analysis results, using nonlinear time series analysis methods, indicating that the acquired signals embed important features associated with the impending EQ.

How to cite: Politis, D. Z., Potirakis, S. M., Malkotsis, P., Papadopoulos, N., Dimakos, D., Exarchos, M., Liadopoulos, E., Contoyiannis, Y. F., Charitopoulos, A., Kontakos, K., Doukakis, D., Koulouras, G., Melis, N., and Eftaxias, K.: New features of the ELSEM-Net electromagnetic monitoring stations network and analysis of recent data associated with strong earthquakes., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2126, https://doi.org/10.5194/egusphere-egu23-2126, 2023.

EGU23-2187 | ECS | Orals | NH4.1

Possible Lithosphere Atmosphere Ionosphere Coupling before 19 September 2021 La Palma volcano eruption 

Dedalo Marchetti, Hanshuo Zhang, Kaiguang Zhu, Zeren Zhima, Rui Yan, Xuhui Shen, Alessandro Piscini, Wenqi Chen, Yuqi Cheng, Xiaodan He, Ting Wang, Jiami Wen, Donghua Zhang, and Yiqun Zhang

On 19 September 2021, La Palma Volcano started a VEI 3 eruption. Here we will illustrate an investigation for at least six months before the eruption with the aim of searching possible lithosphere atmosphere and ionosphere couplings.

We identify and compare the anomalies from the seismic catalogue, the geomagnetic ground observatories, the atmospheric climatological datasets, TEC maps, CSES and Swarm satellites data with respect to the volcano location and the time cumulative trends of anomalies are analyzed.

We identify a temporal migration of the seismicity from one year before the eruption at a depth of 40 km possibly associated with magma migration, firstly to a deep chamber (20-13km depth) and in the last 10 days in a shallower magma chamber. CSES-01 detects an increase in electron density at the same time as vertical ground magnetic field anomalies, very likely due to the magma uprising. A final increase of carbon monoxide 1.5 months before the eruption with unusually high values of TEC suggests the degassing of magma before the eruption associated with shallow seismicity that preceded the eruption by ten days. We identify possible different coupling mechanisms, e.g., chain of mechanical, thermal, chemical and electromagnetic phenomena, or pure electromagnetic coupling). These different lithosphere-atmosphere-ionosphere coupling mechanisms can coexist.

Our results highlight the importance of integrating several observation platforms and datasets from the ground and space (earth observation satellites) to better understand the dynamics of the processes and associated natural hazards affecting our planet.

How to cite: Marchetti, D., Zhang, H., Zhu, K., Zhima, Z., Yan, R., Shen, X., Piscini, A., Chen, W., Cheng, Y., He, X., Wang, T., Wen, J., Zhang, D., and Zhang, Y.: Possible Lithosphere Atmosphere Ionosphere Coupling before 19 September 2021 La Palma volcano eruption, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2187, https://doi.org/10.5194/egusphere-egu23-2187, 2023.

EGU23-3596 | ECS | Orals | NH4.1

Water chemical composition as indicator of geodynamic activity 

Armen Kazarian and Aik Kazarian

WATER’S GEOCHEMICAL COMPOSITION AS INDICATOR OF GEODYNAMIC ACTIVITY 

A.Kazarian, H. Kazarian IGN AN NAN

 

A detailed analysis of a long-term collection of hydro-geochemical data was carried out over a ten-year period. It revealed consistent iterations of signs of a process of earthquake preparation in this region. This preparation process has several distinct stages, which can be identified by noticeable changes in the geochemical composition of self-pouring well water. The earthquake preparation process is graphically visible and has a similar duration to the post-earthquake aftershock activity duration. The visualization of hydro-geochemical data from the pre- and post-earthquake periods for different (M> 6) earthquakes in this region shows a very similar pattern of behaviors and duration of behaviors for events of varying magnitudes and distances from the observation wells.

Changes in the main fluctuation trend of the geochemical data for helium (He) and a decrease in the standard deviation of the series for other main components appear as earthquake precursors (Na, K, HCO3, SO4, Cl, Ca, F). The detectable duration of a main shock's preparation process is approximately a year. The detailed examination of the data time series reveals a strong correlation between the overall geodynamic activity of the region and the hydrogeochemical composition of the observed wells.

The detailed analysis of earthquake activity in the region suggests a periodic nature of basic seismicity and its relationship with earthquake focal mechanisms. The obtained daily histograms for seismic activity in Armenia, Turkey, Greece, and Italy regions calculated by local time show cyclical activity patterns of 24 and 12 hours. This is consistent with variations in He and other important components in the well waters. The hypothesis and conclusion of this scientific research project are that in seismically active zones, the dynamics of hidden active tectonic processes can potentially be a priori diagnosed using this hydro-geochemical monitoring method.

How to cite: Kazarian, A. and Kazarian, A.: Water chemical composition as indicator of geodynamic activity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3596, https://doi.org/10.5194/egusphere-egu23-3596, 2023.

EGU23-3854 | Posters virtual | NH4.1

Comparison of the precursory effects in lithosphere, atmosphere and ionosphere of three large earthquakes with comparable magnitude: the cases of 2019 Kermadec Islands (NZ) and Ridgecrest (USA) earthquakes and 2021 Maduo (China) earthquake 

Angelo De Santis, Saioa A. Campuzano, Massimo Calcara, Gianfranco Cianchini, Serena D'Arcangelo, Mariagrazia De Caro, Domenico Di Mauro, Cristiano Fidani, Adriano Nardi, Martina Orlando, Loredana Perrone, Alessandro Piscini, Dario Sabbagh, and Maurizio Soldani

Three earthquakes of comparable magnitude and in different tectonic contexts occurred on 15 June 2019 (M7.2) in New Zealand (Kermadec Islands), on 6 July 2019 (M7.1) in California (Ridgecrest) and on 21 May 2021 (M7.3) in China (Maduo) (dates in UT). We applied a multiparameter - multilayer approach to lithospheric, atmospheric and ionospheric data, the latter taken from CSES  and Swarm satellites, before the mentioned large earthquakes to detect potential pre-earthquake anomalies. In all case studies, we note the following: a) similar precursor times of occurrences, confirming the Rikitake law for which the larger the earthquake magnitude the longer the anticipation time of the precursor and b) a clear acceleration of the possible precursory anomalies before each mainshock, as typical of critical systems approaching a critical state. We propose an interpretative model to take into account the chain of detected phenomena.

How to cite: De Santis, A., Campuzano, S. A., Calcara, M., Cianchini, G., D'Arcangelo, S., De Caro, M., Di Mauro, D., Fidani, C., Nardi, A., Orlando, M., Perrone, L., Piscini, A., Sabbagh, D., and Soldani, M.: Comparison of the precursory effects in lithosphere, atmosphere and ionosphere of three large earthquakes with comparable magnitude: the cases of 2019 Kermadec Islands (NZ) and Ridgecrest (USA) earthquakes and 2021 Maduo (China) earthquake, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3854, https://doi.org/10.5194/egusphere-egu23-3854, 2023.

EGU23-4399 | Orals | NH4.1 | Highlight

Transient effects in the atmosphere/ionosphere and their re-occurrence before large earthquakes. Case study for the 2022 “anniversary” events. 

Dimitar Ouzounov, Sergey Pulients, Jann-Yenq Liu, Katsumi Hattori, Menas Kafatos, and Patrick Taylor

We present a study on temporal and spatial characteristics of Thermal Radiation anomalies (TRA) and ionospheric total electron content (TEC) pre-earthquake abnormalities associated with the occurred in 2022 “anniversary” earthquakes. “Anniversary”  is a quake occurring on the same date and following the years after the main earthquake, plus or minus several days.

We studied eleven large earthquakes in four regions: i/Japan: M7.3 of 03.16.2022 and M9.0 of 03.11.2011 East Coast Honshu; ii/Mexico: M7.6 of 09.19.2022 Michoacan; M7.1 of 09.19.2017 Puebla and M8.0 of 09.19.1985 Mexico City;/iii Chile: M5.7 02.28.2022 Bio-Bio and M8.8 02.27.2010 Maule and /iv Taiwan: M6.9 of 09.18.2022 Taitung and M7.7 of 09.21.1999 Chi-Chil and M6.7 of 03.22.2022 Taitung and M6 of 03.27.2013 Nantou earthquake.

We analyzed for TRA and TEC anomalies concerning the earthquake preparation zone (EPZ). For EPZ estimates, we use Dobrovolsky et al. (1979), and Bowman et al. (1998) estimates where the EPZ radius scales exponentially with earthquake magnitude, especially from Mw ≥ 6.0 onwards, and gives an extended coverage at larger magnitudes to examine TRA and ionospheric TEC anomalies. The main goals of this study were: 1/to understand the seismotectonic conditions that preceded the earthquake re-occurrence in the same place and on the same day(s): 2/ to perform a validation study about pre-earthquake signal occurrences in the same atmospheric and solar-geophysical conditions and 3/ to understand the potential triggering mechanism. Our preliminary results show synergetic coordination between the appearance of pre-earthquake transients’ effects in the atmosphere and ionosphere (with a short time lag, from hours up to a few days). The spatial characteristics of pre-earthquake anomalies were associated with the large area but inside the preparation region estimated by Dobrovolsky-Bowman. The pre-earthquake nature of the signals in the atmosphere and ionosphere was revealed by simultaneous analysis of satellite, GPS/TEC, and Satellite Earth observations. The “anniversary” events are recognized with common pre-earthquake transient re-occurrence patterns in the atmosphere/ionosphere within EPZ, scaled to the extent of the earthquake magnitude.

How to cite: Ouzounov, D., Pulients, S., Liu, J.-Y., Hattori, K., Kafatos, M., and Taylor, P.: Transient effects in the atmosphere/ionosphere and their re-occurrence before large earthquakes. Case study for the 2022 “anniversary” events., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4399, https://doi.org/10.5194/egusphere-egu23-4399, 2023.

EGU23-5813 | Posters virtual | NH4.1

Mammal abundance varies with geochemical specialisation in the underlying rock formations. 

Rachel Grant, Alexander Shitov, and Andrey V. Karanin

There has been little research on how the composition of underlying rock formation affects animal species’ distribution and abundance. The subject is worthy of consideration as, for example,  it has been shown that ultrabasic and serpentine rocks in particular can give rise to plant biodiversity hotspots with a high level of endemism. Corresponding studies of fauna are lacking. We aim to test the hypothesis that rock type affects mammal abundance and biodiversity.

Here we present a comparative analysis of the abundance of mammals and its relationship with geological composition in the area of Gorny Altai, a mountainous region in Russia.

We used GIS approaches to map the influence of rock types on mammal abundance, while holding other factors such as soil type, relief, etc. constant. The study reveals significant correlations between underlying geology and variation in mammal distribution even when other factors such as soil type, climate and vegetation are held constant.

Intrusive rocks were found to have the greatest impact on variation in mammal distribution whereas sedimentary and metamorphic rocks have almost no effect. A characteristic feature of magmatic formations is their clear geochemical specialization, i.e. certain geochemical anomalies (Fe, Cu, Au, Hg, Ag, etc.) are confined to intrusions. We suggest that geophysical fields (magnetic and electric fields) and geochemical anomalies associated with intrusive rocks may have an impact on the distribution and species composition of mammals, as well as geodynamic processes such as fault activity. This finding has implications for further research into the phenomenon of animals’ anticipatory responses to earthquakes. 

How to cite: Grant, R., Shitov, A., and Karanin, A. V.: Mammal abundance varies with geochemical specialisation in the underlying rock formations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5813, https://doi.org/10.5194/egusphere-egu23-5813, 2023.

EGU23-8521 | Orals | NH4.1

Sub-ionospheric VLF/LF waveguide variations related to magnitude M>5 earthquakes in the eastern Mediterranean area 

Hans Eichelberger, Mohammed Y. Boudjada, Konrad Schwingenschuh, Bruno P. Besser, Daniel Wolbang, Maria Solovieva, Pier F. Biagi, Patrick Galopeau, Ghulam Jaffer, Özer Aydogar, Christoph Schirninger, Cosima Muck, Irmgard Jernej, and Werner Magnes

In this study we examine earthquakes with magnitude M>5 in the year 2022 where the epicenters are crossed by sub-ionospheric narrowband VLF/LF radio links. The study regions are Italy, Aegean area, and the Balkan Peninsula. Ideal suited for this task are paths from the transmitters TBB (26.70 kHz, Bafa, Turkey), ITS (45.90 kHz, Niscemi, Sicily, Italy), and ICV (20.27 kHz, Tavolara, Italy) to the seismo-electromagnetic receiver facility GRZ (Graz, Austria). The receiver is part of a wider network, this gives the opportunity to have multiple simultaneous crossings of an earthquake event.

We investigate electric field amplitude variations in the time span a few days around the main shock, in particular we apply the so-called night-time amplitude method. All electric field data sets have 1 sec temporal resolution. A crucial point is a certain threshold magnitude to obtain statistically significant results, but to firm up the results additional complementary investigations are necessary.

In summary, VLF/LF investigations of strong earthquakes show the complex interplay between the lithospheric events and electric field amplitude waveguide variations, multi-parametric observations in a network could be a tool to derive robust results.

How to cite: Eichelberger, H., Boudjada, M. Y., Schwingenschuh, K., Besser, B. P., Wolbang, D., Solovieva, M., Biagi, P. F., Galopeau, P., Jaffer, G., Aydogar, Ö., Schirninger, C., Muck, C., Jernej, I., and Magnes, W.: Sub-ionospheric VLF/LF waveguide variations related to magnitude M>5 earthquakes in the eastern Mediterranean area, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8521, https://doi.org/10.5194/egusphere-egu23-8521, 2023.

EGU23-9395 | Orals | NH4.1

VLF transmitter signal variations as detected by Graz facility prior to Croatian earthquakes 

Mohammed Y. Boudjada, Pier F. Biagi, Hans U. Eichelberger, Konrad Schwingenschuh, Patrick H.M. Galopeau, Masashi Hayakawa, Maria Solovieva, Helmut Lammer, Wolfgang Voller, and Bruno Besser

We report on two earthquakes (EQs) that occurred in Croatia at a distance less than 200 km from the Austrian Graz facility (15.46°E, 47.03°N). Those EQs happened on March 22 and December 29, 2020, with magnitudes of Mw5.4 and Mw6.4, respectively. The epicenters were at geographical coordinates (16.02°E, 45.87°N; 16.21°E, 45.42°N) with focuses smaller than 10 km.  Austrian Graz facility leads to detect more than fifteen VLF and LF transmitter signals (Schwingenschuh et al., 2011, Biagi et al., 2019). Transmitter ray paths cross over the EQs epicenters in particular those localised in ICV and ITS (Italy) and TBB (Turkey). We emphasize in our study on the signal fluctuations before/after the sunrise- and sunset-times, or terminator times (TTs). Transmitter amplitude signals exhibit precursor anomalies that related to EQs disturbances occurring particularly at the falling off or the growth of the ionospheric D-layer. Ground-based stations (e.g. Rozhnoi et al., 2009) and satellite observations (e.g. Zhang et al., 2020) have reported such EQs ionospheric disturbances at several occasions.

 

References:

Biagi et al., The INFREP Network: Present Situation and Recent Results, Open J. Earth. Research, 8, 2019. Rozhnoi et al., Anomalies in VLF radio signals prior the Abruzzo earthquake (M=6.3) on 6 April, 2009, Natural Hazards and Earth System Science, 9, 2009. Schwingenschuh et al., The Graz seismo-electromagnetic VLF facility, Nat. Hazards Earth Syst. Sci., 11, 2011. Zhang et al., Multi-experiment observations of ionospheric disturbances as precursory effects of the Indonesian Ms6.9 earthquake on August 05 2018, Remote Sens. J., 12, 2020.

 

How to cite: Boudjada, M. Y., Biagi, P. F., Eichelberger, H. U., Schwingenschuh, K., Galopeau, P. H. M., Hayakawa, M., Solovieva, M., Lammer, H., Voller, W., and Besser, B.: VLF transmitter signal variations as detected by Graz facility prior to Croatian earthquakes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9395, https://doi.org/10.5194/egusphere-egu23-9395, 2023.

EGU23-10299 | ECS | Posters virtual | NH4.1

Connectivity of geoelectric network before strong earthquakes 

Hong-Jia Chen and Chien-Chih Chen

Earthquakes are reported to relate to rupture phenomena in complex self-organizing systems. Hence, the earthquake rupture is regarded as a critical point. The preparation process of an earthquake could be considered as the crustal system approaching this critical point. Complex dynamical systems can have critical tipping points at which a sudden shift to a contrasting dynamical regime may occur; in the meantime, the time series of the systems can behave much differently. Although it is extremely challenging to predict such critical points before they are reached, work in different scientific fields is now suggesting the existence of generic early-warning signals that may indicate a wide class of systems if a critical threshold is approaching. Those precursory signals include increasing correlations and variance, varying skewness, and so on. The critical transition of a system includes spatial criticality and temporal criticality. In this study, we attempt to research the spatial and temporal criticality of the crustal system by using the self-potential (SP) signals of the Taiwan Geoelectric Monitoring System (GEMS). The GEMS network consists of 20 SP stations with an interstation distance of 50 km. We calculate the correlations of the daily signals between any two stations, which formed an adjacency matrix. Then, we estimate the connectivity density based on the adjacency matrix and compare the daily connectivity density time series with ML ≥ 5 earthquakes. We would expect to find out high connectivity densities before a strong earthquake. This would mean that earthquake-related telluric currents flow out through the GEMS stations during the earthquake preparation process; hence, the SP signals of most stations would almost be connected. As a result, we might establish an earthquake forecasting technique using the SP data based on the concept of the critical-point theory.

How to cite: Chen, H.-J. and Chen, C.-C.: Connectivity of geoelectric network before strong earthquakes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10299, https://doi.org/10.5194/egusphere-egu23-10299, 2023.

The temporal sequences of magnitudes recorded in seismic active zones exhibit complex behavior which is associated with the wide diversity of scales of fractures sizes when an earthquake on the Earth’s crust occurs. Earthquakes can be considered to be nearly, or even critical phenomena exhibiting dynamic phase transitions, where a mainshock is the beginning of a new phase. Near the critical point is where phase transition (order-disorder) occurs, and scaling laws with long-range order correlations are produced, so that the complexity of seismicity allows earthquakes to be characterized by a more diverse and riche phenomenology. In the last years, the ideas linked to nonlinear time series analysis and complex network theory have been related. Among those ideas,  the visibility graph (VG) method has been applied to the study different complex phenomena. One of the characteristics of this method is its ability to capture dynamic properties, such as non-trivial correlations in nonstationary time series, without introducing elaborate algorithms such as detrending. Seismic processes have been of great interest and their complete understanding is still an open problem. In this work we use the VG method to study the temporal correlations in the seismic sequences monitored in three regions of the subduction zone belonging to the Cocos plate. Our analysis allows estimate persistence and the temporal correlations in the seismic activity monitored in Michoacan State, Mexican Flat Slab and Tehuantepec Isthmus, showing differences in all three.

How to cite: Ramírez-Rojas, A. and Flores-Márquez, E. L.: Correlations of the seismic activity monitored in three subduction zones belonging to Cocos plate by using the visibility graph method., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10458, https://doi.org/10.5194/egusphere-egu23-10458, 2023.

EGU23-10627 | ECS | Orals | NH4.1 | Highlight

Conductivity Anomalies before M > 6 Earthquakes in China during 2014 – 2019 

Zhiqiang Mao and Chieh-Hung Chen

The North-South Seismic Belt of China is one of the most active seismic areas on the Chinese continent.  More than ten strong earthquakes (Ms > 6) have occurred in this region since 2010.  However, Earthquake-related conductivity anomalies are rarely reported for those earthquakes.  In this study, 3-component geomagnetic data recorded at sixty geomagnetic stations are selected to compute the Parkinson vectors to monitor the changes of conductivity before and after the earthquakes.  Considering most fluxgate magnetometers have only been installed since 2014, we concentrate on six Ms > 6 earthquakes occurred during 2014–2019.  To mitigate artificial disturbances, low noise data during the 00:00 – 5:00 LT are utilized.  We compute the background distribution and monitoring distribution using the azimuth of the Parkinson vectors at each station within six years (2014 – 2019) and a 15-day moving window, respectively.  The background distribution is subtracted from the monitoring distributions to mitigate the influences of underlying inhomogeneous tectonic structures.  The obtained difference distributions binned by 10° within 400 km from each station are superimposed during 60 days before and after the earthquake to construct integrated maps.  To analyze the potential frequency characteristics, we compute the results from low to high frequency band.  The results show that for four earthquakes, the conductivity anomalies areas appear near the epicenter 10 to 20 days before earthquakes, while the rest two earthquakes have no anomaly.  The conductivity anomalies appear at all study frequency band from 0.0005 Hz to 0.1 Hz, and significantly at 0.001 – 0.005 Hz before earthquakes.  Meanwhile, we find that the lower frequency band corresponds to larger anomalies area.  These results suggest the change of underlying conductivity near the hypocenter is a possible phenomenon for strong earthquakes, and the frequency characteristics of the seismo-conductivity anomaly during the earthquake are helpful to understand the pre-earthquake anomalous phenomena.

How to cite: Mao, Z. and Chen, C.-H.: Conductivity Anomalies before M > 6 Earthquakes in China during 2014 – 2019, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10627, https://doi.org/10.5194/egusphere-egu23-10627, 2023.

EGU23-13172 | Orals | NH4.1

ULF perturbations: modeling Earth-Atmosphere-Ionosphere coupling, signal processing using information entropy, determination of the electric and magnetic field components and “experiment-theory comparison“ 

Yuriy Rapoport, Volodymyr Reshetnyk, Asen Grytsai, Alex Liashchuk, Masashi Hayakawa, Volodymyr Grimalsky, Sergei Petrishchevskii, Andrzej Krankowski, Leszek Błaszkiewicz, Paweł Flisek, Angelo De Santis, and Carlo Scotto

We have used 2014–2017 data from the eight receiving stations of the Japan very low frequency (VLF) monitoring network. The nighttime data of the signals of the JJI transmitter on Kyushu Island, excited VLF electromagnetic waves (EMWs) in the Earth-Ionosphere waveguide (EIWG) had been processed. The wavelet transform with a preliminary detrending, to exclude influence of daily variations, has been applied. We have observed ultra-low frequency (ULF) modulation of VLF EMW spectra in the EIWG. We therefore concluded that modulating oscillations with periods of 4 minutes belong to the acoustic branch of acoustic-gravity waves (AGWs) in the Earth–Thermosphere waveguide; modulation of VLF with periods of 6–7 minutes corresponds to global evanescent/reactive Brunt–Väisälä AGW oscillations; the oscillations with periods 20–60 min and ~3 hours may characterize evanescent/reactive Lamb gravity wave mode of AGW [1]. The appearance of the combination frequency of VLF EMW and ULF AGW is likely due to the following effects: (1) the drag of charged plasma particles by ULF AGWs jointly with the background of VLF electron density disturbances and (2) the motion of charged plasma particles in the VLF EMW field jointly with the background of ULF changes in the plasma concentration caused by AGWs.

The theory [2,3] is extended to the excitation of ionospheric Schumann resonator (SR) [4] and ionospheric Alfvén resonator (IAR) in the ULF range. It is shown that IAR oscillations with a high quality factor (for geophysical resonators) (>10) can be excited in the SR range. The features of the excited ULF and VLF modes associated with the modification of the ionosphere as a result of the powerful eruption of the Hunga-Tonga volcano are under consideration [5,6].

A ULF model of perturbations in the atmosphere-ionosphere with a boundary transition from dynamic to static limit is developed and the preliminary results of the corresponding modelling will be presented. This ensures the "recovery" of magnetostatic disturbances "lost" in most of previous models of the atmospheric electrical circuit, important for understanding the mechanisms of seismo-ionospheric coupling, volcano-ionospheric coupling and influences of the other natural hazards on the ionosphere and ionospheric monitoring of the natural hazards.

[1] Rapoport et al. Sensors 22, 10.3390/s22218191, 2022; [2] Grimalsky et al. JEMAA 2012, 4, 192-198 ; [3] Yutsis V. et al. Atmosphere 2021, 12, 801 ; [4] Nickolaenko and Rabinovich Space Res. 1982, XX, 67-88 ; [5] Astafyeva et al. GRL, 2022 ; [6] D’Arcangelo et al., Rem. Sens., 14, 3649, 2022.

This research was partially funded by the National Science Centre, Poland, grant No. 970 2022/01/3/ST10/00072

How to cite: Rapoport, Y., Reshetnyk, V., Grytsai, A., Liashchuk, A., Hayakawa, M., Grimalsky, V., Petrishchevskii, S., Krankowski, A., Błaszkiewicz, L., Flisek, P., De Santis, A., and Scotto, C.: ULF perturbations: modeling Earth-Atmosphere-Ionosphere coupling, signal processing using information entropy, determination of the electric and magnetic field components and “experiment-theory comparison“, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13172, https://doi.org/10.5194/egusphere-egu23-13172, 2023.

EGU23-13588 | Posters on site | NH4.1 | Highlight

Improving RST-based analysis of long-term TIR satellite observations in relation with earthquake occurrence 

Valerio Tramutoli, Roberto Colonna, Carolina Filizzola, Nicola Genzano, Mariano Lisi, Nicola Pergola, and Valeria Satriano

In order to build and implement a multi-parametric system for a time‐Dependent Assessment of Seismic Hazard (t‐DASH) the preliminary assessment of the selected parameters is required. To this aim a long-term correlation analysis - among anomalous transients and earthquake occurrence – has to be performed to establish the corresponding forecast capability and particularly the expected false-positive rate. In fact, more than the missing rate (i.e. how many earthquakes occurs in absence of specific precursors) the reliability of the forecast is much more important when the continuity of the observations cannot be guaranteed. This is the case of satellite observations in the optical band  whose continuity can be prevented by the presence of meteorological clouds. Among the others candidate parameters anomalous transients in the Earth’s emitted Thermal Radiation observed from meteorological satellites in the Thermal InfaRed band (TIR) have been since long-term proposed in the framework of a multi-parametric t-DASH system. Results achieved by RST (Robust Satellite Technique) analyses of multi-annual (more than 10 years) time series of TIR satellite images in different continents and seismic regimes, allowed to identify (isolating them from all the others possible sources) those anomalies (in the spatial/temporal domain) possibly associated to the occurrence of major earthquakes. Main lesson learnt until now can be summarized as follows:

a) Thanks to a clear definition of (Significant Sequences of TIR Anomalies (SSTAs) and well-defined validation rules, for earthquakes with magnitude greater than 4 the false positive rate is around 25% (average value over Greece, Italy, Japan, Turkey) oscillating from 7% up to 40% strongly depending on the considered region;

b) Molchan error diagram analyses gave a clear indication that a non-casual correlation exist between RST-based SSTAs and earthquake occurrence time and location;

c) SSTAs are quite rare (sporadic) with quite limited (less than 0,05% of the total investigated) alerted space-time volumes;

d) The approach based on the application of the RETIRA index (Robust Estimator of TIR Anomalies) showed some limitation related to the contextual approach that, in order to take into account of possible large scale changes of the thermal background, consider not just the TIR signal itself but its excess respect to the background (large scale spatial average of the TIR signal) introducing, this way, a strong dependence on the presence and distribution of meteorolical cloud across the scene.

In order to overcome the d) issue an alternative possibility has been investigated which can locally filter-out the contributes of occasional warming (typically associated to meteorological fronts) without the need of analyzing the TIR signal at the large-scale. In this paper RST approach is implemented by introducing the RETIRSA (Robust Estimator of TIR Slope Anomalies) devoted to identify anomalous Nocturnal TIR  Gradients in relation with the preparation phases of earthquakes. The impact in reducing the overall false-positive rates will be particularly discussed in the case of recent earthquakes occurred in Italy, Japan and California. 

How to cite: Tramutoli, V., Colonna, R., Filizzola, C., Genzano, N., Lisi, M., Pergola, N., and Satriano, V.: Improving RST-based analysis of long-term TIR satellite observations in relation with earthquake occurrence, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13588, https://doi.org/10.5194/egusphere-egu23-13588, 2023.

EGU23-14058 | Posters virtual | NH4.1

Improving the statistical correlations between low seismic events and CO2 variations subtracting the rain contribution 

Lisa Pierotti, Cristiano Fidani, Gianluca Facca, and Fabrizio Gherardi

A correlation between low seismic activity and CO2 measurements variations was observed at the Gallicano thermomineral spring, Tuscany, Italy, where an automatic monitoring multiparametric geochemical station is operative since 2003 (Pierotti et al., 2015). The above-mentioned correlation reported a time delay of about 2 days of small earthquakes with respect to CO2 anomalies. Starting from this correlation a conditional probability of earthquake occurrence given the CO2 anomaly detection was calculated, with a probability gain near 4 (Pierotti et al., 2022).  A statistical correlation was also calculated between rain events and CO2 anomalies which was observed for rain vents ahead CO2 anomalies of one days. This permitted to distinguish CO2 anomalies due to meteorological versus tectonic activities.  Following this distinction, and subtracting the rain contribution to the CO2 variations, a new correlation was observed between small earthquakes and CO2 anomalies which confirmed the past results whit a better performance. The new correlation peak is better defined and concentrated in the time lag of 2 days. The p-values of both earthquake and rain to CO2 correlations were calculated. The correspondent probability gain in an earthquake forecasting experiment, taking into account the rain events, increased from less than 4 to 4.5. 

     

 

Fidani, C. (2021). West Pacific Earthquake Forecasting Using NOAA Electron Bursts With Independent L-Shells and Ground-Based Magnetic Correlations. Front. Earth Sci. 9:673105.

Pierotti, L., Botti, F., D’Intinosante, V., Facca, G., Gherardi, F. (2015). Anomalous CO2 content in the Gallicano thermo-mineral spring (Serchio Valley, Italy) before the 21 June 2013, Alpi Apuane earthquake (M= 5.2). Physics and Chemistry of the Earth, Parts A/B/C, 85, 131-140.

Pierotti, L., Fidani C., Facca, G., Gherardi, F. (2022). Local earthquake conditional probability based on long term CO2 measurements. In 40st GNGTS National Conference, Trieste, 27 - 29 June 2022.

How to cite: Pierotti, L., Fidani, C., Facca, G., and Gherardi, F.: Improving the statistical correlations between low seismic events and CO2 variations subtracting the rain contribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14058, https://doi.org/10.5194/egusphere-egu23-14058, 2023.

EGU23-17023 | Orals | NH4.1 | Highlight

Ionospheric electric fields associated with seismo-ionospheric precursors and ionospheric storms observed by FORMOSAT-5/AIP 

Jann-Yenq Liu, Fu-Yuan Chang, Yuh-Ing Chen, and Chi-Kuang Chao

The mission of Advanced Ionospheric Probe (AIP) onboard FORMOSAT-5 (F5) satellite is to detect seismo-ionospheric precursors (SIPs) and observe ionospheric weathers.  F5/AIP plasma quantities in nighttime of 22:30 LT (local time) and the total electron content (TEC) of the global ionosphere map (GIM) are used to study SIPs of an M7.3 earthquake in the Iran-Iraq Border area on 12 November as well as two positive storms on 7 and 21-22 November 2017.  The TEC and the F5/AIP ion density/temperature anomalously increase over the epicenter area on 3-4 November (day 9-8 before the earthquake) and on the two storm days.  The anomalous TEC increase frequently appearing specifically in a small area near the epicenter day 9-8 before the earthquake indicates the SIP being observed, while those frequently occurring at worldwide high-latitudes are signatures of the two positive storms.  TEC increase anomalies most frequently appearing in the Iran-Iraq Border area on 21-22 November (day 10-9 before) is coincidently followed by an M6.1 earthquake on 1 December 2017, which again meets the temporal SIP characteristic.  The F5/AIP ion velocity uncovers that the SIPs of the two earthquakes are caused by eastward seismo-generated electric fields, and the two positive storms are due to the prompt penetration electric fields.

How to cite: Liu, J.-Y., Chang, F.-Y., Chen, Y.-I., and Chao, C.-K.: Ionospheric electric fields associated with seismo-ionospheric precursors and ionospheric storms observed by FORMOSAT-5/AIP, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17023, https://doi.org/10.5194/egusphere-egu23-17023, 2023.

EGU23-17053 | Posters virtual | NH4.1

Detection of correlated anomalous seismic and geomagnetic precursor signals before Vrancea moderate size earthquakes 

Iren Adelina Moldovan, Victorin Toader, Andrei Mihai, Felix Borleanu, Laura Petrescu, Anica Otilia Placinta, and Liviu Manea

Our study aims to detect anomalous seismic and geomagnetic precursor signals appearing before Vrancea, Romania medium sized earthquakes, that occurred in the last decade (2012-2022), using in the first step the visualization processing method, to identify the time lap between the two anomalies and the following earthquakes. During the study period, in Vrancea seismogenic zone there have been recorded 39 earthquakes with magnitude ML>=4.5, both at normal and intermediate depth. We have assumed that the zone of effective manifestation of the precursor deformations is a circle with the radius taken from the equation of Dobrovolsky, 1979, so the studies were done inside this zone. The Seismic data consists in seismic velocities vp and vs (vp/vs), computed from the arrivals of seismic waves at the NIEP stations situated in the earthquake preparation area. The calculations are done automatically by the Phenomenal platform https://ph.infp.ro/seismicity/data, using the corrected Romanian seismic bulletins. The seismic velocity is the geophysical property that has a key role in characterizing dynamic processes and the state of the stress around the faults, providing significant information regarding the change in tectonic regime. In the crust, velocities change before, during and after earthquakes through several mechanisms related to, for example, fault deformations, pore pressure, changes in stress state (pressure perturbation) and rebound processes.

The Geomagnetic data are obtained from Muntele Rosu (MLR) Seismological Observatory of NIEP, situated inside Vrancea seismogenic zone as primary station, and from Surlari (SUA) Geomagnetic Observatory of Intermagnet, as remote station, unaffected by medium size earthquake preparedness processes. Geomagnetic indices taken from GFZ (https://www.gfz-potsdam.de/kp-index) were used to separate the global magnetic variation from possible local seismo-electromagnetic anomalies, that might appear in a seismic area like Vrancea zone and to ensure that observed geomagnetic fluctuations are not caused by solar-terrestrial effect.

In this presentation we study the appearance of the changes of seismic propagation velocities (vp/vs) in time and the geomagnetic deviations from the normal trend before the occurrence of moderate size crustal and intermediate earthquakes from Vrancea zone, to emphasize the time span between the studied phenomena, in order to be able to find a statistical correlation between them.

Acknowledgements. This work was funded by: PN23 36 02 01/2023 SOL4RISC Nucleu Project, by MCD, Phenomenal Project PN-III-P2-2.1-PED-2019-1693, 480PED/2020 and AFROS Project PN-III-P4-ID-PCE-2020-1361, PCE/2021 supported by UEFISCDI

How to cite: Moldovan, I. A., Toader, V., Mihai, A., Borleanu, F., Petrescu, L., Placinta, A. O., and Manea, L.: Detection of correlated anomalous seismic and geomagnetic precursor signals before Vrancea moderate size earthquakes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17053, https://doi.org/10.5194/egusphere-egu23-17053, 2023.

EGU23-17076 | Posters on site | NH4.1 | Highlight

Development of Broadband Interferometer System for Pre-Earthquake Electromagnetic Radiation in LF Band :Design and Performance of Antenna Elements 

Katsumi Hattori, Yu-ichiro Ohta, Chie Yoshino, and Noriyuki Imazumi

Various preseismic electromagnetic variations have been reported so far. Oike et al. reported an increase in the number of electromagnetic pulses in the LF band for the 1995 Kobe Earthquake. However, there is a problem that the electromagnetic pulse due to lightning activity, which is a strong electromagnetic radiation source in the LF band, cannot be sufficiently distinguished from the electromagnetic pulse associated with earthquakes. At that time, it was difficult to observe waveforms with the observation equipment (especially digital measurement units), but with the development of today's ICT equipment and Internet technology, it is possible to realize an LF band broadband interferometer that can estimate the spatio-temporal sources of electromagnetic radiation. If it is an electromagnetic pulse due to lightning activity, the electromagnetic radiation source will move with the front or cloud, and if it is associated with an earthquake, the electromagnetic radiation source will be concentrated near the focal region. In this presentation, we will report the progress of the development of the LF band broadband interferometer, and the waveform analysis and pulse number variation of the nearby earthquake that occurred during the test of the interferometer element.

The developed system is a capacitive circular flat plate fast antenna, consisting of a 500 kHz low-pass filter, a 16bit AD converter, and a PC for data recording, and records 100 ms before and after the pulse waveform that exceeds the trigger level with 4 MHz sampling. The system is installed on the roof of the Faculty of Science Building No.5, Chiba University, and is conducting test observations.

First, we counted the total number of pulses recorded by the system, created an amplitude histogram, and targeted the top 15% of the pulses to investigate hourly fluctuations in the number of pulses. We calculated the average value m and standard deviation σ for the entire analysis period, and defined the anomaly in the number of pulses as m + 2σ. Next, using pulse waveforms and the mine location network blitzortung.org, waveforms (near and distant mines) caused by mine discharges were identified. In addition, we analyzed the earthquakes that occurred within 100 km of the epicenter distance and satisfied log(Es)>8 during the observation period, and investigated the relationship with the earthquakes. where Es=101.5M+4.8/r2 (M: magnitude, r: focal distance). As a result, 4 days before the M5.0 earthquake on November 27, 2018, an abnormal increase in the number of pulses greater than m+2σ was observed, unrelated to the anti-mine. Although similar pulse waveforms did not exceed the m+2σ threshold, they were also observed prior to four other log(Es) > 8 earthquakes during the observation period, and these pulses were associated with preseismic electromagnetic waves. Possible pulse due to radiation. On the other hand, it is also possible that the pulse waveform is caused by cloud discharge, and in order to discriminate between electromagnetic radiation caused by cloud discharge and earthquake precursor electromagnetic radiation, electromagnetic radiation position determination using an interferometer and comparison with satellite images and meteorological data are required. also found to be essential.

How to cite: Hattori, K., Ohta, Y., Yoshino, C., and Imazumi, N.: Development of Broadband Interferometer System for Pre-Earthquake Electromagnetic Radiation in LF Band :Design and Performance of Antenna Elements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17076, https://doi.org/10.5194/egusphere-egu23-17076, 2023.

EGU23-286 | ECS | Orals | NH9.2

Drought impact profiles: Analyzing multivariate socio-economic drought impacts using nonlinear dimensionality reduction 

Jan Sodoge, Christian Kuhlicke, Miguel Mahecha, and Mariana de Brito

Socio-economic drought impacts often occur concomitantly across multiple sectors, leading to more severe consequences than if they affected single sectors. Improved management of such disasters requires cross-sectoral impact assessments and analyses. As such, analyzing how regions are affected by multiple impacts can provide crucial information for mitigating their consequences. Here, we characterize the multivariate distributions of socio-economic drought impacts. Our aim is to understand patterns by which diverse drought impacts co-occur. We introduce the concept of drought impact profiles, which describe characteristic distributions of co-occurring impacts. To this end, we use a unique spatio-temporal dataset generated with text mining and machine learning applied to newspaper articles. This dataset describes reported socio-economic drought impacts along seven categories (agriculture, forestry, fires,  social, aquaculture, livestock, waterways) in Germany between 2000-2022. We combine several dimensionality reduction algorithms (PCA, ISOmap, self-organizing maps) to generate robust and interpretable representations of the drought impacts. Our results show characteristic patterns for both particular drought events and regions. Also, the applied methods provide a low-dimensional representation of the multivariate socio-economic drought impacts. This research provides a methodological contribution to the holistic, empirical investigation of co-occurring drought impacts. The proposed methods can inform risk models, and policy-makers on the urgency of cross-sectoral governance approaches. Also, the proposed method could apply to other hazards or compound events.

How to cite: Sodoge, J., Kuhlicke, C., Mahecha, M., and de Brito, M.: Drought impact profiles: Analyzing multivariate socio-economic drought impacts using nonlinear dimensionality reduction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-286, https://doi.org/10.5194/egusphere-egu23-286, 2023.

EGU23-567 | ECS | Orals | NH9.2

Managing the co-occurrence of natural hazards and pandemics with a new parallel phases DRM model 

Silvia De Angeli, Stefano Terzi, Davide Miozzo, Lorenzo Stefano Massucchielli, Joerg Szarzynski, Fabio Carturan, and Giorgio Boni

The Disaster Risk Management Cycle (DRMC) is a common reference for the international Disaster Risk Management (DRM) community to describe the management of catastrophic anthropogenic and natural events worldwide. Implementing this approach, disaster management is described by a series of separate and consecutive phases (e.g., preparedness, response, and recovery). However, the current DRMC is not able to successfully cover the dynamics of multi-hazard risk scenarios, particularly those involving both sudden- (e.g., earthquakes or flash floods) and slow-onset hazards (e.g., pandemics or  droughts).

Starting from such a complex scenario we propose a ‘parallel phases’ DRM model accounting for the management of interacting sudden- and slow-onset hazards. The framed ‘parallel phases’ model allows to overcome the limitations of the existing models when dealing with complex multi-hazard risk conditions. We supported the identified limitations analysing Italian Red Cross data dealing with past and ongoing emergencies including the COVID-19 pandemic. Key findings from the analysis involve: (i) the spatial-temporal differences between sudden-onset events and pandemic disaster management; (ii) the high demand for emergency response resources during pandemics in comparison to other emergencies; (iii) the need for the DRM system to adjust the response to cope with the pandemic seasonality; (iv) the system over-exposure to pandemic response activities reducing the number of resources for preparedness and entering the system into an unpreparedness negative loop.

Overall, the combination of the key findings that emerged from the management of the COVID-19 pandemic in Italy brought out three main guidelines for advancing multi-hazard DRM by applying our ‘parallel phases’ model:

  • Managing the system with parallel phases. A ‘parallel phases’ DRM allows the system to exploit the low emergency intensity of the slow-onset hazards seasonality for preparedness actions while also preparing for any other hazard that can have relevant impacts on the system. Such an approach allows the DRM system to escape from an unpreparedness negative loop. 
  • Keeping the DRM system capacity far from depletion. The DRM system can learn how to efficiently deploy the available resources keeping its capacity far from total depletion. If the DRM system is able to save part of its capacity, it can continue with the increase of internal resources while also making them available for international mutual support in case of multi-hazard risk. Such a condition triggers a positive loop in the increase of the DRM capacity.
  • Impact-based forecasting for multi-hazard disaster risk management. The implementation of multi-hazard seasonal impact-based forecasts fosters the planning of appropriate anticipatory actions, combining the prediction of slow-onsets waves with the seasonality of sudden-onsets.

Overall, the proposed ‘parallel phases’ model is able to capture the complex management dynamics to deal with the increasingly frequent slow-onset and multi-hazard events, introducing a change of perspective from the cyclic, consecutive-phases, and single-hazard DRM approach. For this reason, the ‘parallel phases’ model can strengthen and boost current and future international policies on multi-hazard DRM towards an effective implementation at a local scale.

How to cite: De Angeli, S., Terzi, S., Miozzo, D., Massucchielli, L. S., Szarzynski, J., Carturan, F., and Boni, G.: Managing the co-occurrence of natural hazards and pandemics with a new parallel phases DRM model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-567, https://doi.org/10.5194/egusphere-egu23-567, 2023.

Between 2020 and 2022, when South Korea experienced Covid-19, it suffered from multiple natural disasters, including typhoons, forest fires, and earthquakes, as well as infectious diseases. Recently, not only in Korea but also worldwide due to climate change, the number and scale of natural disasters are increasing every year, and the damage caused by them is becoming more and more serious. We analyzed big data on disasters in South Korea to identify trends in disasters caused by climate change. So, between 2012 and 2022, we downloaded over 100,000 open data on emergency disaster alert messages (by mobile network Cell Broadcasting Service) provided by the central government and local governments to the general public through Public data portal (https://www.data.go.kr/) open API(Application Programming Interface). And we visualized the collected raw big data based on GIS after refinement, classification((Natural and social disasters, disaster type, disaster level, CBS msg type, emergency disaster message sending agency, etc.), and subdivision by city (we call it Si, Gun, Gu) unit area. Then, it was displayed based on GIS according to the type of disaster. We performed visualization work to derive the results of climate change trends in South Korea by disaster type and by region(Si, Gun, Gu).
Through this, it was possible to identify the types of disasters that are becoming more severe in South Korea according to climate change. Also, based on these results, we were able to identify which disasters each region would be vulnerable to. In addition, based on these results, we were able to identify which disasters are particularly vulnerable according to the characteristics of each region and which disasters it is best to strengthen preparation for in the future.
The results of analyzing the past history big data of our emergency disaster messages can be usefully used to present preventive and prepared plans for future disasters by central and local governments.
This research was supported by a grant (20008820) of Disaster-Safety Inter-Miniterial Cooperation Program funded by Ministry of Interior and Safety (MOIS, Korea)

How to cite: Oh, S.-H., Kang, H., and Ju, S.-L.: Analysis of natural disaster vulnerability by region through the use of big data of emergency disaster message history, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3031, https://doi.org/10.5194/egusphere-egu23-3031, 2023.

EGU23-3422 | Orals | NH9.2

Feedbacks between City Development and Coastal Flood Risk Management: A Systems Thinking Approach 

Anna Lea Eggert, Karsten Arnbjerg-Nielsen, and Roland Löwe

Human activities have a profound impact on climate and hydrological processes, contributing to changes in the frequency and severity of hydrological extremes and, consequently, growing socioeconomic vulnerability [1]. Rising sea levels, continuous urban development in low-lying coastal areas, and corresponding changes in flood risk have resulted in devastating flood impacts. Different Flood Risk Management (FRM) strategies have been adopted in various socioeconomic contexts and spatiotemporal scales, the most prevalent being structural protection. In recent years, numerous scholars have raised concerns about this approach, as studies have shown that increasing protection levels can increase socioeconomic vulnerabilities e.g., [2]. FRM strategies alter the dynamics of risk manifested in sociohydrological systems, which must be disentangled to avoid unintended consequences.
In the “Cities and rising sea levels” project, scientists from different research disciplines, including hydrology, architecture, landscape architecture, and urban planning, collaborate to tackle these challenges. Combining multidisciplinary knowledge has been central to exploring the cross-sectoral processes involved in FRM. In the present study, we focused on (1) uncovering the cascading effects, including unintended consequences of FRM, as well as (2) highlighting the potentials for holistic assessments of FRM strategies.
Our methods include the development of a Causal Loop Diagram (CLD) model describing critical sociohydrological processes of coastal cities operating at different spatial and temporal scales. We identified dynamic feedbacks between (1) flood risk, urban development and economic wealth, (2) flood risk, urban development and social equity, and (3) flood risk, trust in authorities, and institutional capacity, among others. . Based on the CLD, we analyzed key feedback mechanisms and their manifestation in theory and practice. Further, we explored the impacts of different FRM strategies on these feedback mechanisms to uncover differences in impacts on socioeconomic vulnerabilities and wider cross-sectoral impacts. The presentation will present and explore the conceptual model through semiquantitative analyses (Fuzzy Cognitive Maps (FCMs)) and spatiotemporal assessments using a specific case study. We aim at (1) getting case-specific insights into the dynamics produced by the local interplay of flooding events and socioeconomic processes influencing vulnerabilities, and (2) suggesting pathways for new integrated ways of FRM.

References
[1] IPCC, Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. In Press., 2022.
[2] R. W. Kates, C. E. Colten, S. Laska, and S. P. Leatherman, “Reconstruction of New Orleans after Hurricane Katrina: A research perspective,” Proc. Natl. Acad. Sci. U. S. A., vol. 103, no. 40, pp. 14653–14660, Oct. 2006, doi: 10.1073/PNAS.0605726103/ASSET/C486E9DB-5923-43C0-9881-2B57734F2A7C/ASSETS/GRAPHIC/ZPQ0410637570002.JPEG.

How to cite: Eggert, A. L., Arnbjerg-Nielsen, K., and Löwe, R.: Feedbacks between City Development and Coastal Flood Risk Management: A Systems Thinking Approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3422, https://doi.org/10.5194/egusphere-egu23-3422, 2023.

EGU23-4821 | ECS | Orals | NH9.2

A Study on the Monitoring of Complex Disaster Using Crowd Source Data 

Jeongha Lee and Seokhwan Hwang

As industrialization and urbanization progress around the world, more complex and large-scale complex disasters are occurring, causing numerous casualties and property damage every year. As climate change gradually accelerates and its impact grows, such as recent cold waves and heavy snow in the United States and abnormal temperatures in Europe, it is difficult to predict with existing physical modeling alone. Recently, disasters are gradually expanding in the form of covering not only natural disasters but also various social disasters. Social disasters cover disasters such as fires, infectious diseases, and fine dust caused by human activities. Unlike natural disasters, it is difficult to measure numerical values and predict occurrence patterns in real time, so it is very important to respond quickly through information sharing. There is a limit to establishing the same response system globally to respond to disasters that may occur worldwide, so it is necessary to develop a platform that can quickly share cases while being economical. With the recent development of communication technology, about 70% of the world's population uses smartphones, and various unstructured data are being generated in real time through various social media channels. Individuals act as a sensor and can share their location or current situation in real time. Therefore, the purpose of this study is to develop crowd sourcing technology using social media, analyze the collected data, and present ways to use it in the event of a disaster. In this study, a platform was established to collect and analyze disaster-related SNS data such as floods, fine dust, and forest fires, and it was designed so that users could receive information through websites and apps. As a result of application to various disaster cases in Korea, the temporal and spatial correlation between disaster occurrence patterns and social media data was high, and the possibility of using initial monitoring methods was proved. This result can be applied to all disaster disasters or crimes, and it is expected to be highly useful as it can quickly verify disaster thoughts and share cases in real time.

 

How to cite: Lee, J. and Hwang, S.: A Study on the Monitoring of Complex Disaster Using Crowd Source Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4821, https://doi.org/10.5194/egusphere-egu23-4821, 2023.

EGU23-5148 | Orals | NH9.2

Bridge the gap: Linking social vulnerability and adaptive behaviour 

Sungju Han, Torsten Masson, Sabrina Köhler, and Christian Kuhlicke

Individual adaptation is essential for achieving community resilience as well as coping with residual risks that have not been addressed by current structural schemes for reducing flood risks. At the same time, it also implies that individuals should have the resources and capacity to protect themselves. So far, this has been interpreted in the social vulnerability concept as accounting only for income, wealth, or other materially relevant factors, showing how much vulnerable people are exposed to more risk. However, individual behavioural adaptability has hardly been included in the current vulnerability assessment.

In light of this, this study proposes a novel way to expand and link social classes using well-established social vulnerability indicators (i.e. income, education, and job status) with socio-psychological and lifestyle elements theoretically and empirically known to influence individual protective behaviour. We conducted a bias-adjusted three-step Latent Class Analysis (LCA) with covariates (socio-psychological and lifestyle elements) and distal outcomes (adaptive behaviour). A household survey (n = 1,753) conducted between June and July 2020 in 11 cities in Saxony, Germany, was used.

The preliminary result shows that socio-psychological and cultural factors that influence individual decision-making on proactive adaptive behaviour co-vary with social classes based on their resource endowment. It also revealed that the lower class tends to have less implementation of costly adaptation methods, for example, structural measures on housing, while less costly measures did not make a significant difference. As a result, we recommend that, in addition to the lack of material endowment, which can be associated with an increased risk of exposure, individual inaction of protective behaviour motivated by socio-psychological traits be considered for social vulnerability.

How to cite: Han, S., Masson, T., Köhler, S., and Kuhlicke, C.: Bridge the gap: Linking social vulnerability and adaptive behaviour, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5148, https://doi.org/10.5194/egusphere-egu23-5148, 2023.

EGU23-5611 | ECS | Posters on site | NH9.2

A traffic prediction framework under extreme weather combined disaster knowledge and deep learning 

Jiting Tang and Saini Yang

Studying the spatiotemporal patterns of urban road traffic under extreme weather is a key step to building a climate-resilient city. Although existing researches model and simulate traffic states from different perspectives, the traffic forecasting of the urban road networks under extreme weather is seldom addressed. In this paper, a novel Knowledge-driven Attribute-augmented Attention Spatiotemporal Graph Convolutional Network framework is proposed to predict urban road traffic under wind and rain especially in tropical cyclone disasters. Considering the disaster conditions, we model the external dynamic hazard attributes and static environment attributes, and designed an attribute-augmented unit to encode and integrate these factors into the deep learning model. The model is combined with the graph convolutional network (GCN), the gated recurrent unit (GRU), and the attention mechanism. Experiments demonstrate that the predictability of traffic speed can be greatly increased by supplementing the disaster-related factors, the prediction accuracy reaches 0.79. The proposed approach outperforms baselines by 12.16%-31.67% on real-world Shenzhen’s traffic datasets. The model also performs robustly on different road vulnerabilities and hazard intensities. The model errors are mainly occurred in the early peak with extreme wind and rain and the coastal area in the southeast of Shenzhen because of the greater uncertainty. The framework and findings provide a valuable reference for the decision-making of traffic management and control prior to a disaster to alleviate traffic congestion and reduce the negative impact of disasters.

How to cite: Tang, J. and Yang, S.: A traffic prediction framework under extreme weather combined disaster knowledge and deep learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5611, https://doi.org/10.5194/egusphere-egu23-5611, 2023.

EGU23-6810 | ECS | Posters on site | NH9.2

Conceptualizing the long-term interactions between climate services and adaptation to hydrometeorological extremes 

Riccardo Biella, Sina Khatami, Luigia Brandimarte, Maurizio Mazzoleni, and Giuliano Di Baldassarre

Climate services are expected to deliver better climate adaptation by providing decision-makers with timely, salient, credible, legitimate, and accessible climate information. Nonetheless, climate services’ impact on long-term adaptation remains poorly understood due to their ambiguous protocols, quality standards, and inadequate monitoring and evaluation processes.

The aim of this study is to present the underpinnings of a framework representing the causal mechanisms and feedback interactions between adaptation to hydrometeorological extremes, i.e. floods and droughts, and climate services among the partner living labs of the I-CISK project (https://icisk.eu). To this end, a qualitative investigation based on interviews and surveys of the living labs’ stakeholders is performed. Following, the findings from the qualitative analysis are iteratively discussed with the stakeholders and presented as a causal loop diagram, highlighting feedback loops in the coupled human-climate system. Finally, the emerging dynamics are described using system archetypes.

This research offers a systemic tool for evaluating the long-term dynamics of adaptation to hydrometeorological extremes while building the bases for further research in the living labs. Moreover, it shows the efficacy of system dynamics tools for informing adaptive policy-making.

How to cite: Biella, R., Khatami, S., Brandimarte, L., Mazzoleni, M., and Di Baldassarre, G.: Conceptualizing the long-term interactions between climate services and adaptation to hydrometeorological extremes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6810, https://doi.org/10.5194/egusphere-egu23-6810, 2023.

EGU23-7967 | Posters on site | NH9.2

Social media, vulnerability, and risk perception: three main points for geological disaster management 

Olga Nardini, Stefano Morelli, Veronica Pazzi, and Sara Bonati

Social media have the potential to significantly influence the disaster risk understanding of natural events of climatic and geological origin, e.g., earthquakes, volcanic eruptions and landslides. Given their considerable diffusion, nowadays they represent a valid support during emergency management processes thanks to their multiple uses in all the different phases of the disaster cycle. The presented results have been achieved carrying out a literature review in the framework of the European H2020 project LINKS ('Strengthening links between technologies and society for European disaster resilience') which aims to strengthen the link between technology and society to improve resilience in four European countries associated with five different risk scenarios. The aim of this research was to investigate how social media influence and impact vulnerability and risk perception and how the increased use of social media as a communication tool during a disaster is shaped by the way the two concepts interact and are conceptualised. The main results are that through social media, it is possible to raise people's awareness of the disaster, also by working on each individual's trust in those who provide information, but also to disseminate useful information and alerts to the population to keep abreast of real-time events, to connect citizens with each other in order to reduce distances and provide psychological support, and to create a social network for those in need. Additionally, social media can be used to manage an emergency and coordinate volunteer actions. The concepts of vulnerability and risk perception are extremely important to be considered when talking about geological hazards and disasters. They are two interconnected concepts that need to be pursued hand in hand in emergency management. The main challenges and factors impacting the use of social media concern access, quality and reliability of information, trust, and awareness of the news being provided, but also personal experience and geographical, social and demographic factors that may influence the way information is perceived and understood. The perception of geological risks directly influences people's preparedness and the way they act, helping anyone to understand the scope of the event and the potential risks that could occur, in order to make informed decisions on how to react. Furthermore, a real understanding of vulnerability influences the resilience of local communities in relation to disasters and can in turn be influenced using social media. Social media can also amplify public fear and concern about the disaster, especially if there is a lot of misinformation or sensationalism about the event. This can lead to an overestimation of risks and an increased sense of vulnerability among the population. These results could be helpful in identifying possible methods and approaches to study these issues in the future.  

How to cite: Nardini, O., Morelli, S., Pazzi, V., and Bonati, S.: Social media, vulnerability, and risk perception: three main points for geological disaster management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7967, https://doi.org/10.5194/egusphere-egu23-7967, 2023.

Despite major advancements in climate modeling, weather forecasting, and emergency preparedness, deadly floods continue to have a global reach, impacting Eastern Kentucky, USA (July 2022), Assam, India (2022), Cape Town, South Africa (2022), and Insul, Germany (July 2021) to name just a few. The goal of this work is to quantify and forecast in near-real time a flood’s impact at high spatial resolution by estimating how a household’s accessibility to critical infrastructure changes during and immediately after a storm. Our approach consists of a static transportation assignment cost function that solves for the user equilibrium traffic solution. By overlaying the road network with a near-real-time pluvial and fluvial inundation estimate, we estimate the degree to which flooding impacts households’ likely travel patterns to critical resources. The output consists of demand information on both the road and resource infrastructure networks, which we translate into resiliency and redundancy metrics. Our goal for this model is for it to be able to be rapidly deployed across the USA and potentially abroad to better serve communities who would otherwise not have access to such research and information tools. We present a case-study for Austin, Texas as a proof of concept and to highlight the critical decision-making information our approach can provide to those who need it most including emergency responders, flood managers, and residents themselves. Through this network approach, we can estimate who loses access to critical resources completely, whose access has diminished, how resource distribution is or isn’t equitable, hot spot nodes to prioritize remediation, and more. Our approach uses only open-source information including infrastructure, Earth observation, and point measurement data in our multilayer network. This data requirement allows our model to potentially be applicable in numerous regions across the globe. Our future work will explore using the network insights from this model in a dynamic model of adaptive capacity and human infrastructure. This will provide further insights on socio-hydrological interactions and how varying emergency response policies, government interventions, and human trends might impact the recovery trajectories of different communities.

How to cite: Preisser, M., Passalacqua, P., and Bixler, R. P.: A network-based disaster resilience metric for estimating individuals’ loss of access to critical resources during flooding, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9923, https://doi.org/10.5194/egusphere-egu23-9923, 2023.

EGU23-10110 | Posters on site | NH9.2

Testing Spatial Out-of-Sample Area of Influence for Grain Forecasting Models:  How does out of Spatial Out-of-Sample AoI Change through the Season?  

Frank Davenport, Shrad Shukla, Donghoon Lee, Patrese Anderson, Greg Husak, and Chris Funk

The potential for predictive models based on earth observations (EO) and survey data to assist in famine early warning and other development applications is rapidly growing. However, while the spatial-temporal extent of EO data is complete, high quality survey data is generally limited in spatial and temporal scope. The perennial question in all predictive analysis, and especially when trying to move from research to operational application in the developing world is: If we create a forecast model from region A (based on observed outcomes) can we apply the same model in region B, where we do not observe or have limited observations of those outcomes? Prior research has proposed examining the Area of Influence (AoI) based on structurally similar characteristics in the EO predictors. We expand on and evaluate this approach in the context of grain yield forecasting in Sub-Saharan Africa (SSA). Specifically, we evaluate an AoI methodology established for generating raster surfaces and apply it to vector supported grain data.  We ask the following questions: What are the key characteristics that make a forecast fit for one country work in another country? Can pooling models across multiple countries provide more accurate out-of-sample estimates than a model fit to one country or district? Does AoI change through the season? Does a model fit for in early season have the same AoI as a model fit late in the season.

 

How to cite: Davenport, F., Shukla, S., Lee, D., Anderson, P., Husak, G., and Funk, C.: Testing Spatial Out-of-Sample Area of Influence for Grain Forecasting Models:  How does out of Spatial Out-of-Sample AoI Change through the Season? , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10110, https://doi.org/10.5194/egusphere-egu23-10110, 2023.

EGU23-14314 | ECS | Orals | NH9.2

Current and future evolution of drought risk in Ethiopia: A framework to inform disaster risk reduction and climate change adaptation policies 

Domenico Bovienzo, Sepehr Marzi, Letizia Monteleone, Jaroslav Mysiak, and Jeremy Pal

Climate change is projected to increase the frequency and intensity of future droughts particularly affecting the most low-income countries directly dependent on local rainfed food security and livelihoods. Drought risk and its related impacts depend on the drought hazard, the exposure and the vulnerability of the different socioeconomic sectors and/or ecosystems as well as the adaptive capacity of affected locations. The Horn of Africa, which includes Ethiopia, is currently experiencing one of the most severe droughts in the last 40 years. This study applies a storyline approach to investigate changes in drought risk for Ethiopia combining vulnerability, hazard and adaptive capacity information for current and future projected climatic and socio-economic conditions using a subnational level composite indicator. For our analysis, we define drought based on the Standardised Precipitation-Evapotranspiration Index (SPEI) which characterises the deficits in local water availability based on the precipitation and potential evapotranspiration. SPEI is computed using bias corrected Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) project based on the Coupled Model Intercomparison Project Phase 6 (CMIP6). The Drought vulnerability assessment is carried out combining exposure, adaptive capacity and sensitivity indicators, using INFORM index developed by the Joint Research Centre of the European Commission to support humanitarian crisis and disaster decision-making. The analysis shows that future drought will increase people in need of food assistance both under current population and future population projections. If humanitarian aid and assistance are maintained at recent historical levels, these findings show a substantial increase in the required amounts. These conditions are exasperated when humanitarian access is impeded by local conditions such as the current conflict in Ethiopia, when imports are reduced by crises such as those associated with the Russian invasion of the Ukraine, and by pandemics such as COVID-19. Climate change mitigation is shown to reduce the vulnerability of Ethiopia through a reduction in drought hazard frequency and intensity. The framework presented in this study can be used as a policymaking tool to provide information on how to better prioritize future loss and damage funds and adaptation and mitigation investments to reduce population vulnerability and exposure.

How to cite: Bovienzo, D., Marzi, S., Monteleone, L., Mysiak, J., and Pal, J.: Current and future evolution of drought risk in Ethiopia: A framework to inform disaster risk reduction and climate change adaptation policies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14314, https://doi.org/10.5194/egusphere-egu23-14314, 2023.

EGU23-16045 | Posters on site | NH9.2

Compound events from the databases 

Carlo De Michele, Fabiola Banfi, and Viola Meroni

Compound climate-related (or weather-related) events are complex events characterized by the interactions between various physical processes across multiple spatial and temporal scales, generated by meteorological variables, and provoking extreme impacts. Compound climate-related events often include the joint occurrence of multi-hazards like landslides and floods, or heatwaves, droughts and wildfires.

In literature, databases of natural hazards are in general single hazard, like databases of floods (European Flood Database, AVI database), landslides (Global Fatal Landslide Database , AVI database), droughts (European Drought Observatory).

The assessment and understanding of compound events requires an integrated perspective, with the integration of data from multiple variables, combining multiple databases.

In this presentation, we try to address this emerging need, illustrating a possibility of building a compound events database, and presenting some examples.

How to cite: De Michele, C., Banfi, F., and Meroni, V.: Compound events from the databases, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16045, https://doi.org/10.5194/egusphere-egu23-16045, 2023.

EGU23-16481 | ECS | Orals | NH9.2

Limits of adaptation to climate-related risks in the Peruvian Andes: A case study in the Río Santa and Salkantay catchments 

Isabel Hagen, Sanne Schnyder, Inés Yanac León, Sirkku Juhola, Veruska Muccione, and Christian Huggel

The highly populated Peruvian Andes is impacted by a multitude of climate-related risks. Comprehensive climate risk management and adaptation measures can bring risks down to an acceptable level, as determined by the local population. However, increased magnitude and frequency of risks, together with the possibility of reaching adaptation limits, are hindering risk reduction. Adaptation limits are reached due to a complex interplay between socio-economic, cultural, political, institutional, technical and bio-physical factors. Whilst there is an emerging conceptual understanding of adaptation limits, there is little empirical research investigating limits in real-world settings.

The aim of this study is to identify and define the limits of adaptation on a local scale, which limits are approaching and which have already been reached. We investigate the limits of adaptation in two catchments in the Peruvian Andes. The most prevalent climate-related risks in these two regions are from glacial lake outburst floods, landslides, shifts in precipitation patterns, and glacier retreat. We use a conceptual framework developed by Juhola et al. (unpublished), and determine adaptation limits and the intolerable risks space through investigating human wellbeing, governance systems, ecosystem functions and climate hazards in the two localities. The data was collected through a thorough literature review, together with 50 semi-structured interviews conducted in May-July 2022; 28 with local residents in the Río Santa and Salkantay catchments, and 22 interviews with experts from 14 different local and national institutions and NGOs. The interviews were analysed in Atlas.ti using a content analysis approach. We emphasize the focus on basic needs and wellbeing, to encompass not only what are obvious losses from climate impacts, such as loss of life or livelihood, but also more intangible losses, such as limited mobility, loss of a social network, or loss of local knowledge. The conclusions of this study can help decision makers and practitioners improve the positive impact of future risk management and adaptation projects in the two regions.

How to cite: Hagen, I., Schnyder, S., Yanac León, I., Juhola, S., Muccione, V., and Huggel, C.: Limits of adaptation to climate-related risks in the Peruvian Andes: A case study in the Río Santa and Salkantay catchments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16481, https://doi.org/10.5194/egusphere-egu23-16481, 2023.

Societal resilience is built upon effective risk transfer strategies. For most developed countries in the world, insurance and reinsurance continues to be the most effective method of sharing this burden and reducing the need for state intervention. However, it’s becoming increasingly clear that the probabilistic (CAT) models used to price natural hazard risk are struggling to capture the increasingly dynamic changes of the climate and our level of interconnection.

The Gallagher Research Centre (GRC) was established recently to support reinsurance stakeholders navigate an increasingly complex risk management landscape. Though probabilistic and deterministic natural catastrophe models were first pioneered in the early 1960’s (Friedman, 1984) it wasn’t until the 1990’s, and the combined losses from Hurricane Andrew ($27.3 billion USD) and the Northridge Earthquake ($25 billion USD) that such models began to be fully embraced by the mainstream reinsurance industry (Reinsurance News, 2023).

While significant and continued progress has been made in the precision and scalability of these models in the last 30 years, climate change and an increasingly globalized world mean the relative impacts of natural hazards are becoming far more complex and diverse than most models successfully capture. This leads to an increasing basis risk and potentially less utility of the models. This session will outline the growing research concerns of focus for the GRC, including how can stochastic models built around historical periods truly capture the non-stationarity of risk we see occurring for wind and flood perils? Should models capture the seasonal dependencies between perils to more accurately price aggregate insurance risk? Should future model development focus on the compounded scenarios? 

 

Friedman, D. G. (1984). Natural hazard risk assessment for an insurance program. Geneva Papers on Risk and Insurance, 57-128.

Reinsurance News (2023). Last accessed 10/01/2023. https://www.reinsurancene.ws/insurance-industry-losses-events-data/

How to cite: Willis, I. and Papaspiliou, M.: The urgency for (re)insurance probabilistic (CAT) models to capture the dynamics of an increasingly interconnected world, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17449, https://doi.org/10.5194/egusphere-egu23-17449, 2023.

EGU23-1524 | Orals | SM1.2

Insights from the spatial variability of (multiple) uncertainties: Earth-ice interactions for East Antarctica  

Anya Reading, Tobias Stål, Ross Turner, Felicity McCormack, Ian Kelly, Jacqueline Halpin, and Niam Askey-Doran

Uncertainty, as applied to geophysical and multivariate initiatives to constrain aspects of Earth-ice interactions for East Antarctica, provides a number of approaches to appraise and interrogate research results.  We discuss a number of use cases: 1) making use of multiple uncertainty metrics; 2) making comparisons between spatially variable maps of inferred properties such as geothermal heat flow; 3) extrapolating crustal structure given the likelihood of tectonic boundaries; and 4) providing research results for interdisciplinary studies in forms that facilitate ensemble approaches.

 

It proves extremely useful to assess a research finding, such as a mapped geophysical property, through multiple uncertainty metrics (e.g., standard deviation, information entropy, data count).  However, a thoughtful appraisal of multiple metrics could be misleading, i.e., potentially not useful in isolation, in a case where there are significant unquantified uncertainties.  Uncertainties supplied with the mapped geophysical properties can potentially be extended to capture this broader range, but that range in turn could become less helpful as the fine detail in the quantified uncertainty will be lost.

 

In the case of a property such as geothermal heat flow, indirectly determined for East Antarctica, insights can be drawn by subtracting a forward model map from an empirically determined result (e.g. Aq1) to yield the non-steady state components excluded in the forward model.  In such investigations, including the maximum and minimum possible difference between maps is essential to understand which non-steady state anomalies are real, and which could be artifacts attributable to (quantified) uncertainty.

 

In further use cases, we show how the few available seismic measurements that constrain the crust and upper mantle structure of East Antarctica can be placed in context, given the likelihood of major tectonic boundaries beneath the ice, and link this to published constraints on the seismic structure (and hence, rheology) of the deeper lithosphere.  In terms of how the solid Earth interacts with the ice sheet above, the impact of fine scale-length variations in spatial uncertainty may be investigated in relation to, for example, ice sheet modelling. For a large region and relatively unexplored region such as East Antarctica, uncertainty yields many and varied insights. 

How to cite: Reading, A., Stål, T., Turner, R., McCormack, F., Kelly, I., Halpin, J., and Askey-Doran, N.: Insights from the spatial variability of (multiple) uncertainties: Earth-ice interactions for East Antarctica , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1524, https://doi.org/10.5194/egusphere-egu23-1524, 2023.

EGU23-2190 | ECS | Posters on site | SM1.2

Locating earthquake hypocenter using first arrivals and depth phase in 3D model at local and regional distances 

Tianjue Li, Jing Chen, and Ping Tong

Precise determination of earthquake hypocenter (longitude, latitude and depth) and its origin time is of fundamental importance for not only understanding the seismogenic process but also revealing the Earth’s interior structure. Instrumental coverage plays the first-order role in determining earthquake locations. For earthquakes that occurred in the continental interior, it is favorable to have seismic stations with full azimuthal coverage; nonetheless, precise determination of earthquake depth is often challenging due to its tradeoff with earthquake origin time. The situation is even worse for earthquakes that occurred in offshore regions, e.g., Pacific ring of fire, because regional seismic stations are mostly installed on the continent. To deal with those challenges aforementioned, we propose to constrain the earthquake hypocenter by jointly using first arrivals (P and S waves) and depth phase traveltimes. The theoretical travelling times of these phases are precisely and efficiently calculated in 3D velocity model through solving the Eikonal equation. Once the earthquake hypocenter is well constrained, we further improve the accuracy of the origin time. We tested and verified the proposed earthquake location strategy in the Ridgecrest area (southern California), which serves as an end member of continental setting, and central Chile, which serves as another end member of offshore setting. The station coverage is complete in the Ridgecrest area. We have identified and picked first arrivals and sPL phases at local distances. On the contrary, seismic stations are only installed on the continent in central Chile. We have identified and picked first arrivals and sPn phases at regional distances. Determined earthquakes have comparable location accuracy as the regional catalog in the horizontal plane, while the depth uncertainty has been reduced greatly. Our study shows that incorporating depth phases into the earthquake location algorithm together with first arrivals can greatly increase earthquake location accuracy, especially earthquake depth, which will lay the solid foundation for wide-scope topics in earth science studies.

How to cite: Li, T., Chen, J., and Tong, P.: Locating earthquake hypocenter using first arrivals and depth phase in 3D model at local and regional distances, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2190, https://doi.org/10.5194/egusphere-egu23-2190, 2023.

EGU23-2930 | Orals | SM1.2

Defining spatial uncertainty in main field magnetic models 

Ciaran Beggan and William Brown

Models of the Earth’s main magnetic field, such as the International Geomagnetic Reference Field (IGRF), are described by spherical harmonic (Gauss) coefficients to degree and order 13, which allows the continuous evaluation of the field at any location and time on or above the surface. They are created from satellite and ground-based magnetometer data and describe the large-scale variation (spatial scale of 3000 km) of the magnetic field in space and time under quiet conditions.

In its technical form, the model is a spectral representation and thus its formal uncertainty (as a wavelength) is of limited advantage to the spatial value expected by the average user.  To address this, we estimated the large-scale time-invariant spatial uncertainty of the IGRF based on the globally averaged misfit of the model to ground-based measurements at repeat stations and observatories between 1980 and 2021. As an example, we find the 68.3% confidence interval is 87 nT in the North (X) component, 73 nT in the East (Y) component and 114 nT in vertical (Z) component. These values represent an uncertainty of around 1 part in 500 for the total component which, for the (average) compass user is well below instrumental detectability.

For advanced users, in applications such as directional drilling, higher resolution models (<30 km) are required and the associated uncertainties are thus further divided into random and global as well as correlated and uncorrelated parts. However, the distribution of errors is Laplacian not Gaussian and communicating the subtleties of long-tailed distributions to end-users is often a difficult task. We describe the different types of uncertainties for magnetic field models and how these are used (or not) in industrial applications.

How to cite: Beggan, C. and Brown, W.: Defining spatial uncertainty in main field magnetic models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2930, https://doi.org/10.5194/egusphere-egu23-2930, 2023.

EGU23-4074 | Posters on site | SM1.2

Using information entropy to optimise and communicate certainty of continental scale tectonic models 

Tobias Stål, Anya M. Reading, Matthew J. Cracknell, Jörg Ebbing, Jacqueline A. Halpin, Ian D. Kelly, Emma J. MacKie, Mohamed Sobh, Ross J. Turner, and Joanne M. Whittaker

Antarctic subglacial properties impact geothermal heat, subglacial sedimentation, and glacial isostatic adjustment; critical parameters for predicting the ice sheet's response to warming oceans. However, the tectonic architecture of the Antarctic interior is unresolved, with results dependent on datasets or extrapolation used. Most existing deterministic suggestions are derived from qualitative observations and often presented as robust results; however, they hide possible alternative interpretations.

 

Using information entropy as a measure of certainty, we present a robust tectonic segmentation model generated from similarity analysis of multiple geophysical and geological datasets. The use of information entropy provides us with an unbiased and transparent metric to communicate the ambiguities from the uncertainties of qualitative classifications. Information theory also allows us to test and optimise the methods and data to evaluate how choices impact the distribution of alternative output maps. We further discuss how this metric can quantify the predictive power of parameters as a function of regions with different tectonic settings.

How to cite: Stål, T., Reading, A. M., Cracknell, M. J., Ebbing, J., Halpin, J. A., Kelly, I. D., MacKie, E. J., Sobh, M., Turner, R. J., and Whittaker, J. M.: Using information entropy to optimise and communicate certainty of continental scale tectonic models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4074, https://doi.org/10.5194/egusphere-egu23-4074, 2023.

Uncertainties of geological structural geometry constructed based on seismic reflections can stem from data acquisition, processing, analysis, or interpretation. Uncertainties arising from structural interpretations and subsequent estimates of geological slip have been particularly less quantified and discussed. To illustrate the implications of interpretation uncertainties for seismic potential and structural evolution, I use an example of a shear fault-bend fold in the central Himalaya. I apply a simple solution from the kinematic model of shear fault-bend folding to resolve the geological input slip of given structure and then compare the result with a previous study to show how differences in structural interpretations could impact dependent conclusions. The findings show that only a little variance in interpretations owing to subjectivity or an unclear seismic image could yield geological slip rates differing by up to about 10 mm/yr, resulting in significantly different scenarios of seismic potential. To reduce unavoidable subjectivity, this study also suggests that the epistemic uncertainty in raw data should be included in interpretations and conclusions.

How to cite: Hu, W.-L.: How do differences in interpreting seismic images affect estimates of geological slip rates?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4591, https://doi.org/10.5194/egusphere-egu23-4591, 2023.

EGU23-5116 | Posters on site | SM1.2

Realistic uncertainties for Surface Wave dispersion curves and their influences on 1D S-wave profiles 

Nicola Piana Agostinetti and Raffaele Bonadio

Surface wave (SW) dispersion curves are widely used to retrieve 1D S-wave profiles of the Earth at different depth-scale, from local to global models. However, such models are generally constructed with a number of assumptions which could bias the final results. One of the most critical issue is the assumption of a diagonal error covariance matrix as representative of the data uncertainties. Such first-order approximation is obviously wrong for any SW practitioner, given the smoothness of dispersion curves, and could lead to overestimate the information content of the dispersion curves themselves.

In this study, we compute realistic errors (i.e. represented by a non-diagonal error covariance matrix) for Surface Wave dispersion curves, computed from earthquakes data. Given the huge amount of data available worldwide, realistic errors can be easily estimated using empirical formulations (i.e. repeated measurements of the same quantity). Such approach leads to the computation of a full-rank empirical covariance matrix which can be used as input in standard Likelihood computation (e.g. to drive a Markov chain Monte Carlo, McMC, sampling of a Posterior Probability Distribution, PPD, in case of a Bayesian workflow).

We apply our approach to field measurements recorded along one decade in the British Islands. We first compute the empirical error covariance matrices for 12 two-stations dispersion curves, under different assumptions, and, then, we invert the curves using a standard trans-dimensional McMC algorithm, to find relevant 1D S-wave profiles for each curve. We perform both an inversion considering the full-rank error covariance matrix, and one inversion using a diagonal version of the same matrix. We compare the retrieved profiles with published results. Our main finding is that 1D profiles obtained using a full-rank error covariance matrix are often similar to profiles obtained with a diagonal matrix and published profiles obtained with different approaches. However, relevant differences occur in a number of cases, which leads to potentially question some details in 1D models. Given the extreme easiness of computing the full-rank error covariance matrix, we strongly suggest to include realistic error computation in SW studies.

How to cite: Piana Agostinetti, N. and Bonadio, R.: Realistic uncertainties for Surface Wave dispersion curves and their influences on 1D S-wave profiles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5116, https://doi.org/10.5194/egusphere-egu23-5116, 2023.

EGU23-5661 | ECS | Posters on site | SM1.2

3-D joint inversion of surface wave and receiver functions based on the Markov chain Monte Carlo 

Kuan-Yu Ke, Frederik Tilmann, Trond Ryberg, and Stefan Mroczek

Geophysical inverse problems (seismic tomography) are often significantly underdetermined meaning that a large range of parameter values can explain the observed data well within data uncertainties. Markov chain Monte Carlo (McMC) algorithms based on Voronoi cell parameterizations have been used for quantifying uncertainty in seismic tomography for a number of years. Since surface waves constrain absolute shear velocities and receiver functions (RFs) image discontinuities beneath receiver locations, joint inversion of both data types based on McMC become a popular method to reveal the structure near Earth's surface with uncertainty estimates.

 

Joint inversion is usually performed in two steps: first invert for 2-D surface wave phase (or group) velocity maps and then invert 1-D surface wave and RFs jointly to construct a 3-D spatial velocity structure. However, in doing so, the valuable information of lateral spatial variations in velocity maps and dipping discontinuities in RFs may not be preserved and lead to biased 3-D velocity structure estimation. Hence, the lateral neighbors in the final 3-D model typically preserve little of the 2-D lateral spatial correlation information in the phase and group velocity maps.

 

A one-step 3-D direct inversion based on the reversible jump McMC and 3-D Voronoi tessellation is proposed to improve the above issues by inverting for 3-D spatial structure directly from frequency-dependent traveltime measurements and RFs. We take into account the dipping interfaces according to the Voronoi parameterisation, meaning that back azimuth and incidence angle of individual RFs must be taken into account. We present synthetic tests demonstrating the method. Individual inversion of surface wave measurements and RFs show the limitation of inverting the two data sets separately as expected: surface waves are poor at constraining discontinuities while RFs are poor at constraining absolute velocities. The joint solution gives a better estimate of subsurface properties and associated uncertainties. Compared to two-step inversion which may produce bias propagating between two steps and lose valuable lateral structure variations, the direct 3-D direct inversion not only produces more intuitively reasonable results but also provides more interpretable uncertainties.

How to cite: Ke, K.-Y., Tilmann, F., Ryberg, T., and Mroczek, S.: 3-D joint inversion of surface wave and receiver functions based on the Markov chain Monte Carlo, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5661, https://doi.org/10.5194/egusphere-egu23-5661, 2023.

EGU23-8679 | Posters on site | SM1.2

Is Hamiltonian Monte Carlo (HMC) really worth it? An alternative exploration of hyper-parameter tuning in a time-lapse seismic scenario 

Alison Malcolm, Maria Kotsi, Gregory Ely, and Jean Virieux

Determining if uncertainty quantification is worth it or not is closely related to how that uncertainty is computed and the associated computational cost. For seismic imaging, it is typically done using Markov chain Monte Carlo algorithms (McMC). Solving an inverse problem using McMC means exploring and characterizing the ensemble of all plausible models through more or less point-wise random walk in the data misfit landscape. This is typically done using Bayes’ theorem via the computation of a posterior probability density function. Even though this can sound naively simple, it can come with a significant computational burden given the dimension of the problem to be solved and the expense of the forward solver. This is because as the number of dimensions grow, there are exponentially more possible guesses the algorithm can make, while only a few of these models will be accepted as plausible. More advanced uncertainty quantification methods such as Hamiltonian Monte Carlo (HMC) could be beneficial because they can handle higher dimensions because efficient sampling of the model space through pseudo-mechanical trajectories in the data misfit landscape is expected. In order for an HMC algorithm to efficiently sample the model space of interest and provide meaningful uncertainty estimates, three hyper-parameters need to be tuned for trajectory design: the Leapfrog steps L, the Leapfrog stepsize ε, and the Mass Matrix M. There has been already work showing how one can choose L and ε; however designing the appropriate M is far more challenging. We consider a time-lapse seismic scenario and use a local acoustic solver for fast forward solutions. We then use Singular value decomposition, in the vicinity of the true model, to transform our time-lapse optimal model to a system of normal coordinates and use only a few of the eigenvalues and eigenvectors of the Hessian as oscillators. By doing so, we can efficiently understand the impact of the initial conditions and the choice of M and gain insight on how to design M in the standard system. This gives us an intuitive way to understand the mass matrix, allowing us to determine whether gains from the HMC algorithm are worth the cost of determining the parameters.

How to cite: Malcolm, A., Kotsi, M., Ely, G., and Virieux, J.: Is Hamiltonian Monte Carlo (HMC) really worth it? An alternative exploration of hyper-parameter tuning in a time-lapse seismic scenario, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8679, https://doi.org/10.5194/egusphere-egu23-8679, 2023.

EGU23-8767 | ECS | Posters on site | SM1.2

Can Normalizing Flows make Uncertainty Quantification Practical for Time-Lapse Seismic Monitoring 

Changxiao Sun, Alison Malcolm, and Rajiv Kumar

Due to the nonlinearity of inversion as well as the noise in the data, seismic inversion results certainly have uncertainties. Whether quantifying these uncertainties is useful depends at least in part on the computational cost of computing them.  Bayesian techniques dominate uncertainty quantification for seismic inversion.  The goal of these methods is to estimate the probability distribution of the model parameters given the observed data. The Markov Chain Monte Carlo algorithm is widely employed for approximating the posterior distribution. However, generating the posterior samples by combining the prior and the likelihood is intractable for large problems and challenging for smaller problems. We apply a machine learning method called normalizing flows, which consists of a series of invertible and differentiable transformations, as an alternative to the sampling-based methods. In our work, the normalizing flows method is combined with full waveform inversion(FWI) using a numerically exact local solver to quantify the uncertainty of time-lapse changes. We integrate uncertainty quantification(UQ) and FWI by estimating UQ on the images generated by FWI making it computationally practical. In this way, a reasonable posterior probability distribution is directly predicted and produced by transforming from a normal distribution, measuring the amount and spread of variation in FWI images by sample mean and standard deviation. In our numerical results, the method for calculating the posterior distribution of the model is verified to be practical and advantageous in terms of effectiveness.

How to cite: Sun, C., Malcolm, A., and Kumar, R.: Can Normalizing Flows make Uncertainty Quantification Practical for Time-Lapse Seismic Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8767, https://doi.org/10.5194/egusphere-egu23-8767, 2023.

EGU23-10003 | ECS | Orals | SM1.2

Variational Experimental Design Methods for Geophysical Applications  

Dominik Strutz and Andrew Curtis

The design of geophysical surveys or experiments (henceforth, the experimental design) significantly influences the uncertainty in scientific results that can be inferred from recorded data. Typical aspects of experimental designs that can be varied are locations of sensors, sensor types, and the modelling or data processing methods to be applied to recorded data. To tighten constraints on the solution to any inverse or inference problem, and thus to rule out as many false possibilities as possible, the design should be optimised such that it is practically achievable within cost and logistical constraints, and such that it maximises expected post-experimental information about the solution. 

Bayesian experimental design refers to a class of methods that use uncertainty estimation methods to quantify the expected gain in information about target parameters provided by an experiment, and to optimise the design of the experiment to maximise that gain. Information gain quantifies the decrease in uncertainty caused by observing data. Expected information gain is an estimate of the gain in information that will be offered by any particular design post-experiment. Bayesian experimental design methods vary the design so as to maximise the expected information gain, subject to practical constraints. 

We introduce variational experimental design methods that are novel to geophysics, and discuss their benefits and limitations in the context of geophysical applications. The family of variational methods relies on functional approximations of probability distributions, and in some cases, of the model-data relationships. They can be used to design experiments that best resolve either all model parameters, or the answer to a specific question about the system studied. Their potential advantage over some other design methods is that finding the functional approximations used by variational methods tends to rely more on optimisation theory than the more common stochastic uncertainty analysis used to approximate Bayesian uncertainties. This allows the wealth of understanding of optimisation methods to be applied to the full Bayesian design problem. 

Variational design methods are demonstrated by optimising the design of an experiment consisting of seismometer locations on the Earth’s surface, so as to best estimate seismic source parameters given arrival time data obtained at seismometers. By designing separate experiments to constrain the hypocentres and epicentres of events, we show that optimal designs may change substantially depending on which questions about the subsurface we wish the experiment to help us to answer. 

By accounting for differing expected uncertainties in travel time picks depending on the picking method used, we demonstrate that the data processing method can be optimised as part of the design process, provided that expected uncertainties are available from each method.

How to cite: Strutz, D. and Curtis, A.: Variational Experimental Design Methods for Geophysical Applications , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10003, https://doi.org/10.5194/egusphere-egu23-10003, 2023.

EGU23-11807 | Orals | SM1.2

Why probabilistic models are often true, but can be either useful or useless. 

Thomas Mejer Hansen and Rasmus Bødker Madsen

“All models are wrong but some are useful” (most often credited to George Cox) is a commonly used aphorism, probably because it resonates with some truth to many. We argue though, that it would be more correct to say “All deterministic models are wrong but some are useful “. Here, a deterministic model refers to any single, and in some quantitative way ‘optimal’ model, typically the results of minimizing some objective function. A deterministic model may be useful to use as a base for making decisions, but, it may also lead to disastrous results. The real disturbing issue with deterministic models is that we do not know whether it is useful for a specific application, because of a lack of uncertainties.

On the other hand, a probabilistic model, that is described by a probability density, or perhaps by many realizations of a probability density, can represent in principle arbitrarily complex uncertainty. In the simplest case where the probabilistic model is represented by a maximum entropy uncorrelated uniform distribution, one can say that “The simplest probabilistic model is true but not very useful.“.  It is true in the sense that the real Earth model is represented by the probabilistic model, i.e. it is a possible realization from the probabilistic model, but not very useful, as little to no information about the Earth can be inferred.

In an ideal case, a probabilistic model can be set up from a variety of different sources, such that it is both informative (low entropy), and consistent with an actual subsurface model in which case we can say “An informative probabilistic model can be true and also very useful.“. Any uncertainty in the probabilistic model can then be propagated to any other related uncertainty assessment using simple Monte Carlo methods. In such a case clearly, uncertainty is useful.

In practice though, when a probabilistic Earth model has been constructed from different sources (such as structural geology, well logs, and geophysical data) then one will often find that the uncertainty of each source of information will be underestimated, such that the combined model will describe too little uncertainty. This can lead to potentially worse decision-making than when using a deterministic model (that one knows is not correct), as one may take a decision related to a low probability of a risky scenario that may simply be related to the underestimation and/or bias of the uncertainty.

We will show examples of constructing both deterministic and probabilistic Earth models, based on a variety of geo-based information. We hope to convince the audience, that a probabilistic model can be designed such that it is consistent with the actual subsurface, and at the same time provides an optimal base for decision-makers and risk analysis.

In the end, we argue that: Uncertainty is not only useful but essential, to any decision-making, but also that it is of utmost importance that the underlying information is quantified in an unbiased way. If not, a probabilistic model may simply provide a complex base in which to take wrong decisions.

How to cite: Hansen, T. M. and Madsen, R. B.: Why probabilistic models are often true, but can be either useful or useless., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11807, https://doi.org/10.5194/egusphere-egu23-11807, 2023.

This work discusses the use of full waveform inversion (FWI) with fully nonlinear estimates of uncertainty, to monitor changes in the Earth’s subsurface due to dynamic processes. Typically, FWI is used to produce high resolution 2D and 3D static subsurface images by exploiting information in full acoustic, seismic or electromagnetic waveforms, and has been applied at global, regional and industrial spatial scales. To avoid the over-interpretation of poorly constrained parts of resulting subsurface images or models, it is necessary to know their uncertainty – the range of possible subsurface models that are consistent with recorded data and other pertinent constraints. Almost all estimates of uncertainty on the results of FWI approximate the model-data relationships by linearisation to make the calculation computationally efficient; unfortunately this throws those uncertainty estimates into question, since their raison d’etre is to account for possible model and data variations which are themselves related nonlinearly.

In a related abstract and associated manuscript we use variational inference to achieve the first Bayesian uncertainty analysis for 3D FWI that is fully nonlinear (i.e., involves no linearisation of model-data relationships: https://arxiv.org/abs/2210.03613 ). Variational inference refers to a class of methods that optimize an approximation to the probability distribution that describes post-inversion parameter uncertainties.

Here we extend those methods to perform nonlinear uncertainty analysis for 4D (time-varying 3D) FWI monitoring of the subsurface. Specifically we apply stochastic Stein variational gradient descent (sSVGD) to seismic data generated synthetically for two 3D seismic surveys acquired over a changing 3D subsurface structure based on the 3D overthrust model (Aminzadeh et al., 1997: SEG/EAGE 3-D Modeling Series No. 1). Iterated linearised inversion of each data set fails to image changes (~1%) in the wave speed of the medium, both when each inversion begins independently from the same (good) reference model, or when the best-fit model from inversion of the first survey’s data was used as reference model for the second inversion. Nonlinear inversion of each data set from the same prior distribution also fails to detect these ~1% changes. However, the changes can be imaged and their uncertainty estimated if variational methods applied to invert data from the second survey are initiated from their final state in the inversion of the first survey data. In addition, the methods then converge far more rapidly, compared to running each inversion independently.

We conclude that the probability distributions describing 3D seismic velocity uncertainty are sufficiently complex that the computations of 3D parameter uncertainty for each survey independently have not converged sufficiently to detect small 4D changes. However, the change in these probability distributions between surveys must be sufficiently small that the final solution found from the first survey could evolve robustly into the second survey solution, such that changes are resolved above the uncertainty using variational methods. Nevertheless, this change must be sufficiently complex that linearised methods can not evolve smoothly from one solution to the next, explaining why linearised methods fail, and highlighting why the estimation of nonlinear uncertainties is so important for imaging and monitoring applications.

 

How to cite: Curtis, A. and Zhang, X.: On Monitoring Changes in the Earth’s Subsurface using 4D Bayesian Variational Full Waveform Inversion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14914, https://doi.org/10.5194/egusphere-egu23-14914, 2023.

Determining the thermochemical structure of the mantle is crucial for understanding its evolution and dynamics. Temperature variations have long been known as important driving forces of mantle convection; however compositional differences can also influence dynamics. Additionally, compositional differences can act as indicators left behind by processes operating in the past. Both aspects have played a role in the ongoing discussions on the Large Low Shear Wave Velocity Provinces (LLSVP), the proposed Bridgmanite Enriched Ancient Mantle Structures (BEAMS) and the fate of subducted oceanic crust.

A prerequisite for determining compositional differences in terms of major oxides with geophysical techniques is a joint determination of several geophysical properties. A single geophysical property (density, velocity) could almost always be explained by temperature or composition variations alone – except in pathological edge cases. The geophysical signature of composition lies in the pointwise relation between properties. This pointwise relation can be distorted by spectral filtering or inversion smoothing and damping.

In this contribution, I parametrize the mantle as a collection of discrete spatial anomalies in terms of seismic velocity and density. Surface wave phase speed and satellite gravity data are used to constrain the anomalies. A transdimensional Monte Carlo Markov Chain method is used to generate ensembles of solutions that try to balance model complexity and data fit. An important aspect of this setup is that the two data sets used are complementary: While satellite gravity data are available (nearly) globally with homogeneous quality, coverage of phase speed data depends on the spatial distribution of seismic stations and large earthquakes. Conversely, the gravity field lacks true depth sensitivity, which surface wave data can provide by combining several frequencies.

I will present synthetic investigations that aim at determining how accuracy and coverage affect the simultaneous recoverability of seismic velocity and density.

How to cite: Szwillus, W.: Sensitivity of surface wave and gravity data to velocity and density structure in the mantle – insights from transdimensional inversion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15486, https://doi.org/10.5194/egusphere-egu23-15486, 2023.

EGU23-15776 | Orals | SM1.2

Assessing and reducing stratigraphic uncertainty in the subsurface: where are we standing? 

Guillaume Caumon, Julien Herrero, Thomas Bodin, and Paul Baville

Sedimentary strata are essential archives of the past conditions of the earth, and host significant natural resources in the subsurface. However, inferring the features of strata at depth (e.g., geometry, connectivity, physical or geological properties), remains a challenge prone to many uncertainties. Classically, the layers and their geometry are first interpreted from boreholes, geological outcrops and geophysical images, then layer properties can be addressed with geostatistical techniques and inverse methods. Theoretical models considering horizon depth uncertainty have been proposed decades ago, and geostatistical simulation can sample petrophysical uncertainties, but these approaches leave the number of layers fixed and are rely on conformable layering assumptions which are seldom met. We review some recent developments in well correlation in the frame of relative chronostratigraphy, which addresses the problem of locating potential gaps in the stratigraphic record. We also present some first results of the integration of the number of layers in inverse problems using a reversible jump Monte Carlo method. These two elements open interesting perspectives to jointly address topological, geometrical and petrophysical uncertainties at multiple scales in sedimentary basins. Although such uncertainties can have significant impact on quantitative geological and geophysical model forecasts, many computational challenges still lie ahead to appropriately sample uncertainties. Harnessing these challenges should open the way to finding, on a case-by-case basis, the suitable level of detail between detailed stratigraphic architectures and effective medium representations.

How to cite: Caumon, G., Herrero, J., Bodin, T., and Baville, P.: Assessing and reducing stratigraphic uncertainty in the subsurface: where are we standing?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15776, https://doi.org/10.5194/egusphere-egu23-15776, 2023.

EGU23-17147 | Orals | SM1.2

Addressing uncertainty in models for improved decision making 

Daniel Straub, Wolfgang Betz, Mara Ruf, Amelie Hoffmann, Daniel Koutas, and Iason Papaioannou

In science and engineering, models are used for making predictions. These predictions are associated with uncertainties, mainly due to limitations in the models and data availability. While these uncertainties might be reduced with further analysis and data collection, that is often not an option because of constrained resources. Whenever the resulting predictions serve as a basis for decision making, it is important to appraise the uncertainty, so that decision makers can understand how much weight to give to the predictions. In addition, performing uncertainty and sensitivity analysis at intermediate stages of a study can help to better focus the model building process on those elements that contribute most to the uncertainty. Decision sensitivity metrics, which are based on the concept of value of information, enable to identify which uncertainties most affect the conclusions drawn from the model outcomes. We have found that such decision sensitivity metrics can be a powerful tool to understand and communicate an acceptable level of uncertainty associated with model predictions.

In this contribution, we will discuss the general principles of decision-oriented sensitivity measures for dealing with uncertainty and will demonstrate them on two real-life cases: (1) the use of geological models for the choice of the nuclear waste deposit site in Switzerland, and (2) the use of flood risk models for decisions on flood protection along the Danube river.

 

How to cite: Straub, D., Betz, W., Ruf, M., Hoffmann, A., Koutas, D., and Papaioannou, I.: Addressing uncertainty in models for improved decision making, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17147, https://doi.org/10.5194/egusphere-egu23-17147, 2023.

EGU23-17474 | Posters on site | SM1.2

Inconsistency and violation of causality in Bayesian inversion paradigms 

Klaus Mosegaard

Probabilistic formulations of inverse problems are most often based on Bayes Rule, which is considered a powerful tool for integration of data information and prior information about potential solutions. However, since its introduction it has become apparent that the Bayesian inference paradigm presents a number of difficulties, especially in the phase where the problem is mathematically formulated.

 

Perhaps the most notable difficulty arises because Bayes Theorem is usually formulated as a relation between probability densities on continuous manifolds. This creates an acute crisis because of a problem described by the French mathematician Joseph Bertrand (1889), and later investigated by Kolmogorov and Borel. According to Kolmogorov's (1933/1956) investigations, conditioning of a probability density is underdetermined: In different parameterizations (reference frames), conditional probability densities express different probability distributions. Surprisingly, this problem is persistently neglected in the scientific literature, not least in applications of Bayesian inversion. We will explore this problem and show that it is a serious threat to the objectivity and quality of Bayesian computations including Bayesian inversion, computation of Bayes Factors, and trans-dimensional inversion.

 

Another difficulty in Bayesian Inference methods derives from the fact that data uncertainties, and prior information on the unknown parameters, are often unknown or poorly known. Because they are required in the calculations, statisticians have invented

hierarchical methods to compute parameters (known as hyper-parameters) controlling these uncertainties. However, since both the data uncertainties and the prior information on the unknowns are supposed to be known 'a priori', but are calculated 'a posteriori', this creates another crisis, namely a violation of causality. We will take a close look at the consequences of this mixing of 'prior' and 'posterior', and show how it potentially jeopardizes the validity of Bayesian computations.

 

How to cite: Mosegaard, K.: Inconsistency and violation of causality in Bayesian inversion paradigms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17474, https://doi.org/10.5194/egusphere-egu23-17474, 2023.

EGU23-17483 | Orals | SM1.2

Quantifying Uncertainty for Complex Systems 

Lucy Bailey, Mike Poole, Oliver Hall, and Lucia Gray

The ability to quantify uncertainty effectively in complex systems is not only useful, but essential in order to make good decisions or predictions based on incomplete knowledge.  Conversely, failure to quantify uncertainty, and a reliance on making assumptions, prevents a proper understanding of the uncertain system, and leads to poor decision-making. 

In our work to implement a geological disposal facility (GDF) for higher-activity radioactive waste, we need to be very confident in our demonstration of safety of the facility over geological timescales (hundreds of thousands of years). There are inevitably large uncertainties about the evolution of a system over such timescales.  We have developed a strategy for managing and quantifying uncertainty which we believe is more generally applicable to complex systems with large uncertainties.  At the centre of the strategy are three concepts: a top-down, iterative approach to building a model of the ‘total system’; a probabilistic Bayesian mathematical treatment of uncertainty; and a carefully designed methodology for quantifying uncertainty in model parameters by expert judgement that mitigates cognitive biases which usually lead to over-confidence.

Our total system model is a probabilistic model built using a top-down approach. It is run many times as a Monte-Carlo simulation, where in each realisation, parameter values are sampled from a probability density function representing the uncertainty. It is built with the performance measures of interest in mind, starting as simply as possible, then iteratively adding detail for those parts of the model where previous iterations have shown the performance measures to be most sensitive.  It sits well with a similar iterative approach to data gathering, the aim being developing understanding of what parts of the total system really matter. 

In our experience, to be both a tractable and effective strategy, it is essential that the level of detail and complexity in any quantitative analysis, is commensurate with the amount of uncertainty.  There needs to be a recognition that initial consideration of the system in too great a level of detail is futile when the uncertainty is large.  It is through iterative learning, understanding the sensitivities to the total system and refining our analysis and data gathering in areas of significance, that we can handle even complex uncertainty and develop a sound basis for confidence in decision making.

We are now looking to explore new techniques to iterative learning that involve maximising the information that can be gained, even from initially sparse datasets, to aid in confident decision-making.

 

How to cite: Bailey, L., Poole, M., Hall, O., and Gray, L.: Quantifying Uncertainty for Complex Systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17483, https://doi.org/10.5194/egusphere-egu23-17483, 2023.

With increasing global demand for oil and gas, the exploration of unconventional resource plays (shale oil and gas) continues to gain relevance. Such plays could be significant for maximising the production value in proven geological basins, allowing the exploration of a cleaner fossil fuel. Unconventional resources could play a part in the energy transition to lower-impact CO2 fuels while meeting current energy security needs.

For several decades, the UK North Sea has been a prolific oil and gas province, with numerous conventional oil and gas discoveries sourced predominantly by the Kimmeridge Clay Formation (KCF). In this study, we have used 3-D geostatistical modelling of the distribution of key geochemical and geomechanical properties for the KCF to investigate the potential of shale oil and gas plays within Quadrant 15 in the Outer Moray Firth region of the UK North Sea.

The utilized geochemical and geomechanical property logs were generated from sixteen selected drilled wells using machine learning and established property equations, while the top and base KCF structural depth maps used for modelling were created using grid- and isopach creation tools in Zetaware's Trinity software, an existing Base Cretaceous Unconformity (BCU) map of the UK North Sea and well top information from 58 wells within the study area.

The geostatistical property maps created for the KCF in Schlumberger’s Petrel software were then normalised and integrated to identity sweet spots for potential shale oil/gas exploitation, after the application of various cut-offs using standard industry thresholds for unconventional resources.

The modelling results suggest that the KCF show good potential for shale oil and gas exploitation within the central part of the Witch Ground Graben and limited areas of the Piper Shelf and Claymore-Tartan Ridge in the study area.  Further investigations on maturity, saturation and producibility will be conducted by 3-D basin modelling.

How to cite: Akinwumiju, A.: Sweet-spot mapping of the Kimmeridge Clay Formation in the UK North Sea for unconventional resource exploitation using a geostatistical modelling approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-63, https://doi.org/10.5194/egusphere-egu23-63, 2023.

EGU23-543 | ECS | Orals | ERE1.9

Subsurface mechanical modeling of Krishna Godavari basin using petrophysical properties of the rocks by utilizing 3D seismic and well log data sets 

Gagandeep Singh, Anjeeta Rani, William K. Mohanty, and Aurobinda Routray

Three-dimensional seismic data and well-log data analysis deliver complete information on the petrophysical characteristics of reservoir rock and its fluid content. The current study shows the combined interpretation of 3D seismic data and well log responses such as gamma ray, delay time (DT)- P wave and S wave, resistivity, neutron, density, and lithology logs from eight wells under the research area of Krishna-Godavari (KG) basin. The main target of the paper is focused on the prominent positive topographic features in the bathymetry data and on the porous and fractured/faulted hydrocarbon rocks. Fluid/gas migration characteristics like acoustic voids, chimneys, and turbid layers may be seen in the present mounds. Coherence, dip, curvature, and saliency attributes are used to enhance the discontinuities within the seismic volume. After then, well logs were used to identify the hydrocarbon-bearing zones. Finally, the seismic to well tie step was initiated, and the complete earth model of the given data was generated.

The goal of this paper is to describe the offshore KG basin reservoir areas, in a qualitative way using 3D seismic and well log data and its possible correlation with facies. The possible data and wells information are conjugated with other attributes, which are relatively recent methods in this field study, yet it is crucial to reducing geological uncertainty and predicting facies. The characterization of reservoirs using only the seismic volume (impedance dependent data) characteristics is difficult due to the shally environment of the area, which might obscure reservoir identification. As a result, combining a variety of techniques and data is important for better understanding geological settings and identifying meaningful geological features in the shally environment of the KG basin.

How to cite: Singh, G., Rani, A., Mohanty, W. K., and Routray, A.: Subsurface mechanical modeling of Krishna Godavari basin using petrophysical properties of the rocks by utilizing 3D seismic and well log data sets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-543, https://doi.org/10.5194/egusphere-egu23-543, 2023.

EGU23-1319 | ECS | Posters on site | ERE1.9

Effects of Thermal Shocks on Cement for CCS under Confined and Unconfined Conditions 

Kai Li and Anne Pluymakers

In wells for carbon capture and storage (CCS), fractures can develop in the cement due to strong thermal shocks upon pressurized CO2 injection into the subsurface. The network of these fractures forms leakage pathways that can impair well integrity, and thus impede successful geological storage of CO2. In this study, we investigate how thermal shocks affect cement integrity under unconfined and confined conditions. Solid cylindrical samples (Φ3 x 7 cm) and samples of the same size but with a hole (Φ4 mm) in the middle are used. All samples are prepared using class G cement with 35% BWOC silica flour by Halliburton AS Norway, in accordance with API specification 10B-2. In unconfined experiments, we either quench the solid sample into cold water or inject cold water through the hollow-cylindrical sample to induce thermal shocks. In confined experiments, we mount the hollow-cylindrical sample in a triaxial deformation setup with confining pressure and axial stress, then inject cold water to induce the shocks. Before the shocks in all experiments, samples have been heated to 130°C. The temperature of the water is 5°C to achieve a strong thermal shock as possible. We produce eight cycles of thermal shock in all experiments. To study the extent of cracking, we use a micro-computed tomography (μ-CT) scanner to characterize the network of pores and fractures in the cement before and after experiments.

Under unconfined conditions, fractures develop in cement after thermal shocks in both quenching and injecting-through experiments. Both experiments generate sufficient thermal stresses to cause cracking in cement. In quenching, multiple fractures are initiated at different orientations. However, by injecting cold water through the sample, only one longitudinal fracture is created. This fracture is intersected with the injecting hole, where most thermal stresses are built up. The volume ratio of pores and fractures in samples increases to 2.74% by quenching and 1.84% by injecting through respectively, from 0.38%. Compressive strength decreases from 97.9 MPa for intact samples to 53.9 MPa after quenching, and 83.6 MPa after the injecting-through experiment. Under confined conditions, we carry out injecting-through experiments to bring about thermal shocks under 1.5 and 10 MPa confining pressure. We haven’t observed any failure in cement integrity under either confinement. Instead, compressive strength increases by 6.2% and 7.2%, and the volume ratio of pores and fractures decreases by 7.7% and 18.2% after the experiment under the confinement of 1.5 and 10 MPa, respectively. This means the presence of confining pressure not only hinders the adverse effects of thermal stresses on cement integrity but also compacts the samples. Higher confining pressure causes more compression to the sample, then resulting in greater strength.

How to cite: Li, K. and Pluymakers, A.: Effects of Thermal Shocks on Cement for CCS under Confined and Unconfined Conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1319, https://doi.org/10.5194/egusphere-egu23-1319, 2023.

EGU23-1627 | Orals | ERE1.9

Viscosity-reducing and Biosurfactant-producing Bacterial Consortia Isolated from Low-permeability Reservoir in Ordos Basin 

Ziwei Bian, Zena Zhi, Xiangchun Zhang, Yiqian Qu, Lusha Wei, Yifei Wu, and Hanning Wu

Many bacteria have been proved to change physical (viscosity, wettability, and tension), and compositions of crude oil, which can make it easier for oil to be released from rock pores and achieve the purpose of improving recovery, which is called Microbial Enhanced Oil Recovery (MEOR). Our team has previously isolated six emulsified and viscosity-reducing bacteria (Bacillus. sp.) in low permeability layers (Chang 4+5 and Chang 6) of Ordos Basin. However, environmental tolerance of the strains is limited, and the components of crude oil used by the strains were also different. The combination of strains of different species and genera may enhance the effects of single bacteria, surpass the tolerance upper limit, and optimize the viscosity reduction and degradation. Therefore, in this study, it is extremely necessary to study the bacterial consortium. Two consortia were obtained and each consortium consisted of three bacterial strains and was designated as Consortium A (51+61, 61+H-1, 51+H-1; A-ALL) and Consortium B (34(2)+42, 34(2)+A-3; 42+A-3. B-BLL). The performance of the mixed strains was evaluated by the analysis of change in emulsification rate, crude oil composition, viscosity, and the tolerance (temperature, salinity, and pH) though GC-MS, rotational rheometer, and other methods. The results showed that bacterial consortiums had higher alkali resistance and could survive temperatures of 55 °C and salinity of 50 g/L in comparison to single bacterium. The emulsification rate was 22%-48%. Consortium B has better effects than Consortium A. The viscosity reduction rate of the Consortium A after 7 days was exceeded 30% as a whole, and the rate of Consortium B was more than 35%. The crude oil of Consortium B is basically non-stick to flask. Compared with single bacteria, the utilization components of crude oil to bacteria are still different, including both long chain hydrocarbons and short chain hydrocarbons. However, the proportion of long chain n-alkanes is further reduced compared with that of single bacteria, and the highest ratio is reduced by 23.81% (B-ALL). Overall, the bacterial consortium outperforms the single strain in terms of tolerance, viscosity reduction, and degradation, which further optimizes the application of MEOR.

How to cite: Bian, Z., Zhi, Z., Zhang, X., Qu, Y., Wei, L., Wu, Y., and Wu, H.: Viscosity-reducing and Biosurfactant-producing Bacterial Consortia Isolated from Low-permeability Reservoir in Ordos Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1627, https://doi.org/10.5194/egusphere-egu23-1627, 2023.

EGU23-1648 | ECS | Posters on site | ERE1.9

The CO2 storage in coal seams at the influence of coal fines migration 

Qian Wang, Jian Shen, Paul.W.J. Glover, and Piroska Lorinczi

Abstract: the pressure of the coal seam decays to a certain value due to the production of CH4, the production wells are switched to CO2 injection wells. The injection of CO2 can improve the CH4 recovery and realize the CO2 geological storage.The reverse migration of coal fines produced in the CH4 development stage can be caused by CO2 injection, which blocks the pore-thorats and fractures in coal seams and increases the difficulty of CO2 injection. We carried out experiments on coal fine migration and CO2 injection and storage at reservoir conditions on the simulated coal seam, which was a composite core composed of different types of coal. We focus on the migration of coal fine in simulated coal seam and the impact on CO2 storage. The experiment results show that, the permeability of the combined core, which is composed of proppant fractured coal, fractured coal and matrix coal in turn, decreases by 40.6% after being injected with 300ml of coal fine suspension with a concentration of 1g/1L. This is due to the deposition or capture of coal fines during the suspension injection, resulting in surface adsorption, bridging blockage, and direct blockage in the pore space, which seriously damaged the connectivity of the coal pore space. The proppant fractured coal can filter 77.1% of the coal fines in the suspension, and the fractured coal rock can filter the remaining 23.9% of the coal fines. The average CO2 storage capacity and CO2 storage efficiency of the composite core increased by 4.47 cm3·g-1 and 10.8%, respectively after subsequent CO2 injection into the composite core. The corresponding injection pressure difference also increased by 32.5%, and a CH4 recovery improvement of 13.6% is obtained.The migration and balockage of coal fines lead to the most significant improvement of CO2 storage in fractured coal (14.4%), followed by proppant fractured coal (10.3%), and the worst improvement of CO2 storage in matrix coal (3.4%). The migration of coal fines improves the CO2 storage effect in fractured coal seams to a certain extent, but increases the difficulty of CO2 injection, which is not conducive to the CO2 storage of the reservoir.

Keywords: CO2 storage, coal seams, coal fines migration, proppant fracture

How to cite: Wang, Q., Shen, J., Glover, P. W. J., and Lorinczi, P.: The CO2 storage in coal seams at the influence of coal fines migration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1648, https://doi.org/10.5194/egusphere-egu23-1648, 2023.

EGU23-2016 | Posters on site | ERE1.9

GEOMODELATOR – from static geologic models to structured grids for numerical simulations 

Benjamin Nakaten and Thomas Kempka

Conversion of static geologic models into numerical simulation grids is a pre-requisite to undertake site-specific assessments of geologic subsurface utilisation in terms of risk assessments, design and operational optimisations as well as long-term predictions.

GEOMODELATOR is a Python-based Open Source software package which enables modellers to translate static geologic models into regular structured simulation grids with element partitions following a complex model geometry.

For that purpose, geologic models generated by means of Geographic Information Systems (GIS), Computer-Aided Design (CAD) or other specific geologic modelling software packages are integrated in form of point cloud data together with the desired structured simulation grid geometry.

GEOMODELATOR maps geometric features such as lithologic horizons, faults and any kind of other geometric data by 3D Delaunay triangulation onto the pre-defined grid element centres, and provides the modeller with Visualization Toolkit (VTK) data and Python numpy arrays for visual model inspection and their direct application in numerical simulations, respectively.

The present contribution shows the application of GEOMODELATOR to different numerical simulation studies addressing fluid flow as well as transport of heat and chemical species in geological subsurface utilisation.

How to cite: Nakaten, B. and Kempka, T.: GEOMODELATOR – from static geologic models to structured grids for numerical simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2016, https://doi.org/10.5194/egusphere-egu23-2016, 2023.

EGU23-2535 | ECS | Orals | ERE1.9

Composition of pure shale oil with medium-high maturity 

Ming Li, Ming Wang, and Jinbu Li

Continental shale oil can be divided into two categories according to vitrinite reflectance of kerogen: medium-high maturity (Ro > 0.9%) and medium-low maturity (Ro ≤ 0.9%). Due to high ratio of gaseous (C1-5) and light hydrocarbons (C6-14), high GOR and overpressure of the shale section, medium-high maturity shale oil has commercially productivity, which is considered as the target of unconventional resources in China. Shale oil composition is the basic and key parameter for resource evaluation, prediction of favorable areas, well location and field development plan. However, in shale oil composition research projects, the samples used and the analytical methods are quite different, and evaluation standard has not been established, which has restricted the exploration and exploitation of continental shale oil in China.

To understand this effect, we took the first member of Qingshankou Formation (Late Cretaceous) in Songliao Basin in eastern China as the target section. The section develops pure shale oil at a burial depth of 2000-2500m, with vitrinite reflectance of kerogen (Ro) of 1.20%-1.70% and high clay minerals content (40 wt%-60 wt%). We performed four sets of experiments on molecular composition of shale oil, including oil produced from shale section, the full-closure coring shale, the conventional coring shale and extracted hydrocarbons of shale with chloroform. The crude oil and saturated hydrocarbons (extracted hydrocarbons) separated by chromatographic column were directly analyzed by gas chromatography. The full-closure coring and conventional coring shale samples were conducted TG-GC (thermogravimetry-gas chromatography) experiment, where the powder samples were thermally desorbed at 300 ℃ for 3 minutes.

The experimental results show that carbon number of n-alkanes in crude oil is 4–38. The carbon number of n-alkanes in full-closure coring shale is 1–26, and it contains a large amount of gaseous and light hydrocarbons, accounting for up to 60 wt%–80 wt%. It is worth noting, however, that due to the loss of gas and light hydrocarbons in conventional coring, the carbon number of n-alkanes in conventional coring shale is 11–26, and the main peak carbon is 13–16. In the process of shale placement in core library, extraction and concentration, a large amount of hydrocarbons are lost. Through chromatographic analysis, carbon number of n-alkanes in saturated hydrocarbons is 15-38, and the main peak carbon is 18–22. C15- components are totally lost in extraction (Figure 1).

The comparison data we assembled show that shale oil components obtained from different samples vary significantly, especially for medium-high maturity shale containing large amounts of gaseous and light hydrocarbons. The heavy hydrocarbon components (C15+) can be determined by combining the produced oil with extracted hydrocarbons, and the gaseous and light hydrocarbons retained in shale can be determined by combining the produced oil with TG-GC analysis for full-closure coring shale. Pressure-retained coring or full-closure coring is indispensable for obtaining shale oil components in place.

Figure 1 (a) Gas chromatogram of oil produced from shale section; (b) TG-GC chromatogram of conventional coring shale sample; (c) TG-GC chromatogram of full-closure coring shale sample; (d) Gas chromatogram of saturated hydrocarbon extracted from shale sample.

How to cite: Li, M., Wang, M., and Li, J.: Composition of pure shale oil with medium-high maturity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2535, https://doi.org/10.5194/egusphere-egu23-2535, 2023.

EGU23-3107 | ECS | Orals | ERE1.9

Stereoscopic Development Adjustment Mode for Enhanced Oil Recovery in Mature Multi-Layer Oilfield 

Lingbin Lai, Cunyou Zou, Zhibin Jiang, Haibin Su, Xuyang Zhang, Songlin Li, and Hualing Zhang

After a long period of water flooding development, oilfields will enter the production stage of "high water cut, high recovery degree, and low oil recovery rate". On the one hand, due to the displacement effect of the water injection, some oil layers already reached the water flooding limit. On the other hand, due to the effect of reservoir heterogeneity, dominant seepage channels, and imperfect injection-production well pattern, some oil layers are enriched with a large amount of remaining oil. Unbalanced production of reservoirs and difficulty in development and adjustment are common problems in mature oilfields. Mature multi-layer oilfields generally develop many sets of oil-bearing layers vertically. After a long water injection period, the water-flood law and the remaining oil distribution are complex, and the production of different well patterns or strata varies greatly. Through strata and well pattern reorganization, combined with the evaluation results of water flooding adjustment potential, some reservoir engineers and researchers established a stereoscopic development adjustment mode for enhanced oil recovery in mature multi-layer oilfields. This paper summarizes the main technologies of stereoscopic development adjustment mode for enhanced oil recovery in mature multi-layer oilfields. The main technologies of stereoscopic development adjustment mode include research on the remaining oil distribution, evaluation of water flooding adjustment potential, selection of tertiary oil recovery methods, reorganization of strata and well pattern, and optimization of timing from water flooding to tertiary oil recovery, etc. For strata with low water flooding adjustment potential, the tertiary oil recovery well pattern is reorganized and tertiary oil recovery is adopted to improve oil recovery. For strata with large water flooding adjustment potential, the water drive well pattern is reorganized and water flooding development is used to excavate the remaining oil. As for strata with general water flooding adjustment potential, the tertiary oil recovery well pattern is reorganized and water flooding development is used to excavate the remaining oil first, and then transfer to tertiary oil recovery at the proper time. The stereoscopic development adjustment mode is applied to test block K of Q reservoir which is a mature multi-layer oilfield. After stereoscopic development adjustment, the development effect of test block K meliorates. It is estimated that the EOR will be increased by more than 8% after stereoscopic development adjustment in test block K.

How to cite: Lai, L., Zou, C., Jiang, Z., Su, H., Zhang, X., Li, S., and Zhang, H.: Stereoscopic Development Adjustment Mode for Enhanced Oil Recovery in Mature Multi-Layer Oilfield, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3107, https://doi.org/10.5194/egusphere-egu23-3107, 2023.

EGU23-3408 | Orals | ERE1.9

Optimising the drilling process for geothermal wells using legacy oil field data and machine learning 

Andrew Kingdon, Matthew Arran, Mark Fellgett, Shahin Jamali, Henning Knauer, and Kevin Mallin

Deep geothermal heat represents a massive opportunity to provide low-carbon district heating for towns and cities. Space heating represents a large percentage of total energy use in Northern Europe; nearly 40% of all UK energy use (BEIS, 2022) is for heating, predominantly from natural gas. Global pressures on the international gas market and the urgent need to decarbonise the heating system to deliver NetZero highlight the need for identifying renewable heat sources to replace gas.

However, finding reliable high temperatures requires drilling to several-kilometres depth. Achieving sustainable heat supply, without depletion, means that wells must intersect deep permeable strata which are impossible to detect from the surface. Well prognosis is therefore heavily reliant on data from legacy drilling. Drilling is always an expensive process and any operational issues can impose significant additional costs, as rigs capable of drilling such boreholes have rental rates of many €1000s per day. Even when the drilling is completed, financial returns are slow and reaching profit takes years. Therefore, reassuring investors requires de-risking such projects through mitigating avoidable additional costs.

Digital data from wells penetrating many kilometres are needed for understanding subsurface processes. Only small numbers of deep geothermal wells have been drilled, so the best alternatives are legacy hydrocarbon exploration boreholes; these are good analogies for geothermal wells as they rely on permeability at depth. Such legacy hydrocarbon data are increasingly openly available through National Data Repositories (NDR) and/or Geological Survey Organisations. 

The EU Horizon programme funded OptiDrill project (101006964) is using legacy well data to optimise the drilling process, by linking drilling parameters with petrophysical data to understand the constraints upon the drilling processes. This will allow causes of interruptions to drilling and unnecessary down-time to be assessed and hopefully eliminated.

NDR archives have been trawled for modern drilling and logging data that admits optimal analysis. An Isolation Forest machine-learning algorithm was used to analyse Measurement-While-Drilling derived Rate-of-Penetration data and geophysical log data, identifying zones of anomalous responses quickly and without supervision. Examination of newly available daily drilling reports (DDR) data, from the NDR, allows these anomalous responses to be associated with breaks in drilling operations and their causes to be understood. This allows both refinement of the anomaly-detection algorithm for the identification of drilling problems, and differentiation between problems caused by drilling or geological issues and those caused by operational and logistical difficulties (e.g. procurement delays). Where drilling issues are identified these can be used to develop remediation strategies for future wells drilled in similar conditions, through revised drilling programmes and optimised well designs that minimise avoidable drilling operations such as unnecessary round trips etc.

How to cite: Kingdon, A., Arran, M., Fellgett, M., Jamali, S., Knauer, H., and Mallin, K.: Optimising the drilling process for geothermal wells using legacy oil field data and machine learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3408, https://doi.org/10.5194/egusphere-egu23-3408, 2023.

Reservoir heterogeneity is one of the key geological problems in the process of oil and gas exploration and development of clastic rocks. Understanding reservoir heterogeneity is imperative to improve the effectiveness of exploration and development. The primary porosity calculation model proposed by the authors in the previous study is used to calculate the primary porosity of samples from modern braided river sands and sandstone outcrops of braided sand bodies, and the primary porosity heterogeneity (PPH) model of the braided sand body is established. The architectural-elemental structures of braided sand bodies have obvious control effects on the distribution of its primary porosity heterogeneity. The central braided channel and braid bars have strong primary physical properties; the primary porosity is high and always greater than 38%. The contact areas between the braided channel and braided bars have a low value of primary porosity and are always lesser than 33%. The distribution characteristics of the present porosity of braided river reservoirs are also influenced by sedimentary architecture. To compare the relationship between PPH, present porosity heterogeneity (pPH), and sedimentary architecture (SA), the images of PPH, pPH, and SA were digital, graying, and normalized. The digital image Q-Q plots of the distribution probability of PPH, pPH, and SA are calculated. The results show that: the Q-Q plots of the probability distribution of present porosity and architectural-elemental structures (or lithofacies) can reflect the influence and degree of primary porosity and diagenesis on the present heterogeneity of the reservoir. The Q-Q plots of distribution probability primary porosity and present porosity identify the distribution areas; the points are always distributed on different lines. The line ‘y = x’, is derived from compaction and primary porosity; the line ‘y = ax, a > 1’, is derived from diagenesis, which is unfavorable to the reservoir porosity preservation (such as cementation); the line ‘y = ax, a < 1’ is derived from diagenesis, which is beneficial to reservoir porosity preservation (such as dissolution). Based on the Q-Q plots of distribution probability, the influence from primary porosity and diagenesis can be quantitatively analyzed. The influence of primary porosity on pPH in braided sand bodies of Ahe formation (Kuqa depression), middle Jurassic fluvial sandstone (Datong basin), and Karamay Formation (Junggar basin) were 19%, 90%, and 10%, respectively. A quantitative probability distribution Q-Q model of reservoir PPH and pPH is effective for reservoir physical modeling.

How to cite: Yiming, Y., Liqiang, Z., Shuai, J., and Zuotao, W.: The primary porosity heterogenetic model of braided river sandstone reservoirs and its influence on the present porosity heterogeneity in the Kuqe depression, Tarim basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6856, https://doi.org/10.5194/egusphere-egu23-6856, 2023.

EGU23-7034 | Posters on site | ERE1.9

Study on Hydraulic Resistance Damage Law of External Liquid Intrusion in Tight Sand Conglomerate Reservoir 

Jianbang Wu, Shenglai Yang, and Qiang Li

In geological resource exploitation engineering such as reservoir development, the intrusion of foreign liquid will cause water lock damage to the formation rock structure, which affects the effect of reservoir transformation such as CO2 sequestration. The tight sand conglomerate reservoir is characterized by high content of expansive clay minerals, high capillary pressure, small pore throat, and serious heterogeneity, which leads to serious water lock damage. The extent, mechanism and reasonable prediction of damage are the concerns of the engineering community.
In view of this problem, this study uses the laboratory long core experiment method based on nuclear magnetic resonance (NMR) monitoring to simulate and study the reservoir damage law before and after the invasion of foreign liquid into the formation. The damage distance of liquid resistance and influencing factors were studied, and a prediction model was established. The long core experiment used drilled natural cores with a total length of 45 cm that were spliced from short cores with a diameter of 2.5 cm. A total of five pressure points were set up at 10 cm intervals to monitor the pressure gradient. The pressure gradient changes along the long core after saturated oil and water intrusion were tested separately. A new method of calculating the range and degree of water lock damage zone based on pressure gradient was established. According to the damage control factors obtained from the experimental study, the prediction model of water lock damage with the transformation from multiple nonlinear problems to linear problems is established by using permeability, porosity and content of water-sensitive clay minerals as input conditions.
The results show that the physical property of reservoir plays a decisive role in the damage distance of liquid resistance. The foreign liquid intrudes into the formation has obvious characteristics of "three zones", and the "pressed liquid stop zone" is the main factor controlling the damage degree of liquid resistance. Physical property, lithology and expansibility clay mineral content together constitute the 0-1 judgment value to determine the time-varying damage of fluid resistance in reservoir. The accuracy of the established multiple nonlinear regression prediction model of liquid resistance damage is greater than 80%, which can be used to quantitatively predict the liquid resistance damage degree of underground reservoir when it is difficult to conduct indoor simulation experiments in the evaluation of water intrusion damage degree.

How to cite: Wu, J., Yang, S., and Li, Q.: Study on Hydraulic Resistance Damage Law of External Liquid Intrusion in Tight Sand Conglomerate Reservoir, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7034, https://doi.org/10.5194/egusphere-egu23-7034, 2023.

EGU23-8226 | ECS | Posters on site | ERE1.9

Hydrogeochemical impacts of pumped hydropower storage in open-pit lignite mines 

Tobias Schnepper, Michael Kühn, and Thomas Kempka

Large-scale energy storage is becoming more important due to the increase in electricity generation from renewable sources and the related grid balancing requirements. In this context, Pumped Hydropower Storage (PHS) in former open-pit lignite mines can substantially contribute to energy supply safety. Assuming an average storage capacity of 150 MW per open-pit mine, PHS could generate a power output of at least 6 GW in European mines which will be abandoned in the next two decades. Experiences from mine-flooding across Europe demonstrate that hydrogeochemical processes can become a critical environmental and economic factor for the realisation of such projects. Depending on sulphide and oxygen availability, buffer capacities and dilution processes, mine waters with increased acidity as well as elevated sulphate and metal concentrations can pose a threat to adjacent ecosystems, groundwater resources and the installed PHS infrastructure.

We present a generic parameter study by means of numerical simulations to predict changes in the mine water composition as a result of PHS operation in different hydrogeochemical settings. Published datasets on hydrogeochemical, hydrogeological and technical conditions with a focus on German mines were applied for model parametrisation. A reaction path model was developed that accounts for initial mine flooding, inflows and outflows as well as pumping and release cycles between the two reservoirs. The simulations were run until chemical equilibrium was achieved in the lower reservoir.

Simulation results indicate that the long-term availability of buffer capacities in the reservoir water and adjacent sediments determine the development of acidic or neutral mine waters. Sulphate concentrations are mainly influenced by dilution processes, emphasizing the relevance of considering additional in- and outflows. Depending on these fluxes as well as oxygen availability and initial sulphide concentration in the mine sediments, the time to reach chemical equilibrium in the lower reservoir varies significantly from several weeks to months. Furthermore, the dissolution of sulphides and carbonates as well as the precipitation of iron (oxy)hydroxides may affect the properties of the open-pit slope sediments. Their long-term stability may be altered, based on their initial mineral concentration and hydraulic conductivity.

In summary, potential impacts on water quality in the PHS reservoirs have been investigated under different hydrogeochemical settings. We conclude that, under specific boundary conditions such as the availability of sufficient buffer capacities and dilution by controlled inflows and outflows, PHS operation in abandoned open-pit coal mines can be realised from an environmental perspective.

How to cite: Schnepper, T., Kühn, M., and Kempka, T.: Hydrogeochemical impacts of pumped hydropower storage in open-pit lignite mines, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8226, https://doi.org/10.5194/egusphere-egu23-8226, 2023.

EGU23-8407 | ECS | Orals | ERE1.9

Multi-salinity core flooding study in clay-bearing sandstones, a contribution to geothermal reservoir characterisation 

Daniela Navarro-Perez, Quentin Fisher, Piroska Lorinczi, Samuel Allshorn, and Carlos Grattoni

Geothermal reservoir characterisation benefits from the oil and gas petrophysics experience in areas such as porosity and permeability estimation, rock-fluid interactions etc.. Permeability is the crucial parameter in assessing water transmissibility with geothermal reservoirs. Permeability impairment is a key worry due to rock-fluid interactions within the reservoir life cycle management. The laboratory techniques help in recreating the reservoir conditions and determining formation damage. Uncertainty increases for tight geothermal reservoirs (permeability < 1 mD), which often contain significant amounts of clay that reacts with water or ionic species during hydraulic fracturing used in Enhanced Geothermal Systems.

Clay-bearing sandstones are complex reservoirs since their clay minerals actively interact with water, causing formation damage by clay swelling and migration mechanisms. Core flooding experiments study the clay minerals' behaviour in different water conditions - e.g. salinity, electrolytes species, pH, and temperature - helping to understand the impact of clays on reservoir quality and identifying optimal conditions to reduce formation damage.

A multi-salinity experiment was undertaken to study the clay effect of three tight clay-bearing sandstones, samples A, B and C, of different reservoir provenance. Sample A has a core porosity of 18%, gas permeability of 1.28 mD, and 15.5%v/v of XRD clay minerals and kaolinite as the primary group. Sample B has a core porosity of 20.2%, gas permeability of 0.56 mD, and 37%v/v of XRD clay minerals and chlorite as the primary group. Sample C has a core porosity of 18.8%, the gas permeability of 1.95 mD, and 36.3%v/v XRD clay minerals and mica as the primary group. The experiment consisted of flooding brine with constant inflow at different salinities and monitoring the rock resistance, pressure drop, and outlet brine conductivity. High- and low-salinity batteries were flooded, ranging from 200,000-75,000 and 50,000-0 ppm NaCl respectively, at a constant room temperature of 21⁰C. In addition, the brine permeability was measured in steady- and unsteady-states techniques, and pore size distribution was NMR scanned at each run per battery.

Permeability impairment increased in all samples. Samples A (kaolinite) and C (mica) show a staggered increase in the salinity range. In contrast, sample B (chlorite) shows a peculiar upside-down trend in the low-salinity range. Clay migration was detected in the last brine runs since fines grain were released in the outflow. NMR T2 distribution shows a bimodal pore distribution for samples B and C, and the pore-throat connectivity rearranges as salinity decreases in both samples, indicating a clay swelling mechanism. The cation-exchange capacity (CEC) of samples A and C resulted in 3.7 and 3.6 meq/100g, respectively, and sample B was 71.5 meq/100g. CEC values are directly related to the clay mineral content. The highest CEC (sample B) relates to the upside-down permeability impairment with clay swelling. This investigation contributes to the geothermal reservoir characterisation in understanding how the water salinity controls the clay effect in tight clay-bearing sandstone reservoirs.

How to cite: Navarro-Perez, D., Fisher, Q., Lorinczi, P., Allshorn, S., and Grattoni, C.: Multi-salinity core flooding study in clay-bearing sandstones, a contribution to geothermal reservoir characterisation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8407, https://doi.org/10.5194/egusphere-egu23-8407, 2023.

EGU23-9352 | ECS | Posters on site | ERE1.9 | Highlight

Repurposing of idle wells from the oil and gas industry into deep borehole heat exchangers 

Nora Koltzer, Johannes Schoenherr, Maximilian Sporleder, Sebastian Andreas Steininger, Marcel Halm, Michael Kettermann, and Florian Wellmann

The motivation behind this study is to repurpose idle wells from hydrocarbon exploration and production to provide heat for end users being located near the idle well. This is possible by prolonging the value-added chain of idle wells from the gas and oil industry by re-completion as geothermal closed loop wells. This is the most efficient way to produce green energy without drilling new wells by saving the carbon emission and costs of building a new geothermal well.

With this feasibility study we quantify the concept of re-completing idle wells in the North German Basin (NGB) into deep coaxial borehole heat exchangers. With numerical models of two typical geological settings of the NGB and two different completion schemes it was possible to simulate the thermal performance over a lifetime of 30 years. The calculated heat extraction rates are in the range of 200 kW to 400 kW with maximum values of up to 600 kW. This is higher than from already installed deep borehole heat exchangers. Sensitivity analyses demonstrate that flow rate, injection temperature and the final depths of re-completion are the most impacting parameters of thermal output determination.

In the final project stage, the heat demand around two exemplary boreholes was mapped and possible heating networks were simulated. The initial production costs for heat are comparable to other renewable energy resources like biomass and - depending on distance between source and user – well competitive against current gas prices. These calculations highlight not only the environmental valuable motivation behind the concept of repurposing idle wells but could also save capital expenditures for the geothermal industry.

Using a vacuum isolated tubing characterized by very low thermal conductivity of 0.02 W/(m*K), would make it possible to use the geothermal resources even more efficiently from idle wells. This project highlights the major potential of usable geothermal resources in already installed deep wells. The application has almost no geological risk, as the concept is independent of reservoir uncertainties like permeability and reservoir fluid composition, drilling risks are skipped completely and it is realizable at any location.

How to cite: Koltzer, N., Schoenherr, J., Sporleder, M., Steininger, S. A., Halm, M., Kettermann, M., and Wellmann, F.: Repurposing of idle wells from the oil and gas industry into deep borehole heat exchangers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9352, https://doi.org/10.5194/egusphere-egu23-9352, 2023.

Power-to-Methanol is considered as an additional option to Power-to-Gas to convert surplus energy from renewable sources and the electric grid into storable energy carriers. In this context, methanol is an alternative fuel to power combustion engines, and it can be applied to produce chemical feedstock such as formaldehyde required for polymer production, hydrocarbons, gasoline and olefines, as well as gasoline additives and especially as an energy carrier and carbon sink.

As long-term storage of energy carriers is required to realise the transition of the energy sector to renewable sources scheduled in the European Union, the fact that storage of methanol requires less operational and safety efforts compared to natural gas or hydrogen is a significant benefit, i.e. methanol does not require any compression prior to its injection into geologic subsurface reservoirs, while being biodegradable and of generally low environmental toxicity. Existing hydrocarbon transport and storage infrastructure can be directly applied to transport and store methanol in the geologic subsurface. In this context, a major concern besides methanol biodegradability is its high miscibility with water, potentially resulting in relevant storage losses that may favour uneconomic storage operations in active groundwater aquifers. Hence, the present study aims at a quantitative assessment of the mixing behaviour of methanol and water based on a reference numerical simulation benchmark previously applied to investigate that of CH4 stored in a CO2 cushion gas within a depleted natural gas reservoir (Oldenburg et al., 2003, Ma et al., 2019, and others). For that purpose, the TRANSPORTSE numerical simulator (Kempka, 2020), applicable to simulate fluid flow as well as transport of heat and reactive transport of chemical species (Kempka et al., 2022) is used in the present study. Mixing ratio-dependent density and viscosity changes as well as different reservoir dipping angles are considered to determine the chemical storage efficiency in view of mixing losses. Simulation results demonstrate that methanol fraction-driven variations in fluid density and viscosity of up to 20 % and 30 %, respectively, as well as the relatively low diffusion coefficients compared to those of gases result in low mixing degrees of both liquid components. Structural geological features need to be considered in the selection of methanol storage sites, since these directly affect the spatial extent of the mixing region, and thus methanol recovery efficiency.

 

Kempka, T., Steding, S., Kühn, M. (2022) Verification of TRANSPORT Simulation Environment coupling with PHREEQC for reactive transport modelling. Advances in Geosciences, 58, 19-29. https://doi.org/10.5194/adgeo-58-19-2022

Kempka, T. (2020) Verification of a Python-based TRANsport Simulation Environment for density-driven fluid flow and coupled transport of heat and chemical species. Advances in Geosciences, 54, 67-77. https://doi.org/10.5194/adgeo-54-67-2020

Ma, J., Li, Q., Kempka, T., Kühn, M. (2019) Hydromechanical Response and Impact of Gas Mixing Behavior in Subsurface CH4 Storage with CO2-Based Cushion Gas Energy & Fuels 33 (7), 6527-6541. https://doi.org/10.1021/acs.energyfuels.9b00518

Oldenburg, C. M. (2003) Carbon Dioxide as Cushion Gas for Natural Gas Storage. Energy Fuels 17(1), 240−246. https://doi.org/10.1021/ef020162b

How to cite: Kempka, T.: Mixing behaviour of methanol stored in depleted hydrocarbon reservoirs to support the European Union energy transition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9383, https://doi.org/10.5194/egusphere-egu23-9383, 2023.

One of the main challenges in soil science lies in the passage from heterogeneous soil structure to a quantified multi-scale 3D model. Here a new approach to quantify the microbial distribution relating to soil pore structure is presented. Characterising 3D microbial soil structural in digital porous media is not found and most soil process models tend to assume a homogenous spatial distribution of microbes. We measured the in situ spatial distribution of bacteria in arable soils across scales from sub-micrometers to metres and here we describe further progress to quantify and explicitly model the 3D microbial distributions, based on a stochastic Bayesian approach to predict spatial variation in the underlying bacterial intensity measure. A 3D higher order Multi-Markov chain model is introduced to model complex geometry of real soil structure and associated microbial distribution. In this study, Markov random fields are used to construct multiscale 3D Pore Architecture Models (PAM). The binary structure of PAM has been successfully used to predict multiphase flow behaviour in porous media such as hydrocarbon bearing reservoir rocks, we explore further to use such a new multi-components scheme in modelling pore structure incorporating with microbial spatial distribution, the multicomponent Markov chain model, which is a stationary multiple higher order Markov chain. The models parameterisation is based on high resolution SEM images of soil that have been prepared in a manner that preserves the microbial community information in situ. Based on the quantified 3D multiscale soil structure associated with microbial distribution components, the accurate reactive flow of microbial degradation can be simulated to predict environmental impact of microbial activates in the field. A variety of examples of structures and bacterial distribution created by the models are presented.

How to cite: Wu, K.: A new 3D multicomponent markov chain model incorporating multi-scale soil structure with microbial distribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9593, https://doi.org/10.5194/egusphere-egu23-9593, 2023.

EGU23-9686 | ECS | Orals | ERE1.9

Geologic Controls on the Genesis of the Arctic Permafrost and Sub-Permafrost Methane Hydrate-bearing System in the Beaufort–Mackenzie Delta 

Zhen Li, Elena Chabab, Erik Spangenberg, Judith Schicks, and Thomas Kempka

The Canadian Mackenzie Delta (MD) is a river-mouth depocentre and the second-largest Arctic delta. It exhibits high resources of prospected sub-permafrost gas hydrates (GHs), mainly consisting of thermogenic methane (CH4) at the Mallik site, which migrated from deep source rocks. The objective of the present study is to confirm the sub-permafrost GHs formation mechanism proposed by Li et al. (2022a), stating that CH4-rich fluids were vertically transported from deep overpressurized zones via geologic fault systems and formed the present-day GH deposits in the shallower Kugmallit Sequence since the Late Pleistocene. Given this hypothesis, the coastal permafrost began to form since the early Pleistocene sea-level retreat, steadily increasing in thickness until 1 Million years (Ma) ago. Observations from well-logs and seismic profiles were used to establish the first field-scale static geologic 3D model of the Mallik site. A framework of equations of state to simulate the formation of GHs and permafrost (Li et al., 2022a, 2022b) has been developed and coupled with a numerical simulator for fluid flow as well as the transport of chemical species and heat in previous studies. Here, numerical simulations using the proven thermo-hydro-chemical simulation framework were employed to provide insights into the hydrogeologic role of the regional fault systems in view of the CH4-rich fluid migration and the spatial extent of sub-permafrost GH accumulations during the past 1 Ma. The simulated ice-bearing permafrost and GH interval thicknesses, as well as sub-permafrost temperature profiles, are consistent with the respective field observations, confirming our previously introduced hypothesis. In addition, simulation results demonstrate that the permafrost has been substantially heated to 0.8–1.3 °C, triggered by the global temperature increase of about 0.44 °C (IPCC, 2022) and further accelerated by Arctic amplification from the early 1970s to the mid-2000s. Overall, the good agreement between simulations and observations demonstrates that the present modeling study provides a valid representation of the geologic controls driving the complex permafrost-GH deposit system. The model’s applicability for predicting GH deposits in permafrost settings can provide relevant contributions to future GH exploration and exploitation activities.

References

IPCC, 2022: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press. Cambridge University Press, Cambridge, UK and New York, NY, USA, 3056 pp., doi:10.1017/9781009325844.

Li, Z., Spangenberg, E., Schicks, J. M. & Kempka, T. Numerical Simulation of Coastal Sub-Permafrost Gas Hydrate Formation in the Mackenzie Delta, Canadian Arctic. Energies 15, 4986 (2022a). https://doi.org/10.3390/en15144986

Li, Z., Spangenberg, E., Schicks, J. M. & Kempka, T. Numerical Simulation of Hydrate Formation in the LArge-Scale Reservoir Simulator (LARS). Energies 15, 1974 (2022b). https://doi.org/10.3390/en15061974

 

How to cite: Li, Z., Chabab, E., Spangenberg, E., Schicks, J., and Kempka, T.: Geologic Controls on the Genesis of the Arctic Permafrost and Sub-Permafrost Methane Hydrate-bearing System in the Beaufort–Mackenzie Delta, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9686, https://doi.org/10.5194/egusphere-egu23-9686, 2023.

In the past decades, boreholes were drilled all over the world for the purpose of hydrocarbon prospection. Data from these boreholes are a very valuable resource, that can be used in current geological, geothermal and hydrogeological studies. Since the process of drilling is both expensive and disturbing to the environment the possibility of incorporating data that already exists in the current studies is always worth consideration. However, in the case of older boreholes quality of data is not on par with modern standards which limits its usefulness, especially in the case of data from boreholes drilled in thin-bedded rock formations.

Resistivity logs are one of the main logs used both in hydrocarbon prospection and other applications such as geological, geothermal and hydrogeological studies. Resistivity logs measured by older generations of logging tools are characterized by significantly lower vertical resolution in comparison to logs measured by newer logging tools which affect the quality of the interpretation. However, the information averaged in the process of logging can be partially restored in the process of iterative inversion.

The focus of the presentation is on the utilization of open-source global optimization software in the process of inversion of resistivity well logs. Since inverse problems encountered in geophysics tend to be on the difficult side, relatively simple optimization schemas that often can be found in open-source software are not always giving good results. Therefore, in the presentation, a few methods that allow adapting those algorithms to the problem of inversion of well logs are discussed. The performance of the inversion procedure is validated on synthetic data and real data from the borehole where resistivity logs were measured by different generations of logging tools in the same depth intervals, which allows for comparison of the inversion results to logs measured by modern equipment.

 

The research was funded by the National Science Centre, Poland, grant number 2020/37/N/ ST10/03230.

How to cite: Wilkosz, M.: Adaptation of open-source global optimization software to the process of iterative inversion of resistivity well logs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10004, https://doi.org/10.5194/egusphere-egu23-10004, 2023.

EGU23-11350 | ECS | Orals | ERE1.9

New Insights into Underlying Mechanisms of CO2 Wettability and Residual Saturation from Laboratory Measurements of Multi-Phase Zeta Potential in Supercritical CO2-Rock-Brine Systems 

Miftah Hidayat, Jan Vinogradov, Mohammad Sarmadivaleh, Stefan Iglauer, David Vega-Maza, and Jos Derksen

Measurements of the zeta potential using streaming potential method are frequently used to characterise flows in subsurface settings owing to a broad range of applications of this petrophysical property; examples include CO2 geological storage, hydrocarbon reservoirs, geothermal sources and freshwater aquifers. Many experimental studies of the zeta potential have been carried out covering a wide range of parameters including different rock mineralogy, brine concentration and composition, and temperature to understand the impact of each parameter. The capability of the streaming potential method to be used on intact rock samples, single-/ and multi-phase flows, wide range of salinity, pressure and temperature makes the method suitable for representation of typical subsurface conditions. However, none of previous studies reported high multi-phase measurements at high pressure conditions typical for deep reservoirs. To adequately represent subsurface conditions of carbon geological storage sites, the minimum experimental pressure of 7.38 MPa and minimum temperature of 31 °C, consistent with the supercritical-CO2 (scCO2), need to be used. Obtaining stable measurements of the streaming potential under these conditions is extremely challenging. We report a detailed design of a high-pressure experimental system and experimental protocol for multi-phase streaming potential measurements that were carried out on scCO2-sandstone-brine systems at temperature of 40 °C, pressures ≤10 MPa and with a variety of aqueous solutions.

The obtained results demonstrate for the first time that the multi-phase zeta potential correlates with the measured scCO2 residual saturation and rock’s wetting state interpreted from other parameters. Moreover, our results unambiguously identify for the first time the polarity and likely magnitude of the scCO2-brine interfacial zeta potential. Our findings improve the current understanding of the complex wetting behaviour of scCO2 and provide important experimental data for numerical (surface complexation, molecular dynamics), analytical (DLVO) or combined models.

How to cite: Hidayat, M., Vinogradov, J., Sarmadivaleh, M., Iglauer, S., Vega-Maza, D., and Derksen, J.: New Insights into Underlying Mechanisms of CO2 Wettability and Residual Saturation from Laboratory Measurements of Multi-Phase Zeta Potential in Supercritical CO2-Rock-Brine Systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11350, https://doi.org/10.5194/egusphere-egu23-11350, 2023.

Inland salinisation due to the upwelling of highly mineralised deep waters formed by leaching of Upper Permian salt diapirs is a typical phenomenon in the North German Basin. In the German State of Brandenburg, the local absence of the regionally most important aquiclude, the Lower Oligocene Rupelian Clay, separating deep saline waters from the overlying freshwater aquifers, is considered to be the main cause of local salinisation in the freshwater column.

The present study uses density-driven 3D flow and transport simulations to assess saltwater upwelling across Quaternary window sediments in the Rupelian for an area in southeastern Brandenburg with detectable salt concentrations in the freshwater column. Previous simulations along a 55 km long transect in Brandenburg using a 2D model have already demonstrated the potential negative impact of groundwater extraction, the use of the deep subsurface as a storage reservoir or lower precipitation rates and decreasing groundwater levels as a consequence of global climate change on the degree of upper aquifer salinisation (Chabab et al., 2022; Tillner et al., 2016; Wetzel et al., 2016).

The presented simulation results show that 3D flow strongly affects the temporal and spatial distribution of upper aquifer salinisation due to the varying extent of layers and erosion windows in the Rupelian Clay. The location of groundwater extraction sites, hydraulically conductive faults and spatial variations in groundwater recharge additionally influence the location and degree of shallow aquifer salinisation, and must therefore be carefully considered. Depending on topographic gradients and density variations occurring due to differences in pressure and temperature, convective cells with descending flow and freshwater lenses in the saltwater column also develop locally. We show that 3D flow simulations are essential for site-specific analysis to represent the dynamics of the system with many different hydrogeologic interacting and controlling factors.

 

Literature

Chabab, E., Kühn, M., Kempka, T. (2022): Upwelling mechanisms of deep saline waters via Quaternary erosion windows considering varying hydrogeological boundary conditions. Advances in Geosciences, 58, 47-54.

Tillner, E., Wetzel, M., Kempka, T., Kühn, M. (2016): Fault damage zone volume and initial salinity distribution determine intensity of shallow aquifer salinisation in subsurface storage. Hydrology and Earth System Sciences, 20, 1049-1067.

Wetzel, M., Kühn, M. (2016): Salinization of Freshwater Aquifers Due to Subsurface Fluid Injection Quantified by Species Transport Simulations. Energy Procedia, 97, 411-418.

How to cite: Chabab, E., Kühn, M., and Kempka, T.: Saltwater upwelling quantified by density-driven 3D flow and transport simulations for a study area in Brandenburg, Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12741, https://doi.org/10.5194/egusphere-egu23-12741, 2023.

EGU23-12843 | ECS | Posters on site | ERE1.9

Coupling approach in shallow, unconfined aquifers in the Po Plain area: A preliminary study for future ground monitoring purposes. 

Celine Eid, Christoforos Benetatos, and Vera Rocca

The use of the coupling approach in analyzing the interaction between the flow field and the stress field in shallow, unconsolidated aquifers allows a better description of the involved phenomena. We perform our study on an area in the Po Plain (northern Italy) in the province of Bologna in Emilia-Romagna based on intended future studies on ground movements due to the superposition of shallow water production with deep underground gas storage.

The static geological model of the alluvial sediments, locally exceeding 500 meters of thickness, is developed via a stochastic approach in order to manage the high degree of uncertainty in the system spatial continuity and heterogeneities. Corresponding water production data and piezometric measurements are collected for simulating the dynamic behavior of the shallow aquifer. The high uncertainty in water production data are managed considering a maximum and minimum scenarios on the basis of punctual well measurements and regional trend information. Correlation law between petrophysical parameters and deformation variables are derived for technical literature. The coupling technique is then applied and some sensitivity analysis are developed to assess the effects of the correlation laws. The results are finally compared with the output from the uncoupled techniques.

How to cite: Eid, C., Benetatos, C., and Rocca, V.: Coupling approach in shallow, unconfined aquifers in the Po Plain area: A preliminary study for future ground monitoring purposes., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12843, https://doi.org/10.5194/egusphere-egu23-12843, 2023.

The decarbonization of communities and their energy supply is considered as a contemporary priority path forward, although it poses many challenges. In this scenario, geothermal energy can cover a pivotal role in the energy transition and in a wider spread of renewable energies. Moreover, the possibility to reuse or modifying existing wells for geothermal purposes is becoming a hot and promising topic. In Italy, there are more than 8000 abandoned/inactive on-shore wells drilled for hydrocarbon exploration subsequently abandoned either for the end of the resource (exhausted well) or for sterility (barren well). This can represent a huge opportunity for geothermal energy exploitation. The drilled borehole available data, collected during the exploration activity, provide useful information about the sub-surface reservoirs, highly reducing the mining risk level, and allowing direct and low cost access to the sub-surface heat energy.

This work aims to analyse the feasibility of the retrofitting of abandoned oil and gas wells focusing on the Italian territory, proposing a selection methodology of wells starting from raw data collection. We want to evaluate which could be the best technical solutions for the retrofitting of an inactive oil&gas well considering the closed loop geothermal options, both coaxial and deep-U heat exchangers options. We decided to concentrate on the closed loop solution for the retrofitting because of its low environmental impact due to the absence of fluid exchange with the surrounding underground, despite the lower efficiency, compared to a system that involves the extraction of fluids from the subsoil.

A database, that collects data of wells drilled since the middle of 1900, provide by public information, is used, applying a first filter by considering the following discriminant parameters: the depth (more than 1000 m), the Bottom Hole Temperature (BHT), higher than 65°C, and the nearness of possible end-users. After this operation a set of 541 wells has been obtained.  A focus on the status of the well has been performed,  such as vertical or deviated and the availability of a litho-stratigraphic data to thermally characterize the rock formations around the well.  Then, the measured temperature data was analysed to figure out the distribution of geothermal gradient and to identify different situations in terms of temperature at national scale, that could be selected later as representative case studies of high, medium and low enthalpy geothermal plant.  Moreover, the Horner plot approach have been adopted for computing equilibrium temperature at depth after drilling, obtaining the real temperatures for each well. The proximity to possible heat stakeholders was then assessed using a GIS system.

How to cite: Facci, M., Di Sipio, E., and Galgaro, A.: Energy transition and Deep Geothermal solution role: a screening procedure for the retrofitting and reuse of ex Oil&Gas wells as deep closed-loop borehole heat exchangers in Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14599, https://doi.org/10.5194/egusphere-egu23-14599, 2023.

EGU23-15410 | Posters on site | ERE1.9

Sparse image domain wavefield tomography for low-cost CCS monitoring in repurposed hydrocarbon fields 

Sjoerd de Ridder, Afsaneh Mohammadzaheri, Alexander Calvert, and Mikael Lüthje

Seismic time-lapse (4D) imaging has been considered as a key solution to monitor CO2 reservoirs. However, traditionally this technology requires dense data acquisition to produce high-resolution images. It is anticipated that monitoring will be required for more than 50 years after CCS operations cease and the monitoring phase is profit-negative. Developing cheaper 4D seismic imaging techniques is necessary. Historical knowledge of the subsurface structure in and near abandoned hydrocarbon fields, could reduce the dense data requirement of 4D imaging.

Here we present preliminary results of 4D seismic (image-domain) wavefield tomography (IDWT) using pre-stack gathers from a sparse monitoring acquisition. IDWT uses short-offset data to exploit primarily kinematic changes rather than amplitude changes. IDWT minimises the shift between baseline and monitor migrations by optimising the monitor velocity model. Pre-stack IDWT, unlike post-stack methods, can use individual shot gathers to calculate the migration images. This property is beneficial when using sparse data acquisition permitting reliable measurement of shifts between monitor and baseline. Knowing the structure of the subsurface, we can design sparse acquisition surveys for seismic deployment, to minimize uncertainty in target areas. 

We create synthetic models based on Tyra gas field, a prospective future repository of CO2 in the Danish sector of North Sea and simulate CCS and subsequent leakage scenarios. The presence of CO2 in the reservoir, as well as the effect of reservoir pressure on the overburden stress-state, changes the seismic velocity structure of the reservoir and the overburden. These velocity changes cause an apparent depth (or time) shift when migrating the data.

How to cite: de Ridder, S., Mohammadzaheri, A., Calvert, A., and Lüthje, M.: Sparse image domain wavefield tomography for low-cost CCS monitoring in repurposed hydrocarbon fields, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15410, https://doi.org/10.5194/egusphere-egu23-15410, 2023.

Coaxial Deep Borehole Heat Exchanger (DBHE) provides an alternative way to extract geothermal energy by circulating a working fluid without producing geofluids or performing injection processes. It can be used to avoid induced seismicity issues caused by injection operations in hydrothermal doublets or to repurpose damaged or non-productive wells. A detailed numerical model is required to accurately capture as well the thermo-hydraulic processes within the DBHE and the cooling effects in the surrounding reservoir. This numerical model is often high dimensional. For a real-time monitoring purpose and optimization study, a direct numerical simulation with this model is computationally intractable.

In this study, we use a physics-based machine learning method to reduce the computational cost of the performed forward model run. The physics-based machine learning method here is based on the non-intrusive reduced-basis method which expresses a physical solution in a linear combination of basis functions and weights. It is a model-order reduction technique that is mathematically proven to produce physically consistent predictions. The structure of the physics is maintained in basis functions and a machine learning model is deployed to calculate the weight for each basis function.

We show the advantages of using the physics-based machine learning method by applying it to the planned coaxial DBHE in Eden (Cornwall, UK). The forward simulation is performed using the open-source simulator GOLEM, a finite-element (FE) based simulator that is built within the MOOSE framework. In this study we provide a running time comparison between the FE simulations and the physics-based machine learning simulations. We will also evaluate the accuracy of the physics-based machine learning predictions towards the FE solutions. Here, we would like to emphasize the significant computational speed-up that allow us to obtain new temperature and pressure state predictions in real-time context and to perform optimization with numerous iterations.

How to cite: Teza, D., Santoso, R., Koltzer, N., Degen, D., Bennett, T., and Wellmann, F.: Physics-based machine learning for modeling thermo-hydraulic processes in a coaxial deep borehole heat exchanger, considering an explicit reservoir-wellbore representation: A case study of Cornwall, UK , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16369, https://doi.org/10.5194/egusphere-egu23-16369, 2023.

EGU23-16627 | Posters on site | ERE1.9

CCS Reservoir Characterisation using Carbon Quantum Dots 

Paul Glover

Efficient use of new CCS resources depends critically on their characterisation. This is as true for CCS reservoirs that are deep aquifers or reservoirs that have previously been exploited as oil or gas reservoirs. Conventional pre-existing or newly commissioned reservoir characterization methodologies, such as well logs, 3D and 4D seismic reflection and cross-well electromagnetic imaging are limited in their scope and resolution. For CCS, the  crucial characterisation is that of the connectivity of the pore network. Carbon quantum dots (CQDs) are inert carbon nano-particles less than 10 nm in diameter. They can be made easily from environmentally-friendly stock materials and remain stable in aqueous solution no matter the pH or salinity, unlike conventional nanoparticles. In fluorescence spectroscopy CQDs demonstrate a strong absorption in the UV region with peaks at 228 nm and 278 nm. Their fluorescence spectra occupy the visible spectrum and are related to the stimulating frequency. These optical properties allow the number of particles to be ascertained easily and their small size allows them to be pervasive in the porous medium. Consequently, CQDs are ideal for use as a conservative tracer. Core and bead–pack tests have shown that almost 100% of the injected CQDs can be recovered from the porous medium indicating that there would be no damage to the CCS resource by their use. Breakthrough curves (BTCs) can be used to calculate the porosity and connectivity of water saturated rocks and the water saturation and connectivity of rocks from previously exploited hydrocarbon reservoirs at temperatures up to 80oC. Indeed it is possible that CQDs could be used to monitor quantitatively the emplacement of CO2 along the injection path. Although these CQDs have an attenuated performance in carbonate rocks, surface coatings are expected to resolve this question. Surface functionalisation will also allow the properties of the reservoir, such as temperature to be measured by altering the frequency of the emerging CQDs.

How to cite: Glover, P.: CCS Reservoir Characterisation using Carbon Quantum Dots, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16627, https://doi.org/10.5194/egusphere-egu23-16627, 2023.

EGU23-16672 | Posters on site | ERE1.9

Unconventional Fractal Modelling and Simulation of Heterogeneous and Anisotropic Reservoirs 

Paul Glover, Mehdi Yaghoobpour, Piroska Lorinczi, Wei Wei, Li Bo, and Saddam Sinan

One strategy for reducing global greenhouse gas emissions as the world progresses towards net zero is to extract more hydrocarbons from existing resources. Conventional modelling and simulation of heterogeneous and anisotropic reservoirs consistently and significantly underestimates production, sometimes by as much as 70%.

We now understand that many reservoir properties are fractal, such as porosity, grain size and permeability. While water saturation and capillary pressure have distributions which arise from fractally-distributed microstructural properties. Recent work has resulted in the development of the fractal theory of Archie’s laws, providing fractal dimensions underlying both the cementation and saturation exponents that is consistent with the n-phase Archie’s law theory.

The significant underestimation of production by conventional reservoir models can be overcome by the use of advanced fractal reservoir models (AFRMs) which take account of the fractal distribution of key petrophysical properties such as porosity, grain size, cementation exponent, permeability, water saturation and capillary pressure. These models employ existing and interpolated data across an extended range of scales and take account of variability less than the 50 m seismic resolution limit. AFRMs provide production profiles that are much closer to actual production profiles.

This presentation describes briefly the AFRM approach to the modelling and simulation of heterogeneous and anisotropic reservoirs, showing how AFRMs can be generated easily to match an imposed degree of heterogeneity and anisotropy, or can be conditioned to represent the heterogeneity and anisotropy of the target reservoirs. We describe how AFRMs can be generated and normalised to represent key petrophysical parameters, how AFRM models can be used to calculate permeability, synthetic poroperm cross-plots, water saturation maps and relative permeability curves, and how AFRMs which have been conditioned to represent real reservoirs provide a much better simulated production parameters than the current best technology.

Generic AFRM modelling and simulation show that total production, production rate, water cut and the time to water breakthrough all depend strongly on heterogeneity and anisotropy. Counter to expectation, optimal production is obtained from placing both injectors and producers in the most permeable areas of heterogeneous reservoirs. Furthermore, modelling with different degrees and directions of anisotropy shows how hydrocarbon production depends critically on anisotropy direction, which changes over the lifetime of the reservoir.

AFRMs are ultimately only useful if they can be conditioned to real reservoirs. We have developed a method of fractal interpolation to match AFRMs to reservoir data across a wide scale range. Results comparing the hydrocarbon production characteristics of such an approach to a conventional krigging approach show a remarkable improvement in the modelling of hydrocarbon production when AFRMs are used; with AFRMs in moderate and high heterogeneity reservoirs returning values always within 5% of the reference case, while the conventional approach often resulted in systematic underestimations of production rate by over 70%.

Although more work needs to be done on this new approach to reservoir modelling, initial results indicate that it has the potential for improving the accuracy of modelling and simulation in heterogeneous and anisotropic reservoirs by an order of magnitude or more.

How to cite: Glover, P., Yaghoobpour, M., Lorinczi, P., Wei, W., Bo, L., and Sinan, S.: Unconventional Fractal Modelling and Simulation of Heterogeneous and Anisotropic Reservoirs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16672, https://doi.org/10.5194/egusphere-egu23-16672, 2023.

EGU23-17292 | Posters on site | ERE1.9

Molecular simulation of stripping of crude oil by CO2 in tight reservoirs 

Qian Wang, Jian Shen, Bai Jie, Paul W.J. Glover, and Piroska Lorinczi

Tight oil reservoirs are often oil-wet and contain surface adsorbed layers of hydrocarbon. Improvement of production lies in part in the ability to produce this adsorbed oil for its own sake and to unblock small pores that can improve the relative permeability of the reservoir. In this paper we have used molecular modelling and simulation first to study the formation of adsorbed oil films made from n-alkanes of 5 different molecular weights (nC7, nC12, nC18, nC22, nC25) on an hydroxylated ->-SiO2 surface, and then to examine the process of stripping oil from these layers using carbon dioxide, nitrogen and water. It was found that all n-alkanes but nC12 formed a monolayer oil film, while nC12 formed a three-layer oil film. Molecular weight, length and flexibility of the n-alkane were all factors in oil film formation. It was found that flooding with CO2 is able to strip all of the modelled n-alkanes from the α-SiO2 surface effectively. The time required to strip the n-alkane was longer for n-alkanes with higher molecular weights. The stripping process was divided into three stages: (i) CO2 diffusion and dissolution, (ii) competitive adsorption, and (iii) oil film push-off. A fourth stage was recognized only for light n-alkanes, and which involved the dissolution of CO2 in mobilized n-alkane, leading to improvements in its mobility. Comparative simulations using nC12 showed that N2 and H2O exhibit no efficacy in stripping n-alkanes from surface adsorbed oil films. The efficacy of CO2 was attributed to (i) it being a polar molecule that is attracted to the hydroxylated silica surface, (ii) its miscibility in n-alkanes, and (iii) that it is in a supercritical state at reservoir conditions. The failure of N2 arises because it is a non-polar molecule with no affinity for the surface and exists as an immiscible gas at reservoir conditions. Water was ineffective, because, though polar, it is immiscible in the oil layer and so cannot access the rock surface. Consequently, CO2-flooding is expected to be particularly effective in improving production from tight oil-wet clastic reservoirs.

Key words: tight reservoir; pore throats; CO2 flooding; oil film stripping; molecular simulation

How to cite: Wang, Q., Shen, J., Jie, B., Glover, P. W. J., and Lorinczi, P.: Molecular simulation of stripping of crude oil by CO2 in tight reservoirs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17292, https://doi.org/10.5194/egusphere-egu23-17292, 2023.

EGU23-71 | ECS | Orals | ERE4.3

Spectroscopic Studies and Confirmatory Geochemical Analyses of Rare Earth Element Bearing Rocks from the Neoproterozoic Siwana Ring Complex, Rajasthan, India 

Saraah Imran, Ajanta Goswami, Angana Saikia, Hrishikesh Kumar Rai, and Bijan Jyoti Barman

Abstract:

Rare earth elements (REEs) are of high economic value owing to their electronic, magnetic, optical, catalytic, and phosphorescent properties, thereby making them an important part of the development of green technology. They exhibit characteristic sharp absorption features in reflectance spectra in the visible-near infrared (VNIR) to short-wave infrared (SWIR) region due to their 4f-4f orbital intra-configurational electronic transitions.

In this study laboratory based close-range imaging spectroscopy techniques are used along with confirmatory geochemical analytical techniques (petrography, ICPMS, SEM and EPMA) to study 20 samples collected from REE-bearing rocks of the Neoproterozoic Siwana Ring Complex (SRC), a collapsed caldera structure situated in Barmer District, Rajasthan (India).

The SRC is an anorogenic, rift-related bimodal volcano-plutonic rock association belonging to the Malani Igneous Suite. It comprises of felsic and basic volcanic lava flows, rhyolite, peralkaline granite, pyroclastics, tuff and later microgranite, aplite and felsite dykes.

The spectral reflectance curves of the samples collected using an ASD FieldSpec4 (350-2500 nm) exhibit characteristic absorption dips at 439, 491, 580, 740 and 800 nm indicating the presence of Nd3+. Other major absorption dips are attributed to the presence of Sm3+, U4+, etc. Various combinations of absorption features in the VIS-SWIR region indicate the presence of minerals like biotite, epidote, chlorite, nontronite, goethite, and REE fluorocarbonates. The Fourier Transform Infrared (FTIR) spectra of the samples collected using a Thermo Fisher Scientific Nicolet 6700 (400-4000 cm-1) show symmetric and asymmetric bending and stretching vibration features of Si-O, P-O and O-H bonds, which are diagnostic of minerals like aegirine, riebeckite, and REE minerals like monazite apart from other major silicate minerals like quartz and feldspar. The presence of these minerals is confirmed by mineral chemistry, bulk and trace element data.

The observations from the spectroscopic studies seem to correlate well with data obtained from various geochemical analyses. This study provides spectroscopic information on the rocks from SRC for the first time. It shows the proficiency of spectroscopic studies as a cost-effective and non-destructive technique for the identification of REE minerals which can be used before detailed geochemical and mineralogical studies as well as future exploration.

Keywords: Siwana Ring Complex, Spectroscopy, REE

Abbreviations:

ASD – Analytical Spectral Devices, Inc.

EPMA – Electron Probe Micro Analyzer

FTIR – Fourier Transform Infrared

ICPMS – Inductively Coupled Plasma Mass Spectrometry

REE – Rare Earth Elements

SRC – Siwana Ring Complex

SWIR – Short Wave Infrared

VNIR – Visible Near Infrared

How to cite: Imran, S., Goswami, A., Saikia, A., Kumar Rai, H., and Jyoti Barman, B.: Spectroscopic Studies and Confirmatory Geochemical Analyses of Rare Earth Element Bearing Rocks from the Neoproterozoic Siwana Ring Complex, Rajasthan, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-71, https://doi.org/10.5194/egusphere-egu23-71, 2023.

EGU23-1642 | ECS | Orals | ERE4.3

HyMap airborne imaging spectroscopy for mineral potential mapping of cupriferous mineralization in a semi-arid region based on pixel/sub-pixel hydrothermal alteration minerals mapping – A case study 

Soufiane Hajaj, Abderrazak El Harti, Amine Jellouli, Amin Beiranvand Pour, Saloua Mnissar Himyari, Abderrazak Hamzaoui, Mohamed Khalil Bensalah, Naima Benaouis, and Mazlan Hashim

Recently, hyperspectral datasets recognized a great interest in mineral exploration studies due to their high accuracy in detecting and mapping hydrothermal alteration minerals. Remote and mountainous regions are hardly accessible by geologists, while the spectral richness of imaging spectroscopy could provide detailed information about geology/mineralogy without having a direct contact with the ground surface. The Kerdous inlier in the Anti-Atlas belt of Morocco is recognized by several occurrences of Cu, Pb, Zn Au, Ag, and Mn mineral deposits. This study is carried out in Eastern Kerdous where the abandoned Idikel mine occurs in order to perform a high-resolution mineral potential map using Gamma-Fuzzy logic approach with twenty HyMap-derived layers. The HyMap-based thematic layers were generated using Directed Principal Component Analysis (DPCA), Relative Absorption Band Depth (RBD), and the Mixture Tuned Matched Filtering (MTMF) for pixel/sub-pixel mineral mapping. The hydrothermally altered regions within the study area reveal several Minerals/Mineral mixtures of hematite, illite, kaolinite, montmorillonite, muscovite, topaz, dolomite, and pyrophyllite. Then, the line density map extracted automatically from the HyMap data image was also integrated. The findings of the image processing were validated using field investigation, petrographic, and XRD analysis. This study demonstrates the great potential of the present research methodology and HyMap as a tool for mineral exploitation in similar areas in Morocco's western Anti-Atlas belt.

How to cite: Hajaj, S., El Harti, A., Jellouli, A., Beiranvand Pour, A., Mnissar Himyari, S., Hamzaoui, A., Khalil Bensalah, M., Benaouis, N., and Hashim, M.: HyMap airborne imaging spectroscopy for mineral potential mapping of cupriferous mineralization in a semi-arid region based on pixel/sub-pixel hydrothermal alteration minerals mapping – A case study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1642, https://doi.org/10.5194/egusphere-egu23-1642, 2023.

Underground mining is increasing in Korea, primarily due to the depletion of high quality mineral resources from surface open pit mining, and also due to the fact that environmental regulations are gradually tightened and strengthened. For sustainable mine design, safety and environmental issues are the most important factors forcing more specified and systematic guidelines to secure the stability of the mine openings and adits. However, with complex geological settings and various types of rock discontinuities, a geological mapping process to analyze the behavior of fractured rockmass is generally time-consuming. Information on the geologic structures are often collected by visual observation and analyzed based on two-dimensional drawings. Even worse, very limited and unrepresentative data are collected specially at operating mines leading to unreliable conclusions. Hence, construction of three-dimensional hydrogeological models adopting sophisticated surveying techniques has become a routine site investigation process. Laser scanners of high-end specifications are widely used in Korea. In this study, the Trimble X7 with automatic calibration and in-field registration capability has been used to collect accurate geospatial information at an underground limestone mine adopting the room-and-pillar method, with three drifts 9~12m wide and 6m high. For the two pillars of major stability concern, laser scanning was performed to obtain point-cloud data from which a total of 581 discontinuities were extracted. A discrete fracture network was simulated and the stability was evaluated based on the safety factor and displacement using a numerical model.

 

How to cite: Baek, H. and Kim, D.: Application of the 3-D laser scanning method for assessing the stability of fractured rockmass at an underground limestone mine in Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1750, https://doi.org/10.5194/egusphere-egu23-1750, 2023.

Rare earth elements (REE) have been a focus of global interest because of their irreplaceable role in developing “low carbon” technologies. The Bayan Obo is the world’s largest REE deposit, but its genesis is still highly debated. It is considered to have a close genetic association with carbonatite due to the presence of the carbonatite dykes around the orefield, as well as the geochemical similarities between these dykes and the orebody. However, the evolution of the carbonatite dykes and their REE mineralization are still poorly understood, hindering the interpretation of the genesis of the deposit. More than 100 carbonatite dykes have been found within the area of 0-3.5km nearby the orebodies of the deposit. These dykes show significant variations in mineralogy and geochemistry and were classified into dolomite (DC) and calcite carbonatite (CC). The rocks show an evolutionary sequence from DC to CC, and their corresponding REE contents increased remarkably, with the latter having very high REE content (REE2O3 up to 20 wt. %). The DC is composed of coarse-grained dolomite, magnetite, calcite, and apatite without apparent REE mineralization. The medium-grained calcites, and significant amounts of REE minerals, such as monazite, bastnäsite, and synchysite, make up CC. The REE minerals have a close relationship with barite, quartz, and aegirine. The REE patterns of dolomite and calcite in DC showed a steep negative slope with a strong LREE enrichment. In contrast, the calcite from CC has a near-flat REE pattern enriched in both LREE and HREE. Besides, apatite and magnetite in CC are characterized by strong REE enrichment compared to those from DC. Based on detailed petrology, mineralogy, and element geochemistry, we propose that strong fractional crystallization of initial carbonatitic melts led the REE enriched in the residual melt/fluid to form REE mineralization. In addition, sulfate, alkalis, and silica components play an important role in REE transportation and precipitation.

How to cite: Yang, J. and Song, W.: Mineralogy, major and trace element geochemistry of rock-forming and rare earth minerals in the Bayan Obo (China) carbonatite dykes: implications for REE mineralization, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2318, https://doi.org/10.5194/egusphere-egu23-2318, 2023.

EGU23-3180 | ECS | Posters on site | ERE4.3

Radiogenic and stable Sr isotope geochemistry of regolith hosted REE deposits: a preliminary report 

Hamed Pourkhorsandi, Vinciane Debaille, Sophie Decrée, Jeroen de Jong, Ali Yaraghi, Georges Ndzana, Martin Smith, Kathryn Goodenough, and Jindřich Kynický

The increasing global demand for the rare earth elements (REE), that are critical for green energy production, justifies the necessity of understanding REE ore formation processes [1]. The main type of REE mineralization is mostly found in association with carbonatites and alkaline rocks [1,2]. In addition, in some cases the REE can also reach economical levels in secondary products called supergene REE resources [3]. Primary ore mineralizations mostly are composed of mineral phases that are highly unstable and easily soluble in the near-surface conditions in time. The secondary concentration of the REE in weathering regolith into economic deposits is more favourable than those in primary igneous rocks. As the main source of global heavy-REE, weathering deposits in southern China are the most studied ores of this type [4]. Recently, because of the recent surge in REE deposit exploration and their geological importance, other potentially similar deposits are being studied worldwide. Most of these works focus on mineralogical and elemental aspects of these systems. However, those weathering (in cooperation with alteration) systems are complex and a lot of questions on their formation remain unanswered.

In this work, we focus on the isotopic characterization of regolith hosted REE deposits. To better understand their formation, we utilize stable 88Sr/86Sr and radiogenic 87Sr/86Sr ratios, which have been used widely in understanding chemical weathering [5]. Mainly controlled by the incongruent weathering of primary minerals, Sr isotopes can help to identify the sources involved and the main factors affecting regolith hosted REE deposit formation. Strontium is especially important because, as Ca and K, it occurs in different REE-bearing primary and secondary minerals such as carbonates, ancylite, apatite, clays etc.

We will present different regolith profiles’ Sr isotopic data from Asia and Africa. Combining with the elemental and mineralogical data, we will devise a formation model for regolith hosted REE deposits.

References: [1] Goodenough et al. (2016) Ore Geo. Rev., 72, 838. [2] Chakhmouradian & Zaitsev (2012) Elements 8, 347. [3] Estrade et al. (2019) Ore Geo. Rev., 112, 103027. [4] Li et al. (2019) Econ. Geol., 114, 541. [5] Pett-Ridge et al. (2009) GCA, 73, 25.

 

How to cite: Pourkhorsandi, H., Debaille, V., Decrée, S., de Jong, J., Yaraghi, A., Ndzana, G., Smith, M., Goodenough, K., and Kynický, J.: Radiogenic and stable Sr isotope geochemistry of regolith hosted REE deposits: a preliminary report, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3180, https://doi.org/10.5194/egusphere-egu23-3180, 2023.

EGU23-4661 | Posters on site | ERE4.3

Gamma radiation for rare earth elements (REEs) in deep-sea sediments 

Changyoon Lee, Yuri Kim, Yoon-Mi Kim, Sung Kyung Hong, and Seok-Hwi Hong

Gamma ray is routinely used for correlation, evaluation or classification of minerals and rocks on continent and ocean. Using natural gamma radiation (NGR) derived from Integrated Ocean Drilling Program (IODP) and Ocean Drilling Program (ODP), this study focuses on the correlation between lithology and REE (Rare Earth Element)-bearing sediments in two deep-sea areas, IODP Expedition 329 in the Southwest Pacific and ODP Leg 199 Sites in the Northeast Pacific basins, where values of the REEs are abundant. Deep-sea sediments are consisting mainly of clays, calcareous oozes and siliceous oozes. As a result of the correlation, the REEs prefer to the clays rather than oozes and high values of the REEs correspond with intervals of the clays where the upper sediments (0–70 mbsf) are. The clays show relatively high values of the gamma radiation and the differences between significant elements (Th, U and K) for gamma radiation, derived from geochemical analysis at every site, show two trends reflecting characteristics of regions. Therefore we suggest that the gamma radiation is fully useful for detecting REEs in the deep-sea sediments and plays a role as a predictable tool for finding quantitative REEs. 

How to cite: Lee, C., Kim, Y., Kim, Y.-M., Hong, S. K., and Hong, S.-H.: Gamma radiation for rare earth elements (REEs) in deep-sea sediments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4661, https://doi.org/10.5194/egusphere-egu23-4661, 2023.

Carbonatites are known to host over 95% of light rare earth element (REE) resource, and the REEs are commonly hosted in minerals with well-established extraction methods. Most REE mineralized carbonatites are associated with hydrothermal alteration/recrystallization. Identifying the source composition and role of recrystallization is crucial for understanding the formation of the giant carbonatite-associated REE deposit. Here we report the first in-situ carbon and magnesium isotopic compositions for the hosting dolomite in the Bayan Obo deposit.

In-situ carbon isotope analyses of dolomite from the coarse-grained (CM), fine-grained (FM) and heterogeneous-grained (HM) samples show a wide range of δ13C values (-5.19‰ to 2.08‰), which is distinct from the common mantle-derived carbonatite and slightly overlaps the range of sedimentary carbonate. CM dolomite displays almost homogeneous carbon isotope compositions (δ13C=-1.29‰ to 0.16‰) with the average δ13C of -0.82‰. Recrystallized dolomites from both FM and HM samples vary greatly, and FM dolomite generally displays a heavier δ13C range (-3.94‰ to 2.08‰) compared to that for HM dolomite (-5.19‰ to 0.64‰). CM dolomite also shows relative consistent Mg isotope compositions in the range of -0.27‰ to 0.05‰ with an average of -0.10‰, which is similar to the mantle value. δ26Mg values of FM and HM dolomites vary greatly from -1.18‰ to 0.06% with averages of -0.40‰ and -0.32‰, which are lighter compared to that of CM dolomite. The recrystallized dolomites (FM and HM) are characterized by depleted light REE (LREE) and increased Pb/CeN features compared to the pristine dolomite (CM). Moreover, the LREE depletion and Pb/CeN increase correlate with the lighter Mg isotope compositions. The highly variable C isotopes recorded by FM and HM dolomites (lighter or heavier compared to the pristine dolomite) involve both recrystallization and degassing. The combined in-situ Mg and C isotope compositions of the pristine dolomite suggest the Bayan Obo carbonatite sourced from the mantle previously fertilized by fluids derived from the carbonate-bearing subduction slab.

How to cite: Chen, W., Yang, F., and Lu, J.: In-situ C and Mg isotopes of dolomite from the giant Bayan Obo REE deposit: Implications for recrystallization and recycled carbonate in the source, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4823, https://doi.org/10.5194/egusphere-egu23-4823, 2023.

As the world's largest rare earth elements (REEs) deposit, the giant Bayan Obo deposit accounts for more than one third of the world's REEs resources. Fenitization is an alkali metasomatism that widely occurs around the carbonatite dykes at Bayan Obo and recent studies reveal huge quantities of REEs could be transferred from the alkaline magma to fenite (Sokół et al., 2022). However, the contribution of fenitization to REE mineralization at Bayan Obo remains unclear. Here, we present bulk rock chemical compositions, in-situ chemical and C-Sr isotopic investigations of calcite and apatite together with Th-Pb ages of monazite, aiming to provide new constraints on REE mineralization during fenitization.

Carbonatite at Wu dyke is mainly composed of calcite, aegirine and barite associated with REE minerals dominated by bastnasite and parisite, which intruded into the surrounding wall rocks of quartz conglomerate. The associated fenites include the close Na-fenite and faraway K-fenite. Na-fenite contains calcite, riebeckite, aegirine and apatite with minor monazite and bastnasite in association with barite. K-fenite consists of K-feldspar and quartz with accessory riebeckite and albite. Both REE and SO3 contents decrease from the center to the wall rocks. REE are most enriched in the centered carbonatites (up to 7.39 wt%), and Na-fenites also display strong REE enrichment (9876-22492 ppm). Of note, high-grade Na-fenite is characterized by the highest LREE concentrations among fenites, whereas HREE is most enriched in medium-grade Na-fenite. The latter is dominantly controlled by apatite, which hosts abundant HREE (118-677 ppm). Calcite from fenites displays flat REE patterns with more depleted LREE (La/YbN=0.28-3.02) compared to that within carbonatite (La/YbN=1.66-6.52). Th-Pb ages of monazite from fenites cover a wide range from 420 Ma to 1.27 Ga, which suggests these fenites have also undergone the early Paleozoic hydrothermal alteration. In-situ Sr and C isotope analyses of calcite from carbonatite define a limited range (87Sr/86Sr=0.70344 to 0.70358 and δ13C=-4.36 to -5.1 ‰), which are consistent with a mantle origin . 87Sr/86Sr and δ13C values for calcite within Na-fenite show larger variations of 0.70358 to 0.70620 and -4.92 to -9.87 ‰, respectively. Negative shift in δ13C values suggest degassing through the fenitizing reaction of 18CO32-+2Na++3(Mg2+,Fe2+)+2Fe2++8SiO2+24H++0.5O2= Na2(Mg,Fe2+)3Fe3+2Si8O22(OH)2+18CO2+11H2O. More radiogenic Sr isotopic compositions of fenites result from both assimilation of wall rocks during fenitization and the redistribution of Sr isotopes among minerals during the Paleozoic hydrothermal alteration.

Carbonatite-exsolved fenitizing fluids result in predominant REE enrichment within Na-fenite accompanying with light and heavy REE mineralization. LREE mineralization is dominated by monazite precipitation, and HREE enrichment is mostly controlled by apatite. Sulfate is an important ligand for REE transportation and mineralization during fenitization. Barite crystallization and simultaneous precipitation of LREE-bearing minerals lead to fenitizing fluids abundant in HREE, promoting the further formation of HREE-rich apatite.

Reference:

Sokół K., Finch A.A., Hutchison W., et al., 2022. Quantifying metasomatic high-feld-strength and rare-earth element transport from alkaline magmas. Geology, https://doi.org/10.1130/G49471.1.

 

 

How to cite: Yang, F. and Chen, W.: Fenitization associated with the Wu carbonatite dyke at Bayan Obo (Inner Mongolia, China): Implications for REE mineralization, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5183, https://doi.org/10.5194/egusphere-egu23-5183, 2023.

EGU23-8008 | Posters on site | ERE4.3

The metasomatism affecting karstic bauxites from the south-central Pyrenees, Catalonia (NE Spain) and its implications on the REE geochemistry in similar geological settings. 

Josep Roqué-Rosell, Pablo Granado, Juan Diego Martín-Martín, Jordi Ibáñez-Insa,, Ivanna Pérez Bustos, Roger Roca-Miró, and Abigail Jiménez Franco

Karstic bauxite deposits are the main resource of aluminum in Europe and are formed through a combination of weathering, leaching, and deposition processes known as bauxitization. Bauxites have recently been proposed as unconventional resources of rare-earth elements (REE) as well. The studied karstic bauxite deposits are located on the salt-detached Serres Marginals thrust sheet, at the external most unit of the south-central Pyrenees (Catalonia, NE Spain). The Pyrenean bauxites are found overlaying and filling karstic surfaces forming aligned pockets up to several meters thick. These deposits have been mined for more than 20 years and present high variability in SiO2, Al2O3 and Fe2O3 contents. Here, we characterize these deposits for the first time by a combination of field geology, XRD, FTIR and XRF to determine their formation, mineralogy, and geochemistry and to understand the causes affecting their compositional variations. Field data indicate that the bauxite deposits fill a paleokarst system affecting Dogger dolostones and/or Tithonian-Berriasian limestones. XRD data indicate that the studied karstic bauxites are mainly composed of Al-rich minerals kaolinite and boehmite, in addition to the Fe-oxide hematite, and lesser amounts of the Ti-oxides rutile and anatase. The detailed study of the FTIR spectra also confirmed the presence of diaspore and dickite. XRF data confirm the presence of varying amounts of Al, Fe and Si in addition to varying low contents of REE. These results suggest that boehmite was formed first during bauxitization and later transformed to diaspore, kaolinite and finally to dickite upon metasomatism. The presence of dickite in faults and fractures provides a direct proof for such fluid circulation. Our results suggest that the mechanisms responsible of the compositional variations in karstic bauxites are rather complex and fall beyond the standard bauxitization processes. The observed metasomatism should be further assessed, since the inferred fluid-rock interactions are susceptible to affect and mobilize REE not only in the south-central Pyrenees karstic bauxites but elsewhere in similar geological settings.

How to cite: Roqué-Rosell, J., Granado, P., Martín-Martín, J. D., Ibáñez-Insa,, J., Pérez Bustos, I., Roca-Miró, R., and Jiménez Franco, A.: The metasomatism affecting karstic bauxites from the south-central Pyrenees, Catalonia (NE Spain) and its implications on the REE geochemistry in similar geological settings., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8008, https://doi.org/10.5194/egusphere-egu23-8008, 2023.

EGU23-9090 | Orals | ERE4.3

Blast Hole Rock Cuttings analysis: Design and Implementation of an open Architecture LIBS System 

Ad Maas, Jorgina Akushika, and Federico Arboleda

This paper presents the development and implementation of a LIBS (Laser-Induced Breakdown Spectroscopy) system based on a robotic arm for fast chemical characterization of blast hole rock cuttings in open pit mining. The system is designed with an open architecture, allowing for the easy integration of additional sensors such as a spectrophotometer and a magnetic susceptibility meter. The use of the LIBS system significantly reduces the time required to characterize the raw material and obtain a broader characterization, including geological characterization. The preliminary results of this development demonstrate the potential of the LIBS system in improving the efficiency and accuracy of rock characterization in open pit mining operations.

How to cite: Maas, A., Akushika, J., and Arboleda, F.: Blast Hole Rock Cuttings analysis: Design and Implementation of an open Architecture LIBS System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9090, https://doi.org/10.5194/egusphere-egu23-9090, 2023.

Recently, due to the active spread of electric vehicles, the demand for batteries is increasing fast, and for this reason, the exploration for lithium that is an essential mineral for battery production, is increasing. In Korea, lithium exploration is also being conducted around deposits where lithium was identified in the past. However, most lithium mines are located in very rough terrain, so it is not easy to conduct a surface geological and geophysical exploration. Without considering complex topography, errors may occur in the inversion of surface geophysical exploration data, and in particular, it is necessary to use precise topographic information for the three-dimensional inversion. In this study, we would like to introduce a case study using high-resolution topographic data obtained from a drone-mounted LIDAR in the three-dimensional inversion of surface resistivity and IP data conducted for lithium exploration. The target area is the Boam Mine, located in the Middle East of Korea. Surface geophysical exploration was conducted along a road and ridge of the mountain, which are relatively easy to set up the survey line. Because existing topographic maps that are publically available did not include mining traces related to mining development and topographical changes formed by nearby roads, it is not adequate for the 3D inversion of surface resistivity and IP data. To acquire precise topographical information, aerial photography and LIDAR measurements using drones were performed. A numerical topographic model was constructed using the obtained high-precision DEM (digital elevation map). By applying this to the three-dimensional inversion, the distribution of the underground mineralization zone was estimated. The interpreted results were compared with the existing drilling results performed near the mine. Comparing the two results, drilling surveys using only surface geological information proceeded in the direction in which the mineralization zone did not develop. Drone LIDAR measurement is a costly exploration method and is difficult to use actively at all exploration sites. However, if three-dimensional inversion is required where the surface topography is very complex, as in this survey area, it could give more reliable inversion results.

How to cite: Son, J., Kim, C., and Bang, E.: Three-dimensional interpretation of DC resistivity/IP survey for Lithium exploration using high-precision topographic information from drone-mounted LIDAR., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10680, https://doi.org/10.5194/egusphere-egu23-10680, 2023.

EGU23-10689 | Posters on site | ERE4.3

Investigations of Vanadiferous Titanomagnetite Deposit using Drone Magnetic and Electrical Resistivity Surveys in Korea 

Changryol Kim, Jeongsul Son, Eunseok Bang, Gyesoon Park, and Bona Kim

Recently, the demands for energy storage minerals such as vanadium and lithium are increasing as the use of the batteries for electrical vehicles has increased. Vanadium is one of the energy storage minerals occurred in Korea. In this study, vanadium mineralized zones of the ore deposit, named as Gwanin deposit, was investigated using geophysical exploration techniques. The mineralized zone is known as vanadiferous titanomagnetite (VTM) deposit, originated from pre-cambrian igneous intrusions (850-870 m.a.), located in the northwest region of Korea. Since the vanadium has occurred along with magnetite (low electrical resistivity and high magnetic susceptibility) in the study area, geophysical exploration techniques such as magnetic and electrical resistivity surveys were employed. For magnetic exploration, the drone magnetic survey technique was used since it provides more precise and higher resolution data than any other aerial magnetic exploration techniques for relatively small and mountainous areas. In addition, electrical resistivity data were obtained from the six survey lines in the study area. 3D inversion was performed with magnetic and resistivity data. The anomaly zones of low electrical resistivities and high magnetic susceptibilities were interpreted as VTM mineralized zones from the two different inversion results. The mineralized zones were identified from the drilling investigation for overlapping locations of the anomaly zones. The results of the study have shown that magnetic and electrical resistivity techniques are very effective tools for exploring ore deposits of vanadium resource accompanied with magnetite. In the future, drone magnetic exploration technique combined with other (surface) geophysical exploration techniques would provide more effective results of precise geophysical surveys for relatively small and mountainous areas with similar ore deposit environments.

How to cite: Kim, C., Son, J., Bang, E., Park, G., and Kim, B.: Investigations of Vanadiferous Titanomagnetite Deposit using Drone Magnetic and Electrical Resistivity Surveys in Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10689, https://doi.org/10.5194/egusphere-egu23-10689, 2023.

Apatite with high REE content is common in alkaline rocks, carbonatites and products of hydrothermal processes. The REE concentrations could enter mineral structure by different substitution mechanisms (Fleet et al., 2000) and the factors controlling the composition of high-REE apatite are not completely understood. New experimental data (Stepanov et al., 2023) show that at 800 °C and 10 kbar apatite crystalizing from felsic melt with addition of NaCl contains 14 wt.% ΣREEOx and coexists with britholite (37.2 wt.% ΣREEOx). The results suggest that equilibrium has been established during the run and both apatite and britholite contained REE in [Si4+REE3+] to [Ca2+P5+] solid solution, whereas the coupled substitution [Na1+REE3+] to [2Ca2+] was insignificant despite crystallisation from an alkaline, Na-rich melt. Coupling of the new experimental data allowed to constrain the width of the miscibility gap between apatite and britholite, and suggest complete miscibility between apatite and britholite above 950 °C. The substitution [Na1+REE3+] apparently develops mainly in apatite replacement reactions. Therefore, REE content and substitution mechanisms could be useful tools for interpretation of magmatic and metasomatic/hydrothermal associations in alkaline volcanic and plutonic rocks.
References 
Fleet, M., Liu, X., Pan, Y., 2000. Rare-earth elements in chlorapatite [Ca-10(PO4)(6)Cl-2]: Uptake, site preference, and degradation of monoclinic structure. American Mineralogist 85, 1437–1446.
Stepanov, A.S., Zhukova, I.A., Jiang, S.-Y., 2023. Experimental constraints on miscibility gap and partitioning between britholite and chlorapatite in alkaline melt. American Mineralogist.

How to cite: Zhukova, I. and Stepanov, A.: Experimental data on REE in apatite in high-REE environments: distinguishing magmatic and metasomatic compositions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11255, https://doi.org/10.5194/egusphere-egu23-11255, 2023.

EGU23-11997 | Orals | ERE4.3

Hyperspectral mineral mapping for underground mining 

Moritz Kirsch, Mary Mavroudi, Sam Thiele, Sandra Lorenz, Laura Tusa, René Booysen, Erik Herrmann, Ayoub Fatihi, Robert Möckel, Thomas Dittrich, and Richard Gloaguen

Future mining will increasingly require rapid and informed decisions to optimise ore extraction and valuation. In this context, the use of hyperspectral imaging has been proven to be effective for geological mapping in surface mining operations. The potential of hyperspectral methods in underground mining environments, however, remains underexplored due to challenges associated with illumination and surface water. Our contribution addresses this gap by evaluating different lighting setups and the effect of moisture on the spectral quality of hyperspectral data in a laboratory setup. We also compared three commercially available, visible-near infrared to shortwave infrared sensors to assess their suitability for underground hyperspectral scanning. As a demonstration, we acquired hyperspectral data from three adjacent outcrops in the visitor’s mine of Zinnwald, Germany, where rocks of a Late Variscan Sn-W-Li greisen-type deposit are exposed in representative underground mining conditions. A photogrammetric 3D digital outcrop model was used to correct for illumination effects in the data. We then estimated mineral abundance and lithium content across the mine face employing an adapted workflow that combines quantitative XRD measurements with hyperspectral unmixing techniques. Laser-induced breakdown spectroscopy was used to validate the results. While there are still challenges to overcome, this study proves that hyperspectral imaging techniques can be applied underground to yield rapid and accurate geological information. This application will pave the way for the safe, digital and automated underground mine of the future.

How to cite: Kirsch, M., Mavroudi, M., Thiele, S., Lorenz, S., Tusa, L., Booysen, R., Herrmann, E., Fatihi, A., Möckel, R., Dittrich, T., and Gloaguen, R.: Hyperspectral mineral mapping for underground mining, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11997, https://doi.org/10.5194/egusphere-egu23-11997, 2023.

EGU23-12056 | ECS | Posters on site | ERE4.3

ROBOMINERS resilient reflectance/fluorescence spectrometers 

Christian Burlet, Giorgia Stasi, Simon Godon, Roza Gkliva, Laura Piho, and Asko Ristolainen

ROBOMINERS (Bio-Inspired, Modular and Reconfigurable Robot Miners, Grant Agreement No. 820971, http://www.robominers.eu) is a European project funded by the European Commission's Horizon 2020 Framework Programme. The project aims to test and demonstrate new mining and sensing technologies on a small robot-miner prototype (~1-2T) designed to target unconventional and uneconomical mineral deposits (technology readiness level 4 to 5) (Lopez and al. 2020).

As part of the ROBOMINERS sensor array development, a set of mineralogical and geophysical sensors are designed to provide the necessary data to achieve a “selective mining” ability of the miner to reduce mining waste production and increase productivity of a small mining machine. To achieve this, the robot should have the ability to react and adapt in real time to geological changes as it progresses through a mineralized body. This study focuses on a set of compact sensors designed for ultrahigh-resilience and continuous operation in high pressure/vibrations/temperature environment. They are based on reflectance/fluorescence measurements in the visible/near infrared range, using a broadband light source (tungsten-halogen lamps) in reflectance mode and 365nm UV LED in fluorescence mode. 

The ROBOMINERS reflectance/fluorescence spectrometer “Mk1” was developed in collaboration with Taltech University. The spectrometer is built around a monolithic spectrometer (Hamamatsu C12800MA and a wifi capable microcontroller (Arduino RP2040 Connect).. As the ROBOMINERS prototype will be operated by ROS2 (Robotic Operating System v2 - https://www.ros.org/ ), we decided to implement a Micro-ROS publisher on the microcontroller.

The first field trials of the sensor have been carried out in the entrance of abandoned mine (baryte and lead mine, Ave-et-Auffe, Belgium), with the sensor integrated directly in the propulsion mechanism of the “RM3”’ ROBOMINERS prototype. This test allowed to demonstrate the immunity of the sensors to  to shocks, water and dust with no measurable de-calibration of the spectrometer.

References.

Lopes, B. Bodo, C. Rossi, S. Henley, G. Žibret, A. Kot-Niewiadomska, V. Correia, Advances in Geosciences, Volume 54, 2020, 99–108

 

 

How to cite: Burlet, C., Stasi, G., Godon, S., Gkliva, R., Piho, L., and Ristolainen, A.: ROBOMINERS resilient reflectance/fluorescence spectrometers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12056, https://doi.org/10.5194/egusphere-egu23-12056, 2023.

EGU23-13081 | Posters on site | ERE4.3

The surface chemistry of carbonatite soils: Implications for REE resources. 

Martin Smith, Charles Beard, Isaac Watkins, Sam Broom-Fendley, Frances Wall, Xu Cheng, Yan Liu, Wei Chen, and Jindrich Kynicky

The rare earth elements (REE), and in particular neodymium and dysprosium, are essential for the development of renewable energy. At present the REE are sourced from either low concentration weathered granitoid (ion adsorption clay) deposits in southern China, or from high concentration carbonatite-related deposits [1], especially the World’s dominant REE mine at Bayan Obo, China, but also including the Mt Weld weathered carbonatite, Australia. Weathered carbonatites (e.g. Tomtor, Russia; Mount Weld, Australia) are some of the world’s highest grade REE deposits. As part of the NERC Global Partnerships Seedcorn fund project WREED, we have carried out preliminary investigations in weathering products from carbonatite hosted REE deposits. Three end member deposit styles can be identified – in situ residual deposits, where carbonate dissolution has generated primary REE mineral enrichment on palaeosurfaces or in karst; supergene enrichment from dissolution and reprecipitation of REE phosphates and fluorcarbonates forming hydrated phosphates or authigenic carbonate minerals; clay and oxide caps (either from in situ weathering or from soil transport from surrounding rocks) that may hold the REE adsorbed to mineral surfaces (c.f. the ion adsorption deposits). High grade weathered carbonatite deposits typically consist of supergene horizons, that may be phosphate-rich due to dissolution and re-precipitation of apatite and monazite during the weathering process (Mount Weld [2][3]), overlain by later sediments that may be REE enriched by accumulation of residual minerals (e.g. Tomtor [4]). The mineralogy of the ore zone is linked to, but distinct from, the unweathered carbonatite rock, and includes phosphates, crandallite-group minerals, carbonates and fluorcarbonates and oxides. We have carried out leaching studies, SEM examination and XPS characterisation of soil and weathered rock samples from a range of deposits. Residual and supergene processes can result in enrichments up to 100x times bedrock concentrations, with residual enrichments in particular hosted in monazite and bastnäsite. Supergene enrichment results in more complex mineralogy which may present processing challenges. Clay-rich soils have much lower REE concentrations. However, sequential leaching studies demonstrate that a significant proportion of REE are present at trace levels in the oxide fraction in residual and supergene deposits. In clay caps the easily leachable fraction of REE matches that of ion adsorption deposits and may represent a potentially easily extractable resource.

 

References

[1] Wall and Chakhmouradian, 2012, Elements 8, 333-340;

[2] Duncan and Willett, 1990, Geology of Mineral Deposits of Australia pp. 591-597;

[3] Lottermoser, 1990, Lithos 24, 151-167;

[4] Kravchenko and Pokrovsky, 1995, Econ. Geol. 90, 676-689;

How to cite: Smith, M., Beard, C., Watkins, I., Broom-Fendley, S., Wall, F., Cheng, X., Liu, Y., Chen, W., and Kynicky, J.: The surface chemistry of carbonatite soils: Implications for REE resources., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13081, https://doi.org/10.5194/egusphere-egu23-13081, 2023.

EGU23-13899 | ECS | Posters on site | ERE4.3

Robot-aided autonomous hyperspectral mapping in mining environments 

Sandra Lorenz, Moritz Kirsch, Margret Fuchs, Sam Thiele, and Richard Gloaguen

Geological face mapping is a frequently recurring task in mining operations, the results of which have an immediate influence on the mines’ profitability, safety, and environmental impact. Hyperspectral imaging is an increasingly applied technology to improve the efficiency and accuracy of mapping tasks. The rapid and non-destructive acquisition of spectral material properties allows meaningful material information such as mineralogical surface composition to be obtained in a safe and efficient manner. The fusion product of backprojected hyperspectral data with 3D surface information (so-called “hyperclouds”) further enhances the data value by enabling easier data correction, integration, and implementation into digital archives and models. Mining environments, however, remain a challenge for operational hyperspectral mapping, particularly underground where inadequate lighting, access, and safety of operation make data collection difficult. Data processing and interpretation require expert knowledge and are typically performed semi-manually and offline. To be economically viable in such mining environments, the hypercloud technology has to mature toward autonomy and real-time delivery of results. In recent years, terrestrial autonomous platforms have entered the market that are suited to the challenging conditions of underground mining and can maneuver and navigate even in confined, uneven, and poorly lit environments. They provide optimal carriers for hyperspectral sensors, which have simultaneously evolved into lighter, faster, and more robust devices. However, implementing hyperspectral sensors as payload for terrestrial autonomous robots remains challenging, especially in terms of  technical compatibility, ensuring data quality under complex conditions,  and processing large amounts of data quickly and autonomously. In our contribution, we demonstrate the potential of autonomous terrestrial robots combined with hyperspectral technology and advanced data processing for the automation of geological mapping. We present results of hyperspectral data acquisition using an autonomous robotic platform in a confined underground mining environment and discuss strategies for adapted sensor design, autonomous validation, real-time hypercloud processing, and enhanced autonomous navigation supported by hyperspectral information. 

How to cite: Lorenz, S., Kirsch, M., Fuchs, M., Thiele, S., and Gloaguen, R.: Robot-aided autonomous hyperspectral mapping in mining environments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13899, https://doi.org/10.5194/egusphere-egu23-13899, 2023.

EGU23-15053 | Orals | ERE4.3

TIMREX – a European joint master programme to implement innovative mineral exploration achievements in geoscience education 

Ferenc Madai, Sibila Borojević Šoštarić, Gabriela Paszkowska, and Nils Jansson

Mineral resource exploration techniques and methodologies have undergone a very strong development in the last decade: e.g. portable and higher sensitive equipment, robotized exploration equipment, and tools for processing and interpreting of large, multidimensional datasets. In order to meeti the raw materials policy goals of the EU, these technologies should also be incorporated in higher education (Mádai, 2022).

 

TIMREX is a new EIT-Labelled joint master's program to train geoscience students focusing on innovative raw materials prospecting and exploration methods. The consortium consists of four academic partners – University of Miskolc, Hungary, University of Zagreb, Croatia, Wroclaw University of Science and Technology, Poland and Luleå University of Technology, Sweden. All four academic partners run their mineral exploration-focussed, geoscience engineering-type master programmes which comprise the ground for the joint master programme. Participating Universities are located within Fennoscandian, Fore-Sudetic and Tethyan/Carpathian-Balkan metallogenic belts hosting numerous primary, secondary and critical mineral resources essential for green transition of Europe. Scandinavian and West Balkan countries holds first and second place according to total mineral resources investments in Europe (data from 2019).

 

The TIMREX consortium incorporates eight non-academic partners who are at the frontier of mineral resource prospecting and exploration equipment and methodology development in the EU. They represent leading European mining companies such as Boliden Mineral and KGHM, but also SMEs and start-ups such as the Unexmin Georobotics (UGR) and the Geogold Kárpátia Ltd., as well as research institutes such as the Portuguese INESC TEC and the Slovenian Geological Survey (GeoZS).

Non-academic partners are actively involved in the TIMREX joint programme as trainers in field programs, internship mentors or thesis topic providers. Students of the programme can join research and development work at the partners. Examples are development of underwater robotized exploration methodologies (INESC TEC, UGR), drone-based multispectral surveys and complex dataset evaluation (Boliden, KGHM Cuprum, GeoZS, Geogold). The European Federation of Geologists provides a wider network of European prospectors and explorers to the joint programme and contributes to teaching of entrepreneurial skills. Therefore, TIMREX directly address major gaps of the Raw Materials sector: limited availability of qualified technical, scientific and managerial personnel involved in the whole mineral cycle (Borojević Šoštarić et al., 2022) as well as lack of generic skills crucial for increasing the innovation capacity of universities and their graduates (Grgasović and Borojević Šoštarić, 2021).

 

 

Borojević Šoštarić, S., Giannakopoulou, S., Adam, K. i Mileusnić, M. (2022). The future of mining in the Adria region: current status, SWOT and Gap analysis of the mineral sector. Geologia Croatica, 75 (Special issue), 317-334. https://doi.org/10.4154/gc.2022.26

Grgasović, P.; Šoštarić, S.B. (2021) Systematic Development of Generic Skills to Enhance Innovation Capacity of Eastern and Southeastern European Universities. Mater. Proc.

5, 99, 1-7. https://doi.org/10.3390/ materproc2021005099

Mádai F. (2022) Competence requirements of innovation and entrepreneurship oriented training programmes for the mineral exploration sector. In: Veresné Somosi M.; Lipták K.; Harangozó  Zs.(eds) "Mérleg és Kihívások - Fenntarthatóság" Miskolci Egyetem Gazdaságtudományi Kar (2022) pp. 537-547

How to cite: Madai, F., Borojević Šoštarić, S., Paszkowska, G., and Jansson, N.: TIMREX – a European joint master programme to implement innovative mineral exploration achievements in geoscience education, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15053, https://doi.org/10.5194/egusphere-egu23-15053, 2023.

EGU23-15445 | ECS | Posters virtual | ERE4.3

Re-evaluating Caledonian magmatism and associated base metal mineralisation: a case study of the Black Stockarton Moor porphyry copper system 

Chloe Gemmell, David Currie, Iain Neill, Josh Einsle, and Careen MacRae

Following the British Geological Survey’s (BGS) 1970s – 1990s Mineral Reconnaissance Programme (MRP), there has been limited characterisation and quantification of base and precious metal mineralisation in the UK, with the notable exception of Au. Data gaps still exist regarding mineral paragenesis, geochronology, deportment of critical raw materials (CRM), and ore forming processes. With increased focus on CRM, NetZero, and supply risk we must improve our knowledge of deportment in base metal systems. The BGS Critical Minerals Intelligence Centre (CMIC) was recently established to aid the UK in meeting projected future CRM demand and will act as a nexus for industry and academia. Here, we establish a workflow and document a case study where academia and the CMIC have partnered to re-evaluate a potential mineral resource, a starting point for renewed studies elsewhere in the UK. 

The Black Stockarton Moor (BSM) post-subduction porphyry Cu system is thought to have formed by interaction of Devonian plutonic to sub-volcanic complexes with Silurian turbidites in the Southern Uplands of Scotland. No study of the BSM has been undertaken since the 1979 MRP report, thus whether it is of any modern value remains unproven. Field sampling and utilising the National Geological Repository at BGS will allow for optical and scanning electron microscopy (SEM) to quantitatively establish paragenesis and primary mineralogy. Sites will then be identified for chemical mapping to quantify CRM deportment in base metals using SEM-energy dispersive X-ray analysis (EDX), with areas of particular interest further quantified by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Focused ion beam (FIB) nano-tomography will be used to identify the cm to nano-scale distribution of CRM. Finally, magmatism and mineralisation will be fully temporally constrained using U-Pb analysis of zircon, titanite, calcite and epidote and/or Re-Os analysis of sulphides as appropriate. On a large scale, this study will address one set of data gaps by re-invigorating our knowledge of the geology and geodynamic associations of mineralisation. However, by also identifying the quantities and associations of metals at the cm to micron scale, it addresses another, by constraining the extent and nature of processes responsible for the distribution of metals in such deposits. This workflow is to be refined for application to mineralisation elsewhere in the UK including work underway on the Strontian Caledonian granite and associated Pb-Zn mineralisation in the Northern Scottish Highlands.

How to cite: Gemmell, C., Currie, D., Neill, I., Einsle, J., and MacRae, C.: Re-evaluating Caledonian magmatism and associated base metal mineralisation: a case study of the Black Stockarton Moor porphyry copper system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15445, https://doi.org/10.5194/egusphere-egu23-15445, 2023.

EGU23-16567 | ECS | Posters on site | ERE4.3

Deep Electrical Resistivity Tomography as a mineral exploration tool: the Calamita distal Fe-skarn, Elba Island (Italy) 

Damian Braize, Julien Sfalcin, Matteo Lupi, Kalin Kouzmanov, Andrea Dini, and Gianfranco Morelli

To face the growing demand for raw materials, the discovery of new mineral deposits is essential for the future. Geophysical methods, and in particular electrical and electromagnetic tools, have an important role in mineral exploration. Recently, new technological developments made possible targetting deeper ore bodies and large areas with logistical challenges. We use the Deep Electrical Resistivity Tomography (DERT) method to investigate its application in mineral exploration. In particular, we use the Fullwaver technology developed by IRIS Instruments to study the full 3D resistive structure of the Calamita distal Fe-skarn deposit, Elba Island, Italy. This innovative hardware allows a full 3D deployment of autonomous and cable-less receivers and contrasts with traditional resistivity methods by its easy set-up and applicability in difficult contexts.

In November 2022, a 3D DERT survey has been carried out to investigate the Calamita deposit, consisting of massive magnetite-hematite ore bodies hosted in marbles overlaying micaschists of Tuscan Units. Skarn mineralogy/geochemistry and fluid inclusion characteristics suggest a magmatic source for the mineralizing fluids. 148 current injections have been performed on 48 receivers over an area of 2km² with the aim to reach exploration depths ranging from 600 m to 700 m. Geophysical data were combined with a high-resolution 3D Digital Elevation Model acquired by standard and thermal drone imagery.

The 3D inverted resistivity and induced polarization models match with the surface geology and shallow exploration drill hole data and highlight the architecture of Calamita deposit. Strong resistivity contrasts reveal the presence of sub-vertical conductive and chargeable pipes connecting the different skarn bodies at depth, interpreted to represent the paleo-hydrothermal upflow zones. The pipes point towards the inferred cupola of a magmatic intrusion that potentially triggered the formation of the ore deposit. High chargeability anomalies suggest the presence of hidden massive ore bodies and disseminated mineralisation on the flanks of the system.

DERT has the potential to investigate and explore mineral deposits in full 3D, with high sensitivity, and in logistically complex settings.

How to cite: Braize, D., Sfalcin, J., Lupi, M., Kouzmanov, K., Dini, A., and Morelli, G.: Deep Electrical Resistivity Tomography as a mineral exploration tool: the Calamita distal Fe-skarn, Elba Island (Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16567, https://doi.org/10.5194/egusphere-egu23-16567, 2023.

EGU23-17258 | Orals | ERE4.3

Dig_IT – A human-centred Internet of Things platform for the sustainable digital mine of the future 

Diego Grimani, Lorenzo Bortoloni, Damiano Vallocchia, Maria Garcia Camprubi, and David de Paz

Dig_IT project aims to develop a human-centred IIoT platform connecting the mining ecosystem of assets, environment, and humans to increase mining efficiency: saving costs using optimised scheduling, increasing uptime using predictive operation and maintenance, identifying new revenue opportunities using advanced geological interpretation on exploration mining phase. To address industry needs of minimising accidents, optimising production processes and reducing costs, intelligent systems will provide real-time insights for the enterprise at all operational levels.

Dig_IT follows a market need & technology offer approach aiming at covering all aspects of technical, industrial and business requirements towards a sustainable future in mining. The project’s value chain and concept has been built with the utmost objective to provide new solutions addressing the needs for safety, efficiency and sustainability, bringing innovative and competitive solutions to the mining business, face future challenges regarding standards and legislation, and spread the knowledge to as many sectors of the European extractive industry as possible.

The project aims to achieve several objectives: design and validate a smart Industrial Internet of Things platform to improving efficiency and sustainability of mining operations, achieving on-line measurements of asset-bound mining operations and online distributed measurements for broad area sustainability and occupational work environment, and Big Data optimisation through improving data quality. Furthermore, the project aims to develop Digital Twins of the physical mine entities, systems and processes, a Smart Garment and an Intelligent Toolbox for mining personnel sensing OHSE parameters, a Decision Support System and a Predictive Operation System.

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How to cite: Grimani, D., Bortoloni, L., Vallocchia, D., Garcia Camprubi, M., and de Paz, D.: Dig_IT – A human-centred Internet of Things platform for the sustainable digital mine of the future, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17258, https://doi.org/10.5194/egusphere-egu23-17258, 2023.

EGU23-17279 | Orals | ERE4.3

Underwater measurements with UX robots; a new and available tool developed by UNEXUP 

Norbert Zajzon, Boglárka Anna Topa, Richárd Zolzán Papp, Jussi Aaltonen, José Almeida, Balazs Bodo, Stephen Henley, Marcio Pinto, and Gorazd Zibret

The UX-2 robot of the UNEXMIN technology represents the newest generation of underwater explorers capable of operating in flooded mines and other closed underwater environments meanwhile providing geoscientific information. The technology was developed by an international team of scientists during the UNEXMIN (https://www.unexmin.eu/) Horizon 2020 project (2016–2019) and the UNEXUP (https://unexup.eu/) EIT RawMaterials project (2020–2022). The concept was proven in various environments and the first generation of robots was built in the UNEXMIN project. Besides technological upgrades, the UNEXUP project was focusing also on marketing and commercialization thru UNEXMIN Georobotics Ltd. (https://unexmin-georobotics.com/), the spin-off of the consortium.

The technology proved its capabilities at numerous flooded sites in various harsh environments during the last years including, abandoned mines, caves, historical sites and even drinking water facilities.

Although very bad visibility was observed in the South Crofty mine, Camborne (UK), the robot could manoeuvre down to -300 m and investigate a narrow shaft relying mainly on sonar-based navigation.

The Csór water well, the main drinking source of Székesfehérvár (Hungary) was another location where the UX technology proved its usefulness and 3D-mapped the well with centimetre accuracy for reconstruction purposes.

In August of 2022, the UX robot created a 3D topography map and continuous water parameter measurements further exploring the flooded karstic cave Hranice Abyss (Czech Republic) down to -450 m – setting up the current word depth record.

Even remote-control and full autonomy were demonstrated in Kőbánya-mine, Budapest, Hungary. During the remote-control test, the Budapest team launched the robot, but the underwater robot operation was done from INESCTEC, Portugal.

Ecton copper mine (UK) used to be the deepest mine of its age in the 18th century, closed and partially flooded for more than 160 years. Now it is a listed National Monument in the UK and is under strict protection within a site of special scientific interest. Here the UX robots proved their value in discovering new workings, connections, and technological solutions helping the archaeologists which could not be recovered by other methods as well as elucidating the geological structure.

The salt mine of Solotvyno, Ukraine was a demanding challenge as the UX robot had to be capable of operating and measuring in freshwater as well as in fully saturated (ca. 330g/l) brine with 1.25 g/cm3 density, which was located below a freshwater layer.

The abandoned fluorspar mine of Würmtal, Pforzheim, Germany was the last site visited within the frame of the UNEXUP project where the UX robot revealed its unique capabilities by exploring a large part of the flooded workings. More than 3 km was covered laterally in a single dive down to the fluorspar vein, and colour- and UV-images of the ore were delivered successfully. UX robot also brought back data, helping to assess the stability of the walls.

The UNEXMIN project was funded by the European Union thru the Horizon 2020 research and innovation programme under the no. 690008 grant agreement.

The UNEXUP project was funded partially by the European Union thru EIT RawMaterials no. 19160.

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How to cite: Zajzon, N., Topa, B. A., Papp, R. Z., Aaltonen, J., Almeida, J., Bodo, B., Henley, S., Pinto, M., and Zibret, G.: Underwater measurements with UX robots; a new and available tool developed by UNEXUP, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17279, https://doi.org/10.5194/egusphere-egu23-17279, 2023.

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