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

EGU24-8419 | ECS | Orals | MAL20-GI | GI Division Outstanding Early Career Scientist Award Lecture

Towards Sustainable Futures in Tree Assessment using Ground Penetrating Radar: Insights, Developments and Novel Perspectives 

Livia Lantini and Fabio Tosti

The global impact of diseases and environmental pressures on trees and forests has resulted in the decay and loss of a significant portion of the Earth’s natural heritage. Responding to this challenge, Ground Penetrating Radar (GPR), a well-established and reliable non-destructive testing (NDT) method, emerges as a fundamental assessment technique with vast potential. Its efficacy spans various domains, from Earth sciences to engineering, making GPR uniquely suited for forestry applications and offering a sustainable and non-invasive alternative to destructive methods like coring.

Within forestry applications, GPR assumes a critical role in optimising economic expenditure for tree maintenance while simultaneously enhancing public safety. Swift and reliable detection of subsurface anomalies make GPR essential in safeguarding natural heritage and facilitating early identification of tree decay, ultimately supporting effective tree disease control.

The present work explores the extension of GPR's capabilities to evaluate critical parameters in tree health, focusing on the assessment of root systems and the identification of potential structural weaknesses within tree trunks.

The study introduces a series of recent experimental-based and theoretical models, each contributing to the understanding and enhancement of tree assessment. These models refine the interpretation of intricate reflection patterns, providing a refined understanding of tree trunk conditions. Additionally, models for the early detection of decays and cavities in tree trunks are presented, offering valuable insights into the internal structure of trees and enhancing the sensitivity and precision of GPR for proactive tree health management.

In terms of assessing and monitoring tree roots, the study introduces methodologies designed to enhance the understanding of below-ground ecosystems. Developed algorithms for root detection and tracking, along with methodologies for estimating root mass density, offer insights into growth patterns and contribute to sustainable tree management practices. Furthermore, recent methodologies focus on understanding interconnections within tree root systems and the surrounding environment, identifying buried structures within the root system, addressing unique challenges faced by street trees in urban environments, refining the analysis of tree root systems using frequency spectrum-based processing, and integrating artificial intelligence for automatic recognition to enhance the efficiency of root system assessment.

Finally, unique case studies are presented, showcasing the methodology, survey planning, and site procedures. These case studies add depth to the exploration, reflecting the practical application of the research in diverse and challenging scenarios.

How to cite: Lantini, L. and Tosti, F.: Towards Sustainable Futures in Tree Assessment using Ground Penetrating Radar: Insights, Developments and Novel Perspectives, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8419, https://doi.org/10.5194/egusphere-egu24-8419, 2024.

EGU24-14781 | Orals | MAL20-GI | Christiaan Huygens Medal Lecture

The silent degassing of volcanoes: a useful tool for volcanic surveillance and a significant contributor to the global CO2 emission from subaerial volcanism  

Nemesio M. Pérez and the INVOLCAN/ITER Research Team

Volcanoes emit significant amounts of gases into the atmosphere through visible and non-visual degassing manifestations regardless of whether volcanoes are active or quiescent. The latter, also known as diffuse or silent degassing, occurs across the entire volcanic building. Water vapour (H2O), carbon dioxide (CO2), and sulfur (S) are the three most abundant magmatic volatiles, with CO2 being the least soluble in silicate melts. Diffuse volcanic degassing alters the chemical composition of volcanes' ground/soil gas atmosphere, resulting in enrichment of CO2, He, and other gas species. Over the last 25 years, extensive research on diffuse CO2 degassing has been conducted at volcanic and geothermal systems, indicating that silent CO2 degassing is an important mechanism for dissipating energy at volcanoes and contributes significantly to global CO2 emissions from subaerial volcanism. As a result, diffuse CO2 degassing studies have been regarded as a powerful tool in geochemical monitoring programs for volcanic surveillance, particularly in volcanic areas lacking visible gas manifestations (plume, fumaroles, hot springs, etc.), a valuable tool for identifying productive geothermal reservoirs, and a potential source of large amounts of CO2 to the atmosphere via gobal subaerial volcanism.

Diffuse degassing investigations on volcanoes involve primarily in-situ ground CO2 efflux measurements and the collecting of gases at a certain depth for later chemical and isotopic analysis. CO2 and He are the two most interesting gas species to investigate in diffuse degassing studies due to their similar low solubility in silicate melts at low pressures and suitability as geochemical tracers of magmatic activity. However, once exsolved from the silicate melts, their journey through the crust to the surface is considerably different. While CO2, as a reactive gas, is influenced by interfering processes (gas scrubbing by groundwaters and interaction with rocks, decarbonatation processes, biogenic production, and so on), He is chemically inert, radioactively stable, non-biogenic, highly mobile, and relatively insoluble in water. These properties minimize the interaction of this noble gas with the surrounding rocks or fluids during its ascent towards the surface. Their geochemical differences yield higher relative He/CO2 ratio in the fumarole gases than is actually present in the magma, but it decreases when the magma reservoir reaches enough pressure to generate incipient fracture systems approaching the eruption, thus releasing considerably more of the magma volatiles.

Quantifying global volcanic CO2 emissions from subaerial volcanism is critical for gaining a better knowledge of the rates and mechanisms of carbon cycling, as well as their effects on the long-term development of Earth's climate across geological timescales. Recent studies show that diffuse degassing contributes 47 to 174 Tg·y-1 to the atmosphere, although our understanding of the global diffuse CO2 degassing from subaerial volcanism could be larger.

Several examples of diffuse degassing research on many different volcanic systems around the world performed by our research team and collaborators during the last 25 years will be presented during my award/medal lecture, strongly supporting that diffuse degassing is a useful tool for volcanic surveillance and a significant contributor to the global CO2 emissions from subaerial volcanism.

How to cite: Pérez, N. M. and the INVOLCAN/ITER Research Team: The silent degassing of volcanoes: a useful tool for volcanic surveillance and a significant contributor to the global CO2 emission from subaerial volcanism , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14781, https://doi.org/10.5194/egusphere-egu24-14781, 2024.

GI1 – General sessions on geoscience instrumentation

EGU24-201 | ECS | Orals | GI1.1

Automated Static Magnetic Cleanliness Screening for the TRACERS Small-Satellite Mission 

Cole J Dorman, Chris Piker, and David M Miles

The Tandem Reconnection and Cusp Electrodynamics Reconnaissance Satellites (TRACERS) Small Explorers mission requires high-fidelity magnetic field measurements for its magnetic reconnection science objectives and for its technology demonstration payload MAGnetometers for Innovation and Capability (MAGIC). TRACERS needs to minimize the local magnetic noise through a magnetic cleanliness program such that the stray fields from the spacecraft and its instruments do not distort the local geophysical magnetic field of interest. Here we present an automated magnetic screening apparatus and procedure to enable technicians to routinely and efficiently measure the magnetic dipole moments of potential flight parts to determine whether they are suitable for spaceflight. This procedure is simple, replicable, and accurate down to a dipole moment of 1.59 × 10-3 N m T-1. It will be used to screen parts for the MAGIC instrument and other subsystems of the TRACERS satellite mission to help ensure magnetically clean measurements on-orbit.

How to cite: Dorman, C. J., Piker, C., and Miles, D. M.: Automated Static Magnetic Cleanliness Screening for the TRACERS Small-Satellite Mission, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-201, https://doi.org/10.5194/egusphere-egu24-201, 2024.

EGU24-246 | ECS | Orals | GI1.1

Fiber-optic gyroscopes with enhanced temperature adaptability for geophysical rotational sensing 

Yanjun Chen, Lanxin Zhu, Wenbo Wang, Huimin Huang, Xinyu Cao, and Zhengbin Li

Fiber-optic gyroscopes, as rotational motion sensors, have emerged as powerful candidates for rotational seismology and Earth rotation observation due to their portability and high sensitivity. However, the stability of fiber-optic gyroscopes is degraded by environmental temperature variation that optical fibers are sensitive to. For the suppression of effects of temperature variation, conventional methods include the device level and post-processing level. However, the former has additional device requirements and higher costs, while the latter has a degradation of compensation for a more general environment. In this abstract, we propose a suppression method at the device level. We find that the effect of thermally induced phase fluctuations is significantly lower in the high-frequency band compared to the low-frequency band. Therefore, by upconverting the operating point of the fiber-optic gyroscope at a high-order harmonic of eigenfrequency, the effect of thermally induced phase fluctuations on the output is greatly suppressed. This method is easy to operate without requiring any additional optical or electrical components. To validate this method, we have conducted a time-varying temperature variation experiment using a portable fiber-optic gyroscope equipped with a 20 km long and 0.3 m diameter fiber-optic coil. The implementation of this upconverted frequency modulation technology resulted in a 32-fold reduction in temperature sensitivity for the fiber-optic gyroscope. The results demonstrate that the proposed technology enhances the temperature adaptability of fiber-optic gyroscopes, which is a critical aspect in practical geophysical applications. At the same time, the self-noise is reduced from 3×10-8 rad/s/√Hz to 8×10-9 rad/s/√Hz, further improving its sensitivity to observe geophysical rotation signals. Seismic records will be presented to demonstrate its utility in rotational seismology.

How to cite: Chen, Y., Zhu, L., Wang, W., Huang, H., Cao, X., and Li, Z.: Fiber-optic gyroscopes with enhanced temperature adaptability for geophysical rotational sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-246, https://doi.org/10.5194/egusphere-egu24-246, 2024.

EGU24-1499 | Orals | GI1.1

Global sea surface air pressure observations with V-band O2 differential absorption radar 

Bing Lin, Matthew Walker Mclinden, Xia Cai, Gerald M. Heymsfield, Nikki Privé, Steven Harrah, and Lihua Li

Observed meteorological data are essential for initialization, adjustment, assimilation, and prediction of numerical weather prediction (NWP) models and influence daily activities of people and society. Many key weather variables such as temperature, humidity and winds are well observed globally by combined surface weather stations and suborbital and orbital remote sensing platforms of current Earth Observing System (EOS). However, sea surface air pressure is a significant observational gap in the current EOS. There is no operational remote sensing method available for this crucial dynamic variable of the Earth’s climate and weather systems. Over open oceans, the pressure can only be observed by in-situ sensors of very limited buoys, ships, and oceanic platforms. Studies find that accurate sea level pressure (SLP) measurements can significantly improve not only dynamics but also thermodynamics, such as temperature fields of NWP models [1]. Weather forecasts, especially severe weather predictions including hurricanes, can also be improved considerably with pressure measurements.

This study presents the SLP retrieval with emphasis on the evaluation of potential impacts of instrumental and environmental uncertainties on the retrievals for measurements of V-band O2 differential absorption radar systems operating at three spectrally even spaced close frequency bands (65.5, 67.75 and 70.0 GHz). This study finds that precise knowledge on instrument attitude in current design will result in negligible retrieval errors. The spectral control of the instrument and the knowledge on frequency changes will provide accurate information for forward radiative transfer calculations and then, SLP retrieval. Furthermore, the retrieval algorithm combining all three channels, i.e., the 3-channel approach, can effectively mitigate major atmospheric (e.g., water vapor and cloud) and sea surface influences on sea surface air pressure retrieval.

The major uncertainty for sea surface pressure retrieval is caused by the noise in radar power returns for the current design. Analysis demonstrates the potential of global SLP observation with error similar to that of marine in-situ measurements (about 1 ~ 2 mb), which is urgently needed for improvement of NWP models. Currently, NASA is developing an airborne system for demonstration of space applications.  Our presentation will provide more details on the system, SLP retrieval and their applications.

 

Reference

[1] Prive, N., M. Mclinden, B. Lin, I. Moradi, M. Sienkiewicz, G. Heymsfield, and W. McCarty, “Impacts of marine surface pressure observations from a spaceborne differential absorption radar investigated with an observing system simulation experiment”, J. Atmos. Oceanic Tech., 40, 897 – 918, 2023.

How to cite: Lin, B., Mclinden, M. W., Cai, X., Heymsfield, G. M., Privé, N., Harrah, S., and Li, L.: Global sea surface air pressure observations with V-band O2 differential absorption radar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1499, https://doi.org/10.5194/egusphere-egu24-1499, 2024.

EGU24-2442 | ECS | Orals | GI1.1

GAIN, a Machine Learning approach for Airborne, Maritime, and Submarine Gravimeter Systems 

Lorenzo Iafolla, Massimo Chiappini, and Francesco Santoli

Precision gravimeters deployed onboard aerial, groundbased, and underwater moving platforms face significant accuracy challenges due to environmental disturbances such as non-inertial reference systems and temperature variations. The “Gravimetro Aereo INtelligente” (GAIN) concept represents a step forward in tackling this problem by using a data post-processing approach. This approach avoids cumbersome, heavy, and power-intensive active compensation systems, thus increasing the instrument's adaptability to small moving platforms.

The GAIN concept is based on three pillars that define its approach. Firstly, it incorporates a multi-sensor system within the gravimeter framework, which might include a three-axial accelerometer, a three-axial gyroscope, multiple thermometers and a barometer. This set of sensors are designed to measure both the effects of gravity and of other disturbances. By utilizing this information, GAIN employs machine learning algorithms (the second pillar) to map the complex relationship between the measurements and the desired gravity value. However, machine learning heavily relies on the availability of high-quality training datasets, which are often scarce and challenging to obtain in operational environments. To address this bottleneck, the third pillar of GAIN utilizes a training platform that can simulate a wide range of environmental situations in a controlled laboratory setting. This platform enables the generation of labeled data that mimics real-world operational scenarios.

This contribution will present the details of the initial GAIN experimental setup, highlighting the successful integration of a multi-sensor system with the training platform. Additionally, early findings will be shared, demonstrating the potential of the GAIN technique in mitigating temperature changes in gravimeters. Finally, the progress of ongoing experiments will be showcased, as we work towards expanding the capabilities of the GAIN method to also address rotations and linear accelerations as sources of interference.

How to cite: Iafolla, L., Chiappini, M., and Santoli, F.: GAIN, a Machine Learning approach for Airborne, Maritime, and Submarine Gravimeter Systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2442, https://doi.org/10.5194/egusphere-egu24-2442, 2024.

EGU24-3511 | Posters on site | GI1.1

An improved suspension system for the observatory variometer 

Vira Pronenko, Andrii Marusenkov, Igor Parylo, and Andrii Prystai

The observatory variometers have been used for long-term observation of the Earth’s magnetic field for years and more. Because of this, it is necessary to exclude the influence of every external factors at the sensors of these magnetometers. One of the most often ones are tilts of their sensors because of the seasonal tilts of the pears at which they are installed. These variometers are usually equipped with sensors installed on brass or titanium platforms, pendulously suspended for tilt compensation. Here we present a new fiber-suspended sensor that better fits the observatory demands.

Usually, the tilt compensation ratio is defined as a relationship between the pendulum and base rotations in the same vertical plane (around the same horizontal axis). We found that at certain conditions a pendulum may rotate around two other axes perpendicular to the base rotation line.  The first effect appears as a pendulum rotation around the horizontal line belonging to the vertical plane in which the sensor base is tilted.  This effect can be seen not only at the inclination of the base but also at the rotation of the sensor around its vertical axis. We used such a rotation in a horizontally directed magnetic field H to match the alignment of the mechanical axes of suspension and the magnetic axes of the sensor.

The second detected effect was manifested as the pendulum rotation around the vertical axis during the inclination of the platform in the vertical plane where the upper pair of the fibers lies. The cause of the second effect is the imbalance of the lower part of the pendulum - either due to the uneven distribution of masses or due to different lengths of the lower pair cords.

To keep both effects at the lowest possible or negligible level, a new version of the fiber-suspended sensor is designed. This sensor has three supporting feet and a worm drive for fine adjustment of the magnetic components’ orientation and the magnetic axes leveling possibility included in the firmware. The following parameters were obtained: tilt range ±4°, tilt compensation ratio (including off-axis effects) >2000, and thermal factor <0.2 nT/°C.

How to cite: Pronenko, V., Marusenkov, A., Parylo, I., and Prystai, A.: An improved suspension system for the observatory variometer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3511, https://doi.org/10.5194/egusphere-egu24-3511, 2024.

EGU24-5984 | Orals | GI1.1

A portable luminescence dating instrument: a new insight for in-situ Earth applications 

Alessio Di Iorio, Vincenzo Pascucci, Roberto Filippone, Giulia Di Iorio, Daniele Sechi, Stefano Andreucci, and Ilaria Di Pietro

The age determination is crucial to unravel the evolution and to provide a framework of the geological, paleo-anthropological, and cultural conditions of a specific region of interest. The lack of chronological information makes difficult to correlate the site of interest with other temporal attributes provided by stratigraphy and paleoclimatology. Luminescence is a well-established dating technique for determining the absolute age of formation (or most recent reworking event) of geological deposits/sediments and archaeological finds on Earth, with a time range that spans from the last few decades up to one million years. The most common geological targets are dust, silt, sand, cobbles, and rock outcrops originating from different environments: aeolian, fluvial, alluvial, lacustrine, marine, glaciogenic, slope deposits, karstic, soils, tectonic activity. In the archaeological field, this technique is applied not only to the geological sediments in excavation sites but also directly to artifacts of interest, especially when they are made of pottery or stone.

A miniaturized luminescence dating prototype for in-situ examination has been designed by Alma Sistemi S.r.l., Guidonia, Italy, and validated by University of Sassari, Sassari, Italy, under European Union H2020-MSCA-RISE-2018 research programme (G.A. n.823934). The instrument is equipped with an infrared and blue optical stimulation subsystem to perform both optically and infrared-stimulated luminescence (OSL, IRSL) and is able to measure both paleo-dose and dose rate. An X-ray generator (XRG) irradiates the sample, while the response luminescence signal is obtained through a photon counting photomultiplier tube (PMT). A thermal subsystem consisting of a heater and air-cooling pumps allows the instrument to heat during SAR (single-aliquot regenerative-dose) procedure and to perform thermally stimulated luminescence. Remote control for data analysis application and a battery power supply are implemented on the instrument for usage on the field.

The development of this portable instrument is of great relevance since it finds practical use in geological and archaeological Earth's field applications. In fact, compared to current luminescence dating technologies and considering its reduced dimensions (11x11x18 cm excluding electronic box and cover) and weight (currently <5 kg), the presence of the air-cooling system Vs Nitrogen and the use of X-ray vs radiative source, qualify the instrument for direct use in the field. It is also provided with an advanced and user-friendly software tool, thus strongly reducing the need of a skilled operator. The prototype instrument has been validated using different samples and results compared with equivalent laboratory instrument (Risø TL/OSL Reader model TL/OSL-DA-20) at University of Sassari Luminescence laboratory.

At this stage, the instrument can perform a basic SAR protocol and accurately measure the response luminescence signal after different irradiations time and thus, measure the natural dose of the natural sediment sample. Here, the most recent results are presented.

How to cite: Di Iorio, A., Pascucci, V., Filippone, R., Di Iorio, G., Sechi, D., Andreucci, S., and Di Pietro, I.: A portable luminescence dating instrument: a new insight for in-situ Earth applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5984, https://doi.org/10.5194/egusphere-egu24-5984, 2024.

EGU24-7394 | Orals | GI1.1

Automated mineralogy as a key technology toward zero-waste mining – The EXCEED project 

Sonja Lavikko, Quentin Dehaine, Fernando Prado Araujo, and Philippe Muchez

The increasing demand for critical raw materials (CRMs) linked to the energy transition, Europe’s reliance on a few third countries (incl. China) for the supply of these combined with increased ESG issues calls for a new mining paradigm: i.e., responsible, zero-waste, multi-metal/mineral mining. Li-hard rock deposits (pegmatites and rare-metal granites) are perfect candidates for such an approach, where, besides lithium, numerous by-products including industrial minerals (quartz, feldspar, micas) and CRMs (Nb, Ta, and so forth) could be potentially extracted. To assess whether these by-products can be recovered during Li production requires a mineral-centric, integrated geometallurgical approach. Automated mineralogy is a key technology for such an approach. Determining how to utilize the secondary material streams and recovery of the by-products relies on the knowledge of the material, its chemical composition, particle size, crystal structure and texture to grain size, liberation grade and mineral associations. In this study, four European lithium mine projects, two pegmatite projects (Keliber, Finland and Savannah, Portugal) as well as two rare-metal granite (RMG) projects (Beauvoir, France and St Austell, UK), are investigated. Different ore types as well as process samples (concentrates, residues, and tailings) were investigated to assess the by-product potentials of industrial minerals, CRM’s as well as the status and behavior of potentially harmful elements (PHEs) throughout the processing flowsheet. Gathering of all this information is started by the Extended BSE Liberation Analysis (XBSE_STD) and Grain-Based X-ray Mapping (GXMAP) measurements with the FEI Quanta 650F, an automated Scanning Electron Microscope equipped with a field emission gun electron source, two Energy Dispersive X-ray spectrometers (EDX) (Bruker X-Flash 6130), and FEI’s Mineral Liberation Analyzer (MLA) quantitative mineralogy software v. 3.1.4. Additional data is collected with Micro-XRF Bruker M4 Tornado plus with AMICS. Details are further studied with additional methods, such as X-ray powder diffraction, Inductively Coupled Plasma Optical Emission spectroscopy, Electron Probe Micro-Analyses, Laser ablation ICP-MS, and X-ray Fluorescence measurements.  

To define how the ore properties and the PHE/CRM deportment affect the options for usability, a comprehensive geometallurgical assessment will be conducted starting from collecting the basic mineralogical data to creating process flowsheet options and predicting theoretical process performance. These results are then to be tested at the lab and pilot scale according to the produced process protocols to be validated.  

How to cite: Lavikko, S., Dehaine, Q., Prado Araujo, F., and Muchez, P.: Automated mineralogy as a key technology toward zero-waste mining – The EXCEED project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7394, https://doi.org/10.5194/egusphere-egu24-7394, 2024.

EGU24-8193 | ECS | Orals | GI1.1 | Highlight

Three-dimensional reconstruction of high-resolution images of existing tunnels for geo-structural monitoring and inspection purposes. 

Saduni Melissa Dahanayaka, Adrián José Riquelme Guill, Alessia Vecchietti, and Matteo Del Soldato

Geotechnical and structural monitoring and inspection of existing linear infrastructures, with particular focus on tunnels, have gained a great prominence in recent years. In Italy, a new regulation for inspection, monitoring and maintenance of tunnels has been issued and a massive inspection plan is carried out to guarantee a constant maintenance and safe condition of existing tunnels. The relevance of geo-structural monitoring lies in the possibility of controlling the interaction between soil and structure and in prevention of damaging infrastructure systems because of deterioration. Monitoring also helps the prevention of natural disaster effects, according to the rising attention paid to hydrogeological risk in the country in the last decades. The Italian territory is vulnerable to earthquakes, floods, and landslides, which are the major hazards that can involve human settlements, constructions, and big infrastructures such as tunnels. An opportunity arose for the possibility of working on huge amounts of data and develop accurate methods of elaboration and visualisation of the most significant information for inspection and maintenance planning purposes. For this work, innovative methods and mobile survey technologies were used to get linear images and 3D point cloud data of some highway tunnels in central Italy, which are characterised by relevant structural deteriorations and cracks. High-resolution black and white images of tunnel linings were captured through a mobile system composed by line cameras, lamps for a correct illumination of the tunnel surface and positioning system. To represent the whole tunnel surface, 4 runs were performed: right and left wall and right and left ceiling. High-density point clouds of the tunnel were acquired by a mobile laser scanner mounted on a vehicle. The combination of 2D high-resolution images and 3D data can have a significant impact on the data visualisation and presentation in order to have a comprehensive representation of the actual state-of-the-art of the infrastructure. The 3D representation of the tunnel from 2D linear images is accomplished through the reconstruction of a 3D geometrical model of the tunnel section through a tool for the automatic elaboration and management of images. This automatic calculation algorithm provides the three-dimensional reconstruction of the infrastructure through 2D high-resolution images, in order to have the best representation and visualization of the elements inside the tunnel. The major advantage of the tool is the possibility of identifying and evaluating structural defects and cracks in the tunnel surface directly on the 3D model and of better understanding the effects on the infrastructure caused by deformation events in the geological context. It can also provide the comparison of subsequent surveys for monitoring. This work represents an innovative means affecting fundamental aspects of existing tunnels management and monitoring, e.g., the investigation of deformation phenomena, temporal evolution of deteriorations and cracks, causes identification/prevention, soil-structure interaction studies, geological hazard risk reduction.

How to cite: Dahanayaka, S. M., Riquelme Guill, A. J., Vecchietti, A., and Del Soldato, M.: Three-dimensional reconstruction of high-resolution images of existing tunnels for geo-structural monitoring and inspection purposes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8193, https://doi.org/10.5194/egusphere-egu24-8193, 2024.

EGU24-8243 | Orals | GI1.1

A New Approach to Infrasound Sensor Design 

Cansun Guralp, Paul Minchinton, Horst Rademacher, and Murray McGowan

Current infrasound sensor designs have shortcomings inherent in their open-loop arrangement. Among them are the limited dynamic range, the lack of linearity of the response function over the desired frequency range and – may be most importantly – the fact that such sensors can only be calibrated in the laboratory and not under real conditions in the field.

Here we present a novel infrasound sensor design, which overcomes these and other shortcomings. At the core of our new sensor lies a feedback loop. It is based on a proven technology already applied in many sensor and control systems, particularly relevant for Earth science in the design and manufacturing of high fidelity broadband seismic sensors.

The new infrasound sensor uses a precision bellow, which deflects in response to pressure variations or atmospheric infrasound waves. The movement of the bellow in single degree of deflection is measured with a differential capacitive displacement transducer. Its circuitry is a Blumlein bridge arrangement operating at a frequency of 45 KHz and a driver signal amplitude of 20 V. The transducer's output signal is then synchronously fed back to the regular linearised magnetic force transducer after passing through a Proportional Integral and Differential (PID) controller.

This design increases the bandwidth of the sensor to five decades, from 2.7 mHz to more than 200 Hz. At the same time the response of the sensor is essentially flat over the entire frequency range with only minor variations of less than +/- 0.1 dB. We measured the dynamic range of the sensor to be in excess of 155 dB, a significant increase compared to current open loop systems.

The infrasound sensors theoretical transfer function is compared to practical measurements providing sensors characteristics including its detection levels over the complete frequency response.

The system calibration is carried out analogously to the calibration of broadband seismic sensors. We inject a known calibration signal (either sinusoidal, square wave or broadband noise) directly into the feedback force transducer. This setup allows the calibration of the infrasound sensor in the laboratory as well as after deployment in a field station.

How to cite: Guralp, C., Minchinton, P., Rademacher, H., and McGowan, M.: A New Approach to Infrasound Sensor Design, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8243, https://doi.org/10.5194/egusphere-egu24-8243, 2024.

Since few years, a lot of companies and industries are developing battery recycling processes for the recovery of critical elements such as Li, Ni and Co. Before hydrometallurgical processing, mechanical and/or thermal treatment are applied in order to produce a black powder, also called blackmass. This high-value powder contains these above mentioned critical elements as well as graphite, rare earth metals and impurities such as solvents, plastics, aluminium and copper. The only data currently used to determine the quality of blackmass are chemical analyses of the major elements. However, micro-textures, liberation of elements and phases, as well as the amount of impurities in various phases are important parameters for the efficiency and performance of a hydrometallurgical process.

In order to evaluate the suitability for hydrometallurgical recycling process, it is essential to analyse the blackmass not only chemically but also with respect to size, shape and composition of particles. This presentation shows how these data can be acquired by using a refined QEMSCAN database. This database was created based on billions of point analyses on a total of some million particles. The results show that:

  • Particles can be micro-texturally characterized and classified with respect to chemical element contents.
  • Important textural and chemical particle variations exist in the blackmass of different origins showing different qualities.
  • Elements deleterious to hydrometallurgical processing (i.g. Si, Mg, K, Ca, Fe, Al, Cu and others) can be present in specific and well liberated particles.
  • Cathode active material compositions (different types of NMC as well as LCO, NCA, LFP, NiMH, etc) that are specific for each battery type can be distinguished.
  • Digital simulation of additional physical mineral processing can optimize blackmass quality with respect to valuable elements.
  • Special attention must be given to potential health risks during recycling and the processing of blackmass as elements like Cd and Co can be present in ultrafine particles.

How to cite: Dadé, M.: The automated mineralogy: an important tool for geometallurgy studies of battery recycling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9867, https://doi.org/10.5194/egusphere-egu24-9867, 2024.

EGU24-10303 | Posters on site | GI1.1 | Highlight

Airborne Synthetic Aperture Radar and Electromagnetic Technologies of the Italian earth observation platform ITINERIS 

Ilaria Catapano, Andrea Barone, Paolo Berardino, Romeo Bernini, Carmen Esposito, Francesco Mercogliano, Antonio Natale, Stefano Perna, Jorge Andres Rosero Legarda, Pietro Tizzani, Riccardo Lanari, and Francesco Soldovieri

ITINERIS - Italian Integrated Environmental Research Infrastructures System is the Italian hub of research infrastructures in the environmental scientific domain, whose creation is financed by the national recovery and resilience plan (PNRR).

Among the large number of technological solutions made available by the infrastructure, thanks to its skills in the fields of remote sensing and electromagnetic monitoring of the environment, the Institute for Electromagnetic Sensing of the Environment of the National Research Council (CNR-IREA) has in charge the development and optimization of technologies for the Soil-Subsoil System (SSS) observation.

Specifically, CNR – IREA is carrying out activities concerning two technological assets. The first one is made up of airborne Synthetic Aperture Radar (SAR) systems and computing resources suitable to manage large amounts of data and generate SAR derived products. The second one involves mobile (also by exploiting drones) and fixed in-situ sensors, consisting of magnetometers, gradiometer, multi-antenna ground penetrating radar and optical backscatter reflectometer, which are suitable for high resolution imaging and monitoring of the shallower layers of the subsoil, including the groundwater. These activities also involve the design of innovative data processing procedures, aimed at increasing the effectiveness of each one of the observation technologies, as well as the definition of measurement protocols and strategies devoted to the integration of airborne and in-situ sensors, with the final goal to perform a multi-scale and multi-resolution non-invasive monitoring of the dynamic processes affecting the SSS.

A detailed summary of the performed and planned activities will be presented at the conference together with the technical specifics of the purchased instrumentations.

 

Acknowledgement: The communication has been funded by EU - Next Generation EU Mission 4 “Education and Research” - Component 2: “From research to business” - Investment 3.1: “Fund for the realisation of an integrated system of research and innovation infrastructures” - Project IR0000032 – ITINERIS - Italian Integrated Environmental Research Infrastructures System - CUP B53C22002150006.

The authors acknowledge the Research Infrastructures participating in the ITINERIS project with their Italian nodes: ACTRIS, ANAEE, ATLaS, CeTRA, DANUBIUS, DISSCO, e-LTER, ECORD, EMPHASIS, EMSO, EUFAR ,Euro-Argo, EuroFleets, Geoscience, IBISBA, ICOS, JERICO, LIFEWATCH, LNS, N/R Laura Bassi, SIOS, SMINO.

How to cite: Catapano, I., Barone, A., Berardino, P., Bernini, R., Esposito, C., Mercogliano, F., Natale, A., Perna, S., Rosero Legarda, J. A., Tizzani, P., Lanari, R., and Soldovieri, F.: Airborne Synthetic Aperture Radar and Electromagnetic Technologies of the Italian earth observation platform ITINERIS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10303, https://doi.org/10.5194/egusphere-egu24-10303, 2024.

EGU24-10868 | Posters on site | GI1.1

A comparison of next generation mid-band broadband seismometers and traditional sensor technologies 

Connor Foster, Ella Price, Neil Watkiss, Aaron Clarke, Phil Hill, James Lindsey, and Federica Restelli

Mid-band seismometer systems usually have shorter period responses and higher noise floors when compared to broadband seismometer sensors. These seismometers have been hugely popular with permanent seismic networks and temporary experiments alike due to their cost-effectiveness, portability and relative ease of deployments which allow for network densification and quick deployments. Güralp have historically led the way with such sensors with the 6T and 40T series which have been used globally in challenging environments over the last decades for local and regional seismic monitoring applications. GSL have built on this tried and trusted platform to develop the next generation of mid-band sensor technology.

The Güralp next-generation smart sensor module is designed to be able to operate at any angle, without the use of a mechanical gimbal system. This allows for the entire sensor package to be rotated during installation and deployment without sacrificing data quality and means that all three components of the sensor to be manufactured to the same design, eliminating inconsistencies in performance between horizontal and vertical components whilst still maintaining an orthogonal orientation for redundancy. The new generation of sensor makes use of novel materials and techniques to drastically improve the noise performance over traditional mid-band sensors.

The sensor components include digital elements to the feedback loop, allowing for the sensor module to have an on-board serial server. This facilitates greater interoperability with Minimus based digitizer platforms, including automatic pulling of sensor serial number, sensor module SOH channels and the ability to remotely adjust the long period corner between options of 1s and 120s. This therefore makes the sensor module incredibly easy to deploy and mitigates against previous requirements for multiple instruments of varying responses.

The sensor module has now been successfully developed into a number of different packages for varying deployment scenarios including borehole (the Radian), offshore (Aquarius and Maris), vault (Certimus) and posthole (Certis) application. All packages make use of the latest digital technologies to reduce power consumption down to <300mW.

How to cite: Foster, C., Price, E., Watkiss, N., Clarke, A., Hill, P., Lindsey, J., and Restelli, F.: A comparison of next generation mid-band broadband seismometers and traditional sensor technologies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10868, https://doi.org/10.5194/egusphere-egu24-10868, 2024.

EGU24-12932 | Orals | GI1.1

Removing the memory effect from water stable isotope analysis 

Hubert Vonhof, Stefan de Graaf, Elan Levy, and Julian Schroeder

Over the past decade or so, laser spectrometric instruments have revolutionized the field of isotope analysis of water samples. These instruments do not require complex lab facilities, are easy to use and can provide hydrogen and oxygen isotope data at high precision and high throughput.

One well-known shortcoming of these laser spectrometric analyzers is that individual measurements display significant sample-to-sample memory effects. Particularly at larger isotopic differences between samples, isotopic contamination by the previous sample can off-set the following measurements even after multiple injections. Therefore, it is common in many laboratories to run 7 or more replicate analyses of each sample, and discard the first 4 or so, to come to an accurate isotope value of that sample.

Because the single-shot precision of these instruments is rather good, the sample replication is not so much necessary for obtaining better precision, but indeed mostly needed to flush out the memory effect on the isotope values. Therefore, any technical adaptation that decreases the memory effect of these analyzers, and thus reduces the number of replicate analyses required to come to an accurate isotope ratio, would greatly improve the sample throughput of these instruments.

We here present an adapted injection interface system, coupled to a Picarro L2140i analyzer, that practically removes sample to sample memory effects. This effectively leads to accurate and high-precision isotope analysis of single-shot sample injections, even at large sample-to-sample isotope differences. Key to the removal of the memory effect is that the analyzer runs on a moisturized carrier gas, providing a constant water background upon which the injected samples are analyzed (De Graaf et al., 2021). We will present results of series of standard waters and natural samples (including seawaters) and discuss protocols that we developed for data calculation and quality control.

 

Reference:

de Graaf, S., Vonhof, H.B., Levy, E.J., Markowska, M., Haug, G.H., 2021. Isotope ratio infrared spectroscopy analysis of water samples without memory effects. Rapid Communications in Mass Spectrometry 35.

 

How to cite: Vonhof, H., de Graaf, S., Levy, E., and Schroeder, J.: Removing the memory effect from water stable isotope analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12932, https://doi.org/10.5194/egusphere-egu24-12932, 2024.

EGU24-13332 | Posters on site | GI1.1 | Highlight

Twenty five years of geochemical monitoring of the oceanic active volcanic island of El Hierro, Canary Islands 

Fátima Rodríguez, Ana Pires, Aarón Álvarez, María Asesio-Ramos, Gladys V. Melián, Eleazar Padrón, Pedro A. Hernández, Germán D. Padilla, Nemesio M. Pérez, and José Barrancos

El Hierro (278 Km2), the youngest and westernmost island of the Canarian archipelago,  is settled on an ocean floor 3.5 km deep and reaches 1.5 km above sea level. The island was constructed by rapid constructive and destructive processes in ~ 1.12 Ma. A submarine eruption took place from October 2011 to March 2012 about 2 km south of the small village of La Restinga in the southernmost part of the island. The eruptive process was the second longest and the second largest volume discharged in the historical volcanic activity of the Canaries (in the last 500 years) and was the first one to be monitored from the beginning. Since visible volcanic emissions are absent at the surface of El Hierro, one of the most useful geochemical tools to monitor the volcanic activity of El Hierro is the diffuse degassing studies. Diffuse CO2 emissions have been monitored at El Hierro Island since 1998 in a yearly basis, with higher frequency during the pre and eruptive period of 2011-2012. At each survey, 600 sampling sites are studied and measurements of soil CO2 efflux are performed in situ following the accumulation chamber method. During pre-eruptive and eruptive period, the diffuse CO2 emission released by the whole island experienced significant increases before the onset of the submarine eruption and the most energetic seismic events of the volcanic-seismic unrest. In the last survey, performed in the 2023 summer period, soil CO2 efflux values ranged from non-detectable up to 39 g m−2 d−1. Statistical-graphical analysis of the data show three different geochemical populations, background (B), intermediate (I) and peak (P), represented by 97.7%, 1.6 % and 0.7% of the total data respectively, with geometric means of 1.2, 20 and 27 g m−2 d−1, respectively. To quantify the diffuse CO2 emission for the 2023 survey, 100 sequential Gaussian simulations (sGs) were performed as interpolation method. The estimated 2023 diffuse CO2 output released to atmosphere by El Hierro was 528 ± 22 t d-1, value higher than the background average of CO2 emission estimated in 410 t d-1. The data presented here demonstrate that discrete surveys of diffuse CO2 emission offer important information to optimize the early warning system in volcano monitoring programs.

How to cite: Rodríguez, F., Pires, A., Álvarez, A., Asesio-Ramos, M., Melián, G. V., Padrón, E., Hernández, P. A., Padilla, G. D., Pérez, N. M., and Barrancos, J.: Twenty five years of geochemical monitoring of the oceanic active volcanic island of El Hierro, Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13332, https://doi.org/10.5194/egusphere-egu24-13332, 2024.

EGU24-15961 | Posters on site | GI1.1

Spontaneous potential surveys for geothermal exploration in Tenerife and La Palma (Canary Islands) 

David Martínez van Dorth, Silvia Beretta, Giovanni Floridia, Audrey Yin, Aarón Álvarez Hernández, Rubén García Hernández, María Jiménez-Mejías, Víctor Ortega Ramos, Luca D’Auria, and Nemesio M. Pérez

The spontaneous-potential (SP) method is a passive geophysical technique that measures naturally occurring voltage differences on the Earth's surface. This method is capable of identifying geoelectric anomalies which can be generated by different sources. In active volcanic areas, these geoelectrical anomalies may be related to thermoelectric and electrokinetic processes caused by the circulation of hydrothermal fluids in subsurface porous materials. The sensitivity of the SP method in characterizing hydrogeologic and hydrothermal circulations, together with its simplicity and non-intrusive nature, has made this method widely used for geothermal exploration in the last decades.

In the Canary Islands, the surface geothermal manifestations are less evident than in other active volcanic systems worldwide. Thus, exploration techniques used to study the geothermal potential of the Canaries must focus on investigating the possible presence of deep-seated hydrothermal reservoirs. For this purpose, self-potential surveys were conducted on the Tenerife and La Palma islands to determine the spatial variations of the electrokinetic potential related to the geothermal and volcanic-structural characteristics of the study areas. The choice of these two islands to promote the search for geothermal resources lies mainly in their historical volcanism, characterized by five well-documented historical eruptions on Tenerife and up to 8 on La Palma, where the most recent and voluminous eruption occurred in 2021.

The SP campaigns were carried out in two volcanic areas: the NW rift zone of Tenerife and the west flank of the Cumbre Vieja rift zone of La Palma. The instrumentation consisted of several V-FullWaver devices from IRIS Instruments, equipped with Cu-CuSO4 non-polarizable electrodes and copper wire reels ranging from 60m to 250m. The methodology consisted of measuring the potential difference of the electric field along different profiles. These profiles are divided into sections where the reference electrode remains at the beginning of the profile. At the same time, the other is moved, measuring on points spaced of about 60 m m until the maximum length of the cable is reached. Then, a new reference electrode is established, and the measurements continue along the profile. To obtain continuity in the data set along each profile, the reference correction is applied to connect all sub-sections of a single SP profile.

Measurement points were located along several trails within the geothermal prospecting areas. Preliminary results show anomalies ranging between -281 and 198 mV in Tenerife and between -234 and 256 mV in La Palma. The main objective of the SP application is to contribute to delimiting those areas of hydrothermal interest associated with the presence of geothermal resources. Although this study is in its initial stage, it promotes a more sustainable and resilient future for the Canary Islands, in which geothermal resources could provide a reliable and renewable energy source.

How to cite: Martínez van Dorth, D., Beretta, S., Floridia, G., Yin, A., Álvarez Hernández, A., García Hernández, R., Jiménez-Mejías, M., Ortega Ramos, V., D’Auria, L., and Pérez, N. M.: Spontaneous potential surveys for geothermal exploration in Tenerife and La Palma (Canary Islands), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15961, https://doi.org/10.5194/egusphere-egu24-15961, 2024.

EGU24-15994 | ECS | Posters on site | GI1.1

Taking stock of the global area boom for greenhouse cultivation in the 21st century 

Xiaoye Tong, Xiaoxin Zhang, Rasmus Fensholt, Peter Rosendal Dau Jansen, Sizhuo Li, Marianne Nylandsted Larsen, Florian Reiner, Feng Tian, and Martin Brandt

Greenhouse cultivation that favors agricultural productivity is booming globally in the past decades. Yet, currently little knowledge exists on its global extent and possible drivers of the expansion. Here, we present a global assessment of greenhouse cultivation and map 1.3 million hectares of greenhouse infrastructures in 2019, including both large (61%) and small scale (39%) greenhouse infrastructure that are optimally detectable by using commercial satellite data at 3 m resolution. Examining the temporal development of the 65 largest clusters (> 1500 ha), we show a recent upsurge in greenhouse cultivation in the Global South since 2000s, primarily aimed at enhancing agricultural productivity and achieving economic prosperity. China is leading the boom in the Global South and accounts for 61% of the global greenhouse cultivation. Trade and production data for five major greenhouse-cultivated vegetables suggest that China's greenhouse cultivation boom is primarily driven by domestic mechanisms, rather than international ones. To investigate this hypothesis, we examined the spatial patterns of greenhouse cultivation in China and found distinct configurations around urban areas for food provision and around rural areas for poverty alleviation. Our high-resolution thematic map serves as a global baseline for future exploration of environmental and socioeconomic factors related to greenhouse cultivation. Our study also underscores the need for sub-category reporting and optimizing international policies to address measurement, reporting, and verification of greenhouse cultivation.

How to cite: Tong, X., Zhang, X., Fensholt, R., Rosendal Dau Jansen, P., Li, S., Nylandsted Larsen, M., Reiner, F., Tian, F., and Brandt, M.: Taking stock of the global area boom for greenhouse cultivation in the 21st century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15994, https://doi.org/10.5194/egusphere-egu24-15994, 2024.

EGU24-15996 | Orals | GI1.1

Accurate characterization of graphite in ores and black mass using an innovative sample preparation method for automated mineralogy 

Hassan Bouzahzah, Laura Lenoir, Eric pirard, and Raphaël Mermillod-Blondin

Automated mineralogy systems are widely used for the mineralogical characterization of powder samples for mineral processing purposes. This characterization method requires the mineral powder to be embedded in a resin (polished block (PB) preparation). Very quickly, some problems linked to polished block preparation arose. This particularly involves the mineral settlement in the liquid resin due to differences in mineral size and density. Several authors have suggested solutions to overcome the error results due to the PB preparation method, such as vertical section, the addition of sized graphite, dynamic hardening, and the addition of black carbon (BC) to increase resin viscosity avoiding mineral settlement. Only the BC method resolved all the errors associated with the PB preparation. Indeed, it eliminated the mineral settlement and provided excellent spatial dispersion of particles on the observation surface, ensuring better mineral quantification and liberation/association estimation, except for the graphite-bearing samples. In fact, as graphite shows no contrast with resin under back-scattered electron-based based images, it cannot be characterized by the automated mineralogy systems. few studies have addressed this problem by the addition of carnauba wax or iodoform to contrast resin and graphite. The iodoform was easy to use and provided better contrast compared to carnauba wax. This work presents an innovative polished block preparation method that combines CB and iodoform to prevent both particle settlement and to contrast the resin and graphite which was very challenging. The obtained results are highly satisfying and comparable to those of standard characterization techniques such as XRD and chemical assay. This new preparation method is highly useful for graphite-bearing black mass (obtained from battery recycling) characterization by automated mineralogy systems.

How to cite: Bouzahzah, H., Lenoir, L., pirard, E., and Mermillod-Blondin, R.: Accurate characterization of graphite in ores and black mass using an innovative sample preparation method for automated mineralogy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15996, https://doi.org/10.5194/egusphere-egu24-15996, 2024.

The Güralp Minimus broadband digitiser introduced innovative features to the market including easy network configuration; compact form-factor; extensive State of Health (SOH) monitoring; and low latency digitisation. Since it was launched in 2016, technological advances in semiconductors have significantly decreased their power requirements. The latest iteration of Minimus, Minimus2, utilises modern microprocessors to reduce power consumption by over 50% whilst maintaining high levels of functionality. The resulting reduction in power consumption facilitates simplified field deployments for offline deployments.

The Minimus platform also provides a high level of functionality for online stations, including the industry unique option of sending State of Health (SOH) data via the SEEDlink protocol. As well as simplifying SOH monitoring for larger networks, this facility also allows for time-series analysis of SOH data. This means that operators have the data they need to proactively manage their station network and diagnose issues before they result in data loss. The Minimus platform interfaces with Discovery software which seamlessly integrates new stations into existing networks. The management of large numbers of real-time seismic stations is further enhanced with Guralp Data Centre (“GDC”) a cloud-based software package that is an optional add-on of the Discovery tool set.

The Minimus platform was built from the ground up to provide one of the lowest latency digitizers available with digitization latencies down to 40ms, making it well suited to Earthquake Early Warning applications. This is achieved with the use of causal decimation filters, high sample rates and Guralp’s proprietary GDI protocol. The Minimus platform is built as a modular digitizer platform that is available within a number of different packages to suit a range of applications, including as a stand-alone digitiser or built within broadband seismic instruments and force balance accelerometer systems. 

How to cite: Price, E., Watkiss, N., and Restelli, F.: The Minimus Digitizer Platform: a User-Friendly Ecosystem for Efficient Network Management and Seismic Station Configuration., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16231, https://doi.org/10.5194/egusphere-egu24-16231, 2024.

EGU24-16989 | Orals | GI1.1

Inversion of real gravity data from geological faults using a generative neural network model 

Henrietta Rakoczi, Gary Barnes, Abhinav Prasad, Karl Toland, Christopher Messenger, and Giles Hammond

Normalising flows is a novel generative neural network model, which can be applied to Bayesian parameter inference. When gravity inversion is reformulated as a probabilistic inference problem, stable results can be obtained that naturally incorporate the inherent uncertainties and noise from the source background and the instrument. As opposed to some standard methods, Bayesian gravity inversion does not default to a single solution in an ill-posed problem, but informs the user about all possibilities that are consistent with the gravimetry survey of interest. It has been demonstrated that the normalising flow method can provide accurate results for a simulated data set, even when applied to high-dimensional data. Once the network is trained, the results can be obtained within seconds and it can be reused, without retraining, for multiple gravimetry surveys that are consistent with the training data set. Here, improvements on the previous work are presented, where the method is applied to a more realistic and complex geophysical problem; the inversion of gravity measurements to infer parameters of geophysical faults. The normalising flow network is trained and tested for fault models with various complexities, and finally the method is applied to the inversion of airborne gravimetry data. 

 

How to cite: Rakoczi, H., Barnes, G., Prasad, A., Toland, K., Messenger, C., and Hammond, G.: Inversion of real gravity data from geological faults using a generative neural network model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16989, https://doi.org/10.5194/egusphere-egu24-16989, 2024.

Mine optimisation and anticipation of ore behaviour in the mineral processing and separation circuits are major economic drivers for all mining operation. Recent methodological developments with the inception of geometallurgy across multiple commodities has highlighted the importance of mineralogy in addition to grades. Since several decades, many quantitative tools have been developed, mostly SEM-based such as QEMSCAN®, to provide quantitative mineralogical composition and textural properties of ore and gangue samples. We aim to compare the more established SEM-based techniques to the Solsa combined XRD-XRF analyser to highlight their respective potential and limitations depending on the minerals and goals of the mining operators. The combined XRF-XRD of the SOLSA analytical solution brings a new methodology able to produce quantitative mineralogical and geochemical data at a speed compatible with routine data collection, from exploration to quality control on the different streams of minerals in a processing plant.

How to cite: Herbelin, M., Delchini, S., Pillière, H., Lutterotti, L., Nicco, M., Dia, M., and Riegler, T.: The pros or cons of X-ray diffraction vs electron beam techniques in the assessment of mineral assemblages: improvements of Solsa combined XRD-XRF analyses applied to the Grande Cote Operation Ti-Zr mine, Senegal., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17031, https://doi.org/10.5194/egusphere-egu24-17031, 2024.

EGU24-17777 | ECS | Posters on site | GI1.1 | Highlight

Microgravity surveys for geothermal exploration in Tenerife and La Palma islands (Canary Islands) 

Víctor Ortega-Ramos, Julian Benjamin Lai, Isabella Michelle Sulvarán Aguilar, Adriana Quezada-Ugalde, Aarón Álvarez Hernández, Rubén García Hernández, María Jiménez-Mejías, David Martínez van Dorth, Germán D. Padilla, Luca D’Auria, and Nemesio M. Pérez

Gravimetry is a passive geophysical technique that measures variations in the Earth's gravitational field over its surface. This method studies the gravimetric anomalies caused by the presence of heterogeneities in the subsurface, and its values vary depending on the density of the different geological bodies in the subsoil.

This technique has become fundamental in geothermal exploration, providing information on the subsurface density distribution, which allows for constraining underground geological structures. Specifically, it could enable identifying and characterizing gravitational anomalies generated by geothermal resources.

This work is focused on the islands of Tenerife and La Palma, belonging to the Canary Islands. These two islands have been the object of different microgravity studies in recent decades. However, we aim to reach unprecedented detail on some target areas to get a detailed image of the subsurface density distribution. We measured gravity on 109 points in a few target areas of Tenerife and 67 points on the Cumbre Vieja Volcano Complex on the island of La Palma. The precise positioning of the measurement points was realized with a differential GPS (Leica Viva CS10) reaching less than 0.003m of accuracy in the vertical component. Gravity measurements have been realized with a CG-6 Autograv™ gravity meter with a reading resolution of 1 μgal. Every gravity value has been obtained with an average of at least ten measurement cycles of thirty seconds each. This allowed reaching a precision of less than five μgal. Firstly, we got Bouguer anomaly maps of the different target areas of Tenerife and La Palma. Then, we perform inverse modelling to retrieve 3D density models of such regions. Although preliminary, the results reveal a complex geological setting, in accordance with previous geophysical studies

The gravimetric method plays a crucial role in identifying geothermal resources in the Canary Islands. This technique offers perspectives to further develop renewable energies in the Archipelago, fostering a transition towards more sustainable and environmentally friendly energy sources.

How to cite: Ortega-Ramos, V., Lai, J. B., Sulvarán Aguilar, I. M., Quezada-Ugalde, A., Álvarez Hernández, A., García Hernández, R., Jiménez-Mejías, M., Martínez van Dorth, D., Padilla, G. D., D’Auria, L., and Pérez, N. M.: Microgravity surveys for geothermal exploration in Tenerife and La Palma islands (Canary Islands), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17777, https://doi.org/10.5194/egusphere-egu24-17777, 2024.

EGU24-18674 | Posters on site | GI1.1

Ground CO2 monitoring at Timanfaya volcano (Lanzarote, Canary Islands) during the period 1999-2023 

Daniel Di Nardo, Silvia Paglia, Gladys V. Melián, Nemesio M. Pérez, Eleazar Padrón, Pedro A. Hernández, Fátima Rodríguez, and María Asensio-Ramos

Lanzarote Island (795 km2) is a volcanic island located in the eastern part of the Canary Islands and approximately 100 km from the NW coast of Morocco. The largest historical eruption of the Canary Islands, Timanfaya, took place during 1730-36 in this island when long-term eruptions from a NE-SW-trending fissure formed the Montañas del Fuego. Tinguaton volcano, the last eruption at Lanzarote Island, occurred in 1824 and produced a much smaller lava flow that reached the SW coast. At present, one of the most prominent phenomena at Timanfaya volcanic field is the high maintained superficial temperatures occurring in the area since the 1730 volcanic eruption. The maximum temperatures recorded in this zone are 605ºC, measured in a slightly inclined well 13 m deep. Since fumarolic activity is absent at the surface environment of Lanzarote, to study the diffuse CO2 emission becomes an ideal geochemical tool for monitoring its volcanic activity. We report herein the results of eight soil CO2 efflux surveys performed from 2006 to 2023 at Timanfaya Volcanic Field (TVF) with the aim to evaluate the temporal variations of the diffuse CO2 emission. Approximately 400 sampling sites were selected at each survey to obtain an even distribution of the sampling points over the study area. Soil CO2 efflux was measured following the accumulation chamber method. Soil temperature at 40 cm depth and soil gas samples collected at each sampling site was also measured to evaluate the chemical and isotopic composition of soil gases. Diffuse CO2 emission values have ranged between non detectable values to 34 g·m-2·d-1, with the highest values measured in September 2008. Conditional sequential Gaussian simulations (sGs) were applied to construct soil CO2 efflux distribution maps and to estimate the total CO2 output from the studied area at the TVF. Soil CO2 efflux maps showed a high spatial and temporal variability. Most of the study area have shown relatively low values, around the detection limit of the instrument (~0.5 g·m-2·d-1). Higher soil CO2 diffuse emission values were observed where thermal anomalies occur, indicating a convective mechanism transport of gas from depth at these areas. Diffuse CO2 emission rates ranged between 41 and 519 t·d-1 during the study period (57 t·d-1 for 2023). Long-term temporal variation on total CO2 diffuse emission shows a peak recorded on winter 2011, suggesting a seasonal control on the CO2 emission. These observations along with the results from the eight soil gas surveys performed at TVF indicate that the short and long-term trends in the diffuse CO2 degassing are mainly controlled by environmental factors.

How to cite: Di Nardo, D., Paglia, S., Melián, G. V., Pérez, N. M., Padrón, E., Hernández, P. A., Rodríguez, F., and Asensio-Ramos, M.: Ground CO2 monitoring at Timanfaya volcano (Lanzarote, Canary Islands) during the period 1999-2023, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18674, https://doi.org/10.5194/egusphere-egu24-18674, 2024.

EGU24-19227 | Orals | GI1.1

Mineral Exploration of the Senegalese Grande Côte heavy minerals placer: QEMSCAN® characterisation of Fe-Ti oxides for ore modelling 

Aisha Kanzari, Sophie Graul, Arthur Delaporte, Rutt Hints, and Simon Blancher

Titanium-containing minerals serve a variety of industrial applications. Iron and titanium oxides, ilmenite (Fe2+TiO3), pseudorutile (Fe23+Ti3O9), and rutile/anatase (TiO2) are notably used in the production of paint, plastic and paper pigments; moreover, titanium metal is considered as a Critical Raw Material (CRM). Grande Côte Operation (GCO), a subsidiary of Eramet, has been operating the Senegalese Grande Côte heavy minerals (HM) placers for zircon and Fe-Ti oxides since 2014. Senegal's placer deposits extend over 100 km in length and 5 km in width and lie alongside the country's north coast. These Quaternary ore-bodies resulted from the erosion of the Mauritanian belt and repetitive episodes of marine transgression and regression, as well as from aeolian dune formations, leading to significant heterogeneity. Related distribution trends in impurities and heavy minerals are yet not anticipated or understood.

This study explores the mineralogical heterogeneities to investigate variations in terms of the distribution and alteration of the titanium-bearing phases. Ten drill cores were selected to investigate three synthetic profiles based on high-resolution sampling. Heavy minerals from composite samples were recovered using dense liquid. The obtained concentrates were prepared as representative thick sections for textural analysis. Semi-quantification investigations were conducted by means of QEMSCAN® analyses.

The heavy minerals content was not related to sand facies or depth, and the average concentration ranged from 0.1% to 4.2%, with an average of 0.9. From the concentrate, it could be inferred that Fe-Ti phases represented 14.4% for ilmenite, 57.1% for pseudorutile, 1.8% for anatase and 3.7% for rutile. Pseudorutile was the predominant phase, indicating an advanced alteration. A decrease in ilmenite/pseudorutile ratio was observed with increasing depth in all profiles.

Based on these findings, the alteration rate in the ilmenite series was investigated by adding a finely spaced range of Fe/Ti ratios and impurities content (mainly Al) to the QEMSCAN® database. The weathering process is initiated by the oxidation of Fe2+ into Fe3+, progressively leading to the formation of pseudorutile, marked by grains with cracking patterns due to topotaxial reactions. The following stage is driven by iron-lixiviation and implies hydroxylian pseudorutile apparition due to intense hydration and hydroxylation processes. Dissolution and reprecipitation reactions led to a final alteration, creating highly Ti-enriched, impurities-rich and porous grains. The evolution with depth of the coefficient of variation between the content of Fe-Ti phases illustrated an authigenic Ti-enrichment. A substantial drop (-40%) in unaltered ilmenites was observed at surface levels. A downward enrichment of pseudorutile proportion (5 to 10%) was observed up to 13m, where the sharp increase (up to 40%) in Ti-rich phases correlates to the water-table depth above 18m, advanced alteration led to the transformation of almost all ilmenite phases into pseudorutile.

QEMSCAN® analyses contributed to a better understanding of the Grande Côte placer deposits, highlighting the significance of spatial variability and local water table settings for Fe-Ti oxide distribution and alteration processes, allowing a first ore body modelling and a global assessment of HM content.

How to cite: Kanzari, A., Graul, S., Delaporte, A., Hints, R., and Blancher, S.: Mineral Exploration of the Senegalese Grande Côte heavy minerals placer: QEMSCAN® characterisation of Fe-Ti oxides for ore modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19227, https://doi.org/10.5194/egusphere-egu24-19227, 2024.

The Direct Current Resistivity (DCR) method is one of the well-known geophysical methods used for a wide range of areas such as mining geophysics, hydrogeophysics, and archaeogeophysics investigations. DCR data is generally collected along profile using multi-electrode and multi-channel measurement systems and interpreted using ‘two-dimensional (2D) or three-dimensional (3D) inversion algorithms. The inverse problem of DCR data is ill-posed (nonlinear, nonunique, and unstable). Therefore, the generally smoothing regularization inversion method is used for DCR data inversion. Additionally, a homogenous resistivity model is used as the initial model in regularized inversion. Hence, we generally obtain a smooth resistivity model after 2D/3D inversion. However, some structures such as buried archaeological targets, cavities, and fault structures have sharp boundaries with their neighboring medium.

 

In this research, we propose enhancing 2D DCR data inversion results using a convolutional neural network (CNN), aiming for sharp boundaries. We developed a U-net-based CNN algorithm, named DCR2D_Net_Archeo. This method utilizes 2D inversion results as the input, with the real resistivity model serving as the output, streamlining geophysical data interpretation for archeological applications.  We tested the DCR2D_Net_Archeo algorithm by using synthetic and real data.  We showed that the developed resistivity model enhancement algorithm, DCR2D_Net_Archeo, improves smooth inversion results and buried archeological remains' size and position can be delineated from those enhanced models. 

 

KEYWORDS: DC Resistivity, 2D, Inversion, Deep Learning, archaeo-geophysics.

 

ACKNOWLEDGEMENT: This study is part of the Ph.D. thesis of the first author and the manuscript about this study has been submitted to Pure and Applied Geophysics. This study is also made under the Ankara University Technopolis R&D projects (STBP code: 084286).  

How to cite: Över, D. and Candansayar, M. E.: Improving 2D resistivity model obtained from DC Resistivity Data Inversion by using Convolutional Neural Network Algorithm to Find Buried Archaeological Remains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19337, https://doi.org/10.5194/egusphere-egu24-19337, 2024.

EGU24-19641 | Posters on site | GI1.1

Remake of the low cost carbon dioxide sensor of the carbon dioxide network deployed by INVOLCAN in the urban areas of Puerto Naos and La Bombilla, La Palma, Canary Islands 

Gabriel González Rial, Daniel Dinardo, Germán D. Padilla, José Barrancos, Pedro A. Hernández, Nemesio M. Pérez, Konradin Weber, Christian Fischer, and Detlef Amend

An anomalous CO2 degassing appeared by the end of Tajogaite eruption (North-West flank of Cumbre Vieja volcano ridge, La Palma, Canary Islands), in the neighborhoods of La Bombilla and Puerto Naos at about 6 km distance from the volcanic vent. The areas affected by the anomalous CO2 degassing were not directly affected by lava flows during the eruptive period. After the eruption, and due to this strong volcanic-hydrothermal carbon dioxide emissions (CO2>5-20%)  were included in the exclusion zone. CO2 is an invisible toxic gas, as well as asphyxiating, and may be lethal when is present in concentrations higher than 14%. During the post-eruptive period, INVOLCAN deployed its own indoor and outdoor CO2 monitoring networks in collaboration with other institutions, with the aim of delimitating the anomalous CO2 degassing areas, paying attention to those areas where CO2 air concentration exceeds hazardous thresholds. The number of monitoring stations were increasing to cover most of the homes, garages, basements, and local businesses. The first monitoring network were based on a LILYGO® TTGO T-SIM7000G electroniccard, previously programmed with an unstable algorithm that caused problems during the measurements. After some implementations to enhance the stability of the sensor, a new algorithm was developed that consists of the acquisition of ambient values every 5 seconds, applying a Moving Average Filter in every measurement to avoid outliers. The SIM card integrated in the hardware allows the data transmission to an MQTT broker where the values are published every 5 minutes, recollecting them in a unique Raspberry Pi 4 Model B located at the INVOLCAN headquarters, that reads and stores the data in two databases (InfluxDB and Google Sheets). The visualization of the values are done through Grafana Cloud, recollecting the data from InfluxDB and showing them distributed as tables and a geographic map that illustrates the concentration in the measurement points. The difference between this and the last storing is the flexibility when visualizing the data, that can be transformed to different kind of plots as mentioned. Moreover, an API for the management of each subsystem is created using PyQT, allowing to the user the calibration of the sensors in remote, as well as executing a soft reboot, or the integration of deeper parameters like the sensor mode (manual polling, streaming or command mode) or pressure data. Two of the 20 devices have been successfully installed and they are working correctly in La Palma, meanwhile an amount of 18 devices are being tested and recollecting properly with better stability in CO2 concentration measurements at our laboratory and will be installed indoor in different locations soon. The remaking of the algorithm allows to forget previous problems of wrong data and disconnections, obtaining accurate data compared to commercial sensors and helping the operator to configure and control the sensors without moving to conflicting locations.

How to cite: González Rial, G., Dinardo, D., Padilla, G. D., Barrancos, J., Hernández, P. A., Pérez, N. M., Weber, K., Fischer, C., and Amend, D.: Remake of the low cost carbon dioxide sensor of the carbon dioxide network deployed by INVOLCAN in the urban areas of Puerto Naos and La Bombilla, La Palma, Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19641, https://doi.org/10.5194/egusphere-egu24-19641, 2024.

EGU24-19666 | ECS | Orals | GI1.1

Environmental stability of MEMS gravimeters. 

Elizabeth Passey, Abhinav Prasad, Karl Toland, Kristian Anastasiou, Douglas Paul, and Giles Hammond

Wee-g is a new gravimeter that utilises a micro-electromechanical system (MEMS) sensor. The use of MEMS-based sensors has benefits as a new gravimetry technology because the low cost of the base material silicon and accessibility of manufacturing facilities will enable increased availability of gravimeters. However, the challenge of working with silicon for a gravimetry device is its thermal sensitivity, which affects the Young's Modulus of the material. In the context of Wee-g's sensor design, when the flexures that support the proof mass become softer because of temperature changes, under gravity the proof mass change position. Changes to the ambient pressure can also result in changes to the proof mass position. Wee-g has a thermal control system that effectively controls the temperature at the sensor to within 1mK, but field observations indicate that large changes to ambient environmental conditions can be coupled to the sensor output. Here we present the results of environmental stability tests conducted on a Wee-g field prototype with implications for its performance in field environments that vary in temperature and pressure significantly.

How to cite: Passey, E., Prasad, A., Toland, K., Anastasiou, K., Paul, D., and Hammond, G.: Environmental stability of MEMS gravimeters., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19666, https://doi.org/10.5194/egusphere-egu24-19666, 2024.

EGU24-19870 | Orals | GI1.1

Soil H2 degassing studies: a useful geochemical tool for monitoring Cumbre Vieja volcano, La Palma, Canary Islands 

Megan Expósito, Sophia Ioli, Ileana Santangelo, Gladys V. Melián, María Asensio-Ramos, Mónica Arencibia, Sttefany Cartaya, Carla Méndez, Nemesio M. Pérez, Eleazar Padrón, Pedro A. Hernández, Fátima Rodríguez, Germán D. Padilla, and Antonio J. Álvarez

La Palma Island (708 km2), situated in the northwest of the Canarian Archipelago, stands as one of the youngest (~2.0 My) islands. A new volcanic eruption took place at the Cumbre Vieja volcanic system, located in the southwest flank of the island, on September 19, 2021. Cumbre Vieja is renowned as the most active basaltic volcano in the Canaries. The eruptive event, which lasted for 85 days, featured various volcanic activities, including lava effusion, strombolian activity, lava fountaining, ash venting, and gas jetting, and concluded on December 13, 2021.

Regular surface geochemical studies have been conducted focusing on hydrogen (H2) emissions along Cumbre Vieja. H2, being one of the most abundant trace species in volcano-hydrothermal systems, plays a pivotal role in numerous redox reactions occurring in the hydrothermal reservoir gas. This comprehensive study of H2 emissions has been ongoing since 2001, encompassing continuous monitoring of soil gas samples collected at a depth of approximately 40 cm across 600 sites during each survey. H2 concentrations have been meticulously analyzed using a micro-gas chromatograph (Agilent 490 microGC).

Spatial distribution maps have been generated using sequential Gaussian simulation (sGs) techniques to quantify the diffuse H2 emissions from the study area. The time series data of the diffuse H2 emissions indicate significant increases before and during the occurrence of seismic swarms observed between 2017 and 2021. Furthermore, during the eruptive phase, substantial spikes in the diffuse H2 emissions were observed, closely correlating with the volcanic tremor escalation. These fluctuations in diffuse H2 emissions were observed preceding the peak of diffuse CO2 emissions, aligning with the anticipated behavior of these gases. Over the last two years following the eruption, the values have reverted to levels like those observed during periods of volcanic calm, reinstating the stability in the diffuse H2 emissions.

The absence of visible volcanic gas emissions before the eruption, such as fumaroles or hot springs, on the surface of Cumbre Vieja underscores the importance of such studies in serving as a critical tool for continuous volcanic surveillance and monitoring purposes. This update represents ongoing efforts to comprehensively study and understand the behavior of hydrogen emissions within the volcanic system, providing essential insights into volcanic activity and potential precursor signals for enhanced monitoring and risk assessment.

How to cite: Expósito, M., Ioli, S., Santangelo, I., Melián, G. V., Asensio-Ramos, M., Arencibia, M., Cartaya, S., Méndez, C., Pérez, N. M., Padrón, E., Hernández, P. A., Rodríguez, F., Padilla, G. D., and Álvarez, A. J.: Soil H2 degassing studies: a useful geochemical tool for monitoring Cumbre Vieja volcano, La Palma, Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19870, https://doi.org/10.5194/egusphere-egu24-19870, 2024.

Automated mineralogical analysis (quantitative scanning electron microscopy) is a powerful tool that has been used extensively to understand the occurrence and deportment of precious and base metals and critical minerals and is used to optimize the design of extractive metallurgy methodologies. However, this data-rich product can also be used in a predictive context and as the basis for data integration across the range of scales. Automated mineralogical data include quantitative mineral abundance and textural data that can form the basis for machine learning algorithms to improve statistical subsampling strategies, data integration, mineralogical upscaling, and to increase the value of x-ray fluorescence- and hyperspectral data.   

The Mineral and Materials Characterization Facility in the Department of Geology and Geological Engineering at the Colorado School of Mines in Golden, USA, houses two scanning electron microscopy-based automated mineralogy systems. These systems are used to conduct research over a broad range of disciplines including all stages of the mine life cycle, energy and petroleum resources investigations, provenance and climate studies, and environmental and biological studies.   

During this presentation, we will explore examples of how automated mineralogy can play a crucial role across the mine life cycle that spans from mineral exploration, mine planning and mining, extractive metallurgy, proactive waste rock and tailings management, to reclamation. The example use-inspired research projects, conducted through the Center to Advance the Science of Exploration to Reclamation in Mining (CASERM) using the Advanced Mineral Analysis and Characterization System (AMICS) from Bruker based on a field-emission scanning electron microscope from Hitachi, focus on the integration of diverse geoscience data types to accelerate and improve decision making across the mine life cycle.   

Quantitative scanning electron microscopy provides important mineralogical and textural data that can inform statistical, thermodynamic, and kinetic models. These data improve not only our understanding of the subsurface in the context of hard-rock mining, but can inform other disciplines such as geothermal energy exploration and extraction and understanding the carbonation potential, helping move the world towards a greener future. 

How to cite: Pfaff, K.: Automated Mineralogy – A Valuable and Data-Rich Product to Advance the Green Energy Transition  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20638, https://doi.org/10.5194/egusphere-egu24-20638, 2024.

EGU24-22369 | Posters on site | GI1.1

A circular workflow based on Earth Observation tools for the detection and characterization of illegal waste dumping sites in a waste to energy framework and policy assessment 

Alessandro Mei, Alfonso Valerio Ragazzo, Sara Mattei, Emiliano Zampetti, Patrizio Tratzi, Alice Cuzzucoli, Giuliano Fontinovo, Giorgio Pennazza, Marco Torre, Valentina Terenzi, and Mario Grosso

The main illegal Solid Waste Management (SWM) issues concern their detection and their consequent disposal/reuse/recycle, both at the municipal, provincial, and regional scales. Nowadays, an important aspect is that even developed countries show difficulties with the management of illegal wastes and decision-making processes in the field are not enough developed by policymakers. This contribution aims to reduce the environmental pressure caused by the illegal disposal of solid waste through the development of a circular model which includes different approaches. A multiparametric downscaling analysis integrating satellite (Worldview-2), Unmanned Aircraft Vehicle (UAV) and Unmanned Ground Vehicles (UGV) was applied first. From satellite images waste sites were first extracted by supervised techniques, while UAV and ground data were used for their characterization by means of Artificial Intelligence (AI) techniques. Furthermore, a volume’s frequencies map is obtained by using geospatial information, estimating the volume of garbage for each sampling site. Air quality sensors mounted on UGV were used to monitor each sample site to reveal environmental criticalities. Considering such kind of outputs, a Life Cycle Assessment (LCA) was setup to evaluate some waste to energy solutions. A cost analysis was finally performed by including information regarding the transport of waste to the nearest municipal collectors and, subsequently, to the assigned regional recovery plants. For this reason, a spatial model concerning the shortest paths, considering route network and local environmental variables, was made by using R scripts, QGIS geoinformation system, and Dijkstra’s algorithm. Finally, thematic maps and statistics were obtained with the aim of developing methodologies to solve social-political problematics as SWM issues. The project is focused on three municipalities in Calabria (Italy, Province of Catanzaro), within the INTESA project - INtegrazione di sistemi di TElerilevamento e Sensoristica per l’individuazione di accumulo di materiali in Abbandono " - promoted by the National Research Council - Institute for Atmospheric Pollution (CNR-IIA) and funded by POR Calabria FESR FSE 2014/2020 of the Calabria Region (LIVING LABS). Thus, all these information will be fundamental for the development of a regional Decision Support System (DSS) about SWM issues.

How to cite: Mei, A., Ragazzo, A. V., Mattei, S., Zampetti, E., Tratzi, P., Cuzzucoli, A., Fontinovo, G., Pennazza, G., Torre, M., Terenzi, V., and Grosso, M.: A circular workflow based on Earth Observation tools for the detection and characterization of illegal waste dumping sites in a waste to energy framework and policy assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22369, https://doi.org/10.5194/egusphere-egu24-22369, 2024.

EGU24-22519 | Orals | GI1.1

Automated Mineralogy: from drill cores to sub-micron information 

Andrew Menzies, Alan R. Butcher, and Nigel M. Kelly

The transition towards cleaner energy and the manufacture of associated new technologies will require extraction of mineral resources at volumes much greater than at present.  Consequently, identification of new deposits is both economically and strategically important, driving a boom in mineral exploration coupled with a need to lower the environmental impact through more efficient mining capabilities.  Crucial is an understanding of mineralogy and texture across scales, and thus improving knowledge at each stage of the mining cycle – from exploration through to production and ultimately to waste handling.  A key tool in this understanding is Automated Mineralogy.     

Automated Mineralogy has been integral to process mineralogy for more than two decades, with SEM being the traditional analytical platform.  However, the extension of Automated Mineralogy using scanning micro-XRF instruments allows the technique to be implemented across broader spatial scales.  In practice, the same logical workflow can be applied from the scale of large cut or split (minimally prepared) drill-core samples,through to polished thin sections or block mounts of various sample types (fragments or crushed plant material).  At the most detailed level, the information obtained can be at the sub-micron scale of mineral classification, or even zonation withing single grains. 

An example of Automated Mineralogy as applied to Au-Co exploration is presented that highlights the benefit of analysis across scales, integrating information collected using the AMICS platform on drill core measured using scanning micro-XRF, and thin sections measured by SEM.  The example will also demonstrate the ability to use the same Automated Mineralogy approach to define and quantify sub-micron information within individual mineral grains.   

How to cite: Menzies, A., Butcher, A. R., and Kelly, N. M.: Automated Mineralogy: from drill cores to sub-micron information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22519, https://doi.org/10.5194/egusphere-egu24-22519, 2024.

EGU24-2543 | ECS | Posters on site | ITS1.15/GI1.3

Comparative Analysis of Ground-Based and Satellite-Derived UV Index: Variability and Reliability from Three South American Mid-Latitudes Sites 

Gabriela Reis, Hassan Bencherif, Marco Reis, Bibiana Lopes, Marcelo de Paula Corrêa, Damaris Kirsch Pinheiro, Lucas Vaz Peres, Rodrigo da Silva, and Thierry Portafaix

Solar Ultraviolet Radiation (UV) corresponds to electromagnetic waves with wavelengths of 100-400 nm, constituting approximately 5% of the energy emitted by the sun. The risks and benefits of exposure to UV for life on Earth have been known for many years and include impacts on human health, materials, terrestrial and aquatic ecosystems, and biogeochemical cycles. Climate change, influenced by land use change and other factors, can increase or decrease the intensity of the incident UV depending on location, seasons, and changes in the atmospheric composition. UV intensity reaching the surface can be informed as the UV index. This dimensionless indicator often makes it easier for people to assess their UV levels and understand how to protect themselves from excessive sun exposure. In middle-income countries like Brazil and Argentina, networks, and instruments for monitoring UV are often sparse and poorly supported with both capacity and funding, and thus, obtaining reliable UV data is difficult. With only a few stations reporting long-term UV measurements, which significantly restricts its extrapolations to all populated areas, a way to continuous monitoring UV globally is through satellites. Similar to ground-based observations, satellite measurements are affected by instrument errors and are subject to uncertainties in the algorithms used to derive surface UV radiation. Therefore, evaluation of satellite-based estimates of surface UV against available ground measurements at many locations around the world is needed to characterize the errors toward further refinement of the surface UV estimates, especially in the Southern Hemisphere, where there has been relatively limited work to compare ground-based and satellite-derived UV. This study compares ground-based and satellite-derived UV Index levels from OMI (Ozone Monitoring Instrument) at overpass time during clear sky conditions, which are determined using LER (Lambertian Equivalent Reflectivity). A characterization of the diurnal and seasonal variability of the ground-based UV index levels will also be reported. The study period will be from 2005 to 2022, varying according to each data source, and comprises data from two Brazilian cities – Itajubá (22.41ºS, 45.44ºW, 885 m, Davis 6490 UV sensor), Santa Maria (29.4°S, 53.8°W, 476 m, Brewer Spectrophotometer MKIII #167), and from Buenos Aires in Argentina (34.58º S, 58.48°W, 25 m, Solar Light UV Biometer – Radiometer model 501). Comparing satellite-derived data with ground-based measurements helps validate the accuracy of satellite data, which can help identify any discrepancies and improve the satellite data retrieval algorithms, leading to more accurate satellite-derived UV products. Also, such a process of data verification is necessary should these data be used for long-term trend analysis or the monitoring of UV exposure risk and possible impacts on human health, as we intend to do in a future study, to understand better the dynamics of the space-temporal variability of the surface UV in South America. 

How to cite: Reis, G., Bencherif, H., Reis, M., Lopes, B., de Paula Corrêa, M., Kirsch Pinheiro, D., Vaz Peres, L., da Silva, R., and Portafaix, T.: Comparative Analysis of Ground-Based and Satellite-Derived UV Index: Variability and Reliability from Three South American Mid-Latitudes Sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2543, https://doi.org/10.5194/egusphere-egu24-2543, 2024.

A multi-channel brightness temperature (TB) Fundamental Climate Data Record (FCDR) for the period 1991-present has been developed in this study using measurements from two Special Sensor Microwave Imagers (SSM/I) onboard the F11 and F13 satellites and one Special Sensor Microwave Imager/Sounder (SSMIS) onboard the F17 satellite of the US Defense Meteorological Satellite Program (DMSP). Hardware differences among these instruments were corrected using a combination of techniques including Principal Component Analysis (PCA), using the third instrument as an intermediate, and weighted averaging, which accounts for interchannel covariability and observation matching issues. After intercalibration, all imagers were standardized using SSMIS as the observation reference. The average biases of the recalibrated TBs for almost all channels between any two instruments are globally less than 0.2 K, with standard deviations (STDs) of less than 1.2 K. This resulted in a 30-year continuous and stable FCDR. Based on this FCDR, a long time series of column water vapour (CWV) over the global oceans was retrieved. Validation of this retrieved moisture product against reanalysis, in-situ radiosonde, and Global Navigation Satellite System (GNSS) measurements showed reasonable accuracy, suggesting that the presented FCDR has high potential for climate applications. In the future, this research method will be applied to more satellites to create an expanding dataset of satellite observations that could enhance the accuracy of climate model assessments and improve the reliability of climate predictions.

How to cite: Liu, S. and Wang, Y.: Highly consistent brightness temperature fundamental climate data record from SSM/I and SSMIS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4525, https://doi.org/10.5194/egusphere-egu24-4525, 2024.

The National Oceanic and Atmospheric Administration’s (NOAA) Joint Polar Satellite System (JPSS) provides critical observations of the Earth and its atmosphere from the ultraviolet region to the microwave region in Leo Earth Orbit (LEO). The mission now has three satellites in the same orbit: NOAA20 the primary satellite, NOAA21 as secondary and Suomi National Polar-orbiting Partnership (Suomi NPP) as the tertiary satellite. The primary and secondary satellite provide redundancy since measurements from the mission provide critical inputs to global numerical weather prediction. Since 2011, the multi-mission series of Low Earth Orbit (LEO) polar-orbiting environmental satellites is serving as one of the most important sources of continuous state-of-the-art observations of the Earth’s land, oceans, and atmosphere to protect lives and property, and support the global economy by providing accurate and timely environmental information. The Visible Infrared Imaging Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), the Ozone Mapping and Profiler Suite (OMPS), and the Clouds and the Earth’s Radiant Energy System (CERES) observe a large part of the electromagnetic spectrum from the UV region to the microwave region. All the sensors have state of the art onboard calibration sources and the data undergo extensive pre and post launch calibration and validation activities before the data are declared operational. Additionally, NOAA/NESDIS center for satellite applications and research maintains an integrated calibration and validation system to continuously monitor and track the performance of the sensors through the mission life cycle. NOAA also co-leads the Global Space-based Inter-Calibration Sytem (GSICS) which is an international collaborative effort initiated in 2005 by the World Meteorological Organization (WMO) and the Coordination Group for Meteorological Satellites (CGMS) to monitor, improve and harmonize the quality of observations from operational weather and environmental satellites of the Global Observing System (GOS). The level 2 geophysical measurements and products also go through extensive verification and validation through comparison of satellite products with surface-based, airborne, and/or space-based observations that are extensively documented and shared with users. This presentation will highlight the calibration activities and the performance of JPSS sensors and products.

How to cite: Kalluri, S. and Cao, C.: Calibration and Validation of Low Earth Orbit Observations From NOAA to Support Global Environmental Monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6427, https://doi.org/10.5194/egusphere-egu24-6427, 2024.

EGU24-6605 | Posters on site | ITS1.15/GI1.3

Utilizing Libya-4 to intercalibrate overlapping sensors in the same sun-synchronous orbit 

David Doelling, Conor Haney, Prathana Khakurel, Rajendra Bhatt, Benjamin Scarino, and Arun Gopalan

The NASA CERES observed SW and LW broadband fluxes are utilized by the climate community for monitoring the Earth’s energy imbalance and for climate model validation. The SNPP and NOAA20 CERES instruments and associated VIIRS imagers were launched into the same 1:30 PM mean local time sun-sun-synchronous orbits as well as the future NOAA22 Libera broadband instrument and VIIRS imager. The overlapping sensor records need to be intercalibrated to enable consistent broadband fluxes and imager cloud retrievals. The overlapping satellites are typically placed a half an orbit apart, thus preventing any simultaneous nadir overpass (SNO) events required for time-matched inter-calibration strategies. A Pseudo Invariant Calibration Site (PICS), such as Libya-4, can provide overlapping sensor radiometric scaling factors without the use of SNOs. 

The clear-sky Libya-4 observed radiances were characterized both spectrally and angularly and corrected for atmospheric effects. The Libya-4 natural variability was found to be consistent across the CERES and VIIRS records. This fact reveals that the sensor onboard calibration anomalies are smaller than the Libya-4 natural variability. By mitigating the Libya-4 natural variability will reduce the radiometric scaling factor uncertainty needed to provide both broadband flux and cloud retrieval continuity across the overlapping sensor records.

How to cite: Doelling, D., Haney, C., Khakurel, P., Bhatt, R., Scarino, B., and Gopalan, A.: Utilizing Libya-4 to intercalibrate overlapping sensors in the same sun-synchronous orbit, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6605, https://doi.org/10.5194/egusphere-egu24-6605, 2024.

EGU24-6849 | Orals | ITS1.15/GI1.3

Validation and simulation of existing and future satellite mid and thermal infrared sensors using a combination of automated validation sites and airborne datasets 

Simon Hook, Bjorn Eng, Gerardo Rivera, Robert Freepartner, Brenna Hatch, William Johnson, Dirk Schüttemeyer, Mary Langsdale, and Martin Wooster

Post-launch calibration and validation over the lifetime of missions is needed to ensure that any long-term variation in an observation, e.g. an area getting hotter, can be unambiguously assigned to a change in the Earth system, rather than a change in calibration. Such activities enable measurements from different satellites to be inter-compared and used seamlessly to create long-term multi-instrument/multi-platform data records, which serve as the basis for large-scale international science investigations into topics with high societal or environmental importance. In order to help address this need we have established a set of automated validation sites where the necessary measurements for validating mid and thermal infrared data from spaceborne and airborne sensors are made every few minutes on a continuous basis. We have also conducted multi-agency airborne campaigns with thermal infrared sensors to develop precursor datasets for future NASA and ESA missions to acquire mid and thermal infrared data as well as characterize variability within the automated validation sties.

We have established automated validation sites at several locations including Lake Tahoe CA/NV, Salton Sea CA and La Crau, France. The Lake Tahoe site was established in 1999, the Salton Sea site was established in 2008 and the La Crau site was established in 2023. Each site has one or more custom-built highly accurate (50mK) radiometers measuring the surface skin temperature. All the measurements are made every few minutes and downloaded hourly via a cellular modem.

Data from the sites have been used to validate numerous satellite instruments including the Advanced Very High Resolution Radiometer (AVHRR) series, the Along Track Scanning Radiometer (ATSR) series, the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), the Landsat series, the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, the Visible Infrared Imaging Radiometer Suite (VIIRS) and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). In all cases the standard products have been validated including the standard radiance at sensor, radiance at surface, surface temperature and surface emissivity products.

Over the last several years NASA and ESA have conducted multiple joint airborne campaigns to obtain data at high spatial and spectral resolutions to simulate future satellite sensors as well as characterize potential validation sites, such as the La Crau validation site. These data are currently being used to simulate the ASI/NASA Surface Biology and Geology (SBG) thermal infrared (TIR) mission, the ESA Land Surface Temperature Monitoring (LSTM) mission and the ISRO/CNES Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment (TRISHNA) mission.

We will present results from the validation of the mid and thermal infrared data using the automated validation sites as well as results from the recent airborne campaigns.

How to cite: Hook, S., Eng, B., Rivera, G., Freepartner, R., Hatch, B., Johnson, W., Schüttemeyer, D., Langsdale, M., and Wooster, M.: Validation and simulation of existing and future satellite mid and thermal infrared sensors using a combination of automated validation sites and airborne datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6849, https://doi.org/10.5194/egusphere-egu24-6849, 2024.

EGU24-9248 | ECS | Posters on site | ITS1.15/GI1.3

Monitoring Metop ASCAT backscatter stability over tropical rainforests 

Clay Harrison, Sebastian Hahn, and Wolfgang Wagner

The Advanced Scatterometer (ASCAT) on-board the series of Metop satellites is a microwave radar instrument operating in C-band (5.255 GHz). ASCAT has been designed to measure wind speed and wind direction over open ocean, but the instrument has also shown its capabilities to observe changes of sea ice extent and surface soil moisture over land. While two Metop satellites (Metop-B launched in September 2012 and Metop-C launched in November 2018) are operational at the moment, the first Metop mission (Metop-A launched in October 2006) has been successfully completed in November 2021. Regular calibration campaigns based on active transponders located in Turkey ensure a continuous quality monitoring, but natural targets (e.g. tropical rainforests) have also been used in the past. Previous analyses have shown that ASCAT is an extremely stable instrument providing high quality Level 1b backscatter products. Any small changes are evaluated in detail and accounted for if necessary. However, the investigation of calibration anomalies detected by active transponders typically takes time. Monitoring natural targets has the advantage that data is continuously available rather than incremental (as is the case when using active transponders) allowing an earlier detection of anomalies. In any case, calibration problems can only be fully resolved retrospectively during a reprocessing of historic data and not entirely in Near Real-Time (NRT).

The upcoming EUMETSAT H SAF ASCAT Surface Soil Moisture (SSM) products sampled at 6.25 km and 12.5 km are divided into three product categories depending on their timeliness: (i) historic data are available as a Climate Data Record (CDR), (ii) a continuous and consistent extension of the CDR, also known as Intermediate CDR (ICDR) and (iii) Near Real- Time (NRT). It is important to note that NRT products could be subject to intentional (e.g. algorithmic updates) or unintentional (e.g. instrument drifts) changes at any given point in time, which would compromise the consistency compared to historic data. Therefore, ICDR products are introduced in order to fill this gap and maintain a consistency as best as possible. For this reason the ICDR products will be distributed with a one-week delay and ASCAT Level 1b backscatter will be continuously monitored using data over tropical rainforests.

In this study we present our strategy to monitor ASCAT Level 1b backscatter stability over tropical rainforests and show results based on historic ASCAT data for all three Metop satellites. We will also discuss the practical implementation of the monitoring methodology and its application as an early-warning system in case of the ASCAT SSM ICDR product. An anomaly detection should trigger a warning for the users until a more in-depth analysis determines whether it is advisable to continue the product distribution or stop. Discovering problems that undermine the coherence between CDR and ICDR products is of critical importance, since applications like drought monitoring or climate studies rely on consistent time series data.

How to cite: Harrison, C., Hahn, S., and Wagner, W.: Monitoring Metop ASCAT backscatter stability over tropical rainforests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9248, https://doi.org/10.5194/egusphere-egu24-9248, 2024.

EGU24-9252 | ECS | Posters on site | ITS1.15/GI1.3

Using hyperspectral sensors on the ground for satellite validation. A focus on the Fluorescence Explorer mission 

Paul Naethe, Andreas Burkart, Matthias Drusch, Dirk Schuettemeyer, Marin Tudoroiu, Roberto Colombo, Mitchell Kennedy, and Tommaso Julitta

The validation of optical satellite data products is a central but challenging component of the space missions. In order to validate the satellite images, ground data is used for reference and allows also the assessment of the associated total uncertainty budget. Overall, when comparing ground data and satellite measurements three main uncertainty sources need to be considered: i) instrument characterisation, ii) algorithm retrieval performances and iii) spatial representativeness. These key components affect the proper comparison of ground measurements with satellite data and, thus, have to be carefully examined. 

JB devices (FloX and RoX) are hyperspectral instruments acquiring optical field data with standardized hardware and routines. They have collected a legacy of data for over half of a decade using a comprehensive and readily implemented open-source data processing chain, considering the individual laboratory characterization of each instrument’s optical performance. Thus, the instruments are capable of providing valuable data products for the purpose of satellite validation. In particular, the FloX (Fluorescence BoX, JB Hyperspectral Devices GmbH) is the first commercially available device for the measurement of solar-induced chlorophyll fluorescence (SIF). The instrument was developed with the support of the scientific community following the specification of the Fluorescence Explorer mission (FLEX) by the European Space Agency (ESA), expected to be launched in 2024. The FloX features a high performing spectrometer (FWHM: 0.3 nm, SSI: 0.15, SNR: 1000) and allows stand-alone measurement of SIF emission at canopy level on the ground. Furthermore, the FloX enables the continuous measurements of spectral down-welling and up-welling radiance in the VIS-NIR range using an additional spectrometer to cover a larger spectral range and allows the automatic computation of reflectance as well as various vegetation indices (VIs). The instrument synchronously acquires upwelling and downwelling radiance during each measurement cycle, automatically optimizes the integration time according to light conditions and acquires the dark current and internal quality flags to ensure high quality data products. In addition to SIF and VIs, the FloX produces time series of high-resolution radiometric parameters, suitable for the investigation of the optical properties from the monitored targets. In the last years over 60 FloX units have been deployed worldwide.

Within a current ESA project, we are investigating the instrument uncertainty sources, with the final aim of defining a preliminary version of the FLEX validation plan. At the same time, currently deployed instruments in 10 location around the world were used to examine the agreement of the ground measurements with available satellite product (i.e. Sentinel-2). This approach reversed the common practice of validating satellite data with ground measurements by using the globally available, standardized L2A products of Sentiel-2 evaluating the conformance of ground-measured data products across a network of standardized instruments. An unprecedented alignment of satellite and ground data was achieved, confirming high validity of data products from the network of automated field spectrometers around the globe.

In summary, in this contribution we provide an overview of how field spectroscopy systems can be used in the framework of specific activities with the purpose of satellite validation.

How to cite: Naethe, P., Burkart, A., Drusch, M., Schuettemeyer, D., Tudoroiu, M., Colombo, R., Kennedy, M., and Julitta, T.: Using hyperspectral sensors on the ground for satellite validation. A focus on the Fluorescence Explorer mission, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9252, https://doi.org/10.5194/egusphere-egu24-9252, 2024.

EGU24-10447 | Orals | ITS1.15/GI1.3

GBOV (Copernicus Ground-Based Observation for Validation) service: latest product updates and evolutions for EO data Cal/Val 

Christophe Lerebourg, Rémi Grousset, Thomas Vidal, Gabriele Bai, Marco Clerici, Nadine Gobron, Jadu Dash, Somnath Bar, Finn James, Luke Brown, Ernesto Lopez-baeza, Ana Perez-hoyos, Darren Ghent, Jasdeep Anand, Jan-Peter Muller, and Rui Song

GBOV (Copernicus Ground-Based Observation for Validation), is an element of CLMS (Copernicus Land Monitoring Service). Its initial purpose was to support yearly validation effort of core CLMS product (TOC-R, Albedo, LAI, FAPAR, FCOVER, SSM and LST), five of whom are listed among GCOS Essential Climate Variables (ECV). GBOV has however reached a much larger community with about 1200 users, including ESA optical MPC. There is a large variety of ground data publicly available through numerous networks including ICOS, BSRN, NEON, TERN, SurfRad … For GBOV service, the choice was made to focus on data from permanent deployment, i.e. long-term datasets, rather than field campaign data. Indeed, this reduces the number of available ground variables, but long-term deployments ensure the maximum of ground to satellite data matchups as well as measurement protocols consistency.

GBOV provides ground measurement (the so-called “Reference Measurements”) to the community, but its fundamental interest is that up-scaling procedures are applied to these ground measurements in order to provide ARVD (Analysis Ready Validation Data) to the community, the so-called “Land Products”. GBOV service is freely accessible on https://land.copernicus.eu/global/gbov and provides data over 112 sites. Available ground data variables include: Top of Canopy Reflectance (ToC-R), surface albedo, Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Available Radiation (FAPAR), Fraction of Covered ground (FCover), Surface Soil Moisture (SSM) and Land Surface Temperature (LST).

The networks providing GBOV initial input data are unfortunately not evenly distributed. In an attempt to reduce the thematic and geographical gap, GBOV is developing its own network as part of collaboration with the existing networks. In GOBV phase 1, six ground stations have been upgraded with additional instrumentation. In GBOV phase 2, a ground station has been deployed in August 2023 on Fuji Hokuroku research station in Japan for vegetation variables monitoring. This is part of a collaboration with NIES (National Institute of Environmental Studies). In 2024, a vegetation station will be installed over Fontainebleau research station (France) as part of a GBOV/ICOS collaboration. Fuji Hokuroku and Litchfield (TERN network Australia) will receive a GBOV LST station in 2024.

Over the past year, several updates have been implemented in GBOV database to better respond to CLMS and general users requirements. This includes improved uncertainty estimates for vegetation products, improved procedure for Soil Moisture and LST products. More effort is being made for the end-to-end uncertainty budget computation.

This presentation will emphasis product status and recent product evolutions.

How to cite: Lerebourg, C., Grousset, R., Vidal, T., Bai, G., Clerici, M., Gobron, N., Dash, J., Bar, S., James, F., Brown, L., Lopez-baeza, E., Perez-hoyos, A., Ghent, D., Anand, J., Muller, J.-P., and Song, R.: GBOV (Copernicus Ground-Based Observation for Validation) service: latest product updates and evolutions for EO data Cal/Val, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10447, https://doi.org/10.5194/egusphere-egu24-10447, 2024.

EGU24-10864 | Orals | ITS1.15/GI1.3

Calibration and Validation Activities in the Context of the 2023 GABONX Airborne SAR Campaign for Tropical Forest Height and Change Analysis over Gabon 

Marc Jaeger, Irena Hajnsek, Matteo Pardini, Roman Guliaev, Kostas Papathanassiou, Markus Limbach, Martin Keller, Andreas Reigber, Temilola Fatoyinbo, Marc Simard, Michele Hofton, Bryan Blair, Ralph Dubayah, Aboubakar Mambimba Ndjoungui, Larissa Mengue, Ulrich Vianney Mpiga Assele, and Tania Casal

Tropical forests are of great ecological and climatological importance. Although they only cover about 6% of Earth’s surface, they are home to approx. 50% of the world’s animal and plant species. Their trees store 50% more carbon than trees outside the tropics. At the same time, they are one of the most endangered ecosystems on Earth: about 6 million of hectares per year are felled for timber or cleared for farming. Compared to the other components of the carbon cycle (i.e. the ocean as a sink and the burning of fossil fuels as a source), the uncertainties in the local land carbon stocks and the carbon fluxes are particularly large. This is especially true for tropical forests: more than 98% of the carbon flux generated by changes in land-use may be due to tropical deforestation, which converts carbon stored as biomass into emissions.

In this context, the AfriSAR 2015/16 campaign, supported by ESA, was carried out over four forest sites in Gabon by ONERA (July 2015) during the dry season and by DLR (February 2016) during the wet season. From the data collected the innovative techniques applied to estimate forest height and biomass could be improved significantly and are summarized in a special issue ‘Forest Structure Estimation in Remote Sensing’ of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

The motivation of the AfriSAR campaign was to acquire demonstration data for the soon to be launched ESA BIOMASS mission, that was selected as the 7th Earth Explorer mission in May 2013 in order to meet the pressing need for information on tropical carbon sinks and sources by providing estimates of forest height and biomass. AfriSAR focused on African tropical and savannah forest types (with biomass in the 100-300 t/ha range) and complements previous ESA campaigns over Indonesian and Amazonian forest types in 2004 (INDREX-II) and 2009 (TropiSAR).

The present contribution concerns the GABONX campaign, the ESA supported successor to AfriSAR, which took place in May to July 2023. GABONX aims to detect and quantify changes that have occurred since the DLR acquisitions in February 2016. To this end, DLR’s F-SAR sensor acquired interferometric stacks of fully polarimetric L- and P-Band data over the same forest sites in the same flight geometry as in 2016. The results presented give an overview of campaign activities with particular emphasis on the calibration of the SAR instrument as well as the validation of forest parameters derived from polarimetric interferometry. The SAR sensor calibration is based on an innovative approach that leverages state-of-the-art EM simulation to accurately characterize the 5m trihedral reference target deployed for the campaign in Gabon. The validation of derived forest parameters uses lidar measurements obtained in the time frame of the GABONX campaign by NASA’s LVIS sensor. As an outlook, further collaborative calibration and validation activities will hopefully include the cross-calibration of DLR’s F-SAR and NASA’s UAVSAR, which is set to acquire L- and P-Band data over the GABONX sites in 2024.

How to cite: Jaeger, M., Hajnsek, I., Pardini, M., Guliaev, R., Papathanassiou, K., Limbach, M., Keller, M., Reigber, A., Fatoyinbo, T., Simard, M., Hofton, M., Blair, B., Dubayah, R., Mambimba Ndjoungui, A., Mengue, L., Vianney Mpiga Assele, U., and Casal, T.: Calibration and Validation Activities in the Context of the 2023 GABONX Airborne SAR Campaign for Tropical Forest Height and Change Analysis over Gabon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10864, https://doi.org/10.5194/egusphere-egu24-10864, 2024.

EGU24-11905 | ECS | Orals | ITS1.15/GI1.3

Multi-angular airborne observations for simulating thermal directionality at the satellite scale 

Mary Langsdale, Martin Wooster, Dirk Schuettemeyer, Simon Hook, Callum Middleton, Mark Grosvenor, Bjorn Eng, Roberto Colombo, Franco Miglietta, Lorenzo Genesio, Jose Sobrino, Gerardo Rivera, Daniel Beeden, and William Jay

Viewing and illumination geometry are known to have significant impacts on remotely sensed retrieval of land surface temperature (LST), particularly for heterogeneous regions with mixed components. Disregarding directional effects can have significant impacts on both the stability and accuracy of satellite datasets, for example when harmonising datasets from different sensors with different viewing geometries. 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. With LST an Essential Climate Variable and the development of high resolution future thermal infrared missions (e.g. LSTM, SBG, TRISHNA), it is essential that further work is done to redress this.

With this in mind, a joint NASA-ESA airborne campaign focused on directionality was conducted in Italy in the summer of 2023, led by the National Centre for Earth Observation at King’s College London. This campaign involved concurrent acquisition across longwave infrared (LWIR) wavelengths at both nadir and off-nadir viewing angles through the deployment of two aircraft flying simultaneously, each equipped with state-of-the-art LWIR hyperspectral instrumentation. Data was collected to enable simulation of angular effects at the satellite scale over both agricultural and urban surfaces, with the aim of understanding and potentially developing adjustments for wide view angle satellite-based LST retrievals and remotely sensed evapotranspiration estimates. In-situ observations were collected additionally to enable accuracy assessment of the airborne datasets.

This presentation first details the airborne campaign, including the unique and novel data collection strategies and design modifications to enable evaluation of directional effects for thermal satellites. Preliminary results from the campaign are then presented as well as plans for further analysis related to future satellite thermal missions. 

How to cite: Langsdale, M., Wooster, M., Schuettemeyer, D., Hook, S., Middleton, C., Grosvenor, M., Eng, B., Colombo, R., Miglietta, F., Genesio, L., Sobrino, J., Rivera, G., Beeden, D., and Jay, W.: Multi-angular airborne observations for simulating thermal directionality at the satellite scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11905, https://doi.org/10.5194/egusphere-egu24-11905, 2024.

EGU24-12167 | Posters on site | ITS1.15/GI1.3

The Cross-track Infrared Sounder Level 1B Product: NASA’s Accurate and Stable Infrared Hyperspectral Radiance Record 

David Tobin, Joe Taylor, Larrabee Strow, Hank Revercomb, Graeme Martin, Sergio DeSouza-Machado, Jess Braun, Daniel DeSlover, Ray Garcia, Michelle Loveless, Robert Knuteson, Howard Motteler, Greg Quinn, and William Roberts

The Cross-track Infrared Sounder (CrIS) is an infrared Fourier Transform Spectrometer onboard the Suomi-NPP (SNPP), JPSS-1, and JPSS-2 satellites. The CrIS instrument was designed to provide an optimum combination of optical performance, high radiometric accuracy, and compact packaging. While CrIS was developed primarily as a temperature and water vapor profiling instrument for weather forecasting, its high accuracy and extensive information about trace gases, clouds, dust, and surface properties make it a powerful tool for climate applications.

The goal of the NASA CrIS Level 1B project is to support NASA climate research by providing a climate quality Level 1B (geolocation and calibration) algorithm and create long-term measurement records for the CrIS instruments currently on-orbit on the SNPP, JPSS-1, and JPSS-2 satellites, and for those to be launched on JPSS-3 and JPSS-4. The long-term objectives of the project include:

  • Create well-documented and transparent software that produces climate quality CrIS Level 1B data to continue or improve on EOS-like data records, and to provide this software and associated documentation to the NASA Sounder Science Investigator-led Processing System (SIPS).
  • Provide long-term monitoring and validation of the CrIS Level 1B data record from SNPP and JPSS-1 through JPSS-4, and long-term maintenance and refinement of the Level 1B software to enable full mission reprocessing as often as needed.
  • Provide a homogeneous radiance product across all CrIS sensors through the end of the CrIS series lifetime, with rigorous radiance uncertainty estimates.
  • Develop and support of the CrIS/VIIRS IMG software and datasets, which provide a subset of Visible Infrared Imaging Radiometer Suite (VIIRS) products that are co-located to the CrIS footprints.
  • Develop and support of the Climate Hyperspectral Infrared Product (CHIRP) for the AIRS and CrIS sounders. The CHIRP product converts the parent instrument's radiances to a common Spectral Response Function (SRF) and removes inter-satellite biases, providing a consistent inter-satellite radiance record.

The NASA CrIS products are available via the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) at https://www.earthdata.nasa.gov/sensors/cris. This presentation will include (1) an overview of the NASA Level 1B calibration algorithm and product, (2) example post-launch calibration/validation results demonstrating the accuracy and stability of the CrIS Level 1B data, and (3) example science results.

How to cite: Tobin, D., Taylor, J., Strow, L., Revercomb, H., Martin, G., DeSouza-Machado, S., Braun, J., DeSlover, D., Garcia, R., Loveless, M., Knuteson, R., Motteler, H., Quinn, G., and Roberts, W.: The Cross-track Infrared Sounder Level 1B Product: NASA’s Accurate and Stable Infrared Hyperspectral Radiance Record, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12167, https://doi.org/10.5194/egusphere-egu24-12167, 2024.

EGU24-12346 | Posters on site | ITS1.15/GI1.3

Multi-frequency SAR measurements to advance snow water equivalent algorithm development 

Chris Derksen, Richard Kelly, Benoit Montpetit, Julien Meloche, Vincent Vionnet, Nicolas Leroux, Courtney Bayer, Aaron Thompson, and Anna Wendleder

Snow mass (commonly expressed as snow water equivalent – SWE) is the only component of the water cycle without a dedicated Earth Observation mission. A number of missions currently under development, however, will provide previously unachieved coverage and resolution at frequencies ideal for retrieving SWE. These missions include a Ku-band synthetic aperture radar (SAR) mission (presently named the ‘Terrestrial Snow Mass Mission’ – TSMM) under development in Canada, and two Copernicus Expansion Missions: the Radar Observing System for Europe at L-band (ROSE-L) and the Copernicus Imaging Microwave Radiometer (CIMR). Airborne measurements are required to support SWE algorithm development for all three of these missions. In this presentation, we will present analysis of measurements from the ‘CryoSAR’ instrument, an InSAR capable L- (1.3 GHz) and Ku-band (13.5 GHz) SAR installed on a Cessna-208 aircraft.

A time series of CryoSAR measurements were acquired over open, forested, and lake sites in central Ontario, Canada during the 2022/23 winter season. These measurements were used to evaluate a new computationally efficient SWE retrieval technique based on the use of physical snow model simulations to initialize snow microstructure information in forward model simulations for prediction of snow volume scattering at Ku-band. A primary challenge is the treatment of different layers within the snowpack. We show that a k-means classifier based on snow layer properties can effectively reduce a complex snowpack to three ‘radar-relevant’ layers which conserve SWE but simplify calculation of the snow volume radar extinction coefficient. Estimation of the background contribution is based on soil information derived from lower frequency radar measurements (X-, C-, and L-band). Our collective analysis of satellite and airborne radar observations, snow physical modeling, and SWE retrievals is facilitated by the recently developed TSMM simulator, which incorporates outputs from the Environment and Climate Change Canada land surface prediction system to produce synthetic dual-frequency (13.5 and 17.25 GHz) Ku-band radar data products.

The acquisition of multi-frequency airborne radar measurements from the CryoSAR, and the integration of these observation into the TSMM simulator, provides a fundamental new capability to provide pre-cursor datasets to advance SWE algorithms in preparation for upcoming missions.

How to cite: Derksen, C., Kelly, R., Montpetit, B., Meloche, J., Vionnet, V., Leroux, N., Bayer, C., Thompson, A., and Wendleder, A.: Multi-frequency SAR measurements to advance snow water equivalent algorithm development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12346, https://doi.org/10.5194/egusphere-egu24-12346, 2024.

EGU24-12428 | Orals | ITS1.15/GI1.3

ESA/NASA Quality Assurance Framework for Earth Observation Products 

Samuel Hunt, Clément Albinet, Jaime Nickeson, Batuhan Osmanoglu, Alfreda Hall, Guoqing Lin, Leonardo De Laurentiis, Philippe Goryl, Frederick Policelli, Dana Ostrenga, and Nigel Fox

Across the broad potential user base for Earth Observation (EO) data, confidence in the quality of the available products is vital, particularly for users requiring quantitative measured outputs they can rely on. Particularly as the commercial EO sector rapidly expands, however, it is an increasing challenge for the user community to discern between the wide variety of product offerings in a reliable manner, especially in terms of product quality.

 

In response to this ESA and NASA, through their Joint Program Planning Group (JPPG) Subgroup, have developed a common EO product Quality Assurance (QA) Framework to provide comprehensive assessments of product quality. The evaluation is primarily aimed at verifying that the data has achieved its claimed performance levels, and, reviews the extent to which the products have been prepared following community best practice in a manner that is “fit for purpose”. A Cal/Val maturity matrix provides a high-level colour-coded a simple summary of the quality assessment results for users. The matrix contains a column for each section of analysis (e.g., metrology), and cells for each subsection of analysis (e.g., sensor calibration). Subsection grades are indicated by the colour of the respective grid cell, which are defined in the key.

 

Both ESA and NASA have on-going activities supporting the procurement of commercial EO data that make use of the joint QA Framework – to ensure decisions on data acquisition are made with confidence. On the ESA side, the Earthnet Data Assessment Project (EDAP) project performs data assessments on EO missions in optical, atmospheric and SAR domains. Similarly, the NASA Earth Science Division (ESD) Commercial Smallsat Data Acquisition (CSDA) Program, completed a pilot study in 2020, and has since entered sustainment use phase for some of the commercial data sets.

 

In this presentation the joint ESA/NASA QA Framework is described, with some examples of its application to commercial EO products.

How to cite: Hunt, S., Albinet, C., Nickeson, J., Osmanoglu, B., Hall, A., Lin, G., De Laurentiis, L., Goryl, P., Policelli, F., Ostrenga, D., and Fox, N.: ESA/NASA Quality Assurance Framework for Earth Observation Products, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12428, https://doi.org/10.5194/egusphere-egu24-12428, 2024.

EGU24-12444 | Posters on site | ITS1.15/GI1.3

Validation of the Radiometric Scales of GLAMR and Grande 

Julia Barsi, Brendan McAndrew, Boryana Efremova, Andrei Sushkov, Nathan Kelley, and Brian Cairns

The NASA/GSFC Code 618 Calibration Laboratories include the Radiometric Calibration Lab (RCL) and the Goddard Laser for Absolute Measurement of Radiance (GLAMR) facility.  Both have large integrating sphere sources with NIST-traceable radiometric calibration.

The workhorse of the RCL is a 1-m integrating sphere with a 25.4-cm port, called Grande, illuminated by nine 150W halogen lamps, providing a broad-band radiance source (300 nm to 2400 nm).  The radiometric calibration of Grande is NIST-traceable through calibrated FEL lamps and a transfer spectroradiometer.

GLAMR is a tunable-laser based system fiber coupled to a large integrating sphere, providing a full-aperture, uniform, monochromatic radiance source. The GLAMR system has two spheres; the one used for this study was a 50-cm sphere with a 20-cm port.  The radiometric calibration is NIST-traceable through a set of calibrated transfer radiometers.

The Research Scanning Polarimeter was calibrated by both sources in 2023.  There was a 3% discrepancy in the absolute radiometric calibration between the two systems.  In order to investigate the discrepancy, a full wavelength scan of the GLAMR system was run, with the Grande spectroradiometer in front of the GLAMR sphere, along with two other spectoradiometers that are used to monitor Grande in real time.  The analysis of this dataset should establish the source of the discrepancy between the two systems and bring the two radiometric calibration systems, Grande and GLAMR, within the combined uncertainties of the methods and instruments.

How to cite: Barsi, J., McAndrew, B., Efremova, B., Sushkov, A., Kelley, N., and Cairns, B.: Validation of the Radiometric Scales of GLAMR and Grande, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12444, https://doi.org/10.5194/egusphere-egu24-12444, 2024.

EGU24-12761 | Posters on site | ITS1.15/GI1.3

Simulated Sea Surface Salinity Data from a 1/48° Ocean Model  

Frederick Bingham, Séverine Fournier, Susannah Brodnitz, Akiko Hayashi, Mikael Kuusela, Elizabeth Westbrook, Karly Carlin, Cristina González-Haro, and Verónica González-Gambau

In order to study the validation process for sea surface salinity (SSS) we have generated a year (November 2011- October 2012) of simulated satellite and in situ “ground truth” data. This was done using the ECCO (Estimating the Circulation and Climate of the Oceans) 1/48° simulation, the highest resolution ocean model currently available. The ground tracks of three satellites, Aquarius, SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) were extracted and used to sample the model with a gaussian weighting similar to that of the satellites. This produced simulated level 2 (L2) data. Simulated level 3 (L3) data were then produced by averaging L2 data onto a regular grid. The model was sampled to produce simulated Argo and tropical mooring SSS datasets. The Argo data were combined into a simulated gridded monthly 1° Argo product. The simulated data produced from this effort have been used to study sampling errors, matchups, subfootprint variability and the validation process for SSS at L2 and L3.

How to cite: Bingham, F., Fournier, S., Brodnitz, S., Hayashi, A., Kuusela, M., Westbrook, E., Carlin, K., González-Haro, C., and González-Gambau, V.: Simulated Sea Surface Salinity Data from a 1/48° Ocean Model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12761, https://doi.org/10.5194/egusphere-egu24-12761, 2024.

EGU24-12907 | Orals | ITS1.15/GI1.3

Advancing Sea Surface Salinity R&D: The Pi-MEP Initiative for Satellite Salinity Data Validation and Exploitation 

Sébastien Guimbard, Nicolas Reul, Roberto sabia, Raul Díez-García, Sylvain Herlédan, Ziad El Khoury Hanna, Tong Lee, Julian Schanze, Frederic Bingham, and Klaus Scipal

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity (https://www.salinity-pimep.org/) is an initiative originally meant to support and widen the uptake of ESA Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Since its beginning in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data validation, supporting also process studies over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: 1) gathering all the data required to exploit satellite sea surface salinity data, 2) systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and 3) providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. 

Over the years, the Pi-MEP has become a reference hub for the validation of satellite sea surface salinity missions products (SMOS, Aquarius, SMAP), being collocated with an extensive in situ database (e.g. Argo float, thermosalinographs, moorings, surface drifters, saildrones and equipped marine mammals) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc. ). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools of the platform are described in detail in Guimbard et al., 2021. Several dedicated scientific case studies involving satellite SSS data are also systematically investigated by the platform, such as major river plumes monitoring, mesoscale signatures in boundary currents, or spatio-temporal evolution in challenging regions (high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific).

Since 2019, a partnership to sustain the Salinity Pi-MEP project has been agreed between ESA and NASA, encompassing R&D and validation over the entire set of satellite salinity sensors. The two Agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from dedicated in-situ field campaigns (e.g., SPURS, EUREC4A).

In this talk, we will showcase the main results of the latest phase of the project, with the recent distinctive focus on the representation errors characterization of the various satellite salinity missions. 

Guimbard, S.; Reul, N.; Sabia, R.; Herlédan, S.; Khoury Hanna, Z.E.; Piollé, J.-F.; Paul, F.; Lee, T.; Schanze, J.J.; Bingham, F.M.; Le Vine, D.; Vinogradova-Shiffer, N.; Mecklenburg, S.; Scipal, K. & Laur, H. (2021) The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data Remote Sensing 13(22):4600 https://doi.org/10.3390/rs13224600

How to cite: Guimbard, S., Reul, N., sabia, R., Díez-García, R., Herlédan, S., El Khoury Hanna, Z., Lee, T., Schanze, J., Bingham, F., and Scipal, K.: Advancing Sea Surface Salinity R&D: The Pi-MEP Initiative for Satellite Salinity Data Validation and Exploitation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12907, https://doi.org/10.5194/egusphere-egu24-12907, 2024.

EGU24-13262 | Orals | ITS1.15/GI1.3

Intercomparison of Landsat OLI and Sentinel 2 MSI performance 

Esad Micijevic, Cody Anderson, Julia Barsi, Rajagopalan Rengarajan, MD. Obaidul Haque, and Joshua Mann

For Landsat 8 and Landsat 9 (L8 and L9), the radiometric stability of the Operational Land Imager (OLI) is monitored using two solar diffusers, three sets of stimulation lamps, and regular lunar collects. Consistent response to the multiple calibrators provides high confidence in the radiometric characterization of the imagers over time and calibration parameters needed to maintain the stability of image products. After 11 years on orbit, all spectral bands in Landsat 8 OLI are stable within 1.5%, while Landsat 9 OLI degradation over its 2.5 years of life remains within 0.3% across all bands.

The MultiSpectral Instruments (MSIs) onboard Sentinel 2A and 2B (S2A and S2B) satellites were designed with 8 similar spectral bands (out of 13) as the OLIs, which created opportunities to combine data from both types of instruments and obtain higher temporal frequency of Earth observations. To ensure proper interoperability among the different instruments, they need to be radiometrically cross-calibrated and consistently georeferenced. We use coincident acquisitions over Pseudo Invariant Calibration Sites (PICS) to monitor the radiometric calibration consistency and stability of the instruments over time. For geometry, Landsat and Sentinel 2 images acquired within a month of each other over the same ground targets were used to assess the co-registration accuracy between the sensor products.

Our results show a general agreement in radiometry of all four instruments over their lifetimes to within 1%. Following the launch of MSI instruments, the initial geometric co-registration assessment between the MSI instruments and the Landsat 8 OLI instrument showed more than 12 m Circular Error (CE90), larger than a Sentinel 2, 10m, pixel. To further improve co-registration and, thus, interoperability of the four instruments, Landsat Collection-2 products use a geometric reference that was harmonized using the Global Reference Image (GRI). The GRI is a dataset consisting of geometrically refined Sentinel 2 images with an absolute accuracy better than 6 m globally. After adopting a common geometric reference in the generation of Landsat and Sentinel 2 products, our assessment of geometric co-registration of the Landsat and Sentinel terrain-corrected products shows a CE90 error of less than 6 m.

Multiple efforts have also been made to validate the accuracy of surface reflectance products from both Landsat and Sentinel 2. In-situ measurements have been made during overpasses of L8, L9, S2A, and S2B using various methods. These measurements also show consistency between all the sensors and can also be used for other missions.

How to cite: Micijevic, E., Anderson, C., Barsi, J., Rengarajan, R., Haque, MD. O., and Mann, J.: Intercomparison of Landsat OLI and Sentinel 2 MSI performance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13262, https://doi.org/10.5194/egusphere-egu24-13262, 2024.

The fifth FengYun satellite (FY-3E) was successfully launched into orbit on 5 July, 2021. It carries the third-generation microwave temperature sounder (MWTS-III) and the second-generation microwave humidity sounder (MWHS-II), providing the global atmospheric temperature and humidity measurements. It is important to assess the in-orbit performance of MWTS-III and MWHS-II and understand their calibration accuracy before applications in numerical weather prediction. Since atmospheric profiles from Global Positioning System (GPS) radio occultation (RO) are stable and accurate, they are very valuable for assessing the microwave sounder performance in orbit as demonstrated by many previous studies. This study aims at quantifying the calibration biases of FY-3E MWTS-III and MWHS-II sounding channels of interest using the collocated GPS RO data during January 1st to September 30th, 2023. The MWTS-III channels inherit most of the second-generation MWTS features and have frequencies near the oxygen absorption band (50-60 GHz), and channels at the frequencies of 23.8 and 31.4 GHz were added. Considering that the GPS RO data are more stable and accurate in the mid-troposphere to lower stratosphere and the atmospheric radiative transfer model is accurate in the upper troposphere and lower stratosphere, the mid- to upper-level sounding channels of the MWTS-III, i.e. channels 7-14 are of interest in this study. The cross-tracking scanning instrument MWHS-II provides 15 channels, at frequencies near 89, 118.75, 150 and 183.31 GHz. Of interest to this study are MWHS-II channels 2-6 and 11-15. Using the collocated COSMIC RO data in clear-sky conditions as inputs to the Advanced Radiative Transfer Modeling System (ARMS), brightness temperatures and viewing angles are simulated for FY-3E MWTS-III and MWHS-II. The collocation criterion between the radio-occultation data and the MWTS-III/MWHS-II measurements is defined such that the spatial and temporal difference is less than 50 km and 3 h, respectively. To simulate more accurate bright temperatures, the RO data should be obtained under clear sky conditions over oceans. To determine the clear sky for MWTS-III, the cloud liquid water path algorithm developed by Grody et al. (2001) was used for MWTS-III. While for MWHS-II, the cloud detection algorithm developed by Hou et al. (2019) was used. The initial analysis shows that for the upper sounding channels, the mean biases of the MWTS-III observations relative to the GPS RO simulations are negative for channels 7-8 and 10-13, with absolute values <2 K, and positive for channels 9 and 14, with values <1 K. For the MWHS, the mean biases in brightness temperature are negative for channels 2–6, with absolute values < 2 K and relatively small standard deviations. The mean biases are also negative for MWHS-II channels 11–15 with absolute values <1 K, but with relatively large standard deviations. The biases of both MWTS-III and MWHS-II show scan-angle dependence and are almost symmetrical across the scan line. The long-term mean bias shows only a weak dependence on latitude, which suggests that biases do not vary systematically with brightness temperature. The evaluation results indicate very good prospects for the assimilation application of FY-3E microwave sounding data.

How to cite: Hou, X. and Han, Y.: Verification of FengYun-3E MWTS and MWHS Calibration Accuracy Using GPS Radio Occultation Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13926, https://doi.org/10.5194/egusphere-egu24-13926, 2024.

EGU24-14759 | Orals | ITS1.15/GI1.3

Sea Surface Salinity in the Arctic Ocean - Results from the NASA SASSIE Field Campaign, Calibration-Validation of Satellite Observations, and Data Outreach 

Julian Schanze, Peter Gaube, Jessica Anderson, Frederick Bingham, Kyla Drushka, Sebastien Guimbard, Tong Lee, Nicolas Reul, Roberto Sabia, and Elizabeth Westbrook and the NASA Salinity and Stratification at the Sea Ice Edge Field Campaign Team


The National Aeronautical and Space Administration (NASA) Salinity and Stratification at the Sea Ice Edge (SASSIE) field campaign took place in the Arctic Ocean between August and October of 2022. The scientific aim is to understand the relationship between both haline and thermal stratification and sea-ice advance, and to test the hypothesis that a significant fresh layer at the surface can accelerate the formation of sea ice by limiting convective processes. With the advent of satellite-derived sea surface salinity (SSS) observations from SMOS, Aquarius/SAC-D, and SMAP in the last decade, such observations could provide insights into sea ice formation rates and extent. With the sensitivity of L-Band radiometry for SSS being low at the temperatures prevalent in the Arctic Ocean (-2°C – 5°C) and additional problems with sea ice contamination in the satellite footprint, careful calibration and validation is needed to determine the quality of satellite-derived SSS in this region, particularly near the ice-edge.


Here, we present three components that have resulted from this NASA Field Campaign.


1.) An overview of data gathered is presented, including an unprecedented density of near-surface salinity measurements from diverse platforms. These were measured during a one-month shipboard hydrographic and atmospheric survey in the Beaufort Sea and include continuous observations at radiometric depth (1-2cm) from the salinity snake instrument, more than 3000 high-resolution uCTD profiles, and air-sea flux measurements. Concurrent with the shipborne observations, an airborne campaign to observe ocean salinity, temperature, and other parameters from a low-flying aircraft was performed. Finally, we discuss the deployment and results of autonomous assets, buoys, and floats that were able to observe both the melt season and the sea ice advance. We combine these in situ observations with satellite SSS data to examine the effects of stratification on ocean dynamics in the Beaufort Sea near the sea ice edge and discuss the quality of SSS data in this region.


2.) NASA Physical Oceanography Programs has affirmed its commitment to Open Science and reproducibility of results. For the SASSIE field campaign, we have created a unique web portal that showcases the datasets gathered during the campaign, giving video overviews as well as written summaries of the available data and motivations for their collection. We have also created repositories that contain processing code used in the creation of these datasets, as well as example processing scripts in the form of Jupyter notebooks, which allow end users to execute a live download of datasets from NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) as well as processing and plotting these data in Python.


3.) We show the active integration of these tools into the salinity pilot mission exploitation platform (Salinity Pi-MEP), operated by the European Space Agency (ESR) in collaboration with NASA. We demonstrate how such an integration leverages access to other datasets, and facilitates calibration-validation efforts for Level-2 and Level-3 satellite data from multiple satellites. 

How to cite: Schanze, J., Gaube, P., Anderson, J., Bingham, F., Drushka, K., Guimbard, S., Lee, T., Reul, N., Sabia, R., and Westbrook, E. and the NASA Salinity and Stratification at the Sea Ice Edge Field Campaign Team: Sea Surface Salinity in the Arctic Ocean - Results from the NASA SASSIE Field Campaign, Calibration-Validation of Satellite Observations, and Data Outreach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14759, https://doi.org/10.5194/egusphere-egu24-14759, 2024.

EGU24-14920 | Posters on site | ITS1.15/GI1.3

Sentinel-3 Land Ice Thematic Product: Evaluation of Greenland surface elevation and elevation change.  

Sebastian B. Simonsen, Louise Sandberg Sørensen, Stine K. Rose, and Jérémie Aublanc

The Sentinel-3 satellite series, developed by the European Space Agency as part of the Copernicus Programme, currently comprises two satellites, Sentinel-3A and Sentinel-3B, launched on 16th February 2016 and 25th April 2018, respectively. These satellites are equipped with various instruments, including a radar altimeter, enabling them to conduct operational topography measurements of the Earth's surface. The primary objective of the Sentinel-3 constellation concerning land ice is to provide highly accurate topographic measurements of polar ice sheets. This data is crucial in supporting, e.g., ice sheet mass balance studies. Unlike previous missions that utilized conventional pulse-limited altimeters, Sentinel-3 employs an advanced SAR Radar ALtimeter (SRAL) with delay-doppler capabilities, resulting in significantly enhanced spatial resolution for surface topography measurements. The Sentinel-3 Mission Performance Cluster (MPC) is tasked with monitoring the stability and accuracy of the mission. Here, we report on the latest findings on the Greenland ice sheet.

ESA and the MPC recently developed a specialized delay-Doppler Level-2 processing chain (thematic products) over three dedicated surfaces: Inland Waters, sea ice, and Land Ice. For land ice, delay-Doppler processing with an extended window has been implemented to enhance the coverage of the ice sheet margins. With the improved coverage at the ice sheet margins, we can now access and monitor the fastest-changing regions of the Greenland ice sheet. Hence, the essential climate variable surface elevation change (SEC) can directly be derived solely from Sentinel-3 and, due to the operational concept of the Sentinel program, is ensured to provide continuous observations until at least 2030. Here, we present the latest SEC results based on the land ice thematic product and compare it to the other polar altimetric missions (CryoSat-2 and ICESat-2) to provide a benchmark for the performance of the Sentinel-3 mission for the time to come with less abundant polar radar altimeters.   

How to cite: Simonsen, S. B., Sandberg Sørensen, L., Rose, S. K., and Aublanc, J.: Sentinel-3 Land Ice Thematic Product: Evaluation of Greenland surface elevation and elevation change. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14920, https://doi.org/10.5194/egusphere-egu24-14920, 2024.

EGU24-15137 | Orals | ITS1.15/GI1.3

Utilizing surface-based observations from the Micro Pulse Lidar Network (MPLNET) for validation of space-based satellite missions 

Jasper Lewis, James Campbell, Erica Dolinar, Simone Lolli, Sebastian Stewart, Larry Belcher, and Ellsworth Welton

Starting with the Lidar In-Space Technology Experiment (LITE) in 1994, spaceborne lidars have provided highly detailed global views of the vertical structure of clouds and aerosols. And since that time, surface-based lidar, well as aircraft lidar, have been used for validation through correlative measurements. While the validation of space-based lidar systems by surface-based lidar observations is not straightforward, protocols for doing so are well-established and have shown good agreement in many instances.     

The Micro Pulse Lidar Network (MPLNET) is a federated, global network of Micro Pulse Lidar systems deployed worldwide to measure aerosol and cloud vertical structure, and mixed layer heights. The data have been collected continuously, day and night, for more than 20 years from sites around the world with multiple sites containing 5+ or 10+ years of data. MPLNET is also a contributing network to the World Meteorological Organization (WMO) Global Atmospheric Watch (GAW) Aerosol Lidar Observation Network (GALION). The use of common instrumentation and processing algorithms within MPLNET allow for direct comparisons between sites. Thus, long-term MPLNET measurements can be used to verify the fidelity of geophysical parameters measured throughout the lifetime of individual satellite missions (e.g. CALIPSO, CATS, EarthCARE, CALIGOLA, and AOS) and provide a metric for intercomparisons between different space-based lidar missions when gaps between satellite missions occur.

In this presentation, we use multiple years of comparisons between MPLNET and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) flown aboard CALIPSO. For these comparisons, we use newly developed Level 3 MPLNET products consisting of monthly, diurnal statistics for cloud and aerosol retrievals covering a representative range of conditions and locations. Furthermore, we compare top-of-the-atmosphere cirrus cloud radiative forcing derived from these two complementary platforms. Finally, using results from an upcoming validation rehearsal, we demonstrate how these procedures will be utilized during the EarthCARE mission, scheduled to launch in May 2024.    

How to cite: Lewis, J., Campbell, J., Dolinar, E., Lolli, S., Stewart, S., Belcher, L., and Welton, E.: Utilizing surface-based observations from the Micro Pulse Lidar Network (MPLNET) for validation of space-based satellite missions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15137, https://doi.org/10.5194/egusphere-egu24-15137, 2024.

Fundamental climate data records (FCDRs) play a vital role in monitoring climate change. In this article, we develop a spaceborne passive microwave-based FCDR byrecalibrating the Advanced Microwave Scanning Radiometerfor Earth Observing System (AMSR-E) on the Aqua satellite,the microwave radiometer imager (MWRI) onboard the FengYun-3B (FY3B) satellite, and the Advanced Microwave ScanningRadiometer-2 (AMSR2) onboard the JAXA’s Global ChangeObservation Mission first-Water (GCOM-W1) satellite. Beforerecalibration, it is found that AMSR-E and AMSR2 observations are stable over time, but MWRI drifted colder beforeMay 2015 and had nonnegligible errors in geolocation formost channels. In addition, intersensor differences of brightnesstemperatures (TBs) are as large as 5–10 K. To improve dataconsistency and continuity, several intersensor calibration methods are applied by using AMSR2 as a reference while usingMWRI to bridge the data gap between AMSR2 and AMSRE. The double difference method is used to provide intersensordifference time series for correcting calibration biases, such asscene temperature-dependent bias, solar-heating-induced bias,and systematic constant bias. Hardware differences betweensensors are corrected using principal component analysis. Afterrecalibration, the mean biases of both MWRI and AMSR-Eare less than 0.3 K compared to the AMSR2 reference andtheir standard deviations are less than 1 K for all channels.Under oceanic rain-free conditions, the TB biases are less than0.2 K for all channels and no significant relative bias driftswere found between sensors for overlapping observations. Thesestatistics suggest that the consistency between these instrumentswas significantly improved and the derived FCDR could be usefulto obtain long-term water cycle-related variables for climateresearch. 

How to cite: Wu, B. and Wang, Y.:  A Fundamental Climate Data Record Derived fromAMSR-E, MWRI, and AMSR2 , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15316, https://doi.org/10.5194/egusphere-egu24-15316, 2024.

EGU24-15804 | ECS | Orals | ITS1.15/GI1.3

A multi frequency altimetry snow depth product over the Arctic sea ice 

Alice Carret, Sara Fleury, Alessandro Di Bella, Jack Landy, Isobel Lawrence, Antoine Laforge, Nathan Kurtz, and Florent Garnier

Since more than 10 years, CryoSat-2 (CS2) has observed and monitored the Arctic Ocean, providing unprecedented spatial and temporal coverage. Satellite altimetry enables to measure sea ice thickness, one essential variable to understand the sea ice dynamics. Numerous sea-ice products developed by the community showed the skills of CS2 to retrieve sea-ice thickness. Nevertheless, several questions remain to better quantify the quality of the measurements. One of them is to better assess the snow depth, a key parameter to obtain the sea ice thickness. In 2018, ICESat-2 mission was launched carrying a LIDAR altimeter. We took advantage of the difference of penetration in the snow layer of laser and Ku-Band altimetry to compute a snow depth product covering the ICESat-2 period. This product is then validated and compared to in situ datasets, reanalysis, models and other snow depth products from satellite missions such as SARAL. Results are quite good concerning the comparison to in situ datasets giving us confidence in the product reliability. In July 2020, the orbit of CryoSat-2 was raised, as part of the CRYO2ICE project, to coincide in space and time to tracks from NASA high resolution altimeter ICESat-2 over the Arctic ocean. This is a unique opportunity to benefit from along-track colocalised data. We present here a methodology to compare ICESat-2 and CryoSat-2 along coincident tracks and compare the resulting snow depth product to gridded products. The lack of in situ measurements is one of the main limitations to analyze the along-track product contribution. Finally we focus on the advantages of combining laser and Ku-band altimetry to lower the uncertainties. The snow depth uncertainties of our product are about 6 cm on average. This ESA-supported study should help prepare the Copernicus CRISTAL mission, which will include a Ka/Ku dual-frequency altimeter for the first time.

How to cite: Carret, A., Fleury, S., Di Bella, A., Landy, J., Lawrence, I., Laforge, A., Kurtz, N., and Garnier, F.: A multi frequency altimetry snow depth product over the Arctic sea ice, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15804, https://doi.org/10.5194/egusphere-egu24-15804, 2024.

EGU24-15810 | Posters on site | ITS1.15/GI1.3

Building a comprehensive picture of sea surface, troposphere and ionosphere contributions in precise GNSS reflectometry from space 

Maximilian Semmling, Weiqiang Li, Florian Zus, Mostafa Hoseini, Mario Moreno, Mainul Hoque, Jens Wickert, Estel Cardellach, Andreas Dielacher, and Hossein Nahavandchi

Signals of Global Navigation Satellite Systems (GNSS) are subjected to propagation effects, like reflection, refraction and scintillation. Twenty years ago, a first dedicated payload has been launched on a satellite mission (UK-DMC) to study Earth-reflected GNSS signals and their potential for Earth observations. It was a milestone in the research field of satellite-based reflectometry. The altimetric use of reflectometry is of particular interest for the geoscience community. The permanent and global availability of GNSS signals, exploited in an altimetric reflectometry concept, can help to improve the rather sparse coverage of today’s altimetric products.

Studies on altimetric reflectometry concepts started already thirty years ago. However, the sea surface roughness, the limited GNSS signal bandwidth, orbit uncertainties and the sub-mesoscale variability (we assume here a horizontal scale < 50 km) of troposphere and ionosphere pose a persistent challenge for the altimetric interpretation and application of reflectometry data.

The ESA nano-satellite mission PRETTY (Passive REflecTometry and dosimeTrY) will investigate the altimetric application of reflectometry. It concentrates on a grazing-angle geometry. A mitigation of roughness-induced signal disturbance can be expected under these angles. On the other hand, at grazing angles tropospheric and ionospheric variability will rise in importance. The PRETTY satellite and payload have been developed by an Austrian consortium and successfully launched on 9th October 2023 into the dedicated polar orbit (roughly 550 km in orbit height). We formed a science consortium (among the here listed partners) to merge competences in the field of altimetry and GNSS signal propagation effects.

Based on the mission’s ATBD (Algorithm Theoretical Baseline Document), we conducted simulations and case studies of existing satellite data. They allow a first quantification of expected roughness and sea surface topography effects, as well as, tropospheric and ionospheric biases in grazing-angle geometry. The preliminary results show that, for calm ocean areas (significant wave height < 1 m) and over sea ice, altimetric retrievals reach centimeter level precision. In these specific cases, the residual Doppler shift is small (mHz range) which indicates moderate variability of tropospheric and ionospheric contributions. New observation data of the PRETTY mission is expected early in 2024. Then, we will extend our picture for a more general altimetric use of precise reflectometry data.

How to cite: Semmling, M., Li, W., Zus, F., Hoseini, M., Moreno, M., Hoque, M., Wickert, J., Cardellach, E., Dielacher, A., and Nahavandchi, H.: Building a comprehensive picture of sea surface, troposphere and ionosphere contributions in precise GNSS reflectometry from space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15810, https://doi.org/10.5194/egusphere-egu24-15810, 2024.

The US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) created a Joint Program Planning Group (JPPG) in 2010 to enhance coordination between NASA and ESA on current and future space Earth Observation missions. One of the three sub-groups of the JPPG is dedicated to collaboration in field measurement campaigns, mission and product calval and more recent collaborative EO community science projects.

Since 2010 the JPPG has initiated or informed numerous airborne field campaigns to help develop and document the scientific objectives, develop geophysical retrieval algorithms and provide calibration and/or validation for present and/or future satellites to be operated by NASA, ESA, and its partners. The activities address an underlying need to demonstrate unambiguously that space-based measurements, which are typically based on engineering measurements by the detectors (e.g. photons), are sensitive to and can be used to reliably retrieve the geophysical and/or biogeochemical parameters of interest across the Earth and validate mission design. Such campaigns have included as diverse subjects as atmospheric trace gas composition over the western US, solar induced fluorescence over the Eastern United States, wind profiles over the north Atlantic, vegetation canopy profiles in Gabon, and sea ice and ice sheet properties in the Arctic and Antarctic. The collaborative field campaign and calval activities have helped use of surface-based, airborne, and/or space-based observations to develop precursor data sets and support both pre- and post- launch calibration/validation and retrieval algorithm development for space-based satellite missions measuring our Earth system.

The generation of consistent, inclusive, community-based assessments of Earth system change through integrated analyses of these different data sets is also a critically important process in the challenge of documenting Earth system change. To assist in this process the JPPG has supported collaborative community efforts including three installments of the Ice Mass Balance Intercomparison Experiment (IMBIE; two completed, one ongoing), the NASA-ESA Snow on Sea Ice Intercomparison (NESOSI), and the Arctic Methane and Permafrost Challenge (AMPAC).

In this talk a review of JPPG activities and their results, as well current plans for future collaborations including campaigns will be provided. 

How to cite: Davidson, M. W. J., Drinkwater, M., and Kaye, J.: An overview of collaborative field campaigns, calval and community science activities enabled through the ESA-NASA Joint Program Planning Group, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16893, https://doi.org/10.5194/egusphere-egu24-16893, 2024.

EGU24-17973 | Orals | ITS1.15/GI1.3

Post-launch Validation of the Copernicus Atmospheric Composition Satellites: Outcomes of the CCVS Gap Analysis 

Tijl Verhoelst, Jean-Christopher Lambert, Martine De Mazière, Bavo Langerock, Steven Compernolle, Folkert Boersma, Daan Hubert, Arno Keppens, Clémence Pierangelo, Gaia Pinardi, Mahesh Kumar Sha, Frederik Tack, Nicolas Theys, Gijsbert Tilstra, Michel Van Roozendael, Corinne Vigouroux, Angelika Dehn, Philippe Goryl, Thierry Marbach, and Sébastien Clerc

The European Earth Observation programme Copernicus is implementing the next-generation system for atmospheric composition monitoring: after the success of the Sentinel-5 Precursor TROPOMI, a constellation of Sentinel-4 geostationary and Sentinel-5 Low-Earth orbiting missions will be launched in 2025 and beyond for air quality, ozone and climate variables monitoring, while the CO2M missions will observe greenhouse gases emissions and related proxies.  Post-launch validation of the data products is essential to determine their quality and enable users to judge their fitness-for-purpose.  Therefore, in 2021-2022 the European Union funded the H2020 Copernicus Cal/Val Solution (CCVS) project with the aim to review the status of existing validation infrastructures and methods for all Sentinel missions and to define a holistic solution to overcome limitations (https://ccvs.eu).  In this contribution we report on the maturity assessment and gap analysis performed in this project.  This assessment synthesizes lessons learned from earlier work in FP7 and H2020 projects, and from the operational/routine validation services run in the ESA/Copernicus Atmosphere Mission Performance Cluster (ATM-MPC), the EUMETSAT Atmospheric Composition Satellite Application Facility (AC SAF), the Copernicus Atmosphere Monitoring Service (CAMS) and the Copernicus Climate Change Service (C3S).  The CCVS assessment includes feedback from space agencies, Copernicus stakeholders and the CEOS Working Group on Calibration and Validation (WGCV).  

The validation means, such as the precursor data sets and comparison methods, have evolved significantly in the past decade: (1) New ground-based instruments have been developed and networks have expanded  in geographical coverage and in capabilities, (2) traceability to metrological standards and uncertainty characterization of the (Fiducial) Reference Measurements (FRM) has improved considerably, (3) rapid provision of FRM through data distribution services is becoming commonplace, (4)  the advantages of advanced comparison methods have been demonstrated, and (5) all of this has facilitated the development of operational, near-real-time validation systems such as the Validation Data Analysis Facility (VDAF-AVS) of the ATM-MPC for the Sentinel-5P mission. 

On the other hand, a list of remaining challenges still restrain the scope and quality of the validation of several atmospheric data products: (1) Station-to-station differences in ground-based validation results suggest (poorly understood) intra-network and inter-network inhomogeneity, (2) the coverage offered by ground-based networks (of the full range of the measurand values and of the influence quantities affecting the retrieval) can have important gaps, (3) timeliness of ground-based data provision remains poor for several products, (4) comparability (representativeness) between ground-based and satellite measurements requires further methodological advances and supporting measurement campaigns, (5) the accuracy and breadth of scope of the latest generation of satellite sounders puts correspondingly tight and difficult-to-meet requirements on the FRM data quality, (6) cross-validation of the different satellites requires a coordinated approach, and (7) some networks and activities experience increased/recurrent funding difficulties. 

We conclude this overview of the CCVS gap analysis for atmospheric composition data with illustrations of concrete actions undertaken recently to address some of the validation challenges highlighted by the project.

The CCVS project has received funding from the European Union’s Horizon 2020 programme under grant agreement No 101004242 (Project title: “Copernicus Cal/Val Solution). 

How to cite: Verhoelst, T., Lambert, J.-C., De Mazière, M., Langerock, B., Compernolle, S., Boersma, F., Hubert, D., Keppens, A., Pierangelo, C., Pinardi, G., Kumar Sha, M., Tack, F., Theys, N., Tilstra, G., Van Roozendael, M., Vigouroux, C., Dehn, A., Goryl, P., Marbach, T., and Clerc, S.: Post-launch Validation of the Copernicus Atmospheric Composition Satellites: Outcomes of the CCVS Gap Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17973, https://doi.org/10.5194/egusphere-egu24-17973, 2024.

EGU24-19307 | Orals | ITS1.15/GI1.3

Four decades of cryosphere albedo from spaceborne observations - assessment with field data 

Jason Box, Rasmus Bahbah, Andreas Ahlstrøm, Adrien Wehrlé, Alexander Kokhanovsky, Ghislain Picard, and Laurent Arnaud

Snow and ice albedo plays a fundamental role in climate change amplification. Its importance is by modulating absorbed sunlight; the largest average melt energy source. Further, the presence or lack of light absorbing impurities including living matter and meltwater effects can strongly influence snow and ice heating rates. Through multiple consecutive satellite missions, cryosphere albedo has been mapped globally and continuously for more than four decades now.
This work examines a 42 year record of cryosphere albedo by joining the satellite climate records of snow and ice albedo from AVHRR 1982 to present, NASA MODIS 1999 to present, and EU Copernicus Sentinel-3 2017 to present. The long-term stability of the climate records is examined using independent field data from Greenland and Antarctica. Additionally, the work presents long term trends in snow and ice albedo in relation to the competing effects of surface melting, snowfall and rainfall.

How to cite: Box, J., Bahbah, R., Ahlstrøm, A., Wehrlé, A., Kokhanovsky, A., Picard, G., and Arnaud, L.: Four decades of cryosphere albedo from spaceborne observations - assessment with field data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19307, https://doi.org/10.5194/egusphere-egu24-19307, 2024.

EGU24-19918 | Posters on site | ITS1.15/GI1.3

CryoSat Mission: CalVal, Science and International Cooperation Activities 

Alessandro Di Bella and Tommaso Parrinello

Launched in 2010, the European Space Agency’s (ESA) CryoSat mission was the first polar-orbiting satellite flying a SAR Interferometric altimeter dedicated to the cryosphere, with the objectives to monitor precise changes in the thickness of polar ice sheets and floating sea ice. After 14 years in orbit, CryoSat remains one of the most innovative radar altimeters in space and continues to deliver high-quality data, providing unique contributions to several Earth Science and application domains. The mission has been extended until the end of 2025 with the scope to achieve important scientific objectives and to extend the synergy with other missions by further strengthening international cooperation.

Routine CalVal activities are fundamental to evaluate the accuracy of CryoSat measurements, to monitor the long-term stability of the altimeter, and to characterise uncertainties on the final geophysical retrievals. In this talk, we present the CryoSat mission status and show results from some of the several CalVal activities currently in place, e.g., acquisition over transponders, comparison of sea level at tide gauges and exploitation of data collected during polar field campaigns. We also highlight the importance of international cooperation in CalVal and Science activities from the perspective of the ESA-NASA CRYO2ICE campaign, aligning CryoSat orbit to the one of ICESat-2, and the Sea Ice Thickness Intercomparison Exercise (SIN’XS) project, aiming to provide reconciled sea ice thickness estimates in both hemispheres. Finally, we discuss how current and future CryoSat activities are crucial to prepare for the upcoming Copernicus CRISTAL mission which will provide coincident measurements at Ka and Ku bands.

How to cite: Di Bella, A. and Parrinello, T.: CryoSat Mission: CalVal, Science and International Cooperation Activities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19918, https://doi.org/10.5194/egusphere-egu24-19918, 2024.

EGU24-20394 | Orals | ITS1.15/GI1.3

Validation and support of space-based measurements with the Pandonia Global Network of ground-based spectrometers 

Thomas Hanisco, Nader Abuhassan, Stefano Casadio, Alexander Cede, Limseok Chang, Angelika Dehn, Barry Lefer, Elena Lind, Apoorva Pandey, Bryan Place, Alberto Redondas, James Szykman, Martin Tiefengraber, Luke Valin, Michel van Roozendael, and Jonas von Bismarck

Since 2019 the NASA Pandora and ESA Pandonia projects have been collaborating to coordinate and facilitate the expansion of a global network of ground-based spectrometers to support space-based measurements of trace gases relevant to air quality (NO2, O3, HCHO, SO2, …). This network of standardized, calibrated Pandora instruments, the Pandonia Global Network (PGN, https://www.pandonia-global-network.org), is focused on providing data needed to help validate satellite measurements and to contribute to scientific studies of air quality.  As of January 2024, the PGN is comprised of 158 official sites in 34 countries. This presentation will describe recent efforts to expand and improve the network to support the increased capability and complexity of space-based measurements. Collaborative efforts by partner agencies, especially the US Environmental Protection Agency (EPA) and the Korean National Institute of Environmental Research (NIER), and new programs such as the Increasing Participation in Minority Serving Institutions (IPMSI) and Satellite Needs Working Group (SNWG) have accelerated the growth of the PGN, providing greater global coverage and allowing improved data products.  With these improvements and continued input from other suborbital assets, the PGN is well positioned to facilitate the interpretation and validation of high spatial resolution and diurnal measurements provided by the newest orbiting and geostationary satellite instruments. 

How to cite: Hanisco, T., Abuhassan, N., Casadio, S., Cede, A., Chang, L., Dehn, A., Lefer, B., Lind, E., Pandey, A., Place, B., Redondas, A., Szykman, J., Tiefengraber, M., Valin, L., van Roozendael, M., and von Bismarck, J.: Validation and support of space-based measurements with the Pandonia Global Network of ground-based spectrometers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20394, https://doi.org/10.5194/egusphere-egu24-20394, 2024.

EGU24-20397 | Orals | ITS1.15/GI1.3

Integration of ACIX-III Land Atmospheric Correction Inter-comparison eXercise within the Copernicus Expansion Mission Product Algorithm Laboratory to Support Surface Reflectance Cal/Val 

Kevin Alonso, Noelle Cremer, Valentina Boccia, Philip G. Brodrick, Adam Chlus, Georgia Doxani, Ferran Gascon, Sander Niemeijer, David R. Thompson, Philip Townsend, and Nikhil Ulahannan

Atmospheric Correction Inter-comparison eXercise (ACIX) was initiated in 2016 in the frame of the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV) and it is co-organised by ESA and NASA. The aim of ACIX is to compare the state-of-the-art atmospheric correction (AC) processors. ACIX is a voluntary and open-access initiative to which every AC processor’s developer is invited to participate. In the current third edition, ACIX-III Land, the focus is on imaging spectrometer data, also called hyperspectral data. Data from two spectrometers in orbit (PRISMA and EnMAP) will be used in a suite of test sites. These sites were selected based on the availability of ground-based measurements and flight campaign data with coincident acquisitions, i.e., RadCalNet and CHIME-AVIRIS-NG campaigns.

 The ACIX-III Land exercise will intercompare the performances of several AC software suits capable of retrieving Surface Reflectance (SR), Water Vapour (WV) and Aerosols Optical Depth (AOD). The original datasets along with the participant results will be catalogued, intercompared, and analysed within the Copernicus Expansion Mission - Product Algorithm Laboratory (CEM-PAL). The CEM-PAL is a virtual environment aiming to facilitate efficient prototyping of algorithms used to generate and test Expansion Missions Level-2 products, including algorithm modification, hosted processing, qualification functionalities and scientific validation environment. Once the ACIX-III results are published, the dataset will be repurposed to initially support the CHIME L2 developments with plans to extent the support to other missions (e.g., SBG, LSTM).

This contribution will present the ACIX-III Land, and CEM-PAL initiatives, highlighting the main implementation points, latest status, and future developments to support related Cal/Val activities.

How to cite: Alonso, K., Cremer, N., Boccia, V., Brodrick, P. G., Chlus, A., Doxani, G., Gascon, F., Niemeijer, S., Thompson, D. R., Townsend, P., and Ulahannan, N.: Integration of ACIX-III Land Atmospheric Correction Inter-comparison eXercise within the Copernicus Expansion Mission Product Algorithm Laboratory to Support Surface Reflectance Cal/Val, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20397, https://doi.org/10.5194/egusphere-egu24-20397, 2024.

EGU24-20612 | Posters on site | ITS1.15/GI1.3

Using In Situ Airborne Measurements to Evaluate Pandora Ground-based Remote Sensing Formaldehyde Data Products  

Jason St. Clair, Glenn Wolfe, and Thomas Hanisco

Measurements of boundary layer formaldehyde (HCHO) are valuable for air quality monitoring, both because HCHO is classified as an air toxic by the US EPA and because HCHO concentrations directly reflect recent VOC oxidation and therefore are a diagnostic for ozone production. The Pandora network, with instruments deployed across the US and around the world, is a promising source of boundary layer HCHO data but previous evaluation of Pandora HCHO data was limited to total column HCHO at two sites during one campaign. Here we extend the evaluation to include Pandora tropospheric column and profiling data products derived from differential optical absorption spectroscopy (DOAS) operation. NASA’s SARP-East program provided a unique opportunity to evaluate the Pandora DOAS data products with profiling spirals by an airborne in situ payload that included the NASA Goddard CAFE HCHO instrument. Comparison of CAFE and Pandora data will be presented with the goal of better informing the Pandora data community of its performance.

How to cite: St. Clair, J., Wolfe, G., and Hanisco, T.: Using In Situ Airborne Measurements to Evaluate Pandora Ground-based Remote Sensing Formaldehyde Data Products , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20612, https://doi.org/10.5194/egusphere-egu24-20612, 2024.

EGU24-20665 | Orals | ITS1.15/GI1.3

Using Pandora direct sun and MAX-DOAS formaldehyde columns for evaluating satellite retrievals 

Apoorva Pandey, Bryan Place, Jin Liao, Nader Abuhassan, Alexander Cede, Thomas Hanisco, and Elena Lind

Atmospheric formaldehyde (HCHO) is a short-lived but ubiquitous product of hydrocarbon oxidation. It is a tracer of hydrocarbon emissions and reactivity. HCHO has been observed from satellite-based instruments for over two decades. Retrievals typically involve (1) fitting slant columns to the observed UV/IR radiances and (2) deriving vertical columns from the slant columns using air mass factors. Air mass factors are calculated using radiative modeling and a-priori vertical HCHO distributions from a chemical transport model. The Pandora instruments form a ground-based remote sensing network that is valuable for validating satellite retievals. Pandora provides total and tropospheric columns of HCHO via direct sun (DS) and Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations in the UV, respectively. Here, we discuss conversion of slant columns to vertical columns for DS and MAX-DOAS Pandora measurements, neither of which involves radiative modeling and a-priori assumptions. We intercompare daily and seasonal variations in Pandora HCHO columns from these two distinct measurement techniques for ‘hotspot’ and ‘background’ sites to demonstrate their robustness and complementary strengths, as well as to estimate their uncertainties. We further examine the inter-site and seasonal variability in satellite (e.g., OMI, OMPS) retrievals relative to Pandora HCHO columns.     

How to cite: Pandey, A., Place, B., Liao, J., Abuhassan, N., Cede, A., Hanisco, T., and Lind, E.: Using Pandora direct sun and MAX-DOAS formaldehyde columns for evaluating satellite retrievals, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20665, https://doi.org/10.5194/egusphere-egu24-20665, 2024.

EGU24-20707 | ECS | Posters on site | ITS1.15/GI1.3

Intercomparison of Pandora surface and vertical profile NO2 retrievals with in-situ network measurements and airborne observations across the Eastern USA 

Bryan Place, Apoorva Pandey, Lukas Valin, Jason St. Clair, Thomas Hanisco, Nader Abuhassan, Alexander Cede, and Elena Spinei

Trace gas total and tropospheric/stratospheric column retrievals from the Pandora instruments across the Pandonia Global Network (PGN) have played a key role in satellite validation. With the addition of multi-axis differential optical absorption spectroscopy (MAX-DOAS) retrievals to the latest Pandora processing software (Blick v1.8), the PGN now generates surface and vertically-resolved trace gas measurements that will further aid in future satellite product validation. The MAX-DOAS retrievals developed for the Pandora instrument rely upon simple assumptions and measurements and do not require complex radiative transfer calculations, allowing for the columns to be retrieved at a sub-hourly timescale. In this presentation, we give a brief overview of the theory and measurements behind the Pandora MAX-DOAS retrievals and provide an evaluation of the MAX-DOAS NO2 products. For the evaluation we show an intercomparison of PGN NO2 surface products with co-located surface network measurements taken from the US Environmental Protection Agency Air Quality System (EPA AQS) database.  We also compare Pandora NO2 vertical profiles with profiles collected from both sonde and aircraft measurements in the Eastern United States.

How to cite: Place, B., Pandey, A., Valin, L., St. Clair, J., Hanisco, T., Abuhassan, N., Cede, A., and Spinei, E.: Intercomparison of Pandora surface and vertical profile NO2 retrievals with in-situ network measurements and airborne observations across the Eastern USA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20707, https://doi.org/10.5194/egusphere-egu24-20707, 2024.

EGU24-888 | ECS | Posters on site | NH9.11 | Highlight

Identifying Mixing Components by Natural Tracers in the Lake Hévíz System 

Saeed Bidar Kahnamuei, Katalin Hegedűs-Csondor, Petra Baják, Ákos Horváth, Dénes Szieberth, György Czuppon, Márta Vargha, Bálint Izsák, and Anita Erőss

One of the largest natural thermal lakes in the world, Lake Hévíz is located in the southwestern part of the Transdanubian Range’s karst system (Hungary). It is fed by springs with different temperatures, which are located in a cave beneath the lake. The mixing of cold and hot waters generates the lake’s sulphuric therapeutic water, and it is responsible for the cave formation at the bottom, resulting in the lake's unique ecosystem. The presented research aimed at the comprehensive geochemical characterization of waters in the wider surroundings of the lake (lake water, springs, observation, drinking water, and thermal water wells). Investigating the geochemical characteristics of water took on a novel perspective through the innovative application of radionuclides as natural tracers. Within the framework of this investigation, we utilized uranium, radium, and radon isotopes to identify the mixing of fluids and infer the mixing end members in the Hévíz karst system. Alpha spectrometry was applied on selectively adsorbing Nucfilm discs as an inventive approach to measure uranium and radium isotopes. Moreover, stable isotopic ratios of hydrogen and oxygen (δ2H and δ18O) were determined to supplement the information on waters with different origins. Hydrochemical water analysis for measuring the concentration of major ions and trace elements was carried out using ICP-MS, ion chromatography, and UV-Vis spectrophotometry. The inferred fluid end members and their compositions are anticipated to provide insightful information on the hydrogeological functioning of the Lake Hévíz karst system, which is indispensable in sustainable water resource management and understanding climate change's impact.

 

 

Keywords: Thermal lake; Hydrogeochemical characteristics; Mixing fluids; Radionuclides; Stable isotopes; ICP-MS, Nucfilm, Alpha spectroscopy

How to cite: Bidar Kahnamuei, S., Hegedűs-Csondor, K., Baják, P., Horváth, Á., Szieberth, D., Czuppon, G., Vargha, M., Izsák, B., and Erőss, A.: Identifying Mixing Components by Natural Tracers in the Lake Hévíz System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-888, https://doi.org/10.5194/egusphere-egu24-888, 2024.

EGU24-908 | ECS | Posters on site | NH9.11 | Highlight

Proximal Gamma Ray Spectroscopy for monitoring Soil Water Content in vineyards 

Michele Franceschi, Matteo Alberi, Marco Antoni, Ada Baldi, Alessio Barbagli, Luisa Beltramone, Laura Carnevali, Alessandro Castellano, Giovanni Collodi, Enrico Chiarelli, Tommaso Colonna, Vivien De Lucia, Andrea Ermini, Andrea Maino, Fabio Gallorini, Enrico Guastaldi, Nicola Lopane, Antonio Manes, Fabio Mantovani, Samuele Messeri, Dario Petrone, Silvio Pierini, Kassandra Giulia Cristina Raptis, Andrea Rindinella, Riccardo Salvini, Daniele Silvestri, Virginia Strati, and Gerti Xhixha

Soil Water Content (SWC) is a key information in precision agriculture for obtaining high levels of efficiency and health of crops, while reducing water consumption. In particular, for the case of vineyards, due to the recent extreme temperature fluctuations, the knowledge of the SWC of the entire field becomes crucial to allow a timely intervention with emergency irrigation to preserve plant health and yield.

Unlike electromagnetic SWC measurements, that are punctual and gravimetric measurements, that are punctual and also time-consuming, the Proximal Gamma Ray Spectroscopy (PGRS) technique can provide field-scale, non-invasive, and real-time measurements of SWC. This is achievable through an in-situ NaI detector, continuously recording photons resulting from the radioactive decay of 40K in the soil, which are attenuated proportionally based on the amount of stored water. Given the inverse proportionality between soil moisture and photons detected by the gamma ray sensor, the SWC value can be easily obtained.

In this study we investigate the performance of PGRS applied to the case of study of a vineyard at the farm “Il Poggione” located in Montalcino (Siena, Italy).

The effectiveness of the results obtained is supported by different tests: first the validation allowed to compare the PGRS measurement (5.8 ± 1.5)% with a gravimetric measurement (9.0 ± 2.5)%, highlighting a 1-σ agreement; then by the rainfall recognition capability indeed, in correspondence to the most significant rainfall event (18 mm) the SWC value before and after the rain increased of 7.8%.

Moreover, the integration of the in-situ system with an agrometeorological station resulted in a Web App, allowing for real time data storage and thus facilitating data management, spectrum analysis, and display for both gamma ray sensor and agrometeorological station results, enabling comprehensive studies of environmental parameters (e.g., temperature, air humidity).

This research underlines the potential of PGRS as a precise, real-time, and field scale SWC monitoring tool not only in vineyards but for cultivated fields in general. Further refinements concerning the gamma ray spectra analysis and broader applications in environmental monitoring are envisaged for improved agricultural practices.

This study was supported by the project STELLA (Sistema inTEgrato per Lo studio del contenuto d'acqua in agricoLturA) (CUP: D94E20002180009) funded by the Tuscany region under the program POR FESR 2014/2020.

How to cite: Franceschi, M., Alberi, M., Antoni, M., Baldi, A., Barbagli, A., Beltramone, L., Carnevali, L., Castellano, A., Collodi, G., Chiarelli, E., Colonna, T., De Lucia, V., Ermini, A., Maino, A., Gallorini, F., Guastaldi, E., Lopane, N., Manes, A., Mantovani, F., Messeri, S., Petrone, D., Pierini, S., Raptis, K. G. C., Rindinella, A., Salvini, R., Silvestri, D., Strati, V., and Xhixha, G.: Proximal Gamma Ray Spectroscopy for monitoring Soil Water Content in vineyards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-908, https://doi.org/10.5194/egusphere-egu24-908, 2024.

EGU24-1450 | ECS | Orals | NH9.11 | Highlight

Origin of radioactivity in a neoformed mineral: the case of epsomite from the Perticara sulfur mine 

Matteo Giordani, Marco Taussi, Maria Assunta Meli, Carla Roselli, Giacomo Zambelli, Ivan Fagiolino, and Michele Mattioli

Recently, high amounts of toxic and radioactive elements have been discovered in epsomite crystals in the abandoned sulphur mine of Perticara, Italy (Giordani et al., 2022). Epsomite represents a neoformed mineral grown in the galleries after the extraction activities of the sulfur mine. In particular, a content of 5.59 ± 0.84 Bq/g of 210Po was detected in the epsomite phase, coupled with other toxic elements such as 228Th, As, Co, Fe, Mn, Ni, Sr, Ti, Zn.

The anomalous content of polonium led to new investigations of the area through the study of different matrices present in the galleries: minerals, host-rock, water, air, dust and bitumen, with the aim to define the origin and the distribution of this hazardous element. The samples were investigated combining several analytical techniques: X-ray Powder Diffraction (XRPD), Environmental Scanning Electron Microscopy (ESEM-EDS), Inductively Coupled Plasma-Atomic Emission (ICP-AES), Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), Atomic Absorption Spectrometry (AAS), Gamma Spectrometry, Alpha Spectrometry, Radon Monitor, and Alpha Track Detector (ATD).

Water samples showed high Al, Fe, Pb, Mg, and Mn content but not radioactive elements. The bitumen sample showed a higher amount of 210Po and 210Pb (0.12 ± 0.02 Bq/g and 0.11 ± 0.02 Bq/g, respectively), compared to the host-rock and fibrous sericolite samples, but lower than fibrous epsomite crystals (210Po 5.59 ± 0.84 Bq/g; 210Pb 5.93 ± 1.19 Bq/g). A slight anomaly in the 40K and 226Ra content of the host-rock was observed (0.38 ± 0.05 Bq/g and 0.052 ± 0.007 Bq/g respectively), and a high 222Rn concentration (up to 2200 ± 300 Bq/m3) was also detected in the tunnels (Giordani et al., 2024).

The confined atmosphere of the mine, with the high 222Rn concentration, is likely the source of the high level of 210Po and 210Pb, in radioactive equilibrium, detected in epsomite. Thus, the 222Rn-rich, anoxic, and hypoxic atmosphere, coupled with the abundance of Mn, Fe, and organic matter in the mine, could play a key role in the 210Po remobilization. This work highlighted that natural epsomite, which is a very common mineral phase in mines, caves, and underground environments, is able to capture 210Po and 210Pb. For this reason, it should be used as a mineral indicator for the presence of radioactive elements in similar environmental conditions, also helping to ensure safe management. These results indicate that in areas with a long history of mining, despite decommissioning, environmental hazards and human health risks may still emerge in terms of radioactivity and potentially toxic elements (PTEs).

 

Giordani, M., Meli, M.A., Roselli, C., Betti, M., Peruzzi, F., Taussi, M., Valentini, L., Fagiolino, I. and Mattioli, M., 2022. Could soluble minerals be hazardous to human health? Evidence from fibrous epsomite. Environmental Research, 206, p.112579.

Giordani, M., Taussi, M., Meli, M.A., Roselli, C., Zambelli, G., Fagiolino, I. and Mattioli, M., 2024. High-levels of toxic elements and radioactivity in an abandoned sulphur mine: Insights on the origin and associated environmental concerns. Science of the Total Environment, 906, p.167498.

How to cite: Giordani, M., Taussi, M., Meli, M. A., Roselli, C., Zambelli, G., Fagiolino, I., and Mattioli, M.: Origin of radioactivity in a neoformed mineral: the case of epsomite from the Perticara sulfur mine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1450, https://doi.org/10.5194/egusphere-egu24-1450, 2024.

The research aimed to analyse variations in soil gas radon concentrations and geogenic radon potential in areas of typical building plots located in regions known for high and low geogenic radon potential. The study was designated to address the following questions:

  • Are spatial variations in soil gas radon concentrations and radon potential statistically important in the area of a typical building plot? Are these variations similar in regions known for high and low radon potential?
  • How many measurement points should be proposed to properly evaluate geogenic radon potential and radon index on the building plot area?
  • Can an in-situ gamma spectrometric survey, combined with soil properties, be useful in the defining radon index at the area of the building plot?
  • Are seasonal variations of soil gas radon concentration significant at a depth of 0.8 m?  If so, which season is the most appropriate to evaluate geogenic radon potential?

The research was conducted in two counties: Wrocław and Dzierżoniów located in the Lower Silesian Voivodeship in the southwest part of Poland. Dzierżoniów County is among the counties listed in the Regulation of 18 June 2020 of the Minister of Health where the average radon concentration in a significant number of buildings may exceed the reference level of 300 Bq m−3. In both regions, three building plots, each of an area of 300 m2 (which is the size of a typical building plot in an urban area in Poland) were identified. At each building plot, five measurement points were designated -  at the four corners and in the middle of each plot. The research at each measurement point included the following procedures:

  • Soil gas radon concentration measurements at the depth of 0.8 m using solid nuclear track detectors have been performed. The detectors were replaced at the beginning of each season starting from summer 2023.
  • The radionuclides contents in the soil were measured in situ using the gamma-ray spectrometer Exploranium RS-230.
  • The ambient gamma dose rate was measured by the radiometer RK-100
  • Various soil properties including grain size, permeability, and filtration coefficient were determined.

Additionally, at each building plot, the instantaneous radon concentration and soil permeability measurements were performed using Lucas cells and RADON-JOK.

The preliminary research results indicate that in Dzierżoniów County uranium contents were in the range from 1.6 ppm to 3.3 ppm and thorium from 5.4 ppm to 8.2 ppm, whereas in Wrocław County uranium contents were in the range from 1.6 ppm to 2.5 ppm and thorium from 4.3 ppm to 7.4 ppm. The instantaneous survey of radon concentration revealed that in Dzierżoniów County soil gas radon concentration varied from 10.338 kBq m-3 to 31,050 kBq m-3 and soil permeability from 1*10-12 m2 to 1*10 -13 m2, whereas in Wrocław county the soil radon concentration varied from 0.102 to 0.266 kBq m-3 and soil permeability form very low (impossible to measure by used equipment) to 2*10-13m2.

Research project supported by program „Excellence initiative – research university” for years 2020-2026 for University of Wrocław

How to cite: Tchorz-Trzeciakiewicz, D.: Variations of soil gas radon concentrations in a typical building plot area - preliminary results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3352, https://doi.org/10.5194/egusphere-egu24-3352, 2024.

EGU24-4664 | Orals | NH9.11

Gamma spectroscopy for geological studies 

Rares Suvaila

Gamma Ray spectroscopy is used in a large number of interdisciplinary applications, providing information on the identity of radioactive nuclides and allows their quantitative determination. 

Gamma Rays are electromagnetic radiations of nuclear origin and their detection is not a direct one, as it depends on the production of secondary particles which can be collected together to produce an electric signal.

Of all detector types, we prefer semiconductor ones, particularly Hyper-Pure Germanium detectors, which have very high efficiencies and excellent energy resolution. Following the sample type, occasionally the computerized analysis of the spectra has to be adapted or customized. The enormous differences between the environmental samples we need to face (from air filters to sediment, water to organic matter) drove us to develop protocols which have a general structure/pattern/methodology, but different approaches when it comes to treat the different matrices, would they be homogenous or not.

The opposite extremes in terms of use of Gamma Ray spectroscopy are the low and high count rate systems. Our job is to evaluate limits, to adapt to the statistical conditions, to calculate correction factors in order to get the results as close as possible to the reality.

Among our strengths there are various non standcard protocols, but also the use of information from the sum (coincident) peaks in order to acknowledge source activity and volume distribution; if the study is based only on the simple gamma peaks, the only information one would get is a large domain of possible positions of the source, without clear activity information. Another important topic is the information on the source homogeneity which is given by the count rates for peaks of different nature.

Our work is mainly experimental; most of the experiments are meant to be performed in the laboratory, as an interdisciplinary approach to nuclear and environmental science. One very important issue to consider in this field is the necessity to adapt to the changing radiation background, no matter the origins of the modifications. Also, the possibility of performing in situ gamma spectrometry is not to be neglected, as it offers multuple benefits, as on the spot analysis, quick tests, feasibility studies, accident dosimetry or simply mapping.

Additionally, we perform neutron activation on the samples, which means we can get the initially non-emitting nuclei to de-excite by gamma radiation: following neutron capture, the activated nuclei disintegrate by a beta process and subsequently emit characteristic gamma radiation, which helps un identify initially "silent" isotopes, bringing precious additional information.

 

Our results obtained experimentally and by Monte Carlo simulations in hypothesis testing of homogeneity properties and/or hot spots in volume sources are now being patented. Also, we seek to develop the quantum correlated gamma spectroscopy field, as it is emerging with new possibilities of treating entangled photons from environmental materials and specimens. Our main purpose for this event is to seek for partnership opportunities accross Europe.

 

How to cite: Suvaila, R.: Gamma spectroscopy for geological studies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4664, https://doi.org/10.5194/egusphere-egu24-4664, 2024.

EGU24-5787 | ECS | Posters on site | NH9.11

From the collective to the individual radon risk exposure: an insight in the current European regulation 

Eleonora Benà, Giancarlo Ciotoli, Peter Bossew, Eric Petermann, Luca Verdi, Claudio Mazzoli, and Raffaele Sassi

Radon (222Rn) is a radioactive gas considered the major source of ionizing radiation exposure for the population and represents a significant health risk when it accumulates indoor environments. In Europe the regulation has been implemented in order to address the issue of indoor radon exposure, including pose national reference levels and the identification of the so-called Radon Priority Areas (RPAs). Although the European directive states that RPAs are defined as those areas where the annual average Indoor Radon Concentrations in a significant number of dwellings is expected to exceed the reference level the concept and interpretation of “significant number of buildings” in the European Directive remained unclear. According to this idea, radon is classified as an anthropogenic hazard since it has a strong correlation with IRC. However, indoor radon levels can vary significantly at the municipal level also among neighbouring dwellings, mostly due to differences in building characteristics and inhabitants’ habits. Since in this way the radon natural origin may be bypassed, many authors (mostly geologists) propose to use the Geogenic Radon Potential (GRP) as a hazard indicator. The GRP represents the amount of radon that can potentially influx within buildings from geogenic sources. Being the radon hazard and risk concepts still debated, in the last year, researchers proposed a clear transition from the radon hazard to the more comprehensive radon risk concept proposing that mapping this geo-hazard (GRP) is a fundamental step to define the collective radon risk exposure. The Collective Risk Areas (CRAs) are composed by many possible little Individual Risk Areas (IRAs). Considering that the radiation protection aimed to reduce the detriment, radon abatement policies have to take care of these CRAs not forgetting areas with high individual risk in order to protect individuals from high exposure. On the one hand the collective risk areas have proposed as geological-based risk areas; on the other hand, the individual risk areas are strictly linked to the Indoor Radon Concentration (IRC) and may be assimilated to the “classical” RPAs concept. Considering the absence of an unambiguous methodology at the European scale to define the RPAs and the proposed CRAs mapping as the first step to define the IRAs (“classical” RPA), with this work we aimed to lay the foundation to create a definitive methodology for the individual risk-based RAPs mapping considering, first of all, the number of people involved. The test area chosen for this study is the Bolzano province (Italy) due to the high availability of potential predictors variables and a detailed IRC survey campaign on the entire provincial territory. Starting from this we proposed the first IRAs map (i.e., the first individual risk-based RPAs definition) using a set of Machine Learning techniques allowing to connect and validate the geo-hazard with real IRC measured in the province, with the aim to predict both the collective risk and the possible individual detriment as required by the European regulation.

How to cite: Benà, E., Ciotoli, G., Bossew, P., Petermann, E., Verdi, L., Mazzoli, C., and Sassi, R.: From the collective to the individual radon risk exposure: an insight in the current European regulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5787, https://doi.org/10.5194/egusphere-egu24-5787, 2024.

Brazil is envisaging a large scale plan for indoor radon assessment. Radon levels shall be mapped and priority areas identified. Given the size of the country and its diversity in natural and socio-economical respects, this is a challenging project. Pilot studies and local surveys have been performed in the past but no country-wide assessment exists.

In November 2023, the IAEA organized a workshop on radon survey planning in Poços de Caldas, Minas Gerais, Brazil, to support the project. The objective was to identify items which have to be resolved before starting the actual experimental, i.e., field and laboratory work; so to speak, asking the right questions beforehand to render work as efficiently as possible. Experts from several scientific disciplines related to radon participated (physics, statistics, geology, geography, radiology, national demographic database management, etc.). Among the questions which result from experiences with past surveys, are:

  • Which is the objective of the survey? (Assessment of radon hazard, of collective risk, of detriment attributable to radon, decision base for mitigation action, etc.)
  • Which is the target quantity? (Mean concentration in living rooms over an area, probability to exceed a reference level within an area, status of an area as priority area, etc.)
  • Which is the mapping support, i.e., the geographical area to which a value of the target quantity shall be assigned? (Municipality, administrative region, geological unit, grid cell, etc.)
  • Which spatial estimation strategy is chosen: design based (inference only from radon measurements) or model based (inference from predictor quantities such as geology or ambient dose rate)?
  • How to generate a representative sampling scheme, and how to verify it?
  • In case of a design based strategy: which sample size is required to achieve a given accuracy of the result? More generally: which information is necessary to establish an uncertainty budget of the target quantity?
  • How should an operational database be structured, which metadata should be included?
  • How should a "cooking recipe" look like, which generation of new data should follow? ("Bottom-up harmonization") How can existing data be integrated into the database ("Top-down harmonisation")?
  • How can experiences gained during pilot and local projects be transferred and "upscaled" to different environments and larger regions?
  • How should a QA/QC scheme look like, appropriate to the project?

These questions, some of which are by no means trivial, should be thoroughly discussed and answered before actually starting a survey. Some of them will be addressed in the presentation.

 

How to cite: Bossew, P. and Da Silva, N.: Designing an indoor radon survey - results of a recent IAEA workshop on survey planning in Brazil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6182, https://doi.org/10.5194/egusphere-egu24-6182, 2024.

EGU24-7604 | Orals | NH9.11 | Highlight

Long-term atmospheric radon measurements and their connection with environmental conditions 

Sebastian Baumann, Valeria Gruber, Joachim Gräser, and Dietmar Roth

Radon is a radioactive noble gas. Accumulated indoors it is a large source of radiation exposure. Atmospheric radon can be used as a tracer for greenhouse gases and for atmospheric modelling.

We analyzed long-term (> 10 years) time series of atmospheric radon (Rn-222 and Rn-220) at 15 locations in Austria and neighboring countries. The measured concentrations are equilibrium-equivalent concentrations (EEC), where decay products of radon are measured on air filters with a PIPS-detector. Other parameters as ambient dose rate and weather data (wind, rainfall and precipitation) are measured at the same location. Additional for one year the atmospheric radon concentration was measured directly with a different measurement system (Alphaguard) at three locations.

The analysis of the EEC showed that the temporal variation of atmospheric radon (Rn-222, Rn-220) depends on meteorological parameters. Seasonal and diurnal variations are linked to the stability of atmospheric layers. Under stable weather conditions higher radon concentrations occur. Correlation of the radon concentrations were found primarily with temperature and wind speed. At temperatures below 0 °C, Rn-220 shows very low concentrations and a different behavior than Rn-222. This reduction of Rn-220 availability could be associated with frozen or snow-covered soils.

The additional measurements (Alphaguard) of atmospheric radon concentrations provided plausible long-term averages, although individual measurements can provide implausible values (e.g. negative values). The temporal patterns of the two measurement systems are very similar, and the atmospheric radon concentrations are predominantly higher than the EEC.

A connection of the long-term average values of the atmospheric radon and the radon potential of an area was found, by comparing atmospheric radon concentrations with indoor radon measurements and predictions of the radon potential in Austria. This indicates that the radon potential determines the average level of the atmospheric radon concentrations and weather conditions temporally modulate the atmospheric radon concentrations around this level.

This work is supported by the federal ministry of Austria for climate action and the project RadoNORM, which has received funding from the Euratom research and training programme 2019-2020 under grant agreement No 900009.

How to cite: Baumann, S., Gruber, V., Gräser, J., and Roth, D.: Long-term atmospheric radon measurements and their connection with environmental conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7604, https://doi.org/10.5194/egusphere-egu24-7604, 2024.

EGU24-8408 | ECS | Posters on site | NH9.11

Indoor 222-Rn Modeling in Data-Scarce Regions: An Interactive Dashboard Approach for Bogotá, Colombia 

Martín Dominguez Duran, María Angélica Sandoval Garzón, and Carme Huguet

Radon (222Rn) is a naturally occurring gas that represents a health threat due to its causal relationship with lung cancer. Despite its potential health impacts, several regions have not conducted studies, mainly due to data scarcity and/or economic constraints. This study aims to bridge the baseline information gap by building an interactive dashboard that uses inferential statistical methods to estimate indoor radon concentration’s (IRC) spatial distribution for a target area. We demonstrate the functionality of the dashboard by modelling IRC in the city of Bogotá, Colombia, using 30 in situ measurements. IRC measured were the highest reported in the country, with a geometric mean of 91 ±14 Bq/m3 and a maximum concentration of 407 Bq/m3. In 57 % of the residences RC exceeded the WHO's recommendation of 100 Bq/m3. A prediction map for houses registered in Bogotá’s cadastre was built in the dashboard by using a log-linear regression model fitted with the in-situ measurements, together with meteorological, geologic, and building specific variables. The model showed a cross-validation Root Mean Squared Error of 56.5 Bq/m3. Furthermore, the model showed that the age of the house presented a statistically significant positive association with RC. According to the model, IRC measured in houses built before 1980 present a statistically significant increase of 72 % compared to those built after 1980 (p-value = 0.045). The prediction map exhibited higher IRC in older buildings most likely related to cracks in the structure that could enhance gas migration in older houses. This study highlights the importance of expanding 222Rn studies in countries with a lack of baseline values and provides a cost-effective alternative that could help deal with the scarcity of IRC data and get a better understanding of place-specific variables that affect IRC spatial distribution.

How to cite: Dominguez Duran, M., Sandoval Garzón, M. A., and Huguet, C.: Indoor 222-Rn Modeling in Data-Scarce Regions: An Interactive Dashboard Approach for Bogotá, Colombia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8408, https://doi.org/10.5194/egusphere-egu24-8408, 2024.

EGU24-9434 | ECS | Posters on site | NH9.11

A combined approach for the correlation between indoor radon and geological background: application in the western Ligurian Alps (Italy) 

Linda Bonorino, Gianluca Beccaris, Paola Bisi, Paolo Chiozzi, Andrea Cogorno, Elga Filippi, Riccardo Narizzano, Sonja Prandi, and Massimo Verdoya

Radon (222Rn) is one of the most common naturally occurring radioactive elements and is particularly interesting to environmental issues, for it is considered a carcinogenic gas. It is a decay product of 238U, contained in most rocks and soils, and can easily escape from the ground to accumulate in closed spaces where it may become dangerous. The knowledge of its potential is vital to urban development plans and to protect people from potential hazards. We recently conducted monitoring campaigns in Liguria (NW Italy) to investigate the relations between the observed indoor radon concentrations and the geo-lithological background. We focused on the geological units of the Western Alps, characterized by various lithotypes, ranging from sedimentary to metasedimentary and metavolcanic rocks. The natural gamma radiation was measured on outcrops. Spectrometric measurements indicated that metamorphic acid rocks have the highest specific activity values of 238U (75-85 Bq/kg). In metasedimentary rocks, quartz and mica schists show the highest concentration of 238U, with an average specific activity of 56 Bq/kg. Sedimentary rock types are characterized by average specific activities < 40 Bq/kg., The dosimetric indoor surveys highlighted that about 40% of the investigated public and private buildings show indoor radon values above 200 Bq/m3. These preliminary campaigns revealed a relationship between the uranium content of the bedrock and the indoor radon. The correlation can be used to predict the geogenic radon potential based on a geological background when dosimetric data are few or scattered. In this paper, we refined our early analysis by integrating the dataset with further spectrometric and indoor dosimetric records, which were also coupled with soil radon measurements. The radon concentration in soil was investigated focusing on the sites where the previous monitoring campaigns showed high indoor radon concentrations. Soil radon was recorded at depths between 50 and 80 cm, where radon diffusion from the ground to the buildings very likely occurs. Soil radon concentrations substantially agree with spectrometric measurements. The largest concentration of 222Rn was found in the soils on more acid metamorphic rocks (porphyroid and porphyric shists) with values of about 100 kBq/m3. The lowest values about (20 kBq/m3) were recorded in soils occurring in sedimentary rocks. Despite the limitations and uncertainties, mainly related to the uneven data coverage and the complex interaction between the building and the bedrock, the combined techniques can identify areas of potentially high indoor radon concentrations.

How to cite: Bonorino, L., Beccaris, G., Bisi, P., Chiozzi, P., Cogorno, A., Filippi, E., Narizzano, R., Prandi, S., and Verdoya, M.: A combined approach for the correlation between indoor radon and geological background: application in the western Ligurian Alps (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9434, https://doi.org/10.5194/egusphere-egu24-9434, 2024.

EGU24-10152 | ECS | Posters virtual | NH9.11

Exploring the hydrothermal vent field of Milos Island in Aegean Seausing novel radiation instrumentation 

Georgios Siltzovalis, Ioannis Madesis, Varvara Lagaki, Theodoros J. Mertzimekis, Pavlos Krassakis, Stavroula Kazana, and Konstantinos Nikolopoulos

Radioactivity monitoring in the marine environment exhibits various challenges. First and foremost, the water-induced attenuation substantially limits the detection ability and range of the sensors. Additionally, the harshness and remoteness of underwater locations pose significant obstacles to existing technological solutions towards dense and extended radioactivity mapping of the oceans. The highly ambitious EU FET Proactive Research Programme RAMONES (Radioactivity Monitoring in Ocean Ecosystems) is aiming towards overcoming existing limitations by developing and deploying novel underwater radiation-sensing instruments, enabling direct correlation of marine radioactivity with underwater geological and geochemical processes.

The present study will focus on the analysis of experimental data collected during field experiments conducted in the extended hydrothermal vents of Milos, an island located on the south Aegean Sea that is part of the Hellenic Volcanic Arc. The shallow active hydrothermal system of Milos is associated with calc-alkaline volcanic rocks from basaltic andesites to dacites, and rhyolites that have been deposited over several cycles of volcanic activity. Novel portable γ-detectors based on lightweight CdZnTe crystals, were deployed to acquire in situ measurements from coastal locations at the eastern part of the island. Complementary sediment samples were collected to offer baseline NORM (Naturally Occurring Radioactive Material) levels from Milos Island having attracted a lot of attention recently due to its role as a potential geohazards source. These measurements are used to benchmark the γ spectrometers and prepare them for underwater operation aboard autonomous underwater gliders. Collected data will feed a prototype Risk Information System (RIS) titled as POIS2ON (PrOtotype Information System for SOcioecoNomic stakeholders). POIS2ON database will include datasets accompanied by geoinformation to be visualized though NORM levels heat maps, as well as support detailed Monte Carlo simulations to evaluate the radiation doses on local marine ecosystems.

How to cite: Siltzovalis, G., Madesis, I., Lagaki, V., Mertzimekis, T. J., Krassakis, P., Kazana, S., and Nikolopoulos, K.: Exploring the hydrothermal vent field of Milos Island in Aegean Seausing novel radiation instrumentation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10152, https://doi.org/10.5194/egusphere-egu24-10152, 2024.

EGU24-12397 | ECS | Posters on site | NH9.11

Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations 

Diana Altendorf, Henning Wienkenjohann, Florian Berger, Jörg Dehnert, Michal Duzynski, Hannes Grünewald, Dmitri Naumov, Ralf Trabitzsch, and Holger Weiß

Naturally occurring radon-222 (Rn) is a widespread indoor air pollutant, posing a potential health risk for humans, particularly elevating the risk of lung cancer in indoor living and working spaces. One highly promising solution for existing buildings, requiring relatively minimal technical effort to reduce indoor radon, is the installation of a ventilation system.

As a proof of concept, a series of different ventilation experiments, utilising a decentralised ventilation system with heat recovery (inVENTer GmbH, Germany) were performed in an unoccupied ground-floor flat in Bad Schlema (Germany).

The flat was divided into three individually controllable ventilation zones using strategically positioned ventilation devices, controlled by a novel real-time measurement system for indoor radon activity concentration [Rn] (Smart Radon Sensors by SARAD GmbH, Germany) in each room. This innovative approach to eliminate indoor radon by employing [Rn] as a control parameter enabled automated switching between different ventilation modes or the option to deactivate the system entirely.

Over three years, the different ventilation experiments successfully reduced elevated indoor radon levels from up to 7000 Bq/m³ to 300 Bq/m³ and below. The effectiveness varied based on factors such as the initial room-specific radon levels before each experiment, the performance level of the fans and meteorological parameters.

Furthermore, we developed a true-to-scale three-dimensional Computational Fluid Dynamics (CFD) model based on the actual flat, enabling the quantitative interpretation of various ventilation experiments within a CFD environment. The CFD model utilised a stationary k-ε turbulent flow model to simulate ventilation-induced airflow inside the flat and was coupled with a transient transport model for radon simulation.

For the development of the CFD model, the "Cross-Ventilation" experiment was chosen. This experiment successfully achieved a room-specific reduction of indoor radon levels from approximately 3,000 Bq/m³ to about 300 Bq/m³. To precisely capture the impact of ventilation on indoor radon, the initial radon values for each room were utilised as initial conditions for the transient radon transport model.

Base case results showed an overestimation by the model in radon level reduction due to ventilation. Parameter adjustments of the inflowing radon and the airflow velocity at the inlet resulted in good agreement between experimental values and the CFD model's outcome.

In summary, this study highlights CFD modeling as a versatile tool for evaluating and optimising ventilation systems, offering valuable insights into the mechanism of managing the air quality in complex real-world indoor environments with elevated radon levels.

How to cite: Altendorf, D., Wienkenjohann, H., Berger, F., Dehnert, J., Duzynski, M., Grünewald, H., Naumov, D., Trabitzsch, R., and Weiß, H.: Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12397, https://doi.org/10.5194/egusphere-egu24-12397, 2024.

EGU24-12506 | ECS | Orals | NH9.11

Rapid field measurement of uranium in water samples  

Katalin Hegedűs-Csondor, Heinz Surbeck, Petra Baják, and Judit Mádl-Szőnyi

We present an analytical method that allows for the rapid measurement of uranium in water samples. For a 50 ml sample concentrations down to about 2 micro-g/l can be measured within an hour. There are no toxic chemicals used and the whole equipment is portable and can be powered by a 12 V battery. The preparation consists of adding 200 mg silica gel to the 50 ml sample, stirring for 1 hour, filtering out the silica gel and transferring it to a semi-micro cuvette for the measurement. Several samples can be prepared in parallel, depening on the number of magnetic stirrers available. The measurement takes only 1 minute and uses the uranyl fluorescence, enhanced by the adsorption on silica gel. Excitation is done by a pulsed UV-LED at 285 nm. The delayed fluorescence signal around 520 nm is detected by a 6 mm x 6 mm Silicon Photomultiplie (SiPM) behind a 520 nm bandpass filter. Pulsing the LED, converting the SiPM output and displaying the result is controlled by an Arduino microprocessor. All details of the experimental setup as well the software code are presented. It's open source, open to be copied and the whole material costs are only around 500 Euro.

How to cite: Hegedűs-Csondor, K., Surbeck, H., Baják, P., and Mádl-Szőnyi, J.: Rapid field measurement of uranium in water samples , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12506, https://doi.org/10.5194/egusphere-egu24-12506, 2024.

EGU24-12663 | ECS | Posters on site | NH9.11

Preliminary results of two-dimensional multicomponent reactive transport modelling to understand the controlling factors on uranium mobility in a siliciclastic aquifer in Hungary 

Petra Baják, Daniele Pedretti, András Csepregi, Muhammad Muniruzzaman, Katalin Hegedűs-Csondor, and Anita Erőss

In Hungary, the drinking water supply relies upon groundwater resources of up to 98%. As a drinking water resource, groundwater must meet strict quality requirements in order to minimise any health effects arising from daily water consumption. Water-rock interactions enrich groundwater not only with essential elements (e.g. Ca, Mg) but also with undesired substances such as heavy metals or radioactive elements. In the last few years, a thorough drinking water quality monitoring campaign was carried out in Hungary, revealing that some parts of the country are characterised by relatively high uranium concentrations. The causes of these elevated activities have not been properly investigated, yet. However, understanding the controls of the release and mobility of uranium is critical in proper groundwater management.

Baják et al (2022) developed a one-dimensional (1-D) geochemical model using the code PHREEQC (Parkhurst and Appelo, 2013) to examine the processes that determine the fate of uranium in the siliciclastic Miocene-Quaternary aquifer system near Velence Hills, some 50 km off Budapest. Here, the geological build-up (granitic rocks on the surface) favours the high uranium content in groundwater, which is characterised by oxidising conditions. The 1-D model included redox-controlled kinetic reactions as well as other potential uranium-controlling processes (e.g., surface complexation). The results suggested that uranium distribution is sensitive to redox changes in the aquifer and its mobility in groundwater especially depends on the residence time of water compared to the reaction times controlling the consumption of oxidising species.

This study introduces a two-dimensional multicomponent reactive transport model developed using the PHT3D code (Prommer et al., 2003), which is a coupling between MODFLOW and PHREEQC. The model builds on and extends the capability of the 1-D model to simulate uranium mobility across the multiple flow paths of the aquifer systems. The model calibration accounts for 30 groundwater samples collected from drinking water wells in the study area. Physico-chemical parameters (temperature, pH, specific electric conductivity, redox potential) were measured on-site, and the samples were analysed for natural tracers (δ16O, δ2H, 234U, 238U, 226Ra) to gain further insight into the geochemical processes of the aquifer system.

This research was supported by the ÚNKP-23-4 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund and was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. The research is part of a project which was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014.

References:

Baják, P., Csondor, K., Pedretti, D., Muniruzzaman, M., Surbeck, H., Izsák, B., Vargha, M., Horváth, Á., Pándics, T., Erőss, A., 2022. Refining the conceptual model for radionuclide mobility in groundwater in the vicinity of a Hungarian granitic complex using geochemical modeling. Applied Geochemistry 137, 105201.

Parkhurst, D.L., Appelo, C.A.J., 2013. Description of Input and Examples for PHREEQC Version 3—A Computer Program for Speciation, Batch-Reaction, One-Dimensional Transport, and Inverse Geochemical Calculations. (USGS Technical No. 6(A)43). U.S. Geological Survey, Denver, CO, USA.

Prommer H, Barry, D.A., Zheng, C. (2003). MODFLOW/MT3DMS based reactive multi-component transport modeling. Ground Water, 41(2).

How to cite: Baják, P., Pedretti, D., Csepregi, A., Muniruzzaman, M., Hegedűs-Csondor, K., and Erőss, A.: Preliminary results of two-dimensional multicomponent reactive transport modelling to understand the controlling factors on uranium mobility in a siliciclastic aquifer in Hungary, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12663, https://doi.org/10.5194/egusphere-egu24-12663, 2024.

Understanding the temporal and spatial distribution of soil water content (SWC) is critical for efficient water resource management in agriculture. However, the variability of SWC over time and space presents challenges in obtaining accurate values at field scale using conventional methods. Proximal gamma-ray spectroscopy (PGRS), supported by adequate calibration and biomass corrections, emerge as promising methods for monitoring SWC. The inverse correlation between the gamma counts of the radioisotope 40K (1461 KeV) and volumetric SWC (m3/m3) demonstrates potential for reliable soil moisture estimation in agricultural and hydrological applications. This contribution examines the potential application of a portable sodium iodide (NaI) scintillation detector (PGRS) for estimating SWC in an irrigated wheat field. We explore the sensitivity of the 40K variations to changes in soil moisture and detector height. Over the last two months of the growing season, several one-hour manual monitoring surveys were conducted to capture the effect on 40K signal of irrigation and soil moisture status before and after the harvesting. In each survey, total counts of 40K were recorded using a NaI detector positioned at different elevations above the ground in the middle of a wheat field. Preliminary results indicate a general correlation between 40K (cps) and SWC throughout the study period, suggesting the sensitivity of the PGRS detector to SWC variations. Our findings show a slight increase in 40K counts by decreasing the detector height for all the field surveys conducted. In addition, we observed that the lowest counts of 40K were recorded during the survey with the highest soil water content after irrigation. We can conclude that 40K signal is sensitive to both changes in SWC and the height position of the detector. Furthermore, this detector offers a significant advantage, as it not only captures data on the 40K peak but also analyses the full gamma spectrum.

How to cite: Catalá, A., Navas, A., and Gaspar, L.: Assessing the variability of 40K measurements using a portable gamma-ray spectroscopy in an irrigated agricultural field (Spain), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12700, https://doi.org/10.5194/egusphere-egu24-12700, 2024.

EGU24-15380 | Posters virtual | NH9.11

Application of machine learning methods to improve the radon deficit technique 

David Lorenzo, Fernando Barrio-Parra, Humberto Serrano-García, Miguel Izquierdo-Díaz, and Eduardo De Miguel

The Radon deficit technique is a promising screening method for identifying and mapping potential subsurface organic pollution hotspots and thus, for the optimization of intrusive characterization campaigns. Radon (222Rn) a naturally procuded radionucleid and particularly suitable for use as a natural tracer due to its preferential partitioning with non aqueos phase liquids (NAPLs) and and ease of in situ analytical detection (Kram et al., 2001). The ability of the 222Rn technique to locate organic pollution hotspots and provide a semiquantitative analysis has been widely assessed in sites affected by NAPLs (De Miguel et al., 2018, De Miguel et al. 2020). However, the Radon measurement is affected by several confounding factors, such as variations in soil water saturation and ground-level temperature. Machine learning can be used to study and model these confounding factors and improve the interpretation of in situ radon analytical information.

Machine learning is a class of statistical techniques that have proven to be a powerful tool for modelling the behaviour of complex systems in which response quantities depend on assumed controls or predictors in a complicated way (Janik, 2018). The first purpose of this work is the application of machine learning to analyse sampled data of time series outdoor 222Rn. The algorithms "learn" from complete sections of multivariate series (containing measurements of soil water content, soil temperature and meteorological information), derive a dependence model. The model trained in this work can be used to improve the accuracy and reliability of the radon deficit technique, making it a more valuable tool for identifying and mapping subsurface contamination.

 

De Miguel, E., Barrio-Parra, F., Elío, J., Izquierdo-Díaz, M., Jerónimo, García-González, E., Mazadiego, L.F., Medina, R., 2018. Applicability of radon emanometry in lithologically discontinuous sites contaminated by organic chemicals. Environ. Sci. Pollut. Res. 25, 20255–20263. https://doi.org/10.1007/s11356-018-2372-9

De Miguel, E., Barrio-Parra, F., Izquierdo-díaz, M., Fernández, J., García-gonzález, J.E., 2020. Applicability and limitations of the radon-deficit technique for the preliminary assessment of sites contaminated with complex mixtures of organic chemicals: a blind field-test. Environ. Int. 138, 105591. https://doi.org/10.1016/j.envint.2020. 105591.

Janik, P. Bossew, O. Kurihara, 2018,Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data, Scie. Tot. Environ.,630, 1155-1167, https://doi.org/10.1016/j.scitotenv.2018.02.233.

Schubert, M., 2015. Using radon as environmental tracer for the assessment of subsurface non-aqueous phase liquid (NAPL) contamination – a review. Eur. Phys. J. Spec. Top. 224, 717–730. https://doi.org/10.1140/epjst/e2015-02402-3.

How to cite: Lorenzo, D., Barrio-Parra, F., Serrano-García, H., Izquierdo-Díaz, M., and De Miguel, E.: Application of machine learning methods to improve the radon deficit technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15380, https://doi.org/10.5194/egusphere-egu24-15380, 2024.

EGU24-16925 | ECS | Posters on site | NH9.11

Deciphering Radon Variability in the Northern Upper Rhine Graben: An Analysis Using Passive and Active Detection with Random Forest Modelling 

Johannes Mair, Eric Petermann, Rouwen Lehné, and Andreas Henk

This study, conducted about 30km south of Frankfurt in the Northern Upper Rhine Graben, focuses on deepening the understanding of Radon concentrations in soil air. The selected area, where neotectonic activity was proven in an accompanying project, provides an ideal setting for investigating Radon variability, particularly its potential correlation with fault zones in unconsolidated rocks or sedimentary basins. Understanding the factors influencing Radon levels in the environment is a complex task, as they are affected by a multitude of variables. Our work aims to decipher these influences and, if possible, quantitatively analyse the contributions of each variable. By doing so, we hope to gain a clearer understanding of how different environmental factors interact to determine Radon levels.

A central element of our research is the use of Random Forest models, chosen to handle our multidimensional dataset. This dataset includes a variety of parameters such as Radon measurements, nuclide content, soil grain sizes, weather data, and the distance to fault zones. Random Forest models are particularly effective for this type of complex data because they can analyse many different factors at once and uncover hidden patterns.

Contrary to initial hypotheses, our findings indicate that in unconsolidated rocks and sedimentary basins, the grain size of soil is the most influential factor in determining soil air Radon levels, closely followed by soil moisture. These results challenge the previously held belief that fault zones are the primary influencing factors on Radon concentrations in these geological settings.

How to cite: Mair, J., Petermann, E., Lehné, R., and Henk, A.: Deciphering Radon Variability in the Northern Upper Rhine Graben: An Analysis Using Passive and Active Detection with Random Forest Modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16925, https://doi.org/10.5194/egusphere-egu24-16925, 2024.

EGU24-17300 | ECS | Posters on site | NH9.11 | Highlight

Investigating the sensitivity of flux maps in simulating radon concentrations at greenhouse gas monitoring sites 

Adam Howes, Dafina Kikaj, Edward Chung, Ute Karstens, Alistair Manning, Stephan Henne, Angelina Wenger, Grant Foster, Simon O'Doherty, Chris Rennick, and Tim Arnold

Given its unique properties as a radioactive chemically inert gas, radon can act as a valuable atmospheric tracer, for evaluating the performance of atmospheric transport models to calculate the sources of trace gases to the atmosphere. A radon flux map is the scientific starting point for simulating atmospheric radon concentrations using atmospheric transport models. As such, it is important to assess the available high resolution radon flux maps to ensure that simulated concentrations can be accurately interpreted. The spatial fluxes of radon primarily depend on soil and rock types, while temporal variations are influenced by soil moisture content.

The recent advancements in generating two high-resolution radon flux maps for Europe using two different soil moisture reanalysis, GLDAS Noah and the ERA5 maps1, have significantly enhanced our understanding of radon flux dynamics. Yet, the radon flux values diverge notably between these two maps and sometimes these variations can be substantial, with differences as large as the absolute radon flux itself.

In our work, two available versions of European radon flux maps are coupled with two Lagranian particle dispersion models – the Met Office’s Numerical Atmospheric Modelling Environment (NAME) and the FLEXPART model – are used to simulate radon concentrations measured at four tall tower sites in the United Kingdom: Heathfield, Ridge Hill, Tacolneston and Weybourne. We calculate the differences between the modelled radon concentrations to the observed radon concentrations at these sites and use this to investigate the sensitivity of two radon flux maps: GLDAS Noah and ERA5.

 

References: 12022: https://doi.org/10.18160/2ST9-3NAD

How to cite: Howes, A., Kikaj, D., Chung, E., Karstens, U., Manning, A., Henne, S., Wenger, A., Foster, G., O'Doherty, S., Rennick, C., and Arnold, T.: Investigating the sensitivity of flux maps in simulating radon concentrations at greenhouse gas monitoring sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17300, https://doi.org/10.5194/egusphere-egu24-17300, 2024.

EGU24-17369 | Posters on site | NH9.11 | Highlight

INGV experience on radon monitoring in the Ciampino Municipality (Rome, Italy): a link between research and territory 

Alessandra Sciarra, Luca Pizzino, Gianfranco Galli, Daniele Cinti, Giancarlo Ciotoli, and Sabina Bigi

Ciampino area has been the subject, from 1999 onwards, to reiterated geochemical surveys on soil-gas, spring waters and groundwater, commissioned by the municipality to INGV (National Institute of Geophysics and Volcanology). Indeed, this area is affected by huge CO2 emissions of volcanic origin and high levels of indoor radon. Both gases can constitute a big concern for local population known as Natural Gas Hazard (NGH). Accordingly, the distribution of the two gases in groundwater, soils and indoor buildings must be assessed in order to define sectors of the territory more exposed to NGH.
Interest in the Natural Gas Hazard arose mainly starting from November 1995, when several homes, basements and wells were affected by widespread exhalations, to the point of danger to human health.
The most area affected is characterized by abundant and concentrated gas leaks which caused the death of 29 cattle and some sheep in September 1999 and March 2000, until December 2000 when a paroxysmal episode caused the death of a man.
The main activities carried out in the last 25 years have concerned:
-    sampling of water sites (about 100 natural springs, public and private wells), measuring chemical-physical parameters, CO2 and 222Rn contents;
-    monthly indoor radon measurements (around 500/year) in 14 selected sites (both private homes and workplaces, including schools);
-    measurements of radon in soils (about 300) to identify the areas with the greatest degassing and the possible relationship with existing tectonic structures;
-    continuous indoor radon measurements in a selected home;
-    spot measurements in groundwater and intervention in the event of reports from the municipality and/or private citizens of emergency situations resulting from gaseous emanations falling in areas of the municipal territory of Ciampino.
The data obtained include measurements of flux and concentration of soil gases, distribution of pCO2 and radon in groundwater, radionuclide content in soils from different geological units, indoor radon measurements.
All this data has allowed us to define the sectors at greatest risk, by identification and delimitation of NGH risk areas. Dissemination and information activities on the NGH were carried out through public meetings, seminars and the drafting of brochures. Also training activities for the staff of the Civil Protection and Environment Offices of the Municipality were performed.
The experience gained has allowed the participation of INGV in a European project Life Respire for the monitoring and remediation of the radon problem.
Based on the distribution of the different samples collected: soil gas, terrestrial gamma dose rate and rock/soil samples by radionuclide content, we were able to provide the local authorities the map of the geogenic potential of radon for the whole municipal territory.

How to cite: Sciarra, A., Pizzino, L., Galli, G., Cinti, D., Ciotoli, G., and Bigi, S.: INGV experience on radon monitoring in the Ciampino Municipality (Rome, Italy): a link between research and territory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17369, https://doi.org/10.5194/egusphere-egu24-17369, 2024.

Fumaroles spread out several elements to the atmosphere and may include radon that contributes to environmental radioactivity. The long-lasting vigorous gaseous emissions of the Campi Flegrei volcanic caldera, i.e., Solfatara and Pisciarelli, occur in densely inhabited areas of Naples where the population may be exposed to ionizing radiation from 222-radon. In 2021, we started a study on radon levels from the Solfatara and Pisciarelli fumaroles by using the RAD7 commercial detector, one of the most widely used instruments for measuring 222Rn, either dissolved in water or in soil gas. However, the local high H2S levels and hot temperatures did not allow direct measurements of Rn, resulting in the instrumentation (RAD7) damage. Thus, we developed a proper technique for sampling and measuring radon gas from fumarolic gases in such a “critical” areas to overcome the instrumental issue.

At fumarole sites i.e., Bocca Nuova and Bocca Grande within the Solfatara crater, and Pisciarelli, the gas was periodically sampled in Tedlar® bag of 1 or 3 liters in order to have the possibility to repeat the measurements two or three times to verify the accuracy of the data.

In laboratory, at first, H2S traps were prepared by filling silicone tubes with lead acetate powder, bordered, at both ends, by hydrophilic cotton and closed. Then the fumarole gas was transferred from the Tedlar® bag into a glass tube. Finally, radon gas was measured via a closed loop by using the RAD7. Rn printouts obtained from RAD7 were corrected for the time lag between sampling and measurement. RAD7 and charcoal canister measurements were compared to check the obtained results.

Preliminary results, published in Iovine et al. (2023), demonstrate that the methodology utilized enables the analysis of Rn concentrations even in H2S-bearing gases, discharged from the fumaroles of the Campi Flegrei volcano and, most importantly, without instrumental issues. Fumaroles sampled and analyzed over time according to the methodology adopted, may be suitable for environmental radioactivity assessment and volcanic monitoring purposes as well.

 

Iovine RS, Avino R, Minopoli C, Cuoco E, Caliro S, Galli G, Piochi M. (2023). A procedure to use the RAD7 detector for measuring 222Rn in soil gases exceeding instrumental limits: an application to chemically aggressive fumaroles of the Campi Flegrei area. Rapp. Tec. INGV, 473: 1­18, https://doi.org/10.13127/rpt/473.

How to cite: Iovine, R. S., Minopoli, C., Avino, R., Caliro, S., Galli, G., and Piochi, M.: Determination of 222Radon (222Rn) from the hot and acidic fumaroles gases to the atmosphere of the highly populated Campi Flegrei caldera (Naples, Southern Italy) by using a RAD7 detector: a procedure overcoming instrumental limits, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17908, https://doi.org/10.5194/egusphere-egu24-17908, 2024.

EGU24-18058 | ECS | Orals | NH9.11

Studies on radon time series in various underground environments: Case of abandoned Kővágószőlős uranium mine 

Tóth Szabolcs, Horváth Ákos, and Sajó-Bohus László

Field uranium research began in Hungary in 1947 under the guidance of Hungarian specialists. After the research period, mining plants were opened one after the other, and an ore processing plant was also established. The ore grade found in the Mecsek Mountains was less favorable than average, 1 ton of ore contained 1.2 kg of uranium metal. The characteristic of the uranium ore found in the permian sandstones is that it occurs in several layers and levels, not continuously, but in lenticular spots with varied development. This geological occurence significantly increased the costs. By 1989, Hungarian uranium ore mining had become uneconomical, and a government decision was made to close it down, dating back to 1997. The recultivation process began in 1998. Currently, environmental damage is being eliminated under the title of long-term monitoring. Due to the proximity of inhabited areas, NORM anomalies, and the presence of radon gas, radiation protection played a particularly important role during and after remediation.

The radon monitoring of the abandoned mine cavity system was carried out with active radon monitors placed in different boreholes, closed shafts and adits. In the last two years, a radon soil gas monitoring station has also been operated on a waste rock pile site covered with 1 m of loess cover to check the radon retention capacity of the soil.

For radon detection alpha-sensitive photodiode (sensitive area: 1 cm2) or PIPS detector (sensitive area: 3 cm2) are used. The Dataqua monitoring system gives one impulse per hour for 140 and 56 Bq/m3222Rn concentration, respectively, for the photodiode and PIPS detector. The multi-channel devices beside the radon detector can include other additional sensors for temperature, pressure, humidity, water level, salinity, etc. measurements to study the relation between the variation of radon concentration and other environmental parameters. The radon concentration together with other environmental parameters are continuously recorded with one measurement per hour sampling frequency for several years.

In closed, underground places extremely high radon concentration (a couple of tens up to hundred kBq/m3, may occur in the absence of ventilation, even in rocks of average radionuclide content. According to our measurements both the daily and the yearly variation is well recognizable, which originate from the variation of the meteorological and lunisolar parameters. In the case of a few time series, we revealed a strong correlation between the outside temperature and the resulting radon concentrations.  We found the atmospheric pressure also affects radon levels, but extent and only on a smaller scale than temperature. 

Comprehensive statistics and Fourier analysis were also carried out in order to examine the dominant frequencies, and we also examined the change of the one day long components as a function of time.

How to cite: Szabolcs, T., Ákos, H., and László, S.-B.: Studies on radon time series in various underground environments: Case of abandoned Kővágószőlős uranium mine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18058, https://doi.org/10.5194/egusphere-egu24-18058, 2024.

EGU24-19068 | ECS | Orals | NH9.11

Long-term Evaluation of HPGe Calibration for Environmental Radioactivity Assessment Using IAEA-U and IAEA-Th Sources 

Debora Siqueira Nascimento, Riccardo Ciolini, Andrea Chierici, Stefano Chiappini, Francesco d'Errico, and Massimo Chiappini

The investigation of the dynamics between environmental radioactivity and its implications for human health stands as a fundamental pursuit in contemporary scientific research. Employing the Gamma Spectrometry technique, particularly utilizing High Purity Germanium (HPGe) detectors, emerges as a pivotal methodology to study environmental radioactivity with precision. The veracity and dependability of these analyses hinge upon the scrupulous and precise energy and efficiency calibration of the HPGe system. Within this framework,  we used calibrated IAEA-U and IAEA-Th sources, thereby not only ensuring measurement accuracy but also establishing a robust foundation for comprehensive evaluation of radioactivity levels. Our findings illuminate a comprehensive understanding of the energy and efficiency calibration of the HPGe detector, exemplified by linear relationships in the energy calibration curves for both IAEA-U and IAEA-Th sources, manifesting high correlation coefficients (R² > 0.99). Essential for translating count rates to activity, the efficiency calibration consistently yielded low errors, with the maximum observed efficiency error being less than 4% for both sources, significantly below the recommended by standard rules. This study affirms the reliability and stability of our calibration methods through repeatability assessments over four years. Looking forward, the calibrated HPGe systems are prepared to assume a central role in the spectral analysis of different Italian terrains. Application of these calibrated detectors to Italian soil aims to discern and quantify the presence of radionuclides, thereby contributing into the radioprotection of the region. This prospective dimension underscores the practical application and broader implications of our calibrated systems in addressing environmental and health-related concerns.

How to cite: Siqueira Nascimento, D., Ciolini, R., Chierici, A., Chiappini, S., d'Errico, F., and Chiappini, M.: Long-term Evaluation of HPGe Calibration for Environmental Radioactivity Assessment Using IAEA-U and IAEA-Th Sources, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19068, https://doi.org/10.5194/egusphere-egu24-19068, 2024.

EGU24-19881 | Posters on site | NH9.11

Multi-level continuous monitoring of residential radon in the urban contest of Rome 

gaia soldati, maria grazia ciaccio, antonio piersanti, Valentina cannelli, and gianfranco galli

The urbanized area of Rome is largely built over volcanic deposits, characterized by  a significant radionuclides content and radon emanation potential.  A first step towards the mitigation of the indoor radon exposure is the accurate monitoring of workplaces and residential dwellings. Due to the complex interactions among many environmental parameters on different time scales, a proper assessment of radon diffusion dynamics and concentration variations can be better achieved by means of active monitoring approaches. We present here the results of one year of continuous measurements conducted in 6 premises (5 apartments and a basement) at different floors of the same building in the Esquilino district, in the historical center of Rome. The simultaneous tracking of different floors should cancel the influence of geogenic radon and of building characteristics like age, typology, and construction materials, and reveal the characteristics of the gas emanation and transport inside the buildings, and of its temporal fluctuations, with the final goal to select the most suitable preventive measures to reduce radon exposure. Conducting the experiment in the Roman urban contest, we cannot ignore the specificity of the retrieved data, affected not only by endogenous factors like heating and ventilation of the apartments, but also by exogenous factors like the urban heat islands effect.

How to cite: soldati, G., ciaccio, M. G., piersanti, A., cannelli, V., and galli, G.: Multi-level continuous monitoring of residential radon in the urban contest of Rome, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19881, https://doi.org/10.5194/egusphere-egu24-19881, 2024.

EGU24-20104 | Orals | NH9.11 | Highlight

Assessing the chemical availability and environmental fate of fallout radionuclides in cryoconite 

Caroline Clason, Harriet Davidson, Geoffrey Millward, Andrew Fisher, and Alex Taylor

Glaciers are stores for contaminants, both local and further afield in origin, that are released into the environment through anthropogenic processes. Cryoconite, a heterogenous granular material commonly found on glacier surfaces, is now known to be an efficient accumulator of contaminants such as fallout radionuclides (FRNs) and potentially toxic elements, with multiple regional studies reporting notable concentrations of radioactivity in cryoconite that far exceeds that which is found in other environmental matrices. Indeed, concentrations of FRNs in cryoconite can be as much as three orders of magnitude higher than those found in nearby proglacial sediments. While we now understand that this ‘hyper-accumulation’ of FRNs is commonplace on glaciers around the world, our understanding of the extent to which release of contaminants stored in cryoconite poses an environmental downstream risk is in its infancy. To assess both the activity concentrations and chemical availability of FRNs within cryoconite, we conducted novel sequential chemical extractions twinned with gamma spectrometry for cryoconite samples from glaciers in Arctic Sweden and Iceland. Major and minor elemental composition of cryoconite was also analysed with Wavelength Dispersive X-ray Fluorescence (WD-XRF) spectrometry. The results of these experiments demonstrate that different cryoconite-bound FRNs undergo varying degrees of solubilization, with consequences for increased contaminant mobilization under higher melt scenarios. Our work identifies a clear requirement for further research in this field in order to improve understanding of downstream environmental risk from the secondary release of legacy contaminants under continued glacier retreat.

How to cite: Clason, C., Davidson, H., Millward, G., Fisher, A., and Taylor, A.: Assessing the chemical availability and environmental fate of fallout radionuclides in cryoconite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20104, https://doi.org/10.5194/egusphere-egu24-20104, 2024.

EGU24-21822 | Orals | NH9.11

Observation and geological interpretation of the longest vertical radon profile to date: variability of radon concentrations along a 323 m deep drilling 

Rouwen Lehne, Jessica Daum, Johannes Mair, Heiner Heggemann, Christian Hoselmann, and Andreas Henk

Radon soil air measurements and associated permeability measurements are a mandatory prerequisite for the calculation of radon potentials as an important basis for the statistical derivation of an expected radon situation in a defined area. Accordingly, in the federal state of Hesse, as almost everywhere in Germany, numerous measurements have been carried out in recent years and made available to the Federal Office for Radiation Protection (BfS) for the modelling of a radon potential map of Germany, which has since been an important (sometimes the only) basis for the definition of radon precautionary areas for all federal states in Germany. The associated benefits are undoubtedly great.

From a geological perspective, however, the question arises to what extent the large lateral variability of measurable radon concentrations also exists in the vertical and, if so, whether this variability can be placed in a context with the geological development of the area under consideration. The background to this is the fact that the radon soil gas measurements usually address a depth of between 0.8 and 1 m below the ground surface, in rare cases reaching a depth of up to 2 metres.

In addition to the scientific added value, such an investigation approach is also associated with an applied benefit, as building foundations are usually founded significantly deeper than 1 m below the ground surface, which means that a significant part of the building envelope in contact not only with the soil layers, but also to the geological subsurface, must be seen decoupled from the radon concentration determined near the surface, depending on the heterogeneity of the geological bedding.

For this reason, we took a total of 175 samples along an 323 m deep research drilling in the northern Upper Rhine Graben and determined the radon concentration for these in the laboratory (= stationary). The results show a very high variability of the measurable radon concentrations, ranging from 16 Bq/m³ to 9086 Bq/m³ with a mean value of approx. 1527 Bq/m³. At the same time, the radon concentrations determined show a very good correlation with both the geological response of the drill core and the gamma log measurements carried out.

In this presentation, we would like to show the results obtained so far and look at the possibility of regionalising the measured values as well as the next work steps.

How to cite: Lehne, R., Daum, J., Mair, J., Heggemann, H., Hoselmann, C., and Henk, A.: Observation and geological interpretation of the longest vertical radon profile to date: variability of radon concentrations along a 323 m deep drilling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21822, https://doi.org/10.5194/egusphere-egu24-21822, 2024.

EGU24-3806 | ECS | PICO | G2.7

A low-cost commercial off-the-shelf GNSS receiver for space 

Gregor Moeller, Alexander Wolf, Flavio Sonnenberg, Gerald Bauer, Benedikt Soja, and Markus Rothacher

The era of tracking artificial Earth satellites using Global Navigation Satellite Systems (GNSS) began in the early 1980s when a GPS receiver was launched onboard the Landsat-4 mission. Since then, a large number of Low Earth Orbiters has utilized constantly improved GPS receivers for timing and positioning. GNSS has become a key technique not only for satellite orbit determination but also for atmosphere sounding. With the increasing popularity of miniaturized satellites in recent years, the need for an adapted GNSS payload for nanosatellites arose. Therefore, we developed a small-size, versatile payload board using commercial-off-the-shelf (COTS) low-cost multi-GNSS receivers with extremely small weight, size, and power consumption.

The receiver firmware enables multi-constellation navigation solutions and GNSS raw data output in space with a sampling rate of up to 20 Hz. With this configuration, we can retrieve the required GNSS code and carrier phase measurements, e.g. for precise orbit and attitude determination, to monitor the total air density from drag, the distribution of the electron content, or scintillation effects. The high demands on GNSS receiver performance lead to particular requirements for hardware, payload software, onboard computing, data downlink, and remote control, which will be briefly discussed in the presentation. The resulting low-cost GNSS board fits into a 0.25U form factor, and the modular design makes it a scalable and adaptable payload for CubeSat missions.

In this presentation, we will provide insight into the performance of the GNSS payload under simulated orbit conditions and highlight the necessary modifications that allow us to transform a COTS GNSS receiver into a scientific instrument for space applications.

How to cite: Moeller, G., Wolf, A., Sonnenberg, F., Bauer, G., Soja, B., and Rothacher, M.: A low-cost commercial off-the-shelf GNSS receiver for space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3806, https://doi.org/10.5194/egusphere-egu24-3806, 2024.

Real-Time Single-Frequency Precise Point Positioning (PPP) is a cost-effective and promising method for achieving highly accurate navigation at sub-meter or centimeter levels. However, its success heavily relies on real-time ionospheric state estimations to correct delays in Global Navigation Satellite System (GNSS) signals. This research employs the Dynamic Mode Decomposition (DMD) model in conjunction with global ionospheric vertical total electron content (vTEC) Root Mean Square (RMS) maps to create 24-hour forecasts of global ionospheric vTEC RMS maps. These forecasts are integrated with C1P forecast products, and the performance of L1 single-frequency positioning solutions is compared across various ionospheric correction models. The study assesses the impact of assimilating predicted RMS data and evaluates the practicality of the proposed approach using the IGRG product. The results demonstrate that the IGSG RMS prediction-based model significantly enhances positioning accuracy for up to five hours ahead, yielding results comparable to alternative models. This approach holds promise for achieving high precision navigation.

How to cite: Reuveni, Y. and Landa, V.: Advancing Real-Time GNSS Single-Frequency Precise Point Positioning through Ionospheric Corrections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5282, https://doi.org/10.5194/egusphere-egu24-5282, 2024.

EGU24-5511 | ECS | PICO | G2.7

New neutral density estimates and forecasts in the framework of project ESPRIT 

Andreas Strasser, Sandro Krauss, Manuel Scherf, Barbara Suesser-Rechberger, and Helmut Lammer

In the ongoing project ESPRIT, a goal is to investigate the contribution of the chemical composition and associated chemical reactions to the Earth’s upper atmosphere. This is realized through a combined analysis of thermospheric neutral density estimates and the exploration of external parameters of the interplanetary space, including variations in the magnetic field and the merged electric field. Regarding changes in the chemical composition of the Earth’s atmosphere, which might cause heating and cooling effects, we investigated TIMED/SABER measurements in conjunction with findings from the 1D first-principles hydrodynamic upper atmosphere model Kompot code, which shows some significant expansion in the density profile mainly based on the increased XUV flux from the Sun. The neutral mass densities were processed based on accelerometer measurements as well as on kinematic orbit information (Süsser-Rechberger et al. 2022). This allowed us to successfully process kinematic orbits for 19 different satellites at an altitude range of approximately 400 to 1300 km. Both approaches are realized using the in-house software package GROOPS. During the evaluation, significant improvements in the processing and parametrization could be achieved compared to previous solutions, especially through refined models for solar radiation pressure, the Earth’s re-radiation, the thermal radiation of the satellite itself and the consideration of the chemical composition of the atmosphere. Based on these new neutral density estimates, investigations regarding the effects of solar eruptions on the various satellites are performed and used for attempting to forecast the orbital decay of LEO satellites.

How to cite: Strasser, A., Krauss, S., Scherf, M., Suesser-Rechberger, B., and Lammer, H.: New neutral density estimates and forecasts in the framework of project ESPRIT, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5511, https://doi.org/10.5194/egusphere-egu24-5511, 2024.

EGU24-5567 | PICO | G2.7

Sequential calibration and data assimilation for predicting atmospheric variability 

Ehsan Forootan, Saeed Farzaneh, Masoud Dehvari, Leire Retegui-Schiettekatte, and Maike Schumacher

Estimating global and multi-level variations of the atmospheric variables and being able to predict them are very important for studying coupling processes within the atmosphere, and for various geodetic and space weather applications. These variables include the thermosphere neutral density, the ionospheric electron density, and the tropospheric water vapour, which are relevant to applications such as orbit determination, satellite navigation, and weather/climate monitoring. Available models have difficulties in realistic prediction of these variables due to the simplicity of their structure or sampling limitations. In this study, we present an ensemble-based simultaneous Calibration and Data Assimilation (C/DA) algorithm to integrate freely available satellite geodetic data (e.g., CHAMP, GRACE(-FO), Swarm, and GNSS) into empirical models with the focus on improving the predictability of atmospheric variables. The improved model, called `C/DA-model' will be assessed in relevant geodetic and space weather applications. For demonstration, the CDA-NRLMSISE-00 is examined during seven periods with relatively high geomagnetic activity and CDA-IRI-ZWD during extensive rainy events.

How to cite: Forootan, E., Farzaneh, S., Dehvari, M., Retegui-Schiettekatte, L., and Schumacher, M.: Sequential calibration and data assimilation for predicting atmospheric variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5567, https://doi.org/10.5194/egusphere-egu24-5567, 2024.

The upcoming low earth orbit (LEO) constellations can bring new opportunities for ionospheric sounding below the LEO satellite altitude. The CENTISPACETM LEO satellites working with an altitude of 700 km broadcasting navigation augmentation signals to the ground stations. This study established a regional bottomside ionospheric map (RBIM) using navigation augmentation signals from two CENTISPACETM satellites on April 1, 2023, under moderate solar activity and quiet geomagnetic conditions. The RBIM accuracy was subsequently validated through comparison with multiple datasets, including Global and Regional Ionospheric Maps (GIMs and RIMs) constructed from ground-based GNSS observations, as well as the differential Slant Bottomside Electron Content (dSBEC) derived from LEO observations. To build the RBIM, the vertical bottomside electron content (VBEC) is fitted by two distinct methods, which are grid map and polynomial methods. The root mean square (RMS) values of the RBIM fitting residuals are 1.2 TECU and 0.7 TECU for the two methods, respectively. The RBIM precision evaluated by LEO dSBEC is better than 1.0 TECU. Comparing the VBEC from established RBIM to the GIM/RIM indicates that the RMS values mostly within 3-8 TECU, which can attribute to the limited modelling precision of the latter two models. What’s more, the RBIM facilitates the probe of the proportional variation of the VBEC over the total electron content using experimental data. The results derived from LEO observations indicate that the VBEC proportion is 83% at noon and 53% at night in the north mid-latitude region, presenting a reduction of 35.36%, which is more realistic than that calculated values from the empirical International Reference Ionosphere (IRI-2020) model (4.65%). Thus, the RBIM can not only benefit LEO navigation augmentation but also provide significant observations on the vertical distribution of ionospheric electron content.

How to cite: He, R., Li, M., Li, W., and Zhang, Q.: Estimating bottomside ionosphere electron content using navigation augmentation observations from two CENTISPACETM LEO satellites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8540, https://doi.org/10.5194/egusphere-egu24-8540, 2024.

EGU24-9779 | ECS | PICO | G2.7

Monitoring short-term dynamic motion with single-frequency observations from a low-cost GNSS receiver 

Mert Bezcioglu, Berkay Bahadur, Ahmet Anil Dindar, and Cemal Ozer Yigit

In the last few decades, GNSS observations have frequently been used in Structural Health Monitoring (SHM) and Earthquake Early Warning (EEW) systems. The primary advantage of high-frequency GNSS techniques is to detect displacements directly in a terrestrial reference frame compared to conventional geotechnical sensors. Among GNSS techniques, the real-time kinematic (RTK) has predominantly been employed in dynamic displacement monitoring because it provides high accuracy simultaneously. Nevertheless, an external GNSS infrastructure is essential in RTK applications to achieve high positioning accuracy, which restricts its use in possible mega earthquake events. On the other hand, Precise Point Positioning (PPP), which can provide high positioning accuracy with a standalone GNSS receiver on a global scale, emerged as an alternative to traditional GNSS techniques. However, the requirement of an external internet connection for real-time PPP applications is the main restriction of this technique in the employment of possible mega earthquake events like the RTK technique. Instead, the variometric approach (VA) can provide high accuracy in determining dynamic behaviors with a standalone GNSS receiver and broadcast ephemeris only, which means it doesn't require any external infrastructure and connection. Furthermore, the emergence of new navigation systems, such as Galileo and BeiDou, brings considerable opportunities to improve the performance of the VA technique in detecting dynamic behaviors. Thanks to progress in GNSS receiver technology, low-cost GNSS receivers have been introduced and taken considerable attention from the GNSS community. Their more compact design makes low-cost GNSS receivers very usable for establishing monitoring networks in harsh environments, such as high-rise buildings and bridges. In this context, this study aims to evaluate the capability of the VA technique with a low-cost GNSS receiver in detecting horizontal dynamic motion simultaneously. For this purpose, this study employs single-frequency (SF) observations of GPS, GLONASS, Galileo, and BeiDou satellites from the u-blox ZED-F9P receiver for the VA technique. Harmonic motions from 5 to 20 mm with frequencies between 0.3 and 5.0 Hz were generated by a single-axis shake table to analyze the capability of the SF-VA technique in detecting structural motion. Also, a simulation of Mw 6.9 Kobe, 1995 earthquake was performed using the shake table to understand the feasibility of the SF-VA technique in possible EEW systems. In the evaluation, displacements from the Linear Variable Differential Transformer (LVDT) were selected as the reference to assess the capability of the SF-VA technique. The results indicated that the peak frequency value of short-term harmonic oscillations up to 5 Hz can be detected with the SF-VA technique adopting GNSS observations from the low-cost receiver. Besides, the results demonstrated that the SF-VA technique can determine the strong ground motions resulting from mega earthquakes at mm-level.

How to cite: Bezcioglu, M., Bahadur, B., Dindar, A. A., and Yigit, C. O.: Monitoring short-term dynamic motion with single-frequency observations from a low-cost GNSS receiver, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9779, https://doi.org/10.5194/egusphere-egu24-9779, 2024.

EGU24-10188 | PICO | G2.7

A new low-cost GNSS instrument for monitoring of ground motions and critical infrastructures within the Greek “Supersite” 

Athanassios Ganas, George Mavropoulos, Ioannis Karamitros, Konstantinos Nikolakopoulos, Vassiliki Charalampopoulou, Dimitrios Anastasiou, Theodoros Athanassopoulos, Aggeliki Kyriou, and Varvara Tsironi

There is a continuous need for integrating multi-parameter instrumental observations and measurements with Satellite Earth observation data towards continuous monitoring of the environment and infrastructures. This task attains more importance within the tectonic and seismically active area of the Greek "Supersite" (Corinth Gulf, Ionian Islands, etc.). The significant level of geohazards in this region have made necessary the implementation of new technological approaches that could offer reliable augmentation to permanent networks (both geodetic and seismological). In this contribution, we demonstrate the design, construction and installation of a new technological infrastructure that is based on the collaboration of a multidisciplinary research team and on low-cost equipment. Our low-cost instrumentation includes a multi-GNSS dual-frequency chip (Ublox ZED F9P module) mounted on a Raspberry-Pi 4 compute module IO board together with an industry-standard MEMS accelerometer. It provides signal tracking for most of GNSS systems (GPS, GLONASS, Galileo and BeiDou). The GNSS data are collected 24/7/365, quality-checked and processed by use of open-source software. The combined-synergistic use of these new sensors is compatible with ground motion data provided by GNSS reference stations and accelerometers used by seismic agencies. Current work includes the collection, homogenization, processing and archiving of daily data from three test sites using 4G telemetry. The GNSS data support the on-going, pre-operational monitoring of three test sites together with InSAR Copernicus data (Tsironi et al. 2022).

 

Tsironi, V., Ganas, A., Karamitros, I., Efstathiou, E., Koukouvelas, I., Sokos, E. 2022. Kinematics of Active Landslides in Achaia (Peloponnese, Greece) through InSAR Time Series Analysis and Relation to Rainfall Patterns. Remote Sens., 14(4), 844. https://doi.org/10.3390/rs14040844

How to cite: Ganas, A., Mavropoulos, G., Karamitros, I., Nikolakopoulos, K., Charalampopoulou, V., Anastasiou, D., Athanassopoulos, T., Kyriou, A., and Tsironi, V.: A new low-cost GNSS instrument for monitoring of ground motions and critical infrastructures within the Greek “Supersite”, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10188, https://doi.org/10.5194/egusphere-egu24-10188, 2024.

The sensitivity of Global Navigation Satellite Systems (GNSS)  receivers to ionospheric disturbances and their constant growth is nowadays resulting in an increased concern of GNSS-users about the impacts of ionospheric disturbances at mid-latitudes. The geomagnetic storm of June 22-23, 2015, is an example of a rare phenomenon of a spill-over of equatorial plasma bubbles well north from their habitual region of ~+/- 20º around the magnetic equator.

We study the occurrence of small- and medium-scale irregularities in Southern Europe by analysing the behaviour of the amplitude scintillation index S4 and of the Rate Of Total Electron Content Index (ROTI) during the geomagnetic storm of June 22-23, 2015. To the scope, we leverage data obtained by local GNSS receivers for scintillation monitoring located in Lisbon (Portugal) and Lampedusa (Italy). Data is complemented with total electron content (TEC) data both from the local GNSS receivers and from global ionospheric maps.

The multi-source data allows for a better understanding of the ionospheric dynamic during the studied event.

How to cite: Morozova, A., Estaço, D., Spogli, L., and Barata, T.: Scintillations in the Southern Europe during the geomagnetic storm of June 2015: analysis of a plasma bubbles spill-off using local data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10792, https://doi.org/10.5194/egusphere-egu24-10792, 2024.

EGU24-12608 | ECS | PICO | G2.7

NeGIX and TEGIX: two new indices to characterize the topside ionosphere with Swarm 

Juan Andrés Cahuasquí, Mohammed Mainul Hoque, Norbert Jakowski, Dmytro Vasylyev, Stephan Buchert, Grzegorz Nykiel, Martin Kriegel, Paul David, Youssef Tagargouste, and Jens Berdermann

Since its launch in 2013, ESA’s Swarm satellite constellation has pushed the frontiers of space weather research and monitoring by means of its broad spectrum of high-quality experiments on-board. Particularly, Swarm observations are being used to globally characterize small- to mid-scale perturbations in the topside ionosphere that may cause severe amplitude and phase scintillations of trans-ionospheric radio signals. Ionospheric scintillation can cause radio signal outage, as well as disruption of modern technological systems used for telecommunication, navigation and remote sensing.

While performing the Swarm DISC project “Monitoring of Ionospheric Gradients at Swarm (MIGRAS)”, the MIGRAS team has profited from the close orbits and synchronization of Swarm satellites Alpha (A) and Charlie (C) to develop two new products that focus on the monitoring of small- to mid-scale plasma density irregularities with horizontal spatial scales in the order of about 100 km - the electron density (Ne) Gradient Ionospheric indeX (NeGIX), and the Total Electron Content (TEC) Gradient Ionospheric indeX (TEGIX). NeGIX estimates spatial Ne gradients using Langmuir probe measurements, and TEGIX estimates spatial TEC gradients using GNSS Precise Orbit Determination (POD) data of Swarm.

In this work, we provide a comprehensive analysis of the capability of these two novel Swarm data products to characterize the perturbation state of the ionosphere at different geographic locations and conditions of geomagnetic activity. Our analysis covers the whole period of available Swarm observations to quantitively describe expected signatures of ionospheric variability, e.g. gradients at sunrise and sunset time, or equatorial crests. The analysis concentrates also on events of perturbed geomagnetic conditions to compare the performance of NeGIX and TEGIX with existing ground-based indices (e.g. GIX) and Swarm products (e.g. IPIR). Moreover, these indices have been developed technically compatible with Swarm’s and DLR’s operational data services. Therefore, our analysis validates and discusses their applicability for space weather science and purposes.

Acknowledgement: The work is funded by the MIGRAS (Monitoring of Ionospheric Gradients At Swarm) project under the Swarm DISC Subcontract Doc. no: SW‐CO‐DTU‐GS‐133, Rev: 1, 13 September 2022.

How to cite: Cahuasquí, J. A., Hoque, M. M., Jakowski, N., Vasylyev, D., Buchert, S., Nykiel, G., Kriegel, M., David, P., Tagargouste, Y., and Berdermann, J.: NeGIX and TEGIX: two new indices to characterize the topside ionosphere with Swarm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12608, https://doi.org/10.5194/egusphere-egu24-12608, 2024.

EGU24-14279 | PICO | G2.7

Tectonic monitoring with low-cost multi-GNSS installations in Greece 

Jonathan Bedford, Konstantinos Chousianitis, Athanassios Ganas, Vasiliki Mouslopoulou, Efthimios Sokos, Zafeiria Roumelioti, Konstantinos Nikolakopoulos, Christoforos Pappas, Markus Ramatschi, Carsten Falck, Benjamin Männel, Cristian Garcia, Carlos Peña, Kaan Cökerim, Elvira Latypova, Michail Gianniou, Paraskevi Io Ioannidi, Chris Pikridas, Ilias Lazos, and Vasiliki Saltogianni

In 2023, we began installing a low-cost tectonic multi-GNSS network in Greece, funded by the European Research Council. We have installed a total of 45 permanent/continuous-mode stations, with another 15-20 to be installed in 2024. Installations so far have been mainly on the Peloponnese peninsula, with the strategy of increasing spatial resolution in between the existing research and privately operated GNSS networks. Station maintenance is funded by the project (ERC StG: TectoVision) until 2027, but it is the intention that as many as possible of these stations can stay installed (as permanent installations).

The scientific purpose of the new stations is to increase spatial resolution of microplate motions in Greece but these data will also be of use to other research fields needing single- or multi-GNSS observables. Accordingly, these data are being released without embargo subject to completion of quality control checks (with the data publication and link to download to be finalized before EGU 2024).

We consider this installation campaign to be a pilot project in affordable, rapid densification of tectonic-grade GNSS stations. Part of our strategy has been to use relatively low-cost monumentation for the geodetic marker onto which the low-cost installations are installed. Most stations are connected to mains electricity supplies of public buildings, with the monumentation being installed on flat roofs of these buildings. In higher altitude areas where flat roofs are rare, we have made 3 special installations at bedrock sites, with radio telemetry linking to a radio-receiving station in the nearby villages. We use a range of telemetry solutions, with the most common being the transfer of the 30s sampling data via a router containing a Machine-to-Machine (M2M) sim card.

In this presentation, we will show data quality metrics from the initial analysis of 6-11 months of observations and compare to the time series that can be processed from more expensive receiver-antenna combinations. We will also discuss what the team has learned practically (on-site) and logistically about installing low-cost GNSS stations at scale.

How to cite: Bedford, J., Chousianitis, K., Ganas, A., Mouslopoulou, V., Sokos, E., Roumelioti, Z., Nikolakopoulos, K., Pappas, C., Ramatschi, M., Falck, C., Männel, B., Garcia, C., Peña, C., Cökerim, K., Latypova, E., Gianniou, M., Ioannidi, P. I., Pikridas, C., Lazos, I., and Saltogianni, V.: Tectonic monitoring with low-cost multi-GNSS installations in Greece, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14279, https://doi.org/10.5194/egusphere-egu24-14279, 2024.

EGU24-14661 | ECS | PICO | G2.7

Assessing measurement noises from low-cost GNSS receivers and antennas 

Ibaad Anwar and Balaji Devaraju

Observations from the Global Navigation Satellite System (GNSS) play a crucial role in numerous applications, but are prone to measurement noise, especially when utilizing low-cost receivers and antennas. These measurement noises are crucial as they significantly impact the accuracy and reliability of positional data. This study investigates the characteristics and implications of measurement noises in low-cost GNSS systems, with a particular focus on the effects of receiver and antenna quality, environmental factors, and satellite dynamics. It employs a geometry-free approach to GNSS measurement analysis, aiming to identify and quantify the various noise sources in code-pseudorange and carrier phase observations. The analysis utilized data from two low-cost GNSS stations, each equipped with a u-blox dual-frequency receiver. These stations are equipped with survey-grade and navigational antennas. Additionally, data from the IGS station IITK has been used for comparative analysis.

How to cite: Anwar, I. and Devaraju, B.: Assessing measurement noises from low-cost GNSS receivers and antennas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14661, https://doi.org/10.5194/egusphere-egu24-14661, 2024.

EGU24-14817 | ECS | PICO | G2.7

The emergence of low-cost GNSS-IR sensors for surface change monitoring: a case study of the RPR network for measuring the Rhine River level 

Makan A. Karegar, Luciana Fenoglio-Marc, Kristine M. Larson, Jürgen Kusche, and Hakan Uyanik

GNSS Interferometric Reflectometry (GNSS-IR) is redefining its role as an innovative technique in environmental sensing. However, geodetic-quality GNSS receivers and antennas are still very expensive instruments which limits their use as dedicated environmental sensors. Recently, low-cost GNSS-IR sensors have been developed for monitoring surface changes such as water level, snow depth and soil moisture. Real-time signal-to-noise ratio (SNR) observation, the key observable of ground-based GNSS-IR, can open up a range of possibilities for environmental monitoring with low cost sensors that can operate unattended for long periods of time. We have recently successfully developed a low-cost water-level sensor called Raspberry Pi Reflector (RPR) based on GNSS-IR technique (Karegar et al. 2022, Water Resources Research, 58). In spring and summer 2023, a network of eight RPRs was installed along the Rhine, the largest river in Germany, from Petersau to Sankt Goar. We installed some of these RPRs in a relatively steep and narrow middle Rhine valley, where the terrain relief around the instrument can influence the effectiveness of the GNSS-IR approach. The water level measurements provided by these sensors are used to validate the SWOT observations of surface water levels. In this presentation, we will present the results of the deployment of the RPRs and discuss the challenges associated with these low-cost sensors.

How to cite: A. Karegar, M., Fenoglio-Marc, L., M. Larson, K., Kusche, J., and Uyanik, H.: The emergence of low-cost GNSS-IR sensors for surface change monitoring: a case study of the RPR network for measuring the Rhine River level, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14817, https://doi.org/10.5194/egusphere-egu24-14817, 2024.

EGU24-14867 | ECS | PICO | G2.7

GFZRNX-QC: Advanced GNSS Data Processing and Quality Control for Multi-System Observations 

Xinghan Chen, Thomas Nischan, Zhiguo Deng, Benjamin Männel, and Jens Wickert

GFZRNX-QC software is designed to streamline the processing of Receiver Independent Exchange Format (RINEX) observations and the generation of overall information by providing a robust and efficient solution for data cleaning and quality control. With a focus on multiple Global Navigation Satellite System (multi-GNSS) observations, GFZRNX-QC offers a comprehensive approach to ensuring data accuracy and reliability. GFZRNX-QC can allow users to efficiently manage and analyze data from various GNSS receivers, especially for low-cost GNSS receivers. The software incorporates advanced algorithms for data cleaning, helping users to eliminate inconsistencies and enhance the overall quality of GNSS observations. GFZRNX-QC conducts comprehensive quality control assessments on GNSS observations. This ensures that the processed data meets the highest standards of accuracy. The software generates detailed statistical results, offering insights into the performance and reliability of observations across the five major GNSS systems. This information aids researchers and analysts in making informed decisions. GFZRNX-QC produces various outputs that can be e.g. compatible to former processing tools like teqc. This can enhance user convenience and interoperability with other geodetic processing tools.

GFZRNX-QC has been extensively tested by utilizing multi-year data from IGS stations to enable comprehensive long-term statistical analysis. By combining efficient data processing, advanced cleaning algorithms, and extensive quality control measures, GFZRNX-QC serves as a valuable tool for researchers, geodesists, and GNSS professionals seeking reliable and accurate observations and overall information from multiple satellite systems.

How to cite: Chen, X., Nischan, T., Deng, Z., Männel, B., and Wickert, J.: GFZRNX-QC: Advanced GNSS Data Processing and Quality Control for Multi-System Observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14867, https://doi.org/10.5194/egusphere-egu24-14867, 2024.

EGU24-17705 | PICO | G2.7

Atmospheric and Soil Moisture Monitoring in Agriculture Using GNSS: First Results from the MAGDA Project 

Andrea Gatti, Alessandro Fumagalli, Stefano Barindelli, and Eugenio Realini

The Meteorological Assimilation from Galileo and Drones for Agriculture (MAGDA) project aims to advance the integrated use of satellite-borne, drone-borne, and in-situ sensors, enhancing irrigation optimisation and weather hazard mitigation in agriculture. At its core, MAGDA employs low-cost Galileo-enabled GNSS ground stations for retrieving atmospheric water vapour and soil moisture. This data, combined with information from other technologies, is intended for assimilation into numerical weather prediction and hydrological models.

MAGDA’s demonstration sites are strategically located in three diverse agricultural regions of Europe: fruit plantations in Italy’s Piedmont, vineyards in France’s Burgundy, and mixed crops in Romania’s Braila county. Each of these sites is equipped with three low-cost GNSS stations, operational since mid-2023, providing valuable data for testing the efficacy and adaptability of GNSS technology in different agricultural and climatic conditions.

In addition to the three demonstration sites, MAGDA leverages data from pre-existing GNSS permanent stations across these countries. A comprehensive dataset from 397 stations in the Italy-France domain and 74 stations in the Romania domain has been downloaded. This data is specifically designed for the assimilation of GNSS-derived water vapour data, covering the entire weather model domains, complementing the localised information from the project’s targeted low-cost stations.

GNSS data processing utilises GReD’s proprietary Breva software, capable of analysing multi-frequency and multi-constellation observations. Atmospheric water vapour estimates are obtained through an undifferenced and uncombined batch least squares Precise Point Positioning (PPP) approach. This method has been employed to analyse six weather events that significantly impacted agricultural operations at the demonstration sites, two events per site.

Soil moisture results have been obtained by a newly developed module of Breva software that applies GNSS reflectometry based on the analysis of SNR measurements influenced by the humidity of the superficial soil. The methodology has been tested and validated at various previously studied sites, as well as directly at the low-cost GNSS stations established by the MAGDA project.

This work presents the preliminary results achieved in the first half of the MAGDA project, outlining encountered limitations and future development plans related to the analysis of MAGDA’s GNSS stations.

How to cite: Gatti, A., Fumagalli, A., Barindelli, S., and Realini, E.: Atmospheric and Soil Moisture Monitoring in Agriculture Using GNSS: First Results from the MAGDA Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17705, https://doi.org/10.5194/egusphere-egu24-17705, 2024.

EGU24-17764 | ECS | PICO | G2.7

GNSS low-cost prototype on ship for caching tsunami wave propagation  

Paul Jarrin, Lucie Rolland, Maurin Vidal, Pierre Sakic, Frédérique Leclerc, Jean-Xavier Dessa, and Sylvain Palagonia

Ship navigation data records are proposed to be complementary information for monitoring offshore tsunami currents following great earthquakes. Offshore GPS measurements on the research vessel Kilo Moana of the University of Hawaii following the 2010 Mw 8.8 Maule earthquake have illustrated the potential of GPS kinematic positioning solutions, together with a filtering approach, for detecting the ship's vertical displacement promoted by the tsunami travel velocity. However, kinematic positioning of GPS observations on ships is challenging due to the load, ship speed, and wavefield changes on the open ocean that might produce fast changes in the ship's drift and vertical motion. Wavefield could also introduce additional noise frequencies to the GPS positioning, thus decreasing its precision. Herein, we present a dual-frequency Global Satellite Navigation System (GNSS) low-cost prototype based on the Septentrio Mosaic-X5 card and a low-cost AS-ANT2BCAL antenna. Such a low-cost GNSS station has been installed on a non-commercial ship fleet in order to assess the precision and noise content of offshore GNSS positioning and ionosphere Total Electron Content measurements. We discuss our preliminary results by comparing the precision of the multi-GNSS solution (GPS, GLONASS, Galileo) relative to the one from only the GPS solution using both long-baselines and Precise Point Positioning approaches in post-processing mode. In the second step, we simulate a real-time multi-GNSS positioning solution to evaluate their ability to catch wavefield changes. We finally discuss the detectability of tsunamis with the newly developed GNSS low-cost prototype under various conditions.

How to cite: Jarrin, P., Rolland, L., Vidal, M., Sakic, P., Leclerc, F., Dessa, J.-X., and Palagonia, S.: GNSS low-cost prototype on ship for caching tsunami wave propagation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17764, https://doi.org/10.5194/egusphere-egu24-17764, 2024.

EGU24-1261 | Orals | GM3.1

Machine-learning based 3D point cloud classification and multitemporal change analysis with simulated laser scanning data using open source scientific software 

Bernhard Höfle, Ronald Tabernig, Vivien Zahs, Alberto M. Esmorís Pena, Lukas Winiwarter, and Hannah Weiser

AIM: We will present how virtual laser scanning (VLS), i.e., simulation of realistic LiDAR campaigns, can be key for applying machine/deep learning (ML/DL) approaches to geographic point clouds. Recent results will be shown for semantic classification and change analysis in multitemporal point clouds using exclusively open source scientific software.

MOTIVATION: Laser scanning is able to deliver precise 3D point clouds which have made huge progress in research in geosciences over the last decade. Capturing multitemporal (4D: 3D + time) point clouds enables to observe and quantify Earth surface process activities, their complex interactions and triggers. Due to the large size of 3D/4D datasets that can be captured by modern systems, automatic methods are required for point cloud analysis. Machine learning approaches applied to geographic point clouds, in particular DL, have shown very promising results for many different geoscientific applications [1,2].

METHODS & RESULTS: While new approaches for deep neural networks are rapidly developing [1], the bottleneck of sufficient and appropriate training data (typically annotated point clouds) remains the major obstacle for many applications in geosciences. Those data hungry learning methods depend on proper domain representation by training data, which is challenging for natural surfaces and dynamics, where there is high intra-class variability. Synthetic LiDAR point clouds generated by means of VLS, e.g., with the open-source simulator HELIOS++ [3], can be a possible solution to overcome the lack of training data for a given task. In a virtual 3D/4D scene representing the target surface classes, different LiDAR campaigns can be simulated, with all generated point clouds being automatically annotated. VLS software like HELIOS++ allows to simulate any LiDAR platform and settings for a given scene, which offers high potential for data augmentation and the creation of training samples tailored to specific applications. In recent experiments [1], purely synthetic training data could achieve similar performances to costly labeled training data from real-world acquisitions for semantic scene classification.

Furthermore, surface changes can be introduced to create dynamic VLS scenes (e.g., erosion, accumulation, movement/transport). Combining LiDAR simulation with automatic change analysis, such as offered by the open-source scientific software py4dgeo [5], enables to perform ML for change analysis in multitemporal point clouds [6]. Recent results show that rockfall activity mapping and classification for permanent laser scanning data can be successfully implemented by combining HELIOS++, py4dgeo and the open-source framework VL3D, which can be used for investigating various ML/DL approaches in parallel.

CONCLUSION: Expert domain knowledge (i.e., definition of proper 3D/4D scenes) and the power of AI can be closely coupled in VLS-driven ML/DL approaches to analyze 3D/4D point clouds in the geosciences. Open-source scientific software already offers all required components (HELIOS++, VL3D, py4dgeo). 

REFERENCES:

[1] Esmorís Pena, A. M., et al. (2024): Deep learning with simulated laser scanning data for 3D point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing. under revision.

[2] Winiwarter, L., et al. (2022): DOI: https://doi.org/10.1016/j.rse.2021.112772 

[3] HELIOS++: https://github.com/3dgeo-heidelberg/helios

[4] VL3D framework: https://github.com/3dgeo-heidelberg/virtualearn3d

[5] py4dgeo: https://github.com/3dgeo-heidelberg/py4dgeo

[6] Zahs, V. et al. (2023): DOI: https://doi.org/10.1016/j.jag.2023.103406

How to cite: Höfle, B., Tabernig, R., Zahs, V., Esmorís Pena, A. M., Winiwarter, L., and Weiser, H.: Machine-learning based 3D point cloud classification and multitemporal change analysis with simulated laser scanning data using open source scientific software, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1261, https://doi.org/10.5194/egusphere-egu24-1261, 2024.

EGU24-1640 | ECS | Posters on site | GM3.1

Automatic Classification of Surface Activity Types from Geographic 4D Monitoring Combining Virtual Laser Scanning, Change Analysis and Machine Learning 

Vivien Zahs, Bernhard Höfle, Maria Federer, Hannah Weiser, Ronald Tabernig, and Katharina Anders

We advance the characterization of landscape dynamics through analysis of point cloud time series by integrating virtual laser scanning, machine learning and innovative open source methods for 4D change analysis. We present a novel approach for automatic identification of different surface activity types in real-world 4D geospatial data using a machine learning model trained exclusively on simulated data.

Our method focuses on classifying surface activity types based on spatiotemporal features. We generate training data using virtual laser scanning of a dynamic coastal scene with artificially induced surface changes. Scenes with surface change are generated using geographic knowledge and the concept of 4D objects-by-change (4D-OBCs) [1, 2], which represent spatiotemporal subsets of the scene that exhibit change with similar properties. A realistic 3D scene modelling is essential for accurately replicating the dynamic nature of coastal landscapes, where morphological changes are driven by both natural processes and anthropogenic activities.

The Earth's landscapes exhibit complex dynamics, spanning large spatiotemporal scales, from high-mountain glaciers to sandy coastlines. The challenge lies in effectively detecting and classifying diverse surface activities with varying magnitudes, spatial extents, velocities, and return frequencies. Effective characterization of these dynamics is crucial for understanding the underlying environmental processes and their interplay with human activities. Supervised machine learning classification of surface activities from point cloud time series is challenging due to the limited availability of comprehensive and diverse real-world datasets for training and validation. Our approach combines virtual laser scanning with machine learning-based classification, enabling the generation of comprehensive training datasets covering the full spectrum of expected change patterns [3].

In our approach, the simulation of LiDAR point clouds is performed in the open-source framework HELIOS++ [4, 5]. HELIOS++ allows the flexible simulation of custom LiDAR campaigns with diverse acquisition modes and settings together with automatic annotations of artificially induced surface changes. We train a supervised machine learning model to classify synthetic 4D-OBCs into typical surface activity types of a sandy beach (e.g. dune erosion/accretion, sediment transport, etc.). Moreover, we investigate descriptors for 4D-OBCs, assessing their suitability for representing general types of surface activity (transferable between use cases) and types specific to particular surface processes.

We evaluate our model for 4D-OBC classification in terms of its capacity to discriminate surface activity types in a real-world dataset of a sandy beach in the Netherlands [6]. 4D-OBCs are extracted, classified into our target classes and validated with manually labelled reference data based on expert evaluation.

Our study showcases the efficacy of coupling virtual laser scanning, innovative open-source 4D change analysis methods, and machine learning for classifying natural surface changes [7]. Our findings not only contribute to advancing the understanding of landscape dynamics but also provide a promising approach to mitigating environmental challenges.

REFERENCES

[1] Anders et al. (2022): DOI: https://doi.org/10.5194/egusphere-egu22-4225

[2] py4dgeo: https://github.com/3dgeo-heidelberg/py4dgeo 

[3] Zahs et al. (2022): DOI: https://doi.org/10.1016/j.jag.2023.103406

[4] HELIOS++: https://github.com/3dgeo-heidelberg/helios

[5] Winiwarter et al. (2022): DOI: https://doi.org/10.1016/j.rse.2021.112772 

[6] Vos et al. (2022): DOI: https://doi.org/10.1038/s41597-022-01291-9

[7] CharAct4D: www.uni-heidelberg.de/charact4d

How to cite: Zahs, V., Höfle, B., Federer, M., Weiser, H., Tabernig, R., and Anders, K.: Automatic Classification of Surface Activity Types from Geographic 4D Monitoring Combining Virtual Laser Scanning, Change Analysis and Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1640, https://doi.org/10.5194/egusphere-egu24-1640, 2024.

The acquisition of aerial photographs for cartographic applications started in the 1930s, and more intensively after World War II. Such old, often panchromatic, imagery offers metre to sub-metre scale spatial resolution over landscapes that have significantly evolved over the decades. Before the appearance of the first digital aerial camera systems at the end of the 20th Century, surveys were performed with analogue metric cameras, with images acquired on films or glass plates and, next, developed on photo papers. In Europe and North America, several institutions hold unique collections of historical aerial photographs having local, national and, in some cases, colonial coverages. They represent invaluable opportunities for environmental studies, allowing the comparison with today’s land use land cover, and the analysis of long-term surface displacements.

Initially, the photogrammetric processing of analogue aerial photographs would require expensive equipment, specialised operators, and significant processing time. Thanks to the digital revolution of the past two decades and the development of modern digital photogrammetric approaches, the processing of this type of image datasets has become less cumbersome, time consuming and expensive, at least in theory. In practice, this is more complex, with digitising and processing issues related to the ageing and quality of conservation of the aerial photographs, the potential distortions created during the digitising process, and the lack of ancillary data, such as, flight plans, and camera calibration reports. The limited overlap between photographs, typically 60 % and 10-20 %, along-track and across-track, respectively, make their processing with Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry poorly reliable to accurately reconstruct the topography and orthorectify the images. Given the fact that some collections reach up to millions of historical aerial photographs, the digitising, pre-processing, and photogrammetric processing of these images remain a challenge that must be properly tackle if we would like to ensure their preservation and large-scale valorisation.

In the present work, we describe the mass-digitising, digital image pre-processing and photogrammetric processing approaches implemented at the Royal Museum for Central Africa (RMCA, Belgium) to preserve and valorise the collection of >320,000 historical aerial photographs conserved in this federal institution. This imagery was acquired between the 1940’s and the 1980’s, over Central Africa, and mostly D.R. Congo, Rwanda and Burundi. For the digitising, a system of parallelized flatbed scanners controlled by a Linux computer and a self-developed software allows speeding-up the scanning of the entire collection in only few years. A series of Python scripts were developed and combined to allow a swift pre-processing that prepare and optimise the digitised images for photogrammetric processing. Finally, a SfM-MVS photogrammetric approach adapted to historical aerial photos is used. Examples of application for geo-hydrological hazards studies in the western branch of the East African Rift are shown.

How to cite: Smets, B., Dille, A., Dewitte, O., and Kervyn, F.: Digitising, pre-processing and photogrammetric processing of historical aerial photographs for the production of high resolution orthomosaics and the study of geohazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2356, https://doi.org/10.5194/egusphere-egu24-2356, 2024.

EGU24-4399 | ECS | Posters on site | GM3.1

Evaluating the efficacy of multitemporal TLS and UAS surveys for quantifying wind erosion magnitudes of sand dune topography 

László Bertalan, Gábor Négyesi, Gergely Szabó, Zoltán Túri, and Szilárd Szabó

Wind erosion constitutes a prominent land degradation process in regions of Hungary characterized by low annual precipitation. In these areas, it poses significant challenges to agricultural productivity and adversely impacts soil and environmental quality. Presently, human activities exert a more pronounced influence on the endangered areas of Hungary in comparison to climate-related factors. It is noteworthy that the wind erodibility of Hungarian soils not only poses a soil conservation challenge but also gives rise to economic ramifications, such as nutrient loss, as well as environmental and human health concerns. Within agricultural landscapes, wind erosion contributes to the removal and transportation of the finest and biologically active soil fractions, rich in organic matter and nutrients.

High-resolution topographic surveys have become integral for assessing volumetric changes in sand dune mobility and mapping wind erosion. While Unmanned Aerial Systems (UAS) surveys have been extensively employed for erosion rates exceeding the decimeter scale, Terrestrial Laser Scanning (TLS) surveys have demonstrated efficiency in capturing more extensive negative erosional forms, even in a vertical orientation. To enhance the field of view, a mounting framework can be implemented to elevate the TLS. However, determining centimeter-scale material displacement in flat terrain conditions remains challenging and requires an increased number of scanning positions.

To identify optimal settings for surveying centimeter-scale wind erosion magnitudes, we conducted combined multi-temporal TLS and UAS surveys at the Westsik experimental site near Nyíregyháza during the spring of 2023. This site features dune topography with a height of 6 meters. Our investigations encompassed various UAS image acquisition modes, involving different flight altitudes and camera settings, utilizing a DJI Matrice M210 RTK v2 drone and a Zenmuse X7 24 mm lens. Additionally, we generated diverse point clouds through various scanning scenarios using a Trimble X7 TLS device. In the data processing phase, we explored multiple co-registration algorithms to address the challenge of larger Root Mean Square Error (RMSE) in Digital Terrain Models (DTMs) from UAS Structure from Motion (SfM) compared to the actual wind erosion rates.

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The research is supported by the NKFI K138079 project.

How to cite: Bertalan, L., Négyesi, G., Szabó, G., Túri, Z., and Szabó, S.: Evaluating the efficacy of multitemporal TLS and UAS surveys for quantifying wind erosion magnitudes of sand dune topography, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4399, https://doi.org/10.5194/egusphere-egu24-4399, 2024.

EGU24-5142 | Posters on site | GM3.1 | Highlight

Four nationwide Digital Surface Models from airborne historical stereo-images 

Christian Ginzler, Livia Piermattei, Mauro Marty, and Lars T. Waser

Historical aerial images, captured by film cameras in the previous century, have emerged as valuable resources for quantifying Earth's surface and landscape changes over time. In the post-war period, historical aerial images were often acquired to create topographic maps, resulting in the acquisition of large-scale aerial photographs with stereo coverage. Using photogrammetric techniques on stereo-images enables extracting 3D information to reconstruct Digital Surface Models (DSMs), and orthoimages.

This study presents a highly automated photogrammetric approach for generating nationwide DSMs for Switzerland at 1 m resolution using aerial stereo-images acquired between 1979 and 2006. The 8-bit scanned images, with known exterior and interior orientation, were processed using BAE Systems' SocetSet (v5.6.0) with the "Next-Generation Automatic Terrain Extraction" (NGATE) package for DSM generation. The primary objective of the study is to derive four nationwide DSMs for the epochs 1979-1985, 1985-1991, 1991-1998, and 1998-2006. The study assesses DSM quality in terms of vertical accuracy and completeness of image matching across different land cover types, with a focus on forest dynamics and management research.

The elevation accuracy of the generated DSMs was assessed using two reference datasets. Firstly, the elevation differences between a nationwide reference Digital Terrain Model (DTM - swissAlti3d 2017 by Swisstopo) and the generated DSMs were calculated on points classified as "sealed surface". Secondly, elevation values of the DSMs were compared to approximately 500 independent geodetic points distributed across the country. Six study areas were chosen to assess completeness, and it was calculated as the percentage of successfully matched points to the potential total number of matched points within a predefined area. This assessment was conducted for six land cover classes based on the land cover/land-use statistics dataset from the Federal Office of Statistics.

Across the entire country, the median elevation accuracy of the DSMs on sealed points ranges between 0.28 to 0.53 m, with a Normalized Median Absolute Deviation (NMAD) of around 1 m (maximum 1.41 m) and an RMSE of a maximum of 3.90 m. The elevation differences between geodetic points and DSMs show higher accuracy, with a median value of a maximum of 0.05 m and an NMAD smaller than 1 m. Completeness results reveal mean completeness between 64 % to 98 % for the classes "glacial and perpetual snow" and "sealed surfaces," respectively and 93 % specifically for the “closed forest” class.

This work demonstrates the feasibility of generating accurate DSM time series (spanning four epochs) from historical scanned images for the entire Switzerland in a highly automated manner. The resulting DSMs will be available upon publication, providing an excellent opportunity to detect major surface changes, such as forest dynamics.

How to cite: Ginzler, C., Piermattei, L., Marty, M., and Waser, L. T.: Four nationwide Digital Surface Models from airborne historical stereo-images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5142, https://doi.org/10.5194/egusphere-egu24-5142, 2024.

EGU24-5670 | ECS | Posters on site | GM3.1

Enhancing 3D Feature-based Landslide Monitoring Efficiency by Integrating Contour Lines in Laser Scanner Point Clouds 

Kourosh Hosseini, Jakob Hummelsberger, Daniel Czerwonka-Schröder, and Christoph Holst

Landslides are a pervasive natural hazard with significant societal and environmental impacts. In addressing the critical need for accurate landslide detection and monitoring, our previous research introduced a feature-based monitoring method enhanced by histogram analyses, straddling a middle ground between point-based and point cloud-based methods. This paper expands upon that foundation, introducing an innovative contour line extraction technique from various epochs to precisely identify areas prone to deformation. This refined focus diverges from conventional methodologies that analyze entire point clouds. By applying on regions where contour lines do not match, indicating potential ground movement, we significantly elevate the efficiency and precision of our feature-based monitoring system.

 

One of the principal challenges of feature-based monitoring is managing a substantial number of outliers. Our prior research tackled this issue effectively by integrating feature tracking with histogram analysis, thereby filtering these outliers from the final results. However, the process of extracting features from each patch and matching them with corresponding patches from different epochs was time-intensive.

 

The incorporation of contour line extraction into our workflow, using high-resolution laser scanner data, allows for a more focused and efficient analysis. We can now identify and analyze areas of landscape alteration with greater accuracy. This approach limits the application of feature tracking and histogram analysis to these critical areas, thus streamlining the process and significantly reducing computational demands. This focused methodology not only accelerates data processing but also enhances the accuracy of landslide predictions.

 

Our findings indicate a substantial improvement in the efficiency of landslide monitoring methods. This methodology represents a promising advancement in geospatial analysis, particularly for environmental monitoring and risk management in regions susceptible to landslides. This research contributes to the ongoing efforts to develop more effective, efficient, and accurate approaches to landslide monitoring, ultimately aiding in better informed and timely decision-making processes for hazard mitigation and risk management.

How to cite: Hosseini, K., Hummelsberger, J., Czerwonka-Schröder, D., and Holst, C.: Enhancing 3D Feature-based Landslide Monitoring Efficiency by Integrating Contour Lines in Laser Scanner Point Clouds, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5670, https://doi.org/10.5194/egusphere-egu24-5670, 2024.

EGU24-5674 | ECS | Orals | GM3.1

Piecewise-ICP: Efficient Registration of 4D Point Clouds for Geodetic Monitoring 

Yihui Yang, Daniel Czerwonka-Schröder, and Christoph Holst

The permanent terrestrial laser scanning (PLS) system has opened the possibilities for efficient data acquisition with high-temporal and spatial resolution, thus allowing for improved capture and analyses of complex geomorphological changes on the Earth's surface. Accurate georeferencing of generated four-dimensional point clouds (4DPC) from PLS is the prerequisite of the following change analysis. Due to the massive data volume and potential changes between scans, however, efficient, robust, and automatic georeferencing of 4DPC remains challenging, especially in scenarios lacking signalized and reliable targets. This georeferencing procedure can be typically realized by designating a reference epoch and registering all other scans to this epoch. Addressing the challenges in targetless registration of topographic 4DPC, we propose a simple and efficient registration method called Piecewise-ICP, which first segments point clouds into piecewise patches and aligns them in a piecewise manner.

Assuming the stable areas on monitored surfaces are locally planar, supervoxel-based segmentation is employed to generate small planes from adjacent point clouds. These planes are then refined and classified by comparing defined correspondence distances to a monotonically decreasing distance threshold, thus progressively eliminating unstable planes in an efficient iterative process as well as preventing local minimization in the ICP process. Finally, point-to-plane ICP is performed on the centroids of the remaining stable planes. We introduce the level of detection in change analysis to determine the minimum distance threshold, which mitigates the influence of outliers and deformed areas on registration accuracy. Besides, the spatial distribution of empirical registration uncertainties on registered point clouds is derived based on the variance-covariance propagation law.

Our registration method is demonstrated on two datasets: (1) Synthetic point cloud time series with defined changes and transformation parameters, and (2) a 4DPC dataset from a PLS system installed in the Vals Valley (Tyrol, Austria) for monitoring a rockfall. The experimental results show that the proposed algorithm exhibits higher registration accuracy compared to the existing robust ICP variants. The real-time capability of Piecewise-ICP is significantly improved owing to the centroid-based point-to-plane ICP and the efficient iteration process.

How to cite: Yang, Y., Czerwonka-Schröder, D., and Holst, C.: Piecewise-ICP: Efficient Registration of 4D Point Clouds for Geodetic Monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5674, https://doi.org/10.5194/egusphere-egu24-5674, 2024.

EGU24-5757 | Posters on site | GM3.1

Arctic puzzle: pioneering a shrimp habitat model in topographically complex Disko Bay (West Greenland) 

Diana Krawczyk, Tobias Vonnahme, Ann-Dorte Burmeister, Sandra Maier, Martin Blicher, Lorenz Meire, and Rasmus Nygaard

Our study focuses on the geologically, topographically, and oceanographically complex region of Disko Bay in West Greenland. Disko Bay is also considered a marine biodiversity hotspot in Greenland. Given the impact of commercial fishing on seafloor integrity in the area, seafloor habitats studies are crucial for sustainable use of marine resources. One of the key fishery resources in Greenland, as well as in the North Atlantic Ocean, is northern shrimp.

In this study we analyzed multiple (1) monitoring datasets from 2010 to 2019, including data from shrimp and fish surveys, commercial shrimp fishery catches, satellite chlorophyll data, and (2) seafloor models, encompassing high-resolution (25 x 25 m) multibeam data with a low-resolution (200 x 200 m) IBCAO grid. Using multivariate regression analysis and spatial linear mixed-effect model we assessed the impact of physical (water depth, bottom water temperature, sediment type), biological (chlorophyll a, Greenland halibut predation), and anthropogenic factors (shrimp fishery catch and effort) on shrimp density in the area. The resulting high-resolution predictive model of northern shrimp distribution in Disko Bay is the first model of this kind developed for an Arctic area.

Our findings reveal that shrimp density is significantly associated with static habitat factors, namely sediment type and water depth, explaining 34% of the variation. The optimal shrimp habitat is characterized by medium-deep water (approximately 150-350 m) and mixed sediments, primarily in the north-eastern, south-eastern, and north-western Disko Bay. This pioneering study highlights the importance of seafloor habitat mapping and modeling, providing fundamental geophysical knowledge necessary for long-term sustainable use of marine resources in Greenland.

The developed high-resolution model contributes to a better understanding of detailed patterns in northern shrimp distribution in the Arctic, offering valuable insights for stock assessments and sustainable fishery management. This novel approach to seafloor habitat mapping supports the broader goal of ensuring the responsible utilization of marine resources, aligning with principles of environmental conservation and fisheries management. Our work serves as a foundation for ongoing efforts to balance economic interests with the preservation of marine ecosystems, fostering a harmonious coexistence between human activities and the fragile Arctic environment.

How to cite: Krawczyk, D., Vonnahme, T., Burmeister, A.-D., Maier, S., Blicher, M., Meire, L., and Nygaard, R.: Arctic puzzle: pioneering a shrimp habitat model in topographically complex Disko Bay (West Greenland), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5757, https://doi.org/10.5194/egusphere-egu24-5757, 2024.

EGU24-10361 | ECS | Orals | GM3.1

A Time-Series Analysis of Rockfall Evolution in a Coastal Region Using Remote Sensing Data 

Aliki Konsolaki, Emmanuel Vassilakis, Evelina Kotsi, Michalis Diakakis, Spyridon Mavroulis, Stelios Petrakis, Christos Filis, and Efthymios Lekkas

The evolution of technology, particularly the integration of Unmanned Aerial Systems (UAS), earth observation datasets, and historical data such as aerial photographs, stand as fundamental tools for comprehending and reconstructing surface evolution and potential environmental changes. In addition, the active geodynamic phenomena in conjunction with climate crisis and the increasing frequency of extreme weather phenomena can cause abrupt events such as rockfalls and landslides, altering completely the morphology on both small and large scales.

This study deals generally with the temporal evolution of landscapes and specifically focuses on the detection and quantification of a significant rockfall event that occurred at Kalamaki Beach on Zakynthos Island, Greece – a very popular summer destination. Utilizing UAS surveys conducted in July 2020 and July 2023, this research revealed a rockfall that has significantly altered the coastal morphology. During this period, two severe natural phenomena occurred, one of which could potentially be the cause of this rockfall event. Initially, the Mediterranean hurricane (‘medicane’) ‘Ianos’ made landfall in September 2020, affecting a large part of the country including the Ionian Islands. The result was severe damage to property and infrastructures, along with human casualties, induced by intense precipitation, flash flooding, strong winds, and wave action. Second, in September of 2022, an ML=5.4 earthquake struck between Cephalonia and Zakynthos Islands in the Ionian Sea, triggering considerable impact in both islands. The study employs satellite images postdating these natural disasters, to detect the source of the rockfall in Kalamaki Beach. Additionally, historical analog aerial images from 1996 and 2010 were used as assets for understanding the surface’s evolution. For the quantitative analysis, we applied 3D semi-automated change detection techniques such as the M3C2 algorithm, to estimate the volume of the rockfall.

The results provide insights into the complex interplay between natural disasters and geological processes, shedding light on the dynamic nature of landscapes and the potential implications for visitor-preferred areas.

This research not only contributes to our understanding of landscape evolution but also underscores the importance of integrating modern and historical datasets to decipher the dynamic processes shaping the Earth's surface. The methodology proposed, serves as a valuable approach for assessing and managing geological hazards in coastal regions affected by both climatic events and geodynamic activities.

How to cite: Konsolaki, A., Vassilakis, E., Kotsi, E., Diakakis, M., Mavroulis, S., Petrakis, S., Filis, C., and Lekkas, E.: A Time-Series Analysis of Rockfall Evolution in a Coastal Region Using Remote Sensing Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10361, https://doi.org/10.5194/egusphere-egu24-10361, 2024.

EGU24-10373 | Orals | GM3.1

A database for ancillary information of three-dimensional soil surface microtopography measurements. 

Kossi Nouwakpo, Anette Eltner, Bernardo Candido, Yingkui Li, Kenneth Wacha, Mary Nichols, and Robert Washington-Allen

Understanding the complex processes occurring at the soil surface is challenging due to the intricate spatial variability and dynamic nature of these processes. An effective tool for elucidating these phenomena is three-dimensional (3D) reconstruction, which employs advanced imaging technologies to create a comprehensive representation of the soil surface at high spatial resolution, often at the mm-scale. Three-dimensional reconstruction techniques are increasingly available to scientists in the fields of soil science, geomorphology, hydrology, and ecology and many studies have employed these novel tools to advance understanding of surface processes. Much of the data being collected in these studies are however not interoperable, i.e., 3D data from one study may not be directly combined with 3D data from other studies thus limiting the ability of researchers to advance process understanding at a broader scope. The limited interoperability of existing data is due in part to the fact that 3D surface reconstruction data are influenced by many factors including experimental conditions, intrinsic soil properties and accuracy and precision limits of the 3D reconstruction technique used. These ancillary data are crucial to any broad-scope efforts that leverage the increasing number of 3D datasets collected by scientists across disciplines, geographic regions, and experimental conditions. We have developed a relational database that archives and serves ancillary data associated with published high-resolution 3D data representing soil surface processes. This presentation introduces the structure of the database with its required and optional variables. We also provide analytics on the currently available records in the database and discuss potential applications of the database and future developments.

How to cite: Nouwakpo, K., Eltner, A., Candido, B., Li, Y., Wacha, K., Nichols, M., and Washington-Allen, R.: A database for ancillary information of three-dimensional soil surface microtopography measurements., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10373, https://doi.org/10.5194/egusphere-egu24-10373, 2024.

EGU24-11949 | ECS | Posters on site | GM3.1

Employng satellite immagery interpretation tools to detect land-use land-change dynamics in Italian historical rural landscapes 

Virginia Chiara Cuccaro, Claudio Di Giovannantonio, Giovanni Pica, Luca Malatesta, and Fabio Attorre

Rural landscapes inherited from the past are marked by a strong interaction between man and nature, a relationship rooted in a long history that testifies to the importance of the landscape as one of the most historically representative expressions of a country's cultural identity.

In this broad context, olive groves markedly characterize the agricultural landscape of many European rural areas, particularly in the Mediterranean region. Along with other rural landscapes, they form a semi-natural environment that can contribute to biodiversity conservation, soil protection and ecosystem resilience.

In addition to the global increase in temperatures, the main threats affecting these agrarian landscapes include the abandonment of traditional practices and the intensification of cultivation through the installation of irregular, intensive and overly dense planting beds.

The Land Cover classification and change-detection can provide useful indications for the restoration, conservation, and enhancement of olive groves

The objective of this work was to identify , rural landscapes in the Lazio region with characteristics of historical interest and determine their level of conservation. In particular, it was investigated the olive landscape of Cures (historic province of Sabina) trough a multi-temporal analysis of literature and cartographic information (e.g. orthophotos from the Italian Aeronautical Group flight of 1954)

The technique concerns the VASA (Historical Environmental Assessment) methodology, which allows the temporal evaluation of a given landscape and can inform on how agricultural practices and land use have changed over time.

Softwares  Collect Earth and Google Earth were employed to manipulate the historical series of high-resolution satellite images and implement photointerpretation. The coverage of identitied land units  was then estimated to address the configuration of the target landscape.

Landscape evolution over time was achieved by overlaying the 1954 and 2022 land use polygons, resulting in a merging database, in which an evolutionary dynamic was associated with each land use change.

The approach generated in-depth insights on the significant elements of the CURES olive landscape and informed on the dynamics of the area in relation to the risk of their disappearance, making it possible to identify what are the "landscape emergencies," i.e., the land uses that have seen the most̀ reduction in their area.

The methodologies employed have proven reliability in improving the knowledge ng target landscapes.  It might be useful to promote  sustainable agricultural practices for better preservation and management of rural environments so that cultural traditions can be preserved as well, and the environmental balance of the agrarian land can be maintained.

How to cite: Cuccaro, V. C., Di Giovannantonio, C., Pica, G., Malatesta, L., and Attorre, F.: Employng satellite immagery interpretation tools to detect land-use land-change dynamics in Italian historical rural landscapes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11949, https://doi.org/10.5194/egusphere-egu24-11949, 2024.

EGU24-12105 | ECS | Orals | GM3.1 | Highlight

Unleashing the archive of aerial photographs of Iceland, 1945-2000. Applications in geosciences  

Joaquín M. C. Belart, Sydney Gunnarson, Etienne Berthier, Amaury Dehecq, Tómas Jóhannesson, Hrafnhildur Hannesdóttir, and Kieran Baxter

The archive of historical aerial photographs of Iceland consists of ~140,000 vertical aerial photographs acquired between the years 1945 and 2000. It contains an invaluable amount of information about human and natural changes in the landscape of Iceland. We have developed a series of automated processing workflows for producing accurate orthomosaics and Digital Elevation Models (DEMs) from these aerial photographs, which we’re making openly available in a data repository and a web map visualization service. The workflow requires two primary inputs: a modern orthomosaic to automatically extract Ground Control Points (GCPs) and an accurate DEM for a fine-scale (sub-meter) alignment of the historical datasets. We evaluated the accuracy of the DEMs by comparing them in unchanged terrain against accurate recent lidar and Pléiades-based DEMs, and we evaluated the accuracy of the orthomosaics by comparing them against Pléiades-based orthomosaics. The data are becoming available at https://loftmyndasja.lmi.is/. To show the potential applications of this repository, we present the following showcases where these data reveal significant changes the landscape in Iceland in the past 80 years: (1) volcanic eruptions (Askja 1961, Heimaey 1973 and the Krafla eruptions, 1975-1984), (2) decadal changes of Múlajökull glacier from 1960-2023, (3) Landslides (Steinsholtsjökull 1967, Tungnakvíslarjökull 1945-present) and (4) coastal erosion (Surtsey island).

How to cite: Belart, J. M. C., Gunnarson, S., Berthier, E., Dehecq, A., Jóhannesson, T., Hannesdóttir, H., and Baxter, K.: Unleashing the archive of aerial photographs of Iceland, 1945-2000. Applications in geosciences , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12105, https://doi.org/10.5194/egusphere-egu24-12105, 2024.

EGU24-14087 | ECS | Posters on site | GM3.1

A point-cloud deep learning model based on RGB-D images: Application of riverbed grain size survey 

Bo Rui Chen and Wei An Chao

The water level and discharge of river are crucial parameters to understand the variance in riverbed scour. The detail behavior of scouring can be studied by the hydraulic simulation. The grain-size distribution of riverbed is also one of crucial parameter for modeling. Thus, how to investigate the grain-size of riverbed efficiently and swiftly is the urgent issue. However, the conventional measurement methods including Wolman counts (particles sampled at a fixed interval) which are a long and laborious task cannot survey the grain-size efficiently in the large area. In recent years, with an advantage of image segmentation and recognition has been applied to the investigation of grain-size, for example, capturing images through UAV and generating orthoimage is one of commonly used image technique. Although above the method can investigate the grain-size in the large area, it does not provide the information in the field immediately. Hence, a recent study developed the low-cost portable scanner to obtain the information of grain-size distribution in the field. However, the calibrating parameters of camera (e.g., height camera capture) are necessary before survey, and the uncertainties in calculation of image resolution will significantly affect the accuracy of grain-size analysis. Therefore, this study provides the additional algorithm to analyze the grain-size by using RGB-D image as inputs. The application of RGB-D can be categorized into two-dimensional (2D) and three-dimensional (3D) spaces. In a case of 2D, it integrates depth information with traditional RGB image processing to separate the grain-size of riverbed from the background (e.g., bottomland). Furthermore, depth information is also applied for grain-size edge detection. In a case of 3D, the collected RGB-D image information is transformed into point cloud data, then extract 3D features of grain particle by Deep learning, specifically PointNet. Our study demonstrates that clustering of 3D features can achieve the automatic identification of particle. The grain-size of particle can also be estimated by fitting 3D ellipsoid geometry. In the end, results show the grain-size distribution curves with the RGB、RGB-D、PointNet recognition, and compare with the true observations. 3D image information provides the cloud points of grain object, leading the possibility of estimating the 3D geometric morphology of the object. Our study successfully overcomes the limitations of conventional RGB-based process, which could only capture size and shape information in 2D planar. RGB-D-based image recognition, is an innovative technique for the hydraulic problem, not only advances survey efficiency but also addresses the intricate steps required for field investigations.

 

Key words: Riverbed grain size, RGB-D image, Point cloud, Deep Learning

How to cite: Chen, B. R. and Chao, W. A.: A point-cloud deep learning model based on RGB-D images: Application of riverbed grain size survey, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14087, https://doi.org/10.5194/egusphere-egu24-14087, 2024.

EGU24-14680 | Orals | GM3.1

Using current 3D point clouds as a tool to infer on past geomorphological processes 

Reuma Arav, Sagi Filin, and Yoav Avni

Examining deposition and erosion dynamics during the late Pleistocene and Holocene is crucial for gaining insights into soil development, erosion, and climate fluctuations. This urgency intensifies as arable lands face escalating degradation rates, particularly in arid and semi-arid environments. Nevertheless, as the destructive nature of erosional processes allows only for short-term studies, long-term processes in these regions are insufficiently investigated. In that respect, the ancient agricultural installations in the arid Southern Levant offer distinctive and undisturbed evidence of long-term land dynamics. Constructed on a late Pleistocene fluvial-loess section during the 3rd-4th CE and abandoned after 600-700 years, these installations record sediment deposition, soil formation, and erosion processes. The challenge is to trace and quantify these processes based on their current state. In this presentation, we demonstrate how the use of 3D point cloud data enables us to follow past geomorphological processes and reconstruct trends and rates. Utilizing data gathered in the immediate vicinity of the UNESCO World Heritage Site of Avdat (Israel), we illustrate how these point clouds comprehensively document the history of soil dynamics in the region. This encompasses the initial erosion phase, subsequent soil aggradation processes resulting from anthropogenic interruption, and the ongoing reinstated erosion. The unique setting, which uncovers the different fluvial sections, together with the detailed 3D documentation of the site, allows us to develop means for the reconstruction of the natural environment in each of the erosion/siltation stages. Therefore, by utilizing the obtained data, we can recreate the site during its developmental stages till the present day. Furthermore, we utilize terrestrial laser scan data sequence acquired in the past decade (2012-2022) to compute current erosion rates. These are then used to determine past rates, enabling inferences about the climatic conditions prevalent in the region over the last millennium. The in-depth examination of these installations provides valuable insights into approaches for soil conservation, sustainable desert living, and strategies to safeguard world-heritage sites subjected to soil erosion. As the global imperative to address soil erosion intensifies, this case study gains heightened relevance.

How to cite: Arav, R., Filin, S., and Avni, Y.: Using current 3D point clouds as a tool to infer on past geomorphological processes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14680, https://doi.org/10.5194/egusphere-egu24-14680, 2024.

EGU24-15439 | ECS | Orals | GM3.1 | Highlight

Utilizing historical aerial imagery for change detection in Antarctica 

Felix Dahle, Roderik Lindenbergh, and Bert Wouters

Our research explores the potential of historical images of Antarctica for change detection in 2D and 3D. We
make use of the TMA Archive, a vast collection of over 330,000 black and white photographs of Antarctica taken
between 1940 to 1990. These photographs, available in both nadir and oblique, are systematically captured
from airplanes along flight paths and offer an unprecedented historical snapshot of the Antarctic landscape.
Detecting changes between past and present observations provides a unique insight into the long-term impact
of changing climate conditions on Antarctica’s glaciers, and their dynamical response to ice shelf weakening and
disintegration. Furthermore, it provides essential validation data for ice modelling efforts, thereby contributing
to reducing the uncertainties in future sea level rise scenarios.

In previous work, we applied semantic segmentation to these images [1]. By employing classes derived from this
segmentation, we can focus on features of interest and exclude images with extensive cloud coverage, enhancing
the accuracy of change analyses. In the next step, we geo-referenced the images: We assigned the images to
their actual position, scaled them to their true size, and aligned them with their genuine orientation. This
presents novel opportunities for detecting environmental changes in Antarctica, particularly in the retreat of
glaciers and sea ice.

Furthermore, the combination of these two steps allows for the first time a large scale reconstruction of these
images in 3D through Structure from Motion (SfM) techniques, which enables further multidimensional change
detection by comparing historical 3D models with contemporary ones. Due to the high number of images,
manual processing is impractical. Therefore, we are investigating the possibility of automatizing this process.
We utilize MicMac, an open-source software developed by the French National Geographic Institute for the
creation of the 3D models. Its high modularity allows for necessary customizations to automate the SfM
process effectively. Further adaptions are required due to the poor image quality and monotonous scenery. By
comparing historical 3D models with contemporary ones, we can assess alterations in elevation due to factors
such as glacial isostatic adjustments and glacier retreat.

We have already employed geo-referenced images for detecting changes on the Antarctic peninsula and are in the
process of creating initial 3D models. Our presentation will outline the workflow we developed for this process
and showcase the initial results of the change detection, both in 2D and 3D formats. This approach marks a
significant step in understanding and visualizing the impacts of climate change on the Antarctic landscape.

Acknowledgements
This work was funded by NWO-grant ALWGO.2019.044.

References
[1] F. Dahle, R. Lindenbergh, and B. Wouters. Revisiting the past: A comparative study for semantic segmen-
tation of historical images of Adelaide Island using U-nets. ISPRS Open Journal of Photogrammetry and
Remote Sensing, 11:100056, 2024.

How to cite: Dahle, F., Lindenbergh, R., and Wouters, B.: Utilizing historical aerial imagery for change detection in Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15439, https://doi.org/10.5194/egusphere-egu24-15439, 2024.

EGU24-15896 | Orals | GM3.1

Classification and segmentation of 3D point clouds to survey river dynamics and evolution  

Laure Guerit, Philippe Steer, Paul Leroy, Dimitri Lague, Dobromir Filipov, Jiri Jakubinsky, Ana Petrovic, and Valentina Nikolova

3D data for natural environments are now widely available via open data at large scales (e.g., OpenTopography) and can be easily acquired on the field by terrestrial LiDAR scan (TLS) or by structure-from-motion (SFM) from camera or drone imagery. The 3D description of landscapes gives access to an unprecedented level of details that can significantly change the way we look at, understand, and study natural systems. Point clouds with millimetric resolution even allow to go further and to investigate the properties of riverbed sediments: dedicated algorithms are now able to extract the sediment size distribution or their spatial orientation directly from the point cloud. 

Such data can be real game changers to study for example torrential streams prone to flash floods or debris flows. Such events are usually associated with heavy rainfall events, while conditioned by the geomorphological state of a stream (e.g., channel geometry, vegetation cover). The size and the shape of the grains available in the river also strongly influence river erosion and sediment transport during a flood. 3D data can thus help to design prevention and mitigation measures in streams prone to torrential events. 

However, it is not straightforward to go from data acquisition to river erosion or to grain-size distributions. Indeed, isolating and classifying the areas of interest can be complex and time-consuming. This can be done manually, at the cost of time and absence of reproducibility. We rather take advantage of state-of-the-art classification method (3DMASC) to develop a general classifier for point clouds in fluvial environments designed to identify five classes usually found in such settings: coarse sediments, sand, bedrock, vegetation and human-made structures. We also improved the G3Point sediment segmentation algorithm, developed by our team, to make it more efficient and straightforward to use in the CloudCompare software, which is dedicated to point cloud visualization and analysis. We apply it to the coarse sediments class identified by 3DMASC to provide a more accurate description of grain size and orientation. We also make a profit of the sand class to estimate its relative areal distribution that can then be compared to the coarse sediment class. This provides valuable information about the type of flows which are also important for planning torrential events mitigation measures.

We illustrate this combined approach with two field examples. The first one is based on SFM data acquired along streams prone to torrential events in Bulgaria and in Serbia where we documented sediment size and orientation. The second one is based on TLS data acquired along a bedrock river in France that experienced a major flood which induced dramatic changes in the river morphology. 

This work has been partially funded by PHC Danube n° 49921ZG/ n° KP-06-Danube/5, 14.08.2023 (National Science Fund, Bulgaria) and the H2020 European Research Council (grant no. 803721). 

How to cite: Guerit, L., Steer, P., Leroy, P., Lague, D., Filipov, D., Jakubinsky, J., Petrovic, A., and Nikolova, V.: Classification and segmentation of 3D point clouds to survey river dynamics and evolution , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15896, https://doi.org/10.5194/egusphere-egu24-15896, 2024.

EGU24-16939 | ECS | Posters on site | GM3.1 | Highlight

Integrating structure-from-motion photogrammetry with 3D webGIS for risk assessment, mapping and monitoring of coastal area changes in the Maltese archipelago 

Emanuele Colica, Daniel Fenech, Christopher Gauci, and George Buhagiar

The Maltese coasts extend for approximately 273km, representing a notable resource for the country and of one of its pillar economies, the tourism sector. Natural processes and anthropic interventions continue to threaten Malta's coastal morphology, shaping its landscape and triggering soil erosion phenomena. Therefore, many research projects (Colica et al., 2021, 2022 and 2023) have concentrated their work on the investigation and monitoring of the instability of cliffs and the erosion of pocket beaches. The results of such activities can be widely disseminated and shared with expert and non-expert users through web mapping, which has only been used in a very limited way in collaborative coastal management and monitoring by different entities in Malta. This study describes the performance of a WebGIS designed to disseminate the results of innovative geomatic investigations for monitoring and analyzing erosion risk, performed by the Research and Planning Unit within the Public Works Department of Malta. While aiming to include the entire national coastline, three study areas along the NE and NW regional coasts of the island of Malta have already been implemented as pilot cases. This WebGIS was generated using ArcGIS pro software by ESRI and a user-friendly interactive interface has been programmed to help users view in 2D and 3D, satisfying both multi-temporal and multi-scale perspectives. It is envisaged that through further development and wider dissemination there will be a stronger uptake across different agencies involved in coastal risk assessment, monitoring and management.

References

Colica, E., D’Amico, S., Iannucci, R., Martino, S., Gauci, A., Galone, L., ... & Paciello, A. (2021). Using unmanned aerial vehicle photogrammetry for digital geological surveys: Case study of Selmun promontory, northern of Malta. Environmental Earth Sciences, 80, 1-14.

Colica, E. (2022). Geophysics and geomatics methods for coastal monitoring and hazard evaluation.

Colica, E., Galone, L., D’Amico, S., Gauci, A., Iannucci, R., Martino, S., ... & Valentino, G. (2023). Evaluating Characteristics of an Active Coastal Spreading Area Combining Geophysical Data with Satellite, Aerial, and Unmanned Aerial Vehicles Images. Remote Sensing, 15(5), 1465.

How to cite: Colica, E., Fenech, D., Gauci, C., and Buhagiar, G.: Integrating structure-from-motion photogrammetry with 3D webGIS for risk assessment, mapping and monitoring of coastal area changes in the Maltese archipelago, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16939, https://doi.org/10.5194/egusphere-egu24-16939, 2024.

EGU24-17822 | ECS | Posters on site | GM3.1

Evaluating Ordnance Survey sheets (1890s – 1957) for shoreline change analysis in the Maltese Islands  

Daniel Fenech, Jeremie Tranchant, Christopher Gauci, Daniela Ghirxi, Ines Felix-Martins, Emanuele Colica, and George Buhagiar

 

Jeremie' Tranchant1, Daniel Fenech1, Christopher Gauci1, Daniela Ghirxi1, Ines Felix Martins1, Emanuele Colica1, George Buhagiar1

1  Research and Planning Unit, Ministry for Transport, Infrastructure and Public Works, Project House, Triq Francesco    Buonamici, Floriana, FRN1700, Malta

The assessment of coastal erosion through shoreline change analysis, is an exercise of national utility undertaken in many countries. The Maltese Islands are particularly vulnerable to coastal erosion given the economic value of coastal activities and their high ratio of coast-to-land surface. The integration of historical cartographic material is often used to hindcast shoreline change across long periods of time, as well as to model future erosion rates. The Public Works Department have produced detailed 1:2500 maps of Malta in collaboration with the British Ordnance Survey from the end of the 19th century to 1957, however these maps have never been scientifically assessed. The initial research carried out evaluated the usefulness of the two oldest 25-inches Maltese maps series (early 20th century and 1957) for shoreline change analysis.  The two series were digitised, georeferenced, and compared in a GIS environment to assess their differences. The inaccuracies of the original drawings, absent shoreline indicators, and the absence of a geographic coordinate system (datum and projection) were identified as limitations for their use in evaluating small gradual changes, but were ideal for the identification of stochastic, large-scale historic erosion events using difference maps. This assessment showed that the two series are highly congruous and any changes between the two series are largely attributed to changes in infrastructure. There were, however, minor exceptions and these need to be explored on a case-by-case basis. These methods and the insights garnered from their production will function as scientific steppingstones towards developing a holistic coastal erosion national monitoring program.  

How to cite: Fenech, D., Tranchant, J., Gauci, C., Ghirxi, D., Felix-Martins, I., Colica, E., and Buhagiar, G.: Evaluating Ordnance Survey sheets (1890s – 1957) for shoreline change analysis in the Maltese Islands , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17822, https://doi.org/10.5194/egusphere-egu24-17822, 2024.

EGU24-21396 | ECS | Orals | GM3.1

Automatic detection of river bankfull parameters from high density lidar data 

Alexandre Rétat, Nathalie Thommeret, Frédéric Gob, Thomas Depret, Jean-Stéphane Bailly, Laurent Lespez, and Karl Kreutzenberger

The European Water Framework Directive (WFD), adopted in 2000, set out requirements for a
better understanding of aquatic environments and ecosystems. In 2006, following the transposition of
the WFD into French law (LEMA), France began work on a field protocol for the geomorphological
characterization of watercourses, as part of a partnership between the Centre National de la Recherche
Scientifique (CNRS) and the Office Français de la Biodiversité (OFB). This protocol, known as "Carhyce"
(For « River Hydromorphological Caracterisation »), has been tested, strengthened and approved over
the last 15 years at more than 2500 reaches. It consists of collecting standardised qualitative and
quantitative data in the field, essential for the caracterisation of a watercourse: channel geometry,
substrate, riparian vegetation... However, certain rivers that are difficult to survey (too deep or too
wide) pose problems for data collection.
To address these issues, and to extend the analysis to a wider scale (full river section), using
remote sensing, and in particular LiDAR data, was considered. The major advantages of LiDAR over
passive optical sensors are better geometric accuracy and especially under vegetation. For a long time,
LiDAR data rarely exists at national scale with data density similar to passive imagery. Today, the French
LiDAR HD dataset (10 pulses per meter square) program run by the French mapping agency offers an
unprecedented amount of data at this scale. Thanks to them, a national 3D coverage of the ground can
be used, and numerous geomorphological measurements can be carried out on a more or less large
scale. This is the case for hydromorphological parameters such as water level and width.
The aim of this study is therefore to use this high-density lidar to automatically determine the
hydromorphological parameters sought in the Carhyce protocol. In particular, we have developed a
lidar-based algorithm to reconstruct the topography from point cloud and automatically identify the
bankfull level at reach scale. Designed to be applicable to every French river, the method must be
robust to all river features such as longitudinal slope, width, sinuosity, multi-channel etc... For
validation purposes, the bankfull geometry calculated by the algorithm has been compared with field
measurements at some twenty Carhyce stations across France. To determine the test stations, we
looked for the diversity of situations in terms of river characteristics describe above to observed the
influence of this features on the results.

How to cite: Rétat, A., Thommeret, N., Gob, F., Depret, T., Bailly, J.-S., Lespez, L., and Kreutzenberger, K.: Automatic detection of river bankfull parameters from high density lidar data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21396, https://doi.org/10.5194/egusphere-egu24-21396, 2024.

EGU24-22358 | ECS | Orals | GM3.1 | Highlight

UAV’s to monitor the mass balance of glaciers 

Lander Van Tricht, Harry Zekollari, Matthias Huss, Philippe Huybrechts, and Daniel Farinotti

Uncrewed Aerial Vehicles (UAVs) are increasingly employed for glacier monitoring, particularly for small to medium-sized glaciers. The UAVs are mainly used to generate high-resolution Digital Elevation Models (DEMs), delineate glacier areas, determine surface velocities, and map supraglacial features. In this study, we utilise UAVs across various sites in the Alps and the Tien Shan (Central Asia) to monitor the mass balance of glaciers. We present a workflow for calculating the annual geodetic mass balance and obtaining the surface mass balance using the continuity-equation method. Our results demonstrate generally a close alignment between the determined mass balances and those obtained through traditional glaciological methods involving intensive fieldwork. We show that utilising UAV data reveals significantly more spatial details, such as the influence of debris and collapsing ice caves, which are challenging to capture using conventional methods that strongly rely on interpolation and extrapolation. This underscores the UAV's significance as a valuable add-on tool for quantifying annual glacier mass balance and validating glaciological assessments. Drawing on our experience in on-site UAV glacier surveys, we discuss the methodology's advantages, disadvantages, and potential pitfalls. 

How to cite: Van Tricht, L., Zekollari, H., Huss, M., Huybrechts, P., and Farinotti, D.: UAV’s to monitor the mass balance of glaciers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22358, https://doi.org/10.5194/egusphere-egu24-22358, 2024.

EGU24-1857 | Orals | ESSI2.9

A Replicable Multi-Cloud Automation Architecture for Earth Observation 

Armagan Karatosun, Claudio Pisa, Tolga Kaprol, Vasileios Baousis, and Mohanad Albughdadi

The EO4EU project aims at making the access and use of Earth Observation (EO) data easier for environmental, government and business forecasts and operations.

To reach this goal, the EO4EU Platform will soon be made officially available, leveraging existing EO data sources such as DestinE, GEOSS, INSPIRE, Copernicus and Galileo, and offering advanced tools and services, based also on machine learning techniques, to help users find, access and handle the data they are interested in. The EO4EU Platform relies on a combination of a multi-cloud computing infrastructure coupled with pre-exascale high-performance computing facilities to manage demanding processing workloads.

The EO4EU multi-cloud infrastructure is composed by IaaS resources hosted on the WEkEO and CINECA Ada clouds, leveraged by a set of Kubernetes clusters dedicated to different workloads (e.g. cluster management tools, observability, or specific applications such as an inference server). To automate the deployment and management of these clusters, with advantages in terms of minimisation of dedicated effort and human errors, we have devised an Infrastructure-as-Code (IaC) architecture based on the Terraform, Rancher and Ansible technologies.

We believe that the proposed IaC architecture, based on open-source components and extensively documented and tested on the field, can be successfully replicated by other EO initiatives leveraging cloud infrastructures.

How to cite: Karatosun, A., Pisa, C., Kaprol, T., Baousis, V., and Albughdadi, M.: A Replicable Multi-Cloud Automation Architecture for Earth Observation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1857, https://doi.org/10.5194/egusphere-egu24-1857, 2024.

EGU24-6216 | Posters on site | ESSI2.9

Pangeo environment in Galaxy Earth System supported by Fair-Ease 

Thierry Carval, Marie Jossé, and Jérôme Detoc

The Earth System is a complex and dynamic system that encompasses the interactions between the atmosphere, oceans, land, and biosphere. Understanding and analyzing data from the Earth System Model (ESM) is essential, for example to predict and mitigate the impacts of climate change.

Today, collaborative efforts among scientists across diverse fields are increasingly urgent. The FAIR-EASE project aims to build an interdomain digital architecture for integrated and collaborative use of environmental data. Galaxy is a main component of this architecture which will be used by several domains of study chose by FAIR-EASE.

Galaxy, an open-source web platform, provides users with an easy and FAIR tool to access and handle multidisciplinary environmental data. By design, Galaxy manages data analyses by sharing and publishing all involved items like inputs, results, workflows, and visualisations, ensuring reproducibility by capturing the necessary information to repeat and understand data analyses.

From this point on, a Pangeo environment is a tool more than relevant to be used alongside earth-system related data and processing tools in order to create cross domain analyses. The good news is that a Pangeo environment is accessible on Galaxy. It can be exploited as a jupyterlab and allows the user to manage their NetCDF data in a Pangeo environment with the use of notebooks. Multiple tutorials are available on the Galaxy Training Network to learn how to use Pangeo.

The Galaxy Training Network significantly contributes to enhancing the accessibility and reusability of tools and workflows. The Galaxy Training platform hosts an extensive collection of tutorials. These tutorials serve as valuable resources for individuals seeking to learn how to navigate Galaxy, employ specific functionalities like Interactive Tools or how to execute workflows for specific analyses.

In synthetisis, Pangeo in Galaxy provide Pangeo users with an up-to-date data analysis platform ensuring reproducibility and mixing trainings and tools.

On the Earth System side, a first step was the creation of a Galaxy declination for Earth System studies (earth-system.usegalaxy.eu) with dedicated data, models, processing, visualisations and tutorials. It will make Earth System modeling more accessible to researchers in different fields.

In this Galaxy subdomain we choose to have the Pangeo tools. Our hope is to be able to implement cross domain workflows including climate and earth system sciences.

During this session our aim is to present how you can use the Pangeo environment from the Galaxy Earth System.

How to cite: Carval, T., Jossé, M., and Detoc, J.: Pangeo environment in Galaxy Earth System supported by Fair-Ease, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6216, https://doi.org/10.5194/egusphere-egu24-6216, 2024.

EGU24-7765 | Orals | ESSI2.9

Unleashing the power of Dask with a high-throughput Trust Region Reflectance solver for raster datacubes 

Bernhard Raml, Raphael Quast, Martin Schobben, Christoph Reimer, and Wolfgang Wagner

In remote sensing applications, the ability to efficiently fit models to vast amounts of observational data is vital for deriving high-quality data products, as well as accelerating research and development. Addressing this challenge, we developed a high-performance non-linear Trust Region Reflectance solver specialised for datacubes, by integrating Python's interoperability with C++ and Dask's distributed computing capabilities. Our solution achieves high throughput both locally and potentially on any Dask-compatible backend, such as EODC's Dask Gateway. The Dask framework takes care of chunking the datacube, and streaming each chunk efficiently to available workers where our specialised solver is applied. Introducing Dask for distributed computing enables our algorithm to run on different compatible backends. This approach not only broadens operational flexibility, but also allows us to focus on enhancing the algorithm's efficiency, free from concerns about concurrency. This enabled us to implement a highly efficient solver in C++, which is optimised to run on a single core, but still utilise all available resources effectively. For the heavy lifting, such as performing singular value decompositions and matrix operations we rely on Eigen, a powerful open-source C++ library specialized on linear algebra. To describe the spatial reference and other auxiliary data associated with our datacube, we employ the Xarray framework. Importantly, Xarray integrates seamlessly with Dask. Finally, to ensure robustness and extensibility of our framework, we applied state-of-the-art software engineering practices, including Continuous Integration and Test-Driven Development. In our work we demonstrate the significant performance gains achievable by effectively utilising available open-source frameworks, and adhering to best engineering practices. This is exemplified by our practical workflow demonstration to fit a soil moisture estimation model. 

How to cite: Raml, B., Quast, R., Schobben, M., Reimer, C., and Wagner, W.: Unleashing the power of Dask with a high-throughput Trust Region Reflectance solver for raster datacubes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7765, https://doi.org/10.5194/egusphere-egu24-7765, 2024.

The Earth System Grid Federation (ESGF) data nodes are usually the first address for accessing climate model datasets from WCRP-CMIP activities. It is currently hosting different datasets in several projects, e.g., CMIP6, CORDEX, Input4MIPs or Obs4MIPs. Datasets are usually hosted on different data nodes all over the world while data access is managed by any of the ESGF web portals through a web-based GUI or the ESGF Search RESTful API. The ESGF data nodes provide different access methods, e.g., https, OPeNDAP or Globus. 

Beyond ESGF, there has been the Pangeo / ESGF Cloud Data Working Group that coordinates efforts related to storing and cataloging CMIP data in the cloud, e.g., in the Google cloud and in the Amazon Web Services Simple Storage Service (S3) where a large part of the WCRP-CMIP6 ensemble of global climate simulations is now available in analysis-ready cloud-optimized (ARCO) zarr format. The availibility in the cloud has significantly lowered the barrier for users with limited resources and no access to an HPC environment to work with CMIP6 datasets and at the same time increases the chance for reproducibility and reusability of scientific results. 

Following the Pangeo strategy, we have adapted parts of the Pangeo Forge software stack for publishing our regional climate model datasets from the EURO-CORDEX initiative on AWS S3 cloud storage. The main tools involved are Xarray, Dask, Zarr, Intake and the ETL tools of pangeo-forge-recipes. Thanks to similar meta data conventions in comparison to the global CMIP6 datasets, the workflows require only minor adaptations. In this talk, we will show the strategy and workflow implemented and orchestrated in GitHub Actions workflows as well as a demonstration of how to access EURO-CORDEX datasets in the cloud.

How to cite: Buntemeyer, L.: Beyond ESGF – Bringing regional climate model datasets to the cloud on AWS S3 using the Pangeo Forge ETL framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8058, https://doi.org/10.5194/egusphere-egu24-8058, 2024.

EGU24-8343 | ECS | Posters on site | ESSI2.9 | Highlight

Implementation of a reproducible pipeline for producing seasonal Arctic sea ice forecasts 

Vanessa Stöckl, Björn Grüning, Anne Fouilloux, Jean Iaquinta, and Alejandro Coca-Castro

This work highlights the integration of IceNet (https://doi.org/10.1038/s41467-021-25257-4), a cutting-edge sea ice forecasting system leveraging numerous Python packages from the Pangeo ecosystem, into the Galaxy platform—an open-source tool designed for FAIR (Findable, Accessible, Interoperable, and Reusable) data analysis. Aligned with the Pangeo ecosystem's broader objectives, and carried out in the frame of the EuroScienceGateway project (https://eurosciencegateway.eu), this initiative embraces a collaborative approach to tackle significant geoscience data challenges. The primary aim is to democratise access to IceNet's capabilities by converting a Jupyter Notebook, published in the Environmental Data Science book (www.edsbook.org), into Galaxy Tools and crafting a reusable workflow executable through a Graphical User Interface or standardised APIs. IceNet is meant to predict Arctic sea ice concentration up to six months in advance, and it outperforms previous systems. This integration establishes a fully reproducible workflow, enabling scientists with diverse computational expertise to automate sea ice predictions. The IceNet workflow is hosted on the European Galaxy Server (https://climate.usegalaxy.eu), along with the related tools, ensuring accessibility for a wide community of researchers. With the urgency of accurate predictions amid global warming's impact on Arctic sea ice, this work addresses challenges faced by scientists, particularly those with limited programming experience. The transparent, accessible, and reproducible pipeline for Arctic sea ice forecasting aligns with Open and Science principles. The integrated IceNet into Galaxy enhances accessibility to advanced climate science tools, allowing for automated predictions that contribute to early and precise identification of potential damages from sea ice loss. This initiative mirrors the overarching goals of the Pangeo community, advancing transparent, accessible, and reproducible research. The Galaxy-based pipeline presented serves as a testament to collaborative efforts within the Pangeo community, breaking down barriers related to computational literacy and empowering a diverse range of scientists to contribute to climate science research. The integration of IceNet into Galaxy not only provides a valuable tool for seasonal sea ice predictions but also exemplifies the potential for broad interdisciplinary collaboration within the Pangeo ecosystem.

How to cite: Stöckl, V., Grüning, B., Fouilloux, A., Iaquinta, J., and Coca-Castro, A.: Implementation of a reproducible pipeline for producing seasonal Arctic sea ice forecasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8343, https://doi.org/10.5194/egusphere-egu24-8343, 2024.

EGU24-9156 | ECS | Orals | ESSI2.9

DataLabs: development of a cloud collaborative platform for open interdisciplinary geo-environmental sciences  

Michael Tso, Michael Hollaway, Faiza Samreen, Iain Walmsley, Matthew Fry, John Watkins, and Gordon Blair

In environmental science, scientists and practitioners are increasingly facing the need to create data-driven solutions to the environment's grand challenges, often needing to use data from disparate sources and advanced analytical methods, as well as drawing expertise from collaborative and cross-disciplinary teams [1]. Virtual labs allow scientists to collaboratively explore large or heterogeneous datasets, develop and share methods, and communicate their results to stakeholders and decision-makers. 

DataLabs [2] has been developed as a cloud-based collaborative platform to tackle these challenges and promote open, collaborative, interdisciplinary geo-environmental sciences. It allows users to share notebooks (e.g. JupyterLab, R Studio, and most recently VS Code), datasets and computational environments and promote transparency and end-to-end reasoning of model uncertainty. It supports FAIR access to data and digital assets by providing shared data stores and discovery functionality of datasets and assets hosted on the platform’s asset catalogue. Its tailorable design allows it to be adaptable to different challenges and applications. It is also an excellent platform for large collaborative teams to work on outputs together [3] as well as communicating results to stakeholders by allowing easy prototyping and publishing of web applications (e.g. Shiny, Panel, Voila). It is currently deployed on JASMIN [4] and is part of the UK NERC Environmental data service [5]. 

There are a growing number of use cases and requirements for DataLabs and it is going to play a central part in several planned digital research infrastructure (DRI) initiatives. Future development needs of the platform to further its vision include e.g. more intuitive onboarding experience, easier access to key datasets at source, better connectivity to other cloud platforms, and better use of workflow tools. DataLabs shares many of the features (e.g. heavy use of PANGEO core packages) and design principles of PANGEO. We would be interested in exploring commonalities and differences, sharing best practices, and growing the community of practice in this increasingly important area. 

[1]  Blair, G.S., Henrys, P., Leeson, A., Watkins, J., Eastoe, E., Jarvis, S., Young, P.J., 2019. Data Science of the Natural Environment: A Research Roadmap. Front. Environ. Sci. 7. https://doi.org/10.3389/fenvs.2019.00121  

[2] Hollaway, M.J., Dean, G., Blair, G.S., Brown, M., Henrys, P.A., Watkins, J., 2020. Tackling the Challenges of 21st-Century Open Science and Beyond: A Data Science Lab Approach. Patterns 1, 100103. https://doi.org/10.1016/j.patter.2020.100103 

[3] https://eds.ukri.org/news/impacts/datalabs-streamlines-workflow-assessing-state-nature-uk  

[4] https://jasmin.ac.uk/  

[5] https://eds.ukri.org/news/impacts/datalabs-digital-collaborative-platform-tackling-environmental-science-challenges  

How to cite: Tso, M., Hollaway, M., Samreen, F., Walmsley, I., Fry, M., Watkins, J., and Blair, G.: DataLabs: development of a cloud collaborative platform for open interdisciplinary geo-environmental sciences , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9156, https://doi.org/10.5194/egusphere-egu24-9156, 2024.

EGU24-9781 | Posters on site | ESSI2.9

Optimizing NetCDF performance for cloud computing : exploring a new chunking strategy 

Flavien Gouillon, Cédric Pénard, Xavier Delaunay, and Florian Wery

Owing to the increasing number of satellites and advancements in sensor resolutions, the volume of scientific data is experiencing rapid growth. NetCDF (Network Common Data Form) stands as the community standard for storing such data, necessitating the development of efficient solutions for file storage and manipulation in this format.

Object storage, emerging with cloud infrastructures, offers potential solutions for data storage and parallel access challenges. However, NetCDF may not fully harness this technology without appropriate adjustments and fine-tuning. To optimize computing and storage resource utilization, evaluating NetCDF performance on cloud infrastructures is essential. Additionally, exploring how cloud-developed software solutions contribute to enhanced overall performance for scientific data is crucial.

Offering multiple file versions with data split into chunks tailored for each use case incurs significant storage costs. Thus, we investigate methods to read portions of compressed chunks, creating virtual sub-chunks that can be read independently. A novel approach involves indexing data within NetCDF chunks compressed with deflate, enabling extraction of smaller data portions without reading the entire chunk.

This feature is very valuable in use cases such as pixel drilling or extracting small amounts of data from large files with sizable chunks. It also saves reading time, particularly in scenarios of poor network connection, such as those encountered onboard research vessels.

We conduct performance assessments of various libraries in various use cases to provide recommendations for the most suitable and efficient library for reading NetCDF data in different situations.

Our tests involved accessing remote NetCDF datasets (two files from the SWOT mission) available on the network via a lighttpd server and an s3 server. Additionally, simulations of degraded Internet connections, featuring high latency, packet loss, and limited bandwidth, are also performed.

We evaluate the performance of four Python libraries (netcdf4 lib, Xarray, h5py, and our chunk indexing library) for reading dataset portions through fsspec or fs_s3. A comparison of reading performance using netCDF, zarr, and nczarr data formats is also conducted on an s3 server.

Preliminary findings indicate that the h5py library is the most efficient, while Xarray exhibits poor performance in reading NetCDF files. Furthermore, the NetCDF format demonstrates reasonably good performance on an s3 server, albeit lower than zarr or nczarr formats. However, the considerable efforts required to convert petabytes of archived NetCDF files and adapt numerous software libraries for a performance improvement within the same order of magnitude can raise questions about the practicality of such endeavors and benefits is thus extremely related to the use cases.

How to cite: Gouillon, F., Pénard, C., Delaunay, X., and Wery, F.: Optimizing NetCDF performance for cloud computing : exploring a new chunking strategy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9781, https://doi.org/10.5194/egusphere-egu24-9781, 2024.

EGU24-9795 | ECS | Orals | ESSI2.9

Unifying HPC and Cloud Systems; A Containerized Approach for the Integrated Forecast System (IFS) 

Cathal O'Brien, Armagan Karatosun, Adrian Hill, Paul Cresswell, Michael Sleigh, and Ioan Hadade

The IFS (Integrated Forecast System) is a global numerical weather prediction system maintained by the European Centre for Medium-Range Weather Forecasts (ECMWF). Traditionally, ECMWF’s high-performance computing facility (HPCF) is responsible for operationally supporting the IFS cycles. However, with the emergence of new cloud technologies, initiatives such as Destination Earth (DestinE), and growth of OpenIFS users within Europe and around the globe, the need to run IFS outside of ECMWF's computing facilities becomes more evident. Concerning such use cases, IFSTestsuite allows for the complete IFS system and its dependencies (e.g. ecCodes) to be built and tested outside of ECMWF's HPCF and designed to be self-contained, eliminating the need for external tools like MARS or ecCodes. Despite the need for users to perform multiple steps and the dependency of the software availability and versions on the host operating system, this indicates that there might be a potential for more generic and broader approach. 

Containerization might provide the much-needed portability and disposable environments to trigger new cycles with the desired compiler versions, or even with different compilers. In addition, pre-built container images can be executed on any platform, provided there is a compatible container runtime installed on the target system that adheres to Open Container Initiative (OCI) standards like Singularity or Docker. Another benefit of using container images is container image layers which can significantly reduce the image build time. Lastly, despite their differences, both Singularity and Docker adhere to the OCI standards, and converting one container image to another is straightforward. However, despite the clear advantages, there are several crucial design choices to keep in mind. Notably, the available hardware and software stacks varies greatly across different HPC systems. When performance is important, this heterogeneous landscape limits the portability of containers. The libraries and drivers inside the container must be specially selected with regard to the hardware and software stack of a specific host system to maximize performance on that system. If this is done correctly, the performance of containerized HPC applications can match native applications. We demonstrate this process with the use of a hybrid containerization strategy where compatible MPI stacks and drivers are built inside the containers. The binding of host libraries into containers is also used on systems where proprietary software cannot be rebuilt inside the container.  

In this study we present a containerized solution which balances portability and efficient performance, with examples of containerizing the IFS on a variety of systems including cloud systems with generic x86-64 architecture, such as European Weather Cloud (EWC) and Microsoft Azure, on EuroHPC systems such as Leonardo and LUMI and provided container image recipes for OpenIFS. 

How to cite: O'Brien, C., Karatosun, A., Hill, A., Cresswell, P., Sleigh, M., and Hadade, I.: Unifying HPC and Cloud Systems; A Containerized Approach for the Integrated Forecast System (IFS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9795, https://doi.org/10.5194/egusphere-egu24-9795, 2024.

EGU24-10741 | Posters on site | ESSI2.9

Harnessing the Pangeo ecosystem for delivering the cloud-based Global Fish Tracking System 

Daniel Wiesmann, Tina Odaka, Anne Fouilloux, Emmanuelle Autret, Mathieu Woillez, and Benjamin Ragan-Kelley

We present our approach of leveraging the Pangeo software stack for developing the Global Fish Tracking System (GFTS). The GFTS project tackles the challenge of accurately modelling fish movement in the ocean based on biologging data with a primary focus on Sea Bass. Modelling fish movements is essential to better understand migration strategies and site fidelity, which are critical aspects for fish stock management policy and marine life conservation efforts.

Estimating fish movements is a highly compute intensive process. It involves matching pressure and temperature data from in-situ biologging sensors with high resolution ocean temperature simulations over long time periods. The Pangeo software stack provides an ideal environment for this kind of modelling. While the primary target platform of the GFTS project is the new Destination Earth Service Platform (DESP), relying on the Pangeo ecosystem ensures that the GFTS project is a robust and portable solution that can be re-deployed on different infrastructure. 

One of the distinctive features of the GFTS project is its advanced data management approach, synergizing with the capabilities of Pangeo. Diverse datasets, including climate change adaptation digital twin data, sea temperature observations, bathymetry, and biologging in-situ data from tagged fish, are seamlessly integrated within the Pangeo environment. A dedicated software called pangeo-fish has been developed to streamline this complex modelling process. The technical framework of the GFTS project includes Pangeo core packages such as Xarray and Dask, which facilitate scalable computations.

Pangeo's added value in data management becomes apparent in its capability to optimise data access and enhance performance. The concept of "data visitation" is central to this approach. By strategically deploying Dask clusters close to the data sources, the GFTS project aims to significantly improve performance of fish track modelling when compared to traditional approaches. This optimised data access ensures that end-users can efficiently interact with large datasets, leading to more streamlined and efficient analyses.

The cloud-based delivery of the GFTS project aligns with the overarching goal of Pangeo. In addition, the GFTS includes the development of a custom interactive Decision Support Tool (DST). The DST empowers non-technical users with an intuitive interface for better understanding the results of the GFTS project, leading to more informed decision-making. The integration with Pangeo and providing intuitive access to the GFTS data is not merely a technicality; it is a commitment to FAIR (Findable, Accessible, Interoperable and Reusable), TRUST (Transparency, Responsibility, User focus, Sustainability and Technology) and open science principles. 

In short, the GFTS project, within the Pangeo ecosystem, exemplifies how advanced data management, coupled with the optimization of data access through "data visitation," can significantly enhance the performance and usability of geoscience tools. This collaborative and innovative approach not only benefits the immediate goals of the GFTS project but contributes to the evolving landscape of community-driven geoscience initiatives.

How to cite: Wiesmann, D., Odaka, T., Fouilloux, A., Autret, E., Woillez, M., and Ragan-Kelley, B.: Harnessing the Pangeo ecosystem for delivering the cloud-based Global Fish Tracking System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10741, https://doi.org/10.5194/egusphere-egu24-10741, 2024.

EGU24-12410 | Orals | ESSI2.9

Towards Enhancing WaaS and Data Provenance over Reana 

Iraklis Klampanos, Antonis Ganios, and Antonis Troumpoukis

Interoperability and reproducibility are critical aspects of scientific computation. The data analysis platform Reana [1], developed by CERN, enhances the interoperability and reproducibility of scientific analyses by allowing researchers to describe, execute, and share their analyses. This is achieved via the execution of standardised scientific workflows, such as CWL, within reusable containers. Moreover, it allows execution to span different types of resources, such as Cloud and HPC. 

In this session we will present ongoing work to enhance Reana’s Workflows-as-a-Service (WaaS) functionality and also support Workflow registration and discoverability. Building upon the design goals and principles of the DARE platform [2], this work aims to enhance Reana by enabling users to register and discover available workflows within the system. In addition, we will present the integration of Data Provenance based on the W3C PROV-O standard [3] allowing the tracking and recording of data lineage in a systematic and dependable way across resource types. 

In summary, key aspects of this ongoing work include:

  • Workflows-as-a-Service (WaaS): Extending Reana's service-oriented mode of operation, allowing users to register, discover, access, execute, and manage workflows by name or ID, via APIs, therefore enhancing the platform's accessibility and usability.
  • Data Provenance based on W3C PROV-O: Implementing support for recording and visualising data lineage information in compliance with the W3C PROV-O standard. This ensures transparency and traceability of data processing steps, aiding in reproducibility and understanding of scientific analyses.

This work aims to broaden Reana's functionality, aligning with best practices for reproducible and transparent scientific research. We aim to make use of the enhanced Reana-based system on the European AI-on-demand platform [4], currently under development, to address the requirements of AI innovators and researchers when studying and executing large-scale AI-infused workflows.

References: 

[1] Simko et al., (2019). Reana: A system for reusable research data analyses. EPJ Web Conf., 214:06034, https://doi.org/10.1051/epjconf/201921406034

[2] Klampanos et al., (2020). DARE Platform: a Developer-Friendly and Self-Optimising Workflows-as-a-Service Framework for e-Science on the Cloud. Journal of Open Source Software, 5(54), 2664, https://doi.org/10.21105/joss.02664

[3] PROV-O: The PROV Ontology: https://www.w3.org/TR/prov-o/ (viewed 9 Jan 2024)

[4] The European AI-on-Demand platform: https://aiod.eu (viewed 9 Jan 2024)

This work has been has received funding from the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101070000.

How to cite: Klampanos, I., Ganios, A., and Troumpoukis, A.: Towards Enhancing WaaS and Data Provenance over Reana, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12410, https://doi.org/10.5194/egusphere-egu24-12410, 2024.

EGU24-12669 | ECS | Orals | ESSI2.9

DeployAI to Deliver Interoperability of Cloud and HPC Resources for Earth Observation in the Context of the European AI-on-Demand Platform 

Antonis Troumpoukis, Iraklis Klampanos, and Vangelis Karkaletsis

The European AI-on-Demand Platform (AIoD, http://aiod.eu) is a vital resource for leveraging and boosting the European AI research landscape towards economic growth and societal advancement across Europe. Following and emphasising European values, such as openness, transparency, and trustworthiness for developing and using AI technologies, the AIoD platform aims to become the main one-stop shop for exchanging and building AI resources and applications within the European AI innovation ecosystem, whilst also adhering to European values. The primary goal of the DIGITAL-EUROPE CSA initiative DeployAI (DIGITAL-2022-CLOUD-AI-B-03, 01/2024-12/2027) is to build, deploy, and launch a fully operational AIoD platform, promoting trustworthy, ethical, and transparent European AI solutions for the industry, with a focus on SMEs and the public sector.

Building on Open-source and trusted software, DeployAI will provide a number of technological assets such as a comprehensive and Trustworthy AI resource catalogue and marketplace offering responsible AI resources and tools, workflow composition and execution systems for prototyping and user-friendly creation of novel services, responsible foundational models and services to foster dependable innovation, etc. In addition, and building upon the results of the ICT-49 AI4Copernicus project [1], which provided a bridge between the AIoD platform and the Copernicus ecosystem and the DIAS platforms, DeployAI will integrate impactful Earth Observation AI services into the AIoD platform. These will include (but not limited to) satellite imagery preprocessing, land usage classification, crop type identification, super-resolution, and weather forecasting.

Furthermore, DeployAI will allow the rapid prototyping of AI applications and their deployment to a variety of Cloud/Edge/HPC infrastructures. The project will focus on establishing a cohesive interaction framework that integrates with European Data Spaces and Gaia-X initiatives, HPC systems with an emphasis on the EuroHPC context, and the European Open Science Cloud. Interfaces to European initiatives and industrial AI-capable cloud platforms will be further implemented to enable interoperability. This capability enables the execution of Earth Observation applications not only within the context of a DIAS/DAS but also within several other compute systems. This level of interoperability enhances the adaptability and accessibility of AI applications, fostering a collaborative environment where geoscientific workflows can be seamlessly executed across diverse computational infrastructures and made available to a wide audience of innovators.

[1] A. Troumpoukis et al., "Bridging the European Earth-Observation and AI Communities for Data-Intensive Innovation", 2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService), Athens, Greece, 2023, pp. 9-16, doi:10.1109/BigDataService58306.2023.00008.

This work has been has received funding from the European Union’s Digital Europe Programme (DIGITAL) under grant agreement No 101146490.

How to cite: Troumpoukis, A., Klampanos, I., and Karkaletsis, V.: DeployAI to Deliver Interoperability of Cloud and HPC Resources for Earth Observation in the Context of the European AI-on-Demand Platform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12669, https://doi.org/10.5194/egusphere-egu24-12669, 2024.

EGU24-15366 | ECS | Posters on site | ESSI2.9

Enabling seamless integration of Copernicus and in-situ data 

Iason Sotiropoulos, Athos Papanikolaou, Odysseas Sekkas, Anastasios Polydoros, Vassileios Tsetsos, Claudio Pisa, and Stamatia Rizou

BUILDSPACE aims to combine terrestrial data from buildings collected by IoT devices 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 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. A pivotal element and the foundational support of the BUILDSPACE ecosystem is the Core Platform and it plays a crucial role in facilitating seamless data exchange, secure and scalable data storage, and streamlined access to data from three Copernicus services, namely the Land, Atmosphere, and Climate Change.The platform's underlying technology is robust, incorporating two key components: OIDC for user authentication and group authorization over the data, and a REST API to handle various file operations. OIDC stands for OpenID Connect, a standard protocol that enables secure user authentication and allows for effective management of user groups and their access permissions. On the other hand, the platform employs a REST API for seamless handling of file-related tasks, including uploading, downloading, and sharing. This combination ensures efficient and secure data exchange within the system. Additionally, the use of an S3 compatible file system ensures secure and scalable file storage, while a separate metadata storage system enhances data organization and accessibility. Currently deployed on a Kubernetes cluster, this platform offers numerous advantages, including enhanced scalability, efficient resource management, and simplified deployment processes. The implementation of the Core Platform has led to a current focus on integrating APIs from Copernicus services into the Core Platform's API. This ongoing effort aims to enhance the platform's capabilities by seamlessly incorporating external data, enriching the overall functionality and utility of the project.

How to cite: Sotiropoulos, I., Papanikolaou, A., Sekkas, O., Polydoros, A., Tsetsos, V., Pisa, C., and Rizou, S.: Enabling seamless integration of Copernicus and in-situ data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15366, https://doi.org/10.5194/egusphere-egu24-15366, 2024.

EGU24-15416 | ECS | Orals | ESSI2.9

XDGGS: Xarray Extension for Discrete Global Grid Systems (DGGS) 

Alexander Kmoch, Benoît Bovy, Justus Magin, Ryan Abernathey, Peter Strobl, Alejandro Coca-Castro, Anne Fouilloux, Daniel Loos, and Tina Odaka

Traditional geospatial representations of the globe on a 2-dimensional plane often introduce distortions in area, distance, and angles. Discrete Global Grid Systems (DGGS) mitigate these distortions and introduce a hierarchical structure of global grids. Defined by ISO standards, DGGSs serve as spatial reference systems facilitating data cube construction, enabling integration and aggregation of multi-resolution data sources. Various tessellation schemes such as hexagons and triangles cater to different needs - equal area, optimal neighborhoods, congruent parent-child relationships, ease of use, or vector field representation in modeling flows.

The fusion of Discrete Global Grid Systems (DGGS) and Datacubes represents a promising synergy for integrated handling of planetary-scale data.

The recent Pangeo community initiative at the ESA BiDS'23 conference has led to significant advancements in supporting Discrete Global Grid Systems (DGGS) within the widely used Xarray package. This collaboration resulted in the development of the Xarray extension XDGGS (https://github.com/xarray-contrib/xdggs). The aim of xdggs is to provide a unified, high-level, and user-friendly API that simplifies working with various DGGS types and their respective backend libraries, seamlessly integrating with Xarray and the Pangeo scientific computing ecosystem. Executable notebooks demonstrating the use of the xdggs package are also developed to showcase its capabilities.

This development represents a significant step forward, though continuous efforts are necessary to broaden the accessibility of DGGS for scientific and operational applications, especially in handling gridded data such as global climate and ocean modeling, satellite imagery, raster data, and maps.

Keywords: Discrete Global Grid Systems, Xarray Extension, Geospatial Data Integration, Earth Observation, Data Cube, Scientific Collaboration

How to cite: Kmoch, A., Bovy, B., Magin, J., Abernathey, R., Strobl, P., Coca-Castro, A., Fouilloux, A., Loos, D., and Odaka, T.: XDGGS: Xarray Extension for Discrete Global Grid Systems (DGGS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15416, https://doi.org/10.5194/egusphere-egu24-15416, 2024.

EGU24-15872 | Posters on site | ESSI2.9

Deploying Pangeo on HPC: our experience with the Remote Sensing Deployment Analysis environmenT on SURF infrastructure 

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

The Pangeo software stack includes powerful tools that have the potential to revolutionize the way in which research on big (geo)data is conducted. A few of the aspects that make them very attractive to researchers are the ease of use of the Jupyter web-based interface, the level of integration of the tools with the Dask distributed computing library, and the possibility to seamlessly move from local deployments to large-scale infrastructures. 

The Pangeo community and project Pythia are playing a key role in providing training resources and examples that showcase what is possible with these tools. These are essential to guide interested researchers with clear end goals but also to provide inspiration for new applications. 

However, configuring and setting up a Pangeo-like deployment is not always straightforward. Scientists whose primary focus is domain-specific often do not have the time to spend solving issues that are mostly ICT in nature. In this contribution, we share our experience in providing support to researchers in running use cases backed by deployments based on Jupyter and Dask at the SURF supercomputing center in the Netherlands, in what we call the Remote Sensing Deployment Analysis environmenT (RS-DAT) project. 

Despite the popularity of cloud-based deployments, which are justified by the enormous data availability at various public cloud providers, we discuss the role that HPC infrastructure still plays for researchers, due to the ease of access via merit-based allocation grants and the requirements of integration with pre-existing workflows. We present the solution that we have identified to seamlessly access datasets from the SURF dCache massive storage system, we stress how installation and deployment scripts can facilitate adoption and re-use, and we finally highlight how technical research-support staff such as Research Software Engineers can be key in bridging researchers and HPC centers. 

How to cite: Nattino, F., Grootes, M. W., Chandramouli, P., Ku, O., Alidoost, F., and Dzigan, Y.: Deploying Pangeo on HPC: our experience with the Remote Sensing Deployment Analysis environmenT on SURF infrastructure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15872, https://doi.org/10.5194/egusphere-egu24-15872, 2024.

EGU24-17111 | Posters on site | ESSI2.9

Cloudifying Earth System Model Output 

Fabian Wachsmann

We introduce eerie.cloud (eerie.cloud.dkrz.de), a data server for efficient access to prominent climate data sets stored on disk at the German Climate Computing Center (DKRZ). We show how we “cloudify” data from two projects, EERIE and ERA5, and how one can benefit from it. 

The European Eddy-rich Earth System Model (EERIE) project aims to develop state-of-the-art high-resolution Earth System Models (ESM) that are able to resolve ocean mesoscale processes. These models are then used to perform simulations over centennial scales and make their output available for the global community. At present, the total volume of the EERIE data set exceeds 0.5PB  and is rapidly growing, posing challenges for data management.
ERA5 is the fifth generation ECMWF global atmospheric reanalysis. It is widely used as forcing data for climate model simulations, for model evaluation or for the analysis of climate trends. DKRZ maintains a 1.6 PB subset of ERA5 data at its native resolution.

We use Xpublish to set up the data server. Xpublish is a python package and a plugin for Pangeo's central analysis package Xarray. Its main feature is to provide ESM output by mapping any input data to virtual zarr data sets. Users can retrieve these data sets as if they were cloud-native and cloud-optimized.

eerie.cloud features

  • Parallel access to data subsets on chunk-level
  • Interfaces to make the data more FAIR
    • User friendly content overviews with displays of xarray-like dataset representations
    • Simple browsing and loading data with an intake catalog
  • On-the-fly server-side computation 
    • Register simple xarray routines for generating customized variables
    • Compression for speeding up downloads
  • Generation of interactive geographical plots, including animations

Eerie.cloud is a solution to make EERIE data more usable by a wider community.

How to cite: Wachsmann, F.: Cloudifying Earth System Model Output, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17111, https://doi.org/10.5194/egusphere-egu24-17111, 2024.

EGU24-17150 | ECS | Posters on site | ESSI2.9

Data access patterns of km-scale resolution models 

Janos Zimmermann, Florian Ziemen, and Tobias Kölling

Climate models produce vast amounts of output data. In the nextGEMS project, we have run the ICON model at 5 km resolution for 5 years, producing about 750 TB of output data from one simulation. To ease analysis, the data is stored at multiple temporal and spatial resolutions. The dataset is now analyzed by more than a hundred scientists on the DKRZ levante system. As disk space is limited, it is crucial to obtain information, which parts of this dataset are accessed frequently and need to be kept on disk, and which parts can be moved to the tape archive and only be fetched on request.

By storing the output as zarr files with many small files for the individual data chunks, and logging file access times, we obtained a detailed view of more than half a year of access to the nextGEMS dataset, even going to regional level for a given variable and time step. The evaluation of those access patterns offers the possibility to optimize various aspects such as caching, chunking, and archiving. Furthermore, it provides valuable information for designing future output configurations.

In this poster, we present the observed access patterns and discuss their implications for our chunking and archiving strategy. Leveraging an interactive visualization tool, we explore and compare access patterns, distinguishing frequently accessed subsets, sparsely accessed variables, and preferred resolutions. We furthermore provide information on how we analyzed the data access to enable other users to follow our approach.

How to cite: Zimmermann, J., Ziemen, F., and Kölling, T.: Data access patterns of km-scale resolution models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17150, https://doi.org/10.5194/egusphere-egu24-17150, 2024.

EGU24-18256 | Orals | ESSI2.9

Data access for km-scale resolution models 

Florian Ziemen, Tobias Kölling, and Lukas Kluft

With the transition to global, km-scale simulations, model outputs have grown in size, and efficient ways of accessing data have become more important than ever. This implies that the data storage has to be optimized for efficient read access to small sub-sets of the data, and multiple resolutions of the same data need to be provided for efficient analysis on coarse as well as fine-grained scales.

In this high-level overview presentation, we present an approach based on datasets. Each dataset represents a coherent subset of a model output (e.g. all model variables stored at daily resolution). Aiming for a minimum number of datasets makes us enforce consistency in the model output and thus eases analysis. Each dataset is served to the user as one zarr store, independent of the actual file layout on disks or other storage media. Multiple datasets are grouped in catalogs for findability.

By serving the data via https, we can implement a middle layer between the user and the storage systems, allowing to combine different storage backends behind a unifying frontend. At the same time, this approach allows us to largely build the system on existing technologies such as web servers and caches, and efficiently serve data to users outside the compute center where the data is stored.
The approach we present is currently under development in the BMBF project WarmWorld with contributions by the H2020 project nextGEMS, and we expect it to be useful for many other projects as well.

How to cite: Ziemen, F., Kölling, T., and Kluft, L.: Data access for km-scale resolution models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18256, https://doi.org/10.5194/egusphere-egu24-18256, 2024.

EGU24-18585 | ECS | Posters on site | ESSI2.9

STAC catalogs for time-varying in-situ data 

Justus Magin

The ability to search a collection of datasets is an important factor for the usefulness of the data. By organizing the metadata into catalogs, we can enable dataset discovery, look up file locations and avoid access to the data files before the actual computation. Spatio-Temporal Asset Catalogs (STAC) is a increasingly popular language-agnostic specification and vibrant ecosystem of tools for geospatial data catalogs, and is tailored for raster data like satellite imagery. It allows for a search using a variety of patterns, including the spatial and temporal extent.

In-situ data is heterogenous and would benefit from being cataloged, as well as the ecosystem of tools. However, due to the strict separation between the spatial and temporal dimensions in STAC the time-varying nature of in-situ data is not optimally captured. While for approximately stationary sensors like tide gauges, moorings, weather stations, and high-frequency radars this is not an issue (see https://doi.org/10.5194/egusphere-egu23-8096), it becomes troublesome for moving sensors, especially if the sensor moves at a high speed, covers big distances, or if the dataset contains a long time series.

To resolve this, we extend the STAC specification by replacing the geojson data with the JSON-encoded ODC moving feature standard.

How to cite: Magin, J.: STAC catalogs for time-varying in-situ data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18585, https://doi.org/10.5194/egusphere-egu24-18585, 2024.

EGU24-20779 | Orals | ESSI2.9

Project Pythia: Building an Inclusive Geoscience Community with Cookbooks 

John Clyne, Brian Rose, Orhan Eroglu, James Munroe, Ryan May, Drew Camron, Julia Kent, Amelia Snyder, Kevin Tyle, Maxwell Grover, and Robert Ford

Project Pythia is the educational arm of the Pangeo community, and provides a growing collection of community driven and developed training resources that help geoscientists navigate the Pangeo ecosystem, and the myriad complex technologies essential for today’s Big Data science challenges. Project Pythia began in 2020 with the support of a U.S. NSF EarthCube award. Much of the initial effort focused on Pythia Foundations: a collection of Jupyter Notebooks that covered essential topics such as Python language basics; managing projects with GitHub; authoring and using “binderized” Jupyter Notebooks; and many of Pangeo’s core packages such as Xarray, Pandas, and Matplotlib. Building upon Foundations, the Pythia community turned its attention toward creating Pythia Cookbooks: exemplar collections of recipes for transforming raw ingredients (publicly available, cloud-hosted data) into scientifically useful results. Built from Jupyter Notebooks, Cookbooks are explicitly tied to reproducible computational environments and supported by a rich infrastructure enabling collaborative authoring and automated health-checking – essential tools in the struggle against the widespread notebook obsolescence problem.

 

Open-access, cloud-based Cookbooks are a democratizing force for growing the capacity of current and future geoscientists to practice open science within the rapidly evolving open science ecosystem. In this talk we outline our vision of a sustainable, inclusive open geoscience community enabled by Cookbooks. With further support from the NSF, the Pythia community will accelerate the development and broad buy-in of these resources, demonstrating highly scalable versions of common analysis workflows on high-value datasets across the geosciences. Infrastructure will be deployed for performant data-proximate Cookbook authoring, testing, and use, on both commercial and public cloud platforms. Content and community will expand through annual workshops, outreach, and classroom use, with recruitment targeting under-served communities. Priorities will be guided by an independent steering board; sustainability will be achieved by nurturing a vibrant, inclusive community backed by automation that lowers barriers to participation.

How to cite: Clyne, J., Rose, B., Eroglu, O., Munroe, J., May, R., Camron, D., Kent, J., Snyder, A., Tyle, K., Grover, M., and Ford, R.: Project Pythia: Building an Inclusive Geoscience Community with Cookbooks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20779, https://doi.org/10.5194/egusphere-egu24-20779, 2024.

EGU24-20909 | ECS | Orals | ESSI2.9

UXarray: Extensions to Xarray to support unstructured grids 

Orhan Eroglu, Hongyu Chen, Philip Chmielowiec, John Clyne, Corrine DeCiampa, Cecile Hannay, Robert Jacob, Rajeev Jain, Richard Loft, Brian Medeiros, Lantao Sun, Paul Ullrich, and Colin Zarzycki

The arrival of kilometer-scale climate and global weather models presents substantial challenges for the analysis and visualization of the resulting data, not only because of their tremendous size but also because of the employment of unstructured grids upon which the governing equations of state are solved. Few Open Source analysis and visualization software tools exist that are capable of operating directly on unstructured grid data. Those that do exist are not comprehensive in the capabilities they offer, do not scale adequately, or both. Recognizing this gap in much-needed capability, Project Raijin - funded by an NSF EarthCube award - and the DOE SEATS project, launched a collaborative effort to develop an open source Python package called UXarray. 

UXarray extends the widely used Xarray package, providing support for operating directly (without regridding) on unstructured grid model outputs found in the Earth System Sciences, such as CAM-SE, MPAS, SCRIP, UGRID, and in the future, ICON. Much like Xarray, UXarray provides fundamental analysis and visualization operators, upon which more specialized, domain-specific capabilities can be layered. This talk will present an overview of the current capabilities of UXarray, provide a roadmap for near term future development, and will describe how the Pangeo community can contribute to this on-going effort.

How to cite: Eroglu, O., Chen, H., Chmielowiec, P., Clyne, J., DeCiampa, C., Hannay, C., Jacob, R., Jain, R., Loft, R., Medeiros, B., Sun, L., Ullrich, P., and Zarzycki, C.: UXarray: Extensions to Xarray to support unstructured grids, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20909, https://doi.org/10.5194/egusphere-egu24-20909, 2024.

EGU24-271 | PICO | ESSI3.3

Open Science Collaboration across Eath Observation Platforms 

Ingo Simonis, Marie-Francoise Voidrot, Rachel Opitz, and Piotr Zaborowski
Collaborative Open Science is essential to addressing complex challenges whose solutions prioritize integrity and require cross-domain integrations. Today, building workflows, processes, and data flows across domains and sectors remains technically difficult and practically resource intensive, creating barriers to whole-systems change. While organizations increasingly aim to demonstrate accountability, they often lack the tools to take action effectively. By making it simple to connect data and platforms together in transparent, reusable and reproducible workflows, the OGC Open Science Persistent Demonstrator (OSPD) aims to enable responsible innovation through collaborative open science. The OSPD focuses specifically on using geospatial and earth observation (EO) data to enable and demonstrate solutions that create capacity for novel research and accelerate the practical implementation of this research.
Collaborative Open Science and FAIR (Findable, Accessible, Interoperable, Reusable) data are widely recognized as critical tools for taking advantage of the opportunities created through addressing complex social and environmental challenges. To date, many millions have been invested in hundreds of initiatives to enable access to analytical tools, provide data management, data integration and exchange, translate research results, and support reproduction and testing of workflows for new applications. These investments have resulted in a plethora of new data, protocols, tools and workflows, but these resources frequently remain siloed, difficult to use, and poorly understood, and as a result they are falling short of their full potential for wider impact and their long term value is limited.
This presentation will illustrate how the OGC OSPD Initiative, through its design, development and testing activities, provides answers to leading questions such as:
  • How can we design Open Science workflows that enable integration across platforms designed for diverse applications used in different domains to increase their value?
  • How can we lower barriers for end users (decision makers, managers in industry, scientists, community groups) who need to create Open Science workflows, processes, and data flows across domains and sectors remains technically difficult and practically resource intensive, creating?
  • How can Open Science workflows and platforms enable collaboration between stakeholders in different domains and sectors?
  • How can we empower organizations to demonstrate accountability in their analytical workflows, data, and representations of information through Open Science?
  • What Open Science tools do organizations need to take action effectively?
  • How can Open Science and FAIR data standards practically support accountability?
  • How can we make it simple to connect data and platforms together in transparent, reusable and reproducible (FAIR) workflows?
  • What are the specific challenges of using geospatial, earth observation (EO), and complementary data in this context?

How to cite: Simonis, I., Voidrot, M.-F., Opitz, R., and Zaborowski, P.: Open Science Collaboration across Eath Observation Platforms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-271, https://doi.org/10.5194/egusphere-egu24-271, 2024.

EGU24-1445 | ECS | PICO | ESSI3.3

A Software Toolkit for Advancing our Understanding of Land Surface Interactions: Recent developments to the SimSphere SVAT model 

Christina Lekka, George P. Petropoulos, Vasileios Anagnostopoulos, Spyridon E. Detsikas, Petros Katsafados, and Efthimios Karympalis

Mathematical models are widely used today to study the intricate physical processes and interactions among the different components of the Earth’s system. Such models are often used synergistically with Earth Observation (EO) data allowing to derive spatiotemporal estimates of key parameters characterising land surface interactions. This synergy allows combining the horizontal coverage and spectral resolution of EO data with the vertical coverage and fine temporal continuity of those models. SimSphere is a mathematical model belonging to the Soil Vegetation Atmosphere Transfer (SVAT) models. As a software toolkit, it has been developed in Java and it is used either as a stand-alone application or synergistically with EO data. The model use is constantly expanding worldwide both as an educational and as a research tool. Herein we present recent advancements introduced to SimSphere. We have comprehensively tested and updated the model code and added new functionalities which are illustrated herein using a variety of case studies. For example, it presents herein the new functionality that allows it to be applied over complex/heterogeneous landscapes, and this new model capability is demonstrated in experimental settings in various European ecosystems. The present study contributes towards efforts ongoing nowadays by the users' community of the model and is also very timely, given the increasing interest in SimSphere particularly towards the development of EO-based operational products characterising the Earth’s water cycle.  The research presented herein has been conducted in the framework of the project LISTEN-EO (DeveLoping new awareness and Innovative toolS to support efficient waTer rEsources man-agement Exploiting geoinformatiOn technologies), funded by the Hellenic Foundation for Research and Innovation programme (ID 015898). 

Keywords: SVAT, SimSphere, Earth Observation, land surface interactions, LISTEN-EO

How to cite: Lekka, C., Petropoulos, G. P., Anagnostopoulos, V., Detsikas, S. E., Katsafados, P., and Karympalis, E.: A Software Toolkit for Advancing our Understanding of Land Surface Interactions: Recent developments to the SimSphere SVAT model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1445, https://doi.org/10.5194/egusphere-egu24-1445, 2024.

EGU24-1707 | PICO | ESSI3.3

Topic Analysis and Classification of EGU Conference Abstracts 

Jens Klump, Chau Nguyen, John Hille, and Michael Stewart

The corpus of Abstracts from the EGU General Assemblies 2000 - 2023 covers a wide range of Earth, planetary and space sciences topics, each with multiple subtopics. The abstracts are all in English, fairly uniform in length, cover one broad subject area, and are licenced under a permissive licence that allows further processing (CC BY 4.0), making this a high-quality text corpus for studies using natural language processing (NLP) and for the finetuning of Large Language Models (LLM). Our study makes use of openly available NLP software libraries and LLMs.

In the first phase of this study, we were interested in finding out how well abstracts map to the topics covered by EGU Divisions and whether co-organisation of sessions contributes to or dilutes topics. The abstracts are available only in unstructured formats such as Portable Document Format (PDF) or plain text in XML extracts from the conference database. They are identified by abstract numbers but carry no information on the session or division where they were originally presented. We reconstructed this information from the online conference programme.

To be able to employ a supervised learning approach of matching abstracts to topics, we defined the topics to be synonymous with the 23 scientific divisions of the EGU, using the division and co-listed divisions as topic labels.

We finetuned the Bidirectional Encoder Representations from Transformers (BERT) and the slightly simplified DistillBERT language models for our topic modelling exercise. We also compared the machine classifications against a random association of abstracts and topics. Preliminary results obtained from our experiments show that using a machine learning model performs well in classifying the conference abstracts (accuracy = 0.66). The accuracy varies between divisions (0.40 for NP to 0.96 for G) and improves when taking co-organisation between divisions into account. Starting from one year of abstracts (EGU 2015), we plan to expand our analysis to cover all abstracts from all EGU General Assemblies (EGU 2000 - 2024).

How to cite: Klump, J., Nguyen, C., Hille, J., and Stewart, M.: Topic Analysis and Classification of EGU Conference Abstracts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1707, https://doi.org/10.5194/egusphere-egu24-1707, 2024.

EGU24-5658 | ECS | PICO | ESSI3.3

TropiDash: a comprehensive open-source dashboard for Tropical Cyclone data visualization and analysis 

Laura Paredes-Fortuny, Filippo Dainelli, and Paolo Colombo

Tropical Cyclones (TCs) are synoptic-scale storm systems rapidly rotating around a center of low atmospheric pressure which primarily derive their energy from exchanges of heat and moisture between the air and sea. These cyclones are among the most impactful geophysical phenomena, inflicting substantial economic damages and numerous fatalities. Key hazards associated with TCs include intense winds, extreme rainfall, and storm surges, which frequently result in extensive coastal flooding. Because of the severe consequences of their impacts, precise monitoring of these events and effective preparation for their occurrences are crucial to ensure the safety and resilience of populations and infrastructure.

 

For successful monitoring and preparation, the access to relevant factors associated with TC forecasts, such as risk projections and impact variables, must be adequate and user-friendly, enabling users to rapidly locate and comprehend the information they seek. To achieve this objective, visual tools and dashboards that concentrate interdisciplinary information and data from diverse sources serve as powerful summarization methods. Summary dashboards and tools facilitate easy access to information for all users ranging from experts and policymakers to common citizens. They consist of a platform offering a comprehensive overview of the situation, supporting informed decision-making. Current open-source tools for consulting TC data have limitations. They tend to be highly specialized, offering a limited selection of maps or graphs that cover only a portion of TC-related information. They also often lack interactivity, which restricts the user experience and the search for specific information. Furthermore, these tools can be complex to use due to inadequate documentation or challenges in presenting multiple pieces of information concurrently.

 

In this work, we introduce a novel free open-source dashboard designed to surpass the limitations of existing tools, displaying a comprehensive set of information regarding TC hazards. TropiDash presents several strengths that enhance user experience and accessibility. Developed in the widely recognized Jupyter Notebook programming environment, it is easily accessible either through the installation guide on its GitHub repository or by initiating its Binder environment. The dashboard features a user-friendly interface utilizing Python widgets and the Voilà protocol. It aggregates data from various sources spanning multiple domains: from cyclone properties, such as track forecasts and strike probability maps, to atmospheric variable fields (wind speed and direction, temperature, precipitation), to risk and vulnerability information, such as cyclone risk, coastal flood risk, population density. All this is made available while providing the user with a wide range of interactivity, from choosing the cyclone to selecting the variables of their interest to roam over the interactive maps.

 

The first version of TropiDash was realized in the context of Code for Earth 2023,  a program for the development of open-source software organized by the European Centre for Medium-Range Weather Forecasts. Here we present an improved and optimized version. 

How to cite: Paredes-Fortuny, L., Dainelli, F., and Colombo, P.: TropiDash: a comprehensive open-source dashboard for Tropical Cyclone data visualization and analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5658, https://doi.org/10.5194/egusphere-egu24-5658, 2024.

To initiate, maintain and accelerate behavioral change towards Open and FAIR practices, tangible benefits for scientific communities and especially early career scientists are a critical key success factor. The realization of such benefits, by due credit, funding, or other means requires underlying workflows, enabled by underlying infrastructures and standards, which are operational, reliable and trusted. Many education efforts are under way to educate and motivate researchers how to embrace and particpate in Open and FAIR efforts, including the open geospatial community software projects of the OSGeo foundation. Still, from the perspective of a developer of research software, the current general service quality of offerings for PID-/citation-based credit remains limited, fickle, partially unpredictable and frustrating. This presentation demonstrates these challenges by real world examples from OSGeo open geospatial projects, such as QGIS, GRASS GIS and proj and resulting PID-references in publications. Further, a service centered approach is introduced to enable both end users and Open/FAIR communities to assess the overall service quality through Technological Readiness Levels (TRL), to improve the user experience by building trust and to focus further development ressources.

How to cite: Löwe, P.: Open geospatial research software in 2024: Assessing service quality with technology readiness levels , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6254, https://doi.org/10.5194/egusphere-egu24-6254, 2024.

EGU24-8146 | ECS | PICO | ESSI3.3

Xarray-regrid: regridding with ease 

Bart Schilperoort, Claire Donnelly, Yang Liu, and Gerbrand Koren

In geosciences different sources of data are often on different grids. These can be at different resolutions, but also have the grid centers at different locations. To be able to use these different sources of data in models or analyses, they have to be re-projected to a common grid. Popular tools for this are the command-line tool ‘Climate Data Operators’ (CDO) and the Earth System Modeling Framework (ESMF).

These tools work well but have some downsides: CDO is a command-line tool and as such the regridded data has to be written to disk. ESMPy, the Python package for ESMF, is only available on Linux and Mac OSX, and does not support out-of-core computing. Both tools rely on binary dependencies, which can make them more difficult to install. Additionally, many geoscientists already use xarray for analyzing and processing (netCDF) data.

For this use case we developed xarray-regrid, a lightweight xarray plugin which can regrid (rectilinear) data using the linear, nearest-neighbor, cubic, and conservative methods. The code is open source and modularly designed to facilitate the addition of alternative methods. Xarray-regrid is fully implemented in Python and therefore can be used on any platform. Using Dask, the computation is fully parallelized and can be performed out-of-core. This allows for fast processing of large datasets without running out of memory.

Xarray-regrid is available on the Python Package Index (pip install xarray-regrid), and its source code is available on GitHub at https://github.com/EXCITED-CO2/xarray-regrid 

How to cite: Schilperoort, B., Donnelly, C., Liu, Y., and Koren, G.: Xarray-regrid: regridding with ease, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8146, https://doi.org/10.5194/egusphere-egu24-8146, 2024.

EGU24-12004 | PICO | ESSI3.3

NASA’s Open Science Platform VEDA (Visualization, Exploration and Data Analytics) 

Zac Deziel, Aimee Barciauskas, Jonas Solvsteen, Manil Maskey, Brian Freitag, Slesa Adhikari, Anthony Boyd, Alexandra Kirk, David Bitner, and Vincent Sarago

VEDA is an open-source science cyberinfrastructure for data processing, visualization, exploration, and geographic information systems (GIS) capabilities (https://www.earthdata.nasa.gov/esds/veda, https://www.earthdata.nasa.gov/dashboard/). NASA has always had open data policies, so data has always been openly accessible for anyone, but NASA hasn’t constantly exposed it in friendly interfaces or analytics platforms. VEDA attempts to make NASA’s Earth data mean more

As VEDA supplies data and computing services through its dashboard and JupyterHub applications and engages with communities such as EGU, it is a critical component of NASA’s open science initiative. VEDA’s adoption of existing and emerging standards such as STAC, Cloud-Optimized GeoTIFFs, Zarr, the Features API, and the Tiles API ensures interoperability and reusability.

In the past year, VEDA has expanded its impact in 3 ways: (1) the reuse of its infrastructure to stand up the multi-agency Greenhouse Gas Center (https://earth.gov/ghgcenter, announced at COP28) and NASA’s Earth Information Center (https://earth.gov/), (2) the reuse of data APIs across applications, such as VEDA data in NASA’s Enterprise GIS, and (3) the generalization of the data system architecture into a free and open source framework called eoAPI. 

VEDA has also maintained and deepened its connections to the Multi-Mission Algorithm and Analysis Platform (MAAP). MAAP is a research data infrastructure (RDI) for above-ground biomass estimation. MAAP is reusing and contributing to the eoAPI data system and plans to integrate the analytics components (JupyterHub and data processing system) further.

Now that VEDA has manifested GHG Center and EIC, VEDA is a project where innovation happens. The VEDA team, composed of NASA project leads, scientists, designers, and developers, constantly works to resolve old and new challenges in managing EO architectures. For example, the team designs and implements interfaces to manage STAC metadata. eoAPI is a result of this innovative environment.

eoAPI is a new, open-source, installable combination of data catalog and associated services for earth observation and related data with a cloud-computing infrastructure first approach. eoAPI combines STAC data ingestion, data hosting (pgSTAC), and querying services (stac-fastapi) with raster (Titiler) and vector services (TiPg). eoAPI is built for reuse and has been used beyond VEDA, GHG, and EIC to deliver MS Planetary Computer and AWS ASDI’s data catalog and applications for the International Federation of the Red Cross and MercyCorps.

This presentation will demo the current capabilities of eoAPI and VEDA and discuss how these capabilities were designed and architected with the central goals of science delivery, reproducible science, and interoperability to support the re-use of data and APIs across the Earth Science ecosystem of tools. The presentation will close with VEDA and eoAPI’s plans.

How to cite: Deziel, Z., Barciauskas, A., Solvsteen, J., Maskey, M., Freitag, B., Adhikari, S., Boyd, A., Kirk, A., Bitner, D., and Sarago, V.: NASA’s Open Science Platform VEDA (Visualization, Exploration and Data Analytics), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12004, https://doi.org/10.5194/egusphere-egu24-12004, 2024.

Rust Geodesy (RG) is an open source library, written in Rust [1], for experiments with geodetic transformations, software, and standards [2], [3]. RG originated from attempts to demonstrate architectural innovations for potential improvement of the ubiquitous transformation system PROJ, with which it consequentially shares many characteristics.
In parallel, however, RG has also evolved into a quite capable geodetic tool in its own right. And over the last few releases it has expanded from the "geometrical geodesy" background of PROJ, into supporting a number of operations from the realm of physical geodesy (deflections of the vertical, normal gravity models, gravity reduction, etc.), while still maintaining the key architectural feature of run time construction of complex operations from pipelines of simpler operators.
But in particular, the RG design has been nudged towards supporting the development and maintenance of geodetic transformations, as reflected by these characteristics:
  • A clear and compact syntax for specification of processing pipelines
  • ...but also syntactical backward compatibility and interoperability, through additional support for PROJ's older and more verbose syntax
  • Extensibility through straightforward, tight integration betwwen system supplied and user written operators
  • ..but also support for loose integration with arbitrary ancillary software, through support of plain text operator definitions and grid files
  • ...and ad-hoc abstractions through support for run-time defined user macros
  • Seamless interoperability with arbitrarily complex application program data structures, i.e. integrating with the user program, rather than forcing the use of library provided data structures, and
  • Support of roundtrip consistency checks
The RG data flow architecture is based on the foundational concept of "coordinate sets" from the OGC/ISO geospatial standards series [4]. Hence, in contrast to PROJ operators, which operate on a single coordinate tuple, RG operators operate on an entire set of coordinate tuples at a time. While this may seem immaterial at the source code level, it gives the compiler a wider context for introducing vectorisation, leveraging the SIMD instruction sets of modern computers to transform more than one coordinate tuple at a time.
Recently, SIMD-support has also arrived in the Web Assembly (Wasm) implementations of the major web platforms [5], and when compiled to Wasm, RG has shown to be a compact, lightweight and practical library for use on the web [6], [7]. So with RG's combined forays into the realms of Wasm and physical geodesy, the vista of "generic geodesy in the browser" is now more than just a mirage.
 
[1] Steve Klabnik and Carol Nichols, 2022: The Rust Programming Language, 2nd edition, 560 pp., San Francisco, CA, USA: No Starch Press
[2] Thomas Knudsen, 2021: Ruminations on Rust Geodesy: Overall architecture and philosophy.
URL: https://github.com/busstoptaktik/geodesy/blob/main/ruminations/000-rumination.md
[3] Thomas Knudsen: Geodesy. URL https://github.com/busstoptaktik/geodesy
[4] Roger Lott (ed), 2019: OGC Abstract Specification Topic 2: Referencing by coordinates.
URL https://docs.ogc.org/as/18-005r4/18-005r4.html
[5] WebAssembly Feature Extensions. URL: https://webassembly.org/features/
[6] Kyle Barron, 2023: Prototyping GeoRust + GeoArrow in WebAssembly. Efficient, vectorized geospatial operations in the browser,
URL https://observablehq.com/@kylebarron/prototyping-georust-geoarrow-in-webassembly
[7] Sean Rennie, 2023: Testing geodesy-wasm,
URL https://observablehq.com/d/3ff9d9b8f0b5168a

How to cite: Knudsen, T.: Generic geodesy in the browser? Recent developments in Rust Geodesy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12024, https://doi.org/10.5194/egusphere-egu24-12024, 2024.

EGU24-12786 | ECS | PICO | ESSI3.3

Quantifying water security using hyperresolution hydrological modelling on top of an Open Data Cube (ODC) 

Luis Felipe Patino Velasquez, Dr. Elizabeth Lewis, Prof. Jon Mills, and Dr. Stephen Birkinshaw

For many areas across the globe physically-based hydrological models have a fundamental role helping devise a comprehensive and robust plan for future climate change adaption and preparedness informing water management and flood initiatives. Now that the advances in satellite and sensor technology coupled with the development of cloud computing have enable the advancement of hydrology as a data-intensive science, there is a considerable impetus and interest in future research and approaches in the use of these emerging technologies to develop new insights that contribute to fundamental aspects of the hydrological sciences. Whilst increasing volumes of Earth Observation (EO) data couple with advances in cloud computing have enable the enhancement of hydrological modelling, one of the remaining challenges is ensuring a seamless data pipeline to the final hydrological prediction. As a result, this poses a significant set of questions in the use of EO data for hydrology. The current research is situated at the junction of three areas: hydrological physical modelling, satellite EO data and the implementation of the Earth Observation Data Cube (EODC) paradigma. This presentation will outline the development and use of a open source modelling workflow integrating analysis ready data (ARD) through the implementation of the Open Data Cube (ODC) data exploitation architecture with a physically-based, spatially-distributed hydrological model (SHETRAN), as glimpse into the relevance of EO data cube solutions in lowering the technology and EO data barriers. Thus, enabling users to harnes existent open source EO datasets and software at minimum cost and effort with the objective to enable a more open and reproducible hydrological science.

How to cite: Patino Velasquez, L. F., Lewis, Dr. E., Mills, P. J., and Birkinshaw, Dr. S.: Quantifying water security using hyperresolution hydrological modelling on top of an Open Data Cube (ODC), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12786, https://doi.org/10.5194/egusphere-egu24-12786, 2024.

EGU24-15972 | PICO | ESSI3.3

The LUE open source software for building numerical simulation models on HPC 

Derek Karssenberg, Oliver Schmitz, and Kor de Jong

When developing large-scale numerical earth system models traditionally knowledge of a broad range of programming technologies is required to support hardware from laptops up to supercomputers. A knowledge that scientists specialized in a particular geosciences domain mostly do not have and often do not want to acquire. Their emphasis is on describing and implementing the processes rather than for instance dealing with parallelization of model equations. Moreover, when model characteristics or domain extents change their chosen parallelisation technique may already be obsolete or require significant refactoring to adapt to the new situation. We develop the open-source LUE modelling framework, a software environment allowing domain scientists – who may not be familiar with the development of high-performance applications – to develop numerical simulation models that seamlessly scale when adding additional hardware resources. LUE comprises of a data model for the storage of field-based and agent-based data, and provides a broad range of map algebra operations as building blocks for model construction. Each spatial operation is implemented in C++ using HPX, a library and runtime environment providing asynchronous execution of interdependent tasks on both shared-memory and distributed computing systems. LUE provides a Python module and therefore a single high-level API whether models are run on laptops or HPC systems. In our presentation we demonstrate two capabilities of LUE. First, using the built-in operations we implemented a spatially distributed hydrological model including surface water routing. The model runs for the African continent at 100 metres spatial and hourly temporal resolution. Secondly, to demonstrate the extensibility we utilise LUE’s focal operation framework to implement an individual kernel calculating greenness visibility exposure. Our PICO presentation will also include future extensions of the framework in particular for agent-based modelling and integration of machine learning model components.

How to cite: Karssenberg, D., Schmitz, O., and de Jong, K.: The LUE open source software for building numerical simulation models on HPC, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15972, https://doi.org/10.5194/egusphere-egu24-15972, 2024.

EGU24-19155 | PICO | ESSI3.3

FAIR Environmental Data through a STAC-Driven Inter-Institutional Data Catalog Infrastructure – Status quo of the Cat4KIT-project 

Mostafa Hadizadeh, Christof Lorenz, Sabine Barthlott, Romy Fösig, Katharina Loewe, Corinna Rebmann, Benjamin Ertl, Robert Ulrich, and Felix Bach

In the rapidly advancing domain of environmental research, the deployment of a comprehensive, state-of-the-art Research Data Management (RDM) framework is increasingly pivotal.  Such a framework is key to ensure FAIR data, laying the groundwork for transparent and reproducible earth system sciences.

Today, datasets associated with research articles are commonly published via prominent data repositories like Pangaea or Zenodo. Conversely, data used in actual day-to-day research and inter-institutional projects tends to be shared through basic cloud storage solutions or, even worse, via email. This practice, however, often conflicts with the FAIR principles, as much of this data ends up in private, restricted systems and local storage, limiting its broader accessibility and use.

In response to this challenge, our research project Cat4KIT aims to establish a cross-institutional catalog and Research Data Management framework. The Cat4KIT framework is, hence, an important building block towards the FAIRification of environmental data. It not only streamlines the process of ensuring availability and accessibility of large-scale environmental datasets but also significantly enhances their value for interdisciplinary research and informed decision-making in environmental policy.

The Cat4KIT system comprises four essential elements: data service provision, meta(data) harvesting, catalogue service, and user-friendly data presentation. The data service provision module is tailored to facilitate access to data within typical storage systems by using well-defined and standardized community interfaces via tools like the Thredds data server, Intake Catalogues, and the OGC SensorThings API. By this, we ensure seamless data retrieval and management for typical use-casers in environmental sciences.

(Meta)data harvesting via our so-called DS2STAC-package entails collecting metadata from various data services, followed by creating STAC-metadata and integrating it into our STAC-API-based catalog service.

This catalog service module synergizes diverse datasets into a cohesive, searchable spatial catalog, enhancing data discoverability and utility via our Cat4KIT UI.

Finally, our framework's data portal is tailored to elevate data accessibility and comprehensibility for a wide audience, including researchers, enabling them to efficiently search, filter, and navigate through data from decentralized research data infrastructures.

One notable characteristic of Cat4KIT is its dependence on open-source solutions and strict adherence to community standards. This guarantees not just the framework's ability to function well with current data systems but also its simple adaption and expansion to meet future needs. Our presentation demonstrates the technical structure of Cat4KIT, examining the development and integration of each module to adhere to the FAIR principles. Additionally, it showcases examples to illustrate the practical use of the framework in real-life situations, emphasizing its efficacy in enhancing data management practices within KIT and its potential relevance in other research organizations.

How to cite: Hadizadeh, M., Lorenz, C., Barthlott, S., Fösig, R., Loewe, K., Rebmann, C., Ertl, B., Ulrich, R., and Bach, F.: FAIR Environmental Data through a STAC-Driven Inter-Institutional Data Catalog Infrastructure – Status quo of the Cat4KIT-project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19155, https://doi.org/10.5194/egusphere-egu24-19155, 2024.

EGU24-19421 | PICO | ESSI3.3

Implementing National Copernicus services for hydrology and natural hazard monitoring at NVE using Open Source tools Apache Airflow and actinia 

Stefan Blumentrath, Yngve Are Antonsen, Aron Widforss, Niklas Fossli Gjersø, Rune Verpe Engeset, and Solveig Havstad Winsvold

The Norwegian Water Resources and Energy Directorate (NVE) is tasked with management of water- and energy resources in Norway, as well as reducing the risk of damages associated with landslides and flooding. Copernicus satellite data can provide valuable insight for those tasks.

The vast amount of Copernicus data however requires scalable and robust solutions for processing. Standardized and modular workflows help safeguarding maintainability and efficiency of service delivery. In order to implement operational Copernicus services at NVE, the Open Source OSGeo Community project actinia was introduced together with the Open Source Apache Airflow software as a platform for delivering operational Copernicus services at national scale.

actinia (https://actinia-org.github.io/) is a REST API for scalable, distributed, and high performance processing of time series of satellite images, as well as geographical raster and vector data. It is a modular system that uses mainly GRASS GIS for computational tasks.

Apache Airflow (https://airflow.apache.org/) is an orchestration solution that allows to programmatically author, schedule and monitor workflows.

In the presentation, we will illustrate how Apache Airflow and actinia work together and present selected examples of current and future applications operationalized on the platform. Those applications cover currently:

  • Avalanches
  • Flooding
  • snow cover
  • lake ice

More services related to NVE`s area of responsibility are being investigated, like landslides, slush flows, glacier lake outburst floods, and specific land cover changes...

Finally, we discuss challenges and opportunities of using Open Source Software tools and collaborative science approaches at NVE in national, operational services.

How to cite: Blumentrath, S., Are Antonsen, Y., Widforss, A., Fossli Gjersø, N., Verpe Engeset, R., and Havstad Winsvold, S.: Implementing National Copernicus services for hydrology and natural hazard monitoring at NVE using Open Source tools Apache Airflow and actinia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19421, https://doi.org/10.5194/egusphere-egu24-19421, 2024.

EGU24-20137 | PICO | ESSI3.3

ALAMEDA – A scalable multi-domain metadata management platform 

Felix Mühlbauer, Martin Hammitzsch, Marc Hanisch, Gunnar Pruß, Rainer Häner, and Oliver Rach

Modern Earth sciences produce a continuous increasing amount of data. These data consist of the measurements/observations and descriptive information (metadata) and include semantic classifications (semantics). Depending on the geoscientific parameter, metadata are stored in a variety of different databases, standards and semantics, which is obstructive for interoperability in terms of limited data access and exchange, searchability and comparability. Examples of common data types with very different structure and metadata needs are maps, geochemical data derived from field samples, or time series data measured with a sensor at a point, such as precipitation or soil moisture.

So far, there is a large gap between the capabilities of databases to capture metadata and their practical use. ALAMEDA is designed as modular structured metadata management platform for curation, compilation, administration, visualization, storage and sharing of meta information of lab-, field- and modelling datasets. As a pilot application for stable isotope and soil moisture data ALAMEDA will enable to search, access and compare meta information across organization-, system- and domain boundaries.

ALAMEDA covers 5 major categories: observation & measurements, sample & data history, sensor & devices, methods & processing, environmental characteristics (spatio & temporal). These categories are hierarchically structured, interlinkable and filled with specific metadata attributes (e.g. name, data, location, methods for sample preparation, measuring and data processing, etc.). For the pilot, all meta information will be provided by existing and wellestablished data management tools (e.g. mDIS, SMS, LI2, etc.).

In ALAMEDA, all information is brought together and will be available via web interfaces. Furthermore, the project focuses on features such as metadata curation with intuitive graphical user interfaces, the adoption of well-established standards, the use of domain-controlled vocabularies and the provision of interfaces for a standards-based dissemination of aggregated information. Finally, ALAMEDA should be integrated into the DataHub (Hub-Terra).

Currently the project is in the final phase and we want to present the developed concepts and software and lessions learned.

How to cite: Mühlbauer, F., Hammitzsch, M., Hanisch, M., Pruß, G., Häner, R., and Rach, O.: ALAMEDA – A scalable multi-domain metadata management platform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20137, https://doi.org/10.5194/egusphere-egu24-20137, 2024.

Geospatial users have long been constructing immersive 3D environments for diverse applications such as urban planning, environmental and geological studies, 3D analysis, and more recently, by replicating the physical world as a digital twin. In this pico presentation, we aim to illustrate the dynamic evolution of Indexed 3D Scene Layers (I3S), an OGC Community Standard designed for an efficient streaming and storage of substantial geospatial content. I3S has rapidly adapted to encompass new use cases and techniques, pushing the boundaries of geospatial visualization and analysis.

I3S facilitates the efficient transmission of diverse 3D geospatial data types, ranging from discrete 3D objects with attributes and integrated surface meshes to extensive point cloud data covering expansive geographic regions. Moreover, it excels in streaming highly detailed Building Information Model (BIM) content to web browsers, mobile applications, and desktop platforms.

The most recent enhancement to OGC's I3S streaming standard, Building Scene Layer (BSL), introduces a sophisticated framework for effective tiling of massive BIM content. BSL leverages Bounding Volume Hierarchy (BVH) and geometric error driven selection and display criteria, incorporates attribute-driven filtering, and employs various graphics optimizations. These advancements collectively enable the seamless streaming of otherwise voluminous Building Information Model (BIM) 3D assets.

During this session, we will spotlight the practical implementation of I3S BSL across diverse ecosystems, including loaders.gl and CesiumJS. This flexibility empowers users to select their preferred front-end application based on specific requirements and preferences.

How to cite: Belayneh, T.: Democratizing BIM Data Access in Digital Twins Through OGC I3S 3D Streaming Standard, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20842, https://doi.org/10.5194/egusphere-egu24-20842, 2024.

GI2 – Data networks and analysis

EGU24-147 | Orals | GI2.3

Mechanisms of seasonal variations of dissolved 137Cs concentrations in freshwaters: Fukushima and Chernobyl 

Aleksei Konoplev, Honoka Kurosawa, Yoshifumi Wakiyama, Yasunori Igarashi, and Kenji Nanba

Analysis of available monitoring data on seasonal variations of dissolved radiocesium concentrations in the water bodies of accidentally contaminated areas has revealed two basic mechanisms responsible for regular seasonal variations of dissolved 137Cs concentrations in water bodies (increase in summer and decrease in winter), namely temperature dependence of radiocesium desorption from sediments to solution, and ion-exchange remobilization of radiocesium by cations of ammonium generated as a result of organic matter decomposition in anoxic conditions. An equation has been derived describing seasonal variations of dissolved radiocesium in water bodies considering two basic factors: water temperature and combined concentration of basic competitive cations. In Fukushima rivers, which are mostly shallow and fast-flowing, ammonium concentration is usually negligible. For them, the predominant factor of dissolved 137Cs seasonality is the temperature dependence of 137Cs desorption. For stagnated stratified waters of ponds, lakes, and dam reservoirs in anoxic conditions, the role of ammonium in 137Cs mobilization can be comparable with that of water temperature or even be prevalent. Results of a field experimental study of dissolved 137Cs seasonality in three ponds of Okuma town in the near area of the Fukushima Daiichi nuclear power plant are presented.

This research was supported by Environmental Radioactivity Research Center (ERAN) Projects I-23-11 and I-23-12.

How to cite: Konoplev, A., Kurosawa, H., Wakiyama, Y., Igarashi, Y., and Nanba, K.: Mechanisms of seasonal variations of dissolved 137Cs concentrations in freshwaters: Fukushima and Chernobyl, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-147, https://doi.org/10.5194/egusphere-egu24-147, 2024.

EGU24-1993 | ECS | Orals | GI2.3

Optimizing impoundment operation of Three Georges Reservoir for enhancing hydropower output and reducing carbon emission 

Yanlai Zhou, Zhihao Ning, Fanqi Lin, and Fi-John Chang

Reservoir impoundment operation has far-reaching effects on the synergies between hydropower output, floodwater utilization, and carbon fluxes. However, there's a notable rise in flood risks, especially when advancing impoundment timings and lifting reservoir water levels. This study proposed a novel reservoir impoundment operation framework prioritizing flood prevention, hydropower generation, floodwater management, and carbon emission control. The Three Gorges Reservoir in the Yangtze River was selected as a case study. The results demonstrated that initiating impoundment on or after September 1st could ensure flood safety. The best scheme of reservoir impoundment operation could significantly boost synergistic benefits, enhancing hydropower output by 1.39 billion kW·h (5.3%) and the water impoundment rate by 10.2% while reducing carbon emissions by 51.65 GgCO2e/yr (15.8%) and increasing organic carbon burials by 10.03 GgCO2e/yr (10.3%), respectively, compared with the standard operation policy. This study not only provides scientific and technical support for reservoir impoundment operation benefiting water-carbon nexus synergies but also presents policymakers with viable options to pre-experience the risks and benefits for sustainable hydropower through adjusted impoundment schedules and reservoir water levels. 

How to cite: Zhou, Y., Ning, Z., Lin, F., and Chang, F.-J.: Optimizing impoundment operation of Three Georges Reservoir for enhancing hydropower output and reducing carbon emission, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1993, https://doi.org/10.5194/egusphere-egu24-1993, 2024.

EGU24-2292 | ECS | Posters on site | GI2.3

AI-Driven Hydro-Insights: Proactive Water Resource Management for Sustainable Agriculture in the Face of Climate Change 

Pu Yun Kow, Yu-Wen Chang, and Fi-John Chang

Climate change profoundly affects natural water resources by increasing extreme rainfall and persistent drought events. This impact has led to a rising likelihood of over-extraction of groundwater by Taiwanese farmers due to insufficient water resources. Quantifying groundwater pumping activities is challenging, thereby prompting this study to introduce a hybrid AI model combining a Convolutional-based Autoencoder with LSTM. The objective is to explore the spatiotemporal relationship between hydrometeorology and groundwater for providing a quantitative assessment of groundwater resources.

To construct the model, a comprehensive dataset spanning two decades (2000-2019) is utilized, incorporating information from 33 groundwater monitoring wells in the Jhuoshuei River basin of Taiwan. Two types of datasets, observation and simulation, are employed for a robust analysis. The hybrid AI model yields accurate three-month-ahead forecasts for shallow groundwater in the Jhuoshuei River basin, with R2 performance ranging from 0.70 to 0.87 for T+1 (short-term forecasts) and from 0.42 to 0.69 for T+3 (long-term forecasts).

The significance of these forecasts lies in their potential to empower farmers to increase crop cultivation efficiency. The long-term forecasts aid in formulating strategic plans for crop cultivation and fallow periods, promoting efficient agricultural management. Simultaneously, the short-term forecasts empower farmers to enhance irrigation efficiency, leading to a reduction in regional water consumption. This proactive approach aligns with Sustainable Development Goals (SDGs) 11 and 12, fostering sustainable water resource management practices. In essence, this hybrid AI model emerges as a valuable tool for proactive and adaptive water resource management, particularly crucial in the context of evolving climate conditions.

Keywords: Groundwater management, AI, Deep Learning, regional forecast, machine learning, SDGs, Taiwan

How to cite: Kow, P. Y., Chang, Y.-W., and Chang, F.-J.: AI-Driven Hydro-Insights: Proactive Water Resource Management for Sustainable Agriculture in the Face of Climate Change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2292, https://doi.org/10.5194/egusphere-egu24-2292, 2024.

    In the face of evolving global weather patterns attributed to climate change, precise prediction of groundwater levels is increasingly essential for effective water resource management. This significance is particularly pronounced in regions like Taiwan, where groundwater is a pivotal water source. This study focuses on the Zhuoshui River basin in central Taiwan and explores a Transformer Neural Network (TNN) based on a 20-year hydrometeorological dataset at a 10-day scale to predict groundwater levels. Our investigation reveals that the innovative TNN model outperforms conventional models, such as the Convolutional Neural Network (CNN) and the Long Short-Term Memory neural network (LSTM). The TNN model's superiority is evidenced by its enhanced predictive capabilities, as measured by metrics like R2 and MAE. Notably, the TNN model excels in providing precise forecasts (MAE < 1 m) for the majority of groundwater monitoring stations, notwithstanding challenges in areas facing overexploitation.

    This groundbreaking study marks the first attempt of the TNN model to predict groundwater levels, showcasing its robust performance and broad applicability. The TNN model emerges as a valuable tool for groundwater level prediction, contributing to sustainable groundwater management and effective resource utilization amid the backdrop of climate change. With the potential to address climate-related challenges, the TNN model stands as a pivotal asset for optimizing strategies in groundwater resource management.

How to cite: Sun, W., Liou, J.-Y., and Chang, F.-J.: Revolutionizing Groundwater Level Prediction in Taiwan: Unleashing the Power of Transformer Neural Networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2293, https://doi.org/10.5194/egusphere-egu24-2293, 2024.

EGU24-2519 | Posters on site | GI2.3

Enhancing Climate-Resilient Aquaculture in Yunlin County, Taiwan: A Comparative Analysis of Aquavoltaic Systems and Conventional Methods 

Chu-Han Chen, Meng-Hsin Lee, Hang-Yeh Lin, and Fi-John Chang

The escalating frequency of climate-related disasters underscores the imperative need for robust adaptive strategies to mitigate the impacts of extreme weather events. Crafting effective adaptive solutions, however, presents a formidable challenge. This research investigates the potential of aquavoltaic systems to enhance adaptive capacity and promote low-carbon production in fishing villages grappling with climate change. Focused on clam farming in Yunlin County, Taiwan, our study builds innovative Water-Energy-Food-Land-Climate (W-E-F-L-C) Nexus models using system dynamics (SD) techniques to compare the synergistic benefits and resource utilization efficiency between aquavoltaic systems and conventional aquacultural methods. This study meticulously catalogues factors from SD models and incorporates them into a comprehensive life cycle assessment (LCA) to scrutinize the environmental impacts of both aquavoltaic and conventional systems. Carbon emission data is rigorously calculated by LCA, revealing the carbon emissions flow resulting from interactions between these factors.

Additionally, this study conducts a scenario analysis to gain insight into how aquavoltaic and conventional aquacultural systems respond to key influencing factors such as temperature and rainfall. Our findings underscore that elevated temperatures and intensified rainfall significantly impact conventional clam farming compared to the aquavoltaic system. Aquavoltaics emerges as a robust and viable mechanism for aquaculture in the face of capricious weather conditions. Particularly noteworthy is the effectiveness of solar panels in intercepting and diverting rainwater during heavy rainfall in summer, reducing the risk of diluting pond water and thereby stabilize water quality. The shading effect induced by photovoltaic installations also contributes to moderating water temperatures, especially under direct sunlight. By synergizing physical mechanisms with advanced simulation techniques, this study propels toward a more efficient and resilient paradigm in aquaculture. Aquavoltaics demonstrate promising potential for sustainable and low-carbon production as well as promoting the resilience of fishing villages. This study not only illuminates the intricate dynamics of climate-resilient aquaculture but also stands as a milestone for the development of sustainable aquaculture practices.

How to cite: Chen, C.-H., Lee, M.-H., Lin, H.-Y., and Chang, F.-J.: Enhancing Climate-Resilient Aquaculture in Yunlin County, Taiwan: A Comparative Analysis of Aquavoltaic Systems and Conventional Methods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2519, https://doi.org/10.5194/egusphere-egu24-2519, 2024.

EGU24-2601 | ECS | Orals | GI2.3

Regularized framework for inverse problems in continuous atmospheric emissions: An application to the Fukushima accident 

Sheng Fang, Xinwen Dong, Shuhan Zhuang, and Yuhan Xu

The inverse modeling technique has been widely adopted to estimate atmospheric emissions, which aims to complement the subjective inference and provides rare retrieval when unavailable source information. The inversion generally requires the environmental observations and the source-receptor relationship constructed by an air dispersion model. But these two kinds of input lead to an ill-posed inverse problem in continuous atmospheric emissions. For the observations, the measurement network cannot capture all information on a specific emission progress, because of the nature of spatial sparse and limited temporal collections. Besides, there are inevitable model-observation discrepancies introduced by the discretization and imperfect parameters in the physical model and the diagnostic meteorology model. In this dilemma, the estimated atmospheric emissions are featured with discontinuous elements such as temporal gaps, artificial oscillations, and negative values, which are biased from the continuous emission progress in the real world.

This paper describes a regularized inversion framework to objectively address these artifacts and promote the continuity of emissions. This framework consists of the joint estimation model and the total variation (TV) regularization to handle the model-observation discrepancies and the insufficient observations respectively. The former implements site-by-site corrections by adding a diagonal matrix to the residual term of the inversion, and thus reduces the oscillations. The latter enhances a prior with the piecewise-constant feature by the L1-norm of the gradient of the emission vector, and therefore recovers the missing emissions. An adaptive parameterization scheme is tailored for the TV regularization to correct negative values.

The proposed method has been applied to the Fukushima accident to estimate the lasting emissions of 137Cs, facing the observations with nearly half temporal incomplete of the estimation period and unavoidable deviations introduced by the atmospheric dispersion model. The results produce a discrete emission profile that accurately approximates the continuous emission progress, which better matches the recognized one by expert judgments than nine published estimates, with a Pearson’s correlation coefficient of 0.92 and an index of agreement of 0.82. The estimated profile agrees with the timing of on-site gamma dose rate peaks as well. The evaluation was also conducted with respect to atmospheric simulations, providing significantly improved air concentrations and depositions, with the ten-factor agreement (FAC10) values of 0.56 and 0.99 respectively. The uncertainty analysis with respect to the regularization parameters shows a limited variation range of the estimation error (median value below 15.04%), demonstrating the potential for operational inversions with automatic parameterization.

How to cite: Fang, S., Dong, X., Zhuang, S., and Xu, Y.: Regularized framework for inverse problems in continuous atmospheric emissions: An application to the Fukushima accident, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2601, https://doi.org/10.5194/egusphere-egu24-2601, 2024.

EGU24-3268 | Orals | GI2.3

Impacts of wildfire on desorption of radionuclide and subsequent wash-offs in the Chornobyl Exclusion Zone 

Yasunori Igarashi, Valentyn Protsak, Gennady Laptev, Igor Maloshtan, Dmitry Samoilov, Serhii Kirieiev, Yuichi Onda, and Alexei Konoplev

The Chornobyl wildfires of 2020 raises concerns regarding radionuclides wash-off from post fire sites. The objective of this study is to determine the speciation of 137Cs and 90Sr in the ash and soil. And to reveal the impact of the wildfires on concentrations of 137Cs and 90Sr in river water in Chornobyl. To accomplish this objective, extraction tests were conducted using ash and soil samples collected immediately after the 2020 fires to determine the water-soluble and exchangeable fractions of 137Cs and 90Sr in the ash and soil. Long-term river-water radionuclide concentration records were also analyzed.

The results showed that the solid–liquid distribution coefficient (Kd) of ash was significantly lower than that of soil for 137Cs, while for 90Sr there was no significant difference in Kd between ash and soil. Analysis of river water data indicated that 90Sr concentrations higher than the Ukrainian drinking water standard (> 2 Bq/L) were observed more frequently following wildfires in the Sakhan River catchment. The fires increased 90Sr concentrations over the following two years, particularly in the spring, when snowmelt causes substantial releases, and in the summer and autumn, when surface flows occurred. High 90Sr concentrations were observed only within the Chornobyl Exclusion Zone, so additional human uptake of or dose exposure to 90Sr from river water is not expected.

The Chornobyl wildfires, which is a short period when radioactive contamination levels are elevated in the ecosystem, affected radionuclide speciation, turning the catchment into a location where radioactive contamination levels are significantly higher than in the surrounding area for the redistribution of radionuclides.

How to cite: Igarashi, Y., Protsak, V., Laptev, G., Maloshtan, I., Samoilov, D., Kirieiev, S., Onda, Y., and Konoplev, A.: Impacts of wildfire on desorption of radionuclide and subsequent wash-offs in the Chornobyl Exclusion Zone, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3268, https://doi.org/10.5194/egusphere-egu24-3268, 2024.

EGU24-4338 | ECS | Orals | GI2.3

The Influence of Remedial Actions on Ambient Dose Rates in Fukushima Forests 

Donovan Anderson, Hiroaki Kato, and Yuichi Onda

This study evaluates the long-term impact of government-led decontamination efforts on air dose rates in Fukushima forests affected by the 2011 nuclear disaster. While decontamination successfully mitigated radiation risks, its influence on air dose rates over time remains understudied, particularly in comparison to non-remediated forests. A comprehensive assessment spanning 2013 to 2020 was conducted, utilizing governmental decontamination data and monitoring adjacent untreated forests. Despite initial increases post-decontamination, air dose rates generally stabilized, following a trend indicative of physical decay. The study found that dominate tree species in forests influenced dose rate reduction. Broadleaf forests maintained lower post-decontamination dose rates compared to untreated counterparts, while cedar forests experienced increased post-decontamination rates, reverting to pre-decontamination levels. Both forest types exhibited similar annual decrease trends due to physical and environmental decay, with red pine in non-decontaminated forests showing the slowest decline. Analysis of radioactive cesium concentrations in organic matter and soil revealed a gradual transfer from organic matter to soil. Decontamination reduced concentrations in organic material but had no discernible effect on soil concentrations, indicating an ongoing transfer of radioactive materials from organic matter to soil. This emphasizes the need for future remediation strategies to assess local natural restoration potential and this study offers crucial insights for refining forest decontamination strategies and underscores the importance of factoring in ecosystem dynamics in radiation remediation planning.

How to cite: Anderson, D., Kato, H., and Onda, Y.: The Influence of Remedial Actions on Ambient Dose Rates in Fukushima Forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4338, https://doi.org/10.5194/egusphere-egu24-4338, 2024.

EGU24-7089 | Orals | GI2.3

Simulation of tritium releases into the atmosphere during the Fukushima accident and into the ocean due to planned discharge of treated water 

Alexandre Cauquoin, Maksym Gusyev, Yoshiki Komuro, Hayoung Bong, Atsushi Okazaki, and Kei Yoshimura

Following the accident at the Fukushima Daiichi Nuclear Power Plant (FDNPP) in March 2011, large quantities of radioactive materials were released into the atmosphere and ocean. Since the FDNPP nuclear accident, Tokyo Electric Power Company (TEPCO) operators have been implementing measures to reduce groundwater inflow into the FDNPP damaged reactor buildings while pumping water to cool the nuclear reactors and fuel debris. The resulting huge water volume began the discharge into the ocean from August 2023, after being treated by an Advanced Liquid Processing System (ALPS) to remove radionuclides for acceptable discharge levels except tritium. Tritium releases from the FDNPP accident and the ALPS treated water raise questions about the impact on tritium in precipitation in Japan, the removal time of anthropogenic tritium in groundwater and the oceanic transport of tritium from released ALPS treated water. 

In this two-part study, we present (1) the modeling of tritium in precipitation during the FDNPP accident using an atmosphere general circulation model (AGCM), and (2) a sensitivity simulation of tritium concentration in the ocean due to planned ALPS treated water release in the next decades by TEPCO using an ocean general circulation model (OGCM). 

For the atmospheric part, we used the isotope-enabled AGCM MIROC5-iso, in which tritium has been implemented [1], and adapted an estimated atmospheric release of iodine-131 [2] for the anthropogenic tritium source. We found good agreement with the tritium in precipitation observations in Japan for 2011 and subsequent years, despite MIROC5-iso’s rather coarse horizontal resolution (approximately 2.8°). Together with measured tritium data in Japan, our modeled results can be used to interpret mean transit times of Fukushima surface and groundwater systems and in other Asian systems (see abstract of Gusyev et al. in the same session).

For the oceanic part, we used the OGCM COCO4.9, which is the ocean component of the Model for Interdisciplinary Research on Climate, version 6 (MIROC6 [3]), and the tritium discharge scenario from TEPCO. Tritium concentration at the ocean surface reaches approximately 3 Bq/m3 near the release site and varies between 0.01 and 0.25 Bq/m3 in the North Pacific Ocean, well below the natural tritium level (approximately 50 Bq/m3 [4]). For this kind of projection simulation, the use of a fully coupled atmosphere-ocean model would make it possible to model tritium concentration in both the atmosphere and the ocean, as well as the dynamics of exchanges within and between these water cycle reservoirs.

 

[1] Cauquoin et al.: Modeling natural tritium in precipitation and its dependence on decadal variations of solar activity using the atmospheric general circulation model MIROC5-iso, J. Geophys. Res. Atmos., in review (minor revisions).

[2] Katata et al., Atmos. Chem. Phys., 15, 1029–1070, https://doi.org/10.5194/acp-15-1029-2015, 2015.

[3] Tatebe et al., Geosci. Model Dev., 12, 2727–2765, https://doi.org/10.5194/gmd-12-2727-2019, 2019.

[4] Jenkins et al., Earth Syst. Sci. Data, 11, 441–454, https://doi.org/10.5194/essd-11-441-2019, 2019.

How to cite: Cauquoin, A., Gusyev, M., Komuro, Y., Bong, H., Okazaki, A., and Yoshimura, K.: Simulation of tritium releases into the atmosphere during the Fukushima accident and into the ocean due to planned discharge of treated water, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7089, https://doi.org/10.5194/egusphere-egu24-7089, 2024.

EGU24-7140 | Posters on site | GI2.3

Effect of 137Cs desorption from sediment on the formation of dissolved 137Cs concentrations in dam discharge water 

Hideki Tsuji, Hironori Funaki, and Seiji Hayashi

In the region affected by the Fukushima nuclear accident in 2011, some freshwater fish shipments continue to be suspended owing to radioactive contamination (mainly 137Cs) of the aquatic environment. In predicting the future 137Cs contamination of aquatic organisms, investigations must focus on the dynamics of 137Cs in dissolved form, which is highly bioavailable and abundant in the environment. In particular, dam lakes that deposit large amounts of sediment contaminated with 137Cs and have a long residence time of water can substantially influence the dynamics of 137Cs in rivers, as suggested by prior research. This study focuses on the effect of desorption of 137Cs from lake sediment on the formation of dissolved 137Cs concentrations in dam discharge water, using the results from monitoring surveys at two dam lakes located near the Fukushima Daiichi Nuclear Power Plant.

We collected inflow and discharge water from the Matsugabo and Yokokawa dams in Fukushima Prefecture every month from 2014 and measured the concentration of dissolved and particulate 137Cs in the water using the cartridge filter method. On the basis of these results, combined with flow data from the dam lakes, we estimated the annual budgets of 137Cs (inflow/outflow) in the dam lakes. For the particulate form, annual 137Cs inflow into the lakes decreased by more than 80% in most years, indicating that most of the inflow particles sedimented. For the dissolved form, the annual discharge of 137Cs was higher than the annual inflow of 137Cs, concurring with results from a neighboring dam lake. This increment suggests 137Cs desorption from the sediment.

According to the monthly monitoring data, the dissolved 137Cs concentration in the dam discharge water at some periods showed a higher value than the peak value from the previous year. This phenomenon was observed when the reservoir storage rate of the dam lake fell below approximately 30%. To determine the main source of dissolved 137Cs in the dam lake, we investigated the horizontal distribution of the dissolved 137Cs concentrations at several points in Yokokawa dam lake and the vertical distribution of the dissolved 137Cs concentration at the center of the lake in August 2023, when the water level was very low. The concentration of dissolved 137Cs in the lake water was found to increase in the inlet part of the lake, while the concentration remained almost the same in the downstream direction from the site. The concentration of dissolved 137Cs at the center of the lake was almost unchanged vertically. This trend was different from the increase in the concentration of dissolved 137Cs in bottom water, previously observed at the same location (Tsuji et al., 2022). These results indicate that 137Cs desorption from sediment in the inlet area mainly led to the increase in the dissolved 137Cs concentrations in the lake water, in part owing to the low volume of flowing water.

How to cite: Tsuji, H., Funaki, H., and Hayashi, S.: Effect of 137Cs desorption from sediment on the formation of dissolved 137Cs concentrations in dam discharge water, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7140, https://doi.org/10.5194/egusphere-egu24-7140, 2024.

EGU24-7423 | Posters on site | GI2.3

Mechanisms of dissolved-form 137Cs runoff from forest source watersheds  

Yutaro Nagata, Yuichi Onda, Junko Takahashi, and Koichi Sakakibara

The concentration of dissolved-form 137Cs in forested rivers is known to increase during rainstorms, and direct leaching from litter and soil water is considered to be a factor. There have also been many studies showing that competing ions such as K+ and NH4+ promote the elution of 137Cs. However, there are no examples of detailed measurements of 137Cs concentrations and water quality characteristics of stream water and water passing through litter during actual rainstorms. In this study, stream water, throughfall,  water passing through litter, and groundwater were sampled in a small watershed in Fukushima Prefecture, Japan, which was affected by the Fukushima Daiichi Nuclear Power Plant, to measure dissolved 137Cs and dissolved organic carbon (DOC), K+and NH4+. NH4+ was not detected in stream water. The average concentrations of dissolved137Cs, DOC and K+ were 6.36 (mBq/L), 0.51 (mg/L) and 0.14 (mg/L), respectively, while the concentrations of 137Cs and DOC doubled to 13.38 (mBq/L), 1.13 (mg/L) during rainfall event and the K+concentrations remained unchanged (0.15mg/L). The concentrations of 137Cs and DOC  in the water passing through the litter were 50 and 30 times higher than in the stream water, respectively, suggesting that the high concentrations of dissolved 137Cs at the time of runoff were formed by leaching from the litter rather than by the presence of competing ions. The amount of 137Cs and K+eluted from the litter increased in the order of near-channel, saturated zone at run-off and slope, while the amount of DOC eluted from the litter was lower near the channel. These results suggest that 137Cs, K+and DOC release from near-channel litter is lower than that from litter on the slope because of the progress of leaching due to the occurrence of saturated surface flow.

How to cite: Nagata, Y., Onda, Y., Takahashi, J., and Sakakibara, K.: Mechanisms of dissolved-form 137Cs runoff from forest source watersheds , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7423, https://doi.org/10.5194/egusphere-egu24-7423, 2024.

EGU24-7677 | Posters on site | GI2.3

Downward migration of Cs-137 in soils reduce root uptake of Japanese cedar in Fukushima 

Junko Takahashi, Satoshi Iguchi, Takuya Sasaki, and Yuichi Onda

Introduction

Radiocesium (Cs-137) deposited on forests was intercepted by the canopy, then migrated to the litter layer and eventually to the soil layer, where some of it has been absorbed by roots and circulated through the forest ecosystem for a long time. In other words, the amount of Cs-137 uptake by roots will control the long-term dynamics in the forest ecosystem in the future, temporal changes in Cs-137 in tree roots have rarely been reported. In this study, we investigated the Cs-137 concentration and inventory in the soil and very fine (VF) roots (< 0.5 mm) of Japanese cedar from 2011 to 2020.

Methods

An approximately 3 m x 3 m plot was established in a cedar forest (initial deposition 440 kBq m-2) in the Yamakiya district of Kawamata Town, Fukushima Prefecture. Litter and soil samples were collected twice a year during 2011-2012 and once a year after 2013 using a scraper plate at 0.5 cm intervals for 0-5 cm, 1 cm intervals for 5-10 cm, and 5 cm intervals for 10-20 cm. Root samples were collected by further separating only the roots with tweezers from soil samples in 2012, 2015, 2017, and 2020, and washed by ultrasonic homogenizer to remove soil particles on the root surface. The roots measured were absorptive VF roots of 0.5 mm or less of the current year's growth.

Results and discussions

The Cs-137 concentration in the litter layer was still decreasing exponentially more than 12 years after the accident, its inventory was about 0.2-0.5% of the deposited amount. The depth distribution of Cs-137 concentration in the mineral soil layers was fitted with an exponential equation until 2019, but after 2020, the peak concentration shifted slightly downward and was fitted with a hyperbolic function. The Cs-137 inventory in the soil increased over time due to the migration from the forest canopy and litter layers, whereas that in the VF roots decreased in 2020. Especially, the Cs-137 inventory in the VF roots in the 0–2 cm of soil reached 89% in 2012; however, it decreased with time to approximately 43% in 2020. This decrease in the Cs-137 concentration in the VF roots at 0–2 cm was caused by the decrease in Cs-137 concentration in the litter layers. Although the Cs-137 concentration in the VF roots below 2 cm increased with increasing Cs-137 concentration in the soil, the downward migration of Cs-137 within the soil can reduce the amount of Cs-137 absorbed by roots because the VF root biomass decreases exponentially with depth. In other words, Cs-137 can be removed from the long-term active cycles of forest ecosystems as they migrate deeper into the soil without physical decontamination. This natural downward migration process can be regarded as a “self-cleaning” of the forest ecosystem, resulting in a decrease in the air dose rate and the amount of Cs-137 absorbed by roots.

How to cite: Takahashi, J., Iguchi, S., Sasaki, T., and Onda, Y.: Downward migration of Cs-137 in soils reduce root uptake of Japanese cedar in Fukushima, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7677, https://doi.org/10.5194/egusphere-egu24-7677, 2024.

EGU24-7685 | ECS | Posters on site | GI2.3

Comparison of cesium-bearing microparticles from marine and terrestrial sources 

Hikaru Miura, Takashi Ishimaru, Jota Kanda, Yukari Ito, and Atsushi Kubo

Radionuclides including radioactive Cs were released into the environment due to the Fukushima Daiichi Nuclear Power Plant accident in 2011. Two years after the accident, glassy water-resistant particles incorporating radioactive Cs were first reported. Such glassy particles are called cesium-bearing microparticles (CsMPs). CsMPs have been studied because (i) they have information on the condition in the reactor at the time of the accident, and (ii) there is concern about the exposure to the humans and the other organisms.

Several types of CsMPs have been reported, which is assumed to reflect the difference in the accidental progress of each unit. It is also known that CsMPs were transported in the atmospheric plume at the time of emission and therefore have different deposition regions. Type-A CsMPs, are presumed to originate from Unit 2, deposited over a wide area including the Kanto region due to their small size (~0.1–10 µm). Type-B CsMPs, are presumed to originate from Unit 1, deposited in a limited area in the north direction because of their large size (50–400 µm). Matrix of Types-A and -B CsMPs is SiO2 but Type-A CsMPs have higher concentration of volatile elements including Cs than Type-B CsMPs due to the difference in forming process. Type-A CsMPs were formed through gas condensation, whereas Type-B CsMPs were formed through melt solidification.

The presence of CsMPs emitted from Unit 3 in the ocean was confirmed by our research. The plume at the time of the emission of radionuclides from Unit 3 was in the ocean direction, which suggests that many CsMPs from Unit 3 deposited directly into the ocean. We will report the comparison of CsMPs from marine and terrestrial sources. In addition, we reported Type-A CsMPs from suspended particles in rivers and marine samples, such as plankton net and suspended particle samples. This fact suggests that Type-A CsMPs deposited on land and transported to the ocean through rivers. The presence of CsMPs may be the cause of the overestimation of solid–water distribution coefficient for marine sediments and particulate matters and apparent high concentration factor of marine biota of radioactive Cs.

How to cite: Miura, H., Ishimaru, T., Kanda, J., Ito, Y., and Kubo, A.: Comparison of cesium-bearing microparticles from marine and terrestrial sources, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7685, https://doi.org/10.5194/egusphere-egu24-7685, 2024.

The Zaporizhzhia nuclear power plant (ZNPP) has been occupied by Russian aggressors since March 4, 2022. Its proximity to the combat zone results in a real risk of an accident with radioactivity emissions. There have been a number of blackouts at ZNPP (the most recent one was reported on December 2, 2023, lasting for approximately 5 hours), which could potentially lead to an accident with a scenario similar to that of the 2011 Fukushima Daiichi NPP disaster. The objective of this research is to assess possible contamination of the territory of Ukraine and neighboring countries by Cs-137, emitted in a hypothetical accident at ZNPP, depending on weather patterns usually observed over the domain. The assessment is based on numerical simulations of atmospheric transport, dispersion and deposition processes.

In order to obtain an input meteorology for the dispersion/deposition simulations, we chose 37 typical weather patterns out of 153 that were objectively identified in the domain during 2018-2020. Our selection aimed to keep seasonal and frequency distribution of the patterns in the sampled population. Generally, the selected patterns included 22 cyclonic, 12 anticyclonic, and 3 situations of western transport. Their mean duration was approximately 6 days. 3D meteorological data for the selected weather patterns were generated by means of the WRF v4.3 meteorological model based on ERA5 reanalysis data.

The source term parameterization was based on freely available information published in scientific papers, reports etc. Several Cs-137 emission scenarios were considered by varying an emitted fraction of the total core inventory (50% and 3.43%) and a period of time when the source was active (24, 32, and 40 hours). The dispersion/deposition calculations were performed with the CALPUFF v6 and HYSPLIT v5.2.3 atmospheric dispersion models. Using these two models, which implement different computation algorithms, allowed us to perform the verification of the computed results.

Our calculations showed that a hypothetical accident with the most conservative emission scenario (emitted 50% of the total core inventory) could lead to significant contamination of not only the territory of Ukraine but also neighboring countries. Generally, depending on the weather pattern, from 10 to 80% of the emitted Cs-137 could be deposited on the territory of Ukraine. The reduction of the total emission obviously leads to decreased absolute values of the contamination, however the fractions of deposited in Ukraine Cs-137 stay unchanged for each weather pattern.

 

The work is supported by the grant program University for Ukraine (U4U) and The Yale School of the Environment. Oleg Skrynyk also acknowledges the support from the MSCA4Ukraine fellowship program, which is funded by the European Union.

How to cite: Balabukh, V., Skrynyk, O., Bubin, S., and Laptev, G.: Possible contamination of Ukraine and neighboring countries by Cs-137 due to a hypothetical accident at the Zaporizhzhia NPP as a consequence of the Russian aggression, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10247, https://doi.org/10.5194/egusphere-egu24-10247, 2024.

EGU24-12226 | ECS | Orals | GI2.3

Perspectives on dynamic water quality modeling across continental and watershed scales 

Olivia Miller, Scott Ator, Mike Hess, Daniel Jones, Patrick Longley, Morgan McDonnell, Matthew Miller, Annie Putman, Dale Robertson, David Saad, Noah Schmadel, Gregory Schwarz, Andrew Sekellick, Kenneth Skinner, Richard Smith, and Daniel Wise

Stream water-quality and its drivers vary across time and space, but we only monitor a small fraction of streams consistently over long periods of time. Such limited monitoring necessitates the development and application of spatially explicit and dynamic models to predict water quality at unmonitored locations. Historically, data and computational limitations have hindered temporally variable prediction efforts across large spatial scales. However, hybrid statistical and process models, such as Spatially Referenced Regression on Watershed attributes (SPARROW), can provide spatially explicit, accurate predictions of water quality constituents with substantially lower computational cost than process-only models while retaining process-level information that can be obscured within machine learning models. An emerging next generation of such hybrid models moves beyond temporally static predictions into dynamic predictions. Here, we present regional- and continental-scale dynamic SPARROW models developed across the United States to simulate annual salinity and seasonal nutrient loads and concentrations over decades. Dynamic SPARROW models account for temporal variability of constituent sources and processes that deliver constituents from the landscape to streams. In addition, dynamic SPARROW models quantify lagged delivery of contaminants to streams that may have accumulated in soils, groundwater, and vegetation. Results quantify that legacy sources can vary by constituent, location, and time, and provide inference into river responses and lags to management activities. For example, groundwater storage contributes between 66 and 82% of the dissolved solids load to streams in the Upper Colorado River Basin, while lagged storage contributes on average between 20% to nearly 50% of the total nutrient load to Illinois River Basin streams.  Ongoing work to expand dynamic representation of loading up to the continental United States will provide further insight into the continually evolving impacts of legacy and other sources on riverine water quality. Dynamic representation of key processes across spatial scales provides new opportunities for more informed management that can improve water quality for human and ecosystem uses.

How to cite: Miller, O., Ator, S., Hess, M., Jones, D., Longley, P., McDonnell, M., Miller, M., Putman, A., Robertson, D., Saad, D., Schmadel, N., Schwarz, G., Sekellick, A., Skinner, K., Smith, R., and Wise, D.: Perspectives on dynamic water quality modeling across continental and watershed scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12226, https://doi.org/10.5194/egusphere-egu24-12226, 2024.

EGU24-13386 | Posters on site | GI2.3 | Highlight

Multi-model simulation of the radionuclide transfer in the Yellow Sea as a result of hypothetical atmospheric deposition 

Kyeong Ok Kim, Roman Bezhenar, Ivan Kovalets, Igor Brovchenko, Vladimir Maderich, and Kyonghwan Kwon

After accidents at the Chornobyl NPP in 1986 and Fukushima Daiichi NPP in 2011, it became clear that there are many causes that can lead to a nuclear accident, including techno-genic and natural disasters. There is a danger of damage to the Zaporizhzhia NPP, with the subsequent release of radioactivity into the environment, as a result of the Russian invasion of Ukraine. The coastline of the Yellow Sea and East China Sea(YSECS) is a place where 9 NPPs are in operation in China and Korea. Since they are semi-enclosed seas with a very high density of population, any potential nuclear accident in the region can significantly contaminate the marine environment and affect the health of many people.

In the current study, a set of numerical models for the first time was applied to simulate the spreading of radionuclides in the environment as a result of the hypothetical accident at the Haiyang Nuclear Power Plant in China. The scenario of accidental release with containment-bypass was considered in this work. The atmospheric transport and deposition of radionuclides on the sea surface were simulated by the FLEXPART model. The set of 1450 dispersion scenarios following hypothetical accidental releases with different start dates were calculated for the next 120 h after release start, thus covering meteorological conditions from 1 Mar 2020 to 28 Feb 2021. Scenario with the heaviest deposition densities on the Yellow Sea was selected. These results were used as a source term for three different marine dispersion model simulating the transfer and fate of Cs-137 in YSECS: the grid-based Eulerian model THREETOX, Lagrangian radionuclide transport model and compartment model POSEIDON-R. Such approach emulates the application of various models with their own settings in the event of an unexpected accidental release, similar to the Fukushima accident. For THREETOX model setup, 3D current velocities with 30 vertical layers were extracted from the KIOST-MOM model, results of which are monthly averaged and cover North Pacific. The Lagrangian radionuclide transport model used regional currents and suspended sediments concentrations from circulation model adopted for the YSECS taking into account tides and multi-fractional sediments. These two models were applied for emergency and post-emergency phases for the period from half a year to one year after deposition. The POSEIDON-R model already had a system of boxes for the North-Western Pacific covering the YSECS, East/Japan Sea and Eastern coastal area of Japan. It was applied for a long-term assessment of several decades. Obtained concentrations of Cs-137 in water, bottom sediments and partly in marine organisms were compared and the differences were analysed. Application of three marine dispersion models provides the possible ranges of radionuclide concentrations on the one hand and increases the reliability of results on the other.

How to cite: Kim, K. O., Bezhenar, R., Kovalets, I., Brovchenko, I., Maderich, V., and Kwon, K.: Multi-model simulation of the radionuclide transfer in the Yellow Sea as a result of hypothetical atmospheric deposition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13386, https://doi.org/10.5194/egusphere-egu24-13386, 2024.

EGU24-13781 | Orals | GI2.3

Tritium Leakage Traces the Path of Cesium from Fukushima Daiichi Nuclear Power Plant into the Ocean 

Yuichi Onda, Hikaru Sato, and Daisuke Tsumune

Reducing the release of radionuclides into the environment is crucial for decommissioning nuclear facilities and post-accident remediation. After the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, a seawall was constructed to minimize the direct discharge of Cs-137-contaminated groundwater into the ocean. Despite this measure, unexplained seasonal variations in Cs-137 emissions continued. Notably, between 2013 and 2014, groundwater leaks from treated water storage tanks at the site led to detectable levels of tritium (H-3) in the groundwater moving downslope from the plant. Our study, conducted over 2015-2021, utilizes a watershed hydrologic tracer approach to identify the marine sources of Cs-137 and explore the underlying causes of its seasonal fluctuation.

We analyzed H-3 in FDNPP groundwater and drainage channel K, known for high Cs-137 concentrations. By correlating this data with Cs-137 levels and runoff in the channel, we deduced the proportion of surface to total flow, identifying the main sources of Cs-137 and its seasonal variability. The surface flow, indicated by H-3 presence and further subdivided by effective rainfall analysis, revealed that the flow through the plant buildings was heavily contaminated with Cs-137, constituting the primary runoff source. We found that Cs-137 concentrations in basal flow are influenced by temperature, while those in surface flow respond to rainfall.

These insights are crucial for effective cleanup strategies at FDNPP and demonstrate the broader applicability of using leakage H-3 as a tracer to identify sources of radioactive and chemical pollutants from terrestrial to marine environments in similar scenarios.

How to cite: Onda, Y., Sato, H., and Tsumune, D.: Tritium Leakage Traces the Path of Cesium from Fukushima Daiichi Nuclear Power Plant into the Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13781, https://doi.org/10.5194/egusphere-egu24-13781, 2024.

EGU24-13825 | Posters on site | GI2.3

Lagrangian radionuclide transport modeling with fast and slow adsorption-desorption processes: application to the Yellow Sea with a hypothetical atmospheric deposition  

Seongbong Seo, Igor Brovchenko, Vladimir Maderich, Ivan Kovalets, Kateryna Kovalets, and Kyung Tae Jung

To cope with the increasing threat of radioactivity release accidents in the Yellow Sea a Lagrangian radionuclide transport model in the region was recently developed coupled in off-line manner with current-wave-suspended sediment modeling system (Brovchenko et al, 2022).  The radionuclide model included as an essential feature the fast adsortion-desorption processes of dissolved and particulate radionuclides in the presence of multi-ftactional sediments. Upgrade is made in this work by including fast and slow adsorption-desorption processes of radionuclides and a novel approach for lagrangian simulation of the radionuclide exchange between near-bottom water-layer and bed sediments. Lagrangian particles in the model can possess several states: dissolved in the water column, adsorbed on suspended sediment of particular size, dissolved in the pore water, adsorbed on the bed sediments of particular size. Note that, If particles are adsorbed on the sediments then it can be in two different states, namely fast and slow reversible forms; if there are Nsed sediment size classes then we have Ntot =2+4Nsed  total states of the radionuclide. Throughout the numerical integration the model calculates the probabilities to transfer into each possible state (that depends on the current state and time step) during the next time step and then chooses the new particular state by comparing with the generated uniformly distributed random number. Hypothetical accident at the Haiyang NPP in China, which is located at the coast of Yellow Sea close to Korea is considered as a scenario of accident. The atmospheric transport and deposition of radionuclides on the sea surface was simulated by the FLEXPART model. The obtained deposition fluxes were used as a source term in the Lagrangian radionuclide transport model. 3D fields of currents, suspended sediment concentration and turbulent diffusion coefficient as well as bed sediment fractional composition are identical to the previous results of the Yellow Sea (Brovchenko et. al. 2022).  Computational domain of the FLEXPART model includes bigger outer area, which covers Yellow and East China Sea, with spatial resolution of 0.15 deg, and inner area, which covers only Yellow Sea with better spatial resolution of 0.05 deg. The source term of 137Cs released due to hypothetical accident at the Haiyang NPP was obtained from the 6-day simulations of the FLEXPART model. The total amount of radioactivity that deposited on the calculation area is approximately 55 PBq. The radioactivity budget analysis reveals that almost near 50% of the 137Cs was deposited to the bottom sediments and approximately half remained in the dissolved form. About 4% of the total amount remains on the suspended sediments in one-step modelling and about 9% with the use of two-step model. The total bed contamination changed only 1% because for this period bottom contamination fluxes dominated over the bed cleaning process. More differences are expected for simulation with duration of several years when dissolved 137Cs concentration in water will decrease and bed cleaning process become more significant.

How to cite: Seo, S., Brovchenko, I., Maderich, V., Kovalets, I., Kovalets, K., and Jung, K. T.: Lagrangian radionuclide transport modeling with fast and slow adsorption-desorption processes: application to the Yellow Sea with a hypothetical atmospheric deposition , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13825, https://doi.org/10.5194/egusphere-egu24-13825, 2024.

EGU24-13896 | Orals | GI2.3

Linkage of 137Cs dynamics in river and coastal seawater during high-flow events 

Yoshifumi Wakiyama, Shun Satoh, Hyoe Takata, Pierre-Alexis Chaboche, and Honoka Kurosawa

Previous studies indicated that high-flow events can result in substantial 137Cs exportation via river to the ocean and increase 137Cs concentrations in coastal seawater. Assessing response of marine 137Cs behavior to terrestrial 137Cs inflow will lead to a better understanding of 137Cs transfer processes in terrestrial and marine environments. This study presents results of sample collections under various flow conditions on a river system and its coastal seawater to discuss the transfer processes in detail. The study was conducted in the Ukedo river system and its coastal sea during 3rd-19 th September 2023. Water samples were collected for 13 times at two downstream points of the river system, on the mainstream (Ukedo river) and a tributary (Takase river), and 8 times at seashore locating at 500 m north from the river mouth. In the sampling period, the catchment mean rainfall was totaled 300 mm with intensive rainfalls on 4, 6 and 8 September. Collected water samples were filtrated to measure 137Cs concentration in suspended solids (Bq/kg) and dissolved 137Cs concentrations (Bq/L). 137Cs concentrations in suspended solids in Ukedo and Takase river ranged from 7.0 to 67 kBq/kg and from 2.4 to 15 kBq/kg, respectively. The concentrations at peak water discharge phases in Takase river tended to be high when ratio of rainfall amount on downstream parts to that on whole catchments were high, but vice versa in the Ukedo river. This discrepancy can be attributed to the difference in spatial distribution of 137Cs inventory between the two catchments. Dissolved 137Cs concentrations in Ukedo and Takase rivers ranged from 52 to 70 mBq/L (5 samples measured out of 13) and from 8.4 to 37 mBq/L, respectively. At the seashore, 137Cs concentrations in suspended solids and dissolved 137Cs concentration ranged from 2.0 to 95 kBq/kg and from 6.7 to 410 mBq/L, respectively. Both concentrations appeared maximum in the sample collected 5 hours after the peak river water discharge which occurred with intensive rain on 8th September. Higher dissolved 137Cs concentration in seawater than in corresponding river water for the high-flow event indicates considerable desorption of 137Cs from terrestrial suspended solids into coastal seawater. Both 137Cs concentrations in seawater decreased with time to reach the background levels in 10 days after the event despite of quite stable concentrations in rivers. These results provide important implications for quantifying 137Cs transfer processes in terrestrial-marine environments.

How to cite: Wakiyama, Y., Satoh, S., Takata, H., Chaboche, P.-A., and Kurosawa, H.: Linkage of 137Cs dynamics in river and coastal seawater during high-flow events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13896, https://doi.org/10.5194/egusphere-egu24-13896, 2024.

EGU24-14216 | ECS | Posters on site | GI2.3

Spatiotemporal Variation of DOM Concentration and Composition along the Subtropical Small River Continuum in Taiwan 

Li-Chin Lee, Jr-Chuan Huang, Gabriele Weigelhofer, Thomas Hein, Yu-Lin Yu, and Pei-Hao Chen

The fate and reactivity of dissolved organic matter (DOM) in river networks is critical to understanding carbon cycling in inland water systems, and is highly regulated by physio-geographic factors and water residence time (WRT). In this study, we investigate the spatiotemporal variation of DOM concentration and composition in two SMRs in Taiwan with different landscapes and anthropogenic impacts. The WRT for these two rivers, the Keelung and Lanyang River, are around 34 and 23 hours, respectively. Dissolved organic carbon (DOC) concentration measurements and optical analyses (absorbance and fluorescence) were used to examine DOM quantity and quality along the river continuum. The comparative results showed that, along the SMR continuum, the DOC concentrations and optical indexes exhibited slight changes, with significant increases observed only at downstream sites influenced by human activities. Meanwhile, the higher biological index (BIX) and lower humification index (HIX) indicated an increase in autochthonous sources and a decrease in the degree of humic characters. In addition, we observed a positive correlation between WRT and DOC concentration variability, yet not significant for DOM compositions. When comparing the two rivers, the one with steeper topography and less human influence shows lower levels of DOC concentration and degree of humification. Overall, the SMRs seem to have lower DOC concentrations (0.26 - 1.65 mg-C L-1), lower HIX (0.28 - 0.76), and slightly higher BIX (0.8 - 1.9) on a global scale, which might be attributed to Taiwan's steep landscape and shorter water residence time, limiting soil organic carbon (SOC) production and in-stream processes rates. Through our investigation, DOC concentration and DOM composition across river networks will be better understood and potentially improve the assessment of the global carbon cycle.

How to cite: Lee, L.-C., Huang, J.-C., Weigelhofer, G., Hein, T., Yu, Y.-L., and Chen, P.-H.: Spatiotemporal Variation of DOM Concentration and Composition along the Subtropical Small River Continuum in Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14216, https://doi.org/10.5194/egusphere-egu24-14216, 2024.

The March 11, 2011, Great East Japan Earthquake triggered accidents at the Fukushima Daiichi Nuclear Power Plant (1F NPP), releasing radioactive substances into the ocean. Sparse observational data on 137Cs in the ocean led to interpolation and simulation for a comprehensive understanding. The primary focus was on direct release, emphasizing the need for a suitable source.

The direct release rate (Bq/day) was calculated by multiplying the seawater exchange flow rate (m3/day) and observed 137Cs concentration (Bq/m3). Using a mesh size of 735 m x 929 m x 8 m on the model, the seawater exchange flow rate at the release point was simulated. The 137Cs concentration relied on average observed radioactivity at 5, 6, and the south discharge canals near the 1F NPP. Direct release was estimated at 2.2x1014 Bq/day from March 26 to April 6, 2011, aligning with rates derived from other methods.

The seawater exchange flow rate's dependency on the model's mesh size was acknowledged. For this estimation, a 735 m x 929 m mesh size encompassing key points was considered reasonable for the seawater exchange flow rate, given the complex transport process from the release source (Unit 2 intake) to observation points (5, 6, and the south discharge point) due to port structures.

A higher resolution model with a 147 m x 186 m mesh (1/5) was used for a detailed analysis of direct release rates. The size of the sea area for determining the volume of seawater exchange flow rate can now be changed. Despite challenges in setting due to damaged ports, using the seawater exchange flow rate in a similar area as the previous resolution was deemed appropriate. The results of the validation of the release rate and the observed results by the relationship equation confirmed the consistency with the amount of seawater exchange obtained by the results of the dye tracer release experiments in the 1970s.

The release of 137Cs from the 1F NPP site persists. Estimating direct release rates up to 2016, a long-term simulation with a higher resolution model was conducted for validation. Results showed the oceanic 137Cs concentration distribution influenced by coastal currents, eddies, and the Kuroshio Current, leading to spatio-temporal variability. Validation with observed annual mean concentrations revealed good agreement. The higher resolution improved coastal transport reproducibility, addressing 137Cs radioactivity underestimation at the Fukushima 2 NPP, 10 km south of the 1F NPP.

How to cite: Tsumune, D., Tsubono, T., and Misumi, K.: Verification of direct release rate of oceanic 137Cs from Fukushima Daiichi Nuclear Power Plant Accident by higher resolution ocean dispersion model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14451, https://doi.org/10.5194/egusphere-egu24-14451, 2024.

EGU24-14837 | Posters on site | GI2.3

Spatiotemporal variations of 137Cs and 90Sr in the global ocean based on the historical data 

Yayoi Inomata and Daisuke Tsumune

The anthropogenic radionuclides such as caesium-137 (137Cs), strontium-90 (90Sr), 3H, 14C, and plutonium (Pu) were released into the global ocean as results with large scale weapon tests in the late 1950s and early 1960s. Because these anthropogenic radionuclides have been still existed in the ocean, it is necessary to investigate the behavior of these anthropogenic radionuclides due to investigate the effects of human health. In this study, the spatiotemporal variations in the 137Cs and 90Sr activity concentrations in global ocean surface seawater from 1956 to 2021 using the HAMGlobal2021: Historical Artificial radioactivity database in Marine environment, Global integrated version 2021. The global ocean was divided into 37 boxes. The 0.5-yr average value of 90Sr in the northern North Atlantic Ocean and its marginal sea, decreased exponentially in 1970–2010, just before the F1NPS accident. Estimated apparent half residence time of 137Cs and 90Sr ranged from 4.1-34.1 years and 3.6-25.2 years, respectively. Considering that longer Tap occurs larger inflow and shorter Tap occurs larger outflows/smaller inflow of radionuclide from the upstream region, 137Cs and 90Sr were inflowed into the Eastern China Sea from the subtropical western North Pacific Ocean. Inflow of 90Sr into the Sea of Japan from the Eastern China Sea were relatively smaller than those of 137Cs. Although 90Sr were decreased exponentially, these trends tended to be larger than those of 137Cs, which was investigated by our previous study (Inomata and Aoyama, 2023). This might be caused by the different behavior of 90Sr and 137Cs such as particulate form for 90Sr in the seawater.

 

Keywords: 90Sr, 137Cs, Database, surface seawater, global ocean

Reference: Inomata and Aoyama, Evaluating the transport of surface seawater from 1956 to 2021 using 137Cs deposited in the global ocean as a chemical tracer. Earth Syst. Sci. Data, 15, 1969–2007, 2023.

How to cite: Inomata, Y. and Tsumune, D.: Spatiotemporal variations of 137Cs and 90Sr in the global ocean based on the historical data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14837, https://doi.org/10.5194/egusphere-egu24-14837, 2024.

EGU24-17332 | Orals | GI2.3

Anthropogenic and natural tritium radioisotope in terrestrial water cycle of Fukushima, Japan 

Maksym Gusyev, Alexandre Cauquoin, Yasunori Igarashi, Hyoe Takata, Shigekazu Hirao, and Naofumi Akata

Environmental tritium (3H) radioisotope with a half-life of 12.32 years is naturally generated in the upper atmosphere by cosmic rays and enters the water cycle in the troposphere as the water molecule (HTO) to become a useful tracer in Japan and other countries. In 2011, anthropogenic 3H entered the terrestrial water cycle due to the Fukushima Daiichi Nuclear Power Plant (FDNPP) atmospheric release and discharged in Advanced Liquid Processing System (ALPS) treated water from the FDNPP site to the Pacific Ocean in 2023 raising concerns internationally. In Japan, 3H measurements in monthly precipitation have been conducted by the Government and Universities while many surface water sites were sampled twice per year across Fukushima Prefecture accumulating a decade-long record of 3H measurements. However, there are no 3H measurements in precipitation during the FDNPP accident requiring atmospheric numerical modeling to quantify anthropogenic 3H in Fukushima. To utilize 3H as a tracer in Fukushima, we combine simulated anthropogenic 3H released by the FDNPP in 2011 with the long-term time-series of 3H in precipitation from 1950 to present in the Tokyo area, which was scaled to Fukushima area. Using annual 3H in precipitation is 2.86 TU-3.70 TU with an average of 3.37 TU from 2016 to 2021 lead to the scaling factor from Tokyo area to Fukushima city between 1.30 and 1.61. For Fukushima surface water sites, measured 3H concentrations are at low levels of natural 3H concentrations and lead to insignificant doses due to drinking water exposure. In addition, we sampled several headwater catchments near Fukushima city in October 2023 for measuring 3H and estimated tritium-tracer mean transit time and subsurface water storage volume after the ALPS-treated water discharge. As a result, we demonstrate that environmental 3H radioisotope is a useful tracer with developed 3H time-series in precipitation and surface water measurements to evaluate terrestrial water cycle in Fukushima. 

How to cite: Gusyev, M., Cauquoin, A., Igarashi, Y., Takata, H., Hirao, S., and Akata, N.: Anthropogenic and natural tritium radioisotope in terrestrial water cycle of Fukushima, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17332, https://doi.org/10.5194/egusphere-egu24-17332, 2024.

EGU24-17762 | Posters on site | GI2.3

Assessment of nutrient export in agroforestry catchments dominated by tea farms in subtropical small mountainous rivers, Taiwan 

Pei-Hao Chen, Hasan Raja Naqvi, Guan-Zhou Lin, Tsung-Yu Lee, Li-Chin Lee, and Jr-Chuan Huang

Human-induced land-use change has profound effects on both societies and ecosystem services. For example, transitioning from forests to conventional farms using fertilizers can escalate soil nitrogen, degrade groundwater, and impair downstream ecosystems. This study explores the intricate dynamics of human-induced land-use change, focusing on the shift from forests to tea farm-dominated catchments in Taiwan, where conventional farming practices with fertilizers impact soil quality, groundwater, and downstream ecosystems. Utilizing the Soil and Water Assessment Tool (SWAT) for nutrient export analysis, our research reveals that when agricultural land use exceeds 2%, exports of nitrate, phosphate, and potassium spike significantly, ranging from 25% to 150%. Notably, agricultural land use induces a higher impact on nitrate, with concentrations surpassing those by 120% and 233% during the dry season and wet season, respectively. Tea farms, constituting a substantial portion, exhibit a nearly tenfold increase in NO3-N yield compared to forests. Implementing a modified fertilization strategy, involving application during small rainfall events, enhances nitrogen uptake and tea tree harvest yield while reducing nitrogen input by 10%. This research offers actionable recommendations for sustainable agroforestry practices by integrating river and rainwater data with SWAT modeling. By doing so, it advances our understanding of hydrological and biogeochemical processes in subtropical tea farm-dominated catchments, providing valuable insights into hydrology and biogeochemistry.

How to cite: Chen, P.-H., Naqvi, H. R., Lin, G.-Z., Lee, T.-Y., Lee, L.-C., and Huang, J.-C.: Assessment of nutrient export in agroforestry catchments dominated by tea farms in subtropical small mountainous rivers, Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17762, https://doi.org/10.5194/egusphere-egu24-17762, 2024.

EGU24-20396 | Orals | GI2.3

Evidence of radioactive contamination of the Abai Region, Kazakhstan, from the Chinese nuclear testing program at Lop Nor 

Richard Harbron, Aleksandra Lipikhina, Kazbek Apsalikov, and Evgenia Ostroumova

Between 1949 and 1990, tests of nuclear weapons and other explosive devices were performed by the Soviet Union at the Semipalatinsk Nuclear Test Site (SNTS) in Kazakhstan, resulting in radioactive contamination of surrounding settlements. This contamination and the associated impact on the health of the local population are a subject of ongoing radioecological, radiobiological, dosimetric, and epidemiological research. Less in known about potential additional radioactive contamination of settlements SE of SNTS, close to the border with China. This region may have been contaminated by fallout from weapons tests performed by China at Lop Nor between 1964 and 1981, during which time all tests at SNTS were underground. Here, we review available evidence of this contamination, including the results of sampling campaigns performed both at the time of the Chinese tests and in recent years, and electron paramagnetic resonance (EPR) of tooth enamel.

Soil, vegetation, and milk sampling performed in the weeks following the Lop Nor tests revealed the presence of short-lived fission products, including I-131, I-133, Sr-89, Zr-95 and Ba-140 well in excess of background levels. Contamination was greatest following the thermonuclear tests on 17/06/1967 and 27/06/1973. Contemporary soil sampling in Kazakhstan and NW China suggests radioactivity levels have returned to background levels, though with ratios of Pu-240 / Pu-239, and Pu-240+239 / Cs-137 that differ from global fallout levels. Efforts to reconstruct exposure levels are ongoing, including collection of fortuitous dosimeters (e.g. bricks from settlement buildings) and teeth of exposed residents.

How to cite: Harbron, R., Lipikhina, A., Apsalikov, K., and Ostroumova, E.: Evidence of radioactive contamination of the Abai Region, Kazakhstan, from the Chinese nuclear testing program at Lop Nor, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20396, https://doi.org/10.5194/egusphere-egu24-20396, 2024.

The Mesozoic in Chengdao-Zhuanghai area is affected by complex tectonic evolution, diverse sedimentary types and lithology, and the reservoir heterogeneity is extremely strong, and the prediction of reservoir quality is difficult, and the accurate identification and division of lithofacies types plays a crucial role in the classification and evaluation of reservoirs. In the well section with relatively few corings, four logging curves sensitive to diagenesis, GR, AC, DEN, and RD were selected as the basis for diagenetic facies division, and the diagenetic facies division was carried out by the method of machine Xi. The traditional machine Xi is divided into two Xi: supervised Xi and unsupervised, in which supervised Xi requires a large number of Xi samples to ensure its accuracy, and unsupervised Xi does not need to learn Xi samples, but the classification results may not be the expected classification type. Combined with the characteristics of strong heterogeneity, relatively few coring sections and limited results of unsupervised Xi in this area, the method of unsupervised Xi with single factor constraint was considered to identify and divide the logging facies of the three formations in the Chengdao-Zhuhai area. Combined with the geological data such as core, cast thin section identification, logging data, etc., the calibration of logging facies and diagenetic facies is realized, so as to complete the identification and division of regional diagenetic facies. Finally, the accuracy of the Xi method is verified by comparing the thin section identification results, which provides a basis for the identification of reservoir diagenetic facies in the lack of coring well sections.

Keywords: clastic rocks; Chengdao-Zhuanghai area; The Mesozoic;Diagenetic facies logging identification; Univariate constrained unsupervised learning

How to cite: meng, Y. and zhang, L.: Identification and Application of Detrital Diagenetic Facies Logging Based on Unsupervised Xi Technology: A Case Study of the Mesozoic in Chengdao-Zhuanghai Area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-77, https://doi.org/10.5194/egusphere-egu24-77, 2024.

EGU24-340 | ECS | Orals | GI2.4 | Highlight

Super-resolution for satellite imagery: uncovering details using a new Cross Band Transformer architecture 

Jasper S. Wijnands, Nikolaos Ntantis, Jan Fokke Meirink, and Domenica Dibenedetto

Recent advances in artificial intelligence (AI) techniques have enabled the processing and analysis of vast datasets, such as archives of satellite observations. In the geosciences, remote sensing has transformed the way in which the atmosphere and surface are observed. Traditionally, substantial funding is directed towards the development of new satellites to improve observation accuracy. Nowadays, novel methods based on AI could become a complementary approach to further enhance the resolution of observations. Therefore, we developed a new, state-of-the-art super-resolution methodology.

Satellites commonly measure electromagnetic radiation, reflected or emitted by the earth's surface and atmosphere, in different parts of the spectrum. Many instruments capture both panchromatic (PAN) and low-resolution multi-spectral (LRMS) images. While PAN typically covers a broad spectral range, LRMS focuses on details in narrow bands within that range. Pansharpening is the task of fusing the spatial details of PAN with the spectral richness of LRMS, to obtain high-resolution multi-spectral (HRMS) images. This has proven to be valuable in many areas of the geosciences, leading to new capabilities such as detecting small-sized marine plastic litter and identifying buried archaeological remains. Although HRMS images are not directly captured by the satellite, they can provide enhanced visual clarity, uncover intricate patterns and allow for more accurate and detailed analyses.

Technically, pansharpening is closely related to the single image super-resolution task, where attention-based models have achieved excellent results. In our study a new Cross Band Transformer (CBT) for pansharpening was developed, incorporating and adapting successful features of vision transformer architectures. Information sharing between the panchromatic and multi-spectral input streams was enabled through two novel components: the Shifted Cross-Band Attention Block and the Overlapping Cross-Band Attention Block, implementing mechanisms for shifted and overlapping cross-attention. Each block led to a more accurate fusion of panchromatic and multi-spectral data. For evaluation, CBT was also compared to seven competitive benchmark methods, including MDCUN, PanFormer and ArbRPN. Our model produced state-of-the-art results on the widely used GaoFen-2 and WorldView-3 pansharpening datasets. Based on peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) scores of the generated images, CBT outperformed all benchmark methods. Our AI method can be integrated in existing remote sensing pipelines, as CBT converts actual observations into a high-resolution equivalent for use in downstream tasks. A PyTorch implementation of CBT is available at https://github.com/VisionVoyagerX/CBT.

Furthermore, we developed the Sev2Mod dataset, available at https://zenodo.org/record/8360458. Unlike conventional benchmark datasets, Sev2Mod acquired input and target pairs from two different satellite instruments: (i) SEVIRI onboard the Meteosat Second Generation (MSG) satellite in geostationary orbit and (ii) MODIS onboard the Terra satellite in polar, sun-synchronous orbit. SEVIRI measures a fixed field of view quasi-continuously, while MODIS passes only twice a day but observes at a much higher spatial resolution. Our study investigated image generation at the spatial resolution of MODIS, while preserving SEVIRI's high temporal resolution. Since Sev2Mod is better aligned with actual situations one may encounter in applications of pansharpening methods (e.g., noise, bias, approximate temporal matching), it provides a solid foundation to design robust pansharpening models for real-world applications.

How to cite: Wijnands, J. S., Ntantis, N., Meirink, J. F., and Dibenedetto, D.: Super-resolution for satellite imagery: uncovering details using a new Cross Band Transformer architecture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-340, https://doi.org/10.5194/egusphere-egu24-340, 2024.

EGU24-1619 | ECS | Orals | GI2.4

Near real-time drillhole data analysis using non-destructive mineral exploration tools 

Hamid Zekri, David Cohen, Neil Rutherford, and Matilda Thomas

Field-based data acquired from drillholes by pXRF, spectrometer, and wireline loggings can provide prompt, relatively inexpensive and precise information about the geochemistry, mineralogy and petrophysical properties of geological units. When on-site data capture is followed by proper visualisation and statistical analyses, these non-destructive methods can assist in rapid interpretations and decision makings.

Identification of distinctive units and critical zones in exploration under cover can be challenging for even experienced geologists when dealing with drilling chips. This study presents a data-driven framework for rapid boundary detection from drillhole cuttings through a combination of geochemical, mineralogical, and geophysical data. The workflow was tested on two drillholes during a drilling campaign conducted by Mineral Exploration Cooperative Research Centre (MinEx CRC) for Geoscience Australia's Exploring for the Future program in the Delamerian orogeny located in far western New South Wales, Australia.

A multivariate change point detection technique was applied to the 30 effective attributes retained from various geochemical variables, spectral scalars, and petrophysical parameters obtained through field-based instruments. These include major (e.g., Al, K, Ca, Fe etc.), conserved (Ti and Zr), and trace elements (e.g., Cu, Pb, and Zn), as well as spectral features associated with ferric oxides, kaolinite, micas, smectite, chlorites, and epidote. Natural gamma, electrical conductivity and resistivity, and magnetic susceptibility were also used as petrophysical parameters. Various interfaces between the weathered profile and basement rocks were detected at two scales providing useful insights into the stratigraphy and detailed geochemical logs previously carried out by the field geologists. Using different data types resulted in more reliable boundary detection compared to the limitations of using each data type on its own. This approach was also able to delineate a critical zone in the saprock zone above the fresh basement where elevated concentrations of lead and zinc are accumulated, providing guidance for more detailed sampling and analysis.

This framework can be utilised for data-driven stratigraphy/lithology logging, regolith characterisation, identification of the key horizons for further sampling and studies and can facilitate decision-making during exploration drilling campaigns. 

How to cite: Zekri, H., Cohen, D., Rutherford, N., and Thomas, M.: Near real-time drillhole data analysis using non-destructive mineral exploration tools, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1619, https://doi.org/10.5194/egusphere-egu24-1619, 2024.

EGU24-2695 | Posters on site | GI2.4

Data inheritance concept in mineralogical warehouse 

Liubomyr Gavryliv, Vitalii Ponomar, and Marián Putiš

Recently, there has been a substantial surge in the availability of web services offering access to geological, geochemical, crystallographic, and mineralogical data. Embracing this data-rich environment, mineralogy.rocks emerges as a pioneering outreach project, poised to harness the vast potential embedded in this information reservoir. Focused on extracting valuable insights, the project seeks to leverage the wealth of open-access data and fosters knowledge dissemination by openly sharing the underlying code of its processes under MIT, available on https://github.com/orgs/mineralogy-rocks. 

Mineralogy.rocks' core developers recently tackled the challenge of establishing relationships between minerals and their associated entities such as synonyms, varieties, and parental groups. Often, these related entries lack distinct properties; synonyms may only have a name and historical context, chemical varieties might differ only in impurity presence, and structural variations may diverge solely in crystal system. Database-wise, all other properties remain identical to the parent mineral. 

In response, we introduce the concept of Data Inheritance, drawing parallels with Object-Oriented Programming's class inheritance mechanism. This concept permits multiple base classes, enabling a derived class to override methods of its base class or classes, thus allowing objects to encompass diverse and arbitrary data. Applied to a data warehouse dimension, this concept facilitates the retrieval of the actual properties of a related entry defined in the database and the inherited properties not defined for this specific entry but established for the parental mineral. 

To implement this, we calculate the inheritance chain, representing the chain of relations from the bottom-most child entry to the top-most parental mineral, such as in the case of agate—chalcedony—quartz. The chain, coupled with specific code rules and patterns, enables the retrieval of properties for each entry in the chain, effectively determining which properties are pertinent to the child species. This systematic approach adds precision and clarity to the extraction and utilization of mineralogical data in the context of inherited properties.

mineralogy.rocks is dedicated to open science, prioritizing innovation, quality, and public impact in mineralogical research. Our commitment is evident through actions that swiftly share research outcomes and metadata, fostering accessibility and reuse. Embracing open science principles, we contribute to advancing the field with transparent and collaborative practices.

This project, No. 3007/01/01, has received funding from the European Union’s Horizon 2020 research and innovation Programme based on a grant agreement under the Marie Skłodowska-Curie scheme No. 945478 and was supported by the Slovak Research and Development Agency (contracts APVV-19-0065 and APVV-22-0092).

How to cite: Gavryliv, L., Ponomar, V., and Putiš, M.: Data inheritance concept in mineralogical warehouse, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2695, https://doi.org/10.5194/egusphere-egu24-2695, 2024.

EGU24-5002 | Orals | GI2.4 | Highlight

Geochemistry π: Automated Machine Learning Python Framework for Tabular Data 

Jianming Zhao, Johnny ZhangZhou, Can He, and Yang Lyu and the ZJU Earth Data Group

Machine learning has significantly advanced geochemistry research, but its implementation can be arduous and time-consuming. In response to this challenge, we introduce Geochemistry π, an open-source automated machine learning Python framework. With Geochemistry π, geochemists can effortlessly process tabulated data and execute machine learning algorithms by selecting preferred options. This streamlined process operates in a user-friendly question-and-answer format, eliminating the need for coding expertise. Following automatic or manual parameter adjustment, Geochemistry π furnishes users with comprehensive performance metrics and predictive outcomes for their machine learning models. Leveraging the scikit-learn library, Geochemistry π has developed a tailored automated workflow encompassing classification, regression, dimensionality reduction, and clustering algorithms. The framework’s extensibility and portability are enhanced through a modular pipeline architecture, segregating data handling from algorithm application. Geochemistry π’s Auto Machine Learning module integrates Cost-Frugal Optimization and Blended Search Strategy hyperparameter search methods from the A Fast and Lightweight Auto Machine Learning Library. Additionally, model parameter optimization is expedited using the Ray distributed computing framework. Efficient machine learning lifecycle management is facilitated through integration with the MLflow library, allowing users to compare multiple trained models at various scales and manage generated data and visualizations. To enhance accessibility, Geochemistry π separates front-end and back-end frameworks, culminating in a user-friendly web portal. This portal not only showcases the machine learning model but also presents the data science workflow, making it accessible to both researchers and developers. In summary, Geochemistry π offers a robust Python framework that empowers users and developers to significantly enhance their data mining efficiency, with options for both online and offline operation.

How to cite: Zhao, J., ZhangZhou, J., He, C., and Lyu, Y. and the ZJU Earth Data Group: Geochemistry π: Automated Machine Learning Python Framework for Tabular Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5002, https://doi.org/10.5194/egusphere-egu24-5002, 2024.

EGU24-5256 | ECS | Orals | GI2.4 | Highlight

Hydroacoustic geophony automatic detection: an open benchmark dataset with an open model 

Pierre-Yves Raumer, Sara Bazin, Jean-Yves Royer, Cazau Dorian, and Vaibhav Vijay Ingale

Underwater seismic events such as earthquakes are known to produce not only seismic waves but also hydro-acoustic waves. Indeed, seismic waves arriving at the ocean bottom convert into acoustic waves in the water column. Other events, such as hot lava-seawater interactions or icequakes, also generate water-born acoustic signals. Monitoring these different signals with moored hydrophones proved to be useful and very efficient thanks to the little attenuation of acoustic waves propagating in the Sound Fixing and Ranging (SOFAR) channel. This led to the deployment of wide-range moored hydrophone networks to monitor active seafloor-spreading ridges in the world ocean. However, analyzing year-round data recordings from several stations is a cumbersome, user-dependent and most importantly time-consuming task. Despite some efforts to develop automatic detection algorithms, the community still lacks efficient and available off-the-shelf tools, as well as open datasets and benchmarks against which they could be compared objectively. To address this problem, we are glad to make publicly available three partially-annotated hydroacoustics datasets consisting of recordings from Atlantic and Indian oceans, with a total of ~60,000 hours. We propose a benchmark of models on a first task of binary classification, and an original convolutional neural network (CNN) model called TiSSNet showing promising results. To maximize the reliability of the evaluations, two datasets have been carefully and exhaustively annotated to serve as evaluation datasets. The getting started codes have also been made available on GitHub. We wish the datasets and benchmarks will be used as references upon which the state-of-the-art could be developed in a collaborative way. In the future, the best model, used as an automatic or semi-automatic detection framework, will be applied to larger datasets, and combined with multi-stations association and trilateration techniques to output nearly complete catalogs of geophonic events (source type and location, with signal characteristics).

How to cite: Raumer, P.-Y., Bazin, S., Royer, J.-Y., Dorian, C., and Vijay Ingale, V.: Hydroacoustic geophony automatic detection: an open benchmark dataset with an open model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5256, https://doi.org/10.5194/egusphere-egu24-5256, 2024.

EGU24-5905 | ECS | Orals | GI2.4

Deep Learning for Detecting Thrust Faults in Subduction Zones 

Wenhao Zheng, Rebecca Bell, Cédric M. John, and Lluis Guasch

Subduction plate boundary faults and splay faults in accretionary wedges are capable of generating some of the largest earthquakes and tsunamis on Earth. Owing to the complexity of geological structures and the inherent ambiguity in geophysical data, comprehensively characterizing potential thrust fault systems presents a considerable challenge. Current automated fault detection methods, primarily targeting normal faults, show limited efficacy in complex fault systems of subduction zones. Treating the task of fault detection as a binary image segmentation issue, we propose a supervised end-to-end fully convolutional neural network (U-Net) to automatically and accurately delineate thrust faults from seismic data. To circumvent the labour-intensive and potentially subjective manual labelling process required for model training, we have designed a workflow to efficiently auto-generate more than 10000 training pairs comprising both 2D synthetic seismic images and their corresponding labelled images of the thrust faults simulated in the seismic images. Each synthetic seismic image includes randomly undulating stratigraphic strata and faults with dip angles between 5 and 40 degrees, aiming to simulate realistic and varied geological structures and thrust fault features in subduction zone, which equipped the U-Net model to achieve a 91% accuracy rate in fault detection within the test dataset. The example from the Hikurangi subduction zone, New Zealand demonstrates that the U-Net trained by only synthetic data is superior to conventional automatic methods, such as unsupervised methods or supervised methods trained by normal faults, in delineating more than 70% thrust faults from seismic images. To enhance the U-Net model's adaptation to specific regional fault characteristics and reduce the interference from noise, we incorporated a select set of real 2D seismic images and manually interpreted fault labels into the transfer learning process, which significantly improved its prediction accuracy and make the results clearer. From the comprehensive 2D characterizations based on the U-Net model, we can further extract 3D thrust fault systems and quantitatively measure their geometric parameters.

How to cite: Zheng, W., Bell, R., John, C. M., and Guasch, L.: Deep Learning for Detecting Thrust Faults in Subduction Zones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5905, https://doi.org/10.5194/egusphere-egu24-5905, 2024.

In Korea, when a disaster occurs, numerous news related to the disaster are reported very quickly through various media. These news contain useful disaster-related information that disaster researchers need, such as the causes of disasters, problems in the process of disaster occurrence, and improvement measures suggested by related experts. However, finding articles containing the disaster-related information we need from the numerous news reports in the media is not easy and takes a long time. Accordingly, in this study, the R-Scanner model using text mining technology was developed to extract disaster and safety information desired by users from large-scale news data, which is 'unstructured big data'. Here, R stands for Risk. The developed model was constructed based on natural language processing systems for Korean and English and was developed to perform Sentence Segmentation, Tokenization, and Morphological Analysis using text as analysis data. In the Morphological Analysis process, the model was developed to perform Entity Recognition, Semantic Role Labeling, and Semantic Chunking. Additionally, the model was developed to extract articles containing the desired information from news big data reported through the media when the user inputs keywords related to the desired information, and the extracted articles can be downloaded in Excel format. To verify the performance of the developed model, we applied it to landslides that resulted in 14 deaths due to torrential rains in Korea in 2023. Problems and improvement measures in the landslide occurrence process were set with the desired information, and keywords were set to extract each information. About 200 keywords related to problems were set, such as 'procrastination', 'defenseless', 'ignored', 'sloppy', and 'careless', and about dozens of keywords such as ‘suggested’, ‘should be prepared’, and ‘necessary’ were set as keywords related to improvement measures. As a result of applying the model, a total of 364 articles related to problems and improvement measures were extracted from 30 media news 15,911,665 articles, and as a result of grouping the extracted problems and improvement measures into similar contents, 24 problems and 22 improvement measures were finally derived. As a result of the review of related experts on the problems and improvement measures derived, it was confirmed that the contents were quite meaningful. The problems and improvement measures derived in this way were used as basic data for the establishment of government measures to prevent landslides. In the future, the developed model is expected to be used not only to establish the government's countermeasures for disaster, but also to monitor real-time disaster and safety issues, and furthermore to detect disaster risks at an early stage.

How to cite: Choi, S., Kim, D. W., Shin, E. H., and Kim, Y. J.: Development and Application of a Model to Extract Disaster and Safety-related Information from News Big Data reported in the Media using Text Mining, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6817, https://doi.org/10.5194/egusphere-egu24-6817, 2024.

The ground-source heat pump (GSHP) is an efficient thermal exchange system that utilizes natural environmental heat for heating and cooling. Heat exchange efficiency depends not only on factors such as pipe material and diameter but also on groundwater's flow field and soil's thermal parameters. This study aims to estimate hydraulic and geothermal parameters by utilizing convolutional encoder-decoder architecture neural networks and hydraulic tomography, a data collection strategy. The proposed method is named THT-NN. To examine the capability of the THT-NN on parameter estimation, we developed numerical experiments to test THT-NN. Further, to produce the training and validation data pairs, we create a two-dimensional heterogeneous groundwater and heat transport model by TOUGH2 with constant injection patterns and 10000+ realizations of parameter fields. The groundwater heads and temperature collected from the monitoring well groups are used to develop two channels of the input layers, and four parameters' fields (hydraulic conductivity, porosity, heat conductivity, and specific heat) are used to develop four channels of the output layers. Subsequently, the estimated parameters results are examined by R2 and root mean squared error. The performance of the proposed THT-NN is discussed in this study.

How to cite: Liang, C.-W. and Tsai, J.-P.: Estimation of Hydraulic and Thermal Parameters Using Convolutional Neural Network and Hydraulic Tomography, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7272, https://doi.org/10.5194/egusphere-egu24-7272, 2024.

EGU24-7440 | ECS | Orals | GI2.4

Recover the Water Content of Mid-Ocean Ridge Basalts by a Machine Learning Method 

Jingjun Zhou, Jia Liu, Qunke Xia, Cheng Su, Takeshi Kuritani, and Eero Hanski

Water's impact on the physicochemical attributes of mantle rocks makes it a pivotal factor in mantle evolution. Mid-ocean ridge basalts (MORBs) are essential for analyzing the upper mantle's composition, yet many global MORB samples lack direct water content assessment. The common method, using a correlation between H2O and trace elements like Ce to estimate MORB water contents, often presume a constant H2O/Ce ratio. Sometimes this assumption is unreliable due to the heterogeneity in H2O/Ce ratios, even within short ridge segments. For addressing this gap, we utilize compositional data from 1,467 global MORB glasses with measured water contents to develop a Random Forest Regression model. This machine learning-based model can predict water concentrations of MORB glasses based on major and trace element data, without the need for a fixed H2O/trace element ratio. Our model accurately recovers water contents of MORB glasses, showing comparable precision to traditional analytical methods. Applying this model to 1,931 MORB glass samples has significantly expanded the global MORB water content database, revealing the widespread presence of high-water MORBs. Importantly, this innovative approach enables the exploration of water content in MORBs from regions previously without such data, like the Chile Ridge and the Pacific-Antarctic Ridge. Moreover, it allows us to deduce variations of water contents of MORB sources by applying the model to transform fault samples, thereby offering novel insights into the dynamics of the mantle.

How to cite: Zhou, J., Liu, J., Xia, Q., Su, C., Kuritani, T., and Hanski, E.: Recover the Water Content of Mid-Ocean Ridge Basalts by a Machine Learning Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7440, https://doi.org/10.5194/egusphere-egu24-7440, 2024.

EGU24-8771 | ECS | Posters virtual | GI2.4

An Automated Conformalized Causal Learning System for Enhanced Mineral Prospectivity Mapping 

Evelyn Jessica Jaya, Xinbing Wang, Chenghu Zhou, and Nanyang Ye

Mineral Prospectivity Mapping (MPM) is a crucial process in mineral exploration, traditionally hampered by subjective interpretations and labor-intensive methods leading to unreliable outcomes. Predominantly focused on Independent and Identically Distributed (IID) scenarios, traditional research in MPM often struggles to generalize in Out of Distribution (OOD) scenarios, which are vital for accurate mineral exploration. Addressing these challenges, we introduce an innovative automated conformalized causal learning system for MPM. This system integrates a comprehensive data preprocessing pipeline that includes interpolation, feature filtering, data augmentation, and splitting, effectively managing diverse and imbalanced geological datasets. A central component of the system is Bayesian Optimization, autonomously selecting optimal machine learning models and hyperparameters to significantly enhance performance over non-automated methods. The system's most significant innovation is the incorporation of conformalized causal learning, exceptionally effective in handling OOD data scenarios. This methodology introduces an 'uncertainty region' in predictive models through conformal prediction, substantially reducing misclassification risks, while causal learning elucidates complex cause-and-effect relationships among geological features, essential for precise mineral deposit predictions. We evaluated the performance of our approach on six datasets, where the Area Under the Receiver Operating Characteristic (AUC ROC) of our automated optimized system surpassed the baseline method by an overall 17.84%, and the false positive rate (FPR) was reduced by an overall 84.31%. This development marks a significant advancement in MPM, enhancing accuracy and efficiency in mineral resource exploration and setting a new benchmark in the field. Released as an open-source platform, it offers the geological community a highly efficient, adaptable, and user-friendly tool, poised to revolutionize mineral prospectivity mapping in varied real-world scenarios.

How to cite: Jaya, E. J., Wang, X., Zhou, C., and Ye, N.: An Automated Conformalized Causal Learning System for Enhanced Mineral Prospectivity Mapping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8771, https://doi.org/10.5194/egusphere-egu24-8771, 2024.

EGU24-8843 | Posters on site | GI2.4

Use of deep learning and a partial convolutional neural network to gap-fill a long term time series of NO2 columns from satellite impacted by cloud 

wanli ma, Hugh Coe, David Topping, Zhonghua Zheng, Congbo Song, and Hao Zhang

Satellite monitoring plays a significant role in monitoring nitrogen dioxide (NO2) concentrations in the atmospheric column, but it is often affected by clouds and ice and snow surface. This leads to much missing data. Deep learning with Partial Convolutional Neural Network (PCNN) is adept at handling incomplete or missing data in image processing by focusing only on the known pixels during convolution, thus making approach ideal for tasks such as image restoration, denoising, and enhancing resolution.

 

It is therefore important to reduce such data gaps.. Under cloudy skies, ground-level NO2 often tends to be higher. Clouds are typically associated with low pressure and increased wind speeds in mid-latitudes, leading to enhanced dispersion of pollutant. However, low cloud often occurs during periods of high pressure when boundary layer heights are lower and air pollutants are trapped closer to the ground. Additionally, clouds intensify the Surface Sensible Heat Flux, contributing to the urban heat island effect and potentially increasing NO2 concentrations. On the other hand, clouds decrease Surface Net Solar Radiation, which might mitigate NO2 photolysis.

 

It is therefore likely that NO2 concentrations close to the surface during cloudy conditions will not necessarily be well represented by satellite derived NO2 columns in clear sky conditions.. It becomes necessary to recalibrate satellite-derived data to reflect actual meteorological conditions. In this work we separate out ground-level data from an urban network across Paris, France, into two categories: those with contemporaneous TROPOMI and those without. Each category is then analyzed with the weather conditions at that time. This analysis helps estimate the variance in NO2 concentrations due to cloud presence. Subsequently, the determined percentage difference, indicative of the cloud cover's impact, is applied to the NO2 estimates provided by the PCNN model.

 

This adjustment not only strengthens the data's coverage but also its reliability, reducing the biases in the original satellite data resulting from clear sky viewing only and are therefore a closer representation of the urban atmospheric pollution. This approach, combining technical precision with contextual sensitivity, improves the use of satellite data as a tool for understanding and interpreting urban pollution.

How to cite: ma, W., Coe, H., Topping, D., Zheng, Z., Song, C., and Zhang, H.: Use of deep learning and a partial convolutional neural network to gap-fill a long term time series of NO2 columns from satellite impacted by cloud, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8843, https://doi.org/10.5194/egusphere-egu24-8843, 2024.

EGU24-9192 | Orals | GI2.4

XAI for small-data problems in remote sensing: monitoring Atlantic forests with UAVs 

Pranav Chandramouli, Caroline M. Gevaert, Francesco Nattino, Ou Ku, Alexandra Aguiar Pedro, Patricia do Prado Oliveira, Eduardo Hortal Pereira Barreto, and Felipe de Ovileira

Despite the increased availability of UAV / drone imagery in Low- to upper  Middle-Income countries and the demonstrated potential of deep learning to support the interpretation of these images for sustainable development purposes, practical operations in these countries are constrained by the need for sufficient labeled data-sets which are often difficult to obtain (especially for tropical forest). This makes it difficult to train suitable networks and assess whether the model is performing well. One such example is the use of drones to monitor the Atlantic Forest in Sao Paulo, Brazil. Here, members of the Sao Paulo Municipal Green and Environment Secretariat (Secretaria do Verde e do Meio Ambiente - SVMA) are starting to use drones to  identify some native and invasive species in their forests. Deep learning will quickly speed up this process, but there is little training data available. This refers to the so called ‘small-data problem’ commonly found in DL for remote sensing applications [1]. A workflow was designed to support this application through a novel zero-shot learning technique and explainable AI methods. A pre-trained tree-crown detection model ‘DeepForest’ [2] is used to identify individual tree crowns in the UAV imagery. The detected tree-crowns are further classified using a Siamese network architecture using zero-shot learning – the model is trained on relevant data-sets but not exposed to species found in the test data-set. A Siamese network architecture is motivated by the need for explainability in DL models – the results will be used for making administrative decision for forest management. A more intricate DL model (such as image segmentation) could be more accurate but at the cost of transparency/explainability. In particular, we apply a variation of the ‘What I Know’ (WIK) explainability method [3] which provides examples from the training set along with the test sample increasing transparency and understanding of the model results.

[1] Safonova, Anastasiia, et al. "Ten deep learning techniques to address small data problems with remote sensing." International Journal of Applied Earth Observation and Geoinformation 125 (2023): 103569.

[2] Weinstein, Ben G., et al. "DeepForest: A Python package for RGB deep learning tree crown delineation." Methods in Ecology and Evolution 11.12 (2020): 1743-1751.

[3] Ishikawa, Shin-nosuke, et al. "Example-based explainable AI and its application for remote sensing image classification." International Journal of Applied Earth Observation and Geoinformation 118 (2023): 103215.

 

 

How to cite: Chandramouli, P., Gevaert, C. M., Nattino, F., Ku, O., Aguiar Pedro, A., do Prado Oliveira, P., Hortal Pereira Barreto, E., and de Ovileira, F.: XAI for small-data problems in remote sensing: monitoring Atlantic forests with UAVs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9192, https://doi.org/10.5194/egusphere-egu24-9192, 2024.

EGU24-10105 | ECS | Orals | GI2.4

Estimation of Lateral River Aquifer Exchanges with Physics Informed Neural Networks 

Mayank Bajpai, Lakhadive Mehulkumar Rajkumar, Shreyansh Mishra, and Shishir Gaur

This study introduces a novel approach for estimating lateral river-aquifer exchanges by employing Physics Informed Neural Networks (PINNs). The methodology compares the predictive capabilities of neural networks with the physics-based modeling provided by MODFLOW's Horizontal Flow Barrier (HBF) package, implemented through FloPy. As a foundation, the HBF package in MODFLOW establishes a baseline model, serving as a benchmark for performance comparison.

The integrated model leverages observed data and the fundamental principles of hydrogeology, enabling a robust estimation of lateral exchanges. The synergy of PINNs and MODFLOW HBF enhances the model's adaptability to diverse hydrogeological conditions, providing accurate predictions of intricate river-aquifer interactions. The comparative analysis with the MODFLOW HBF package underscores the efficacy of the proposed approach, offering insights for improved water resource management and environmental decision-making.

How to cite: Bajpai, M., Mehulkumar Rajkumar, L., Mishra, S., and Gaur, S.: Estimation of Lateral River Aquifer Exchanges with Physics Informed Neural Networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10105, https://doi.org/10.5194/egusphere-egu24-10105, 2024.

EGU24-10627 | ECS | Orals | GI2.4 | Highlight

Enhancing Geoscience Analysis: AI-Driven Imputation of Missing Data in Well Logging Using Generative Models 

Abdulrahman Al-Fakih, Ardiansyah Koeshidayatullah, and Sanlinn Kaka

The integrity of well logging data is paramount in geophysical explorations for accurate subsurface analysis, notably in the North Sea Dutch region known for its extensive hydrocarbon exploration. Addressing the common challenge of missing data in well logs, our study introduces an AI-driven methodology employing generative models. These models utilize machine learning to analyze existing data patterns and generate realistic imputations for missing values. The approach has shown to not only enhance the quality of geological interpretations but also to streamline the workflow in hydrocarbon exploration. This integration of AI signifies a substantial move towards more precise and efficient geoscience data analysis. A qualitative comparison using Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) was conducted to evaluate the results. The PCA comparison demonstrates the synthetic data’s alignment with real data in principal component space, effectively capturing the variance. The t-SNE analysis further validates the model's fidelity, with the synthetic data exhibiting clustering behaviors analogous to real data. Together, these results showcase the transformative potential of machine learning in geosciences, providing a robust framework for enhancing data reliability in geophysical studies.

How to cite: Al-Fakih, A., Koeshidayatullah, A., and Kaka, S.: Enhancing Geoscience Analysis: AI-Driven Imputation of Missing Data in Well Logging Using Generative Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10627, https://doi.org/10.5194/egusphere-egu24-10627, 2024.

EGU24-11007 | ECS | Orals | GI2.4 | Highlight

MagMaTaB: A machine learning-based model for magmatic liquid thermobarometry 

Gregor Weber and Jon Blundy

Determining pressures and temperatures of magmas is crucial for addressing diverse challenges in petrology, geodynamics, and volcanology. However, inherent inaccuracies, especially in barometry, have limited the effectiveness of existing models in unravelling the architecture of crustal igneous systems. In this presentation, I will introduce a novel machine learning model, calibrated using an extensive experimental database, to create regression models for extracting P-T conditions of magmas. Calculations are conducted by considering melt chemistry and the coexisting mineral assemblage as input variables.
Our approach is versatile, applicable across a wide range of compositions from basalt to rhyolite, covering pressures from 0.2 to 15 kbar and temperatures ranging from 675 to 1400°C. Testing and optimization demonstrate that the model can recover pressures with a root-mean-square error of 1.1-1.3 kbar and temperature estimates with errors as low as 21°C. This indicates that melt chemistry-mineral assemblage pairs reliably capture magmatic variables across a broader spectrum of conditions than previously thought. We propose that this reliability arises from the relatively low thermodynamic variance in natural magma compositions, despite the presence of numerous oxide components.
Applying our model to two cases with well-constrained geophysics - Mount St. Helens volcano (USA) and the Askja caldera in Iceland - we analyse dacite whole-rocks from Mount St. Helens, erupted between 1980-1986. These rocks, inferred to represent liquids extracted from a complex mineral mush, yield melt extraction source pressures that align remarkably well with geophysical constraints. For Askja caldera, our model allows to assign basaltic and rhyolitic magma chemistries to distinct seismic wave speed anomalies, highlighting the potential of our model to bridge the gap between petrology and geophysics. Our model, named MagMaTaB, is accessible through a user-friendly web application.

How to cite: Weber, G. and Blundy, J.: MagMaTaB: A machine learning-based model for magmatic liquid thermobarometry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11007, https://doi.org/10.5194/egusphere-egu24-11007, 2024.

EGU24-11850 | ECS | Posters virtual | GI2.4

Revolutionizing Igneous Rock Classification: Proportion-Based Deep Learning Analysis of Petrographic Thin Section Photomicrographs 

Evelyn Jessica Jaya, Xinbing Wang, Chenghu Zhou, and Nanyang Ye

In our study, we present a segmented-based, rule-driven classification of igneous rocks through the analysis of thin section photomicrographs, representing a significant advancement over traditional petrographic methods. This deep learning-based approach is especially innovative in its recognition that the naming of rocks is intrinsically linked to the proportion of minerals they contain, a vital aspect frequently overlooked in conventional classification techniques. By focusing on accurately quantifying these mineral proportions, our method effectively addresses the subjectivity and observer variability inherent in traditional petrography. Utilizing semantic image segmentation on 963 petrographic thin section photomicrographs, we have successfully identified 29 distinct minerals and classified 15 types of igneous rocks. This showcases the precision and scope of our approach, which automates the quantification of mineral proportions, thus ensuring a more objective and precise rock classification. The development of our proprietary dataset mask, despite its labor-intensive nature and the challenges with incomplete labelling, was crucial for achieving accurate segmentation based on the proportional regions of each mineral within the photomicrographs. This segmentation, key to our rule-driven classification, streamlines the rock naming process. Our method not only sets new standards in igneous rock classification but also signifies a transformative leap in geological research. By integrating advanced image processing with deep learning, we are opening new frontiers in Earth sciences, highlighting the transformative impact of technology in refining traditional geological methodologies. Considering the dataset's incomplete and highly imbalanced mask scenario, our method achieves an accuracy of 73.32%, significantly surpassing the baseline method using VGG16 as the backbone, which attains only 63.64% classification accuracy.

How to cite: Jaya, E. J., Wang, X., Zhou, C., and Ye, N.: Revolutionizing Igneous Rock Classification: Proportion-Based Deep Learning Analysis of Petrographic Thin Section Photomicrographs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11850, https://doi.org/10.5194/egusphere-egu24-11850, 2024.

EGU24-14437 | ECS | Posters on site | GI2.4

PredRNNv2-based drought prediction using Vegetation Health Index (VHI) 

Soo-Jin Lee and Yangwon Lee

Droughts are expected to increase in both frequency and severity, exacerbated by rising global temperatures associated with climate change. These trends pose serious threats to the agricultural sector, directly impacting food production and security. Moreover, increasing drought incidence increases the risks associated with agricultural and forestry disasters, including reduced crop yields, soil degradation, and wildfires. Given these challenges, the ability to accurately monitor and predict drought conditions is critical. Effective drought forecasting plays an important role in establishing agricultural and water management policies and enabling better handling of the impacts of these events. This will enable timely and informed decisions to ensure that appropriate measures are in place to mitigate the adverse impacts of drought on ecosystems, food supplies and overall environmental health. The development and improvement of tools for drought time series forecasting is therefore essential to ongoing efforts to adapt to and mitigate the impacts of climate change. This study introduces a model designed to predict Vegetation Health Index (VHI) time series data using the Predictive Recurrent Neural Network Version 2 (PredRNN-V2). The VHI, which effectively integrates land surface temperature and vegetation status, has been widely used in drought assessment. The study focuses on South Korea, utilizing long-term weekly VHI data from NOAA for short-term prediction. The PredRNN-V2 model utilizes a network of interconnected spatio-temporal LSTM cells to learn and predict the temporal and spatial characteristics of time series images. This architecture can properly handle the complex spatial and temporal dynamics inherent in satellite-based drought data and can therefore be an effective tool for drought prediction.

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF-2022R1I1A1A01073185)

How to cite: Lee, S.-J. and Lee, Y.: PredRNNv2-based drought prediction using Vegetation Health Index (VHI), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14437, https://doi.org/10.5194/egusphere-egu24-14437, 2024.

EGU24-14857 | ECS | Orals | GI2.4

Nitrate contamination prediction in Groundwater data in Karnataka, India, using Machine Learning (ML) Techniques 

Himanshi Bansal, Venkataramana Devarakonda, and Mayank Dixit

Groundwater is a natural water source crucial in sustaining ecosystems and meeting various human needs. Groundwater is often contaminated due to the various anthropogenic and non-anthropogenic activities. Nitrate is the most abundant pollutant of Groundwater, which may be exogenic and anthropogenic. We studied nitrate ion concentration in Groundwater from dug well data. The Karnataka state's nitrate ion concentration varies from 0 to 1696 mg/l, which is higher in most places than the admissible limit of 45 mg/l as per the World Health Organisation (WHO). The correlation of various parameters, such as pH, electrical conductivity (EC), fluoride, chloride, etc., was studied with nitrate, and maximum correlation was found with chloride and EC.  Our prediction concentration of nitrate ion using Different Machine Learning (ML) algorithms, including Regression, Random Forest (RF), Support Vector Regression (SVR) and Decision Tree (DT) models using the input parameters as pH, EC chloride, and fluoride.  The result showcased that the best model is Support Vector Regression (SVR) with an R2 value of 0.93 and a Mean Square Error (MSE) value of 0.02 for the region. The region's nitrate pollution might be forecast using the SVR model for better estimation.

How to cite: Bansal, H., Devarakonda, V., and Dixit, M.: Nitrate contamination prediction in Groundwater data in Karnataka, India, using Machine Learning (ML) Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14857, https://doi.org/10.5194/egusphere-egu24-14857, 2024.

In this study, we propose a method for monitoring the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar (SAR) images and deep learning models. This approach includes verifying the correlation between water surface area and water level, using data from both the monitored water surface area and real-time water level gauges. Leveraging the Google Earth Engine (GEE) platform, we constructed datasets for seven reservoirs, each with capacities of 700,000 tonnes, 900,000 tonnes, and 1.5 million tonnes, covering the period from 2017 to 2021. The model training was conducted on 1,283 images from four reservoirs, applying shuffling and 5-fold cross-validation techniques. The models' detection results were evaluated based on mean Intersection over Union (mIoU). Utilizing the highest-performing model, we analyzed the correlation between surface area and water level changes from 2017 to 2021. By integrating the water surface area data calculated by the model with real-time reservoir water level information from RAWRIS (Rural Agricultural Water Resource Information System), we confirmed the correlation between changes in water surface area and water levels from 2017 to 2021. This study illustrates that monitoring of water surface areas by satellite can be effectively utilized for tracking status changes in agricultural reservoirs in South Korea.

How to cite: Choi, S. and Lee, Y.: Waterbody Detection of Korean Reservoirs from Sentinel-1 Images and the Analysis of its Relationship with Water Level: A Deep Learning Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16211, https://doi.org/10.5194/egusphere-egu24-16211, 2024.

EGU24-18300 | Orals | GI2.4

Geospatial Foundation Models for Efficient Retrieval of Remote Sensing Images 

Thomas Brunschwiler, Benedikt Blumenstiel, Viktoria Moor, and Romeo Kienzler

This work explores the potential of content-based image retrieval to enable efficient search through vast amounts of satellite data. Images can be identified across multiple semantic concepts without needing specific annotations. We propose to use Geospatial Foundation Models (GeoFM), for remote sensing image retrieval and evaluated the models on two datasets. The GeoFM named Prithvi uses six bands and outperforms other RGB-based models by achieving a mean Average Precision of 61% on ForestNet-4 and 98% on BigEarthNet-19. The results demonstrate that the model efficiently encodes multi-spectral data and generalizes without requiring further fine-tuning. Additionally, this work evaluates three compression methods: i) binary embeddings, ii) trivial hashing, and iii) locality-sensitive hashing. Compression with binarized embeddings isthe best option for balancing retrieval speed and accuracy. It matches the latency of much shorter hash codes while maintaining the same accuracy as floating-point embeddings.

How to cite: Brunschwiler, T., Blumenstiel, B., Moor, V., and Kienzler, R.: Geospatial Foundation Models for Efficient Retrieval of Remote Sensing Images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18300, https://doi.org/10.5194/egusphere-egu24-18300, 2024.

EGU24-18515 | ECS | Posters on site | GI2.4

Toward Determining the Controls on Subduction Zone Seismic Behaviour with Machine Learning 

Valerie Locher, Rebecca Bell, Cedric John, and Parastoo Salah

Variations in earthquake frequency and magnitude across global subduction zones are thought to be influenced by a combination of geological and geophysical factors, such as the age and dip angle of the subducting plate. Despite numerous previous qualitative studies on the correlation between seismic behaviour and subduction zone characteristics, the parameters and mechanisms governing seismicity at subduction zones remain elusive. Our limited historical record of earthquakes further complicates this understanding. Finding underlying general correlations and mechanisms that are valid across different subduction trenches is critical for assessing seismic behaviour and earthquake hazards along subduction plate boundaries which are poorly monitored or have been seismically quiet during the short instrumental record. 
This study aims to bridge the knowledge gaps highlighted above by applying specific unsupervised machine learning techniques to publicly available data on subduction zone parameters and earthquake catalogues. This approach is particularly adept at uncovering hidden correlations in complex, high-dimensional datasets, which might not be discernible through traditional analysis methods. We suggest that seismic behaviour may be describable as a non-linear combination of subduction margin parameters and present a quantitative tool for comparing seismic behaviours across different margins. This may help assess seismic hazards in regions with scant seismic records or that have been historically quiescent. By doing so, we hope to contribute significantly to the predictive modelling of earthquake occurrences and their potential impacts globally.  

How to cite: Locher, V., Bell, R., John, C., and Salah, P.: Toward Determining the Controls on Subduction Zone Seismic Behaviour with Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18515, https://doi.org/10.5194/egusphere-egu24-18515, 2024.

EGU24-19015 | ECS | Orals | GI2.4

Explainable machine learning to uncover hydrogen diffusion mechanism in clinopyroxene 

Anzhou Li, Sensen Wu, Huan Chen, Zhenhong Du, and Qunke Xia

Estimating the water content of mantle-derived magma using clinopyroxene (cpx) phenocrysts serves as a valuable constraint on the water budget in deep Earth. Intricate magma processes and the high hydrogen diffusion rate necessitate careful evaluations of whether the water content in cpx preserves its original state. Machine learning (ML) has been utilized to develop a classifier for judging hydrogen diffusion in cpx. Never- theless, the opaqueness and complexity of most ML models hinder a clear understanding of their classification principles. To elucidate the mechanistic basis of the ML model, the Shapley theory is integrated to determine the contributions of major elements of cpx as features in a linear additive manner. This study achieves superior classification performance using an extreme gradient boosting model and innovatively presents a quantitative evaluation of feature importance at the sample level for each observation. The results indicate that Na plays a predominant role in the diffusion process surpassing other major elements and its associated hydrogen can easily diffuse out of cpx. Our model also identifies various hydrogen association modes in different elemental com- positions and puts constraints on the properties of incorporated hydrogen with non-lattice forming elements in cpx. The findings demonstrate that the application of explainable ML methods in mineralogy holds significant potential for advancing the comprehension of geological phenomena.

How to cite: Li, A., Wu, S., Chen, H., Du, Z., and Xia, Q.: Explainable machine learning to uncover hydrogen diffusion mechanism in clinopyroxene, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19015, https://doi.org/10.5194/egusphere-egu24-19015, 2024.

EGU24-19021 | ECS | Orals | GI2.4 | Highlight

Optimizing crop type mapping for fairness  

Ilya Gorbunov, Caroline Gevaert, and Mariana Belgiu

Minor crops are crucial for food security, especially due to their resilience against climate change related challenges (Renard & Tilman, 2019) . Consequently, accurate crop mapping is essential for monitoring policies seeking to incentivize minor crop production. However, the class imbalance problem in machine learning introduces a bias against these crops, leading to unfair classifications. This research aims to explore how this bias is mitigated through two main class imbalance correction approaches: sample balancing methods and cost-sensitive learning. Apart from investigating how these methods address the typical class imbalance problem, where there are simply less labelled samples of a specific class, we investigate how these methods can be used to address another level of bias, that created by omitted sensitive attributes. These are attributes such as parcel size, which are not explicitly considered by the classifier, yet significantly impact accuracy and contribute to the unfairness of the classification, as evidenced by notably lower accuracy for smaller parcels. By integrating these attributes into the class imbalance correction methods, we assess the potential for enhancing fairness. This approach is vital, as it corrects performance biases affecting specific sub-groups, which are not necessarily class dependent, thus addressing a critical but overlooked dimension of fairness in classification.

Utilizing the BreizhCrops dataset, we create sub-sampled datasets that represent a variety of class imbalance problems. This enables us to conduct an across-the-board comparison of the selected class imbalance correction techniques, providing insights that may help streamline future research looking to employ these techniques. For the classifier architecture, we select the transformer encoder, chosen for its greater performance among deep learning methods tested on the BreizhCrops dataset (Rußwurm et al., 2020).

This research contributes to the broader understanding of class imbalance correction in classification tasks, particularly for crop mapping, though the methods can also be applied in other GeoAI contexts. By evaluating sample balancing and cost-sensitive learning in varied contexts, we provide insights into optimizing classification tasks for fairness. Our work contributes to the development of responsible AI practices by offering valuable insights on how fairness can be enhanced across GeoAI applications.

 

Renard, D., & Tilman, D. (2019). National food production stabilized by crop diversity. Nature, 571(7764), 257–260. https://doi.org/10.1038/s41586-019-1316-y

Rußwurm, M., Pelletier, C., Zollner, M., Lefèvre, S., & Körner, M. (2020). BreizhCrops: A Time Series Dataset for Crop Type Mapping (arXiv:1905.11893). arXiv. https://doi.org/10.48550/arXiv.1905.11893

How to cite: Gorbunov, I., Gevaert, C., and Belgiu, M.: Optimizing crop type mapping for fairness , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19021, https://doi.org/10.5194/egusphere-egu24-19021, 2024.

EGU24-19139 | ECS | Posters on site | GI2.4

Data Bridges: Modeling Marine Science Information to Heterogeneous Information Network for Research Data Management 

Muhammad Asif Suryani, Ewa Burwicz-Galerne, Klaus Wallmann, and Matthias Renz

Research Data Management (RDM) in Natural Science establishes a structured foundation for organizing and preserving scientific data. Effective management and access to these diverse data sources are crucial for supporting domain scientists in future knowledge discovery. Scientific publications, a primary data source often presented in Portable Document Format (PDF), serve as a rich source of information, encompassing text, tables, figures, and metadata. These components present information individually or collectively, offering the potential to explore exciting research directions. However, to fully address these aspects, it is necessary to be able to perform data acquisition from these publications, focusing on these data components, and conducting respective information extraction. Furthermore, modeling the extracted information into a Heterogeneous Information Network of publications enhances accessibility, collaboration, and information harvesting within the natural sciences domain.

We developed a comprehensive framework ensuring user accessibility and widespread applicability, which is capable of modeling diverse information from marine science publications into a Heterogeneous Information Network. The framework comprises three modules: Data Acquisition, Information Extraction, and Information Modeling. The Data Acquisition (DA) module extracts various data components from the relevant publications and transforms them into machine-readable formats. The Information Extraction (IE) module includes two sub-modules: Named Entity Recognition (NER) modules trained on marine science annotated text, capable of extracting eight different types of entities from plain text; and an information parser module responsible for extracting quantitative information from tabular data. It initially detects and then extracts scientific measurements, relevant spatial information, and other available characteristics. Finally, the information modeling module exhibits the extracted information from data components and performs information linking. Consequently, the information is structured into a Heterogeneous Information Network (HIN) of scientific publications, ensuring effective information delivery and providing diverse information to domain experts while supporting the Research Data Management initiative.

How to cite: Suryani, M. A., Burwicz-Galerne, E., Wallmann, K., and Renz, M.: Data Bridges: Modeling Marine Science Information to Heterogeneous Information Network for Research Data Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19139, https://doi.org/10.5194/egusphere-egu24-19139, 2024.

EGU24-19507 | ECS | Orals | GI2.4 | Highlight

Ground Deformation Forecasting and Modeling in Mining Areas Using Artificial Intelligence Techniques 

Patryk Balak, Przemysław Tymków, and Paweł Bogusławski

Underground mining activities cause ground deformations that threaten the stability of surface infrastructure and ecosystems, posing risks to both the environment and human populations. In response to these threats, this study focuses on developing a method for forecasting and modelling ground deformations, which are a consequence of underground mining activities, using advanced artificial intelligence (AI) techniques. The primary goal is to create a model utilising data from Differential Interferometric Synthetic Aperture Radar (DInSAR) and specialised mining data, enabling precise monitoring and forecasting of future changes which will support an adequate upgrade of the decision-making procedure in the mining industry.

 

The study employed two categories of neural networks: Convolutional Neural Networks (CNN) and Feedforward Neural Networks (FNN). In the application FNN, a detailed analysis was conducted on a per-pixel basis across the entire dataset. Each pixel, representing a specific point on the terrain, was analysed with its associated feature vector. This vector comprised multiple attributes derived from the mining data and DInSAR images, effectively capturing the local characteristics of each point, such as its relative position, historical deformation patterns, and proximity to mining activities. For the CNN method, the study focused on exploring the impact of different kernel sizes on model performance. Kernels in CNNs are small matrices used to process data across the image, essential for extracting and learning features crucial for understanding and predicting ground deformations. Varying kernel sizes allow the network to capture different aspects of the data. Considered features included the distance from the centre of the subsidence basin and the mining face at different time intervals. In the context of forecasting, the use of high-quality data is crucial. Unfortunately, some DInSAR images exhibited noise, due in part to a lack of stable coherence and adverse atmospheric effects. A key aspect of the study was therefore the creation and testing of a classifier for the suitability of DInSAR images for forecasting purposes. The analyses showed that the developed classifier achieved an accuracy of 83%. The training data for the prediction study came from the Budryk-Knothe method. The network was tasked with reproducing the operation of this method while simultaneously predicting six days ahead. The models were evaluated based on the mean squared error (MSE) in the areas of the subsidence basin. The test set consisted of specially prepared and trimmed DInSAR images. The FNN-based solution achieved the best results. For this network, satisfactory accuracy was achieved in determining the direction of settlement, with an MSE of 0.12, corresponding to a percentage error of approximately 10% (5 cm for a subsidence of 50 cm).

 

The  results from the study highlight the significant potential of integrating AI techniques with advanced geodetic methods, opening new possibilities in monitoring the impact of mining on the environment. Future work may focus on further optimization of AI algorithms to increase forecasting accuracy over longer periods and in various geological and operational conditions.

How to cite: Balak, P., Tymków, P., and Bogusławski, P.: Ground Deformation Forecasting and Modeling in Mining Areas Using Artificial Intelligence Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19507, https://doi.org/10.5194/egusphere-egu24-19507, 2024.

EGU24-20777 | Orals | GI2.4

The EGDI Knowledge Infrastructure – the next step of Geological data 

Carlo Cipolloni, Jasna Šinigoj, Martin Schiegl, Ángel Prieto Martin, Jorgen Tulstrup, and Stephan Gruijters

One of the main objectives of the European project GSEU (Geological Service for Europe) is to, starting from the EGDI (European Geological Data Infrastructure), develop a system for exchanging knowledge and skills in the geological and geothematic fields, as well as strengthening the development of data and information standards and harmonization frameworks.

To achieve this objective, it was decided to evolve EDGI towards a Geospatial Knowledge Infrastructure (EGDI-KI), for which the conceptual model and the first prototype under development are presented here, which were developed starting from the document developed by UN-GGIM in 2021 for Geospatial Knowledge Infrastructure.

Essential elements of the EGDI-KI are shown in figure 1 and are: The Knowledge Hub forms part of the EGDI structure and serves as a gateway to facilitate access to other components. It enhances the accessibility and usability of the following components:

  • Data Hub: This component focuses on data exchange, access technologies, and supports data science, data engineering, and data warehouse endpoints. The Knowledge Hub helps streamline access to the data hub, making it easier for users to leverage data resources.
  • Applications: The Applications component encompasses WebGIS or thematic portals designed to share information, data, and enable big data analysis. The Knowledge Hub contributes to the seamless integration and utilization of these applications, ensuring efficient access to information and facilitating analysis.
  • Collaboration Tools: Collaboration Tools within EGDI enable the sharing of documents, models, and methods among users. The Knowledge Hub complements this by providing a platform for organizing and accessing these shared resources, fostering collaboration and knowledge exchange.
  • Educational Facilities: EGDI includes educational facilities that support end-users and thematic domains in sharing and transferring knowledge. The Knowledge Hub plays a role in facilitating access to these educational resources, making them readily available to users seeking to enhance their understanding of relevant topics.
  • Expertise & Networking Hub is thematic expert and physical Infrastructure catalogue as well as the possible research and Industry community interactions.

Finally, the knowledge infrastructure platform is the portal to query and navigate all the knowledge resources available in the Knowledge Hub.

The Knowledge Hub plays an important role in the European Geological Data Infrastructure (EGDI) by ensuring that the wealth of knowledge and expertise available within the system is not fragmented and disconnected. Instead, it enables the organisation and accessibility of this knowledge using a semantic Knowledge engine.

By leveraging the semantic Knowledge engine, the Knowledge Hub facilitates the integration and structuring of diverse pieces of information within the EGDI system. It allows for the establishment of meaningful connections and relationships between different data sources, ensuring a coherent and organized presentation of knowledge.

Through the Knowledge Hub, users can efficiently navigate and explore the EGDI system, accessing relevant information in a structured and interconnected manner. It enhances the overall usability and effectiveness of the system, enabling users to leverage the collective knowledge and expertise within the EGDI framework.

How to cite: Cipolloni, C., Šinigoj, J., Schiegl, M., Martin, Á. P., Tulstrup, J., and Gruijters, S.: The EGDI Knowledge Infrastructure – the next step of Geological data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20777, https://doi.org/10.5194/egusphere-egu24-20777, 2024.

EGU24-22089 | ECS | Orals | GI2.4

Classification of different physical scatterers in weather radar data using machine learning techniques 

Alakh Agrawal, Swasti Pahuja, Anjita Neelatt, and JDr Indu

The present study classifies echoes from meteorological and biological targets using dual-polarization Doppler weather radar data from the Next Generation Weather Radar (NEXRAD).  Preliminary results are presented using six key variables namely, Base reflectivity, Base velocity, Spectrum width, Differential reflectivity, Correlation Coefficient, and Differential Phase. A threshold-based filtering methodology was implemented for biological scatterers and heavy precipitation events. To automate the classification, machine learning algorithms were implemented. Multiple machine learning algorithms were implemented and fine-tuned for the highest classification accuracy. Through the integration of machine learning techniques with dual-polarization Doppler weather radar data, this research endeavors to contribute to the development of robust models capable of distinguishing multiple types of physical scatterers from each other.

How to cite: Agrawal, A., Pahuja, S., Neelatt, A., and Indu, J.: Classification of different physical scatterers in weather radar data using machine learning techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22089, https://doi.org/10.5194/egusphere-egu24-22089, 2024.

EGU24-394 | ECS | PICO | GM2.2 | Highlight

Smart boulders for real-time detection of hazardous movement on landslides 

Kate Newby, Georgina Bennett, Kyle Roskilly, Alessandro Sgarabotto, Chunbo Luo, and Irene Manzella

Landslides present a substantial hazard across coastal and mountainous regions in Europe and worldwide, and are becoming increasingly prevalent due to extreme rainfall linked to climate change. There is a need to develop new technologies for landslide monitoring and early warning systems, as traditional approaches alone are insufficient due to low temporal resolution and high costs. The SENSUM project (smart SENSing of landscapes Undergoing hazardous hydrogeologic Movement) has deployed manmade boulders, called SlideCubes, that monitor landslide movement in real-time across two coastal slow-moving landslide sites in southern England (Lyme Regis and Isle of Wight).

SlideCubes are embedded with low-power low-cost sensors that comprise an inertial measurement unit (IMU with accelerometers and gyroscopes) and magnetometers. The SlideCubes are part of a wireless sensor network (WSN) that communicates via Long Range Wide Area Network (LoRaWAN) and Internet of Things (IoT) technologies. Rain gauges and other third-party sensors can be easily integrated into the network to provide additional data sources. Our novel WSN allows for near real-time wireless monitoring of the landslides, only requiring field visits to replace sensor batteries every 9-12 months. The sensors are motion-triggered, significantly saving battery power, meaning the WSN requires little and less frequent maintenance than other sensor-based monitoring approaches. This allows long-term remote measurement of landslide kinematics (inferred from SlideCubes) and initiation of movement, which is key for early warning.

In the present work, initial findings from the SlideCubes installed at two UK-based sites are discussed. The movement events detected and recorded over 2 years are validated by periodic GNSS and drone imagery surveys. We present an overview of temporal and spatial motion across both landslide sites and evaluate sensor performance. Using gyroscope and accelerometer readings from field and laboratory data, we demonstrate how types of motion (e.g. rolling, sliding) can begin to be categorised, which is not possible with the accelerometer alone. This research will be developed in future with machine learning to detect hazardous movement including large magnitude catastrophic events. These findings will be integrated into a SENSUM early warning online portal, in development, for use by stakeholders.

How to cite: Newby, K., Bennett, G., Roskilly, K., Sgarabotto, A., Luo, C., and Manzella, I.: Smart boulders for real-time detection of hazardous movement on landslides, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-394, https://doi.org/10.5194/egusphere-egu24-394, 2024.

EGU24-558 | ECS | PICO | GM2.2

Estimating bed material transport in Himalayan streams using the virtual velocity approach 

Anshul Yadav, Sumit Sen, Luca Mao, and Marwan A. Hassan

This study investigates sediment mobility and transport dynamics in two Himalayan rivers, the Aglar and Paligad Rivers, during both monsoon and non-monsoon flows. Employing the virtual velocity approach, key parameters such as bed proportional mobility (Y), active layer depth (ds), and displacement length were measured to estimate the virtual velocity of mobilized grains. Local parameters (0.5 m sub-sections) and wetted cross-sectional averages were utilized. Using local parameters, the total annual bed material transport was determined as 67,100 t (±20,400 t) and 18,400 t (±6,000 t) for the Aglar and Paligad Rivers, respectively, with nearly 60% occurring during the monsoon. The significant contribution of non-monsoonal flows (~ 40 %) could be ascertained to higher enough flows in specific sub-sections inducing partial or full mobility. Still, the contribution of partial transport (PT) remained lower (< 6%). In contrast, based on cross-section average parameters, total transport was estimated at 42,300 t (±15,800 t) and 12,200 t (±4,700 t) for the Aglar and Paligad Rivers, respectively, with approximately 79% and 68% occurring during the monsoon. The contribution of PT increased to nearly 18% and 29% for the Aglar and Paligad Rivers, respectively, attributed to the averaging effects of shallower sections. Furthermore, the interdependence of partial transport on Y and full transport on ds leads to discontinuities in transport curves, prompting the proposal of a unified function to represent transport extent for both partial and full transport conditions. The unified function ensured the generation of continuous transport curves, yielding similar transport patterns concerning the contribution of PT, FT, monsoonal, and non-monsoonal flows. The findings are particularly relevant for efficient river management as the region houses several hydropower plants and is highly susceptible to climate change.

Keywords:

Painted tracers, partial transport, full transport, active layer, monsoonal flows

How to cite: Yadav, A., Sen, S., Mao, L., and A. Hassan, M.: Estimating bed material transport in Himalayan streams using the virtual velocity approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-558, https://doi.org/10.5194/egusphere-egu24-558, 2024.

EGU24-1825 | ECS | PICO | GM2.2

The Transition from Granular Debris Flow to Bedload: a force balance perspective 

Islam Koa, Alain Recking, and Florent Gimbert

Sediment transport can occur in a so-called “debris flow” form, where concentrations are high and movement is driven by gravity. Previous studies have predominantly used simple rheological fluids or uniform granular materials to study the characteristics of debris flows. However, a fundamental question remains regarding the characteristics of the complex granular debris flow, and the transition from granular debris flow to bedload remains poorly understood. In this contribution, we present an experiment in the laboratory where this phenomenon could be studied. Our experiment setup, a 6-meter-long wooden flume, involved a 1 m-long low-slope trapezoidal storage area and a 5 m-long and 0.1 m-wide wooden flume channel inclined at 33%, equipped with a force plate and hydrometer sensors. Our observations show that self-formed, highly concentrated sediment accumulation in the storage area, influenced by flow rate, generates pulses that exhibit three phases: the tail phase containing sand particles, the body phase containing a mixture of particles, and the front phase containing coarse particles. As discharge was dynamically increased, two distinct domains controlled by the forefront coarse particles were observed. Firstly, at low flow (0.14-0.16 l/sec), a static-dynamic domain is identified, characterized by a high sediment concentration and very low velocity. This generates a high resultant force magnitude that affects the forefront coarse particles, resulting in debris-flow-like pulses controlled by the sediment density. Secondly, at higher flows (0.17–0.24 l/sec), a full-dynamic domain is identified, characterized by a lower sediment concentration and very high velocities. This behavior generates hyperconcenrated flow-like pulses controlled by momentum transfer between the pulse phases. We demonstrated that the transition from debris and hyperconcentrated flow to bedload is controlled by the coarse particle’s mobility, whose threshold discharge in clear water was 0.22 l/sec. The important role played by the sand fraction is also demonstrated, which permits the static dynamics behavior by ensuring momentum transfer either directly, by mass transfer, or indirectly by reducing the medium porosity.

How to cite: Koa, I., Recking, A., and Gimbert, F.: The Transition from Granular Debris Flow to Bedload: a force balance perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1825, https://doi.org/10.5194/egusphere-egu24-1825, 2024.

EGU24-9717 | ECS | PICO | GM2.2 | Highlight

Vertical Mixing of Suspended Sediment in Big Rivers using ADCP data and Machine Learning 

Chris Tomsett, Julian Leyland, Steve Darby, Tom Gernon, Dan Parsons, Thea Hincks, and Josh Wolstenholme

Sediment is an intrinsic component of the fluvial network, supplying material for floodplains and coastal landforms which provide resilience during flooding and storms. As a result, an understanding of the fluvial processes that control how much sediment moves through our river systems, and how this varies across the globe, is of fundamental importance.

For the purpose of estimating sediment delivery through the fluvial network, it is often assumed that rivers are well mixed through their vertical extent. However, empirical data reveals that there is frequently large variability in the concentration of sediment through the water column. Better understanding this variability is of interest to the geomorphological community to help explain variations in sediment transport and improve estimates of sediment flux.

In this research, we utilise a collection of Acoustic Doppler Current Profiler (ADCP) data from large rivers across the globe to investigate variations in the vertical distribution of suspended sediment. Calibrations of ADCP backscatter to Suspended Sediment Concentration (SSC) from the wider literature are used, alongside median grainsize and acoustic frequency, to create a Machine Learning (ML) model from which SSC from uncalibrated ADCPs can be estimated. This new ML model is subsequently implemented to explore the variations in the vertical mixing of suspended sediment both temporally and spatially. This variability is explored to identify the importance of catchment characteristics in determining variations in suspended sediment concentration within the water column. Comparison of multiple river systems and their catchment characteristics, both between sites and through time, enables the identification of key attributes which exert a greater control on this variation through the water column. Subsequently, this leads to an improved understanding of sediment flux through the river system, whereby knowing the variation in sediment concentration within the water column can help to better calibrate current methods of estimating flux.

How to cite: Tomsett, C., Leyland, J., Darby, S., Gernon, T., Parsons, D., Hincks, T., and Wolstenholme, J.: Vertical Mixing of Suspended Sediment in Big Rivers using ADCP data and Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9717, https://doi.org/10.5194/egusphere-egu24-9717, 2024.

EGU24-11132 | PICO | GM2.2

Comparing methods to quantify grain-scale sediment structure in gravel-bed rivers 

Rebecca Hodge, Hal Voepel, Elowyn Yager, Julian Leyland, Joel Johnson, David Sear, and Sharif Ahmed

Understanding when gravel moves in river beds is essential for a range of different applications, but is still surprisingly hard to predict. The critical shear stress at which a grain will move depends on its relative size and structure within the bed, and spatial and temporal changes in grain-scale structure are likely to be a major driver of changes in critical shear stress. Consequently grain-structure metrics such as protrusion, pivot angle and contact with any surrounding fine grained matrix are used as parameters in models to predict critical shear stress, and so there is an increasing demand for measurements of these parameters in order to improve our predictive ability. However, we do not have established methods for measuring these parameters, nor do we know whether different methods provide consistent results. Here we present and compare new datasets of sediment structure metrics collected from eight locations in a small gravel-bed stream using three different methods: direct field-based measurements, terrestrial laser scanning (TLS), and computed tomography (CT) scanning. Using each method, we measure metrics including grain size distribution, grain protrusion and fine matrix content. We find that distributions of grain size are consistent between field-based and TLS data, but smaller in CT data. All three methods produce similar distributions of protrusion relative to grain size. There is also some consistency between field and CT measures of fine-grained matrix. However, the identification of similarity also depends on the type of analysis, and an alternative analysis shows less similarity in protrusion and fine-grained matrix between the different methods. Of the three methods, TLS-based approaches have potential to be most easily applied, and our analysis suggests that for grain-size and protrusion they perform as well as the alternative methods. However, they cannot currently be used for measuring fine-grained matrix content.

How to cite: Hodge, R., Voepel, H., Yager, E., Leyland, J., Johnson, J., Sear, D., and Ahmed, S.: Comparing methods to quantify grain-scale sediment structure in gravel-bed rivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11132, https://doi.org/10.5194/egusphere-egu24-11132, 2024.

EGU24-11623 | ECS | PICO | GM2.2

Application of Entropy theory to estimate the sediment transport 

Farhad Bahmanpouri, Silvia Barbetta, Christian Massari, Domenico De Santis, Ashutosh Sharma, Ankit Agarwal, and Sumit Sen

Abstract: Sediment transport is a natural process where sediment particles can be deposited downstream and exacerbate flooding. The movement of sediments can be observed in flows through rivers, canals, and coastal areas which include suspended load transport and bed-load transport. Bed-load transport occurs in the area close to the riverbed, which is of particular importance in shaping the riverbed. The present research aims to investigate the sediment transport process by applying the Entropy concept as a theoretical approach to the activities of the project ‘Probabilistic floods and sediment transport forecasting in the Himalayas during extreme events’, funded in the context of the Italy-India joint science and technology cooperation program.

Specifically, based on collected field data through the Alaknanda River at Srinagar in India by current meter, first, the Entropy theory was applied to obtain the cross-sectional distribution of the velocity (based on recent developments of Entropy theory in Bahmanpouri et al., 2022a, b). The calculated mean velocity and discharge were compared with the observed data collected by the Central Water Commission (CWC). Next, shear velocity was calculated for different cross-sections based on different flow conditions. Further, shear stress was calculated based on two terms induced by skin friction and bedforms, respectively. Finally, the shield parameter was obtained based on shear velocity distribution to find out if sediment particles have the potential to be transported or not. Overall, the findings of the current research highlighted the potential of the theoretical method of Entropy to calculate sediment transport in developing countries.

 

Bahmanpouri, F., Barbetta, S., Gualtieri, C., Ianniruberto, M., Filizola, N., Termini, D., & Moramarco, T. (2022a). Prediction of river discharges at confluences based on entropy theory and surface-velocity measurements. Journal of Hydrology606, 127404.

Bahmanpouri, F., Eltner, A., Barbetta, S., Bertalan, L., & Moramarco, T. (2022b). Estimating the Average River Cross‐Section Velocity by Observing Only One Surface Velocity Value and Calibrating the Entropic Parameter. Water Resources Research58(10), e2021WR031821.

How to cite: Bahmanpouri, F., Barbetta, S., Massari, C., De Santis, D., Sharma, A., Agarwal, A., and Sen, S.: Application of Entropy theory to estimate the sediment transport, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11623, https://doi.org/10.5194/egusphere-egu24-11623, 2024.

EGU24-11689 | PICO | GM2.2 | Highlight

Using seismic and timelapse camera observations to study flood-induced morphological changes on an alpine gravel-bed reach 

Adele Johannot, Florent Gimbert, Alain Recking, and Marco Piantini

Morphological changes in alluvial rivers are very active and remain very complex to predict because of the high spatio-temporal variability of bedload. This strongly limits the ability of river managers to assess risk or conduct ecological restoration. With the recent development of non-intrusive methods to monitor bedload, such as seismic or acoustic tools, acquisition of data has been highly facilitated compared to direct measurement methods involving in-situ sampling. The challenging task remains in the interpretation of the signals during phases of intense bedload transport which are responsible for major morphological changes. The analysis of such signals requires a good understanding of the underlying physics as well as in-situ field observations to confort interpretation. In this work, we combine seismic with timelapse camera observations with the objective to have a better understanding of bedload behavior and its consequences on the morphology during floods on an alluvial reach of the Severaisse river in the French Alps. Data consists in 3 seismic sensors continuously recording at 200Hz from upstream to downstream along the reach, as well as data from 2 cameras taking timelapse photos of the reach at a 10 min interval during flood. We We find that high frequency seismic power, attributed to bedload, exhibits a characteristic scaling relationship against discharge, materialized by two different phases: a scaling of about 5 from above the threshold of motion (around 12m3/s water discharge) up to a critical discharge of 25 m3/s, and a scaling of about 1.4 above 25 m3/s. We interpret the first scaling to be due to bedload occurring in a diluted regime as described in previous models, and the second scaling to be due to bedload in an intense transport phase. This shift only occur during floods where we observe channel shifting or important re-working of the bed and we suppose that it represents a phase of intense transport responsible for morphological changes. Interestingly, for the most extreme flood with a return period of 50-years, the seismic power versus discharge relationship shows a distinct behavior form the other floods, materialized by a particularly larger and singular hysteresis. Next steps include understanding why this distinct signature occurs, quantify the morphological changes by calculating indexes from image analysis and investigate how bedload and hence the morphological changes depends on the season, characterized by a snow-melting spring and summer and rainy autumn and winter through a multi-year scale.

How to cite: Johannot, A., Gimbert, F., Recking, A., and Piantini, M.: Using seismic and timelapse camera observations to study flood-induced morphological changes on an alpine gravel-bed reach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11689, https://doi.org/10.5194/egusphere-egu24-11689, 2024.

Bedload transport plays a crucial role in shaping landscapes, yet monitoring it is challenging. Seismic sensors have emerged as valuable tools for continuous and non-invasive bedload transport monitoring. However, isolating the seismic signal of bedload transport from other environmental signals such as flow turbulence remains a challenge. While seismic waves propagate both vertically and horizontally, previous seismic bedload transport studies focused solely on the vertical component. This was based on the assumption that the bedload transport signal was mainly contained in Rayleigh waves which propagate with both vertical and horizontal motion, as opposed to Love waves which propagate with only horizontal motion. We hypothesise that there may be a significant signal from horizontally-propagating waves that characterises the interactions of coarse bedload impacts, and that this signal will be strongest in a flow-parallel orientation.  

This study employs the Horizontal-to-Vertical Spectral Ratio (HVSR) which is a passive method, commonly used in engineering seismology, that determines the ratio between horizontal and vertical seismic signal components. In this study, we explore the potential of the HVSR method to isolate the dominant component in seismic bedload transport signals and its applicability for monitoring fluvial processes within rivers. Using seismic, hydroacoustic, and hydrological measurements from the River Feshie in Scotland, our findings challenge prior belief that the seismic signal of bedload transport predominantly resides in the vertical component; instead, the horizontal component contains significant fluvial and bedload transport information. Due to differences in seismic wave characteristics, the HVSR method acts as a tool to isolate signals of bedload transport and water turbulence.

Additionally, the HVSR method demonstrates promise in effectively filtering out meteorological signals that may contaminate raw river-induced seismic signals, enabling more accurate monitoring of bedload transport occurrences. However, we acknowledge that the contributions of horizontal and vertical signals greatly depend on sensor location and site characteristics. This study emphasises the significance of utilising horizontal seismic signals for comprehensive bedload transport monitoring, presenting an opportunity for this method to enhance our understanding of complex fluvial processes within river systems.

How to cite: Matthews, B., Naylor, M., Sinclair, H., and Gervais, M.: Exploring vertical component dominance in seismic bedload transport signals: Horizontal-to-Vertical Spectral Ratio (HVSR) analysis in the River Feshie, Scotland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12924, https://doi.org/10.5194/egusphere-egu24-12924, 2024.

We present results from a particle-scale numerical model inspired by the idea that a majority of the time during transport capable floods, bedload transport in rivers is rarefied, and a stochastic process. Physical experiments conducted by others to explore this idea suggest that the time varying particle activity N measured within a control area A above the bed surface is described by a Poisson probability mass function (pmf), assuming an absence of collective entrainment. This implies that particles are sporadically entrained from the bed surface at rate λ with no “memory” of prior entrainment events, when and where local flow conditions favor particle lift or dislodgement. In this context we developed a new open source kinematic particle-scale model written in Python (Zwiep and Chartrand, 2022). Notably, the model includes no information related to the bed surface shear stress or Shields conditions, and no sediment transport functions are used to drive the model.

The model domain measures a use specified length nD of the particle diameter D, with a width of 1D. At present we have tested the model with 30 simulations using a uniform particle diameter. Each simulation was run for 1 million iterations to explore the governing model parameters: SRe is the number of subregions within the domain length nD; En is the particle entrainment rate per iteration, which we randomly sample from a Poisson pmf for a specified value of λ; lt is the particle travel distance which we randomly sample from either a lognormal distribution or a truncated normal distribution for specified values of the distribution expected value and standard deviation; and Sh is the vertical particle stacking height ranging from 1-3D.

The model produces a time varying signal of particle flux counted at downstream points of internal subregion domains, and at the downstream end of the model domain. The simplified particle bed changes “relative” elevation distributions through particle stacking and downstream motions of travel distance. An implication of particle stacking within the context of a stochastic model framework is a time varying signal of the average “particle age” defined as the number of iterations since last entrainment, as well as the average “particle age range” defined as the difference of the maximum and minimum particle ages, both metrics calculated at each iteration and across all subregions. The age dynamics correlate with the magnitude of N following an initial period of particle bed organization. Our initial tests suggest that the relatively simple model logic captures the essence of rarefied particle transport. We believe the model can be used to ask basic science questions, and as a classroom tool to introduce students to bedload transport in a straightforward and illustrative manner.

References:

Zwiep, S., & Chartrand, S. M. (2022). pySBeLT: A Python software package for stochastic sediment transport under rarefied conditions. Journal of Open Source Software, 7(74), 4282. https://doi.org/10.21105/joss.04282.

How to cite: Chartrand, S.: A simplified Python-based kinematic model of particle transport in rivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13064, https://doi.org/10.5194/egusphere-egu24-13064, 2024.

EGU24-16886 | PICO | GM2.2

Resolving bedload flux variability 

Thomas Pähtz, Yulan Chen, Jiafeng Xie, Rémi Monthiller, Raphaël Maurin, Katharina Tholen, Hao-Che Ho, Peng Hu, Zhiguo He, and Orencio Durán

Bedload transport plays a vital role in shaping Earth’s environment by promoting the formation and growth of geological features of various scales, including ripples and dunes, deltas and fans, and laminations and cross-bedding. A key problem hampering our understanding of bedload-induced landscape evolution is the notoriously large variability commonly associated with measurements of bedload flux, even under controlled and highly idealized conditions in the laboratory, such as fully-developed, unidirectional open-channel flows over flat beds composed of grains of nearly uniform sizes. For example, two recent experimental studies report a nearly sixfold different nondimensionalized bedload flux at a comparable Shields number for spherical grains [1, 2]. The likely culprit is the immense difficulty experimentalists face in estimating the transport-driving bed shear stress. There is currently no universally accepted method of even determining the bed surface elevation in the presence of bedload transport, which is particularly problematic for shallow flows where small changes have a large effect. Neither is there agreement on how to account for the effects of sidewall friction, which become the stronger the smaller the width-to-depth ratio b/h of the open-channel flow. Standardly employed empirical sidewall corrections have arguably a greater resemblance to cooking recipes than to formal physically-derived methods. In addition to such experimental difficulties, there is the physical question of how grain shape, which usually is not controlled for in laboratory experiments, affects bedload flux. A recent prominently published study argued that grain shape is the predominant reason for bedload flux variability and put forward a semi-empirical, analytical bedload transport model to account for it [1].

Here, we compile data from existing experiments and existing and new DNS-DEM, LES-DEM, and RANS-DEM numerical simulations of turbulent bedload transport of shape-controlled grains, in which b/h varies between 0.1 and infinity (periodic boundary conditions in simulations). After employing a non-empirical sidewall correction, which we derived from the phenomenological theory of turbulence, and a granular-physics-based method to determine the bed surface elevation, all data for spherical grains of sufficient size collapse onto a single curve, resolving the experimental problem of bed shear stress determination. Furthermore, the combined data for spherical and non-spherical grains are in strong disagreement with the model of Ref. [1] but support our alternative analytical bedload model across grain shapes, bed slopes, flow strengths, and channel widths.

[1] Deal et al., Nature 613, 298 (2023). https://doi.org/10.1038/s41586-022-05564-6

[2] Ni & Capart, Geophysical Research Letters 45, 7000 (2018). https://doi.org/10.1029/2018GL077571

How to cite: Pähtz, T., Chen, Y., Xie, J., Monthiller, R., Maurin, R., Tholen, K., Ho, H.-C., Hu, P., He, Z., and Durán, O.: Resolving bedload flux variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16886, https://doi.org/10.5194/egusphere-egu24-16886, 2024.

EGU24-18899 | ECS | PICO | GM2.2

Hydro-acoustic multi-frequency measurements of suspended sediment flux in rivers 

Jakob Höllrigl, Koen Blanckaert, David Hurther, Guillaume Fromant, and Florian R. Storck

Currently, the estimation of suspended sediment concentration (SSC) fluxes in rivers relies on river discharge and an average SSC, the latter is commonly determined through optical turbidity measurements at a single point in the river cross-section. This approach has limitations, such as the SSC data being extrapolated from a one-point measurement and indirectly determined depending on regular sampling and laboratory analysis, which is cost-intensive.


Hydro-acoustic echosounders are an alternative to derive SSC across an entire profile, for accurate conversion from backscatter intensity to SSC knowledge of particle size is a requirement. In this approach, we present a method utilizing multi-frequency hydro-acoustic echosounding in addition to velocity measurements via an ADCP. Operating on various acoustic frequencies allows for the direct estimation of mean particle size from backscatter data at different frequencies over a water profile. River in-situ measurements as well as laboratory experiments have been conducted in different concentration as well as particle size distribution regimes.

How to cite: Höllrigl, J., Blanckaert, K., Hurther, D., Fromant, G., and Storck, F. R.: Hydro-acoustic multi-frequency measurements of suspended sediment flux in rivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18899, https://doi.org/10.5194/egusphere-egu24-18899, 2024.

EGU24-18979 | ECS | PICO | GM2.2

Exploring moisture-constrained aeolian sediment transport through a discrete particle modelling framework 

Xiuqi Wang, Geert Campmans, Thomas Weinhart, Anthony Thornton, Stefan Luding, and Kathelijne Wijnberg

Moisture is a crucial environmental factor that shapes the dynamics of aeolian sediment transport along coastal beaches. Despite the existence of empirical formulations, little is known about the mechanism through which moisture influences this dynamic process. To address this knowledge gap, we present a numerical modelling framework implemented in the open-source software package MercuryDPM [1].
This framework combines a discrete particle model, a one-dimensional airflow model and a liquid migration model. The two-way coupling between the discrete particle model and the airflow model can accurately represent the momentum exchange between these phases, yeilding reasonable sediment transport rates [2]. The inter-particle moisture distribution is modelled by a liquid migration law, which governs the presence of liquid films covering the particle surfaces and liquid bridges spanning the particle contacts [3]. The liquid bridge model introduces a static capillary force as well as a dynamic lubrication force, which is necessary to model the dynamic effects of moisture. This comprehensive model effectively captures particle behaviour under moist conditions and demonstrates the dependence of bed erodibility on particle impact and wind entrainment for varying moisture levels.
Our approach provides valuable insights on the moisture effect in aeolian sediment transport. It advances our understanding of this complex phenomenon, and gives insights on the development of geomorphological patterns at coastal sandy areas. With its flexilibity and versatility, it can be extended to study many more specific processes related to sediment transport.


[1] Weinhart, T., Orefice, L., Post, M., et al (2020). Fast, flexible particle simulations—an introduction to MercuryDPM. Computer physics communications, 249, 107129.
[2] Campmans, G., & Wijnberg, K. (2022). Modelling the vertical grain size sorting process in aeolian sediment transport using the discrete element method. AeolianResearch, 57, 100817.
[3] Mani, R., Kadau, D., Or, D., & Herrmann, H. J. (2012). Fluid depletion in shear bands. Physical review letters, 109 (24), 248001.

How to cite: Wang, X., Campmans, G., Weinhart, T., Thornton, A., Luding, S., and Wijnberg, K.: Exploring moisture-constrained aeolian sediment transport through a discrete particle modelling framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18979, https://doi.org/10.5194/egusphere-egu24-18979, 2024.

EGU24-20740 | ECS | PICO | GM2.2

Multi-Model Comparison of Suspended Sediment Flux in the Sagavanirktok River, Alaska.  

Theodore Langhorst, Konstantinos Andreadis, and Tamlin Pavelsky

Fluvial sediment transport is an important component of the global sediment budget, yet in-situ monitoring is limited. Researchers and practitioners employ various methods to fill in these gaps, each with their own advantages and drawbacks. In this study, we compare four different models for estimating the total annual suspended solids and daily suspended sediment flux for the Sagavanirktok River in Alaska. These four models include: 1) in-situ turbidity calibration; 2) WBMsed global sediment flux estimates 3) optical remote sensing random forest model; and 4) Long-short term memory (LSTM) model trained on remote sensing and modeled inputs. We focus particularly on the summers of 2022 and 2023, when we have continuous validation data via a USGS discharge gage and turbidity sensors that we installed. We evaluate the accuracy, practicality, and shortcomings of each approach to reconstructing the total suspended sediment flux of the Sagavanirktok River. We highlight the necessity of high temporal resolution (approximately daily) for estimating suspended sediment flux in the Sag. River due to the frequency of high discharge events and variable hysteresis between discharge and sediment load. We find that, for the Sag. River, optical imagery alone does not have sufficient temporal resolution to estimate suspended sediment flux (due to orbit repeat and clouds), despite the accuracy of individual estimates. The geomorphic model, WBMsed, is not accurate enough for the unusual hydrology, but does produce daily estimates. Finally, the LSTM model shows promise in being able to bridge the temporal mismatch between satellite, in-situ, and modeled dataset. The LSTM can take advantage of daily discharge models, while incorporating the accuracy of optical satellite sediment models

How to cite: Langhorst, T., Andreadis, K., and Pavelsky, T.: Multi-Model Comparison of Suspended Sediment Flux in the Sagavanirktok River, Alaska. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20740, https://doi.org/10.5194/egusphere-egu24-20740, 2024.

EGU24-226 | ECS | Posters on site | NH9.2

Propagation of climate extremes across global value chains 

Serine Guichoud, Laurent Li, and Patrice Dumas

This paper presents a theoretical frame relying on the graph theory for assessing extreme weather events relative damage to global value chains. 
The approach is defined in three steps: the first part of the paper presents the intuition inspiring the defined model and associated theory , the second part is focused on a scenario analysis declining extreme events relative severity by countries, the third part leverages on the graph theory to translate the damages associated to these events into macro-sectorial value chains disruptions. A numerical application is then run by estimating drought global damages.
We consider damage as a score based on extreme events occurrence, calibrated in this article with historical data. Using the graph theory, we incorporate these damages to a network of countries moving from a stationary state of constant flows before a distribution of extreme events, to a modified state considering the extreme events occurrence. The spread of these production damages is modeled as a contagion applied to a network representing intermediate consumption financial flows, to assess the cumulative effect of a damage to value chains. 

How to cite: Guichoud, S., Li, L., and Dumas, P.: Propagation of climate extremes across global value chains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-226, https://doi.org/10.5194/egusphere-egu24-226, 2024.

EGU24-681 | ECS | Orals | NH9.2

Windstorm risk assessment in the Netherlands: Evaluation of statistical dependencies between hazard and damage data 

Maria del Socorro Fonseca Cerda, Toon Haer, Hans de Moel, Jeroen Aerts, Wouter Botzen, Elco Koks, and Daan van Ederen

Extreme windstorms pose significant societal and economic challenges, ranking among the costliest natural disasters in Europe. This study addresses the complex task of quantifying windstorm impacts, with a specific focus on the Netherlands. Despite their substantial economic cost, windstorm risks in the Netherlands have been underexplored in dedicated regional studies. Existing large-scale investigations often rely on hazard-loss relationships derived from data from other European countries. We aim to enhance the accuracy of windstorm risk assessment by utilizing not only higher-resolution hazard data but also higher-resolution Dutch damage data. Our methodology involves analyzing high-resolution data to identify hazard variables that best correlate with losses. This is done by leveraging post-disaster loss data from a private Dutch insurance company. In particular, we use the aggregated losses per postal code 4 area, which delivers a nuanced understanding of the spatial distribution of losses. Simultaneously, we account for hazard intensities using the wind climatology data from KNMI North Sea Wind (KNW). This data is derived from 40 years (1979-2019) of ERA-Interim re-analyzed data and downscaled to a higher resolution (2.5 x 2.5 km) tailored specifically for the Netherlands. Through statistical analysis, the study aims to determine the most suitable hazard components for a regional windstorm damage assessment model. This approach aims to move beyond the conventional use of daily maxima wind speed or gust speed by evaluating the appropriateness of hazard variables concerning observed losses. This meticulous integration of proprietary loss records and refined wind climatology enables developing new spatial windstorm hazard maps and a high-resolution windstorm risk database, which provide a solid basis for risk assessment.

How to cite: Fonseca Cerda, M. S., Haer, T., de Moel, H., Aerts, J., Botzen, W., Koks, E., and van Ederen, D.: Windstorm risk assessment in the Netherlands: Evaluation of statistical dependencies between hazard and damage data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-681, https://doi.org/10.5194/egusphere-egu24-681, 2024.

EGU24-3045 | Posters on site | NH9.2

Applying Mobile Phone Data on Seismic Disaster Reduction 

Sheu-Yien Liu and Ming-Wey Huang

To grasp specific population distribution information is crucial for accurate impact assessments and preparedness planning on natural disasters. With the high popularization of mobile phones, it is possible to know the distribution trend of the people movement in different regions. The mobile phone data from Chunghwa Telecom (the telecommunications company with largest market share in Taiwan) displayed in 500m×500m grids gives the spatiotemporal distribution of people around the Taiwan area on the geographic information system (GIS). Combined with immediate reception of earthquake intensity distribution map, not only can the number of people at risk be more accurately estimated, but also the abnormal flow of people can be highlighted in areas, and then provide real-time warning messages. Except for the real-time crowd data, the historical data from one year of 2018, which is converted into weekly crowd data, are also provided for the purpose of seismic disaster scenarios to improve the precision of relief needs by the grid-base earthquake impact assessment technology of TERIA (Taiwan Earthquake Impact Research and Information Application Platform, established by NCDR) for enhancing the disaster resilience against future major earthquakes.

How to cite: Liu, S.-Y. and Huang, M.-W.: Applying Mobile Phone Data on Seismic Disaster Reduction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3045, https://doi.org/10.5194/egusphere-egu24-3045, 2024.

EGU24-3851 | ECS | Posters on site | NH9.2

Development of the Methodology to Identify Potential Modes of Dam Failure and to Estimate Structural Health of Water Management Dams 

Mateja Klun, Žiga Begelj, and Andrej Kryžanowski

Here we present the project activities of an ongoing project aiming at the identification of potential failure modes of dams and the development of the methodology to be applied on water management dams in Slovenia. Water is the most important natural resource for human existence, while changes in hydrological conditions have an impact on the water balance and require innovative approaches in water management. There are currently 68 registered infrastructure facilities in Slovenia, 42 of which meet the criteria of large dams or are subject to a special regime for operational safety as critical infrastructure. According to the Slovenian National Committee for Large Dams the average age of our dams is already more than 45 years.

Objectives of the project proposal, which will last 24 months, are the following: the analysis of the current state of the practice in the field of dam surveillance in Slovenia, provision of a summary document with a set of potential failure mechanisms for each type of dams, and development of a methodology for identifying failure mechanisms and monitoring the condition of dams. Monitoring of dams is regularly carried out in Slovenia, at least in the form of technical monitoring of the structures. However, we must note that professional knowledge of the operational safety of dams has advanced considerably since the time when most of the dams in Slovenia were built. In particular, the understanding of dam safety has changed and is now understood in a broader sense, encompassing the safety of the dam and auxiliary structures under all conditions throughout its life cycle, as well as the safety of the population and the environment in the dams' impact area. The lifetime of dams is very long, and sound structural management improves their structural health of dams and extends their service life.

The main output of the project is the development of the methodology for identification of potential failure modes. The steps of the methodology will also be implemented on at least 3 pilot cases and will be presented to the professional public and to institutions working in the field of dams and dam engineering. The project addresses both the World Declaration on Dam Safety, (Porto, 2019), and the World Declaration Water Storage for Sustainable Development, from (Kyoto, 2012). The authors acknowledge that the research is financially supported by the Slovenian Research and Innovation Agency research project No. V2-2340 and by the Ministry of Natural Resources and Spatial Planning.

How to cite: Klun, M., Begelj, Ž., and Kryžanowski, A.: Development of the Methodology to Identify Potential Modes of Dam Failure and to Estimate Structural Health of Water Management Dams, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3851, https://doi.org/10.5194/egusphere-egu24-3851, 2024.

EGU24-5387 | ECS | Orals | NH9.2 | Highlight

High-resolution Downscaling of Disposable Income in Europe using Open-source Data 

Mehdi Mikou, Améline Vallet, Céline Guivarch, and David Makowski

Poverty maps have been extensively used for identifying populations vulnerable to global changes. The frequency and intensity of extreme events are likely to increase in coming years as a result of climate change. In this context, several studies have hypothesized that the economic and social impact of extreme events depends on income. However, to rigorously test this hypothesis, it is necessary to have income data on a fine spatial scale, compatible with the analysis of extreme climatic events. In order to produce reliable high-resolution income data, we have developed an innovative machine learning framework, based on random forests, that we applied to produce a 1 km-gridded dataset of disposable income for 2015 in Europe. This dataset was generated by downscaling disposable income data available for more than 120,000 administrative units. Our learning framework showed high accuracy levels, and outperformed other existing approaches used in the literature for downscaling income. Using SHAP values, we explored the contribution of the model input factors to income predictions and found that, in addition to geographic inputs (country, latitude, longitude), distance to public transport or nighttime light intensity were key drivers of income predictions. Finally, we illustrated how this new dataset can help identifying poverty areas in Europe. More broadly, this dataset offers an opportunity to explore the relationships between economic inequality and environmental degradation in health, adaptation or urban planning sectors. It can also facilitate the development of future income maps that align with the Shared Socioeconomic Pathways, and ultimately enable the assessment of future climate risks.

How to cite: Mikou, M., Vallet, A., Guivarch, C., and Makowski, D.: High-resolution Downscaling of Disposable Income in Europe using Open-source Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5387, https://doi.org/10.5194/egusphere-egu24-5387, 2024.

EGU24-8752 | ECS | Orals | NH9.2 | Highlight

Identifying global biases in hydro-hazard research by mining the scientific literature 

Lina Stein, S. Karthik Mukkavilli, Birgit M. Pfitzmann, Peter W. J. Staar, Ugur Ozturk, Cesar Berrospi, Thomas Brunschwiler, and Thorsten Wagener

Floods, droughts, and rainfall-induced landslides are hydro-geomorphic hazards that affect millions of people every year. These hazards are therefore heavily researched topics with several hundred thousand articles published. The large number of published articles means identifying existing gaps is a challenge, especially regarding research specific to local risk conditions and impacts. How well does hydro-geomorphic hazard research cover heavily impacted regions, different hydro-climatic processes, or relevant socio-economic aspects? In this work, we use natural language processing to search a database of 100 million abstracts for mentions of floods, droughts, and landslides. We annotate all hazards and location mentions and geolocate each study via Nominatim. We use this information to create global gridded research densities for the three hazards based on all study locations from 293,156 abstracts. We then compare research density to environmental, socio-economic, and disaster impact data. The global distribution of research is heavily influenced by human activity, national wealth, data availability, and population distribution. Countries that have been heavily impacted by hydro-geomorphic hazards in the past have a higher research density. However, this relationship strongly depends on country wealth. In low-income countries 100 times more people need to be affected before a comparable research density to high-income countries is reached. This disparity needs to be addressed to reduce disaster impact and adapt to changing conditions in the future. We here give guidance for which regions and hydro-climatic conditions an increased research focus on hydro-geomorphic hazards is most urgent.

How to cite: Stein, L., Mukkavilli, S. K., Pfitzmann, B. M., Staar, P. W. J., Ozturk, U., Berrospi, C., Brunschwiler, T., and Wagener, T.: Identifying global biases in hydro-hazard research by mining the scientific literature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8752, https://doi.org/10.5194/egusphere-egu24-8752, 2024.

The Central American Dry Corridor (CADC) spans Guatemala, Honduras, El Salvador, Costa Rica, and Nicaragua. Over half of the population in this region is engaged in agricultural activities, with more than 73% of the rural population living in poverty, and 7.1 million people experiencing severe food insecurity. The increasingly frequent droughts exacerbate the challenges faced by agricultural production in this area. Long-term series of agricultural drought mapping can assist agricultural planners in minimizing the impact of drought on production. Based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) spanning from 2001 to 2021, this study will utilize the Vegetation Health Index to map agricultural drought in CADC at monthly, seasonal, and interannual scales. Multi-temporal agricultural drought mapping will reveal the spatiotemporal distribution patterns of agricultural drought in CADC over the past 20 years. Additionally, the study will employ the Mann-Kendall test and Sens' slope estimator to simulate the changing trends of agricultural drought, aiming to identify regions where agricultural drought is worsening.

How to cite: Qiu, J. and Tarolli, P.: Long-term agricultural drought monitoring in the Central America Dry Corridor using Vegetation Health Index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9901, https://doi.org/10.5194/egusphere-egu24-9901, 2024.

EGU24-10678 | ECS | Orals | NH9.2

Leveraging Multi-Sector Needs Assessments to Assess Dynamic Social Vulnerability: A Methodological Exploration 

Jean-Baptiste Bove, Silvia De Angeli, Lorenzo Massucchielli, and Davide Miozzo

In the context of escalating climate change impacts, conflicts, urbanization, and the complex interplay between ecological, physical, human, and technological systems, this research explores an innovative methodology for the assessment of dynamic social vulnerability for disaster risk assessment and management by exploiting Multi-Sector Needs Assessments (MSNA) data. Current frameworks for assessing social vulnerability frequently exhibit a hazard-specific focus and are not often generalizable because of differences in methodologies or limits in data availability. Moreover, they often fail to incorporate the dynamic nature of vulnerability, and neglect the inclusion of critical context-specific elements. The proposed research addresses these limitations by exploring the innovative application of MSNAs conducted by humanitarian organizations for assessing dynamic social vulnerability. MSNAs, by providing data across various sectors and geospatial scales, offer an underutilized resource for understanding the multi-dimensional and dynamic aspects of vulnerability in crisis-affected contexts. The use of MSNA data, which includes repeated assessments over time and disaggregation by different population groups and geographic levels, presents new opportunities to understand how and why social vulnerability can change over time. This research aims to address the methodological challenges of data accessibility,  standardization, comparability, and representation of socio-economic factors by proposing an innovative way of constructing a social vulnerability index based on MSNA data and indicators that can capture and reflect changes in social vulnerability over time. This approach will be demonstrated through a case study, providing a practical illustration of how dynamic social vulnerability can be effectively measured and analyzed using MSNA data. The research will also highlight how the methodology can be replicated to any other country for which MSNA data is available. By bridging the gap between crisis-driven needs assessments and long-term social vulnerability analysis, this study contributes to more informed, context-specific, and timely strategies in disaster risk management, humanitarian response and policy-making. The findings are expected to enhance the understanding of social vulnerability in varied contexts, highlighting the dynamic nature of vulnerability from a multi-risk and multi-hazard perspective.

How to cite: Bove, J.-B., De Angeli, S., Massucchielli, L., and Miozzo, D.: Leveraging Multi-Sector Needs Assessments to Assess Dynamic Social Vulnerability: A Methodological Exploration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10678, https://doi.org/10.5194/egusphere-egu24-10678, 2024.

EGU24-12391 | ECS | Orals | NH9.2

Developing a micro-scale population exposure model: insights from the Italian context 

Sara Rrokaj, Daniela Molinari, Francesco Ballio, Alice Gallazzi, Stefano Annis, Maria Grazia Badas, Anna Rita Scorzini, and Marco Zazzeri

The increasing impacts of climate change and urbanization underscore the critical importance of micro-scale population data for enhancing natural risk management and emergency preparedness. Access to high resolution population information enables better correlation with the spatial variability of hazards, leading to more accurate damage estimations. However, such data are typically available at macro and meso-scales. In the case of Italy, for example, population data from the National Institute of Statistics (ISTAT) is provided at the census tract scale (meso-scale) for the entire country, despite the uneven distribution of residents within these areas. This study focuses on developing an exposure model for resident population in Italy at a finer spatial resolution than the currently available data. The model uses point data of resident population in the Emilia Romagna region, relating this information to residential building footprint area and volume, as well as land use features. The analysis reveals a notable portion of vacant residential buildings, with approximately 30% of Italian residential buildings reported as uninhabited by ISTAT. The study suggests that incorporating information on the type of residential buildings (main, secondary, or vacant) could significantly enhance the model's performance, especially in tourist-centric cities characterized by a high share of holiday houses. Additionally, the results of this study highlight the need for public entities to invest efforts in the development of a reliable and comprehensive spatial database that includes information on permanently inhabited properties.

How to cite: Rrokaj, S., Molinari, D., Ballio, F., Gallazzi, A., Annis, S., Badas, M. G., Scorzini, A. R., and Zazzeri, M.: Developing a micro-scale population exposure model: insights from the Italian context, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12391, https://doi.org/10.5194/egusphere-egu24-12391, 2024.

EGU24-12963 | ECS | Orals | NH9.2

Systemic human-biosphere-atmosphere monitoring and diagnostics 

Wantong Li, Gregory Duveiller, Fabian Gans, Dorothea Frank, and Markus Reichstein

Here we propose a planetary health diagnostic framework, which aims to track, understand, and characterize the Earth system during the onset and progression of both chronic change (such as climate change) and abrupt disruptions (stemming from climate extremes and socio-economic shocks). However, monitoring a single component of the Earth system to guide policy, but ignoring other essential components, could lead to misleading diagnostics and maladaptation. To gain insights into the integration of climate, biosphere, and society, we apply an interactive dimensionality reduction to the annual variability of multi-stream global data from 2003-2022, including data representing the biosphere and climate combined with national socio-economic indicators.

We find that the interactions between biosphere, atmosphere and socio-economy can be captured by three principal axes, which cumulatively explain 17.3%, 22.8% and 24.5% of the variability condensed by non-interactive dimensionality reduction in each individual domain, respectively. First principal components are related to long-term trends in global warming, land surface dimming, and socio-technical development, while the second and third components are related to changes of other processes under climate and biospheric extremes and socioeconomic shocks. These processes include vegetation dynamics, land surface and atmospheric water demand, life and environmental inequality. We find distinct trajectories across countries with the most distinct cluster is Middle East and North Africa that exhibit climate extremes in 2010 and 2016, socio-financial shocks between 2010-2012 and COVID-19 in 2020. This study advocates for a data-driven paradigm to jointly monitor the recent trajectories of the biosphere, atmosphere, and society that could provide a better understanding and early warning of the state of the Earth system for human well-being.

How to cite: Li, W., Duveiller, G., Gans, F., Frank, D., and Reichstein, M.: Systemic human-biosphere-atmosphere monitoring and diagnostics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12963, https://doi.org/10.5194/egusphere-egu24-12963, 2024.

EGU24-13968 | Posters virtual | NH9.2

Flood Severity, Socio-Economic Impacts, and Elevation Strategy Effectiveness in a Subset of Louisiana Post-Hurricanes Katrina and Rita 

Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland, and Fuad Hasan

FEMA's Hazard Mitigation Grant Program (HMGP) assisted survivors of Hurricanes Katrina and Rita, necessitating a 25% homeowner contribution for post-disaster home elevation. The federal Community Development Block Grant Disaster Recovery (CDBG-DR) program allocated $13.4 billion to Louisiana, offering $30K grants per home, aligning with HMGP needs. This study focused on elevated residential homes in a subset of Louisiana's housing data, aiming to understand the intersection of flood risk when disaggregated by frequency, vulnerable populations, and mitigation costs.

The analysis investigating the correlation between flood frequency/severity and variables such as race and ethnicity, and socioeconomic status, exploring their interconnections. Subsequently, we explored how flood risk changed both pre- and post-implementation of elevation strategies across various return periods, aiming to determine the proportional attribution of the total AAL to these different periods. Additionally, it examined the comparative flood risk before and after elevation strategies across diverse socioeconomic statuses. Finally, it analyzed the absolute benefits of elevation strategies, particularly the avoided AAL, compared with investment values and socioeconomic statuses.

The result of this study indicates that Poverty levels remain consistent across different return periods, a notable increase in Non-white population percentages with longer return periods, and a peak in Renters' percentage at floods with a return period of ≥200 years. It’s demonstrated that a substantial percentage of the total AAL is attributed to less frequent but more severe events—those occurring with return periods between 100 and 500 years, as well as those with return periods greater than 500-year. The results show inconsistencies in the Avoided AAL values across different investment levels suggest that the relationship between investment in elevation costs and Avoided AAL is not directly proportional.

The study results provide multifaceted insights, aiding in the identification of vulnerable communities and offering guidance for resource allocation decisions, and demonstrating the impact of elevation strategies. The economic analysis enhances understanding of federal mitigation investments' cost-effectiveness across diverse socio-economic statuses.

 

How to cite: Al Assi, A., Mostafiz, R. B., Friedland, C. J., and Hasan, F.: Flood Severity, Socio-Economic Impacts, and Elevation Strategy Effectiveness in a Subset of Louisiana Post-Hurricanes Katrina and Rita, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13968, https://doi.org/10.5194/egusphere-egu24-13968, 2024.

EGU24-14637 | Posters on site | NH9.2

A systems approach for holistic resilience building 

Alison Sneddon

Resilience for Social Systems (R4S) is an approach to analyse the resilience of socioeconomic systems. Societies are made up of socio-economic systems which service the needs of their populations, and addressing recurrent crises and effectively building resilience requires an integrated systems approach. Where these systems are fragile and large portions of the population are socially or economically marginalized, communities are highly susceptible to external shocks and stresses; coordination among stakeholders to strengthen these systems will ultimately improve resilience and lead to resilient and inclusive development.

The R4S approach to resilience helps to understand how various system components (stakeholders, resources, regulations) interact and interconnect, as well as assessing the potential impacts from risk scenarios. In other words, when applying the R4S Approach to build resilience, the user can anticipate better how natural hazards can trigger economic shocks, how conflicts can leave people more exposed to additional shocks or stresses (e.g., an outbreak of cholera can be triggered when water, sanitation and hygiene systems are destroyed or become inaccessible), and how long-term stresses such as environmental degradation can lower agricultural productivity, weakening food security and income levels, and impacting a household’s ability to pay for health care or education.

Understanding these dynamics is critical to deliver better programming that addresses root causes of constraints rather than symptoms alone. The R4S Approach is based on best practice in Systems Thinking, Network Theory, Scenario Thinking, Social and Behaviour Change, Inclusion and Resilience approaches and provides a logical step by step process for assessing resilience of socio-economic systems.

This presentation will provide an overview of the R4S, the innovations in the assessment of complex and interlinked vulnerabilities it provides, and practical examples drawn from GOAL’s experience of conducting the assessment and implementing resilience-building strategies based on the needs and opportunities identified.

How to cite: Sneddon, A.: A systems approach for holistic resilience building, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14637, https://doi.org/10.5194/egusphere-egu24-14637, 2024.

EGU24-15543 | ECS | Orals | NH9.2 | Highlight

Collection, Standardization and Attribution of Robust Disaster Event Information — A Demonstrator of a National Event-Based Loss and Damage Database in Austria 

Dominik Imgrüth, Katharina Enigl, Matthias Themessl, and Stefan Kienberger

Loss and damage databases are essential tools for disaster risk management in order to make informed decisions. However, even in data-rich countries such as Austria, there has been no consistent and curated multi-hazard database to date. Based on the demands of the United Nations, the European Union and national requirements for monitoring and managing the effects of disasters, the CESARE project (funded by KIRAS/FFG; project end 02/2022) designed and developed a demonstrator for a consistent national event-based damage database. This demonstrator enables event identification, loss and damage monitoring and assessment according to international standards and offers the possibility of disaster forensics. The CESARE system is based on existing data collected by administrations as well as federal authorities which are consolidated according to a common data model. By this means, the primary data and the data collection procedures are not affected and a sustainable exchange of data is made possible. The demonstrator currently focuses on two Austrian federal states, three hazard types - floods, storms and mass movements - and the period between 2005 and 2018. By analysing over 140,000 individual event descriptions, we demonstrated that - despite some limitations in retrospective data harmonisation - the implementation of an event-based national damage database is feasible and offers considerable added value compared to the use of individual data records. The demonstrator will in future substantially support quantitative analysis in the context of the national risk assessment, national UNDRR-Sendai monitoring and disaster risk management at federal level by providing the best possible harmonised damage information, tailored indicators and statistics as well as maps on the impact of hazards at municipal level. The CESARE system is currently being rolled out operationally as well as extended to other hazard categories and the remaining provinces of Austria. With its final implementation, CESARE will provide the most complete event and damage database in Austria.

How to cite: Imgrüth, D., Enigl, K., Themessl, M., and Kienberger, S.: Collection, Standardization and Attribution of Robust Disaster Event Information — A Demonstrator of a National Event-Based Loss and Damage Database in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15543, https://doi.org/10.5194/egusphere-egu24-15543, 2024.

EGU24-18132 | Posters on site | NH9.2

Revealing Environmental Threats: Harmonizing Indigenous Narratives with Geomorphic Hazard Thematic Maps for Community Awareness 

Sheng-Chi Lin, Su-Min Shen, Sendo Wang, Mu-Ti Yua, Si-Chin Lin, and Chih-Hsin Chang

From the perspective of natural disaster prevention, larger-scale and higher-intensity geomorphic events often have longer recurrence intervals. The impact of these events on a region is frequently underestimated unless residents have experienced them firsthand. Consequently, the success of promoting self-reliant disaster-prepared communities by the government heavily relies on the experiences of the affected population. In this context, our study integrates government cartographic data and interprets the geomorphic evidence preserved in the landscape.

We conducted in-depth interviews with elders from indigenous tribes, leveraging their rich storytelling tradition and local residents' experiences to collect observations of environmental changes, past disaster experiences, and ancestral stories. The spirit of storytelling is incorporated into the map user manual, emphasizing a place-based approach. Using the devastating impact of Typhoon Morakot in 2009 on the Tjalja'avus Tribe in southern Taiwan as a case study, we produced a geomorphological hazard thematic map of the tribe. This map utilized national environmental mapping imagery, including landslide records, large-scale landslide-prone areas, potential debris flow streams, and high-resolution digital elevation models created by unmanned aerial vehicles LiDAR.

Through a combination of multi-temporal data visuals, we highlighted recent (within the last five years) highly active landslide locations, emphasizing dynamic geomorphic features. In the context of environmental awareness and risk communication between the government and local communities, we structured the map user manual to revolve around the narrative axis of visible terrain features in the tribal landscape and experiences or stories related to soil and rock disasters. This approach allows individuals to comprehend the geomorphic influences leading to disasters in their communities, facilitating collaboration between the government and community builders. Ultimately, our initiative aims to achieve environmental management and disaster prevention goals within indigenous communities.

How to cite: Lin, S.-C., Shen, S.-M., Wang, S., Yua, M.-T., Lin, S.-C., and Chang, C.-H.: Revealing Environmental Threats: Harmonizing Indigenous Narratives with Geomorphic Hazard Thematic Maps for Community Awareness, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18132, https://doi.org/10.5194/egusphere-egu24-18132, 2024.

EGU24-18238 | ECS | Orals | NH9.2 | Highlight

Risk Tipping Points in an Interconnected World 

Caitlyn Eberle, Jack O'Connor, Liliana Narvaez, Melisa Mena-Benavides, and Zita Sebesvari

The convergence of multiple societal and ecological challenges threatens to push us into an uncertain, risky future. Our critical life-supporting systems, such as the human climate niche, hydrological cycles, natural ecosystems, food production, knowledge systems, and risk management tools, are all fundamentally challenged. While these systems have been continually reshaped throughout human history, the speed of change and the simultaneous changes occurring today are unprecedented. Our research shows how we are teetering on the precipice of multiple tipping points that can trigger abrupt and often irreversible changes to the systems we rely upon.

Our research provides a conceptual definition of risk tipping points as a new way to think about the risks we face and illustrates examples of how the concept can be applied. While climate tipping points refer to tipping elements of Earth systems, such as hydrological cycles or climate patterns, risk tipping points concern the socioecological systems dependent on them and when they stop being able to buffer risk and provide their expected functions. We discuss six prominent examples of risks facing these socioecological systems, such as groundwater depletion and space debris, and identify conceptual tipping points for each of them.

Furthermore, our research discusses each of these risk tipping points within a context of interconnectivity. We analyze how similar human behaviors and values are at the root of multiple risk tipping points, putting pressure on multiple systems simultaneously. Since none of these systems are isolated from each other, when one system passes a risk tipping point, it increases the overall risk across systems and may actually accelerate tipping in another system. Feedback loops between systems can amplify the impacts of risks and can create self-reinforcing dynamics that increase the speed of change. The effects of these manifesting risks may accumulate over time, causing multiple risk tipping points to overlap and increase risk even further.

Finally, our research demonstrates that any attempt to reduce risk in these systems must acknowledge and understand these underlying pressures and their interconnectivity. Actions that affect one system will likely have consequences on another, so integrated and informed solutions are necessary to avoid negative consequences. This also means that interconnectivity can be used as an advantage through solutions that provide co-benefits to address risk tipping points in multiple systems at once. Interconnected risks require interconnected solutions to ensure a safe and sustainable future for all.

How to cite: Eberle, C., O'Connor, J., Narvaez, L., Mena-Benavides, M., and Sebesvari, Z.: Risk Tipping Points in an Interconnected World, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18238, https://doi.org/10.5194/egusphere-egu24-18238, 2024.

EGU24-18933 | ECS | Posters on site | NH9.2

A holistic examination of Disaster Risk Management in the context of volcanic risk in the Canary Islands 

María García-Vaquero, Sara García-González, Noemi Padrón-Fumero, Julia Crummy, Tamara Febles-Arévalo, and Jaime Díaz_Pacheco

Understanding the complexity of past chain events in depth and learning from them to improve
decision-making in a dynamic context can be challenging. Although efforts have been made to
address these challenges, further research is needed. Storylines have proven to be a valuable
qualitative tool not only for describing multi-hazard scenarios, understanding the system and
the interrelationships between different elements, but also for improving resilience by taking
into account lessons learned throughout the process.


The 2021 La Palma volcanic eruption, with its enduring aftermath characterised by atmospheric
gas emissions in one of the island's prime tourist locales, exemplifies the intricate challenges in
decision-making for planning, procedural execution, and organisational management. This
event highlights the extensive and profound impacts of such dynamic risks, underscoring the
need for adaptable and robust strategies in risk management and response. Our study aims to
provide a comprehensive understanding of the whole volcanic disaster in detail by integrating
the different dimensions (multi-hazard, multi-risk and systemic impacts) into the disaster risk
reduction cycle (prevention and preparedness, response and recovery). This approach provides
a holistic and proactive approach and allows for an assessment of the impact and
consequences of the decision making process in the Canary Islands at each stage over time. For
this purpose, a 20-year timeline will be used, starting in 2004 when the first seismic swarm
indicated a possible volcanic eruption in the island of Tenerife.


This research uncovers a significant shortfall in risk planning across all stages of the disaster
reduction cycle on the islands, noting a disproportionate emphasis on administrative
coordination during emergencies. The absence of preemptive measures in land-use planning,
especially in areas highly vulnerable to exposure, exacerbates the complexity of post-eruption
recovery. By thoroughly examining the decision-making processes, planning strategies, and
organisational procedures, this study aims to distil key lessons from recent experiences. Such
an endeavour enhances our comprehension of the complex interplay between decisions and
risks, providing critical insights for bolstering resilience against volcanic disasters.

How to cite: García-Vaquero, M., García-González, S., Padrón-Fumero, N., Crummy, J., Febles-Arévalo, T., and Díaz_Pacheco, J.: A holistic examination of Disaster Risk Management in the context of volcanic risk in the Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18933, https://doi.org/10.5194/egusphere-egu24-18933, 2024.

EGU24-19054 | ECS | Posters on site | NH9.2

Agricultural Drought Case Study in South Korea: Selection of Rural Specialization Districts based on Principal Component Analysis 

Hyochan Kim, Hoyoung Cha, Jongjin Baik, Kihong Park, and Changhyun Jun

Recently, the frequency and severity of droughts have gradually increased due to extreme weather events and global warming. As the demand for drought management increases, field surveys and water supply are actively conducted in many countries. Given that such drought assessment and support require the consumption of labor and financial resources, the prioritization of essential agricultural areas has become a major topic for efficient decision-making in drought relief. In this study, we proposed a Principal Component Analysis (PCA) for selecting rural specialization districts across the 162 administrative regions of South Korea. Additionally, we aimed to investigate real cases of agricultural drought occurred in these regions by utilizing the survey of water supply measures derived from Ministry of Agriculture, Food and Rural Affairs. The research data comprised seven agricultural specialization factors, exemplified by agricultural workforce and infrastructure. First, we implemented singular decomposition method included in PCA process to represent the comprehensive trends of the agricultural specialization factors with maximum reflection. High value of principal component scores (PCS) estimated from PCA was interpreted as regions with high agricultural relevance. Lastly, the PCS were classified into different levels, defining top-ranking regions as rural specialization districts. Based on agricultural drought case studies from 2018 to 2021, it is expected that finding relative damage-prone areas and establishing appropriate drought responses will be feasible.

Keywords: Principal Component Analysis, Rural Specialization Districts, Agricultural Specialization Factors, Principal Components Score

Acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00250239) and this research was supported by Korea Environment Industry & Technology Institute (KEITI) through Water Management Innovation Program for Drought (RS-2022-KE002032) funded by Korea Ministry of Environment.

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: Kim, H., Cha, H., Baik, J., Park, K., and Jun, C.: Agricultural Drought Case Study in South Korea: Selection of Rural Specialization Districts based on Principal Component Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19054, https://doi.org/10.5194/egusphere-egu24-19054, 2024.

EGU24-19940 * | ECS | Orals | NH9.2 | Highlight

A global database of natural hazards impacts reported in the scientific literature 

Taís Maria Nunes Carvalho, Jakob Zscheischler, Christian Kuhlicke, and Mariana Madruga de Brito

The increased frequency and magnitude of natural hazards might significantly increase social, economic, and health impacts on society in the next decades. Existing studies and databases of natural hazard impacts have several limitations, such as (1) a low level of detail on how people were affected; (2) an underestimation of the impacts; (3) a limited geographical range; and (4) a lack of information on the source of the data. However, scientific publications, reports, and handbooks compose a large data repository that can provide valuable and trustworthy information on natural hazards. We are building a global database on the impacts of natural hazards that have been documented since 1950 in the scientific literature. We mapped global research on climatological, hydrological, and meteorological extremes, such as heatwaves and floods. We retrieved over 40 thousand full-text open-access papers from ScienceDirect and Pubmed. Documents were coded according to (i) relevance: if the study describes impacts from a natural hazard, (ii) hazard class: single or multiple hazards, and (iii) event assessment: specific or multiple climate-related events. A randomly selected sample of the documents was manually labeled and a classification model was trained to classify the remaining papers. We further developed an annotation scheme for marking information on climate-related hazards in scientific publications, such as the date and location of hazard and their impacts. The inter-annotator agreement analysis shows the complexity of this task and the high annotation quality in our corpus. This work fills a critical gap in information extraction tasks within the natural hazards research domain, providing a robust foundation for future studies and analysis.

How to cite: Nunes Carvalho, T. M., Zscheischler, J., Kuhlicke, C., and Madruga de Brito, M.: A global database of natural hazards impacts reported in the scientific literature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19940, https://doi.org/10.5194/egusphere-egu24-19940, 2024.

Landslides cause severe impacts on society, infrastructure, and the environment globally, and their occurrence in some regions is expected to rise due to climate change. Although the cumulative impacts of landslides do not reach the level of earthquakes or floods, their disperse occurrence in space and difficult prediction pose a fundamental challenge for landslide disaster risk reduction effort. Clearly, accurate information is needed both for understanding spatiotemporal occurrence of landslides and their social impacts and responses held by societies. Documentary data are among the key sources that enable compilation of regional landslide databases, allow to quantify the landslide impacts and describe both quantitatively and qualitatively causal chains leading to increased landslide risk and the societal responses to landslide events. In this respect, the documentary data fill the time gap between the landslide occurrence in the past environments studied by proxy data, and the present-day landslides, for which different monitoring and mapping techniques may be used. Over the last decades, important progress has been made in employing various documentary data for landslide research, and extending empirical evidence about advantages and limitations is available thanks to case studies from different environmental and institutional settings. The synthesis of this progress that would guide further research is missing though. The overall goal of this paper is to broaden the perspective on the use of documentary data in historical landslide research, which has so far too much concentrated around the landslide inventories. To do so, we present a scoping literature review with three main objectives. First, we present a classification of both quantitative and qualitative approaches and related research questions in historical landslide research, linking them to key challenges in landslide disaster risk reduction. Second, we review the types and content of available documentary data sources with special attention paid to sources that have been underresearched so far. Finally, we review the quantitative and qualitative methods used to analyse the content of documentary data. While doing so, we draw also from comparative evidence in historical climatology and hydrology in order to point to methods that may hold a potential, but have not been validated in landslide research yet. The paper concludes with identifying challenges and pathways for future research.  

How to cite: Raška, P.: Recent progress in the use of documentary data in landslide research: a review of approaches, sources, and methods , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20289, https://doi.org/10.5194/egusphere-egu24-20289, 2024.

EGU24-1844 | ECS | Orals | BG3.26

Tracking shifts of mountain forest ecotones in aerial imagery with deep learning 

Michael Maroschek, Rupert Seidl, Cornelius Senf, and Werner Rammer

Forest ecosystems are sensitive to global change; especially at the ecotones we expect high sensitivity to changes in climate, disturbance regimes or land use. For instance, the treeline ecotone is expected to move upward in elevation with global warming. The advent of machine learning, specifically computer vision, provides powerful tools for monitoring ecotones across large spatial scales using remote sensing data. In this study, we focused on the spatiotemporal development of ecotones bracketing the subalpine forest belt (i.e., the upper boundary, formed by the treeline, and the ecotone to montane forests as the lower boundary) in a protected forest landscape in the European Alps. Our objectives were threefold: First, we aimed to identify trees and shrubs on historic and recent orthophotos using deep learning, with special attention to integrating multiple sensor types into one computer vision framework. Second, based on the computer vision inference, we sought to map the a) treeline and b) montane-subalpine ecotone. Third, we aimed to describe the spatiotemporal changes occurring in both ecotones.

We based our analysis on historic and recent aerial images of Berchtesgaden National Park in the Northern Alps, covering roughly 210 km² in nine time steps from 1953 to 2020. The images were captured through both analog (panchromatic and color infrared) and digital (color infrared, RGB) sensors. To generate training data for deep learning, we manually interpreted randomly distributed 0.5 ha segments across all time steps, resulting in over 110,000 annotations of coniferous and broadleaved trees, shrubs, and standing dead trees. We tested different instance segmentation frameworks and selected the best performing model architecture to create wall-to-wall tree maps for each time step. Using structure and composition of the tree maps, we spatially delineated the ecotones and tracked their changes over time.

We did not find a spatially consistent pattern of ecotones shifting upwards, however we were able to identify areas of change and stability linked to climate, topography, disturbances and land use. We observed remarkable local upward shifts in ecotones, particularly of the montane-subalpine ecotone, which shifted up to five times faster than the treeline. In general, we found that subalpine forests, situated between the two ecotones, decreased in area because of an upward shift of its lower boundary, and exhibited an increase in crown cover over time.

Changes in these ecotones and related vegetation zones pose challenges to conservation, restoration and management. Our approach can help to address these challenges, e.g., in the combination with habitat modelling.

How to cite: Maroschek, M., Seidl, R., Senf, C., and Rammer, W.: Tracking shifts of mountain forest ecotones in aerial imagery with deep learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1844, https://doi.org/10.5194/egusphere-egu24-1844, 2024.

Green alder (Alnus alnobetula (Ehrh.) K. Koch = Alnus viridis (Chaix) DC), a tall multi-stemmed deciduous shrub, is widespread at high elevations in the Central European Alps especially within avalanche slide path, screes and steep, north-facing slopes with high water availability. The ascending growth of stems frequently leads to eccentric growth, discontinuous rings and elliptical shape of annual rings making development of representative ring-width time series, necessary to determine climate forcing of radial growth and long-term growth trends, a challenge. Therefore, the focus of this study was to assess growth variability among radii of one shoot (n=4 radii), among shoots belonging to one stock (n=20 shoots per stock) and among stocks exposed to different site conditions (n=3 sites). Stem discs were sampled within the treeline ecotone (c. 2150 m asl) on Mt. Patscherkofel (Tyrol, Austria), and annual increments were measured along 188 radii. Variability in inter-annual agreement among ring-width series was evaluated by applying dendrochronological techniques, i.e., the parameters (i) percentage of parallel variation (“Gleichläufigkeit”, Glk) and (ii) the correlation coefficient r, adjusted for the amount of overlap (tBP-score) were determined. Variation in intra-annual dynamics of radial growth among shoots belonging to different stocks was evaluated by mounting diameter dendrometers (n=6). Results revealed a high agreement in ring-width variation among radii of one shoot (Glk: P<0.001; tBP-score>5), among shoots of one stock (Glk: P<0.05; tBP-score>4) and among stocks from different sites (Glk: P<0.05; mean tBP-score=4.5). Dendrometer records gathered from shoots belonging to different stocks also revealed a high agreement in intra-annual radial growth dynamics, which started in 2023 at the end of June and already terminated in early August. In contrast to this, a high variability in both absolute growth rates and long-term growth trends was found at selected study sites. We attribute our findings to the pronounced limitation of radial stem growth in Alnus alnobetula by climate factors (mainly summer temperature and winter precipitation) leading to a high agreement among ring width series developed from different radii, shoots and individuals. On the other hand, differences in compressive and tensile forces and variation in microsite conditions determine absolute growth rates and long-term growth trends.

This research was funded by the Austrian Science Fund (FWF), P34706-B.

How to cite: Oberhuber, W., Gruber, A., and Wieser, G.: Climate factors control inter-annual variability of radial growth, while microsite conditions affect absolute growth and long-term growth trend in the multi-stemmed shrub Alnus alnobetula at the alpine treeline, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2339, https://doi.org/10.5194/egusphere-egu24-2339, 2024.

EGU24-4049 | ECS | Orals | BG3.26

Patterns of Treeline Rise with Climate Change Across Western North America from the 1980s to Present 

Joanna Corimanya, Daniel Jimenez-Garcia, and A. Townsend Peterson

Previous research has shown that (1) treelines are shifting upward in elevation on high mountain peaks worldwide, and (2) the rate of the upward shift appears to have increased markedly in recent decades. Because treeline shift is a process manifested over broad scales of space and time, a particular challenge has been that of obtaining a broad-enough view of patterns of treeline shift to permit inferences about geographic and environmental patterns. What is more, intensive studies of treelines have been concentrated in North Temperate regions, such that little information is available about treeline shift patterns in the Tropics. We have attempted to broaden this viewpoint by means of analysis of long  time series of vegetation indices derived from Landsat imagery obtained and analyzed via Google Earth Engine for the 1980s to present. We sampled vegetation indices at points spaced every 100 m along 100 km transects radiating out from 120 high peaks across western North America (Canada to Central America); considerable data preparation was necessary, including ending transects <2 km into closed forest, identifying current treelines via reference to Google Earth imagery, and consideration only of up to <1 km above treeline. Patterns that emerged were—as is well known—that treelines are generally higher at lower latitudes, but also that magnitude of treeline shifts is nonrandomly distributed with respect to latitude, location with respect to coastlines, and size of the mountain mass within which the peak is located. Although analyses are continuing at the time of preparation of this abstract, this analysis offers a broadscale view of treeline shifts over a period of almost 40 years, and over a geographic span of more than 40° of latitude.

How to cite: Corimanya, J., Jimenez-Garcia, D., and Peterson, A. T.: Patterns of Treeline Rise with Climate Change Across Western North America from the 1980s to Present, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4049, https://doi.org/10.5194/egusphere-egu24-4049, 2024.

EGU24-5709 | Posters on site | BG3.26

Dynamics of alpine treeline in the High Tatra Mts., Slovakia 

Svetlana Varsova, Veronika Lukasova, Milan Onderka, and Dusan Bilcik

Global warming affects the climatic conditions in the mountain environments. The climate of the alpine treeline ecotone (ATE) in the High Tatra Mts. is represented by unique conventional long-term climatological series from Skalnaté Pleso Observatory (49°11'21.9” N; 20°14'02.7” E). When considering the two last normal periods (1961-1990 and 1991-2020), the average air temperature in ATE increased by  1.1 °C. In this work, we analysed the altitudinal shift of the boundary 6°C isotherm, which represents the minimum temperature requirements for the growth and reproduction of tree vegetation. To determine the altitude of the cold treeline limit, i.e. upper limit of ATE, we used climate data from Skalnaté Pleso Observatory (1,778 m a.s.l.) and the near top meteorological station Lomnicky štít (2,634 m a.s.l.).  We found that over the analysed period 1951-2020, the limiting isotherm moved upwards from the level of 1,950 m a.s.l. to 2,200 m a.s.l.. Preliminary field monitoring and mapping indicated the colonisation of the dominant subalpine vascular species Pinus mugo Tura (mountain pine) into alpine summits. We identified young individuals or small groups of mountain pine at altitudes between 2,000-2,200 m a.s.l., which is consistent with the assumption of vertical extension of low tree vegetation due to positive changes in ambient thermal conditions. The warming of the alpine tree line ecotone may lead to a gradual reduction and eventual disappearance of montane species due to their strict ecological specialisation. The replacement of the populations of cold-adapted alpine species by those profiting from the warmer climate may cause a decline in the ecosystem's biodiversity. Therefore, further research will be focused on verification of the climate-related shift of the boundary line for the growth of mountain pine at the ATE zone in the highest mountain range of the central-eastern region of Europe.

How to cite: Varsova, S., Lukasova, V., Onderka, M., and Bilcik, D.: Dynamics of alpine treeline in the High Tatra Mts., Slovakia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5709, https://doi.org/10.5194/egusphere-egu24-5709, 2024.

EGU24-9480 | ECS | Orals | BG3.26

Linking deep learning-based forest cover maps to treeline spatio-temporal patterns 

Thiên-Anh Nguyen, Marc Rußwurm, Gaston Lenczner, and Devis Tuia

Over the last decades, the position of the upper treeline in the Swiss Alps has been highly affected by drivers such as climate change and land use change interacting at various spatial and temporal scales. To better understand these interactions, it is necessary to quantify treeline dynamics over large areas at high spatial resolution and over long time scales. This can be decomposed into three tasks: mapping forest cover, delineating the treeline, and comparing the treeline position through time.

We leverage archives of optical aerial imagery acquired over the Swiss Alps to map forest cover. These images constitute a large dataset of time series of 12 to 20 ortho-rectified aerial images at 1 m spatial resolution acquired throughout the time period 1946-2020. We have developed a deep learning-based method to automatically extract multi-temporal forest masks from these aerial images (under review).

We then explore how treeline dynamics can be characterized using these forest cover maps. More specifically, we look at designing a spatio-temporal processing pipeline that implements widely used definitions of the treeline and treeline displacement, while being robust to potential errors in our deep learning-generated maps, such as noise caused by differing sensors and imaging conditions. We find that through a series of pixel-based processing steps, based solely on the generated forest cover maps and a Digital Elevation Model, we manage to 1. delineate the treeline at a chosen spatial scale and 2. measure the elevational treeline shift between two dates. The flexible choice of the spatial scale enables multi-scale analysis and comparison with existing treeline shift measurements derived from different data sources and methods.

We hope that this automatic and flexible spatial analysis pipeline can link deep learning-based forest cover maps to ecologically relevant variables in a way that can foster the understanding of treeline dynamics.

How to cite: Nguyen, T.-A., Rußwurm, M., Lenczner, G., and Tuia, D.: Linking deep learning-based forest cover maps to treeline spatio-temporal patterns, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9480, https://doi.org/10.5194/egusphere-egu24-9480, 2024.

EGU24-10161 | Orals | BG3.26

Warming-induced phenological mismatch between trees and shrubs explains high-elevation forest expansion 

Eryuan Liang, Xiaoxia Li, J. Julio Camarero, Sergio Rossi, Jingtian Zhang, Haifeng Zhu, Yongshuo H. Fu, Jian Sun, Tao Wang, Shilong Piao, and Josep Peñuelas

 Despite the importance of species interaction in modulating the range shifts of plants, little is known about the responses of coexisting life forms to a warmer climate. Here, we combine long-term monitoring of cambial phenology in sympatric trees and shrubs at two treelines of the Tibetan Plateau, with a meta-analysis of ring-width series from 344 shrubs and 575 trees paired across 11 alpine treelines in the Northern Hemisphere. Under a spring warming of + 1°C, xylem resumption advances by 2–4 days in trees, but delays by 3–8 days in shrubs. The divergent phenological response to warming was due to shrubs being 3.2 times more sensitive than trees to chilling accumulation. Warmer winters increased the thermal requirement for cambial reactivation in shrubs, leading to a delayed response to warmer springs. Our meta-analysis confirmed such a mechanism across continental scales. The warming-induced phenological mismatch may give a competitive advantage to trees over shrubs, which would provide a new explanation for increasing alpine treeline shifts under the context of climate change.

How to cite: Liang, E., Li, X., Camarero, J. J., Rossi, S., Zhang, J., Zhu, H., Fu, Y. H., Sun, J., Wang, T., Piao, S., and Peñuelas, J.: Warming-induced phenological mismatch between trees and shrubs explains high-elevation forest expansion, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10161, https://doi.org/10.5194/egusphere-egu24-10161, 2024.

EGU24-10168 | ECS | Posters on site | BG3.26

Assessing vegetation dynamics in global high-mountain ecotones 

Linqing Zou, Gabriela Schaepman-Strub, Feng Tian, and Tianchen Liang

As the climate warms, vegetation within treeline ecotones is responding. The high-mountain ecotones, which are less affected by anthropogenic disturbances, present an optimal environment for investigating the effects of climate change on terrestrial ecosystems. Accurately delineating the trends of vegetation in high-mountain ecotones is pivotal for a comprehensive understanding how climate change affects these ecosystems. Remote sensing technology has a significant potential in detecting and quantifying vegetation variation. While previous studies have identified greening trends within certain mountainous regions, there remain a gap in global-scale analysis concerning vegetation dynamics in high-mountain ecotones.

In this study, we utilize long time-series Landsat imagery to monitor and analyze vegetation dynamics in high-mountain ecotones. Our approach includes assessing changes in the physiological properties of the vegetation and analyzing temporal patterns in spatial distribution changes. The results reveal a consistent trend of increased vegetation density and enhanced greening of vegetation in global high-mountain ecotones under the influence of climate change.

How to cite: Zou, L., Schaepman-Strub, G., Tian, F., and Liang, T.: Assessing vegetation dynamics in global high-mountain ecotones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10168, https://doi.org/10.5194/egusphere-egu24-10168, 2024.

EGU24-10296 | ECS | Orals | BG3.26

Characterizing Spatial Patterns of the Alpine Treeline Ecotone Across the European Alps 

Jana-Sophie Kruse, Werner Rammer, Lisa Mandl, Rupert Seidl, and Michael Maroschek

Ecotones – transition zones between ecosystems – are sentinels of global change, as they are sensitive to changes in environmental conditions and land use. The alpine treeline ecotone - where the continuous, subalpine forest transitions into the treeless alpine zone – is a characteristic feature of many mountain ecosystems. The transition at the ecotone can be characterized by distinct treeline patterns. Treeline patterns can be simple, such as sharp transitions from forest to alpine vegetation, or complex, e.g., islands of trees and krummholz in a matrix of alpine vegetation. This variation can mediate the impact of global change at the alpine treeline ecotone. However, large-scale attribution, e.g., for an entire mountain range, and spatiotemporal quantification of treeline patterns remain challenging. Automated methods, such as deep learning-based computer vision systems, can help to overcome these challenges. Building on existing definitions of treeline patterns, we aim to characterize the alpine treeline ecotone for the entire mountain range of the European Alps. Our particular objectives are:

  • To characterize the patterns of a representative sample of the alpine treeline ecotone of the European Alps based on remote sensing information as training data for deep learning.
  • To quantify treeline patterns across the Alps and identify spatial differences in the prevalence of patterns.

In an alpine treeline ecotone, we considered the transition between three vegetation classes: trees (i.e., upright woody plants with a minimum height of 3m), krummholz (i.e., stunted trees and woody shrubs), and treeless alpine vegetation. Three spatial patterns were considered for trees and krummholz describing their state: closed, islands, or isolated individuals. The transitions between these states across elevation, a total of 24 combinations, were used to quantitatively characterize treeline patterns. We selected 1,000 randomly distributed elevational transects between 1,100 and 2,800 m.a.s.l. that include the alpine treeline ecotone across the European Alps. For each transect, we classified treeline patterns for areas of 90m×90m using satellite and orthophoto images. Based on this dataset, we quantified differences in treeline patterns and their distribution in elevation across the European Alps: While in the Prealps, the alpine treeline ecotone is located in lower elevations and treeline patterns tend to be more complex, the ecotone is higher in elevation and less complex in the Central Alps.

The quantification of treeline patterns and their distribution can serve as a basis for further investigations of the alpine treeline ecotone and its spatiotemporal development. We provide an outlook for a deep learning approach that uses the presented dataset combined with a time series of spectrally unmixed satellite data, i.e., fractional abundances of land cover per pixel, as training data. Utilizing satellite data of the past 35 years in annual resolution, we will be able to automatically classify and analyze treeline patterns and their changes across the entire European Alps.

How to cite: Kruse, J.-S., Rammer, W., Mandl, L., Seidl, R., and Maroschek, M.: Characterizing Spatial Patterns of the Alpine Treeline Ecotone Across the European Alps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10296, https://doi.org/10.5194/egusphere-egu24-10296, 2024.

EGU24-11942 | ECS | Orals | BG3.26 | Highlight

Treeline spatial patterns for biodiversity monitoring detected by spectral and 3D information from UAV‐based aerial imagery 

Erik Carrieri, Fabio Meloni, Carlo Urbinati, Emanuele Lingua, Raffaella Marzano, and Donato Morresi

Treeline ecotones spatial patterns and dynamics are influenced by factors acting at regional, landscape, and local scales. It is widely accepted that treelines change in complex ways depending on their diverse structural features and environmental conditions.
The high variability of environmental conditions and ecological drivers hampers the creation of a general pattern from case studies. A multi-scale approach applied at numerous locations is needed to discriminate between natural and anthropogenic factors that are driving treeline dynamics. Remote sensing techniques are today fundamental tools for a comprehensive assessment of the spatial heterogeneity of treeline patterns and their changes over space and time. Continuous improvements in remote sensing platforms, sensors, and methodologies have considerably increased the quality and reliability of spatial information, such as forest maps, which are essential for monitoring ecotonal dynamics.
In this study, we aimed to comprehensively map individual tree canopies at the treeline ecotone in 10  different sites distributed across the Italian Alps by integrating field and UAV-based data. We first mapped the position of the forestline using the 2018 pan-European Tree Cover Density layer provided by the Copernicus Land Monitoring service. In particular, we considered the pixel line where the tree canopy cover was less than 10% as the forestline. Field data consisted of position, height, and species of 100 trees taller than 50 cm scattered over a 9-hectare area. Each site was also flown over by a multirotor drone to produce an RGB orthomosaic, a digital surface model, and a canopy height model. A total of 1016 individual canopies of different coniferous species were manually classified on the orthomosaics with the aid of semi-automatic annotation software. These data were used to train a deep learning model based on the Mask R-CNN algorithm for object detection and segmentation. The classification masks were lastly combined with a canopy height model providing 3-dimensional information allowing to measure tree height. Preliminary results evidenced that remotely sensed data collected with low-cost equipment such as commercial drones with RGB cameras, coupled with the proposed canopy detection method can be used to produce highly accurate and reliable maps of treeline ecotones. These maps will serve as a starting point to study and monitor the spatio-temporal dynamics of treeline ecotones at the local scale and how they affect biodiversity in high-altitude environments.

How to cite: Carrieri, E., Meloni, F., Urbinati, C., Lingua, E., Marzano, R., and Morresi, D.: Treeline spatial patterns for biodiversity monitoring detected by spectral and 3D information from UAV‐based aerial imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11942, https://doi.org/10.5194/egusphere-egu24-11942, 2024.

Treeline elevation is expected to shift upward in response to climate warming. However, over half of alpine treelines worldwide appear to be lagging, possibly due to moisture limitations. Seedling niches tend to have narrower climate envelopes than those of mature, established trees, and regeneration requirements can vary substantially among species. We examined the density and species composition of recruitment at alpine treeline sites west and east of the Continental Divide, Central Rocky Mountains.  In the arid Colorado Front Range, the Divide results in a rain shadow on the east side due to orographic uplift. We stratified our sampling effort by proximity to subalpine limber pine (Pinus flexilis), a generalist, drought-tolerant conifer with a patchy metapopulation distribution in the Front Range. We expected to find higher abundance of limber pine regeneration than that of drought-averse Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) in two regeneration height categories (≤ 100 cm and ≤ 20 cm). Regeneration occurred at low densities on both sides of the Continental Divide and did not differ significantly between sites east and west of the Divide. Regeneration density also did not differ significantly between communities dominated by limber pine and communities dominated by Engelmann spruce and subalpine fir. However, the quadrats with highest regeneration densities were east of the Divide where limber pine was the dominant conifer. These sites were also in the rain shadow and associated with higher climate water deficit and lower growing season precipitation. Limber pine also comprised the majority of this regeneration. The site with the highest observed regeneration rates also had high rates of viable limber pine seed production at treeline. We observed a significantly higher proportional abundance of limber pine in the 100 cm regeneration class (relative to established trees) in quadrats east of the Divide, corresponding to establishment roughly in the last 30-70 years. The greater proportional abundance in limber pine regeneration at these treeline study sites occurred despite increasing temperatures, reduced growing season precipitation, and increased climate water deficit over the past 30 years. Drought-tolerant limber pine may therefore be the best-suited conifer in this region to persist and to migrate to higher elevations as temperatures continue to increase. Our findings underscore the importance of considering differences in seedling tolerances (niches) among different species in alpine treeline systems when aiming to predict landscape-scale treeline responses to climate warming.

How to cite: Sindewald, L. and Tomback, D.: Recruitment at treeline in the Central Rocky Mountains shifts in favor of a drought-tolerant species as climate water deficit increases, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14114, https://doi.org/10.5194/egusphere-egu24-14114, 2024.

Whitebark pine (Pinus albicaulis) and limber pine (Pinus flexilis), related five-needled white pines (Pinus subgenus Strobus, section Quinquefoliae, subsection Strobus), are distributed throughout the mountains of the western United States and Canada. Whitebark pine ranges from about  36° to 56 ° N latitude, and limber pine ranges from about 34° to 52° N latitude.  Both pines are tolerant of harsh sites, including poor soils and arid conditions, but whitebark pine inhabits colder sites and is restricted to high elevations, and limber pine occupies a broader elevational range and has more drought-resistance. The seeds of both pines are dispersed primarily by Clark’s nutcrackers (Nucifraga columbiana), which often cache seeds at treeline and in tundra.  In the Rocky Mountains, both pines are components of treeline communities but differ in growth form and foliage density and thus potential capacity to serve a facilitation function. Our previous studies identified different ecological functions or roles assumed by trees in Rocky Mountain treeline communities: isolated solitary tree, most windward tree of a tree island (potential tree island “initiator”), satellite tree (sheltered by a tree island), or tree island component (leeward of windward tree).  We examined whether whitebark and limber pine differ in ecological functions in treeline communities.  Whitebark and limber pine primarily co-occur with Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) at treeline, and both pines have higher abundance at treeline east of the Continental Divide. In treeline communities broadly sampled from 42° to 53° N latitude, whitebark pine was the majority solitary conifer in 9 out of 10 treeline study sites and had the highest representation within tree islands at 8 of 10 study sites.  Whitebark pine was the most frequently occurring windward conifer in tree islands at half of the study sites, and its proportional abundance as a solitary tree predicted its proportional abundance as a windward conifer.  Limber pine, in contrast, was rare at treeline at northern latitudes but more common in the arid southern Rocky Mountains.  We studied treeline communities in Rocky Mountain National Park, both east and west of the Continental Divide in 19 study sites.  Limber pine was found only east of the Divide and varied in prevalence from 0% to 97.6% of trees within a study site. It most frequently occurred as a satellite or solitary tree and less frequently as a windward tree than expected by its representation as a solitary tree.  We found a relationship between the proportion of limber pine at our treeline sites and the distance to a subalpine limber pine seed source, likely resulting from seed dispersal by nutcrackers against prevailing winds.  In sum, tolerance of harsh, windy conditions by both pines, coupled by avian seed dispersal, leads to their prevalence as solitary trees in treeline communities east of the Continental Divide.  Whitebark pine’s denser morphology likely facilitates establishment of conifers to its lee. Limber pine’s drought tolerance enables it to survive well on windswept ridges and slopes—which have earlier snowmelt dates—and may lead to increasing prevalence with climate change.

How to cite: Tomback, D. and Sindewald, L.: Differences in functional ecology of two western North American ‘five-needle’ white pines in treeline communities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14685, https://doi.org/10.5194/egusphere-egu24-14685, 2024.

EGU24-15287 | ECS | Orals | BG3.26 | Highlight

Is anthropogenic pressure limiting the climate-induced upward shift of the subalpine forest line in the French Northern Alps? 

Noémie Delpouve, Cyrille Rathgeber, Laurent Bergès, Jean-Luc Dupouey, Sandrine Chauchard, and Nathalie Leroy

The forest line is a key feature of mountain landscapes around the world. Currently, most forest lines in the Northern Hemisphere are rising due to the combined effects of land-use and climate changes. This upward shift has led to major changes in the functions and services provided by the adjacent socio-ecosystems (e.g. carbon sequestration, biodiversity hosting, services to people…). However, it has not been elucidated how the recent forest-line upward shift fits into the longer context of land abandonment (occurring since the beginning of the 19th century in France), and how it is currently responding to the accelerating global warming. To answer this question, we assessed the elevation change of the forest line over the French northern Alps since the forest minimum (mid-19th century in France) using old and current land cover maps.

Three digitalised maps: the État-Major map, BD Forêt® v1.0 and BD Forêt® v2.0 were used to display forest cover at three dates: 1859, 1994 and 2007, respectively. These maps were standardized and combined with a digital elevation model to estimate the average elevation of the subalpine forest lines for 178 municipalities across the French departments of the Northern Alps: Haute-Savoie, Savoie and Isère. We compared forest-line elevations between dates and municipalities to explore temporal and spatial patterns.

The forest line in the French Northern Alps has risen by an average of 152 ± 18 m from its ancient position (1879 ± 21 m a.s.l. in 1859) to its current position (2032 ± 12 m in 1994).  However, no general upward shift was observed during the most recent period from 1994 to 2007, as the forest-line position was 2013 ± 13 m in 2007. In the Haute-Savoie department, a downward shift of 69 ± 12 m was even observed, while forest lines in Isère and Savoie were stable. Forest-lines upward shift in the French Northern Alps has been driven by agricultural abandonment, mountain land restoration and global warming since the period of the forest minimum (around 1860). However, it is noteworthy that forest line dynamics are no longer influenced by these factors nowadays and do not follow the acceleration of temperature increase. The current recession of the forest lines may be attributed to anthropogenic pressure related to the tourism activity. This new anthropogenic pressure corresponds to the development of alpine ski resorts and the increase in the human population in Haute-Savoie since 1925, and later in the other departments.

This large-scale spatial and temporal study shows how global and regional factors interact in the long-term to shape mountain landscapes, in particular the ecotone between subalpine forest and alpine grassland. Today, the dynamics of this ecotone is still linked to the contradictory tensions that divide our societies (conservation vs. exploitation). This is why we advocate the cautious management of alpine forest line ecotones, which could contribute to carbon sequestration and biodiversity conservation, provided they are not subjected to excessive human pressure (tourism and grazing).

How to cite: Delpouve, N., Rathgeber, C., Bergès, L., Dupouey, J.-L., Chauchard, S., and Leroy, N.: Is anthropogenic pressure limiting the climate-induced upward shift of the subalpine forest line in the French Northern Alps?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15287, https://doi.org/10.5194/egusphere-egu24-15287, 2024.

EGU24-15620 | ECS | Orals | BG3.26

Forestline detection and treeline ecotone dynamics in the Italian Alps and Apennines by satellite remote sensing 

Lorena Baglioni, Donato Morresi, Enrico Tonelli, Emanuele Lingua, Raffaella Marzano, and Carlo Urbinati

Treelines are dynamic ecotones largely influenced by climate and land use changes. The increasing development of remote sensing techniques and the interest on the ecological effects of global warming on forest vegetation have raised the number of treeline studies.

The aims of this study were: i) to define an automatic approach for mapping the current position of the upper forestlines in the Italian Alps and Apennines and ii) to locate hotspots of long-term vegetation dynamics using Landsat-based spectral trend analysis. Hotspots will serve us to analyse the ecological drivers of vegetation change and to predict future vegetation dynamics.

We used the Tree Cover Density (TCD) dataset (Copernicus Land Monitoring Service) and a nationwide digital elevation model to define the polylines representing the forestlines for the reference year 2018. We used the main Italian mountain peaks, extracted from the Global Mountain Biodiversity Assessment (GMBA) dataset polygons, as reference points to detect only the upper forest ecotones based on the elevation difference between peaks and forest pixels. We defined our study areas by applying a positive and negative buffer around the forestlines and we calculated several spectral vegetation indices (e.g. NDVI, EVI, Tasseled Cap Angle) from Landsat timeseries of the last 40 years. In this way, we inferred inter-annual vegetation dynamics, discriminating two sub-areas of interest: the closed forest (below the current forestline) and the upper treeline ecotone (above the current forestline). It should be noted that on the Alps, treelines mainly host conifer species, whereas on the Apennines, broadleaf species (mostly European beach) prevail. We tested the significance of long-term spectral trends through a Mann-Kendall test for monotonicity that accounted for autocorrelation in space and time.

An important outcome of the study was to set up a replicable and unsupervised method to enhance the study of vegetation dynamics at treeline ecotones. This approach will allow the delimitation of the forestlines on a global scale and an ecologically sound comparison between different treeline ecotones. This study is the first step in a nationwide project and will provide the basis for future local-scale investigations of treeline ecotones.

How to cite: Baglioni, L., Morresi, D., Tonelli, E., Lingua, E., Marzano, R., and Urbinati, C.: Forestline detection and treeline ecotone dynamics in the Italian Alps and Apennines by satellite remote sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15620, https://doi.org/10.5194/egusphere-egu24-15620, 2024.

EGU24-20484 | Orals | BG3.26

Treeline resposes to 2K warming in the Alps in half a century 

Christian Körner

Since climatic treelines track the elevational position of isotherms across the globe, it is not the question if, but when and how they will arrive at a novel steady-state position. After briefly recalling the essential difference between the edge of the realized and fundamental niche of the life form tree (not to be confused with species’ range limits), I will present data on recent climatic trends in the Alps based on long term meteorological records. Two years of in-situ temperature records from Pinus cembra trees growing right at the current upper edge of tree size individuals in Eastern Tyrol (supplemented with data from the Swiss Engadin region), make it obvious that the current high elevation record positions around 2500 m elevation are lagging substantially behind the upslope shift of the isotherm. This explains, why these trees grew so exceptionally rapid over the past 10 years, partly growing a meter in height in only 6-8 years. The locations with rapid tree radiation are all under nutcracker control. These data permit projections on forthcoming treeline shifts. For the Austrian Alps, the current uppermost trees represent all-time elevation records, and will soon out-range the uppermost fossil elevation records of trees that date back to the warmest period of the Holocene. Suggested reading: Körner C, Hoch G (2023) Not every high-elevation or high-latitude forest edge is a treeline. J Biogeography, open access.

How to cite: Körner, C.: Treeline resposes to 2K warming in the Alps in half a century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20484, https://doi.org/10.5194/egusphere-egu24-20484, 2024.

EGU24-21283 | ECS | Posters on site | BG3.26

Young trees climate sensitivity above the forestline: the case study of Pinus nigra upward shift in Central Apennines (Italy)  

Enrico Tonelli, Alessandro Vitali, Alma Piermattei, and Carlo Urbinati

In the context of ecological research, tree-ring analysis often deals with short time series (< 30 years). Their crossdating and averaging can be difficult but crucial to use such data for ecological modelling, multivariate statistics, and climate-growth analysis. Several studies were conducted in the Central Apennines (Italy) on recent encroachment of European black pine (Pinus nigra J.F. Arnold) on treeless areas above the current forestline. Growth of young trees is mainly controlled by endogenous or microclimatic factors making usual dendrochronology methods less applicable and crossdating very difficult or even impossible. The potential ecological information deriving from tree-ring growth in short series is therefore limited by this methodological bias. The aim of this study is to test suitable methods for optimizing the use of short ring series for further analytical use. A dataset of 734 tree-ring series of young European black pines (mean cambial age 15 years) growing at high altitude in 8 sites was used in this analysis. At each site tree-ring series were divided in two groups based on inter-series correlation: the crossdated or selected series (SEL), and non-crossdated or rejected ones (REJ). The following dendrochronological parameters were calculated for SEL and REJ series: mean tree-ring width, mean sensitivity, Gini coefficient, first order autocorrelation, inter-series correlation, and Gleichläufigkeit (GLK). Two methods of pointer years analysis were tested in order to detect years with synchronous growth: i) Normalization in a moving Window (NW) and ii) the RElative growth change method (RE). The two methods were applied to the raw series varying the standard thresholds, in order to detect synchronous growth-years in SEL and REJ group. A sensitivity analysis was included to assess how the threshold choice in the analysis could affect the results obtained. The term “common” was used to indicate years with similar tree growth response. Differences in the detected number of common years within SEL and REJ were obtained using different time windows with the RE and NW methods. The 47 % of all series were classified as SEL, showing more common years than the REJ series. However, a similar result occurred considering all the series together without SEL/REJ discrimination. In general, a significant occurrence of common years could be a tool to select series to be averaged for a site mean chronology. These are preliminary but encouraging results contributing to a more efficient use of the ecological information provided by short time series from young trees.

How to cite: Tonelli, E., Vitali, A., Piermattei, A., and Urbinati, C.: Young trees climate sensitivity above the forestline: the case study of Pinus nigra upward shift in Central Apennines (Italy) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21283, https://doi.org/10.5194/egusphere-egu24-21283, 2024.

EGU24-21593 | ECS | Posters on site | BG3.26

Spatio-temporal dynamics of four pine species recolonization in Southern Europe human-disturbed forestlines 

Alessandro Vitali, Matteo Garbarino, J. Julio Camarero, Elvin Toromani, Velibor Spalevic, Milić Čurović, and Carlo Urbinati

In this study we compared the encroachment patterns of four pine species across anthropogenic forestlines in Southern Europe. Using a synchronic approach, we studied structure and recent spatio-temporal patterns of pine recruitment at upper forestline ecotones in Albania, Italy, Montenegro and Spain. Within altitudinal transects we mapped and sampled 964 living individuals of Pinus heldreichii, Pinus peuce, Pinus sylvestris and Pinus uncinata growing above the current forest line. We measured their basal diameter, total height, and counted the number of seed cones. We differentiated seedlings (height < 0.5 m) from saplings (0.5m≤height < 2 m) and trees (height≥2 m). From individuals with basal stem diameter>4 cm we extracted one increment core for cambial age determination and tree-ring width measurements. On smaller specimens, we estimated the age by counting annual internodes (terminal bud scars) along the whole stem. We compared the ground cover around each pine, applied point pattern analyses, modelled the probability of seed cone production and estimated the average distance of seed dispersal. The four pine species exhibited heterogeneous density values and the overall averaged means ranged 2–7 cm for basal diameter, 54–106 cm for total height and 9–20 years for cambial age, suggesting a recent encroachment process. None of these structural variables decreased with increasing relative altitude and distribution patterns exhibited a few higher density spots but not cohort spatial structure. Ground cover differed between species and more significantly between size classes. Grass was the most frequent type at all sites except for P. sylvestris where shrubs prevailed. Basal area increments increased from 1990 and stabilized in recent years at all species except for P. peuce. Height and basal diameter predicted cones production better than cambial age. P. heldreichii and P. peuce dispersed seeds at longer distances than P. uncinata and P. sylvestris, suggesting different potential for further encroaching. Pine recruitment above the forestlines is quite synchronic at all sites (last 30 years), but in some cases it appeared as a high altitude tree densification process, whereas in others as a starting forestline advance.

How to cite: Vitali, A., Garbarino, M., Camarero, J. J., Toromani, E., Spalevic, V., Čurović, M., and Urbinati, C.: Spatio-temporal dynamics of four pine species recolonization in Southern Europe human-disturbed forestlines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21593, https://doi.org/10.5194/egusphere-egu24-21593, 2024.

EGU24-21595 | Posters on site | BG3.26

Linking ecological processes and spatial patterns: the promise of remote sensing in treeline ecology 

Matteo Garbarino, Donato Morresi, Peter Weisberg, and Nicolò Anselmetto

Treelines are ecotones with a strong spatial nature. Remote sensing (RS) tools provide spatially explicit wall-to-wall maps in time. Nevertheless, despite the potential of RS to inform treeline ecologists on spatial patterns and underlying processes, its application is still scarce and heterogeneous. We performed a systematic review and meta-analysis of published literature with the aim to provide a question-oriented discussion of RS in treeline ecology. The main focus of the review was the role of RS as a tool for measuring spatial patterns and dynamics of treeline globally. We assessed the geographic distribution, scale of analysis, and relationships between RS techniques and ecological metrics through cooccurrence mapping and multivariate statistics. Only 10% of treeline studies applied RS. We observed four main types of applications; long-term aerial, long-term oblique, satellite timeseries, and high-resolution mapping. Long-term research and monitoring adopted coarser spatial resolution over long temporal extent, either with oblique or aerial photographs to measure treeline position and shift. Shorter temporal extents (i.e., up to 40 years) were investigated through satellite time-series, especially when dealing with coarse dynamics such as changes in climate. High-resolution imagery derived from UAV recently emerged as promising tools to measure tree height, canopy cover, and spatial patterns at a very fine spatial resolution (i.e., centimetres to metres). A multiscale and multi-sensor spatial approach was implemented in just 19% of papers. We advocate for an increasing interaction between classic treeline ecology based on field surveys and RS techniques. Also, the multi-dimensional structural complexity of treeline ecotones calls for a multiscale and multi-sensor approach, with high-resolution and low cost UAV acting as a powerful tool to fill the gap between local-scale ecological patterns and coarse-resolution satellite sensors.

How to cite: Garbarino, M., Morresi, D., Weisberg, P., and Anselmetto, N.: Linking ecological processes and spatial patterns: the promise of remote sensing in treeline ecology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21595, https://doi.org/10.5194/egusphere-egu24-21595, 2024.

EGU24-21677 | ECS | Posters on site | BG3.26

Exploring alpine seedling dynamics: microsite preferences and physiological performance in the French treeline ecotone 

Lirey A. Ramirez, Hannah Loranger, Lukas Flinspach, Nada Nikolic, Johanna Toivonen, Hanna Wenzel, Gerhard Zotz, and Maaike Y. Bader

Seedling establishment is a major bottleneck in plant community dynamics and is particularly critical for tree advance in the treeline ecotone. However, the characteristics and availability of safe sites for tree regeneration in alpine ecosystems remain unclear, while the criteria for safe sites may differ between tree species. Tree seedlings in the treeline ecotone are exposed to multiple environmental stressors that may differ from those affecting adult trees. Understanding the response of seedlings to different combinations of abiotic and biotic constraints is essential for predicting future treeline shifts. We therefore aimed to: 1) evaluate differences in microsite preferences of the conifers Larix decidua, Pinus uncinata, and P. cembra at treeline sites with two different types of bedrock chemistry, and 2) study the response of these species plus two further treeline-forming tree species, Picea abies and Sorbus aucuparia, to microclimatic manipulation. We evaluated microsite preferences at four sites in the upper treeline ecotone in the French Alps, two with calcareous and two with siliceous bedrock, and compared, at each site, the microsite characteristics of 50 tree species individuals with 50 random microsites, describing the substrate, ground cover, macro- and microtopography, and nearest shelter of each microsite. In a field experiment, also in the French Alps, seedlings were planted in 40 plots arranged in five blocks with the following treatments: Day warming, Day warming + watering, Night warming, Night warming + shade, Shade, Control, Watering, and Vegetation cover. We evaluated survival, growth, and biochemistry (chlorophyll fluorescence and nonstructural carbohydrates) of two seedling cohorts (planted in two consecutive years). We found that microsites were similar, and mostly sheltered, in both bedrock types, and the occupied microsites were a good representation of the available microsites in the respective areas, suggesting that safe-site availability does not limit the establishment of these species in the treeline ecotone. In the experiment, the two seedling cohorts responded differently to the treatments, but in general the vegetation treatment had the strongest effect on seedling performance in all the species studied. Our results imply that, contrary to our expectations, seed availability, rather than safe site availability, is a primary constraint for tree establishment in these alpine-treeline ecotones. Furthermore, in our experiment, the presence of vegetation affected seedling performance more than shading or warming, but given the differences between cohorts, this result must be carefully considered.

How to cite: Ramirez, L. A., Loranger, H., Flinspach, L., Nikolic, N., Toivonen, J., Wenzel, H., Zotz, G., and Bader, M. Y.: Exploring alpine seedling dynamics: microsite preferences and physiological performance in the French treeline ecotone, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21677, https://doi.org/10.5194/egusphere-egu24-21677, 2024.

EGU24-22195 | Posters on site | BG3.26

The Spatial Treeline-Ecotone Model (STEM) as a tool for understanding pattern-process relationships in alpine-treeline ecotones 

Maaike Bader, Lukas Flinspach, Bradley Case, Julio Camarero, and Thorsten Wiegand

Spatial patterns in alpine-treeline ecotones reflect the ecological processes that have shaped and probably continue to shape these transition zones. Understanding these processes is essential for predicting treeline responses to global-change factors. To connect treeline-ecotone patterns and processes, we developed a spatially-explicit individual-based model. The first version of this Spatial Treeline Ecotone Model (STEM 1.0) represents the growth, mortality and dieback (biomass loss leading to stunted trees or krummholz) of all individual trees within a treeline transect, and uses variation in these demographic rates, imposed along elevation gradients or emerging as a result of neighbor interactions, to create treeline ecotones with different spatial patterns. The model could reproduce many of the expected treeline types, but some types required very particular parameter combinations. These results helped to identify missing elements in the model and thus to sharpen our conceptual model of treeline-forming processes. The next mayor development step for the model is to let demographic rates emerge from the interaction of environmental influences, modified by plant-plant interactions, rather than being imposed. However, this first version is a very important first step to formalizing and developing our conceptual model of pattern-process relationships in alpine-treeline ecotones.

How to cite: Bader, M., Flinspach, L., Case, B., Camarero, J., and Wiegand, T.: The Spatial Treeline-Ecotone Model (STEM) as a tool for understanding pattern-process relationships in alpine-treeline ecotones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22195, https://doi.org/10.5194/egusphere-egu24-22195, 2024.

EGU24-1555 | ECS | Orals | ESSI3.5

eLTER and its role of providing in-situ data to large scale research projects for modelling biodiversity dynamics 

Christoph Wohner, Alessandro Oggioni, Paolo Tagliolato, Franziska Taubert, Thomas Banitz, Sarah Venier, Philip Trembath, and Johannes Peterseil

The integrated European Long-Term Ecosystem, critical zone and socio-ecological Research (eLTER) is an emerging pan-European, in-situ Research Infrastructure (RI). Once fully established, it will serve multiple scientific communities with high-level central facilities and distributed well-instrumented eLTER sites. In the Horizon Europe project Biodiversity Digital Twin (BioDT), eLTER already plays the role of a provider for European datasets, in particular for the Grassland Dynamics prototype digital twin. Here, GRASSMIND, an individual- and process-based grassland model designed for simulating the structure and dynamics of species-rich herbaceous communities, including these communities’ responses to climate and management, is to be upscaled to model different local grassland sites across Europe. As the eLTER in-situ site network also comprises such grassland sites, the site registry DEIMS-SDR (deims.org) was used to identify relevant sites and contact the respective site managers and researchers to mobilise data. This selection process was aided by the machine-actionable data endpoints of eLTER also accessible using the Python and R packages, deimsPy and ReLTER, enabling script-based extraction and analysis. Collected and mobilised data is to be published on the persistent data storage B2Share and made centrally accessible through the eLTER central data node. Metadata about the resources is also available in RDF format, making them interlinked and accessible via a SPARQL endpoint. 

The data provided will enable stronger validation and improvements of the grassland simulations, and thus to better scientific insights and grassland management recommendations.

How to cite: Wohner, C., Oggioni, A., Tagliolato, P., Taubert, F., Banitz, T., Venier, S., Trembath, P., and Peterseil, J.: eLTER and its role of providing in-situ data to large scale research projects for modelling biodiversity dynamics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1555, https://doi.org/10.5194/egusphere-egu24-1555, 2024.

EGU24-1724 | ECS | Orals | ESSI3.5

Improving the Findability of Digital Objects in Climate Science by adopting the FDO concept 

Marco Kulüke, Karsten Peters-von Gehlen, and Ivonne Anders

Climate science relies heavily on the effective creation, management, sharing, and analysis of massive and diverse datasets. As the digital landscape evolves, there is a growing need to establish a framework that ensures FAIRness in handling climate science digital objects. Especially, the machine-to-machine actionability of digital objects will be a crucial step towards future AI assisted workflows. Motivated by a use case, this contribution proposes the adoption of the Fair Digital Object (FDO) concept to address the challenges associated with the emerging spread in interdisciplinary reuse scenarios of climate model simulation output.

FDOs are encapsulations of data and their metadata made accessible via persistent identifiers (PIDs) in a way that data and their context will remain a complete unit as FDO travels through cyberspace and time. They represent a paradigm shift in data management, emphasizing the machine-actionability principles of FAIRness and the requirements enabling cross-disciplinary research. The FDO concept can be applied to various digital objects, including data, documents and software within different research disciplines and industry areas.

The aim of this work is to commit to an FDO standard in climate science that enables standardized and therefore automated data analysis workflows and facilitates the extraction and analysis of relevant weather and climate data by all stakeholders involved. The current work  expands on the efforts made to enable broad reuse of CMIP6 climate model data and focuses on requirements identified to enable automated processing of climate simulation output and their possible implementation strategies. The exemplary use case of an automated, prototypical climate model data analysis workflow will showcase the obstacles occuring when analyzing currently available climate model data. In particular, the findability of digital objects required for a particular research question in climate science or a related field shows to be challenging. In order to mitigate this issue, we propose certain strategies: (1) Enriching the PID profiles of climate model data in accordance with the FDO concept and taking into account the needs of the climate science community will lead to improved findability of digital objects, especially for machines. (2) Defining a standardized, unique association between climate model variables and their meaningful long names will increase the findability of climate model data, especially for researchers in other disciplines. (3) Furthermore, combining the FDO concept with existing data management solutions, such as the intake-esm catalogs, can lead to improved data handling in line with prevailing community practices.

Eventually, implementing an FDO standard will benefit the climate science community in several ways: The reusability of the data will facilitate the cost-effective use of existing computationally expensive climate model data. Improved data citation practices will promote data sharing, and ultimately, high transparency will increase the reproducibility of research workflows and consolidate scientific results.

How to cite: Kulüke, M., Peters-von Gehlen, K., and Anders, I.: Improving the Findability of Digital Objects in Climate Science by adopting the FDO concept, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1724, https://doi.org/10.5194/egusphere-egu24-1724, 2024.

EGU24-3441 | Orals | ESSI3.5

How EOSC became our best ally? 

Anne Fouilloux

In this presentation, we will share firsthand experiences and insights gained from navigating the EOSC (European Open Science Cloud), offering a glimpse into how EOSC influences our day-to-day work and how it has become an invaluable ally for our team. We belong to the Nordic e-Infrastructure Collaboration on Earth System Modeling Tools (NICEST), a small community composed of researchers, Research Software Engineers (RSEs), and engineers from Norway, Sweden, Finland, Denmark, and Estonia, working in different organisations such as national meteorological services, national compute/storage infrastructure providers and support services, universities and other research institutes either working directly on climate or supporting related activities. The NICEST community strengthens the Nordic position in climate modelling by addressing e-infra challenges, leveraging Earth System Models (ESMs) to understand climate processes, adapt to global change, and mitigate impacts.

Our presentation extends beyond the technical aspects, offering a narrative of collaborative discovery that illustrates how EOSC has transformed into an indispensable companion, enabling our team to embody the principles of FAIR (Findable, Accessible, Interoperable, and Reusable) and open science. Throughout the session, we will highlight the operational intricacies of frameworks like EOSC, emphasising our nuanced approach to leveraging these frameworks for maximum impact.

This personal narrative is not just about success stories; it explores the challenges we've faced and the lessons we've learned. We place a special emphasis on our evolving understanding of effectively exploiting specific EOSC services, transforming it into more than just infrastructure but a trusted friend in our professional lives.

As we reflect on our collaborative journey, we'll share stories of triumphs, challenges, and the unique bond that has developed between our team and those contributing to EOSC's development. We'll explain how we've moved from being mere users to active contributors, contributing to the deployment of our own services to serve our community. Today, our aim is to actively participate in the construction of EOSC, demonstrating that through collaboration and co-design, we can significantly contribute to its ongoing evolution. This collaboration becomes truly effective when each actor recognizes the value of others, enabling us to pool efforts and enhance efficiency together.



How to cite: Fouilloux, A.: How EOSC became our best ally?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3441, https://doi.org/10.5194/egusphere-egu24-3441, 2024.

EGU24-3937 | Orals | ESSI3.5

New horizons for the Data Store Infrastructure at ECMWF 

Angel Lopez Alos, Baudouin raoult, Ricardo correa, Andre obregon, Chris stewart, James varndell, Edward comyn-platt, Eduardo damasio da-costa, and Marcus Zanacchi

Since its official launch in 2018 supporting the implementation of the Copernicus Climate Change Service (C3S), the Climate Data Store (CDS) software infrastructure has evolved in many ways driven by an expanding catalogue of resources, a growing user community and the evolution of technologies and standards. On 2020 a twin instance, the Atmosphere Data Store (ADS), as support of the Atmosphere Monitoring Service (CAMS) was released. Since then, Infrastructure was renamed as Climate and Atmosphere Data Store (CADS). Combined, CDS and ADS, provide nowadays service to more than 270k registered users, delivering over 130 TBs of data on daily average in the form of more than 700k processed requests.

In 2024, a modernized CADS will take over. A configurable framework built on cloud oriented and state-of-the-art technologies providing more scalable, wider, and open access to data and services which will foster the engagement with a broader user community and will facilitate interaction with different platforms in the future EU Green Deal Data Space.

Despite changes, CADS foundational principles of simplicity and consistency remains along with FAIR. A rigorous content management methodology is at the core of the system, supported by automatic deployment tools and configuration files that range from web portal content to metadata, interactive forms, dynamic constraints, documentation, adaptors, and quality control. This versatile mechanism provides huge flexibility for adaptation to different standards and FAIR principles. 

In addition to improved capabilities for discovery, search and retrieve, the modernized system brings new or re-engineered components aiming to improve the usability of resources,  such as compliant OGC APIs, integrated and interactive Evaluation and Quality Control (EQC) function, open-source expert python packages (earthkit) for climate and meteorological purposes able to deploy & run anywhere, or Serverless Analysis-Ready Cloud Optimized (ARCO) Data and Metadata Services supporting responsive WMS/WMTS interfaces.

Modernization also involves the underlaying Cloud Infrastructure which aligned with the ECMWF’s Strategy for a Common Cloud Infrastructure (CCI) brings extended compute and storage resources and more importantly, closer, and efficient access to ECMWF resources, data, and services.

All new capabilities combined power a new generation of interactive user applications, training material, EQCs functions, and efficient access mechanisms to large data volumes driven among others by ML/AI requirements.  

Here we describe the new horizons that the modernized Data Store infrastructure open to users, introduce the broad spectrum of functionalities, open-source code, and material currently available and we open for debate the expectations and requirements that will foster the future evolution of the different components of the infrastructure.

How to cite: Lopez Alos, A., raoult, B., correa, R., obregon, A., stewart, C., varndell, J., comyn-platt, E., damasio da-costa, E., and Zanacchi, M.: New horizons for the Data Store Infrastructure at ECMWF, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3937, https://doi.org/10.5194/egusphere-egu24-3937, 2024.

EGU24-5989 | Orals | ESSI3.5

The EPOS open source platform for multidisciplinary data integration and data analysis in solid Earth science 

Daniele Bailo, Rossana Paciello, Helen Glaves, Jean-Baptiste Roquencourt, Jakob Molander, Alessandro Spinuso, Tor Langeland, Jan Michalek, Otto Lange, Agata Sangianantoni, Carine Bruyninx, and Carmela Freda and the EPOS Group

Established as a European Research Infrastructure Consortium (ERIC)  in 2018, the European Plate Observing System (EPOS) Research Infrastructure represents a significant advancement in solid Earth sciences. Its aim is to harmonize and integrate data, services, and computational resources across diverse solid Earth science domains. These include Seismology, Near-Fault Observatories, GNSS Data and Products, Volcano Observations, Satellite Data, Geomagnetic Observations, Anthropogenic Hazards, Geological Information and Modeling, Multi-Scale Laboratories, Tsunami Research, each leveraging EPOS for the integration of domain specific data and services into a wider European multi-disciplinary context.

The EPOS platform ( https://www.epos-eu.org/dataportal) provides access to harmonized and quality-controlled data from thematic solid Earth science services through over 250 interoperable multidisciplinary services. The platform adopts a microservice-based architecture serving RESTful APIs, ensuring seamless interoperability between thematic core services (TCS) and the integrated core services central hub (ICS-C). The ICS-C, as the central system underpinning the EPOS platform, enables interoperability by adopting a multidimensional approach using metadata, semantics, and web services. Released under a GPL license as open-source software (https://epos-eu.github.io/epos-open-source/), EPOS adheres to the FAIR Principles, fostering interdisciplinary collaboration and technological advancement in Earth sciences and beyond.

In addition to data access, the EPOS platform also integrates complementary visualization tools and computational services. These Integrated Core Services - Distributed (ICS-D) enhance the user experience by simplifying complex interactions, offering functionalities like visualization, coding, and processing for data analysis, including machine learning applications.

This presentation will explore how the EPOS platform facilitates the entire research data lifecycle, connecting integrated multidisciplinary data provision to remote data analysis environments. By leveraging third-party cloud and supercomputing facilities equipped with specialized APIs (eg. SWIRRL https://gitlab.com/KNMI-OSS/swirrl/swirrl-api), we will demonstrate how EPOS seamlessly integrates with external services for reproducible data analysis and visualization, relying on common workflows to gather and pre-preprocess the data. External service examples include Jupyter Notebooks developed by domain-specific communities, using which the users can immediately analyze and process the data online. This adaptability streamlines scientific research and also promotes data reusability and collaboration within the portal, showcasing the EPOS platform's role in advancing Earth sciences research.

How to cite: Bailo, D., Paciello, R., Glaves, H., Roquencourt, J.-B., Molander, J., Spinuso, A., Langeland, T., Michalek, J., Lange, O., Sangianantoni, A., Bruyninx, C., and Freda, C. and the EPOS Group: The EPOS open source platform for multidisciplinary data integration and data analysis in solid Earth science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5989, https://doi.org/10.5194/egusphere-egu24-5989, 2024.

EGU24-6798 | ECS | Posters on site | ESSI3.5

Novel environmental big data grid integration and interoperability model 

Daoye Zhu, Yuhong He, and Kent Moore

Currently, effectively managing, retrieving, and applying environmental big data (EBD) presents a considerable challenge owing to the abundant influx of heterogeneous, fragmented, and real-time information. The existing network domain name system lacks the spatial attribute mining necessary for handling EBD, while the geographic region name system proves inadequate in achieving EBD interoperability. EBD integration faces challenges arising from diverse sources and formats. Interoperability gaps hinder seamless collaboration among systems, impacting the efficiency of data analysis.

To address the need for unified organization of EBD, precise man-machine collaborative spatial cognition, and EBD interoperability, this paper introduces the EBD grid region name model based on the GeoSOT global subdivision grid framework (EGRN-GeoSOT). EGRN-GeoSOT effectively manages location identification codes from various sources, ensuring the independence of location identification while facilitating correlation, seamless integration, and spatial interoperability of EBD. The model comprises the grid integration method of EBD (GIGE) and the grid interoperability method of EBD (GIOE), providing an approach to enhance the organization and interoperability of diverse environmental datasets. By discretizing the Earth's surface into a uniform grid, GIGE enables standardized geospatial referencing, simplifying data integration from various sources. The integration process involves the aggregation of disparate environmental data types, including satellite imagery, sensor readings, and climate model outputs. GIGE creates a unified representation of the environment, allowing for a comprehensive understanding of complex interactions and patterns. GIOE ensures interoperability by providing a common spatial language, facilitating the fusion of heterogeneous environmental datasets. The multi-scale characteristic of GeoSOT allows for scalable adaptability to emerging environmental monitoring needs.

EGRN-GeoSOT establishes a standardized framework that enhances integration, promotes interoperability, and empowers collaborative environmental analysis. To verify the feasibility and retrieval efficiency of EGRN-GeoSOT, Oracle and PostgreSQL databases were combined and the retrieval efficiency and database capacity were compared with the corresponding spatial databases, Oracle Spatial and PostgreSQL + PostGIS, respectively. The experimental results showed that EGRN-GeoSOT not only ensures a reasonable capacity consumption of the database but also has higher retrieval efficiency for EBD.

How to cite: Zhu, D., He, Y., and Moore, K.: Novel environmental big data grid integration and interoperability model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6798, https://doi.org/10.5194/egusphere-egu24-6798, 2024.

EGU24-6810 | Posters on site | ESSI3.5

OpenAQ: Harmonizing Billions of Air Quality Measurements into an Open and FAIR Database 

Chris Hagerbaumer, Colleen Marciel Fontelera Rosales, Russ Biggs, and Gabe Fosse

OpenAQ is the largest open-source, open-access repository of air quality data in the world, integrating and hosting over 50 billion measurements from air monitors and sensors at more than 59,000 ground-level locations across 153 countries. The OpenAQ platform supports data on a variety of pollutants in different temporal frequencies. The platform is a one-stop solution for accessing air quality data in a consistent and harmonized format, thereby facilitating findability, accessibility, interoperability and reusability. OpenAQ utilizes modern cloud computing architectures and open-source data tools to maintain a highly scalable data pipeline, which can be resource- and computationally intensive, thus requiring thoughtful and efficient data management and engineering practices. Being an open-source platform that is grounded in community, OpenAQ strives to be transparent, responsible, user-focused, sustainable and technologically-driven.

OpenAQ supports innovation and collaboration in the air quality space by: 

  • Ingesting and sharing data on an open, low-bandwidth platform to ensure data is broadly accessible
  • Providing tools  to help  interpret the data and create visualizations for users with varied technical skills
  • Providing a user guide and trainings on how to use the OpenAQ platform for community-level pilot purposes and beyond
  • Catalyzing specific analyses through intentional outreach to a broad community of data stakeholders

OpenAQ has been widely used for research, informing nearly 300 scientific and data-oriented publications/proceedings. OpenAQ trainings and workshops around the world have resulted in community statements demanding increased coverage and frequency of air quality monitoring, the donation of air quality monitoring equipment to local communities, and adoption of APIs to make open-source city data available. As one example, our work with the Clean Air Catalyst supports pilots to clean the air in Jakarta (Indonesia), Indore (India) and Nairobi (Kenya). As another example, our Community Ambassador program trains emerging air quality leaders in low- and middle-income countries to utilize open data to spur community action to fight air pollution. 

Our poster describes how OpenAQ ingests and harmonizes heterogeneous air quality data at scale and how we conduct outreach to increase impactful usage of the hosted data.

How to cite: Hagerbaumer, C., Rosales, C. M. F., Biggs, R., and Fosse, G.: OpenAQ: Harmonizing Billions of Air Quality Measurements into an Open and FAIR Database, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6810, https://doi.org/10.5194/egusphere-egu24-6810, 2024.

EGU24-7290 | Posters on site | ESSI3.5

Blue-Cloud 2026, services to deliver, access and analyse FAIR & Open marine data 

Dick M. A. Schaap, Tjerk Krijger, Sara Pittonet, and Pasquale Pagano

The pilot Blue-Cloud project as part of ‘The Future of Seas and Oceans Flagship Initiative’ of EU HORIZON 2020 combined interests of developing a thematic marine EOSC cloud and serving the Blue Economy, Marine Environment and Marine Knowledge agendas. It deployed a versatile cyber platform with smart federation of multidisciplinary data repositories, analytical tools, and computing facilities in support of exploring and demonstrating the potential of cloud based open science for ocean sustainability, UN Decade of the Oceans, and G7 Future of the Oceans. The pilot Blue-Cloud delivered:

  • Blue-Cloud Data Discovery & Access service (DD&AS), federating key European data management infrastructures, to facilitate users in finding and retrieving multi-disciplinary datasets from multiple repositories
  • Blue-Cloud Virtual Research Environment infrastructure (VRE) providing a range of services and facilitating orchestration of computing and analytical services for constructing, hosting and operating Virtual Labs for specific applications
  • Five multi-disciplinary Blue-Cloud Virtual Labs (VLabs), configured with specific analytical workflows, targeting major scientific challenges, and serving as real-life Demonstrators, which can be adopted and adapted for other inputs and analyses.    

Since early 2023, Blue-Cloud 2026 aims at a further evolution into a Federated European Ecosystem to deliver FAIR & Open data and analytical services, instrumental for deepening research of oceans, EU seas, coastal & inland waters.

The DD&AS already federates leading Blue Data Infrastructures, such as EMODnet, SeaDataNet, Argo, EuroArgo, ICOS, SOCAT, EcoTaxa, ELIXIR-ENA, and EurOBIS, and facilitates common discovery and access to more than 10 million marine datasets for physics, chemistry, geology, bathymetry, biology, biodiversity, and genomics. It is fully based on machine-to-machine brokering interactions with web services as provided and operated by the Blue Data Infrastructures. As part of Blue-Cloud 2026 it will expand by federating more leading European Aquatic Data Infrastructures, work on improving the FAIRness of the underpinning web services, incorporating semantic brokering, and adding data subsetting query services.

The Blue-Cloud VRE, powered by D4Science, facilitates collaborative research offering computing, storage, analytical, and generic services for constructing, hosting and operating analytical workflows for specific applications. Blue-Cloud 2026 will expand the VRE by federating multiple e-infrastructures as provided EGI, Copernicus WEkEO, and EUDAT. This way, it will also open the connectivity to applications as developed in other EU projects such as iMAGINE (AI applications for marine domain), and EGI-ACE (applications for ocean use cases).

During EGU we will share insight in the solutions regarding semantics supporting interoperability and harmonised data access. This will be especially illustrated via developments of new Blue-Cloud analytical Big Data “WorkBenches” that are generating harmonised and validated data collections of Essential Ocean Variables (EOVs) in physics (temperature and salinity), chemistry (nutrients, chlorophyll, oxygen) and biology (plankton taxonomy, functions and biomass). The access to harmonised subsets of the BDI’s data collections will be supported by new tools like BEACON and the I-Adopt framework. The EOV collections are highly relevant for analysing the state of the environment.  This way, Blue-Cloud 2026 will provide a core data service for the Digital Twin of the Ocean, EMODnet, Copernicus, and various research communities.

How to cite: Schaap, D. M. A., Krijger, T., Pittonet, S., and Pagano, P.: Blue-Cloud 2026, services to deliver, access and analyse FAIR & Open marine data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7290, https://doi.org/10.5194/egusphere-egu24-7290, 2024.

EGU24-7391 | Posters on site | ESSI3.5

Fostering cross-disciplinary research - Training, workshops and summer schools of Geo-INQUIRE EU-project 

Mariusz Majdanski, Iris Christadler, Giuseppe Puglisi, Jan Michalek, Stefanie Weege, Fabrice Cotton, Angelo Strollo, Mateus Prestes, Helle Pedersen, Laurentiu Danciu, Marc Urvois, Stefano Lorito, Daniele Bailo, Otto Lange, and Gaetano Festa

The Geo-INQUIRE (Geosphere INfrastructure for QUestions into Integrated REsearch) project, supported by the Horizon Europe Programme, is aimed at enhancing the Earth Sciences Research Infrastructures and 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 Geosystem processes at the interface between the solid Earth, the oceans and the atmosphere using big data collections, high-performance computing methods and cutting-edge facilities.

The project has a strong focus on supporting dynamic development of the actual use of research infrastructures. Training, networking, and community-building activities will be key to foster it. The methodology ensures empowering participation of both young and experienced researchers, also from often underrepresented communities, but also incorporates new and intersectional perspectives, while addressing current major environmental and economic challenges and fertilising curiosity-driven, cross-disciplinary research.

The project dissemination activities include a series of open online training and more specialised on-site workshops focused on data, data products and software solutions. Researchers, early-stage scientists, students are communities which will be able to explore the various fields of geosphere-related science, also not directly related to their field, with the possible connection through Research Infrastructures. Through lectures and use cases, we expect to show and teach them how to use data and information coming from cross-disciplinary RIs. We would like to increase the awareness of the capacity and capabilities of “other” RIs, as well as data integration and importance of FAIR principles. The training offer is constantly updated on the project web page www.geo-inquire.eu.

In addition, two summer schools will be organised, dedicated to cross-disciplinary interactions of solid Earth with marine science and with atmospheric physics. The first school will be organised in autumn 2024 in Gulf of Corinth (Greece), and the second one in autumn 2025 in Catania, Sicily (Italy).

The applications for training activities will be evaluated by a panel that reviews the technical and scientific feasibility of the proposed application project, ensuring equal opportunities and diversity in terms of gender, geographical distribution and career stage. The data and products generated during the Transnational Accesses to research facilities will be made available to the scientific community via the project strict adherence to FAIR principles.

Geo-INQUIRE is funded by the European Commission under project number 101058518 within the HORIZON-INFRA-2021-SERV-01 call.

How to cite: Majdanski, M., Christadler, I., Puglisi, G., Michalek, J., Weege, S., Cotton, F., Strollo, A., Prestes, M., Pedersen, H., Danciu, L., Urvois, M., Lorito, S., Bailo, D., Lange, O., and Festa, G.: Fostering cross-disciplinary research - Training, workshops and summer schools of Geo-INQUIRE EU-project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7391, https://doi.org/10.5194/egusphere-egu24-7391, 2024.

EGU24-8255 | ECS | Orals | ESSI3.5

The Castanhão EPISODE - the case study of Reservoir Induced Seismicity (RIS) in NE Brazil. 

Helena Ciechowska, Łukasz Rudziński, Beata Orlecka-Sikora, Alessandro Vuan, Anastasios Kostoglou, and Aderson Farias do Nascimento

The man-made alteration to the environment can become a source of seismic activity. The Castanhão region (Ceará, NE Brazil) can pose as an example of such. The Castanhão Reservoir was created as a result of dam construction over the Jaguaribe River, which triggered the occurrence of earthquake swarms on the site. 

In the following study, we aim to analyze the data and understand the seismic mechanism behind the seismic activity in the Castanhão region. Such study required an interdisciplinary approach employing data from various disciplines such as seismology, geology, geomechanics, and hydrology. The starting data set contains continuous waveforms recorded on 6 seismological stations from January to December 2010. The two detection algorithms were applied for earthquake detection. Initial detection was performed with the use of the STA/LTA algorithm, which allowed for the preparation of 53 templates with a good S/N ratio. Further, in the frequency range from 5 to 100 Hz, the input templates were used to match self-similar events to augment the initial catalog.

Due to the station coverage and low magnitude of the events, the detailed analysis of the quakes is performed on 187 events out of over 300 that were detected during PyMPA template matching. The localization was performed using Hypo71 software and analysis of mechanisms is done with the KiwiTool. 

The Castanhão EPISODE is planned to be made available on the EPISODES Platform of EPOS Thematic Core Services Anthropogenic Hazards.

How to cite: Ciechowska, H., Rudziński, Ł., Orlecka-Sikora, B., Vuan, A., Kostoglou, A., and Nascimento, A. F. D.: The Castanhão EPISODE - the case study of Reservoir Induced Seismicity (RIS) in NE Brazil., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8255, https://doi.org/10.5194/egusphere-egu24-8255, 2024.

EGU24-8465 | Orals | ESSI3.5

ENVRI-Hub-NEXT, the open-access platform of the environmental sciences community in Europe 

Ulrich Bundke, Daniele Bailo, Thierry Carval, Luca Cervone, Dario De Nart, Claudio Dema, Tiziana Ferrari, Andreas Petzold, Peter Thijsse, Alex Vermeulen, and Zhiming Zhao

Easy and fast access to reliable, long-term, and high-quality environmental data is fundamental for advancing our scientific understanding of the Earth system, including its complex feedback mechanisms, as well as for developing mitigation and adaptation strategies, for fact-based decision-making, and for the development of environment-friendly innovations. In response to the continuously growing demand for environmental scientific knowledge, the ESFRI-listed environmental research infrastructures (ENVRIs/RIs) in Europe have formed a strong community of principal producers and providers of environmental research data and services from the four subdomains of the Earth system (Atmosphere, Marine, Solid Earth and Biodiversity/Ecosystems) through the cluster projects ENVRI (2011-2014), ENVRIplus (2015-2019), and ENVRI-FAIR (2019-2023). The further integration of ENVRIs across the subdomains is considered critical for leveraging the full potential of the ENVRI cluster for integrated environmental research. This step will be taken by ENVRI-Hub NEXT.

To transform the challenging task of integrated Earth observation into a concept towards a global climate observation system, the World Meteorological Organisation (WMO) has specified a set of Essential Climate Variables (ECV) relevant for the continuous monitoring of the state of the climate. ECV datasets provide the empirical evidence needed to understand and predict the evolution of climate, guide mitigation and adaptation measures, assess risks, enable attribution of climatic events to the underlying causes, and underpin climate services. ENVRIs are critical for monitoring and understanding changes in ECVs, as has been identified by the ESFRI Strategy Working Group on Environment in their recent Landscape Analysis of the Environment Domain.

The recently finished cluster project ENVRI-FAIR has launched an open access hub for interdisciplinary environmental research assets utilising the European Open Science Cloud (EOSC). The ENVRI-Hub is designed as a federated system to harmonise subdomain- or RI-specific access platforms and offers a user-centered platform that simplifies the complexity and diversity of the ENVRI landscape while preserving the structure of the individual RIs needed to fulfil the requirements of their designated communities. Building on the ENVRI-Hub, ENVRI-Hub NEXT aims at creating a robust conceptual and technical framework that will empower the ENVRI Science Cluster to provide interdisciplinary services that enable cross-RI exploitation of data, guided by the science-based framework of ECVs.

This presentation will summarise the status of the ENVRI-HUB and the plans for ENVRI HUB-NEXT.

Acknowledgement:

ENVRI-HUB-NEXT has received funding from the European Union’s Horizon Europe Framework Programme under grant agreement No 101131141.

ENVRI-FAIR has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824068 101131141.

This work is only possible with the collaboration of the ENVRI-HUB-NEXT partners and thanks to the joint efforts of the whole ENVRI-Hub team.

How to cite: Bundke, U., Bailo, D., Carval, T., Cervone, L., De Nart, D., Dema, C., Ferrari, T., Petzold, A., Thijsse, P., Vermeulen, A., and Zhao, Z.: ENVRI-Hub-NEXT, the open-access platform of the environmental sciences community in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8465, https://doi.org/10.5194/egusphere-egu24-8465, 2024.

EGU24-9244 | Orals | ESSI3.5

Analysing open climate data - a case study using the MATLAB Integration for Jupyter on the ENES Data Space environment 

Kostas Leptokaropoulos, Shubo Chakrabarti, and Fabrizio Antonio

The increasing volume and complexity of Earth and environmental data requires an efficient, interdisciplinary collaboration between scientists and data providers. This can be achieved by utilising research infrastructures providing advanced e-services exploiting data integration and interoperability, seamless machine-to-machine data exchange and HPC/ cloud facilities.  

In this contribution we will present a case study of geodata import, analysis and visualization, carried out on the ENES Data Space (https://enesdataspace.vm.fedcloud.eu), a cloud-enabled data science environment for climate data analysis built on top of the European Open Science Cloud (EOSC) Compute Platform. After joining the service by using an institutional or social media account, the site users can launch JupyterLab where they have access to a personal workspace as well as compute resources, tools and ready-to-use climate datasets, comprising past data recordings and future projections, mainly from the CMIP (Coupled Model Intercomparison Project) international effort. In this example, global precipitation data from CMCC experiments will be used. The analysis will be carried out within the ENES workspace in two different ways:

First, we will launch MATLAB Online from a web browser directly from the ENES Data Space JupyterLab where a Live Script (.mlx) will import, filter, and manipulate the data, create maps, compare results and perform hypothesis testing to evaluate the statistical significance of different outcomes. Live Scripts are notebooks that allow clear communication of research methods and objectives, combining data, hyperlinks, text and code and can include UI (User Interface) tools for point-and-click data processing and visualization, without the need for advanced programming skills.

Second, we will demonstrate the same process running the MATLAB kernel from a Jupyter notebook (.ipynb) in the same JupyterLab.

In both cases results can be exported in multiple formats (e.g., PDF, markdown, LaTeX, etc.), downloaded and shared with other researchers, students, and fellow educators. The entire process is carried out in MATLAB within the ENES Data Space environment with no need to install software or download data on the users’ local (non-cloud) devices.

How to cite: Leptokaropoulos, K., Chakrabarti, S., and Antonio, F.: Analysing open climate data - a case study using the MATLAB Integration for Jupyter on the ENES Data Space environment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9244, https://doi.org/10.5194/egusphere-egu24-9244, 2024.

EGU24-9486 | ECS | Posters on site | ESSI3.5

Best practices for using and reporting subsurface geological/geophysical data in defining and documenting seismogenic faults. 

Giuseppe Vico, Rita Chiara Taccone, Francesco Emanuele Maesano, Mara Monica Tiberti, and Roberto Basili

Earthquakes of engineering significance (magnitude 5 and above) are generated by pre-existing, relatively mature geological faults. These faults generally span a length from a few to several tens or hundreds of kilometers and can break the entire Earth’s crust.   

Defining the three-dimensional configuration of such seismogenic faults is crucial for developing applications for earthquake hazard analyses at different spatial scales and, in turn, contributing robust information to promoting earthquake risk mitigation strategies.

The reconstruction of geological fault surfaces is a typical multidisciplinary study involving a large variety of data types and processing methods that, inevitably, imply various degrees of geometric simplifications depending on the available data. Among them, the most powerful, although expensive, approaches are the techniques developed for hydrocarbon exploration, namely seismic reflection (2D-3D) data combined with logs of drilled wells, which can illuminate the Earth’s subsurface at several kilometers depth. The mining and oil and gas industries have historically collected a large amount of this data, which remained classified depending on the regulations of the country from which they obtained the license for exploration. As time passes, and with the waning of fossil fuel exploitation, the exploration licenses expire or are not renovated, and more of such data becomes available to amalgamate with data collected by research institutions or public/private ventures using public funding. 

Despite the vast literature on and applications of hydrocarbon exploration data, no standard procedure exists for documenting the use of such data in characterizing seismogenic faults. In this respect, scientists face challenges posed by the intersection of industry data with public research outputs, with important societal implications and barriers to ensuring FAIRness. To this end, we devised a workflow detailing the best practices to follow in the various steps geologists undertake in using hydrocarbon exploration data, starting from the source of the raw/processed data (public vs confidential) and ending with the final geological fault model. The workflow output is then ready to be integrated with the information and data from other scientific disciplines (e.g., seismology, paleoseismology, tectonic geomorphology, geodesy, geomechanical modeling, earthquake statistics) to obtain the most reliable seismogenic fault model. As proof of concept, we will present a simplified version of a software tool that guides the user in incorporating the workflow's various elements into a structured database of seismogenic faults.

How to cite: Vico, G., Taccone, R. C., Maesano, F. E., Tiberti, M. M., and Basili, R.: Best practices for using and reporting subsurface geological/geophysical data in defining and documenting seismogenic faults., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9486, https://doi.org/10.5194/egusphere-egu24-9486, 2024.

EGU24-10536 | Posters on site | ESSI3.5

CDGP data center, new data for interdisciplinarity research  

Salsabyl Benlalam, Benoit Derode, Fabien Engels, Marc Grunberg, and Jean Schmittbuhl

The Data Center for Deep Geotermal Energy (CDGP-Centre de Données de Géothermie Profonde, https://cdgp.u-strasbg.fr/) was launched in 2016 and managed by Interdisciplinary Thematic Institute for Geosciences for the energy system Transition (ITI GeoT, https://geot.unistra.fr/), with the purpose of archiving, preserving and distributing deep geothermal data in the Alsace region (France) for the scientific community and R&D activities. The CDGP is furthermore an internal node of EPOS TCS Anthropogenic Hazards (https://www.epos-eu.org/tcs/anthropogenic-hazards), the data provided concerning geothermal sites in Alsace are therefore also available on the EPISODES platform (https://episodesplatform.eu/), which enables users to process and analyze the data they download. The CDGP collects high-quality data from different phases of deep geothermal projects, especially from exploration and development phases. The aim of this service is to provide downloadable multi-disciplinary data, ranging from industrial hydraulic information to seismic records and catalogs, through geological logs and fault maps for example. The data are thoroughly filtered, controlled and validated by analysts, and are grouped into “episodes”, referring to a set of relevant geophysical data correlated over time, and establishing links between anthropogenic seismicity and an industrial activity.

As part of the European Geo-INQUIRE project (GA n. 101058518, https://www.geo-inquire.eu/), we are now expanding the types of data that we distribute. The raw data (RINEX) from GNSS stations that are monitoring the surface deformation around geothermal site are now available on the website. In a next step, we will add complementary information and metadata to our provided database (e.g. precise position/velocity/strain) thanks to our collaboration with EPOS TCS GNSS. We are currently in the process of developing strategies with EPOS TCS GIM (Geological Information and Modeling)  to provide geological maps and borehole data for the “episodes” sites. The aim is to use the TCS GIM services currently under development and benefit of the synergy from the various leading projects.

Specific procedures have also been implemented since the beginning of the project to respect international requirements for data management. FAIR recommendations, for example, are followed to distribute data that are Findable, Accessible, Interoperable, and Reusable. 

How to cite: Benlalam, S., Derode, B., Engels, F., Grunberg, M., and Schmittbuhl, J.: CDGP data center, new data for interdisciplinarity research , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10536, https://doi.org/10.5194/egusphere-egu24-10536, 2024.

EGU24-10742 | Posters on site | ESSI3.5

EU-financed transnational access in Geo-INQUIRE: an opportunity for researchers to develop leading-edge science at selected test-beds and research facilities across Europe. 

Shane Murphy, Gaetano Festa, Stefano Lorito, Volker Röhling, Fabrice Cotton, Angelo Strollo, Marc Urvois, Andrey Babeyko, Daniele Bailo, Jan Michalek, Otto Lange, Javier Quinteros, Mariusz Majdanski, Iris Christadler, 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. 

The Geo-INQUIRE Transnational Access (TA) covers both virtual and on-site access to a variety of state of the art laboratories, facilities, experimental sites (testbeds) and computational resources with the aim of enabling the development of excellent ground-breaking science. Six research infrastructures located across Europe, referred to as “testbeds”, will provide locations for users to perform experiments in a variety of environments from the Earth’s surface (both on land and at sea) to the subsurface; over different spatial scales: from small-scale experiments in laboratories to kilometric submarine fibre cables. These sites are: 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). In addition, ECCSEL-ERIC is providing access to 5 of its research facilities focussing on CO2 Capture, Utilisation, Transport and Storage. The facilities providing access are: Svelvik CO2 Field Lab (Norway), PITOP Borehole Geophysical Test Site (Italy), Sotacarbo Fault Laboratory (Italy), Catenoy experimental site and gas-water-rock interaction Laboratory in Oise (France) and the Mobile Seismic Array (the Netherlands) which is fully mobile and can be deployed anywhere in the world. 

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. 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-based or numerical experiments with the aim of advancing scientific knowledge of Earth processes while fostering cross-disciplinary research across Europe. 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. 

To be granted, researchers submit a proposal to the TA calls that will be issued three times during the project life. The first call was launched on the 9th January. Calls will be advertised on the Geo-INQUIRE website https://www.geo-inquire.eu/ and through the existing community channels.

How to cite: Murphy, S., Festa, G., Lorito, S., Röhling, V., Cotton, F., Strollo, A., Urvois, M., Babeyko, A., Bailo, D., Michalek, J., Lange, O., Quinteros, J., Majdanski, M., Christadler, I., Prestes, M., and Weege, S.: EU-financed transnational access in Geo-INQUIRE: an opportunity for researchers to develop leading-edge science at selected test-beds and research facilities across Europe., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10742, https://doi.org/10.5194/egusphere-egu24-10742, 2024.

EGU24-11000 | Posters on site | ESSI3.5

Multidisciplinary integration of FAIR Research Infrastructures in the Geo-INQUIRE initiative: the EPOS – EMSO case 

Kety Giuliacci, Daniele Bailo, Jan Michalek, Rossana Paciello, Valerio Vinciarelli, Claudio Goffi, Angelo Strollo, Fabrice Cotton, Harald Nedrebø, Sven Peter Näsholm, Quentin Brissaud, Tina Kaschwich, Enoc Martinez, Aljaz Maslo, Volker Röhling, Olivier Frezot, Javier Quinteros, Kuvvet Atakan, and Wolfgang zu Castell

In the last decade, the scientific community has witnessed growing emphasis on data integration. The primary objective is to harness multidisciplinary data and resources to drive novel methodological approaches and scientific breakthroughs. Among the projects that have emerged in response to this trend is the Geosphere INfrastructures for QUestions into IntegratedREsearch (Geo-INQUIRE, https://www.geo-inquire.eu/).

Geo-INQUIRE was launched in October 2022 and comprises a unique consortium of 51 partners, including prominent national research institutes, universities, national geological surveys, and European consortia. Geo-INQUIRE is dedicated to surmounting cross-domain challenges, particularly those pertaining to land-sea-atmosphere environments. To accomplish this mission, Geo-INQUIRE is committed to consolidating the resources and capabilities of key research infrastructures (RIs) specializing in geosphere observations. These RIs include EPOS, EMSO, ARISE, ECCSEL, and ChEESE.

By providing access to its expanded collection of data, products, and services, Geo-INQUIRE empowers the upcoming generation of scientists to conduct cutting-edge research that addresses complex societal challenges from a multidisciplinary viewpoint. This encourages the utilization of these resources to foster curiosity-driven research endeavors.

To harmonize and prepare the data produced by these different RIs for integration, substantial efforts have been undertaken, which required cataloging all installations provided by the data providers, their analysis, and assessment concerning the maturity level required for FAIR (Findable, Accessible, Interoperabile, and Reusable) data integration. In addition, dedicated seminars focused on data integration were carried out to boost the FAIR data provision process. Technical activities have been carried out to achieve cross-RI integration. In this contribution, we demonstrate and exemplify one such integration: between EMSO (https://emso.eu/) and EPOS (https://www.epos-eu.org/). This has been achieved on multiple fronts, including metadata and services.

The successful integration of metadata and services was made possible by adopting the EPOS-DCAT Application Profile (https://epos-eu.github.io/EPOS-DCAT-AP/v3/), allowing an intelligent system like the EPOS platform (https://www.ics-c.epos-eu.org/) to access the EMSO services seamlessly. Work is currently underway to develop software that will enable the visualization of heterogeneous time series data from EMSO within the integrated framework, a crucial step to achieve full data integration.

How to cite: Giuliacci, K., Bailo, D., Michalek, J., Paciello, R., Vinciarelli, V., Goffi, C., Strollo, A., Cotton, F., Nedrebø, H., Näsholm, S. P., Brissaud, Q., Kaschwich, T., Martinez, E., Maslo, A., Röhling, V., Frezot, O., Quinteros, J., Atakan, K., and zu Castell, W.: Multidisciplinary integration of FAIR Research Infrastructures in the Geo-INQUIRE initiative: the EPOS – EMSO case, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11000, https://doi.org/10.5194/egusphere-egu24-11000, 2024.

EGU24-11659 | Posters virtual | ESSI3.5

Standardization of geospatial analysis ready data via OGC and ISO  

Liping Di, Eugene Yu, Liying Guo, Patrick Quinn, and Joshua Lieberman

Geospatial data are data with location information. Geospatial data are very diverse and widely used in various socioeconomic applications and decision makings. Typically, geospatial data obtained from data providers needs to go through a long chain of pre-processes and quality measures before the data can be analyzed for a specific application. For a specific type of geospatial data, many of the pre-processes and quality measures are common to different data users regardless the data applications. It is possible to pre-apply those common pre-processes and quality measures to the geospatial data so that the repetitive preprocesses can be avoided, the pre-process chain at user side can be significantly shorten, and the data is more ready for analysis. The geospatial data, which has been pre-applied with a set of pre-processes to meet certain quality specifications and be ready for analysis in applications, are called geospatial analysis ready data (ARD). In the satellite remote sensing domain, the Committee on Earth Observation Satellites (CEOS) has defined the CEOS Analysis Ready Data (CEOS-ARD) as satellite remote sensing data that have been processed to a minimum set of requirements and organized into a form that allows immediate analysis with a minimum of additional user effort and interoperability both through time and with other datasets. CEOS has set a number of ARD product family specifications (PFS) and encouraged its member space agencies to produce CEOS ARD PFS compliant products. However, CEOS ARD PFS are limited to satellite remote sensing data and are not the recognized international standards, which prevents them from being widely accepted and adopted by the broad geospatial community. Other geospatial communities, such as ARD.Zone, are also developing their ARD concepts.  Formal ARD standardization through authoritative international standard bodies is necessary to achieve broad uptake, particularly by the commercial sector, promote widely acceptance of the standardized concept, and help avoid the divergence that can be caused by various groups working towards different interpretations of the concept. Therefore, a joint effort between ISO TC 211 and the Open Geospatial Committee (OGC) was officially formed in May 2023 to set international ARD standards through forming the broadest consensus within the geospatial community. ISO has designated the geospatial ARD standards as ISO 19176, and the first one to be developed is ISO 19176-1: Geographic information —Analysis Ready Data — Part 1: Framework and Fundamentals. In addition, OGC, through its testbed and pilot initiatives, has been evaluating the applicability, advantage, and gaps of using existing geospatial ARD products from various sources in different applications. The findings and lessons learned from the evaluation are reinforcing the development of ISO 19176.  This presentation will report the progress so far on the development of ISO 19176-1 and recapture the findings from ARD activities in OGC Testbed 19. It will discuss the joint ISO/OGC ARD standard development process, the ISO 19176-1 development timeline, the ARD framework and UML models defined in ISO 19176-1, the findings from OGC Testbed 19 on ARDs, and the future workplan.

How to cite: Di, L., Yu, E., Guo, L., Quinn, P., and Lieberman, J.: Standardization of geospatial analysis ready data via OGC and ISO , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11659, https://doi.org/10.5194/egusphere-egu24-11659, 2024.

The use of airborne cloud imaging probes has resulted in decades of in situ particle-by-particle data taken across the gamut of pristine and anthropogenically-modified cloud types around the globe. Image data from such probes is recorded in proprietary and instrument- or system-specific formats. Binary formats have evolved to minimise the stress on, now possibly outdated, hardware and communication systems that must operate in the difficult aircraft environment. This means that there is a significant knowledge and technical barrier to new users, particularly for those that are not from fields that have traditionally used such cloud data. Processed image data is generally available, however this precludes the application of more advanced or specialised processing of the raw data. For example, historical cloud campaigns of the 1970s and 80s used imaging probes for cloud microphysical measurements at a time when satellite measurements of those regions were sparse or nonexistent. Fields such as atmospheric processes modelling, climate modelling, and remote sensing may well benefit by being able to ingest raw cloud particle data into their processing streams to use in new analyses and to address issues from a perspective not normally used by those in the cloud measurement community.

The Single Particle Image Format (SPIF) data standard has been designed to store decoded raw binary data in netCDF4 with a standardised vocabulary in accordance with FAIR Guiding Principles. This improves access to this data for users from a wide range of fields and facilitates the sharing, refinement, and standardisation of data processing routines. An example is the National Research Council of Canada (NRC) Single Particle Image Format (SPIF) conversion utility which converts binary data into SPIF files. In a similar fashion to  the Climate and Forecast (CF) Conventions, SPIF defines a minimum vocabulary (groups, variables, and attributes) that must be included for compliance while also allowing extra, non-conflicting data to be included. 

The ability to easily check files for compliance to a data standard or convention is an important component of building a sustainable and community supported data standard. We have developed a Python package called vocal as a tool for managing netCDF data product standard vocabularies and associated data product specifications. Vocal projects define standards for netCDF data, and consist of model definitions and associated validators. Vocal then provides a mapping from netCDF data to these models with the Python package pydantic being used for compliance checking of files against the standard definition. 

We will present the vocal package and the SPIF data standard to illustrate its use in building standard compliant files and compliance-checking of SPIF netCDF files.

How to cite: Nott, G. and Sproson, D.: An Open Data Standard for Cloud Particle Images and Reference Software to Produce and Validate Compliant Files, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11901, https://doi.org/10.5194/egusphere-egu24-11901, 2024.

EGU24-12102 | Posters virtual | ESSI3.5 | Highlight

A preliminary analysis of a crowdsourcing platform for participatory assessment of urban landscapes by university students using GIS 

Nikos Mamassis, Romanos Ioannidis, Christos Daskalakis, Fotis Loukidis-Andreou, Margarita Zakynthinou-Xanthi, Lucas Gicquel, Lucile Samah--Ribeiro, Filio Iliopoulou, G.-Fivos Sargentis, and Kontantinos Moraitis

The fields of information technology and geoinformatics have experienced rapid growth and widespread public adoption, with technologies like crowdsourcing facilitating advances in how the public can communicate with scientific communities and even contribute valuable data.

However, there is still hesitation in actively engaging the public in environmental or landscape related studies. The start contract of availability of crowdsourcing technologies and lack of use thereof is particularly noticeable in university education, where the technological potential of smartphones, widely owned and used by students, remains largely untapped for educational and research purposes. This study is part of a larger exploration of the potential of engaging students in participatory georeferenced landscape assessment, aiming to advance relevant environmental research and also make education in landscape and architecture more interactive and synergistic.

Starting from an initial theoretical investigation our work proceeded to the examination of the developed ideas in practice. A dedicated crowdsourcing mobile application was developed and tested as a pilot study with a small number of students, before proceeding to the inclusion of large numbers of students which is the end goal of the ARCHIMAP crowdsourcing project. This initial “test” targeted both potential practical challenges as well as software and generated-data related challenges. To this aim the Lycabettus hill and surrounding neighborhoods were investigated as a case study. Students were given the application and their interactions with it were recorded in detail, tracking their movement and location, recording their landscape and architecture assessments and evaluating the technical performance of the application.

Other than the observation of technical and functional challenges the study also initiated a brief investigation of the potential utility of the results. This was carried out by implementing a conventional method of analysis of landscapes, the so called ULQI (Urban Landscape Quality Index) and investigating its correlation and potential synergy with the results submitted by the students through the novel crowdsourcing app for georeferenced landscape assessment.

The results demonstrated that the developed app was both functional and useful and could therefore be shared to more students of NTUA, with expected benefits both for the educational processes but also for the scientific research of the institution on landscape quality.

How to cite: Mamassis, N., Ioannidis, R., Daskalakis, C., Loukidis-Andreou, F., Zakynthinou-Xanthi, M., Gicquel, L., Samah--Ribeiro, L., Iliopoulou, F., Sargentis, G.-F., and Moraitis, K.: A preliminary analysis of a crowdsourcing platform for participatory assessment of urban landscapes by university students using GIS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12102, https://doi.org/10.5194/egusphere-egu24-12102, 2024.

EGU24-12230 | Posters on site | ESSI3.5

Semantic Interoperability Profiles as knowledge base for semantic solutions 

Barbara Magagna, Marek Suchánek, and Tobias Kuhn

Central for research is the capability to build on existing research outcomes and to aggregate data from different sources to create new research findings. This is particularly true for environmental research, which tries to face global challenges like climate change and biodiversity loss by integrating diverse long-term monitoring and experimental data.

Interoperability is the ability of computer systems to exchange information but to get a shared understanding of the meaning of that information semantic interoperability is required. Shared understanding between all parties involved can be achieved using common standards like vocabularies, metadata and semantic models.

But how can researchers find out which standards are used and by whom? FAIR Implementation Profiles (FIPs), co-developed by GO FAIR Foundation and ENVRI-FAIR in 2020 (https://doi.org/10.1007/978-3-030-65847-2_13) and used by more than 120 communities so far like ENVRIs and WorldFAIR (see also https://fairdo.org/wg/fdo-fipp/), might be a good source of knowledge. This socio-technical approach drives explicit and systematic community agreements on the use of FAIR implementations including domain-relevant community standards, called FAIR-Enabling Resources. The FIP Wizard (https://fip-wizard.ds-wizard.org/) is implemented through the DSW open-source tool as a user interface by which the researcher is asked to answer questions related to each of the Principles by selecting FERs expressed as nanopublications. A nanopublication (https://nanopub.net/) is represented as a machine-interpretable knowledge graph and includes three elements: assertions, provenance, and publication info where in the context of FIPs the assertion contains essential metadata about a FER.

Using the same approach and technology but focusing on semantic interoperability aspects the Semantic Interoperability Profile (SIP) was developed in the context of the EOSC Semantic Interoperability Task Force to interview semantic or data management experts involved in research projects or infrastructures to collectively contribute to a knowledge base of interoperability solutions (https://doi.org/10.5281/zenodo.8102786). The SIP focuses on standards used to implement the Principle F2 (metadata) and the Interoperability Principles (I1, I2, I3 related to semantic artefacts) but queries also about the services used to generate, edit, publish, and transform them, altogether called FAIR Supporting Resources (FSRs). The survey is an ongoing effort and everybody can contribute to it via the SIP Wizard (https://sip-wizard.ds-wizard.org/). In summary, a SIP is a machine-interpretable collection of resources chosen by a community whereby the collection can be made specific for a data type and a semantic interoperability case study. 

FAIR Connect (https://fairconnect.pro/) is being developed to provide a user-friendly, graphics rich dashboard and search engine on nanopublications of type FSR. It will enable users to find FSRs based on its type or label and will inform at the same time by which communities it is used. In a future iteration it will also enable filters on data types and case studies.   

How to cite: Magagna, B., Suchánek, M., and Kuhn, T.: Semantic Interoperability Profiles as knowledge base for semantic solutions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12230, https://doi.org/10.5194/egusphere-egu24-12230, 2024.

EGU24-12844 | Orals | ESSI3.5

EPOS Seismology: Connecting Communities, Advancing Research, and Paving the Way Forward 

Margarita Segou, Kiratzi Anastasia, Carlo Cauzzi, Susana Custódio, Rémy Bossu, Florian Haslinger, Laurentiu Danciu, Fatemeh Jalayer, Roberto Basili, Irene Molinari, and Adrien Oth

We present the dynamic landscape of EPOS Seismology, a Thematic Core Service consortium at the foundation of the European Plate Observing System (EPOS) infrastructure. Cultivated over the past decade through partnerships with prominent pan-European seismological entities,  the ORFEUS (Observatories and Research Facilities for European Seismology), EMSC (Euro-Mediterranean Seismological Center), and EFEHR (European Facilities for Earthquake Hazard and Risk), EPOS Seismology stands out as a collaborative governance framework. Facilitating the harmonized interaction between seismological community services, EPOS, and its associated bodies, endeavors to widen the collaboration to include data management, product provision, and the evolution of new seismological services.

Within the EPOS Delivery Framework, EPOS Seismology pioneers a diverse array of services, fostering open access to a wealth of seismological data and products while unwaveringly adhering to the FAIR principles and promoting open data and science. These services encompass the archival and dissemination of seismic waveforms of  24,000 seismic stations, access to pertinent station and data quality information, parametric earthquake data spanning recent and historical events, as well as advanced event-specific products such as moment tensors and source models together with reference seismic hazard and risk for the Euro-Mediterranean region. 

The seismological services are seamlessly integrated into the interoperable centralized EPOS data infrastructure and are openly accessible through established domain-specific platforms and websites. Collaboratively orchestrated by EPOS Seismology and its participating organizations, this integration provides a cohesive framework for the ongoing and future development of these services within the extensive EPOS network. The products and services support the transformative role of seismological research infrastructures, showcasing their pivotal contributions to the evolving narrative of solid Earth science within the broader context of EPOS.

How to cite: Segou, M., Anastasia, K., Cauzzi, C., Custódio, S., Bossu, R., Haslinger, F., Danciu, L., Jalayer, F., Basili, R., Molinari, I., and Oth, A.: EPOS Seismology: Connecting Communities, Advancing Research, and Paving the Way Forward, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12844, https://doi.org/10.5194/egusphere-egu24-12844, 2024.

EGU24-12891 | Posters on site | ESSI3.5

Multidisciplinary analysis of near fault observatory data: example from the Alto Tiberina fault (Northern Apennines, Italy) 

Enrico Serpelloni, Lucia Zaccarelli, Licia Faenza, Antonio Caracausi, Carlos Almagro Vidal, Francesco Pintori, Eugenio Mandler, and Lauro Chiaraluce

Earthquakes, intricate natural events spanning multiple spatio-temporal scales, necessitate a comprehensive understanding of the physical and chemical processes driving a broad spectrum of fault slip modes. To achieve this, the acquisition of multidisciplinary and dense datasets is imperative. Near Fault Observatories (NFOs) play a pivotal role by offering spatially and temporally dense, high-precision near-fault data, fostering the generation of novel observations and innovative scientific insights. However, the integration and interpretation of diverse datasets from various disciplines (geophysics, geochemistry, hydrology, etc.) present challenges. These datasets often consist of time-series depicting the temporal evolution of different parameters, sampling diverse temporal and spatial scales, depths, and the distinct or cumulative effects of various multiscale processes. In this presentation, we share outcomes from the INGV multidisciplinary project MUSE: M​ultiparametric and m​U​ltiscale ​S​tudy of ​Earthquake preparatory phase in the central and northern Apennines. Our emphasis lies in showcasing the approaches developed to analyze, integrate, and extract new knowledge from the EPOS Near Fault Observatory TABOO. This state-of-the-art observatory, managed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), boasts a dense network with an average inter-distance of approximately 5 km between multidisciplinary sensors. These sensors, deployed at the surface and within shallow boreholes, include seismometrical, geodetic, geochemical, hydrological, and strain stations. The project's core objective is to unravel the interconnections between different observables and explore the causal relationships among them. We will present the datasets, the methods employed, and discuss the significance of considering the interaction between fluid and solid geophysical processes in comprehending earthquake phenomena. Additionally, we will articulate the potential innovative scientific products that can arise from this research, contributing to a deeper understanding of earthquake processes.

How to cite: Serpelloni, E., Zaccarelli, L., Faenza, L., Caracausi, A., Almagro Vidal, C., Pintori, F., Mandler, E., and Chiaraluce, L.: Multidisciplinary analysis of near fault observatory data: example from the Alto Tiberina fault (Northern Apennines, Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12891, https://doi.org/10.5194/egusphere-egu24-12891, 2024.

EGU24-12925 | ECS | Orals | ESSI3.5

SESAME: Software tools for integrating Human - Earth System data 

Abdullah Al Faisal, Maxwell Kaye, and Eric Galbraith

Human activities have extensively modified over 70% of Earth’s land surface and two-thirds of marine environments through practices such as agriculture, industrialization, and urbanization. These activities have resulted in a wide range of environmental problems, including biodiversity loss, water pollution, soil erosion, and climate change. However, human data is often available only in tabular form, is difficult to integrate with natural Earth variables, and can pose significant challenges when trying to understand the complex integration between human activities and natural Earth systems. On the other hand, scientific datasets, which are spread across websites, come in different formats, may require preprocessing, use different map projections, spatial resolution, and non-standard units, are difficult for both beginner and experienced researchers to access and use due to their heterogeneity. This discrepancy hinders our understanding of complex interactions between human activities and the environment.

To bridge this gap, we have created the Surface Earth System Analysis and Modelling Environment (SESAME) software and dataset package, which aims to solve the problem of fragmented and difficult-to-use human-Earth data. It can handle various data formats and generate a standardized gridded dataset with minimal output. SESAME is a software infrastructure that automatically transforms five input data types (raster, point, line, polygon, and tabular) into standardized desired spatial grids and stores them in a netCDF file. The ability of a netCDF file to store multidimensional timeseries data makes it an ideal platform for storing complex global datasets. SESAME utilizes the dasymmetric mapping technique to transform jurisdiction-level tabular data into a gridded layer proportional to the corresponding surrogate variable while considering changes in country boundaries over time. It maintains the consistency between input and output data by calculating the global sum and mean.

By converting human tabular data into a gridded format, we can facilitate comprehensive and spatially explicit analyses, advancing our understanding of human-Earth systems and their complex interactions. These gridded datasets are intended to be used as inputs to a range of different Earth system models, potentially improving the simulation and evaluation of scenarios and leading to more informed and strategic future policy decisions.

How to cite: Faisal, A. A., Kaye, M., and Galbraith, E.: SESAME: Software tools for integrating Human - Earth System data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12925, https://doi.org/10.5194/egusphere-egu24-12925, 2024.

EGU24-12962 | Posters on site | ESSI3.5

The Marble climate informatics platform: data discovery and data access 

Deepak Chandan, Misha Schwartz, and Steve Easterbrook

Advances in remote sensing and computing infrastructure, and demands of modern climate research are driving the production of new climate datasets at a breathtaking pace. It is increasingly felt by researchers, that the growing volume of climate datasets is challenging to store, analyze or generally "shepherd" through their analysis pipelines. Quite often, the ability to do this is limited to those with access to government or institutional facilities in wealthier nations, raising important questions around equitable access to climate data.

The Data Analytics for Canadian Climate Services (DACCS) project has built a cloud based network of federated nodes, called Marble, that allows anyone seeking to extract insights from the large volumes of climate data to undertake their study without concerning themselves with the logistics of acquiring, cleaning and storing data. The aspiration for building this network is to provide a low-barrier entry not only to those working in core climate change research, but also to those involved in climate mitigation, resilience and adaptation work and to policy makers, non-profits, educators and students. Marble is one of the platforms selected to contribute to the 'Open Science Platform' component of the OGC’s OSPD initiative.

The user-facing aspect of the platform is comprised of two components: (i) the Jupyter compute environment and (ii) the data server and catalogue. Here, we focus on the latter and present details of the infrastructure, developed on top of proven open-source software and standards (e.g. STAC), that allows for discovery and access of climate datasets stored anywhere on the network by anyone on the network. We will also discuss the publication capability of the platform that allows a user to host their own data on the network and make it quickly available to others.

How to cite: Chandan, D., Schwartz, M., and Easterbrook, S.: The Marble climate informatics platform: data discovery and data access, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12962, https://doi.org/10.5194/egusphere-egu24-12962, 2024.

EGU24-13367 | Orals | ESSI3.5

EPOS-GNSS – Operational Advancements in EPOS GNSS Data and Product Services 

Rui Fernandes, Carine Bruyninx, Luis Carvalho, Paul Crocker, Gael Janex, Juliette Legrand, Jean-Luc Menut, Anne Socquet, and Mathilde Vergnolle and the EPOS-GNSS Contributors

As the European Plate Observing System (EPOS) transitions into its Operational Phase, the EPOS-GNSS Thematic Core Service continues to play a pivotal role in managing and disseminating Global Navigation Satellite Systems (GNSS) data and products across Europe. As EPOS-GNSS advances into its operational stage, the commitment to organizational effectiveness and technical innovation has been reinforced. This ensures that EPOS-GNSS continues to provide valuable services and products tailored for Solid Earth research applications.

In this presentation, we highlight key developments achieved during the pre-operational phase and the ongoing operational status where evolution continues to be a central component for the EPOS-GNSS community. The four critical pillars of EPOS-GNSS are discussed: (a) Governance – we have Intensified efforts to ensure the representation and recognition of the entire community as well as deepening collaboration with data providers, end-users, and pan-European infrastructures, notably EUREF; (b) Metadata and Data – the dissemination of quality controlled GNSS data and associated metadata has been integrated into the operational framework; (c) Products – internally consistent GNSS solutions of dedicated products (time-series, velocities, and strain-rates) using state-of-art methodologies; and (d) Software – GLASS, the dedicated software package that facilitates the dissemination of GNSS data and products using FAIR principles while maintaining rigorous quality control procedures through four different GNSS dedicated web portals and the EPOS Integrated Core Services Data Portal.

Finally, we also present some examples of the usage of the EPOS-GNSS Data Products in multi-, inter-, and trans-disciplinaries studies where we exhibit the importance of the geodetic information for Solid Earth studies particularly in an integrated environment as promoted by EPOS.

How to cite: Fernandes, R., Bruyninx, C., Carvalho, L., Crocker, P., Janex, G., Legrand, J., Menut, J.-L., Socquet, A., and Vergnolle, M. and the EPOS-GNSS Contributors: EPOS-GNSS – Operational Advancements in EPOS GNSS Data and Product Services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13367, https://doi.org/10.5194/egusphere-egu24-13367, 2024.

EGU24-13654 | ECS | Posters on site | ESSI3.5

Federated Climate Research Software: improving data and workflow management for climate researchers 

Misha Schwartz, Deepak Chandan, and Steve Easterbrook

Climate researchers have access to astronomical amounts of data; but finding that data and downloading it so that it can be useful for research can be burdensome and expensive.

The team at Data Analytics for Canadian Climate Services (DACCS) is solving that problem by creating a new system for conducting climate research and providing the software to support it. The system works by providing researchers the tools to analyze the data where it’s hosted, eliminating the need to download the data at all.

In order to accomplish this, the DACCS team has developed a software stack that includes the following services:

- data hosting
- data serving (using OPeNDAP protocols)
- data search and cataloging
- interactive computational environments preloaded with climate analysis tools
- remote analysis tools (WPS and OGCAPI features)

Partner organizations can deploy this software stack and choose to host any data that they wish. This data then becomes available to every other participating organization, allowing them seamless access each others data without having to move it for analysis.

This system will allow researchers to more easily:

- discover available data hosted all over the world
- develop analysis workflows that can be run anywhere
- share their work with collaborators without having to directly share data

The DACCS team is currently participating in the Open Science Persistent Demonstrator (OSPD) initiative and we hope that this software will contribute to the ecosystem of earth science software platforms available today.

How to cite: Schwartz, M., Chandan, D., and Easterbrook, S.: Federated Climate Research Software: improving data and workflow management for climate researchers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13654, https://doi.org/10.5194/egusphere-egu24-13654, 2024.

EGU24-14052 | Orals | ESSI3.5

Who has got what where? FAIR-ly coordinating multiple levels of geophysical data products over distributed Research Infrastructures (RIs) to meet diverse computational needs and capabilities of users. 

Lesley Wyborn, Nigel Rees, Jo Croucher, Hannes Hollmann, Rebecca Farrington, Benjamin Evans, Stephan Thiel, Mark Duffett, and Tim Rawling

Modern research data processing pipelines/workflows can have quite complex lineages. Today, it is more than likely that a scientific workflow will rely on multiple Research Infrastructures (RIs), numerous funding agencies and geographically separate organisations to collect, produce, process, analyse and reanalyse primary and derivative datasets. Workflow components can include:

  • Shared instruments to acquire the data;
  • Separate research groups processing/calibrating field data and developing additional derived products;
  • Multiple repository infrastructures to steward, preserve and provide access to the primary data and resultant products sustainably and persistently; and
  • Different types of software and compute infrastructures that enable multiple ways to access and process the data and products, including in-situ access, distributed web services and simple file downloads.

In these complex workflows, individual research products can be generated through multiple levels of processing (L0-L4), as raw instrument data is collected by remote instruments (satellites, drones, airborne instruments, shared laboratory and field infrastructures) and is converted into more useful parameters and formats to meet multiple use cases. Each individual level of processing can be undertaken by different research groups using a variety of funding sources and RIs, whilst derivative products could be stored in different repositories around the globe.

An additional complexity is that the volumes and resolution of modern earth and environmental datasets is exponentially growing and many RIs can no longer store and process the volumes of primary data acquired. Specialised hybrid HPC/Cloud infrastructures with co-located datasets that allow for virtual in situ high volume data access are emerging. But these petascale/exascale infrastructures are not required for all use cases, and traditional small volume file downloads of evolved data products and images for local processing are all that many users need. 

At the core of many of these complex workflows are the primary, often high resolution observational dataset that can be in the order of terabytes and petabytes. Hence for transparent Open Science and to enable attribution to funders, collectors and repositories that preserve these valuable data assets, all levels of all derivative data products need to be able to trace their provenance back to these source datasets.

Using examples from the recently completed 2030 Geophysics Data Collection project in Australia (co-funded by AuScope, NCI and ARDC), this paper will show how original primary field acquired datasets and their derivative products can be accessible from multiple distributed RIs and government websites. They are connected using the FAIR principles and ensure that at a minimum, lineage and prehistory is recorded in provenance statements and linked using metadata elements such as ‘isDerivedFrom’ and DOIs. Judicious use of identifiers such as ORCIDs, RORs and DOIs links data at each level of processing with the relevant researchers, research infrastructure, funders, software developers, software etc. Integrating HPC centers that are colocated with large volume high resolution data infrastructures within complex and configurable research workflows is providing a key input to supporting next-generation earth and environmental research and enabling new and exciting scientific discoveries. 

How to cite: Wyborn, L., Rees, N., Croucher, J., Hollmann, H., Farrington, R., Evans, B., Thiel, S., Duffett, M., and Rawling, T.: Who has got what where? FAIR-ly coordinating multiple levels of geophysical data products over distributed Research Infrastructures (RIs) to meet diverse computational needs and capabilities of users., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14052, https://doi.org/10.5194/egusphere-egu24-14052, 2024.

EGU24-14521 | Orals | ESSI3.5

Towards a Digital Twin for the Alps to simulate water-related processes and geohazards for climate change adaptation strategies. 

Jean-Philippe Malet, Maxime Lamare, Lucia Guardamino, Jonas Viehweger, Stefania Camici, Luca Brocca, Silvia Barbetta, Bianca Bonaccorsi, Sara Modanesi, Angelica Tarpanelli, Matteo Dall’Amico, Federico Di Paolo, Nicolo Franceschetti, Clément Michoud, Thierry Oppikoffer, David Michéa, Floriane Provost, Aline Déprez, Michaelis Foumelis, and Philippe Bally

The Alps are the most densely populated mountain range in Europe and water resources play a central role in the socio-economic developments of the area (agriculture, tourism, hydropower production...). Furthermore, the Alps are particularly sensitive to the impacts of climate change and thus to hydro-meteorological hazards such as landslides, floods, droughts and glacier related processes, which are expected to increase in the near future, constitute a major threat to human activity. Indeed, over the last century, temperatures have risen twice as fast as the northern-hemisphere average, whereas precipitation has increased non-linearly and has become more discontinuous.

Because of the increasing pressure on human settlements and infrastructure, there is a strong priority for policy-makers to implement climate change adaptation strategies from the local to the regional scale. To support and improve the decision-making process, numerical decision support systems may provide valuable information derived from multi-parametric (in-situ sensors, satellite data) observations and models, linked to computing environments, in order to better manage increasing threats and weaknesses.

The main objective of the Digital Twin of Alps (eg. DTA) platform is to provide a roadmap for the implementation of future Digital Twin Components, with a focus on the Alpine chain. In this context, a demonstrator has been developed that enables a holistic representation of some of the major physical processes specific to the Alpine context, powered by a unique combination of Earth Observation data analytics, machine learning algorithms, and state-of-the-art hydrology and geohazard process-based models. Advanced visualization tools have been specifically implemented to favor easy exploration of the products for several categories of stakeholders.

The resulting Digital Twin Earth precursor will provide an advanced decision support system for actors involved in the observation and mitigation of natural hazards and environmental risks including their impacts in the Alps, as well as the management of water resources. For instance, through the demonstrator users can investigate the availability of water resources in terms of snow, soil moisture, river discharge and precipitation. Furthermore, it is possible to stress the system with scenario based options to see the impacts on the various hydrological drivers in terms of drought and flood probability. Finally, the user can assess flood hazard, forecast (with a daily leading time) the occurrence of shallow landslides (slope failure probability and material propagation) and predict the activity (e.g. velocity) of large deep-seated and continuously active landslides from extreme rain events through the use of a combination of physics- and AI-based simulation tools. Use cases in Northern Italy, South Swiss and South France are provided.

Finally, the user can visualise maps and time series of terrain motion products over several Alpine regions generated with advanced Earth Observation processing chains and services (GDM-OPT, Snapping) available on the Geohazards Exploitation Platform and the eo4alps-landslides App, providing a consistent description of Earth surface deformation (unstable slopes, large deep-seated landslides, ice glacier) for the period 2016-2022. The data, services and technologies used and developed for the platform will be presented.

How to cite: Malet, J.-P., Lamare, M., Guardamino, L., Viehweger, J., Camici, S., Brocca, L., Barbetta, S., Bonaccorsi, B., Modanesi, S., Tarpanelli, A., Dall’Amico, M., Di Paolo, F., Franceschetti, N., Michoud, C., Oppikoffer, T., Michéa, D., Provost, F., Déprez, A., Foumelis, M., and Bally, P.: Towards a Digital Twin for the Alps to simulate water-related processes and geohazards for climate change adaptation strategies., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14521, https://doi.org/10.5194/egusphere-egu24-14521, 2024.

EGU24-15585 | Orals | ESSI3.5

On the exploitation of the Sentinel-1 P-SBAS service within the EarthConsole® platform for unsupervised on-demand DInSAR processing  

Claudio De Luca, Massimo Orlandi, Manuela Bonano, Francesco Casu, Maddalena Iesuè, Michele Manunta, Giovanni Onorato, Mario Fernando Monterroso Tobar, Giancarlo Rivolta, and Riccardo Lanari

The current remote sensing scenario is nowadays characterized by an extensive exploitation of spaceborne Synthetic Aperture Radar (SAR) data to investigate the Earth surface dynamics. Such a request is rather well satisfied by the huge archives collected in the last ten years by the Copernicus Sentinel-1 (S1) SAR mission, which is distinguished by a “free and open” access data policy and a nearly global coverage acquisition strategy. In this regard, the most used space-borne geodetic technique for the investigation of the ground deformation is Differential Synthetic Aperture Radar Interferometry (DInSAR) that has largely demonstrated its effectiveness in measuring surface displacements in different scenarios. In particular, the advanced DInSAR method referred to as Parallel Small BAseline Subset (P-SBAS) approach has emerged as particularly effective to examine the temporal evolution of the detected surface displacements both in natural and anthropogenic hazard contexts, such as volcanoes, earthquakes, landslides and human-induced deformation due to mining activities, fluids exploitation, and large infrastructures construction.

In this context, the availability to the scientific community of algorithms and tools suitable to effectively exploit such huge SAR data archives, for generating value added products, is becoming crucial. To this aim, the P-SBAS algorithm has been released as an on-demand web-based tool by integrating it within the EarthConsole® platform, and currently contributes to the on-demand remote sensing component of the EPOSAR service. More in detail, EarthConsole® is a cloud-based platform supporting the scientific community with the development, testing, and hosting of their processing applications to enable Earth Observation (EO) data exploitation and processing services. EPOSAR, instead, is a service available in the framework of the European Plate Observing System (EPOS) Satellite community, which provides systematic ground displacement products relevant to various areas on Earth.

In this work we present the deployment of the P-SBAS tool within the EarthConsole® platform, in order to extend the EPOSAR service portfolio to the on-demand generation of DInSAR displacement maps and time series exploiting C-band satellite data. In particular, the developed service builds up on the already available capability to carry out a multi-temporal DInSAR processing of ENVISAT data and allow the scientific users to process also Sentinel-1 SAR images in a fully autonomous manner, through a user-friendly web graphical interface which permits to them to follow the progress of the processing tasks and to avoid the need of the SAR data download on their own processing and archiving facilities. The availability for the EPOS community of such an on-demand P-SBAS-based DInSAR processing service, which allows the scientific users to retrieve in an unsupervised way and in very short time ground displacement maps and time series relevant to large areas, may open new intriguing and unexpected perspectives to the comprehension of the Earth surface deformation dynamics.

How to cite: De Luca, C., Orlandi, M., Bonano, M., Casu, F., Iesuè, M., Manunta, M., Onorato, G., Monterroso Tobar, M. F., Rivolta, G., and Lanari, R.: On the exploitation of the Sentinel-1 P-SBAS service within the EarthConsole® platform for unsupervised on-demand DInSAR processing , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15585, https://doi.org/10.5194/egusphere-egu24-15585, 2024.

EGU24-15898 | Posters on site | ESSI3.5

Open Polar: A Comprehensive Database for Advancing Arctic and Antarctic Research 

Tamer Abu-Alam, Katie A. Smart, Per Pippin Aspaas, Leif Longva, Noortje Haugstvedt, and Karl Magnus Nilsen

In the realm of environmental and climate science, addressing the multifaceted challenges our planet faces necessitates a comprehensive approach. Holistic solutions are crucially dependent on the integration and interoperability of data. The polar regions, especially the Arctic, are particularly vulnerable to climate changes, experiencing a rate of temperature increase that is four times faster than the global average [1]. Accelerated polar warming is frequently marked by sea ice loss, but also includes shrinking habitats for polar biospheres that in turn drastically affect Arctic peoples. Though enhanced at the poles, the effects of warming are wide-ranging across the oceans and continents of our planet, affecting weather patterns, ecosystems and human activities. Polar research is thus invaluable for researchers and policymakers and should be widely and freely available. However, In 2019 a significant findability gap was discovered for open access polar records, indicating the need for a cross-disciplinary research service to provide efficient and seamless access to open polar research [2].  

 The Open Polar database [3] was launched in cooperation between the University Library at UiT The Arctic University of Norway and the Norwegian Polar Institute in 2021. Open Polar promotes Findable and Accessible polar research, such that researchers, policymakers, and society have equal and unfettered access to polar region publications and data. Open Polar harvests metadata from over 4600 open access providers, filters for polar research using over 11000 keywords, and enriches the record result by defining geolocations and applying correct DOIs, before finally building the Open Polar database that is searchable by standard text or geolocation. Currently, the database includes nearly 2.5 million open access records, consisting of approximately 75% publications and 25% datasets. Nearly 2 years after its launch, Open Polar maintains a constant robust engagement, and we aim to improve our usage by incorporating new sources, reducing redundancies and considering integration with data archiving and open education services.  

 [1] Rantanen, M., Karpechko, A.Y., Lipponen, A. et al. (2022). The Arctic has warmed nearly four times faster than the globe since 1979. Commun Earth Environ 3, 168. https://doi.org/10.1038/s43247-022-00498-3 

 [2] Abu-Alam, T. S. (2019). Open Arctic Research Index: Final report and recommendations. Septentrio Reports, (3). https://doi.org/10.7557/7.4682 

 [3] https://openpolar.no/ 

How to cite: Abu-Alam, T., Smart, K. A., Aspaas, P. P., Longva, L., Haugstvedt, N., and Nilsen, K. M.: Open Polar: A Comprehensive Database for Advancing Arctic and Antarctic Research, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15898, https://doi.org/10.5194/egusphere-egu24-15898, 2024.

EGU24-15957 | ECS | Orals | ESSI3.5

A Swedish National Infrastructure for Interdisciplinary Environmental Research Integrating Archaeological and Quaternary Geological Data 

Ershad Gholamrezaie, Philip Buckland, Roger Mähler, Johan von Boer, Rebecka Weegar, Mattias Sjölander, and Carl-Erik Engqvist

The Newly formed Swedish National Infrastructure for Digital Archaeology (SweDigArch) and the Strategic Environmental Archaeology Database (SEAD) are positioned at the intersection of environmental research, data science and humanities. They represent a considerable upscaling of archaeological and Quaternary geological databases, combining meticulous data management, collaborative stewardship, advanced online interfaces, and visualization.

SweDigArch seeks to enhance the open accessibility of archaeological data from Swedish institutions, unlocking the knowledge embedded in cultural heritage and environmental repositories to facilitate interdisciplinary and international research. At its core, SweDigArch aims to enable data-driven analyses across diverse archaeological, palaeoecological, and related materials, including links to biodiversity and other external data sources. This initiative advances research on the intricate relationships between human societies and their environments over long timescales, empowering scholars to formulate inquiries that contribute not only to historical comprehension but also hold contemporary relevance and prospective implications.

In the pursuit of data-driven analyses, SweDigArch focuses on facilitating research which examines past human-environment interactions. Through the analysis of archaeological and recent geological datasets, the project endeavors to stimulate research providing insights into the functioning of socio-ecological systems, identifying historical vulnerabilities and resilience-building factors. This knowledge, in turn, will inform contemporary design, planning, and policy frameworks across various institutional and infrastructural domains, from environmental and cultural impact assessments to assessing risks from future climate change.

SweDigArch aims to optimize the utility of Swedish archaeological and palaeoecological data through linked data, open formats, shared vocabularies, and the semantic web. This approach enriches national and international research initiatives and facilitates cross-cultural comparative research, contributing to a broader understanding of global human history.

Integral to the collaborative framework is SEAD, an Open Access repository for proxy environmental data, including various archaeological and palaeoecological datasets. Incorporating datasets such as BugsCEP fossil insect data and Swedish data on plant macrofossils, pollen, dendrochronology, geochemistry, and ceramic thin sections, SEAD's evolving functionality now extends to accommodate osteological and isotope analyses, underscoring its role as a dynamic platform for data visualization and semantic networking.

Together, SweDigArch and SEAD aim to bridge the divide between academic and contract archaeology, offering a pivotal resource for cultural and environmental historical research, urban planning, and sustainability analyses. These initiatives aspire to become the standard primary data infrastructure for all users of Swedish archaeological information, transcending scholarly circles to encompass fields such as cultural heritage preservation and urban planning. This collaborative endeavor invites active engagement from a diverse user base, fostering a scholarly ethos of openness, data-driven inquiry, and interdisciplinary collaboration to deepen our comprehension of the past and contribute to the sustainable shaping of the future.

This presentation will describe the infrastructure and provide examples of its use in the analysis and visualization of interdisciplinary data, including fossil insects, past climate change and human impact on biodiversity and the environment.

How to cite: Gholamrezaie, E., Buckland, P., Mähler, R., von Boer, J., Weegar, R., Sjölander, M., and Engqvist, C.-E.: A Swedish National Infrastructure for Interdisciplinary Environmental Research Integrating Archaeological and Quaternary Geological Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15957, https://doi.org/10.5194/egusphere-egu24-15957, 2024.

The Horizon Europe interTwin project is developing a highly generic yet powerful Digital Twin Engine (DTE) to support interdisciplinary Digital Twins (DT). Comprising thirty-one high-profile scientific partner institutions, the project brings together infrastructure providers, technology providers, and DT use cases from Climate Research and Environmental Monitoring, High Energy and AstroParticle Physics, and Radio Astronomy. This group of experts enables the co-design of the DTE Blueprint Architecture and the prototype platform; benefiting end users like scientists and policymakers but also DT developers. It achieves this by significantly simplifying the process of creating and managing complex Digital Twins workflows.

In the context of the project, among others, Digital Twin (DT) applications for extreme events (such as tropical cyclones and wildfires) on climate projections are being implemented. Understanding how climate change affects extreme events is crucial since such events can have a significant impact on ecosystems, and cause economic losses and casualties. In particular, the DT applications are based on Machine Learning (ML) approaches for the detection and prediction of the events exploiting climate/environmental variables. The interTwin DTE is aimed at providing the software and computing infrastructure for handling these complex applications in terms of AI model, data processing and workflow management.

 

The contribution will cover the use cases concerning extreme weather events, supported by project partner CMCC. 

interTwin is funded by the European Union (Horizon Europe) under grant agreement No 101058386.

How to cite: Franck, G. and Elia, D.: The interTwin DTE: supporting the development of extreme weather events applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16311, https://doi.org/10.5194/egusphere-egu24-16311, 2024.

EGU24-16403 | Posters on site | ESSI3.5

Implementation of a hydrogeochemical monitoring network following a multi-risk vision: the Strait of Messina (Italy) case. 

Marianna Cangemi, Carlo Doglioni, Paolo Madonia, Mario Mattia, and Giulio Selvaggi

The Strait of Messina, separating Sicily from continental Italy, is an area prone to different, high-grade, geological hazards. Here, many of the most devastating earthquakes of Italy have occurred, including the M 7.1 Messina-Reggio Calabria earthquake of 28 December 1908, the most intense event recorded in southern Europe in the instrumental epoch. The strait, on both sides, is surmounted by a mountain chain, directly degrading on a narrow, densely urbanized, coastal belt. Its steep slopes, composed of geological terrains with poor geotechnical characteristics, are affected by diffuse mass movements, as the 1 October 2009 landslide, triggered by an intense rainfall, which destroyed several little villages immediately southward of Messina, causing 37 causalities. The Peloro Cape area, the north-eastern termination of Sicily, hosts a lacunar environmental system, protected by the Ramsar Convention but also of economic interest, because exploited for shellfish livestock; these lagoons are extremely sensible to changes in sea level and temperature, which can pose serious threats to its ecological stability. This complex scenario exhibits a further criticality: the planned bridge for linking Sicily and continental Italy that, if realized, will be the longest single span bridge of the world.

This complex natural-built environment needs a multidisciplinary monitoring network for mitigating the multiple risks that affect both its natural and anthropic components. Its implementation is the aim of the Work Package 5 “NEMESI” of the Italian PNRR project MEET, the post-Covid 19 pandemic national plan for recovery and resilience, financed in the framework of the European Next Generation EU initiative.

Part of this multidisciplinary monitoring system will consist of a hydrogeochemical network, composed of 11 stations measuring, acquiring in a local logger and transmitting to the INGV data centre, data of temperature, level, electric conductivity, turbidity and dissolved O2 and CO2.

The main challenge in the implementation of the Strait of Messina hydrogeochemical network is the correct selection of the monitoring sites, which will be based in underground and surface water bodies, whose physic-chemical characteristics should contemporary work as indicators of very different processes: changes in electrical conductivity due to sea level rise, variations of temperature and piezometric levels induced by permeability changes driven by seismic and aseismic deformations, changes in oxygenation, turbidity and dissolved CO2, which can be controlled by both eutrophication and mixing with deep volatiles, whose flux is driven by neotectonic activity.

For accomplishing this mission, and producing open access data of interest for the different stakeholders, spanning from the scientific community to the shellfish food industry, it will be mandatory a real multidisciplinary approach, embracing geological, geophysical, geodetic, geochemical, eco-hydrological and socio-economic data.

 

How to cite: Cangemi, M., Doglioni, C., Madonia, P., Mattia, M., and Selvaggi, G.: Implementation of a hydrogeochemical monitoring network following a multi-risk vision: the Strait of Messina (Italy) case., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16403, https://doi.org/10.5194/egusphere-egu24-16403, 2024.

In-situ Earth observation data play a key role in environmental and climate related domains. However, in-situ data is often missing or hardly accessible for users due to technical barriers, for example, unstructured metadata information, missing provenance, lack of links to standard vocabularies or units of measure definitions. This communication presents a well-defined, formalized methodology for identifying and documenting requirements for in-situ data from a user’s point of view initially tested within the Group on Earth Observations. This is materialized into a comprehensive Geospatial In-situ Requirements Database and a related tool called G-reqs.

The G-reqs facilitates the requirements gathering process via a web-form that acts as the user interface. It compasses a variety of Needs: Calibration/Validation of remote sensing products, Calibration/Validation of other in-situ data, input assessment for a numerical modeling, creation of an Essential Variable product, etc. Depending on the type of need, there will be requirements for in-situ data that can be formally expressed in the main components of the geospatial information: spatial, thematic, and temporal (e.g. area of scope, variable needed, thematic uncertainty, positional accuracy, temporal coverage and frequency, representative radius, coordinate measurements, etc). The G-reqs is the first in-situ data requirements repository at the service of the evolution of the GEO Work Programme but it is not limited to them. In fact, the entire Earth observation community of users is invited to provide entries to G-reqs. The requirements collected are technology-agnostic and neither takes into account the specific characteristics of any dedicated instrument nor sensors acquiring the data. The web-form based tool and the list of all validated requirements are FAIRly accessible in the G-reqs web site at https://www.g-reqs.grumets.cat/.

After a process of requirements gathering, the presented approach is aiming to discover where similar requirements across different scientific domains are shared, fostering in-situ data reusability, and guiding the priorities for the creation of new datasets by key in-situ data providers. For example, in-situ networks of observation facilities (ENVRI, e.g. ELTER, GEOBON, among others) are invited to direct their users to provide requirements to the G-reqs and participate in the analysis of the requirements, detect gaps in current data collection and formulate recommendations for the creation of new products or refine existing ones. The final aim is to improve the interoperability and accessibility of actionable in-situ Earth observation data and services, and its reuse.

This work is inspired by the OSAAP (formerly NOSA) from NOAA, the WMO/OSCAR requirements database and the Copernicus In-Situ Component Information System (CIS2) and developed under the InCASE project, funded by the European Environment Agency (EEA) in contribution to GEO and EuroGEO.

How to cite: Brobia, A., Maso, J., Serral, I., and Voidrot, M.-F.: G-reqs as a framework for defining precise, technology-agnostic, user-driven geospatial in-situ requirements. Towards a FAIR Global Earth Observation System of Systems without data gaps., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16756, https://doi.org/10.5194/egusphere-egu24-16756, 2024.

EGU24-17229 | Orals | ESSI3.5

Active structures and thermal state of the Piton de la Fournaise summit revealed by multi-methods high resolution imaging 

Lydie Gailler, Philippe Labazuy, Romain Guillard, Solène Buvat, Clément Grace, Erwan Thébault, and Edouard Régis and the ERT3D Scan4Volc

Our understanding of dynamic volcanic processes (fluid transfers at depth and eruptions, collapses and sliding, etc.) relies directly on our knowledge of the geometries of magmatic and hydrothermal systems, mechanical heterogeneities and how these structures evolve in time. Imaging the internal structure and temporal dynamics of volcanoes still represents a real challenge to univocally identify the processes that govern their evolution, including eruptive precursors, instabilities phenomena, surface manifestations and their repercussions. It is therefore necessary to more rigorously constrain the geometry and the spatio-temporal dynamics of these structures, and their activation at different depths.

The behaviour of these structural volcanic features strongly depends on physical parameters such as temperature and fluid composition that can be assessed using a range of complementary ground and remote observations. Among these, geophysical methods provide images of the internal structure, which can subsequently be translated in terms of geological structure and evolution. Such constraints are also necessary to provide more realistic numerical models. Recent improvements to the available suite of the instrumentation for volcanological studies, including field geophysics (ground and airborne-Unmanned Aerial Vehicles, UAVs), remote sensing methods and numerical capabilities, allows us to build even more comprehensive analyses of such terrestrial phenomena. In addition, combining several spatial (local and more regional) and temporal scales (one-off studies, time lapse through reiterations, time series) help to better follow the dynamics of the edifices, anticipate eruptive crises and associated hazards.

Here we focus on the highly active and well monitored Piton de la Fournaise laboratory volcano, which is an excellent case study to develop and apply new methodologies in order to address both scientific and societal issues. Amongst the most significant parameters, recent studies have evidenced the potential of magnetic field measurements in imaging thermal anomalies (strong influence of temperature on magnetic measurements) and mechanical heterogeneities (fracturing-alteration at depth). Electrical resistivity is also a powerful tool in volcanic contexts, being very sensitive to fluid contents and particularly well suited to image the shallow structure of a volcanic edifice through, for example, innovative 3D surveys, or more in-depth using magnetotellurics measurements. Based on the analysis of combined recent reiterations of ground magnetic measurements, UAV magnetic and thermal infrared acquisitions, as well as high resolution electrical resistivity measurements, we focus on the 3D structure and recent evolution of the summit activity at Piton de la Fournaise, using additional constraints such as seismicity and deformation (InSAR inverse modelling).

This study confirms that detecting resistivity and magnetization anomalies, and quantifying their spatiotemporal evolution, can provide powerful tools for imaging volcanic systems at various scales and for providing warning of associated hazards. It also highlights the necessity for 4D monitoring of volcanic edifices using this method to provide greater precision, an important issue that is now made possible using UAV and near real time analyses.

These observational datasets aim to be integrated in open databases distributed through French and European research structures and infrastructures, namely the National Volcanology Observation Service (CNRS-INSU), Epos-France and Data Terra Research Infrastructures, as well as the EPOS VOLC-TCS.

How to cite: Gailler, L., Labazuy, P., Guillard, R., Buvat, S., Grace, C., Thébault, E., and Régis, E. and the ERT3D Scan4Volc: Active structures and thermal state of the Piton de la Fournaise summit revealed by multi-methods high resolution imaging, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17229, https://doi.org/10.5194/egusphere-egu24-17229, 2024.

EGU24-17596 | Orals | ESSI3.5

Challenges and opportunities from an in-house cross collaboration between three research infrastructure data repositories 

Claudio D'Onofrio, Ute Karstens, Alex Vermeulen, Oleg Mirzov, and Zois Zogopoulos

The ICOS Carbon Portal is the main data repository for the Integrated Carbon Observation System Research Infrastructure (ICOS RI), covering the domains Atmosphere, Ocean, and Ecosystems. Data from ICOS is available and accessible for humans and machines with a rich set of metadata under a CC BY 4.0 licence. The core services for the data portal (https://data.icos-cp.eu/portal/) are open-source software and are available on GitHub (https://github.com/ICOS-Carbon-Portal). The main goal for the development was to make the European greenhouse gas measurements accessible as FAIR as possible. This led to a mature and stable data portal which was subsequently adapted to be applied by another Research Infrastructure namely SITES, a national Swedish Infrastructure for Ecosystem Science, and the European Horizon 2020 project PAUL, pilot applications in urban landscapes (ICOS Cities). Although all three data portals use the same software core and are hosted at the ICOS Carbon Portal, they are independent from each other and base on slightly different ontologies. Hence, we have a unique opportunity to explore the challenges and opportunities of accessing and combining data from three or more different data sources and compare FAIR aspects of the datasets. How do we deal with attribution of the used data using correct citations? Do we have access to the licence for each data sets, are they different and what are the implications? How do we combine the data for further analysis keeping track of provenance and origin?

Further we will try to step back from the implementation of a service on specific data sets (which is kind of a hands-on bottom-up approach) and look at scalability to include other (environmental/ENVRI) data portals and think more about the top-down approach like the European Open Science Cloud EOSC. Can we offer a generalised service level for automated data processing from machine to machine? What do we need to process cross domain data sets?

How to cite: D'Onofrio, C., Karstens, U., Vermeulen, A., Mirzov, O., and Zogopoulos, Z.: Challenges and opportunities from an in-house cross collaboration between three research infrastructure data repositories, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17596, https://doi.org/10.5194/egusphere-egu24-17596, 2024.

EGU24-17978 | Posters on site | ESSI3.5

Notebook-as-a-VRE (NaaVRE): From private notebooks to a collaborative cloud virtual research environment 

Gabriel Pelouze, Spiros Koulouzis, and Zhiming Zhao

Studying many scientific problems, such as environmental challenges or cancer diagnosis, requires extensive data, advanced models, and distributed computing resources. Researchers often reuse assets (e.g. data, AI models, workflows, and services) from different parties to tackle these issues. This requires effective collaborative environments that enable advanced data science research: discovery access, interoperation and reuse of research assets, and integration of all resources into cohesive observational, experimental, and simulation investigations with replicable workflows. Such use cases can be effectively supported by Virtual Research Environments (VREs). Existing VRE solutions are often built with preconfigured data sources, software tools, and functional components for managing research activities. While such integrated solutions can effectively serve a specific scientific community, they often lack flexibility and require significant time investment to use external assets, build new tools, or integrate with other services. In contrast, many researchers and data scientists are familiar with notebook environments such as Jupyter. 

We propose a VRE solution for Jupyter to bridge this gap: Notebook-as-a-VRE (NaaVRE). At its core, NaaVRE allows users to build functional blocks by containerizing cells of notebooks, composing them into workflows, and managing the lifecycle of experiments and resulting data. The functional blocks, workflows, and resulting datasets can be shared to a common marketplace, enabling the creation of communities of users and customized VREs. Furthermore, NaaVRE integrates with external sources, allowing users to search, select, and reuse assets such as data, software, and algorithms. Finally, NaaVRE natively works with modern cloud technologies, making it possible to use compute resources flexibly and cost-effectively.

We demonstrate the versatility of NaaVRE by building several customized VREs that support legacy scientific workflows from different communities. This includes the derivation of ecosystem structure from Light Detection and Ranging (LiDAR) data, the tracking of bird migrations from radar observations, and the characterization of phytoplankton species. The NaaVRE is also being used to build Digital Twins of ecosystems in the Dutch NWO LTER-LIFE project.

How to cite: Pelouze, G., Koulouzis, S., and Zhao, Z.: Notebook-as-a-VRE (NaaVRE): From private notebooks to a collaborative cloud virtual research environment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17978, https://doi.org/10.5194/egusphere-egu24-17978, 2024.

EGU24-18535 | Orals | ESSI3.5

Using IGSN IDs in Geosciences Sample Management with RSpace: Use Case & Workflows 

Vaida Plankytė, Rory Macneil, Rorie Edmunds, and Noortje Haugstvedt

Overview

The International Generic Sample Number (IGSN ID), functionally a DataCite DOI, enables material samples from any discipline to be identified with a globally unique and persistent ID. 

This scalable FAIRification of samples enables transparent and traceable connections between a sample and other research entities, including (sub)samples, collections, instruments, grants, data, publications, people, and organizations. In 2023, support for the registration, metadata input, and publication of IGSN IDs was incorporated into the RSpace sample management system.

After introducing IGSN IDs, we overview the use case developed in collaboration with UiT The Arctic University of Norway regarding research workflows involved in geosciences field studies, and the corresponding IGSN ID and sample management functionality required to support these research workflows.

We then present our incorporation of IGSN IDs into RSpace as part of an institutional deployment solution for FAIR samples, detailing features and their various design considerations based on researcher needs.

Geosciences Use Case – UiT The Arctic University of Norway

A research group within the Department of Geosciences plans to assign IGSN IDs to samples collected during their 2024 field campaign in a remote Arctic area. The group needs to record basic structured sample information offline, while in the field. The institutional research data managers wish to increase sample visibility within the greater research community, ensure metadata format standardization, and facilitate metadata management by using an ELN with IGSN ID capabilities.

An offline field data collection tool, FieldMark, can be used to design powerful templates for metadata capture, and links IGSN IDs scanned from physical labels with rich metadata, including geolocation capture. Once back from the field, the sample metadata and templates, and their associated IGSN IDs, can be imported into RSpace, preserving format.

What is more, by assigning IGSN IDs to samples as well as features-of-interest, using instrument PIDs, and linking related entities, researchers model a rich PID graph that accurately portrays these relationships.

The samples are then utilized in active research: metadata editing as well as underlying template editing, linking experimental records and materials with samples, and inclusion of optional metadata fields are supported in RSpace.

Finally, the samples can be published alongside other materials, with RSpace generating a public metadata landing page for each sample containing both IGSN ID and domain-specific metadata. The IGSN ID metadata also becomes findable in DataCite’s records and API.

RSpace IGSN ID Features

We present the IGSN ID implementation in RSpace, including recent functionality:

  • Assigning ROR (Research Organization Registry) IDs to an RSpace instance, automatically populating IGSN metadata with affiliation information
  • Geolocation support for dynamic point, box, and polygon map previews alongside the coordinates on the public landing page
  • Ability to display domain-specific sample fields on the landing page to enable comprehensive metadata sharing

As well as upcoming work:

  • Integrating with other DataCite Service Providers to facilitate deposit of sample metadata into domain-specific repositories, analogous to ELN document export to repositories
  • Facilitating the use of singleton samples alongside batches of subsamples, while retaining the system’s ease of navigation and conceptual clarity

How to cite: Plankytė, V., Macneil, R., Edmunds, R., and Haugstvedt, N.: Using IGSN IDs in Geosciences Sample Management with RSpace: Use Case & Workflows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18535, https://doi.org/10.5194/egusphere-egu24-18535, 2024.

EGU24-19358 | ECS | Posters on site | ESSI3.5

Research Notebook Retrieval with Explainable Query Reformulation 

Na Li, Peide Zhu, Gabriel Gabriel Pelouze, Spiros Koulouzis, Zhiming Zhao, and Zhiming Zhao

Data science and Machine learning techniques are increasingly important in tackling societal challenges and complex problems in environmental and earth sciences. Effectively sharing and (re)using research assets, including data sets, models, software tools, documents, and computing notebooks, are crucial for such data-centric research activities. Researchers can reproduce others’ experiments with the available research assets to verify the results and to further develop new experiments. Computational notebooks, as an important asset, comprise free-form textual descriptions and code snippets. The notebook runtime environments, e.g., Jupyter, provide scientists with an interactive environment to construct and share the experiment descriptions and code as notebooks. 

 

To enable effective research assets discovery, research infrastructures not only need to FAIRify the assets with rich meta information and unique identifiers but also provide search functionality and tools to facilitate the construction of scientific workflows for the data sciences experiments with research assets from multiple sources. The general-purpose search engines are helpful for initial coarse-grained search but often fail to find multiple types of research assets such as the data sets and notebooks needed by the research. The community-specific catalogues, e.g., in ICOS and LifeWatch, provide search capabilities for precisely discovering data sets, but they are often characterized by a specific type of asset. A researcher has to spend lots of time searching across multiple catalogues to discover all types of assets needed. 

In the search process, user queries tend to be short and comprised of several key phrases that demand great efforts to understand users’ information needs. Given the complexity of computational notebook contents and the mismatch between the form of user queries and the computational notebooks, it is critical to understand queries by augmentations and make explainable relevance judgments. To address these challenges, we developed a research asset search system for a Jupyter notebook-based Virtual Research Environment (called Notebook as a VRE) that supports scientific query understanding with query reformulation and explainable computational notebook relevance judgments via computational notebook summarization. 

The proposed system includes four major components: the query reformulation module, the notebook indexer and retriever, the summarization component, and the user interface.  The query reformulation module performs active query understanding via query reformulation, where we extract scientific entities from user queries and search related entities from external knowledge graphs and resources as expansions and rank the reformulated queries for users to choose from. The system has been validated via a small user group and will be further developed in the coming ENVRI-HUB next project to support conversational search and recommendation. 

How to cite: Li, N., Zhu, P., Gabriel Pelouze, G., Koulouzis, S., Zhao, Z., and Zhao, Z.: Research Notebook Retrieval with Explainable Query Reformulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19358, https://doi.org/10.5194/egusphere-egu24-19358, 2024.

EGU24-19379 | Posters on site | ESSI3.5

Status and Planning Update on Big Data Standardization in OGC and ISO 

Peter Baumann

Earth data are an archetypical case of Big Data, in all their Volume, Velocity, Variety, and Veracity challenges. Since long, therefore, standardization in ISO, OGC, and further bodies is concerned with developing and advancing specifications for structures and services suitable for Big Data. Questions to keep in mind include:
- How can data wrangling be simplified, for example through better suited concepts and elimination of unnecessary technicalities?
- How can specifications support scalable implementations?
- What is necessary to make data ready for analysis, more generally: for the various types of consumption?

Specifically, the commonly accepted concept of multi-dimensional coverages - corresponding to the notion of spatio-temporal "fields" in physics" - addresses Big Data, in practice: regular and irregular grids, point clouds, and general meshes. Recently, ISO has adopted two "abstract" standards with normative definitions of coverage concepts and terminology. 19123-1 addresses the coverage data model whereas 19123-3 is about coverage processing fundamentals, utilizing the OGC Web Coverage Processing Service (WCPS) model. OGC has adopted both as an update to its Abstract Topic 6.

On the level of "concrete" specifications directed towards implementation and conformance testing there is the joint OGC/ISO Coverage Impementation Schema. In OGC the current version is 1.1 which introduces the General Grid Coverage as a more powerful, yet simplified structure for regular and irregular grids. ISO has commenced work on updating its 19123-2, which is still based on OGC CIS 1.0), with  CIS 1.1. On the processing side, there are various activities in addition to the proven, mature WCS and WCPS, such as drafts for OAPI-Coverages and GeoDataCube.

We present the current status of ISO and OGC standardization work on coverages. The author is active as editor of adopted and in-progress standards in OGC and ISO since over 15 years, and intimately familiar with standardization work there. By sharing the status and plans of standardization the talk provides an opportunity for the community to comment on plans and share any comments and suggestions.

 

How to cite: Baumann, P.: Status and Planning Update on Big Data Standardization in OGC and ISO, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19379, https://doi.org/10.5194/egusphere-egu24-19379, 2024.

EGU24-19603 | Posters on site | ESSI3.5

ITINERIS HUB: the unified access point to Italian environmental facilities, FAIR data and related services 

Claudio Dema, Francesco Izzi, Lucia Mona, Vito Salvia, Carmela Cornacchia, Ermann Ripepi, Michele Volini, and Gelsomina Pappalardo

The Italian Integrated Environmental Research Infrastructures System (ITINERIS) Project coordinates a network of national nodes from 22 RIs.

ITINERIS has been designed looking at synergy with the European RI framework, and it will support the participation of Italian scientists in pan-European initiatives (like ENVRI-Hub NEXT and EOSC). ITINERIS will have significant impact on national environmental research, providing scientific support to the design of actionable environmental strategies.

To this end, ITINERIS will build the Italian HUB of Research Infrastructures in the environmental scientific domain providing a single and unified access point to facilities, FAIR data and related services available within the Italian RIs network through an easy-to-navigate interface.

Through the ITINERIS HUB all users will have access to data and services, with a complete catalogue of data and services and a proper access management system. ITINERIS will not duplicate existing data provided by European RIs, but will make them discoverable in a unique place together with other National RI resources. Additionally, ITINERIS HUB will make accessible data resulting from specific ITINERIS project activities like campaign data and novel data products.

ITINERIS will also offer a system of Virtual Research Environments (VRE), that will provide new services to address scientifically and societally relevant issues starting from an ensemble of cross-disciplinary actions on the data, information and knowledge generated by the different RIs in the different environmental subdomains.

State-of-the-art applications and custom-made tools will be integrated in the HUB to respond to the needs of: collecting and preparing information on products, resources and services to be advertised in a way that users can easily discover and access them and the RIs; facilitating the management of user access requests through the automated workflows and specific features that are peculiar to the online submission and management systems.

The main concept includes a GeoServer with the possibility of discovery, visualization and plotting RI data available. To be more precise, a scalable infrastructure for the provision of mapping services compliant with the standards of the Open Geospatial Consortium (OGC) WMS (Web Map Service), WFS (Web Feature Service), WCS (Web Coverage Service) will be implemented. A Metadata Service will be responsible for providing OGC CSW services. It will therefore offer a data discovery service through metadata consultation, corresponding to the most common metadata profiles. A stack of support services (REST/SOAP interfaces) for queries on geographic databases will be provided.

The ITINERIS HUB is candidate to become the integrated system of the Italian Environmental RIs to be connected to European initiatives like ENVRI-Hub NEXT and EOSC, fostering the ability to address current and expected environmental challenges at National level and beyond.

Acknowledgement

IR0000032 – ITINERIS, Italian Integrated Environmental Research Infrastructures System (D.D. n. 130/2022 - CUP B53C22002150006) Funded by EU - Next Generation EU PNRR- Mission 4 “Education and Research” - Component 2: “From research to business” - Investment 3.1: “Fund for the realisation of an integrated system of research and innovation infrastructures”

How to cite: Dema, C., Izzi, F., Mona, L., Salvia, V., Cornacchia, C., Ripepi, E., Volini, M., and Pappalardo, G.: ITINERIS HUB: the unified access point to Italian environmental facilities, FAIR data and related services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19603, https://doi.org/10.5194/egusphere-egu24-19603, 2024.

EGU24-20005 | Posters on site | ESSI3.5

Cloudnet – an ACTRIS data repository for cloud remote sensing observations 

Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor

Clouds strongly regulate the Earth’s water cycle and the planetary radiation balance. Clouds are one of the largest contributors to the overall uncertainty in climate feedbacks, propagating into global temperature projections (Arias et al., 2021). Cloudnet data repository provides long-term datasets of cloud property profiles with a high temporal and vertical resolution, derived from synergetic ground-based measurements and numerical weather prediction model data.

These datasets can be used, for example, to validate satellite-based products and to improve the accuracy of climate and weather forecast models. Cloudnet is part of the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) which is now in the implementation phase and plans to be fully operational in 2025 (Häme et al., 2018).

Cloudnet receives data regularly from around 20 stationary observational facilities. Each facility is equipped with instruments that meet the requirements of the ACTRIS Centre for Cloud Remote Sensing (CCRES). These instruments include Doppler cloud radars, Doppler lidars, ceilometers, microwave radiometers, disdrometers, and weather stations. We also host and process data from mobile and campaign platforms.

Cloudnet processes raw instrument data into cloud property products such as target classification of the scatterers, liquid and ice water content, and drizzle drop size distribution (Illingworth et al., 2007) using the open-source Python package CloudnetPy (Tukiainen et al., 2020). Processed data products are provided in near-real time, typically within one hour from the measurement. In the future, Cloudnet will also provide wind and boundary layer height products derived from Doppler lidar data.

All the raw and processed data are freely available according to the FAIR principles (Wilkinson et al., 2016) via cloudnet.fmi.fi. Furthermore, our software are freely and openly available from https://github.com/actris-cloudnet/.

ACKNOWLEDGEMENTS

We thank the Academy of Finland Flagship (grant no. 337552), the European Union’s Horizon 2020 research and innovation programme (grant no. 654109), and ACTRIS (project no. 739530, grant no. 871115) for funding this project.

REFERENCES

Arias et.al. (2021) Technical Summary. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. (Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA)

Häme et.al. (2018). ACTRIS stakeholder handbook 2018. (Painotalo Trinket Oy).

Illingworth et.al. (2007). Cloudnet: Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations. Bulletin of the American Meteorological Society, 6, 88.

Tukiainen, S., O’Connor, E., and Korpinen, A. (2020). CloudnetPy: A Python package for processing cloud remote sensing data. Journal of Open Source Software, 5(53), 2123.

Wilkinson et.al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), 160018.

How to cite: Tukiainen, S., Siipola, T., Leskinen, N., and O'Connor, E.: Cloudnet – an ACTRIS data repository for cloud remote sensing observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20005, https://doi.org/10.5194/egusphere-egu24-20005, 2024.

This study employs spatial and semantic modeling to formally specify the intersection of environmental concerns and social justice, focusing on the unequal impact of environmental hazards on the economically disadvantaged people living in the Proctor Creek watershed within the Atlanta Metropolitan area. Our 'Public Health-Urban-Socio-economic-Environmental Justice' (PUSH-EJ) ontology formally integrates environmental justice indices and all concepts from the EPA’s EJScreen, such as Environmental Indicator, Demographic Indicator, EJ Index, Particulate Matter, Risk, and Proximity to hazardous sites. PUSH-EJ also formalizes the National Air Toxics Assessment (NATA)’s Air Toxics Cancer Risk, Air Toxics Respiratory Hazard Index, and Diesel Particulate Matter. The modeled environmental indicators include levels of ozone, particulate matter 2.5 (micrometer or smaller-sized particles), and lead paint (for houses built before 1960) in the air, count of underground leaking storage tanks, and count and proximity to wastewater discharge areas. The ontology also models proximity of housing units to waste and hazardous chemical facilities or sites related to National Priorities List (NPL) Superfund Program, Risk Management Plan (RMP) sites, Treatment, Storage, and Disposal Facilities (TSDFs), and Traffic volume. Environmental, demographic, and socioeconomic indicators are mapped to the objectives of UN SDGs 1, 3, 4, 5, 8, and 10, bridging the gap between environmental justice, public health, urban dynamics, and socio-economic aspects. Our analysis of Proctor Creek's socioeconomic indicators reveals a combined Demographic Index of 73%, driven by Low Income (61%) and People of Color (90%). These findings indicate that Proctor Creek exhibits the lowest scores across all categories when compared to other regions in Georgia, EPA Region 4, and the nation. Our results call for minimizing contamination in the Proctor Creek area and uplifting socioeconomic conditions by the authorities responsible for the watershed. Our spatial analysis highlights urgent priorities in the Proctor Creek area, for the management of air toxic sources, emissions, and addressing proximity issues linked to environmental pollutants from hazardous waste sites, lead paint, and traffic.

How to cite: Davarpanah, A., Shafiei, F., and Jelks, N.: Semantic and spatial Proximity Modeling of Equitable Sustainability in Proctor Creek, Atlanta: Merging Environmental Justice and Sustainable Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20704, https://doi.org/10.5194/egusphere-egu24-20704, 2024.

EGU24-24 | Orals | NP4.1

The fractional Sinusoidal wavefront Model (fSwp) for time series displaying persistent stationary cycles 

Gael Kermarrec, Federico Maddanu, Anna Klos, and Tommaso Proietti

In the analysis of sub-annual climatological or geodetic time series such as tide gauges, precipitable water vapor, or GNSS vertical displacements time series but also temperatures or gases concentrations, seasonal cycles are often found to have a time-varying amplitude and phase.

These time series are usually modelled with a deterministic approach that includes trend, annual, and semi-annual periodic components having constant amplitude and phase-lag. This approach can potentially lead to inadequate interpretations, such as an overestimation of Global Navigation Satellite System (GNSS) station velocity, up to masking important geophysical phenomena that are related to the amplitude variability and are important for deriving trustworthy interpretation for climate change assessment.

We address that challenge by proposing a novel linear additive model called the fractional Sinusoidal Waveform process (fSWp), accounting for possible nonstationary cyclical long memory, a stochastic trend that can evolve over time and an additional serially correlated noise capturing the short-term variability. The model has a state space representation and makes use of the Kalman filter (KF). Suitable enhancements of the basic methodology enable handling data gaps, outliers, and offsets. We demonstrate our method using various climatological and geodetic time series to illustrate its potential to capture the time-varying stochastic seasonal signals.

How to cite: Kermarrec, G., Maddanu, F., Klos, A., and Proietti, T.: The fractional Sinusoidal wavefront Model (fSwp) for time series displaying persistent stationary cycles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-24, https://doi.org/10.5194/egusphere-egu24-24, 2024.

On some maps of the first military survey of the Habsburg Empire, the upper direction of the sections does not face the cartographic north, but makes an angle of about 15° with it. This may be due to the fact that the sections were subsequently rotated to the magnetic north of the time. Basically, neither their projection nor their projection origin is known yet.

In my research, I am dealing with maps of Inner Austria, the Principality of Transylvania and Galicia (nowadays Poland and Ukraine), and I am trying to determine their projection origin. For this purpose, it is assumed, based on the archival documentation of the survey, that these are Cassini projection maps. My hypothesis is that they are Graz, Cluj Napoca or Alba Julia and Lviv. I also consider the position of Vienna in each case, since it was the main centre of the survey.

The angle of rotation was taken in part from the gufm1 historical magnetic model back to 1590 for the assumed starting points and year of mapping. In addition, as a theoretical case, I calculated the rotation angle of the map sections using coordinate geometry. I then calculated the longitude of the projection starting point for each case using univariate minimization. Since the method is invariant to latitude, it can only be determined from archival data.

Based on these, the starting point for Inner Austria from the rotation of the map was Vienna, which is not excluded by the archival sources, and since the baseline through Graz also started from there, it is partly logical. The map rotation for Galicia and Transylvania also confirmed the starting point of the hypothesis.  Since both Alba Julia and Cluj Napoca lie at about the same longitude, the method cannot make a difference there; and the archival data did not provide enough evidence. In comparison, the magnetic declination rotations yielded differences of about 1°, which may be due to an error in the magnetic model.

On this basis, I have given the assumed projections of the three maps with projection starting points, and developed a method for determining the projection starting points of the other rotated grid maps. The results suggest that there is a very high probability that the section network was rotated in the magnetic north direction, and thus provide a way to refine the magnetic declination data at that time.

With this method I managed to give new indirekt magnetic declinations data from Central-East Europe, which can help to improve the historical magnetic field models. The main reason for this is that we don’t have any measurement from that region.

Furthermore the difference beetwen the angle of the section north and the declination data from gufm1 always 0.8-1°. Maybe there are systematical data error at that region.

Supported by the ÚNKP-23-6 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: Koszta, B. and Timár, G.: A possible cartographical data source for historical magnetic field improvement: The direction of the section north of the Habsburg first military survey, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-582, https://doi.org/10.5194/egusphere-egu24-582, 2024.

EGU24-1988 | ECS | Posters on site | NP4.1

Predictive ability assessment of Bayesian Causal Reasoning (BCR) on runoff temporal series 

Santiago Zazo, José Luis Molina, Carmen Patino-Alonso, and Fernando Espejo

The alteration of traditional hydrological patterns due to global warming is leading to a modification of the hydrological cycle. This situation draws a complex scenario for the sustainable management of water resources. However, this issue offers a challenge for the development of innovative approaches that allow an in-depth capturing the logical temporal-dependence structure of these modifications to advance sustainable management of water resources, mainly through the reliable predictive models. In this context, Bayesian Causality (BC), addressed through Causal Reasoning (CR) and supported by a Bayesian Networks (BNs), called Bayesian Causal Reasoning (BCR) is a novel hydrological research area that can help identify those temporal interactions efficiently.

This contribution aims to assesses the BCR ability to discover the logical and non-trivial temporal-dependence structure of the hydrological series, as well as its predictability. For this, a BN that conceptually synthesizes the time series is defined, and where the conditional probability is propagated over the time throughout the BN through an innovative Dependence Mitigation Graph. This is done by coupling among an autoregressive parametric approach and causal model. The analytical ability of the BCR highlighted the logical temporal structure, latent in the time series, which defines the general behavior of the runoff. This logical structure allowed to quantify, through a dependence matrix which summarizes the strength of the temporal dependencies, the two temporal fractions that compose the runoff: one due to time (Temporally Conditioned Runoff) and one not (Temporally Non-conditioned Runoff). Based on this temporal conditionality, a predictive model is implemented for each temporal fraction, and its reliability is assessed from a double probabilistic and metrological perspective.

This methodological framework is applied to two Spanish unregulated sub-basins; Voltoya river belongs to Duero River Basin, and Mijares river, in the Jucar River Basin. Both cases with a clearly opposite temporal behavior, Voltoya independent and Mijares dependent, and with increasingly more problems associated with droughts.

The findings of this study may have important implications over the knowledge of temporal behavior of water resources of river basin and their adaptation. In addition, TCR and TNCR predictive models would allow advances in the optimal dimensioning of storage infrastructures (reservoirs), with relevant substantial economic/environmental savings. Also, a more sustainable management of river basins through more reliable control reservoirs’ operation is expected to be achieved. Finally, these results open new possibilities for developing predictive hydrological models within a BCR framework.

How to cite: Zazo, S., Molina, J. L., Patino-Alonso, C., and Espejo, F.: Predictive ability assessment of Bayesian Causal Reasoning (BCR) on runoff temporal series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1988, https://doi.org/10.5194/egusphere-egu24-1988, 2024.

EGU24-3857 | ECS | Posters on site | NP4.1 | Highlight

Spatial-Temporal Analysis of Forest Mortality 

Sara Alibakhshi

Climate-induced forest mortality poses an increasing threat worldwide, which calls for developing robust approaches to generate early warning signals of upcoming forest state change. This research explores the potential of satellite imagery, utilizing advanced spatio-temporal indicators and methodologies, to assess the state of forests preceding mortality events. Traditional approaches, such as techniques based on temporal analyses, are impacted by limitations related to window size selection and detrending methods, potentially leading to false alarms. To tackle these challenges, our study introduces two new approaches, namely the Spatial-Temporal Moran (STM) and Spatial-Temporal Geary (STG) approaches, both focusing on local spatial autocorrelation measures. These approaches can effectively address the shortcomings inherent in traditional methods. The research findings were assessed across three study sites within California national parks, and Kendall's tau was employed to quantify the significance of false and positive alarms. To facilitate the measurement of ecosystem state change, trend estimation, and identification of early warning signals, this study also provides "stew" R package. The implications of this research extend to various groups, such as ecologists, conservation practitioners, and policymakers, providing them with the means to address emerging environmental challenges in global forest ecosystems.

How to cite: Alibakhshi, S.: Spatial-Temporal Analysis of Forest Mortality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3857, https://doi.org/10.5194/egusphere-egu24-3857, 2024.

Iram Parvez1, Massimiliano Cannata2, Giorgio Boni1, Rossella Bovolenta1 ,Eva Riccomagno3 , Bianca Federici1

1 Department of Civil, Chemical and Environmental Engineering (DICCA), Università degli Studi di Genova, Via Montallegro 1, 16145 Genoa, Italy (iram.parvez@edu.unige.it,bianca.federici@unige.it, giorgio.boni@unige.it, rossella.bovolenta@unige.it).

2 Institute of Earth Sciences (IST), Department for Environment Constructions and Design (DACD), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), CH-6952 Canobbio, Switzerland(massimiliano.cannata@supsi.ch).

3 Department of Mathematics, Università degli Studi di Genova, Via Dodecaneso 35, 16146 Genova, Italy(riccomag@dima.unige.it).

The deployment of hydrometeorological sensors significantly contributes to generating real-time big data. The quality and reliability of large datasets pose considerable challenges, as flawed analyses and decision-making processes can result. This research aims to address the issue of anomaly detection in real-time data by exploring machine learning models. Time-series data is collected from IstSOS - Sensor Observation Service, an open-source software that stores, collects and disseminates sensor data. The methodology consists of Gated Recurrent Units based on recurrent neural networks, along with corresponding prediction intervals, applied both to individual sensors and collectively across all temperature sensors within the Ticino region of Switzerland. Additionally, non-parametric methods like Bootstrap and Mean absolute deviation are employed instead of standard prediction intervals to tackle the non-normality of the data. The results indicate that Gated Recurrent Units based on recurrent neural networks, coupled with non-parametric forecast intervals, perform well in identifying erroneous data points. The application of the model on multivariate time series-sensor data establishes a pattern or baseline of normal behavior for the area (Ticino). When a new sensor is installed in the same region, the recognized pattern is used as a reference to identify outliers in the data gathered from the new sensor.

How to cite: Parvez, I.: Exploring Machine Learning Models to Detect Outliers in HydroMet Sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4280, https://doi.org/10.5194/egusphere-egu24-4280, 2024.

EGU24-5268 | ECS | Orals | NP4.1

Unveiling Geological Patterns: Bayesian Exploration of Zircon-Derived Time Series Data 

Hang Qian, Meng Tian, and Nan Zhang

For its immunity to post-formation geological modifications, zircon is widely utilized as chronological time capsule and provides critical time series data potential to unravel key events in Earth’s geological history, such as supercontinent cycles. Fourier analysis, which assumes stationary periodicity, has been applied to zircon-derived time series data to find the cyclicity of supercontinents, and wavelet analysis, which assumes non-stationary periodicity, corroborates the results of Fourier Analysis in addition to detecting finer-scale signals. Nonetheless, both methods still prognostically assume periodicity in the zircon-derived time-domain data. To stay away from the periodicity assumption and extract more objective information from zircon data, we opt for a Bayesian approach and treat zircon preservation as a composite stochastic process where the number of preserved zircon grains per magmatic event obeys logarithmic series distribution and the number of magmatic events during a geological time interval obeys Poisson distribution. An analytical solution was found to allow us to efficiently invert for the number and distribution(s) of changepoints hidden in the globally compiled zircon data, as well as for the zircon preservation potential (encoded as a model parameter) between two neighboring changepoints. If the distributions of changepoints temporally overlap with those of known supercontinents, then our results serve as an independent, mathematically robust test of the cyclicity of supercontinents. Moreover, our statistical approach inherently provides a sensitivity parameter the tuning of which allows to probe changepoints at various temporal resolution. The constructed Bayesian framework is thus of significant potential to detect other types of trend swings in Earth’s history, such as shift of geodynamic regimes, moving beyond cyclicity detection which limits the application of conventional Fourier/Wavelet analysis.

How to cite: Qian, H., Tian, M., and Zhang, N.: Unveiling Geological Patterns: Bayesian Exploration of Zircon-Derived Time Series Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5268, https://doi.org/10.5194/egusphere-egu24-5268, 2024.

Semi-enclosed freshwater and brackish ecosystems, characterised by restricted water outflow and prolonged residence times, often accumulate nutrients, influencing their productivity and ecological dynamics. These ecosystems exhibit significant variations in bio-physical-chemical attributes, ecological importance, and susceptibility to human impacts. Untangling the complexities of their interactions remains challenging, necessitating a deeper understanding of effective management strategies adapted to their vulnerabilities. This research focuses on the bio-physical aspects, investigating the differential effects of spring and summer light on phytoplankton communities in semi-enclosed freshwater and brackish aquatic ecosystems.

Through extensive field sampling and comprehensive environmental parameter analysis, we explore how phytoplankton respond to varying light conditions in these distinct environments. Sampling campaigns were conducted at Müggelsee, a freshwater lake on Berlin's eastern edge, and Barther Bodden, a coastal lagoon northeast of Rostock on the German Baltic Sea coast, during the springs and summers of 2022 and 2023, respectively. Our analysis integrates environmental factors such as surface light intensity, diffuse attenuation coefficients, nutrient availability, water column dynamics, meteorological data, Chlorophyll-a concentration, and phytoplankton communities. Sampling encompassed multiple depths at continuous intervals lasting three days.

Preliminary findings underscore significant differences in seasonal light availability, with summer exhibiting extended periods of substantial light penetration. These variations seem to impact phytoplankton abundance and diversity uniquely in each ecosystem. While ongoing analyses are underway, early indications suggest distinct phytoplankton responses in terms of species composition and community structure, influenced by the changing light levels. In 2022 the clear water phase during spring indicated that bloom events have occurred under ice cover much earlier than spring, while in the summer there were weak and short-lived blooms of cyanobacteria. The relationship between nutrient availability and phytoplankton dynamics, however, remains uncertain according to our data.

This ongoing study contributes to understanding the role of light as a primary driver shaping phytoplankton community structures and dynamics in these environments.  Our research findings offer insights for refining predictive models, aiding in ecosystem-specific eutrophication management strategies, and supporting monitoring efforts of Harmful Algal Blooms.

How to cite: Kaharuddin, A. and Kaligatla, R.: Comparative Study of Spring and Summer Light Effects on Phytoplankton Communities in Semi-Enclosed Fresh- and Brackish Aquatic Ecosystems., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5733, https://doi.org/10.5194/egusphere-egu24-5733, 2024.

EGU24-6065 | ECS | Orals | NP4.1

Magnetospheric time history:  How much do we need for forecasting? 

Kendra R. Gilmore, Sarah N. Bentley, and Andy W. Smith

Forecasting the aurora and its location accurately is important to mitigate any potential harm to vital infrastructure like communications and electricity grid networks. Current auroral prediction models rely on our understanding of the interaction between the magnetosphere and the solar wind or geomagnetic indices. Both approaches do well in predicting but have limitations concerning forecasting (geomagnetic indices-based model) or because of the underlying assumptions driving the model (due to a simplification of the complex interaction). By applying machine learning algorithms to this problem, gaps in our understanding can be identified, investigated, and closed. Finding the important time scales for driving empirical models provides the necessary basis for our long-term goal of predicting the aurora using machine learning.

Periodicities of the Earth’s magnetic field have been extensively studied on a global scale or in regional case studies. Using a suite of different time series analysis techniques including frequency analysis and investigation of long-scale changes of the median/ mean, we examine the dominant periodicities of ground magnetic field measurements at selected locations. A selected number of stations from the SuperMAG network (Gjerloev, 2012), which is a global network of magnetometer stations across the world, are the focus of this investigation.

The periodicities retrieved from the different magnetic field components are compared to each other as well as to other locations. In the context of auroral predictions, an analysis of the dominating periodicities in the auroral boundary data derived from the IMAGE satellite (Chisham et al., 2022) provides a counterpart to the magnetic field periodicities.

Ultimately, we can constrain the length of time history sensible for forecasting.

How to cite: Gilmore, K. R., Bentley, S. N., and Smith, A. W.: Magnetospheric time history:  How much do we need for forecasting?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6065, https://doi.org/10.5194/egusphere-egu24-6065, 2024.

EGU24-6151 | Posters on site | NP4.1

Using information-theory metrics to detect regime changes in dynamical systems 

Javier Amezcua and Nachiketa Chakraborty

Dynamical systems can display a range of dynamical regimes (e.g. attraction to, fixed points, limit cycles, intermittency, chaotic behaviour) depending on the values of parameters in the system. In this work we demonstrate how non-parametric entropy estimation codes (in particular NPEET) based on the Kraskov method can be applied to find regime transitions in a 3D chaotic model (the Lorenz 1963 system) when varying the values of the parameters. These infromation-theory-based methods are simpler and cheaper to apply than more traditional metrics from dynamical systems (e.g. computation of Lyapunov exponents). The non-parametric nature of the method allows for handling long time series without a prohibitive computational burden. 

How to cite: Amezcua, J. and Chakraborty, N.: Using information-theory metrics to detect regime changes in dynamical systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6151, https://doi.org/10.5194/egusphere-egu24-6151, 2024.

EGU24-9367 | ECS | Orals | NP4.1

Fractal complexity evaluation of meteorological droughts over three Indian subdivisions using visibility Graphs 

Susan Mariam Rajesh, Muraleekrishnan Bahuleyan, Arathy Nair GR, and Adarsh Sankaran

Evaluation of scaling properties and fractal formalisms is one of the potential approaches for modelling complex series. Understanding the complexity and fractal characterization of drought index time series is essential for better preparedness against drought disasters. This study presents a novel visibility graph-based evaluation of fractal characterization of droughts of three meteorological subdivisions of India. In this method, the horizontal visibility graph (HVG) and Upside-down visibility graph (UDVG) are used for evaluating the network properties for different standardized precipitation index (SPI) series of 3, 6 and 12 month time scales representing short, medium and long term droughts. The relative magnitude of fractal estimates is controlled by the drought characteristics of wet-dry transitions. The estimates of degree distribution clearly deciphered the self-similar properties of droughts of all the subdivisions. For an insightful depiction of drought dynamics, the fractal exponents and spectrum are evaluated by the concurrent application of Sand Box Method (SBM) and Chhabra and Jenson Method (CJM). The analysis was performed for overall series along with the pre- and post-1976-77 Global climate shift scenarios. The complexity is more evident in short term drought series and UDVG formulations implied higher fractal exponents for different moment orders irrespective of drought type and locations considered in this study. Useful insights on the relationship between complex network and fractality are evolved from the study, which may help in improved drought forecasting. The visibility graph based fractality estimation evaluation is efficient in capturing drought and it has vast potential in the drought predictions in a changing environment.

Keywords:  Drought, Fractal, SPI, Visibility Graph

How to cite: Rajesh, S. M., Bahuleyan, M., Nair GR, A., and Sankaran, A.: Fractal complexity evaluation of meteorological droughts over three Indian subdivisions using visibility Graphs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9367, https://doi.org/10.5194/egusphere-egu24-9367, 2024.

EGU24-9537 | Posters on site | NP4.1

Wavelet-Induced Mode Extraction procedure: Application to climatic data 

Elise Faulx, Xavier Fettweis, Georges Mabille, and Samuel Nicolay

The Wavelet-Induced Mode Extraction procedure (WIME) [2] was developed drawing inspiration from Empirical Mode Decomposition. The concept involves decomposing the signal into modes, each presenting a characteristic frequency, using continuous wavelet transform. This method has yielded intriguing results in climatology [3,4]. However, the initial algorithm did not account for the potential existence of slight frequency fluctuations within a mode, which could impact the reconstruction of the original signal [4]. The new version (https://atoms.scilab.org/toolboxes/toolbox_WIME/0.1.0) now allows for the evolution of a mode in the space-frequency half-plane, thus considering the frequency evolution of a mode [2]. A natural application of this tool is in the analysis of Milankovitch cycles, where subtle changes have been observed throughout history. The method also refines the study of solar activity, highlighting the role of the "Solar Flip-Flop." Additionally, the examination of temperature time series confirms the existence of cycles around 2.5 years. It is now possible to attempt to correlate solar activity with this observed temperature cycle, as seen in speleothem records [1].

[1] Allan, M., Deliège, A., Verheyden, S., Nicolay S. and Fagel, N. Evidence for solar influence in a Holocene speleothem record, Quaternary Science Reviews, 2018.
[2] Deliège, A. and Nicolay, S., Extracting oscillating components from nonstationary time series: A wavelet-induced method, Physical Review. E, 2017.
[3] Nicolay, S., Mabille, G., Fettweis, X. and Erpicum, M., A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method, Nonlinear Processes in Geophysics, 2010.
[4] Nicolay, S., Mabille, G., Fettweis, X. and Erpicum, M., 30 and 43 months period cycles found in air temperature time series using the Morlet wavelet, Climate Dynamics, 2009.

How to cite: Faulx, E., Fettweis, X., Mabille, G., and Nicolay, S.: Wavelet-Induced Mode Extraction procedure: Application to climatic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9537, https://doi.org/10.5194/egusphere-egu24-9537, 2024.

EGU24-10258 | Orals | NP4.1

New concepts on quantifying event data 

Norbert Marwan and Tobias Braun

A wide range of geoprocesses manifest as observable events in a variety of contexts, including shifts in palaeoclimate regimes, evolutionary milestones, tectonic activities, and more. Many prominent research questions, such as synchronisation analysis or power spectrum estimation of discrete data, pose considerable challenges to linear tools. We present recent advances using a specific similarity measure for discrete data and the method of recurrence plots for different applications in the field of highly discrete event data. We illustrate their potential for palaeoclimate studies, particularly in detecting synchronisation between signals of discrete extreme events and continuous signals, estimating power spectra of spiky signals, and analysing data with irregular sampling.

How to cite: Marwan, N. and Braun, T.: New concepts on quantifying event data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10258, https://doi.org/10.5194/egusphere-egu24-10258, 2024.

EGU24-10415 | ECS | Orals | NP4.1

Application of Transfer Learning techniques in one day ahead PV production prediction 

Marek Lóderer, Michal Sandanus, Peter Pavlík, and Viera Rozinajová

Nowadays photovoltaic panels are becoming more affordable, efficient, and popular due to their low carbon footprint. PV panels can be installed in many places providing green energy to the local grid reducing energy cost and transmission losses. Since the PV production is highly dependent on the weather conditions, it is extremely important to estimate expected output in advance in order to maintain energy balance in the grid and provide enough time to schedule load distribution. The PV production output can be calculated by various statistical and machine learning prediction methods. In general, the more data available, the more precise predictions can be produced. This poses a problem for recently installed PV panels for which not enough data has been collected or the collected data are incomplete. 

A possible solution to the problem can be the application of an approach called Transfer Learning which has the inherent ability to effectively deal with missing or insufficient amounts of data. Basically, Transfer Learning is a machine learning approach which offers the capability of transferring knowledge acquired from the source domain (in our case a PV panel with a large amount of historical data) to different target domains (PV panels with very little collected historical data) to resolve related problems (provide reliable PV production predictions). 

In our study, we investigate the application, benefits and drawbacks of Transfer Learning for one day ahead PV production prediction. The model used in the study is based on complex neural network architecture, feature engineering and data selection. Moreover, we focus on the exploration of multiple approaches of adjusting weights in the target model retraining process which affect the minimum amount of training data required, final prediction accuracy and model’s overall robustness. Our models use historical meteorological forecasts from Deutscher Wetterdienst (DWD) and photovoltaic measurements from the project PVOutput which collects data from installed solar systems across the globe. Evaluation is performed on more than 100 installed PV panels in Central Europe.

How to cite: Lóderer, M., Sandanus, M., Pavlík, P., and Rozinajová, V.: Application of Transfer Learning techniques in one day ahead PV production prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10415, https://doi.org/10.5194/egusphere-egu24-10415, 2024.

EGU24-11897 | Posters on site | NP4.1

Results of joint processing of magnetic observatory data of international Intermagnet network in a unified coordinate system 

Beibit Zhumabayev, Ivan Vassilyev, Zhasulan Mendakulov, Inna Fedulina, and Vitaliy Kapytin

In each magnetic observatory, the magnetic field is registered in local Cartesian coordinate systems associated with the geographic coordinates of the locations of these observatories. To observe extraterrestrial magnetic field sources, such as the interplanetary magnetic field or magnetic clouds, a method of joint processing of data from magnetic observatories of the international Intermagnet network was implemented. In this method, the constant component is removed from the observation results of individual observatories, their measurement data is converted into the ecliptic coordinate system, and the results obtained from all observatories are averaged after the coordinate transformation.

The first data on joint processing of measurement results from the international network of Intermagnet magnetic observatories in the period before the onset of magnetic storms of various types, during these storms and after their end are presented. There is a significant improvement in the signal-to-noise ratio after combining the measurement results from all observatories, which makes it possible to isolate weaker external magnetic fields. A change in the shape of magnetic field variations is shown, which can provide new knowledge about the mechanism of development of magnetic storms.

How to cite: Zhumabayev, B., Vassilyev, I., Mendakulov, Z., Fedulina, I., and Kapytin, V.: Results of joint processing of magnetic observatory data of international Intermagnet network in a unified coordinate system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11897, https://doi.org/10.5194/egusphere-egu24-11897, 2024.

We introduce the CLEAN algorithm to identify narrowband Ultra Low Frequency (ULF) Pc5 plasma waves in Earth’s magnetosphere. The CLEAN method was first used for constructing 2D images in astronomical radio interferometry but has since been applied to a huge range of areas including adaptation for time series analysis. The algorithm performs a nonlinear deconvolution in the frequency domain (equivalent to a least-squares in the time domain) allowing for identification of multiple individual wave spectral peaks within the same power spectral density. The CLEAN method also produces real amplitudes instead of model fits to the peaks and retains phase information. We applied the method to GOES magnetometer data spanning 30 years to study the distribution of narrowband Pc5 ULF waves at geosynchronous orbit. We found close to 30,0000 wave events in each of the vector magnetic field components in field-aligned coordinates. We discuss wave occurrence and amplitudes distributed in local time and frequency. The distribution of the waves under different solar wind conditions are also presented. With some precautions, which are applicable to other event identification methods, the CLEAN technique can be utilized to detect wave events and its harmonics in the magnetosphere and beyond. We also discuss limitations of the method mainly the detection of unrealistic peaks due to aliasing and Gibbs phenomena.

How to cite: Inceoglu, F. and Loto'aniu, P.: Using the CLEAN Algorithm to Determine the Distribution of Ultra Low Frequency Waves at Geostationary Orbit, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12928, https://doi.org/10.5194/egusphere-egu24-12928, 2024.

EGU24-12938 | Posters on site | NP4.1

Applying Multifractal Theory and Statistical Techniques for High Energy Volcanic Explosion Detection and Seismic Activity Monitoring in Volcanic Time Series 

Marisol Monterrubio-Velasco, Xavier Lana, Raúl Arámbula-Mendoza, and Ramón Zúñiga

Understanding volcanic activity through time series data analysis is crucial for uncovering the fundamental physical mechanisms governing this natural phenomenon.

In this study, we show the application of multifractal and fractal methodologies, along with statistical analysis, to investigate time series associated with volcanic activity. We aim to make use of these approaches to identify significant variations within the physical processes related to changes in volcanic activity. These methodologies offer the potential to identify pertinent changes preceding a high-energy explosion or a significant volcanic eruption.

In particular, we apply it to analyze two study cases. First, the evolution of the multifractal structure of volcanic emissions of low, moderate, and high energy explosions applied to Volcán de Colima (México years 2013-2015). The results contribute to obtaining quite evident signs of the immediacy of possible dangerous emissions of high energy, close to 8.0x10^8 J. Additionally, the evolution of the adapted Gutenberg-Richter seismic law to volcanic energy emissions contributes to confirm the results obtained using multifractal analysis. Secondly, we also studied the time series of the Gutenberg-Richter b-parameter of seismic activities associated with volcanic emissions in Iceland, Hawaii, and the Canary Islands, through the concept of Disparity (degree of irregularity), the fractal Hurst exponent, H, and several multifractal parameters. The results obtained should facilitate a better knowledge of the relationships between the activity of volcanic emissions and the corresponding related seismic activities.  

How to cite: Monterrubio-Velasco, M., Lana, X., Arámbula-Mendoza, R., and Zúñiga, R.: Applying Multifractal Theory and Statistical Techniques for High Energy Volcanic Explosion Detection and Seismic Activity Monitoring in Volcanic Time Series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12938, https://doi.org/10.5194/egusphere-egu24-12938, 2024.

EGU24-13593 | ECS | Posters on site | NP4.1

Characterizing Uncertainty in Spatially Interpolated Time Series of Near-Surface Air Temperature 

Conor Doherty and Weile Wang

Spatially interpolated meteorological data products are widely used in the geosciences as well as disciplines like epidemiology, economics, and others. Recent work has examined methods for quantifying uncertainty in gridded estimates of near-surface air temperature that produce distributions rather than simply point estimates at each location. However, meteorological variables are correlated not only in space but in time, and sampling without accounting for temporal autocorrelation produces unrealistic time series and potentially underestimates cumulative errors. This work first examines how uncertainty in air temperature estimates varies in time, both seasonally and at shorter timescales. It then uses data-driven, spectral, and statistical methods to better characterize uncertainty in time series of estimated air temperature values. Methods for sampling that reproduce spatial and temporal autocorrelation are presented and evaluated. The results of this work are particularly relevant to domains like agricultural and ecology. Physical processes including evapotranspiration and primary production are sensitive to variables like near-surface air temperature, and errors in these important meteorological inputs accumulate in model outputs over time.

How to cite: Doherty, C. and Wang, W.: Characterizing Uncertainty in Spatially Interpolated Time Series of Near-Surface Air Temperature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13593, https://doi.org/10.5194/egusphere-egu24-13593, 2024.

EGU24-13879 | ECS | Posters on site | NP4.1

Understanding the role of vegetation responses to drought in regulating autumn senescence 

Eunhye Choi and Josh Gray

Vegetation phenology is the recurring of plant growth, including the cessation and resumption of growth, and plays a significant role in shaping terrestrial water, nutrient, and carbon cycles. Changes in temperature and precipitation have already induced phenological changes around the globe, and these trends are likely to continue or even accelerate. While warming has advanced spring arrival in many places, the effects on autumn phenology are less clear-cut, with evidence for earlier, delayed, or even unchanged end of the growing season (EOS). Meteorological droughts are intensifying in duration and frequency because of climate change. Droughts intricately impact changes in vegetation, contingent upon whether the ecosystem is limited by water or energy. These droughts have the potential to influence EOS changes. Despite this, the influence of drought on EOS remains largely unexplored. This study examined moisture’s role in controlling EOS by understanding the relationship between precipitation anomalies, vegetation’s sensitivity to precipitation (SPPT), and EOS. We also assess regional variations in responses to the impact of SPPT on EOS.

The study utilized multiple vegetation and water satellite products to examine the patterns of SPPT in drought and its impact on EOS across aridity gradients and vegetation types. By collectively evaluating diverse SPPTs from various satellite datasets, this work offers a comprehensive understanding and critical basis for assessing the impact of drought on EOS. We focused on the Northern Hemisphere from 2000 to 2020, employing robust statistical methods. This work found that, in many places, there was a stronger relationship between EOS and drought in areas with higher SPPT. Additionally, a non-linear negative relationship was identified between EOS and SPPT in drier regions, contracting with a non-linear positive relationship observed in wetter regions. These findings were consistent across a range of satellite-derived vegetation products. Our findings provide valuable insights into the effects of SPPT on EOS during drought, enhancing our understanding of vegetation responses to drought and its consequences on EOS and aiding in identifying drought-vulnerable areas.

How to cite: Choi, E. and Gray, J.: Understanding the role of vegetation responses to drought in regulating autumn senescence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13879, https://doi.org/10.5194/egusphere-egu24-13879, 2024.

EGU24-16981 | ECS | Orals | NP4.1

A machine-learning-based approach for predicting the geomagnetic secular variation 

Sho Sato and Hiroaki Toh

We present a machine-learning-based approach for predicting the geomagnetic main field changes, known as secular variation (SV), in a 5-year range for use for the 14th generation of International Geomagnetic Reference Field (IGRF-14). The training and test datasets of the machine learning (ML) models are geomagnetic field snapshots derived from magnetic observatory hourly means, and CHAMP and Swarm-A satellite data (MCM Model; Ropp et al., 2020). The geomagnetic field data are not used as-is in the original time series but were differenced twice before training. Because SV is strongly influenced by the geodynamo process occurring in the Earth's outer core, challenges still persist despite efforts to model and forecast the realistic nonlinear behaviors (such as the geomagnetic jerks) of the geodynamo through data assimilation. We compare three physics-uninformed ML models, namely, the Autoregressive (AR) model, Vector Autoregressive (VAR) model, and Recurrent Neural Network (RNN) model, to represent the short-term temporal evolution of the geomagnetic main field on the Earth’s surface. The quality of 5-year predictions is tested by the hindcast results for the learning window from 2004.50 to 2014.25. These tests show that the forecast performance of our ML model is comparable with that of candidate models of IGRF-13 in terms of data misfits after the release epoch (Year 2014.75). It is found that all three ML models give 5-year prediction errors of less than 100nT, among which the RNN model shows a slightly better accuracy. They also suggest that Overfitting to the training data used is an undesirable machine learning behavior that occurs when the RNN model gives accurate reproduction of training data but not for forecasting targets.

How to cite: Sato, S. and Toh, H.: A machine-learning-based approach for predicting the geomagnetic secular variation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16981, https://doi.org/10.5194/egusphere-egu24-16981, 2024.

EGU24-17344 | Posters on site | NP4.1

Introducing a new statistical theory to quantify the Gaussianity of the continuous seismic signal 

Éric Beucler, Mickaël Bonnin, and Arthur Cuvier

The quality of the seismic signal recorded at permanent and temporary stations is sometimes degraded, either abruptly or over time. The most likely cause is a high level of humidity, leading to corrosion of the connectors but environmental changes can also alter recording conditions in various frequency ranges and not necessarily for all three components in the same way. Assuming that the continuous seismic signal can be described by a normal distribution, we present a new approach to quantify the seismogram quality and to point out any time sample that deviates from this Gaussian assumption. To this end the notion of background Gaussian signal (BGS) to statistically describe a set of samples that follows a normal distribution. The discrete function obtained by sorting the samples in ascending order of amplitudes is compared to a modified probit function to retrieve the elements composing the BGS, and its statistical properties, mostly the Gaussian standard deviation, which can then differ from the classical standard deviation. Hence the ratio of both standard deviations directly quantifies the dominant gaussianity of the continuous signal and any variation reflects a statistical modification of the signal quality. We present examples showing daily variations in this ratio for stations known to have been affected by humidity, resulting in signal degradation. The theory developed can be used to detect subtle variations in the Gaussianity of the signal, but also to point out any samples that don't match the Gaussianity assumption, which can then be used for other seismological purposes, such as coda determination.

How to cite: Beucler, É., Bonnin, M., and Cuvier, A.: Introducing a new statistical theory to quantify the Gaussianity of the continuous seismic signal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17344, https://doi.org/10.5194/egusphere-egu24-17344, 2024.

EGU24-17566 | ECS | Posters on site | NP4.1

Unveiling Climate-Induced Ocean Wave Activities Using Seismic Array Data in the North Sea Region 

Yichen Zhong, Chen Gu, Michael Fehler, German Prieto, Peng Wu, Zhi Yuan, Zhuoyu Chen, and Borui Kang

Climate events may induce abnormal ocean wave activities, that can be detected by seismic array on nearby coastlines. We collected long-term continuous array seismic data in the Groningen area and the coastal areas of the North Sea, conducted a comprehensive analysis to extract valuable climate information hidden within the ambient noise. Through long-term spectral analysis, we identified the frequency band ranging from approximately 0.2Hz, which appears to be associated with swell waves within the region, exhibiting a strong correlation with the significant wave height (SWH). Additionally, the wind waves with a frequency of approximately 0.4 Hz and gravity waves with periods exceeding 100 seconds were detected from the seismic ambient noise. We performed a correlation analysis between the ambient noise and various climatic indexes across different frequency bands. The results revealed a significant correlation between the North Atlantic Oscillation (NAO) Index and the ambient noise around 0.17Hz.

Subsequently, we extracted the annual variation curves of SWH frequency from ambient noise at each station around the North Sea and assembled them into a sparse spatial grid time series (SGTS). An empirical orthogonal function (EOF) analysis was conducted, and the Principal Component (PC) time series derived from the EOF analysis were subjected to a correlation analysis with the WAVEWATCH III (WW3) model simulation data, thereby confirming the wave patterns. Moreover, we conducted the spatial distribution study of SGTS. The spatial features revealed that the southern regions of the North Sea exhibit higher wind-wave energy components influenced by the Icelandic Low pressure system and topography, which explains the correlation between ambient noise in the region and the NAO index. Furthermore, spatial features disclosed a correlation between the first EOF mode of the North Sea ocean waves and the third mode of sea surface temperature anomalies. This research shows the potential of utilizing existing off-shore seismic monitoring systems to study global climate variation and physical oceanography.

How to cite: Zhong, Y., Gu, C., Fehler, M., Prieto, G., Wu, P., Yuan, Z., Chen, Z., and Kang, B.: Unveiling Climate-Induced Ocean Wave Activities Using Seismic Array Data in the North Sea Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17566, https://doi.org/10.5194/egusphere-egu24-17566, 2024.

EGU24-18061 | ECS | Orals | NP4.1

A new methodology for time-series reconstruction of global scale historical Earth observation data 

Davide Consoli, Leandro Parente, and Martijn Witjes

Several machine learning algorithms and analytical techniques do not allow gaps or non-values in input data. Unfortunately, earth observation (EO) datasets, such as satellite images, are gravely affected by cloud contamination and sensor artifacts that create gaps in the time series of collected images. This limits the usage of several powerful techniques for modeling and analysis. To overcome these limitations, several works in literature propose different imputation methods to reconstruct the gappy time series of images, providing complete time-space datasets and enabling their usage as input for many techniques.

However, among the time-series reconstruction methods available in literature, only a few of them are publicly available (open source code), applicable without any external source of data, and suitable for application to petabyte (PB) sized dataset like the full Landsat archive. The few methods that match all these characteristics are usually quite trivial (e.g. linear interpolation) and, as a consequence, they often show poor performance in reconstructing the images. 

For this reason, we propose a new methodology for time series reconstruction designed to match all these requirements. Like some other methods in literature, the new method, named seasonally weighted average generalization (SWAG), works purely on the time dimension, reconstructing the images working on each time series of each pixel separately. In particular, the method uses a weighted average of the samples available in the original time series to reconstruct the missing values. Enforcing the annual seasonality of each band as a prior, for the reconstruction of each missing sample in the time series a higher weight is given to images that are collected exactly on integer multiples of a year. To avoid propagation of land cover changes in future or past images, higher weights are given to more recent images. Finally, to have a method that respects causality, only images from the past of each sample in the time series are used.

To have computational performance suitable for PB sized datasets the method has been implemented in C++ using a sequence of fast convolution methods and Hadamard products and divisions. The method has been applied to a bimonthly aggregated version of the global GLAD Landsat ARD-2 collection from 1997 to 2022, producing a 400 terabyte output dataset. The produced dataset will be used to generate maps for several biophysical parameters, such as Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), normalized difference water index (NDWI) and bare soil fraction (BSF). The code is available as open source, and the result is fully reproducible.

References:

Potapov, Hansen, Kommareddy, Kommareddy, Turubanova, Pickens, ... & Ying  (2020). Landsat analysis ready data for global land cover and land cover change mapping. Remote Sensing, 12(3), 426.

Julien, & Sobrino (2019). Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data. International Journal of Applied Earth Observation and Geoinformation, 76, 93-111.

Radeloff, Roy, Wulder, Anderson, Cook, Crawford, ... & Zhu (2024). Need and vision for global medium-resolution Landsat and Sentinel-2 data products. Remote Sensing of Environment, 300, 113918.

How to cite: Consoli, D., Parente, L., and Witjes, M.: A new methodology for time-series reconstruction of global scale historical Earth observation data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18061, https://doi.org/10.5194/egusphere-egu24-18061, 2024.

EGU24-18197 | ECS | Orals | NP4.1 | Highlight

The regularity of climate-related extreme events under global warming 

Karim Zantout, Katja Frieler, and Jacob Schewe and the ISIMIP team

Climate variability gives rise to many different kinds of extreme impact events, including heat waves, crop failures, or wildfires. The frequency and magnitude of such events are changing under global warming. However, it is less known to what extent such events occur with some regularity, and whether this regularity is also changing as a result of climate change. Here, we present a novel method to systematically study the time-autocorrelation of these extreme impact events, that is, whether they occur with a certain regularity. In studies of climate change impacts, different types of events are often studied in isolation, but in reality they interact. We use ensembles of global biophysical impact simulations from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) driven with climate models to assess current conditions and projections. The time series analysis is based on a discrete Fourier transformation that accounts for the stochastic fluctuations from the climate model. Our results show that some climate impacts, such as crop failure, indeed exhibit a dominant frequency of recurrence; and also, that these regularity patterns change over time due to anthropogenic climate forcing.

How to cite: Zantout, K., Frieler, K., and Schewe, J. and the ISIMIP team: The regularity of climate-related extreme events under global warming, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18197, https://doi.org/10.5194/egusphere-egu24-18197, 2024.

EGU24-18210 | ECS | Posters on site | NP4.1

Long-term vegetation development in context of morphodynamic processes since mid-19th century 

Katharina Ramskogler, Moritz Altmann, Sebastian Mikolka-Flöry, and Erich Tasser

The availability of comprehensive aerial photography is limited to the mid-20th century, posing a challenge for quantitatively analyzing long-term surface changes in proglacial areas. This creates a gap of approximately 100 years, spanning the end of the Little Ice Age (LIA). Employing digital monoplotting and historical terrestrial images, our study reveals quantitative surface changes in a LIA lateral moraine section dating back to the second half of the 19th century, encompassing a total study period of 130 years (1890 to 2020). With the long-term analysis at the steep lateral moraines of Gepatschferner (Kauner Valley, Tyrol, Austria) we aimed to identify changes in vegetation development in context with morphodynamic processes and the changing climate.

In 1953, there was an expansion in the area covered by vegetation, notably encompassing scree communities, alpine grassland, and dwarf shrubs. However, the destabilization of the system after 1980, triggered by rising temperatures and the resulting thawing of permafrost, led to a decline in vegetation cover by 2020. Notably, our observations indicated that, in addition to morphodynamic processes, the overarching trends in temperature and precipitation exerted a substantial influence on vegetation development. Furthermore, areas with robust vegetation cover, once stabilised, were reactivated and subjected to erosion, possibly attributed to rising temperatures post-1980.

This study demonstrates the capability of historical terrestrial images to enhance the reconstruction of vegetation development in context with morphodynamics in high alpine environments within the context of climate change. However, it is important to note that long-term mapping of vegetation development through digital monoplotting has limitations, contingent on the accessibility and quality of historical terrestrial images, as well as the challenges posed by shadows in high alpine regions. Despite these limitations, this long-term approach offers fundamental data on vegetation development for future modelling efforts.

How to cite: Ramskogler, K., Altmann, M., Mikolka-Flöry, S., and Tasser, E.: Long-term vegetation development in context of morphodynamic processes since mid-19th century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18210, https://doi.org/10.5194/egusphere-egu24-18210, 2024.

EGU24-19601 | ECS | Posters on site | NP4.1

Discrimination of  geomagnetic quasi-periodic signals by using SSA Transform 

Palangio Paolo Giovanni and Santarelli Lucia

Discrimination of  geomagnetic quasi-periodic signals by using SSA Transform

  • Palangio1, L. Santarelli 1

1Istituto Nazionale di Geofisica e Vulcanologia L’Aquila

3Istituto Nazionale di Geofisica e Vulcanologia Roma

 

Correspondence to:  lucia.santarelli@ingv.it

 

Abstract

In this paper we present an application of  the SSA Transform to the detection and reconstruction of  very weak geomagnetic signals hidden in noise. In the SSA Transform  multiple subspaces are used for representing and reconstructing   signals and noise.  This analysis allows us to reconstruct, in the time domain, the different harmonic components contained in the original signal by using  ortogonal functions. The objective is to identificate the dominant  subspaces that can be attributed to the  signals and the subspaces that can be attributed to the noise,  assuming that all these  subspaces are orthogonal to each other, which implies that the  signals and noise  are independent of one another. The subspace of the signals is mapped simultaneously on several spaces with a lower dimension, favoring the dimensions that best discriminate the patterns. Each subspace of the signal space is used to encode different subsets of functions having common characteristics, such as  the same periodicities. The subspaces  identification was performed by using singular value decomposition (SVD) techniques,  known as  SVD-based identification methods  classified in a subspace-oriented scheme.The  quasi-periodic variations of geomagnetic field  has been investigated in the range of scale which span from 22 years to 8.9 days such as the  Sun’s polarity reversal cycle (22 years), sun-spot cycle (11 years), equinoctial effect (6 months), synodic rotation of the Sun (27 days) and its harmonics. The strength of these signals vary from fractions of a nT to tens of nT. Phase and frequency variability of these cycles has been evaluated from the range of variations in the geomagnetic field recorded at middle latitude place (covering roughly 4.5 sunspot cycles). Magnetic data recorded at L'Aquila Geomagnetic observatory (geographic coordinates: 42° 23’ N, 13° 19’E, geomagnetic coordinates: 36.3° N,87°.2 E, L-shell=1.6) are used from 1960 to 2009.

 

 

How to cite: Paolo Giovanni, P. and Lucia, S.: Discrimination of  geomagnetic quasi-periodic signals by using SSA Transform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19601, https://doi.org/10.5194/egusphere-egu24-19601, 2024.

EGU24-22262 | ECS | Posters on site | NP4.1

Temporal Interpolation of Sentinel-2 Multispectral Time Series in Context of Land Cover Classification with Machine Learning Algorithms 

Mate Simon, Mátyás Richter-Cserey, Vivien Pacskó, and Dániel Kristóf

Over the past decades, especially since 2014, large quantities of Earth Observation (EO) data became available in high spatial and temporal resolution, thanks to ever-developing constellations (e.g.: Sentinel, Landsat) and open data policy. However, in the case of optical images, affected by cloud coverage and the spatially changing overlap of relative satellite orbits, creating temporally generalized and dense time series by using only measured data is challenging, especially when studying larger areas.

Several papers investigate the question of spatio-temporal gap filling and show different interpolation methods to calculate missing values corresponding to the measurements. In the past years more products and technologies have been constructed and published in this field, for example Copernicus HR-VPP Seasonal Trajectories (ST) product.  These generalized data structures are essential to the comparative analysis of different time periods or areas and improve the reliability of data analyzing methods such as Fourier transform or correlation. Temporally harmonized input data is also necessary in order to improve the results of Machine Learning classification algorithms such as Random Forest or Convolutional Neural Networks (CNN). These are among the most efficient methods to separate land cover categories like arable lands, forests, grasslands and built-up areas, or crop types within the arable category.

This study analyzes the efficiency of different interpolation methods on Sentinel-2 multispectral time series in the context of land cover classification with Machine Learning. We compare several types of interpolation e.g. linear, cubic and cubic-spline and also examine and optimize more advanced methods like Inverse Distance Weighted (IDW) and Radial Basis Function (RBF). We quantify the accuracy of each method by calculating mean square error between measured and interpolated data points. The role of interpolation of the input dataset in Deep Learning (CNN) is investigated by comparing Overall, Kappa and categorical accuracies of land cover maps created from only measured and interpolated time series. First results show that interpolation has a relevant positive effect on accuracy statistics. This method is also essential in taking a step towards constructing robust pretrained Deep Learning models, transferable between different time intervals and agro-ecological regions.

The research has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the KDP-2021 funding scheme.

 

Keywords: time series analysis, Machine Learning, interpolation, Sentinel

How to cite: Simon, M., Richter-Cserey, M., Pacskó, V., and Kristóf, D.: Temporal Interpolation of Sentinel-2 Multispectral Time Series in Context of Land Cover Classification with Machine Learning Algorithms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22262, https://doi.org/10.5194/egusphere-egu24-22262, 2024.

GI3 – Planetary Atmosphere and Ocean instrumentation system

EGU24-275 | ECS | Orals | GI3.3

Detection and localisation of fluid emissions in water column data using Deep Learning with acoustic and spatial information 

Tyméa Perret, Gilles Le Chenadec, Arnaud Gaillot, Yoann Ladroit, and Stéphanie Dupré

Fluid emissions from the seafloor affect ocean chemistry and are involved in the geological processes taking place along active and passive continental margins. These emissions are linked to geological hazards, such as earthquakes, sedimentary instabilities, and extensive methane release. Detecting and locating the sources of fluid emissions is therefore of paramount importance. Hydrographic MultiBeam EchoSounders (MBES) designed for seafloor mapping can record the acoustic backscatter of the water column. Due to the impedance contrast between gas and seawater, gas bubbles form "acoustic plumes" in the echograms. Acoustic data assists in guiding the exploration of seeps and their associated geological structures. However, processing the vast amount of data generated by these sounders is a significant undertaking.

The present study is based on the data collected from two surveys, GAZCOGNE1 (Bay of Biscay, Aquitaine Basin) and GHASS2 (Black Sea) during which data were collected using a Kongsberg EM302 MBES (30 kHz transmit frequency) and a Reason Seabat 7150 MBES (24 kHz transmit frequency) respectively. These sounders have proven to be very effective in identifying fluid emissions.

Deep learning has become increasingly popular in marine science over the last few decades due to the use of Graphical Processing Units and large amounts of labelled data. This method has proven to be particularly robust in accurately analysing large datasets and identifying complex patterns. We have devised a deep-learning approach that allows us to: 1) Detect fluid-related echoes in multibeam echograms. 2) Conduct near real-time fluid detection and tracking during the acquisition surveys and provide accurate positioning of the fluid outlet beneath the seafloor based on acoustic and spatial attributes. 3) Discriminate between fluid-related echoes emanating from the primary lobe of the multibeam directivity and those originating from the side lobes, in order to accurately locate the fluid outlet. This last approach results from antenna modelling and multibeam survey simulation. The technique for echo discrimination using antenna modelling was produced with the open-source toolbox published by Urban et al 2023 (https://doi.org/10.1002/lom3.10552).

Detection on the multibeam echograms is performed by adapting the open-source You-Only-Look-Once algorithm (version 5). Training on Ifremer datasets showed that the results surpass those of a state-of-the-art method regardless of the MBES used for training and testing. Hence, this method can be applied to diverse MBES data, acoustic acquisition parameters and environmental conditions. The algorithm can detect signals throughout the entire water column, even in areas affected by acoustic artefacts such as specular side lobes and different emission sectors. We have developed methods to improve neural network learning using training sets when limited labelled MBES data are available. The method was tested during an oceanographic expedition in the summer of 2022 (MAYOBS23), demonstrating its ability to operate in near real-time with excellent performance.

The marine expedition GAZCOGNE1, part of the PAMELA project, was co-funded by TotalEnergies and IFREMER. The expedition GHASS2 was co-founded by the Agence Nationale de la Recherche for BLAck sea MEthane (BLAME) project and IFREMER. MAYOBS23 was funded by the Mayotte volcanological and seismological monitoring network REVOSIMA.

 

How to cite: Perret, T., Le Chenadec, G., Gaillot, A., Ladroit, Y., and Dupré, S.: Detection and localisation of fluid emissions in water column data using Deep Learning with acoustic and spatial information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-275, https://doi.org/10.5194/egusphere-egu24-275, 2024.

EGU24-1200 | ECS | Posters on site | GI3.3

Unveiling Exoplanets Through the Power of ML: A Comparative Analysis of RandomForest and Gaussian Models 

Fatemeh Fazel, Bernard Foing, Amin Rostami, and Álvaro Ropero López

In recent years, the exploration of exoplanets has gained momentum due to the increasing volume of data collected from missions like Kepler. Machine learning (ML) techniques have proven to be valuable tools for efficiently analyzing and classifying exoplanet candidates. This study focuses on the application of ML models, specifically Random Forest and Gaussian methods, to identify exoplanets using the light curves obtained from Kepler's archived data.

The research aims to develop accurate and robust models capable of distinguishing exoplanets from other celestial objects. Feature engineering techniques are employed to extract relevant information from the light curves, including transit depth, transit duration, and periodicity patterns. These features serve as inputs for both the Random Forest and Gaussian models, enabling them to learn and generalize from the training data.

The Random Forest model, known for its ensemble-based approach, demonstrates exceptional performance in exoplanet identification. Its ability to capture complex relationships among features and make accurate predictions results in high precision and recall scores. On the other hand, the Gaussian method, which relies on probabilistic modeling, exhibits competitive results through a different classification approach.

The performance of the Random Forest and Gaussian models is compared using comprehensive evaluation metrics such as accuracy, precision, recall, and F1 score. The results indicate that the Random Forest model outperforms the Gaussian method in terms of precision and recall. This highlights the effectiveness of ensemble-based ML techniques for exoplanet identification tasks.

In conclusion, this study successfully demonstrates the utilization of ML models, specifically Random Forest and Gaussian methods, for exoplanet identification using Kepler's archived data and light curves. The Random Forest model emerges as the superior choice, achieving higher accuracy and recall rates in distinguishing exoplanets from other celestial objects. These findings contribute to the advancement of exoplanet research and pave the way for the development of more precise and efficient identification methods in the future.

How to cite: Fazel, F., Foing, B., Rostami, A., and Ropero López, Á.: Unveiling Exoplanets Through the Power of ML: A Comparative Analysis of RandomForest and Gaussian Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1200, https://doi.org/10.5194/egusphere-egu24-1200, 2024.

EGU24-1359 | ECS | Orals | GI3.3

Towards 3D SPM monitoring in the North Sea using multibeam sonar 

Nore Praet, Peter Urban, Marc Roche, Jonas Mortelmans, Rune Lagaisse, and Thomas Vandorpe

Monitoring suspended particulate matter (SPM) in coastal areas is essential for research, management and protection of coastal ecosystems. In the Belgian part of the North Sea, the dynamic nature of SPM variability and the increasing human activities (offshore windmill parks, dredging and dumping) call for 3D monitoring of these natural and human-induced SPM changes.

Multibeam echosounders (MBES) provide, in addition to bathymetry and seafloor backscatter data, a 3D dataset of acoustic measurements in the water column, which can be used to monitor SPM in coastal waters. Although MBES water column data are commonly used by fisheries and gas seepage research, only a handful of studies focus on the quantification of SPM in the water column.

During the Timbers project, we developed a novel methodology to convert MBES water column data into 3D SPM maps. In contrast to most studies that deploy the MBES from stations, we quantified SPM using MBES from a sailing vessel. Simultaneous optical and acoustic measurements were collected during ship transects to yield an empirical relation using linear regression modeling. This relationship was then used to convert the acoustic measurements into a 3D grid that displays the mass concentration of SPM. The large spatial coverage of these SPM maps allows us to observe phenomena in the water column that otherwise would be missed by traditional monitoring approaches. Furthermore, several valuable lessons were learned. In particular, the interpretation of the acoustic signal is not straightforward, which makes it difficult to distinguish between different types of scatterers (sediment, plankton, flocs, bubbles, fish, etc.) captured by the MBES. Hence, additional research efforts focusing on discriminating scatterers in the water column are needed to unlock the full monitoring potential of MBES water column data.

In the ongoing Turbeams project, we are exploring multi-frequency approaches to differentiate between various scatterers and their wide spectrum of sizes. Additionally, we are applying imaging tools on collected water samples and we are using underwater cameras that capture particles in their natural environment. These improvements will help to move towards operational use of MBES as a common tool for SPM monitoring in the future.

How to cite: Praet, N., Urban, P., Roche, M., Mortelmans, J., Lagaisse, R., and Vandorpe, T.: Towards 3D SPM monitoring in the North Sea using multibeam sonar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1359, https://doi.org/10.5194/egusphere-egu24-1359, 2024.

EGU24-5925 | Orals | GI3.3

Mapping gas seeps with multibeam water column data in the Norwegian offshore – Challenges and way forward 

Shyam Chand, Alexandre C. G. Schimel, Terje Thorsnes, and Valérie Bellec

Seepage of gases from natural sources of subsurface hydrocarbon accumulations escaping through the seafloor to the water column is recorded in many parts of the world’s oceans. These occurrences can be acoustically and visually observed using various sensors onboard various platforms. This is particularly common when carrying out bathymetric surveys of large areas using multibeam echosounder systems with the capability of recording the whole water column acoustic backscattering. The so-called “water-column data” that these systems produce can then be inspected for acoustic anomalies that are characteristic of gas seepages (i.e. acoustic “gas flares”), and those instances and their attributes (e.g. strength, confidence, height, etc.) can be recorded in a database. The Geological Survey of Norway has been building such a database for the Norwegian offshore since 2010. To date, this database includes over 5,000 flares of varying magnitudes and sizes, detected in an area of >140,000 km2. The water-column data used for this task mainly originates from the many multibeam surveys carried out since 2005 over large areas of the Norwegian offshore for the MAREANO program, which is aimed at mapping habitats, but also from datasets acquired in associated projects and sources.

We present the results from these comprehensive surveys and discuss the various challenges faced in making such a database. Our main challenges are the very large size of the datasets and our reliance on visual interpretation, which necessitate dedicated software, high-performance processing systems, storage solutions of very large capacity and fast access, considerable interpretation time, and procedures of cross-validation between different interpreters. Another challenge is the variety of the data and its quality due to various acquisition parameters, weather conditions, and water depths, but also from the use of various systems, models, generations, and frequencies. This variety impacts the visual aspect of acoustic gas flares and thus affects the ability of the interpreters to consistently estimate flare magnitude and size. However, this variety also presents research opportunities. For example, we possess several instances of acoustic gas flares that were imaged with a range of frequencies, allowing for frequency dependence analysis. Finally, we will discuss future possibilities for interpreting water-column data in more time-efficient and interpreter-independent manners.

How to cite: Chand, S., Schimel, A. C. G., Thorsnes, T., and Bellec, V.: Mapping gas seeps with multibeam water column data in the Norwegian offshore – Challenges and way forward, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5925, https://doi.org/10.5194/egusphere-egu24-5925, 2024.

EGU24-7810 | ECS | Orals | GI3.3

Multidisciplinary approach to assess the far-field effects of sand extraction in the Belgian part of the North Sea.  

Benjamin Van Roozendael, Koen Degrendele, Florian Barette, Helga Vandenreyken, Anne-Sophie Piette, Vera Van Lancker, Lars Kint, Katrijn Baetens, Pauline Denis, Peter Urban, Nore Praet, and Marc Roche

Sand extraction on the sand banks in the Belgian part of the North Sea has various impacts on the marine environment. The direct near-field effects in areas where extraction takes place, are regularly monitored for at least two decades and well understood. In contrast, several important questions remain regarding the far-field impact associated with the dispersion of suspended particle matter (SPM) plumes. On the longer term, these SPM plumes could significantly change the integrity of the seafloor and damage the ecological valuable habitats bordering the exploited sand banks. Therefore, the Continental Shelf Service of the SPF Economy, responsible for the management of the sand extraction, instigated a project to define the range and significance of the far field impact of this activity. In close partnership with RBINS, UGent and VLIZ, a number of controlled measurements were devised to validate models predicting far field dispersal and, if necessary, improve them. Based on these models, frequency and magnitude of disturbance on nearby marine protected areas can then be determined for all sand extraction sectors.

In order to characterize SPM plumes and to estimate their dispersion distance, several experimental setups were developed, combining continuous and point measurements with the use of a quasi-real-time dispersion model. The measurements were performed on board the RV Belgica during two campaigns in November 2022 and March 2023 following dredging vessels performing extraction operations.

During the experiments, the dispersion model mapped the estimated trajectory, extension, and the deposition of the SPM plumes in real time, using a combination of hydrodynamic, waves and wind data, estimated sediment properties and the position and activity of the dredging vessels. This real-time information allowed us to position the vessel in the ideal location to validate the presence of the plume and its properties using an experimental set-up of combined acoustic and in-situ measurements. Continuous acoustic measurements of the water column involving a Kongsberg EM2040 dual RX multibeam echosounder (MBES), a Simrad EK80 single beam echosounder (SBES) and a Teledyne Acoustic Doppler Current Profiler (ADCP) were carried out jointly to map the actual position, extent and density of the plumes. These continuous measurements were completed with in situ point measurements of the water column properties through the use of several acoustic (Aquascat 1000R) and optical (LISST-200X, OBS) sensors mounted on a carousel. Additionally, water samples were collected using Niskin bottles that were filtered on board for further analyses (SPM, particulate organic carbon and nitrogen, Chlorophyl a), and analysed using a Hach turbidimeter.  Samples of the extracted sediments were collected on the seafloor and onboard the extraction vessels for granulometric analysis.

The first analysis of the November 2022 and March 2023 experiments indicate the good performance of the used dispersion model and the excellent concordance between the continuous acoustic detection of the sediment plumes with the MBES, SBES and ADCP. Additionally, our results show the importance of a profound knowledge of the spatial configuration of the involved instruments and the impact of the research vessel itself on the water column.

How to cite: Van Roozendael, B., Degrendele, K., Barette, F., Vandenreyken, H., Piette, A.-S., Van Lancker, V., Kint, L., Baetens, K., Denis, P., Urban, P., Praet, N., and Roche, M.: Multidisciplinary approach to assess the far-field effects of sand extraction in the Belgian part of the North Sea. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7810, https://doi.org/10.5194/egusphere-egu24-7810, 2024.

Sediment delivery to Greenland’s glacial fjords is expected to increase significantly in response to accelerated atmospheric and oceanic warming. As glaciers retreat on to land, melt-water will enter the fjords at the water surface rather than rising as buoyant plumes from the base of the calving front, thus reducing mixing with the nutrient-rich waters below. Increased surface sediment concentrations will prevent light penetration which, together with decreased nutrient availability, will cause a reduction in primary production and ultimately effect rates of seafloor carbon burial. Glacial fjords are a major global carbon sink, but it remains unclear how sediment delivery and transport processes in glacial fjords will change as deglaciation progresses. We present water column data acquired with an Acoustic Doppler Current Profiler (ADCP) and a multi-frequency Sonic 2026 multibeam echo-sounder deployed on a vessel in a Greenland fjord with a land-retreated glacier and a fjord with a recently-retreated glacier. The results demonstrate the capability of the multibeam echo-sounder to image suspended sediment plumes in the water column, which we compare with backscatter acquired with the ADCP. The water column imaging demonstrates how mixing processes between the freshwater plumes and tidally-driven oceanic saltwater causes sediment plumes to form near-bed concentrations of fluid mud that align with seafloor channels observed in the bathymetry data acquired with the Sonic 2026, providing new insights into sediment transport processes in fjords at different stages of deglaciation.

How to cite: Simmons, S., Trenholm, N., and Parsons, D.: Imaging suspended sediment plumes in Greenland’s fjords using a multi-frequency multibeam echo-sounder and an acoustic Doppler current profiler, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7926, https://doi.org/10.5194/egusphere-egu24-7926, 2024.

EGU24-8635 | Orals | GI3.3

Sub-Terahertz Inverse Synthetic Aperture Radar (ISAR) for monitoring of high-value space assets  

Leah-Nani Alconcel, Gruffudd Jones, Morgan Coe, Marina Gashinova, and Mikhail Cherniakov

With the rise of commercial constellation implementation in low earth orbit (LEO), the near-Earth space environment is becoming increasingly challenging to monitor and protect. As well as carefully considered policy frameworks, new observational techniques and instrumentation are needed to ensure that safe operations can be maintained by all space users. The Pervasive Sensing group at the University of Birmingham is exploring in-orbit conditional monitoring of satellites using inverse synthetic aperture radar (ISAR) as a technique for dedicated observation of high-value space-based assets. Our previous concept and design results for fixed-beam dual freqency ISAR observations in circular orbits have been extended to a variety of scenarios. I will discuss some of our recent results from both experiments and simulation. 

How to cite: Alconcel, L.-N., Jones, G., Coe, M., Gashinova, M., and Cherniakov, M.: Sub-Terahertz Inverse Synthetic Aperture Radar (ISAR) for monitoring of high-value space assets , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8635, https://doi.org/10.5194/egusphere-egu24-8635, 2024.

EGU24-8663 | ECS | Posters on site | GI3.3

Modular seismo-acoustic float technology for coastal and open ocean observation 

Sébastien Bonnieux, Karin Sigloch, Yann Hello, and Frederic Rocca
Lagrangian floats are used since the early 2000s for monitoring temperature and salinity of the oceans, and more recently for recording tele-seismic waves. This technology is originally dedicated to global monitoring because it’s drifting with oceanic currents over thousands of kilometers. Recent developments have shown that the floats can also be equipped with an anchoring or semi-anchoring system to prevent the current drift. It opens up even more possible applications for many multidisciplinary ocean science studies.
 
However, it also highlights the needs of modularity to handle different users, and evolving needs, while reducing development time without affecting reliability and cost of the instrument. We introduce some use cases from seismology to biology to identify the main requirements of modularity and discuss about software and hardware limitations. We present our approach of modular software, with a domain-specific language, allowing deployment of several applications, on a float equipped with  high and low frequency hydrophones for multidisciplinary acoustic monitoring. A first prototype will be deployed in 2023 and further developments are to come in the next years.

How to cite: Bonnieux, S., Sigloch, K., Hello, Y., and Rocca, F.: Modular seismo-acoustic float technology for coastal and open ocean observation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8663, https://doi.org/10.5194/egusphere-egu24-8663, 2024.

EGU24-8823 | ECS | Posters on site | GI3.3

Space-based sub-terahertz Inverse Synthetic Aperture Radar (ISAR) image formation and orbital assessment for monitoring of geostationary assets 

Gruffudd Jones, Morgan Coe, Leah-Nani Alconcel, Marina Gashinova, and Mikhail Cherniakov

The Pervasive Sensing group at the University of Birmingham is exploring in-orbit conditional monitoring of satellites using inverse synthetic aperture radar (ISAR) as a technique for dedicated observation of high-value space-based assets. In this work, the feasibility of geostationary orbit (GEO) observation by optimising monitoring satellite orbital parameters for sub-THz ISAR data acquisition has been assessed. A proprietary propagation simulator, Gofod, has been used to devise the scenarios for which launch conditions, stability, periodicity and time of dwell on the target will deliver the best observation of key observed satellite features. Simulation results have been validated with commercial software.

How to cite: Jones, G., Coe, M., Alconcel, L.-N., Gashinova, M., and Cherniakov, M.: Space-based sub-terahertz Inverse Synthetic Aperture Radar (ISAR) image formation and orbital assessment for monitoring of geostationary assets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8823, https://doi.org/10.5194/egusphere-egu24-8823, 2024.

EGU24-10895 | ECS | Orals | GI3.3

Visualization of Real-time Processed Multibeam SONAR Data for 3D Water-column Reconstruction 

Christian Kanarski, Bastian Kaulen, Frederik Kühne, Karoline Gussow, Finn Röhrdanz, Marco Driesen, Konstantinos Karatziotis, Jens Greinert, and Gerhard Schmidt

The use of multibeam MIMO-SONAR systems on marine vehicles (e.g. remotely operated vehicles, ROVs) enables the visual 3D reconstruction of the water-column by hydroacoustic ensonification of the surrounding environment in real-time. For underwater target detection and classification purposes, the processed SONAR data must be visualized for interpretation of the results by a human operator and to allow for a corresponding re-adjustment of the system parametrization during operation. Therefore, conventional 2D visualization approaches such as the plan position indicator (PPI) plot must be adapted to 3D. Challenges such as different signal-to-noise ratios, beamforming artifacts, and overlapping objects must be considered when choosing how to visualize the processed data to allow for the correct semantic interpretation of the scanned water-column.

In this presentation, an approach for the 3D voxel- and mesh-based visualization of real-time processed multibeam SONAR data is shown. The focus will be on how to consider the 3D beamforming and signal correlation processing, combined with data interpolation and filtering techniques, to allow for a visual reconstruction of the water-column from the SONAR data. An implementation of this approach in the C++ programming language using the Qt visualization framework will be shown in the Kiel Real-time Application Toolkit (KiRAT) for a virtual ocean environment.

How to cite: Kanarski, C., Kaulen, B., Kühne, F., Gussow, K., Röhrdanz, F., Driesen, M., Karatziotis, K., Greinert, J., and Schmidt, G.: Visualization of Real-time Processed Multibeam SONAR Data for 3D Water-column Reconstruction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10895, https://doi.org/10.5194/egusphere-egu24-10895, 2024.

EGU24-11043 | Posters on site | GI3.3

Espresso: An Open-Source Software Tool for Visualizing and Analysing Multibeam Water-Column Data 

Alexandre Schimel, Yoann Ladroit, and Sally Watson

There is currently a lack of tools for the rapid visualisation and analysis of multibeam water-column data. To address this gap, a software tool named Espresso has been developed at NIWA. Its main feature is the capability to echo-integrate the water-column data vertically and display the result in the manner of an “aerial shot”, allowing for rapid broadscale visualisation of georeferenced acoustic anomalies in the water-column across multiple files. Espresso is now open-source, licensed under MIT, maintained internationally, and available on GitHub. The software is coded in MATLAB and a compiled version is available for Windows.

Espresso is a lightweight tool with a focused set of features. It can read water-column data in the Kongsberg formats (.all/.wcd, and .kmall/.kmwcd) and Teledyne Reson format (.s7k). Data from a single ping can be visualised in the traditional “wedge” display, while multiple pings can be visualised stacked in range, depth, and vertically echo-integrated. It allows the parameterizable masking of data to be ignored, such as samples within a set distance from the seabed, from the outer beams, or within the innermost or outermost range. Espresso incorporates the “slant-range signal normalisation” algorithm (Schimel et al. 2020, doi:10.3390/rs12091371) to filter out specular artefacts. Echo-integration can be referenced to the water surface or to the seabed, with parameterizable limitations in depth or height above the seabed. The software also includes geo-picking tools for interpreters to record the location of acoustic anomalies of interest and export their information.

Espresso implements strategies to manage the typical high-volume of water-column data including memory-mapping the converted data, and parallel processing on machines disposing of a GPU. As a research software, Espresso still has some limitations, including the need for data conversion into its internal format and limited data capacity (depending on the available RAM), and thus is best seen as a complement, rather than a replacement, to commercial software for the analysis of water-column data. Despite these limitations, Espresso has already been used for several research projects, including detecting gas seeps and extracting water-column features for supervised classification approaches to habitat mapping.

How to cite: Schimel, A., Ladroit, Y., and Watson, S.: Espresso: An Open-Source Software Tool for Visualizing and Analysing Multibeam Water-Column Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11043, https://doi.org/10.5194/egusphere-egu24-11043, 2024.

EGU24-12272 | ECS | Orals | GI3.3

Disturbances compensation in high accuracy spaceborne accelerometers using multi-sensors and machine learning approach. 

Giacomo Fusco, Carlo Lefevre, Lorenzo Iafolla, Carmelo Magnafico, Massimo Chiappini, and Francesco Santoli

Italian Spring Accelerometer (ISA) is a scientific payload of the European Space Agency’s BepiColombo mission to Mercury. It aims to measure the Non Gravitational Perturbations acting on the MPO (Mercury Planetary Orbiter) spacecraft, allowing to consider it as a test-mass free falling in the planetary gravity field and hence disclosing the possibility to study the  Mercury's interior, surface, and environment, as well as to preform tests of Einstein's General Relativity theory.

ISA sensitivity to thermoelastic deformations of the spacecraft panel on which it is mounted on, is one of the limiting factors of the achievable acceleration measurements accuracy, whose target value is 10-8 m/s2 .

To address this challenge, a data analysis and reduction procedure is being developed; it is based on machine learning techniques and allows to compute an acceleration measurements correction signal, starting from the data provided by multiple supplementary sensors. Specifically, we employed the temperatures recorded by several thermometers and the information about power dissipated across the MPO in order to compute the correction signal to be applied to the ISA output. Indeed, these temperatures and dissipated power variations are responsible for the thermoelastic deformations of the mounting plate housing ISA.

The technique is being developed during the mission's cruise towards Mercury, exploiting also the outcomes of the GAIN “Gravimetro Aereo INtelligente” project, which developed a similar methodology for airborne gravimetry.

The preliminary results related to measurement sessions during the cruise phase will be presented, and considerations on the implementation of such techniques for future space missions will be provided.

Indeed, despite ISA was not specifically designed for the use of the "GAIN method”, the preliminary results are promising, underscoring its potential and allowing to envisage that future space missions could benefit of a full implementation of such a method that should go through the development of purpose built and trained multi-sensor systems.

How to cite: Fusco, G., Lefevre, C., Iafolla, L., Magnafico, C., Chiappini, M., and Santoli, F.: Disturbances compensation in high accuracy spaceborne accelerometers using multi-sensors and machine learning approach., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12272, https://doi.org/10.5194/egusphere-egu24-12272, 2024.

EGU24-13912 | Posters on site | GI3.3

Reducing uncertainty in seafloor fluid vent localization 

Garrett Mitchell and Jim Gharib

Modern water-column-imaging multibeam sonars have been shown to be effective tools for a variety of ocean mapping applications but generate immense amounts of raw data when recording acoustic backscatter over the entire water column. High data acquisition rates can pose logistic, economic, and technical challenges for rapid processing, analysis, and archiving of these data. These limitations in multibeam water column imaging often provide unique challenges in commercial marine seep hunting surveys that routinely acquire large basin-scale high-resolution multibeam datasets that require rapid processing and interpretation required for selection of coring targets for geochemical sampling of seep sediments. Interpreting the seafloor position of gas emissions in multibeam water column data using common commercial software packages is hindered by slow processing due to these large file sizes, a manual “by eye” qualitative assessment of each sonar ping searching for acoustic anomalies, skill and experience of the interpreter, fatigue of the interpreter during field operations, and environmental or acquisition artifacts that can mask the location of gas emission on the seafloor. These restrictions over regional basin-scale surveys create a qualitative data set with varying inherent positional errors that can lead to missed or incorrect observations about seep-related seafloor features and processes. By vertically integrating midwater multibeam amplitude samples over a desired range of depths, a 2D integrated midwater backscatter raster can be generated and draped over bathymetric data, providing a quantitative synoptic overview of the spatial distribution of gas plume emission sites for enhanced seafloor interpretation. We reprocess a multibeam midwater data set from NOAA Cruise EX1402L2 in the northwestern Gulf of Mexico using a vertical amplitude stacking technique. Constructed midwater backscatter surfaces are compared with digitized plume positions interpreted during EX1402L2 for a comparison into assessing uncertainty in mapping approaches. Our results show that the accuracy of manually digitizing gas emission sites varies considerably when compared with the midwater backscatter amplitude maps. This quantitative plume mapping technique offers multiple advantages over traditional geopicking from cost effectiveness, offshore efficiency, mapping repeatability, and ultimately improving the detectability of gas plume emission on the seafloor. This study shows datasets generated from this method can be reliably be used as a geophysical proxy for locating chemosynthetic and related benthic habitats.

How to cite: Mitchell, G. and Gharib, J.: Reducing uncertainty in seafloor fluid vent localization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13912, https://doi.org/10.5194/egusphere-egu24-13912, 2024.

EGU24-14741 | Posters on site | GI3.3

Machine Learning approaches to predict turbidity from multibeam echosounder data 

Thomas Hermans, Robin Thibaut, Nore Praet, and Peter Urban

Turbidity is an essential indicator of the water quality in coastal settings as it influences the penetration of light in coastal waters. Next to natural processes, turbidity is influenced by human activities such as dredging or bottom-trawling fishing activities. If turbidity is commonly characterized locally through a range of methods (moorings, tripods, ship-based samples, ACDP), the dynamic nature of turbidity requires the development of 4D monitoring methods. Recent years have seen a growth in the use of multibeam echosounder (MBES) to characterize the water column, such as for the detection of gas bubbles and MBES is also an excellent candidate to characterize the turbidity as the backscatter value is sensitive to density.

A recent study by Praet et al. (2023) analyzed the potential of MBES data to predict the suspended particle matter  concentration (SPMC). They identified a linear correlation between the average backscatter data within a sphere of predefined radius and the SPM concentration measured in-situ using a laser in-situ scattering and transmissometer (LISST). The analyzed data revealed a broad variability in the backscatter response as well as a variable correlation within the investigated SPMC range.

In this contribution, we revisit this data set using machine learning approaches to explore non-linear relationships between backscatter values and SPMC, with a special focus on uncertainty. We extended the input variables to the depth and the percentiles of the distribution of backscatter values within the predefined sphere as we anticipate they influence the uncertainty. First, we compared the ability of XGBOOST and a neural network classifier to classify MBES data into three predefined SPMC classes. Both approaches allow to identify with 90% accuracy SPMC belonging to the low value class. The accuracy for the two other classes lies around 60%, indicating the difficulty to discriminate between moderate and high concentration. Then, we used a Bayesian Probabilistic Neural Network to predict the SPMC. The latter outputs not only the estimated value but a full posterior distribution allowing uncertainty quantification. The results confirm the conclusion of the classification, with larger uncertainty observed for larger SPM concentration. Finally, preliminary tests indicate that the MBES data contain enough information to estimate the full particle size distribution within the investigated volume.

Our results reveal a complex relationship between MBES data and SPMC, requiring the use of non-linear approaches to fully exploit the information content of MBES data. The acquisition of new data should enable us to confirm and refine the machine learning models developed in this contribution and eventually use them for monitoring in real-time the turbidity of coastal waters. Particular attention should be paid to the absolute calibration of MBES data in order to use the identified relationship across multiple surveys.

Praet N., Collart T., Ollevier A., Roche M., Degrendele K., De Rijcke M., Urban P. and Vandorpe T. 2023. The potential of multibeam sonars as 3D turbidity and SPM monitoring tool in the North Sea. Remote sensing, 15(20), 4918.

How to cite: Hermans, T., Thibaut, R., Praet, N., and Urban, P.: Machine Learning approaches to predict turbidity from multibeam echosounder data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14741, https://doi.org/10.5194/egusphere-egu24-14741, 2024.

EGU24-14791 | ECS | Posters on site | GI3.3

Gas migration beneath Laacher See: acoustic imaging of shallow CO₂ in the sediment and water column 

Stijn Albers, Thomas Vandorpe, Corentin Caudron, Bernd Schmidt, Joachim Ritter, Klaus Reicherter, and Marc De Batist

The East Eifel Volcanic Field in the west of Germany has received increased scientific attention in recent years due to new findings on ongoing deep magma-related seismicity and regional uplift. Related CO2-degassing phenomena in the region have also been investigated, more specifically in and around the Laacher See volcanic lake, formed by a series of eruptions ca. 13 ka BP. Present-day degassing activity in the Laacher See caldera is most notably evidenced by several gas seeps (i.e. mofettes) in the lake and its surrounding shore, emitting CO2 of magmatic origin. During two surveys in 2019 and 2021, several geophysical techniques were used to image and monitor this CO2 seepage, both in the water column and in the sedimentary infill of the lake. A multibeam echosounder was used to locate gas flares in the water column, visible by their high backscatter intensity, as well as the bathymetric expression of gas escape features on the lake floor. Additionally, high-resolution seismic reflection profiles were acquired with different acoustic sources at different frequencies. These profiles were used to identify accumulated gas in the subsurface, evidenced by enhanced reflections and acoustic blanking.

Our results show that accumulated gas is present at different depths in the lake subsurface, from ca. 2 m to more than 25 m below the lake floor, making it possible to map out areas with high concentrations of free gas at different levels. Locations of subsurface gas accumulations often coincide with areas that have a high concentration of gas flares in the water column. Furthermore, depressions resulting from gas escape (i.e. pockmarks) can be identified on the lake floor bathymetry, linking the upward migration of CO2 gas in the subsurface to the seepage in the water column. Our data confirm that gas is actively migrating through the sedimentary infill and water column of Laacher See and illustrate the need for monitoring these gas migration processes, which can ultimately contribute to a better volcanic hazard assessment in the Eifel region.

How to cite: Albers, S., Vandorpe, T., Caudron, C., Schmidt, B., Ritter, J., Reicherter, K., and De Batist, M.: Gas migration beneath Laacher See: acoustic imaging of shallow CO₂ in the sediment and water column, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14791, https://doi.org/10.5194/egusphere-egu24-14791, 2024.

Commencing with the launch of the lunar orbiter Danuri in 2022, South Korea sets forth an ambitious space exploration roadmap. This roadmap includes plans for a lunar lander in 2032, followed by Mars exploration missions in 2035 and 2045, utilizing an orbiters and a lander, respectively. Moreover, South Korea aims to actively contribute to the United States' Commercial Lunar Payload Services by developing scientific payloads for lunar landing missions.

To harness the wealth of scientific mission data from diverse space explorations and scientific missions, we have developed the KARI Planetary Data System. This system is designed not only to store and disclose scientific data from the lunar orbiter Danuri, currently in its early stage, but also to pave the way for systematic advancements in the future. While acknowledging the system's early development stage, we believe it marks the systematic evolution for enhancing the outcomes of diverse space exploration and scientific endeavors.

This presentation outlines the functionalities and structure of the KARI Planetary Data System, emphasizing the role in its facilitating the open access to Korea's space exploration mission data. We also discuss the system's current features, potential areas for improvement, and future plans.  We embark on this systematic development, laying the foundation for a more profound understanding of our universe through the dissemination of space exploration data.

How to cite: Kim, J. H.: The scientific data release of Korean space exploration missions for public users, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14858, https://doi.org/10.5194/egusphere-egu24-14858, 2024.

EGU24-15822 | ECS | Posters on site | GI3.3

Automatic detection of seaweed and mussels in the water column using Python scripts 

Samira Lashkari, Ine Moulaert, and Thomas Vandorpe

Aquaculture installations become more abundant in large parts of the oceans, with the tendency to promote dual usage of marine space, combining windmill farms and aquaculture installations. In the Horizon Europe funded ULTFARMS project, research into acoustic detection of seaweed and mussel/oyster aquaculture using multibeam echosounders is conducted. Through the acquisition of multibeam water column data and conversion into point cloud data (containing x, y, z, intensity and beam number), automatic detection of relevant cultures is attempted. The conversion of the raw multibeam data into point cloud data is performed using commercial software packages (Qimera and AutoClean), but the open-source software “Ping” (https://github.com/themachinethatgoesping) is a promising candidate for future applications.

To obtain automatic detection and volume calculation, several steps are conducted using tailor-made Python scripts. First, the point cloud data are filtered based on their intensity values, discarding low-intensity scatterers and retaining aquaculture installations and (unfortunately) some noise. Second, noise and outliers are removed using statistical outlier removal. Both standard deviation of the point cloud data and outlier detection, deleting points with few neighboring points, is used to retain the dense point cloud areas. Thirdly, clustering of the data is introduced based on the intensity values or the proximity of points using unsupervised machine learning methods including K-means clustering (grouping points into predefined clusters based on their proximity to cluster centers), Gaussian Mixture Model (assigning points to clusters by modeling data as a mixture of probability distributions) or Hdbscan (automatically identifying clusters based on the  varying shapes and densities in a dataset). The result is clusters of seaweed or individual volumes of mussel aquaculture installations. Finally, for each cluster, the volume is calculated using weighted voxelization; each voxel is assigned a weight based on the number of points in the voxel. Voxels with a large weight are considered to be entirely consisting of aquaculture species, while those with a low weight are only partly filled and thus only partly considered in the total volume. In some instances, interpolation of datapoints between beam numbers is needed to obtain a sufficient resolution. This depends on the beam spacing and hence the ping frequency and vessel speed.

The scripts are still under development and improvements are still being implemented. Undoubtedly, being able to automatically detect volumes of clusters in aquaculture installations will prove to be a huge cost-reducing step in future aquaculture installations.

How to cite: Lashkari, S., Moulaert, I., and Vandorpe, T.: Automatic detection of seaweed and mussels in the water column using Python scripts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15822, https://doi.org/10.5194/egusphere-egu24-15822, 2024.

EGU24-15847 | Posters on site | GI3.3

Removing spacecraft-generated disturbances from the BepiColombo magnetic field data  

Dragos Constantinescu, Uli Auster, Daniel Heiner, and Ingo Richter

In order to be useful for scientific analysis, the raw magnetic field 
data delivered by the BepiColombo Planetary Magnetometer must first be 
cleaned from stray magnetic fields originating from the spacecraft 
itself. This is especially important during the cruise phase, when the 
magnetic field instrument is still in the stowed position, close to 
various artificial magnetic field sources. The method we employ to 
remove these disturbances is a further development of the Maximum 
Variance Gradiometer technique already in use for cleaning the magnetic 
field data measured by the GeoKompsat-2A geostationary satellite. The 
main improvement over the above mentioned technique is the use of an 
intermediate non-orthogonal reference system which allows for decoupling 
of multiple disturbances. Here we describe the method and present the 
results of its application to the last Mercury flyby.

How to cite: Constantinescu, D., Auster, U., Heiner, D., and Richter, I.: Removing spacecraft-generated disturbances from the BepiColombo magnetic field data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15847, https://doi.org/10.5194/egusphere-egu24-15847, 2024.

EGU24-16222 | ECS | Posters on site | GI3.3

Comparison of noise levels of different magnetometer types and space environments 

Gerlinde Timmermann, Adrian Pöppelwerth, Ingo Richter, Hans-Ulrich Auster, and Ferdinand Plaschke

The plasma environment around Earth is divided into several distinct regions with vastly different characteristics of the magnetic field. For example, inside the magnetosphere the magnetic field can reach tens of thousands of nanotesla. In the magnetosheath between Earth’s magnetosphere and the bow shock, the magnetic field is lower, but significantly more turbulent. In the solar wind outside Earth’s magnetic influence, magnetic fields are low and less fluctuating. Magnetic fields in space have typically been measured with fluxgate magnetometers on spacecraft. In recent years, various magnetometer types have been discussed and/or flown, i.e. optically pumped magnetometers or anisotropic magnetoresistive magnetometers. We discuss and compare noise level performances of diverse magnetometer types and contrast them with the requirements needed to accurately observe the magnetic field and distinct plasma phenomena therein in particular regions of space for scientific research.

How to cite: Timmermann, G., Pöppelwerth, A., Richter, I., Auster, H.-U., and Plaschke, F.: Comparison of noise levels of different magnetometer types and space environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16222, https://doi.org/10.5194/egusphere-egu24-16222, 2024.

EGU24-19013 | Orals | GI3.3

Tracking climate-driven changes of water masses and fluxes in polar regions using acoustics.  

Yoann Ladroit, Sarah Seabrook, Elisabeth Weidner, and Scott Loranger

Climate warming increases glacial melt in polar environments, altering the pressure on extensive networks of nutrient-rich fluids and climate-changing gases below the surface and connecting from land to sea.

The increased transport of these fluids and gases to the marine environment has been observed in polar regions, but such processes remain difficult to detect and monitor. To that purpose, water-column acoustic measurements have proven extremely effective, allowing the detection, identification and quantification of fine changes in oceanography, stratified turbulence and mixing at large scales.

Here, we highlight recent visualisations of such anomalous acoustic features in polar regions collected on broadband split-beam systems ranging from 12 to 200 kHz. This allowed us to perform fine analysis of water masses and near-seafloor features. By coupling these acoustic with profiles of chemical properties of the water column and multi-disciplinary datasets, we interpret those, including meltwater, subglacial plumes, and seafloor seeps.

These observations show the potential of using water-column acoustics in the context of long-term monitoring changes in those regions, with the potential to capture short and long-term variations in sensitive areas to better understand those rapidly changing environments.

How to cite: Ladroit, Y., Seabrook, S., Weidner, E., and Loranger, S.: Tracking climate-driven changes of water masses and fluxes in polar regions using acoustics. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19013, https://doi.org/10.5194/egusphere-egu24-19013, 2024.

EGU24-19250 | Orals | GI3.3

Themachinethatgoesping: Pythonic(++) processing of MBES and SBES data 

Peter Urban, Nore Praet, Thomas Vandorpe, and Thomas Hermans

A few powerful tools already exist for processing and investigating multibeam echosounder (MBES) data. They fulfill many industrial and scientific needs regarding quick visualization and bathymetric processing. However, none of these tools sufficiently target scientists that need to- develop new or custom MBES processing methods.

Projects focusing on investigating objects in the water column (e.g. gas bubble streams, suspended particulate matter, fish, …) formed the base for a new MEBS processing tool that is currently being developed within the framework of the TURBEAMS project. The aim is a tool that possesses the flexibility to execute custom processing routines, the transparency to understand the specific equations applied to the acoustic raw data, and the power to efficiently apply these customized routines to large amounts of MBES data gathered during scientific surveys.

The result of these specifications evolved into themachinethatgoesping (short: Ping), a new open-source python library (implemented in c++) for processing multi- and singlebeam echosounder data. Ping aims at simplifying the development and application of novel processing methods by providing a performant, pythonic interface to the acoustic raw data, together with commonly needed processing routines. A few examples:

  • Extract configuration and navigation data.
  • Extract quantitative meaningful backscatter data.
  • Implement and test water column calibration routines.
  • Create time series echograms or render water column images.
  • Filter, georeference and grid acoustic samples in 2D and 3D space.

These functions – and the large amount of python data science libraries – form the base to implementing processing methods (or tools) that are shareable as comprehensive python scripts. Ping is still incomplete and e.g. currently limited to processing Kongsberg .all and Simrad EK80 .raw data files. But you can test it and follow the active development here: https://github.com/themachinethatgoesping

How to cite: Urban, P., Praet, N., Vandorpe, T., and Hermans, T.: Themachinethatgoesping: Pythonic(++) processing of MBES and SBES data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19250, https://doi.org/10.5194/egusphere-egu24-19250, 2024.

EGU24-20149 | ECS | Orals | GI3.3

The Tumbleweed Mission: A new paradigm of Martian exploration through swarm-based, wind-driven rovers 

James Kingsnorth, Luka Pikulić, Abhimanyu Shanbhag, Leonardo Bonanno, Mário de Pinto Balsemão, Julian Rothenbuchner, and Onė Mikulskytė

Comprehensive characterisation of Mars requires global surface observations at high resolution. However, current exploration is conducted through large, infrequent, risky, and relatively high-cost space missions that gather highly localised data. For human missions in the upcoming decades, a new paradigm of exploration involving notable reductions in cost, risk, and timeframe is necessary.

The Tumbleweed Mission proposes a novel architecture, with a swarm of 90 spheroidal, autonomous, wind-driven, and solar-powered mobile impactors (rovers). Unfolding mid-air, they land near one of the poles and spread across the Martian surface for approximately 90 sols. Each impactor follows a different route, planned with consideration for the topography, wind conditions and sites of scientific interest. Once the desired spatial distribution is achieved, the rovers are arrested to a stationary phase for an undefined period. Rovers collect scientific data during both mobile and stationary phases. Each 5-meter diameter, 20 kg rover accommodates up to 5 kg of scientific payload.

The mission aims to produce (atmospheric) data over a multitude of spatial and temporal scales, corresponding to existing strategic knowledge gaps as outlined by NASA’s Mars Exploration Program Analysis Group (MEPAG). The mission would be able to characterise the dynamical and thermal state of the lower atmosphere and controlling processes on local to regional scales. Measure variations in the abundance of species such as water vapour, carbon dioxide and methane. As well as improve constraints to computational models and overall understanding of Martian climate and weather. In the stationary phase, Environmental Sensing Suites (ESS) will act as weather stations, providing frequent near-surface atmospheric data from up to 90 surface points of Mars to allow for the observation of changes at hourly, diurnal and seasonal time scales. Additionally, the ionising radiation environment at the surface would be characterised by unprecedented spatio-temporal resolution. The geomorphology and composition of previously inaccessible areas of Mars can now be constrained through imaging and spectroscopy. Also, the large network setup could provide Martian mantle properties through continuous measurements of nutation, precession, tidal deformation, and gravimetry. Identifying the abundance of carbon and other biologically important (CHNOPS) elements near the surface would provide contextual information concerning habitability and possibly, evidence of indigenous life. Surface measurements can be used to map future landing sites to mitigate the risks posed by hazardous terrain and radiation exposure.

The rover swarm will leverage a heterogeneous complement of analytical instruments during the mission and mostly employ legacy instruments. Currently, the integrated set of instrumentation is under investigation through an objective trade-off. A preliminary list includes a multispectral camera, environmental sensing suite, magnetometer, radio beacon, laser retroreflector, and miniaturised spectrometers. The next stage of development involves testing the proposed instrumentation in Mars analogous environments.

By providing large-scale data sets using rover swarms, the Tumbleweed Mission offers the opportunity to make deep space accessible for everyone. The presentation will provide an overview of the mission concept, review the most desirable science applications and their relevance to MEPAG goals, and discuss the instrument recommendations and main limitations.

How to cite: Kingsnorth, J., Pikulić, L., Shanbhag, A., Bonanno, L., de Pinto Balsemão, M., Rothenbuchner, J., and Mikulskytė, O.: The Tumbleweed Mission: A new paradigm of Martian exploration through swarm-based, wind-driven rovers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20149, https://doi.org/10.5194/egusphere-egu24-20149, 2024.

EGU24-1383 | ECS | PICO | CR5.1

Basal debris at an Antarctic ice rise revealed by seismic amplitude-vs-angle analysis.  

Ronan Agnew, Alex Brisbourne, Adam Booth, and Roger Clark

Reconstructing past ice sheets is important for understanding the response of modern ice sheets to changes in climate. The evolution of the Weddell Sea Sector’s grounding line since the last glacial maximum (LGM) to its present position remains ambiguous; previous authors have proposed hypotheses both of monotonic grounding line retreat and of rapid grounding line retreat followed by readvance. However, distinguishing these scenarios with current observations remains difficult. To explore these scenarios, we report seismic measurements of basal properties at KIR, an ice rise in the Weddell Sea Sector, West Antarctica. A three-component seismic survey enabled detection of the compressional (P) wave reflection and the converted (PS) wave reflection (an incident P wave converted to a shear wave at the base-ice reflector) from the base of KIR. Amplitude-vs-angle (AVA) analysis aims to constrain the physical properties (namely density, seismic velocity, by measuring the variation of reflectivity with incidence angle at the reflector. By jointly inverting the AVA responses of the PP wave reflection and the PS reflection, we increase the confidence in the interpretation of the base-ice properties. 

Analysis of PP and PS AVA responses at KIR indicates that the reflection arises from a material with a P wave velocity of 4.03 ± 0.05 km/s, an S wave velocity of 2.16 ± 0.06 km/s and a density of 1.44 ± 0.06 g/cm3; these properties are consistent with a reflection from a layer of entrained basal debris, with 20-30% debris by volume. The observed properties are not indicative of interference at a thin layer, as observed beneath glaciers elsewhere. The absence of deeper subglacial reflections indicates a poorly-defined boundary between this basal debris layer and the underlying subglacial material, which we therefore propose consists of frozen sediments . If this interpretation is correct, the presence of a debris layer overlying basal frozen sediment indicates a potential retreat/readvance scenario for KIR. A possible scenario is a previous episode of flow during which KIR may have been weakly grounded as an ice rumple, followed by grounding on the lee side of the bathymetric high and subsequent freezing of subglacial sediments. However, the origin of such a homogeneous and debris-rich layer remains unclear. The indication of a reflection from a basal debris layer raises questions about whether conventionally interpreted basal reflections can truly be considered as such, and whether these interpretations may mask the true nature of the underlying subglacial material. This ambiguity may be most effectively reconciled by borehole sampling.

How to cite: Agnew, R., Brisbourne, A., Booth, A., and Clark, R.: Basal debris at an Antarctic ice rise revealed by seismic amplitude-vs-angle analysis. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1383, https://doi.org/10.5194/egusphere-egu24-1383, 2024.

EGU24-4532 | ECS | PICO | CR5.1

Conductive textile electrodes for time-efficient ERT surveys performed in coarse-blocky mountain environments 

Mirko Pavoni, Jacopo Boaga, Alexander Bast, Matthias Lichtenegger, and Johannes Buckel

Electrical resistivity tomography (ERT) is one of the most accurate geophysical techniques to distinguish between frozen and unfrozen ground in permafrost areas. Performing the measurements, however, requires considerable logistics and time efforts. This is mainly due to the fact that optimal galvanic contact between the electrodes and the ground surface is necessary to collect reliable ERT datasets. Therefore, the traditional steel-spike electrodes must be steadily coupled between the boulders and wet with salt water on coarse blocky surfaces. To further decrease the contact resistances, sponges soaked in salt water can be inserted between the spike and the surface of rocks. Nevertheless, this traditional coupling system is particularly time-consuming, making it challenging to collect several ERT survey lines in a single workday in mountain environments. Recently developed conductive textile electrodes were applied to facilitate the deployment of ERT arrays in rock glacier environments. Instead of hammering the steel spikes, the conductive textile electrodes can be easily pushed between the boulders and wet with less water (compared to the sponges). Consequently, this new electrode approach decreases the time needed to prepare an ERT array. In this work, we evaluate the performance of the textile electrodes by comparing these with the traditional electrode approach, considering common investigation lines. This comparative test has been carried out in three test sites, which present different lithologies, surface characteristics and using different electrode spacing. The collected datasets were statistically analysed with robust regression analysis and Wilcoxon rank-sum test to examine the accuracy and significant differences between the two electrode systems regarding contact resistances, injected electrical current, measured apparent resistivities, reciprocal error, and inverted resistivity values. The obtained results demonstrate that conductive textile electrodes are suitable to collect reliable ERT datasets and, consequently, applying this approach in future ERT measurements performed in high mountain environments with coarse blocky surfaces (e.g. rockfall deposits, blocky slopes, or rock glaciers) would allow to acquire more survey lines (e.g. realisation of pseudo-3D geometries) extending the characterisation of the subsurface.

How to cite: Pavoni, M., Boaga, J., Bast, A., Lichtenegger, M., and Buckel, J.: Conductive textile electrodes for time-efficient ERT surveys performed in coarse-blocky mountain environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4532, https://doi.org/10.5194/egusphere-egu24-4532, 2024.

EGU24-5435 | PICO | CR5.1

Demonstrating a large UAV for Antarctic environmental science 

Tom Jordan and Carl Robinson

Airborne survey is one of the most important observational techniques in environmental science. This is especially true in polar settings where access is challenging and observational requirements, such as ice sounding radar, in situ study of turbulent atmospheric processes, cloud cover, or requirements for high resolution potential field data, limit use of satellite data. Although critical, airborne survey using traditional platforms, such as the versatile twin otter aircraft operated by the British Antarctic Survey (BAS), come with a relatively high logistical, financial, and environmental (CO2) footprint. Larger UAV’s offer an alternative, but as yet un-realised, lower impact platform to deliver the same, if not more scientific data.

Through the Innovate UK SWARM project BAS is collaborating with Windracers to trial their large (10 m wing span) Ultra UAV as a platform for environmental science. Making use of the large (700 L/max 100 kg), easily accessible payload bay and a series of interchangeable payload floors this trial will be carried out in February/March 2023. The science payloads will include: Atmospheric (turbulence probe), environmental (hyperspectral and visual cameras), cryosphere (600-900 MHz accumulation radar), and potential field geophysics (gravity/magnetic sensors). The missions, between 10 and 330 km long, will be flown beyond visual line of sight (BVLOS) of the operator using the Distributed Avionics autopilot, including take-off and landing, which will be overseen by an in-field safety pilot.

Here we present the first results of this trial, including our experience integrating BVLOS UAV operations with traditional aircraft in an Antarctic context and initial results and lessons learned from the four trailed instrument suites. Our demonstration will be an important milestone in the transition to widespread use of larger UAVs for environmental science. We will discuss how the reduced environmental and logistical impact can open up new opportunities in Antarctic and beyond.

How to cite: Jordan, T. and Robinson, C.: Demonstrating a large UAV for Antarctic environmental science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5435, https://doi.org/10.5194/egusphere-egu24-5435, 2024.

EGU24-5751 | ECS | PICO | CR5.1

Firn Density Distribution and Annual Snow Water Equivalent Estimates from Ground Penetrating Radar 

Akash Patil, Christoph Mayer, and Matthias Braun

Abstract: Accurate estimation of glacier volume-to-mass conversion relies on a thorough understanding of firn density, both in-depth and over time. Ground-penetrating radar (GPR) serves as a suitable geophysical tool to trace internal reflection horizons (IRHs) and estimate the physical properties of different layers. Our goal is to characterize the IRHs as annual layers and ascertain the spatial firn density-depth profile in the accumulation zone of the Aletsch glacier.

The process involves identifying IRHs from radargrams and iteratively selecting the annual layers by excluding unreasonable layer structures. For an accurate estimation of firn density distribution, it is necessary to derive the velocity-depth profile of electromagnetic waves within the firn zone. The common mid-point (CMP) method was applied to track the velocity distribution within the firn body. Additionally, a method was introduced to estimate the velocity-depth profile for longer GPR profiles by backtracking the calculated velocity from the CMP gather.

To validate IRHs as annual firn layers, we utilized annual accumulation measurements at a nearby stake for Snow Water Equivalent (SWE) estimation. The resulting firn density-depth profile was compared to different firn densification models, considering regional meteorological information. This approach enables us to determine a reliable density-depth function for bulk SWE computations. The study also addresses uncertainties associated with selecting IRHs as annual layers and enhances the application of local volume-to-mass estimates.

How to cite: Patil, A., Mayer, C., and Braun, M.: Firn Density Distribution and Annual Snow Water Equivalent Estimates from Ground Penetrating Radar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5751, https://doi.org/10.5194/egusphere-egu24-5751, 2024.

EGU24-7654 | ECS | PICO | CR5.1

Coupling Solid Earth and ice temperature models to estimate geothermal heat flow 

Judith Freienstein, Wolfgang Szwillus, Marion Leduc-Leballeur, Giovanni Macelloni, and Joerg Ebbing

Geothermal heat flow (GHF) is a key element of Solid Earth-cryosphere interactions. However, polar regions as Antarctica are only sparsely covered with heat flow determinations from boreholes, so one must rely on interpolation or regression models of GHF (e.g. machine learning) from other sources to derive a regional map. Interpolation/regression of GHF in this manner depends strongly on the available sparse boreholes, which can distort the resulting regional map.

Additional information can be gained from the SMOS (Soil Moisture and Ocean Salinity) satellite by inferring ice temperature profiles with a Bayesian inversion from remote sensing microwave radiometer data. This retrieval uses geothermal heat flow as a free parameter so that it provides a posterior distribution of the GHF needed to explain the ice temperature profiles.

We aim to reconcile geophysical geothermal heat flow models with the ice temperature profiles and improve the estimates of GHF with this coupling.

We use stationary thermal modelling where we force the ice temperature and lithospheric temperature model to converge at the base of the ice. Using stochastic inversion, we estimate the thermal parameters in the lithosphere. The posterior distribution of the retrieval as constraint for the GHF is included as prior distribution to the inversion to the stationary thermal modelling so that the GHF with the highest likelihood can be estimated.

With our approach, we can evaluate a GHF distribution that both explains the ice temperature and lithospheric temperature models and covers large parts of Antarctica.

How to cite: Freienstein, J., Szwillus, W., Leduc-Leballeur, M., Macelloni, G., and Ebbing, J.: Coupling Solid Earth and ice temperature models to estimate geothermal heat flow, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7654, https://doi.org/10.5194/egusphere-egu24-7654, 2024.

EGU24-8245 | ECS | PICO | CR5.1

Sensitivity Study for Seismic Waves Guided in an Ice Pack: Influence of the Frequency Content and Snow Layer Thickness Covering the Ice 

Hooshmand Zandi, Ludovic Moreau, Ludovic Métivier, and Romain Brossier

Studying Arctic sea ice is essential as it plays an important role in climate regulation, influencing weather
patterns, as well as impacting the local ecosystems and living conditions of people. Among different
methods for collecting data and studying sea ice, seismology has proved to be an efficient way to extract
the ice properties, from which the mechanical behavior of sea ice can be explored. Seismic data recorded on
sea ice, using 3-component geophones, are used as a starting point to derive useful information regarding
the ice. To devise an efficient inversion method for deriving ice properties, an effective tool would be
necessary to generate synthetic data in a way that encompasses the physics of sea ice. While there are
approximate solutions to wave propagation problem in a floating ice layer based on plate theory, which is
based on the assumptions of homogeneity of the ice layer and valid at low values of frequency×wavelength,
numerical counterparts such as wavenumber integration method and finite element method have been
also used to to create synthetic waveforms. The numerical methods have shown the limitations of these
approximate solutions in modeling wave propagation; nonetheless, the effects of these limitations on the
estimations of the location of icequakes and thickness of ice need to be investigated.

In this study, these limitations are explored. To do this, two possible scenarios that can happen in
practice are taken into account: (1) when there is high-frequency content in the source generating the
seismic data, and (2) when the physical model includes a snow layer overlying the ice layer. First, we
will show the limitations of the approximate solutions for these two cases by comparing the waveforms,
derived from these approximate solutions, with those of a numerical method at a given distance from
the source. The numerical used here is spectral element method. Then, the effects of these limitations
on the estimations of icequake location and ice thickness are explored in an inversion process, in which
synthetic data are created using the approximate solutions. Results indicate that when there are high-
frequency content in the data and a snow layer on top of the ice, the use of the approximate solutions
to generate synthetic data introduces bias in the estimation of ice thickness and source-receiver distance
in the inversion process. This bias is in the form of underestimations, smaller ice thicknesses and smaller
source-receiver distances. Furthermore, to tackle the biases associated with the inversion method based on
the approximate solutions, a novel strategy is adopted, where a database of simulations using the proposed
numerical method is built for various models of ice and snow. Here the inversion comprises of searching
in the database to find the best ice thickness and source-receiver distance for each icequake. In addition,
the database-based inversion reduces the computational cost. Thanks to this inversion strategy, and
using real data recorded on sea ice, the ice thicknesses along different source-receiver paths are estimated
efficiently, from which a 3D map of ice thickness is constructed.

How to cite: Zandi, H., Moreau, L., Métivier, L., and Brossier, R.: Sensitivity Study for Seismic Waves Guided in an Ice Pack: Influence of the Frequency Content and Snow Layer Thickness Covering the Ice, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8245, https://doi.org/10.5194/egusphere-egu24-8245, 2024.

EGU24-9857 | ECS | PICO | CR5.1

Broadband Spectral Induced Polarization in Permafrost Peatlands of Northern Sweden  

Madhuri Sugand and Andreas Hördt

Permafrost peatlands, located in the Arctic and high mountain regions, are typically known to be ice-rich. This is primarily linked to significant water content and often oversaturation, a characteristic property of peat soil. The current understanding of the effects of human-induced climate warming suggests that these regions are approaching a climatic tipping point with substantial permafrost thaw expected in the coming decades. Ice content is an important parameter for modelling permafrost evolution and at present limited studies exist that determine its in-situ spatial distribution in such areas.

The geophysical method known as high-frequency induced polarisation (HFIP) is advantageous for cryohydrological research in these environments. This method can capture the frequency-dependent polarisation of ice (also termed dielectric relaxation peak), which occurs within the range of 100 Hz to 100 kHz and is expressed by complex resistivity. Therefore, by analysing the spectral behaviour of this complex resistivity within the target frequency range the distribution and quantity of ice can be estimated.

The results from the latest field campaign conducted at Storflaket mire and Stordalen mire in Abisko, Sweden, are presented. Two-dimensional HFIP profiles were measured to resolve the near-surface unfrozen layer (no-ice) and the underlying frozen layer (ice-bearing). The measurements were performed in late summer when the depth of the unfrozen layer was at its maximum. Field data are inverted as independent frequencies to obtain the spectral variation of complex resistivity. No-ice and ice-bearing regions are classified by the presence of the relaxation peak. Subsequently, a two-component mixture model, with one component as ice and the second as the surrounding matrix, is applied to determine ice content distribution. Boundary constraints and starting parameters are chosen using the spectral analysis of the inverted complex resistivity. The model accuracy is evaluated using unfrozen layer probing and a permafrost core extracted along the HFIP profile. The HFIP-derived ice content distribution is consistent with unfrozen layer probing, i.e., the classification of no-ice and ice-bearing regions is successful. The model tends to underestimate ice content percentages compared to permafrost core laboratory measurements. This discrepancy can be explained since laboratory measurements are based on gravimetric water content and assumes all pore-water is frozen. However, it is known that residual pore-water is present in these soils even below 0°C. Additionally, it is observed that the model performs well when the ice content percentage is 10% or greater and its applicability might be limited in scenarios where the ice content is less than 10%.

The latest results are discussed in comparison with previous findings from Heliport, a permafrost mire also located in Abisko. In the Heliport study, HFIP successfully resolved the complex resistivity and ice content distribution on a larger scale. Building on the field knowledge gained at Heliport, this study incorporates improvements in electrode configuration setup, data acquisition speed, and minimising cable-earth coupling effects. The findings contribute to the understanding of the induced polarisation of permafrost peatlands, which is an underexplored area from a geophysical perspective.

How to cite: Sugand, M. and Hördt, A.: Broadband Spectral Induced Polarization in Permafrost Peatlands of Northern Sweden , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9857, https://doi.org/10.5194/egusphere-egu24-9857, 2024.

EGU24-10814 | ECS | PICO | CR5.1

Analysis of H/V spectral ratio curves from passive seismic data acquired on glaciers worldwide 

Julien Govoorts, Koen Van Noten, Corentin Caudron, Bergur Einarsson, Thomas Lecocq, Sylvain Nowé, Finnur Pálsson, Jonas Pätzel, and Harry Zekollari

Estimations of bedrock topography below glaciers and ice thickness are vital for quantifying freshwater availability for surrounding populations and understanding the contribution of melting glaciers to sea-level rise in the context of global warming. While active seismology is commonly used for ice thickness estimation, the utilization of passive methods remains relatively rare. Passive seismology solutions offer cost-effectiveness, non-invasiveness and continuous monitoring capabilities that present valuable benefits in glaciological research.

Over the past two decades, numerous seismic stations have been deployed on glaciers worldwide for various purposes. Through passive seismology approaches, these seismic stations could show their potential as new sources of ice thickness measurements and feed the related database. For this purpose, we analyzed data of 3-components seismic sensors from different deployments as well as data from open access databases, such as IRIS, employing the Horizontal-to-Vertical Spectral Ratio (HVSR) technique. HVSR has been predominantly used in microzonation studies to determine site effects and the thickness of sediments in sedimentary basins.  Even though the use of this technique in glacial seismology is quite new, HVSR has been already utilized to estimate in-situ ice thickness, to retrieve the basal properties or to detect cavities under the ice.

Our primary objective is to demonstrate the potential of the HVSR technique to retrieve in-situ ice thickness on different glaciers. Subsequently, we will compare the HVSR results with different data sources including models, ground-penetrating radar or active seismology. By performing this comparison we evaluate the limitations of the HVSR method in an icy environment. We investigate these limitations by studying the effect of other natural agents such as wind on the H/V amplitude and fundamental frequency retrieved from the HVSR curves. Having a global understanding of these influences will eventually help deciphering variations in continuous H/V monitoring.

How to cite: Govoorts, J., Van Noten, K., Caudron, C., Einarsson, B., Lecocq, T., Nowé, S., Pálsson, F., Pätzel, J., and Zekollari, H.: Analysis of H/V spectral ratio curves from passive seismic data acquired on glaciers worldwide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10814, https://doi.org/10.5194/egusphere-egu24-10814, 2024.

EGU24-11300 | PICO | CR5.1

Icequakes beneath Thwaites Glacier eastern shear margin  

Emma C. Smith, Ronan Agnew, Adam D. Booth, Poul Christoffersen, Eliza J. Dawson, Lucia Gonzalez, Marianne Karplus, Daniel F. May, Nori Nakata, Andrew Pretorius, Paul Summers, Slawek Tulaczyk, Stephen Vietch, Jake Walter, and Tun Jan Young

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 of Thwaites Glacier 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.  

In this study, we present an analysis of ~4000 icequakes, recorded over a two-year-period on a broadband seismic array deployed across the eastern shear margin of Thwaites Glacier. The array consisted of seven three-component seismometers, deployed around a central station in a circle, roughly 10 km in diameter.  We use an automated approach to detect and locate “high-frequency” seismic events (10-90 Hz), the majority of which are concentrated in clusters around the ice-bed interface on the slow-moving side of the shear margin, as opposed to within the ice-stream itself. The event waveforms exhibit clear shear-wave splitting, indicative of the presence of an anisotropic ice fabric, likely formed within the shear margin, which is consistent with published radar studies from the field site. Initial analysis of the split shear-waves suggests that they can be used to better constrain the region's ice fabric, and likely used to infer past shear margin location and assess the future stability of this ice rheology.

How to cite: Smith, E. C., Agnew, R., Booth, A. D., Christoffersen, P., Dawson, E. J., Gonzalez, L., Karplus, M., May, D. F., Nakata, N., Pretorius, A., Summers, P., Tulaczyk, S., Vietch, S., Walter, J., and Young, T. J.: Icequakes beneath Thwaites Glacier eastern shear margin , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11300, https://doi.org/10.5194/egusphere-egu24-11300, 2024.

EGU24-11386 | PICO | CR5.1

Towards a unified description of the count rate – snow water equivalent relationship in cosmic-ray neutron sensing 

Benjamin Fersch, Markéta Součková, Paul Schattan, Nora Krebs, Jannis Weimar, Carsten Jahn, Peter Martin Grosse, and Martin Schrön

The observation of near-ground cosmogenic neutrons enables the monitoring of various water storage variations at the land surface at the field scale including soil moisture and the water content of snow layers. The parabolic neutron-count versus soil moisture function is quite uniform among different locations, and soil types and requires typically a one-time-only in situ reference observation. For the detection of snowpack water equivalent (SWE) variations by cosmic-ray neutron sensing such a uniform approach has so far not been developed. Therefore, the establishment of new cosmic-ray snow monitoring sites requires substantial in situ measurements for obtaining the local relationship of SWE amounts and neutron count rates. Observations suggest that the relationship is quite uniform for grass-vegetated locations which is different to what is found for stony ground.

Within the framework of the research unit Cosmic Sense, we generated extensive in situ measurements of snow water equivalent and cosmogenic neutron count rates at various sites with differing elevations in the German and Austrian Alps. From these data, we investigate commonalities among the site conditions and if the varying patterns of the relationships can be reasonably explained by physical reasons and therefore be modeled with a unified approach.

How to cite: Fersch, B., Součková, M., Schattan, P., Krebs, N., Weimar, J., Jahn, C., Grosse, P. M., and Schrön, M.: Towards a unified description of the count rate – snow water equivalent relationship in cosmic-ray neutron sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11386, https://doi.org/10.5194/egusphere-egu24-11386, 2024.

EGU24-11729 | ECS | PICO | CR5.1

A physically-based fractal model for predicting the electrical conductivity in partially saturated frozen porous media 

Haoliang Luo, Damien Jougnot, Anne Jost, Aida Mendieta, and Luong Duy Thanh

Macro-scale transport properties (e.g., electrical conductivity, effective excess charge density and hydraulic conductivity) can be conceptualized as capillary bundle models, in which the pore structure of porous medium is viewed as a bundle of capillary tubes of varying sizes. This approach can be used to understand and address the relationship between the petrophysical properties and the geometry of soil phases. When the temperature of porous medium decreases below the freezing temperature, the soil physical properties (transport properties) change drastically. This is attributed to the complexity of the heterogeneous formation of ice in the porous medium. Therefore, understanding better pore ice formation from microscale insights is crucial to describe the evolution of electrical conductivity with temperature in frozen porous medium. In this study, we consider that capillary radius and tortuous length follow fractal distributions, and that total conductance at the microscale scale is determined by the Gibbs-Thomson and Young-Laplace effects as well as by the surface complexation model. A new capillary bundle model is then proposed using an upscaling procedure, which considers the effects of both bulk and surface conductions. Based primarily on an electrical resistance apparatus and the NMR method, a series of laboratory experiments are carried out to study the influence of initial water saturation and salinity on electrical conductivity under unfrozen and frozen conditions. Additionally, the rationality and validity of the proposed model were successfully verified with published data in the literature and experimental data of this study. Our new physically-based model for electrical conductivity opens up new possibilities to interpret electrical and electromagnetic monitoring to easily infer changes in key variables such as liquid water content and moisture gradients.

How to cite: Luo, H., Jougnot, D., Jost, A., Mendieta, A., and Thanh, L. D.: A physically-based fractal model for predicting the electrical conductivity in partially saturated frozen porous media, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11729, https://doi.org/10.5194/egusphere-egu24-11729, 2024.

EGU24-12583 | PICO | CR5.1

Locating subglacial cavities and investigating basal conditions on glaciers with ambient seismic noise: toward acquisition optimization. 

Eric Larose, Noelie Bontemps, Antoine Guillemot, and Laurent Baillet

Subglacial cavities may trap a considerable quantity of liquid water, causing devastating outburst floods in densely populated mountain areas. Both active and passive geophysical methods are employed for the glacier-bedrock interface and intra-glacial characterization, including Ground Penetrating Radar (GPR), refraction seismic, borehole measurements, and surface nuclear magnetic resonance (SNMR). 

Ambient seismic noise can be collected by light and dense arrays at a relatively moderate cost, and allows to access some mechanical properties of the glacier, including the detection and localization of ice cavities and, possibly, basal detachment, taking advantage of spectral anomalies in the horizontal-to-vertical-spectral ratio (HVSR) and in the Vertical-to-Horizontal spectral ratio (VHSR). Specifically, a peak in the VHSR indicates a low impedance volume beneath the surface [1,2]. As a simple picture, we can refer to the “bridge” vibrating mode, where the vertical displacement in the middle of the bridge largely dominates other components of the movement.  Antunes et al. [2] furthermore noticed that the VHSR gives information about seismic energy anomalies generated by fluids in reservoirs since the wavefield is polarized mainly in the vertical direction.
In this work, we apply the HVSR and VHSR techniques to locate a subglacial water-filled cavity in the Tête Rousse glacier (Mont Blanc area, French Alps), using 15 days of data collected in may, 2022 [3]. The results also confirm the general basal conditions of the glacier suggested by other methods, locating temperate areas of the glacier where basal detachments are possible.

We evaluate the optimal seismic noise record duration to obtain a reliable and stable mapping of the VHSR over the glacier to properly locate the main cavity (or secondary cavities). In our case, results suggest that 6 days of record are enough to detect and locate a cavity

 

[1] Saenger, E-H. et al: A passive seismic survey over a gas field: Analysis of low-frequency anomalies, Geophysics, 74 (2), O29–O40 (2009).

[2] Antunes V. et al: Insights into the dynamics of the Nirano Mud Volcano through seismic characterization of drumbeat signals and V/H analysis. Journal of Volcanology and Geothermal Research, 431 (2022).

[3] A. Guillemot, N. Bontemps, E. Larose, D. Teodor, S. Faller, L. Baillet, S. Garambois, E. Thibert, O. Gagliardini, C. Vincent: Investigating Subglacial Water-filled Cavities by Spectral Analysis of Ambient Seismic Noise : Results on the Polythermal Tête-Rousse Glacier (Mont Blanc, France), Geophys. Res. Lett. accepted (2024). DOI:10.1029/2023GL105038

How to cite: Larose, E., Bontemps, N., Guillemot, A., and Baillet, L.: Locating subglacial cavities and investigating basal conditions on glaciers with ambient seismic noise: toward acquisition optimization., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12583, https://doi.org/10.5194/egusphere-egu24-12583, 2024.

The Totten Glacier is a fast moving glacier that serves as a major outlet of the East Antarctic Ice Sheet. During December 2018 and January 2019, we deployed a 12 station broadband seismic array near the grounding zone of the Totten Glacier. We observed a significant number ( > 10,000) of repeating basal stick-slip icequakes across the region. Much of this seismic activity was dominated by higher frequency events (20-75 Hz) similar in size and temporal character (“bursty”) to those found in previous studies, such as those on the Rutford Ice Stream and Greenland Ice Sheet. Additionally, we observe a large number of repeating events dominated by lower frequencies (< 10 Hz) that have larger magnitudes and longer inter-event time than the high-frequency seismic activity. We will provide an overview into both the temporal and spatial variability of this seismic activity and discuss implications for fast flow in the region.

How to cite: Winberry, P.: Repeating Glacier Seismicity Near the Totten Glacier Grounding Zone., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12865, https://doi.org/10.5194/egusphere-egu24-12865, 2024.

EGU24-13124 | ECS | PICO | CR5.1

Exploring englacial hydrology with surface nuclear magnetic resonance 

Laura Gabriel, Marian Hertrich, Raphael Moser, Christophe Ogier, Hansruedi Maurer, and Daniel Farinotti

The amount and distribution of liquid water inside a glacier are relevant for its dynamics, related natural hazards or for sediment transport. Experimentally investigating the glacier's hydrology is challenging because of restricted accessibility, investigation depth, material properties, and environmental factors. In addition, the subglacial drainage network is highly dynamic and undergoes diurnal and seasonal changes.

This contribution investigates the application of surface nuclear magnetic resonance (SNMR) to characterize the liquid water distribution within Swiss Alpine glaciers. Analogous to magnetic resonance imaging (MRI) in medicine, SNMR utilizes an oscillating magnetic field to excite nuclear spins of hydrogen atoms within water molecules. The subsequent spin relaxation is then analyzed, providing insights into the probed material. In simpler terms, this process allows us to directly detect liquid water in ice and gain information on its spatial distribution.

We conducted a first SNMR field survey on Rhonegletscher in the summer of 2023. During this survey, we tested various measurement configurations, including separate-loop measurements and the application of noise-compensation loops. The latter proved crucial for subsequent data processing. After carefully optimizing the processing scheme, we extracted SNMR signals in several recordings despite the poor signal-to-noise ratio. The results were compared to 1D forward-modelled data, suggesting that the average water content in the survey area lay between 0.7 and 1.2 %. In addition, we could show that a homogenous water distribution over the entire ice column cannot explain the observed data and that we need to consider more complex subsurface models including at least one additional water layer. Specifically, our ongoing research aims to identify which configurations of the subglacial water distribution (e.g., homogenous water distribution vs layered water-ice structure resulting from an englacial water channel) are distinguishable experimentally. Moreover, the study seeks to optimize measurement design and data processing methodologies to acquire information more efficiently, and effectively handle the expected low signal-to-noise ratios.

In future field campaigns, we intend to deploy SNMR for selected glaciological case studies within the Swiss Alps. A primary focus will be on efficiently detecting water pockets that may pose a potential risk of downstream flooding upon rupture. Similarly, we want to investigate the extent to which we can distinguish cold from temperate ice.

How to cite: Gabriel, L., Hertrich, M., Moser, R., Ogier, C., Maurer, H., and Farinotti, D.: Exploring englacial hydrology with surface nuclear magnetic resonance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13124, https://doi.org/10.5194/egusphere-egu24-13124, 2024.

EGU24-13663 | ECS | PICO | CR5.1

 Assessing the rate of ice fracture using co-located geophysical surveys on the Brunt Ice Shelf, Antarctica 

Emma Pearce, Oliver Marsh, Alex Brisbourne, and Thomas Hudson

The rate of fracture-induced ice instability is an important factor contributing to uncertainties in sea level projections used for global flood mitigation planning. While the occurrence of ice fracturing at critical stress thresholds is well-documented, the detailed mechanisms controlling fracture timing, rate, and orientation are not fully understood. This gap is particularly evident in differences in fracture behaviour across varying ice types, such as meteoric ice and ice mélange. Observations on the Brunt Ice Shelf reveal a unique behaviour, where rifts deviate from the pathway predicted by the principal stresses to avoid thick blocks of meteoric ice. Their growth rate is significantly reduced when required to cross through these blocks. This stands in contrast to observations on other ice shelves, such as Larsen C, where rift propagation is slower in marine ice bands.

Here we use co-located geophysical methods, seismic and ground-penetrating radar (GPR), to assess the fracture pattern and dynamics and the relationship to ice properties at the leading edge of two active rifts, Halloween Crack and Chasm 2, on the Brunt Ice Shelf.

By determining the depth of seismic events using P to Rayleigh wave amplitude ratios, we estimate a theoretical maximum dry crevasse depth—the depth at which fracturing can occur without the presence of englacial water. Additionally, GPR data are used to precisely locate rift terminations and identify refrozen layers associated with seawater intrusion into the firn layer. Combining these data, we provide new insight into the mechanisms controlling fracture propagation within the Brunt Ice shelf. The synthesis of observations from Chasm 2 and Halloween Crack contributes to a comprehensive understanding of fracture mechanics, enhancing our knowledge of regional-scale ice dynamics.

How to cite: Pearce, E., Marsh, O., Brisbourne, A., and Hudson, T.:  Assessing the rate of ice fracture using co-located geophysical surveys on the Brunt Ice Shelf, Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13663, https://doi.org/10.5194/egusphere-egu24-13663, 2024.

EGU24-13683 | ECS | PICO | CR5.1

Testing four Sentinel (1 and 2) and MODIS Fractional Snow Cover products for the evaluation of five Alpine Cosmic Ray Neutron Sensing sites 

Nora Krebs, Paul Schattan, Valentina Premier, Abraham Mejia-Aguilar, and Martin Rutzinger

Above-ground cosmic ray neutron sensing (CRNS) is an emerging technique for the investigation of dynamics in soil moisture, snow water equivalent (SWE), and vegetation at a spatial scale of several hectares. The measurement principle is based on the moderation of natural secondary cosmogenic neutrons by hydrogen atoms. On the earth surface hydrogen atoms are mainly bound in water molecules. However, at complex research sites the signal distinction between various water sources remains challenging. Especially in alpine terrain and at elevated topography, hydrological features are linked in an intricate patchwork, hampering signal discrimination. Satellite observations offer valuable complementary surface information and are commonly provided at a spatial resolution that meets the integrated footprint area of the CRNS detector. In this study we investigate if the interpretation of the CRNS signal can be enhanced by the use of remote sensing products. We compare three readily available fractional snow cover (FSC) products based on Sentinel (1 and 2) and MODIS and one reference FSC Sentinel-2 scene-based machine learning product at the approximate footprint resolution of CRNS, comprising a circular area of 250 m radius. The performance of all four products is assessed at five CRNS sites in the Austrian and Italian Alps that represent a variety of environmental properties, ranging from flat to steep topography, from low to high elevation and from sparse to abundant vegetation cover. At three sites, the presence and absence of snow can be validated by local snow height measurements. The analysis shows that remote sensing snow cover information can be extracted on around 80% of the analyzed days, demonstrating the use of FSC products for the estimation of snow cover duration and timing. Comparing the four products shows overall agreements and allows to deduce product-specific thresholds for the distinction of snow-covered and snow-free situations. Further, pairing remote FSC observations with neutron count measurements provides a first indication on the complexity of local hydrogen pool dynamics and consequent requirements on the calibration routine for ambient water monitoring with CRNS. We conclude that satellite-based FSC products can be used to fortify the choice of CRNS observation location and period prior to the detector installation and for a robust and viable first-order assessment of expected CRNS site conditions. Remote sensing FSC products and CRNS measurements hold complementary data that can mutually benefit snow observations and should be explored further in the future.

How to cite: Krebs, N., Schattan, P., Premier, V., Mejia-Aguilar, A., and Rutzinger, M.: Testing four Sentinel (1 and 2) and MODIS Fractional Snow Cover products for the evaluation of five Alpine Cosmic Ray Neutron Sensing sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13683, https://doi.org/10.5194/egusphere-egu24-13683, 2024.

EGU24-14420 | PICO | CR5.1

Using seismic and gravity data to constrain subglacial seafloor stratigraphy in the vicinity of the Kamb Ice Stream grounding line, Ross Ice Shelf, Antarctica 

Andrew Gorman, Gary Wilson, Huw Horgan, Gavin Dunbar, Caitlin Hall, Jenny Black, Bob Dagg, Matthew Tankersley, and Laurine van Haastrecht

The sedimentary units beneath the Ross Ice Shelf in the vicinity of the Kamb Ice Stream grounding line on the Siple Coast of the eastern Ross Ice Shelf play an important role in evaluating past advances and retreats of grounded ice in West Antarctica through the Quaternary. This region is an ongoing focus for drilling efforts that involve melting through the ice shelf and recovering sediments from beneath the seafloor. Seismic (and to a lesser extent gravity) methods have played a critical role in establishing a stratigraphic framework for these sediment sampling endeavours. Approximately 73 km of seismic data have been collected in this region during three seasons since early 2015, complemented by finely sampled gravity transects and a coarser regional gravity grid. Data acquisition provides localised coverage of the sub-ice-shelf ocean and sediments in a region where ROSETTA-Ice airborne-gravity data identified a gravity low. Seismic acquisition parameters have varied from survey to survey, but all involve explosive charges frozen into a hot-water-drilled holes that are recorded by conventional geophones buried in the firn. Such an acquisition configuration provides imaging of the ice shelf and underlying geological units. Processed seismic data show a mostly flat layered seafloor lying beneath the ocean cavity with at least 200 m of sub-horizontally layered sedimentary strata containing several mappable unconformities that are identified as distinct reflective horizons in the seismic data as well as reflection terminations and pinchouts in overlying and underlying units. These unconformities could correspond to past glacial erosion episodes as the position of the grounding line in this region has migrated landward and oceanward. Gravity modelling suggests that the thickness of the sedimentary basins in the region are variable beyond what we see in the shallow (few hundred metre) penetration of the seafloor.

How to cite: Gorman, A., Wilson, G., Horgan, H., Dunbar, G., Hall, C., Black, J., Dagg, B., Tankersley, M., and van Haastrecht, L.: Using seismic and gravity data to constrain subglacial seafloor stratigraphy in the vicinity of the Kamb Ice Stream grounding line, Ross Ice Shelf, Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14420, https://doi.org/10.5194/egusphere-egu24-14420, 2024.

EGU24-14548 | ECS | PICO | CR5.1

Applications of geophysical techniques for the analysis of the internal structure and understanding of the hydrological system of the Kinzl Covered Glacier, Cordillera Blanca, Peru  

Velnia Chacca Luna, Widmark Harrinson Jara Infantes, Manuel Antonio Cosi Fajardo, Milagros Lizbeth Aquino Morales, Leila Mamani Yampi, Sara Cachay, and Juan Carlos Torres Lázaro

The Cordillera Blanca is currently home to 384 covered glaciers, which constitutes 46.5 % of the total of 825 covered glaciers registered in the 20 glacier ranges of Peru, according to data provided by the Glacier Inventory 2023 (INAIGEM, 2023). Therefore, in the framework of climate fluctuations driven by global warming, covered glaciers stand out as crucial elements, as their level of thawing is much slower in response to climate variability and in contrast to their debris- free glacier counterparts. This characteristic consolidates them as increasingly essential and valuable water resources.

The objective of the study is to determine the physical characteristics of the Kinzl Covered Glacier, located in the Cordillera Blanca, by applying the geophysical methods of ground penetrating radar (GPR) and vertical electrical sounding (VES). The methodology employed includes georadar profiling and point soundings to understand the composition and distribution of materials and the physical properties of the glacier. From the detailed analysis of electrical soundings and georadar profiles, a correlation of both methods has been achieved through the resistivities obtained and established for similar environments, with phases of reflected signals coming from the contours of the interfaces identified in the radargrams analysed and interpreted. This correlation has provided us with a comprehensive understanding of the internal characteristics of the Kinzl Covered Glacier, where three horizons have been identified: The first horizon composed of variable surface debris, ranging from 2 to 9 metres thick, with resistivities that remain above 16k Ohm.m; the second horizon composed of massive ice with debris, fluctuating between 40k and 300k Ohm.m and with thicknesses ranging from 40-60 metres, parallel to this horizon we also have massive ice corroborated by values of 400k and 6000k Ohm.m with thicknesses exceeding 60 metres and below this we have a third horizon composed of bedrock with average resistivity between 1.2k and 9k Ohm.m. These data found in the Kinzl Covered Glacier fit with those frequently found in glacial-periglacial deposits in the Andes.

The results provide a comprehensive understanding of the internal characteristics of the Kinzl Covered Glacier, highlighting its relevance for understanding the complexity and implications for glacial dynamics. These findings are valuable for numerical modelling, glacier risk management and water resource management.

How to cite: Chacca Luna, V., Jara Infantes, W. H., Cosi Fajardo, M. A., Aquino Morales, M. L., Mamani Yampi, L., Cachay, S., and Torres Lázaro, J. C.: Applications of geophysical techniques for the analysis of the internal structure and understanding of the hydrological system of the Kinzl Covered Glacier, Cordillera Blanca, Peru , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14548, https://doi.org/10.5194/egusphere-egu24-14548, 2024.

EGU24-15907 | PICO | CR5.1

Long-term refraction seismic monitoring: a reliable method to detect ground ice loss at mountain permafrost sites 

Christin Hilbich, Bernd Etzelmüller, Ketil Isaksen, Coline Mollaret, Sarah Morard, Cécile Pellet, and Christian Hauck

Geophysical monitoring becomes more and more popular in permafrost environments due to its remarkable success to detect permafrost thawing and spatio-temporal changes in the ground ice content. Mostly geoelectric methods such as Electrical Resistivity Tomography (ERT) are applied due to the strong differences in the electrical properties between frozen and unfrozen state. However, seismic properties also change markedly upon freezing/thawing and time-lapse refraction seismic tomography (RST) has been shown to be applicable to permafrost over smaller time scales (e.g., Hilbich 2010). The reason why only few studies employ long-term seismic monitoring in permafrost is probably due to the higher logistical effort required.

At two Swiss permafrost monitoring sites (Schilthorn and Stockhorn) yearly RST surveys are conducted using the same setup for more than 15 years, in addition to standard borehole temperature, climatic and ERT measurements (www.permos.ch). The monitoring aim is to image the interannual changes of the thickness of the active layer as well as differences in ice content within the permafrost layer below.

Additional long-term observations are available from RST (and contemporary ERT) surveys from several mountain permafrost sites in Norway that were initially conducted to characterise permafrost conditions around boreholes drilled in 1999/2008 (Juvvasshoe/Jotunheimen), and 2007/2008 (Iskoras/Finnmark, Guolasjavri/Troms, and Tronfjell, cf. Isaksen et al. 2011, Farbrot et al. 2013). These surveys were repeated with the same geometry in 2019 after 11 years in northern Norway, and after 8 and 20 years in southern Norway. As for the Swiss sites, temperatures from all these boreholes show a clear warming trend over the last 1-2 decades (Etzelmüller et al, 2020, 2023).

We here present the observed long-term changes in electrical resistivity and seismic P-wave velocity based on a) annually repeated measurements in the Swiss Alps, and b) on long-term repetition in northern and southern Norway. The geophysical changes are related to the observed borehole temperature increase during the same period (Etzelmüller et al. 2023) and analysed with respect to climate-induced thawing. We evaluate the advantages and disadvantages of seismic monitoring compared to the more standard ERT monitoring. Finally, the results are also analysed with respect to their suitability for future ERT-seismic joint inversion approaches in a monitoring context.

 

References

Etzelmüller B, Guglielmin M, Hauck C, Hilbich C, Hoelzle M, Isaksen K, Noetzli J, Oliva M and Ramos M 2020. Twenty years of European mountain permafrost dynamics—the PACE legacy. Environ. Res. Lett. 15 104070 DOI 10.1088/1748-9326/abae9d

Etzelmüller B, Isaksen K, Czekirda J, Westermann S, Hilbich C, Hauck C 2023. Rapid warming and degradation of mountain permafrost in Norway and Iceland. The Cryosphere. 17.5477-5497.10.5194/tc-17-5477-2023.

Farbrot H, Isaksen K, Etzelmüller B, Gisnås K 2013. Ground Thermal Regime and Permafrost Distribution under a Changing Climate in Northern Norway. Permafrost Periglac.,24(1):20-38. https://doi.org/10.1002/ppp.1763

Isaksen K, Ødegård RS, Etzelmüller B, Hilbich C, Hauck C, Farbrot H, Eiken T, Hygen HO, Hipp T 2011. Degrading mountain permafrost in southern Norway - spatial and temporal variability of mean ground temperatures 1999-2009. Permafrost Periglac.,22(4):361-377, https://doi 10.1002/ppp.728.

Hilbich C 2010. Time-lapse refraction seismic tomography for the detection of ground ice degradation, The Cryosphere, 4, 243–259, https://doi.org/10.5194/tc-4-243-2010, 2010.

How to cite: Hilbich, C., Etzelmüller, B., Isaksen, K., Mollaret, C., Morard, S., Pellet, C., and Hauck, C.: Long-term refraction seismic monitoring: a reliable method to detect ground ice loss at mountain permafrost sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15907, https://doi.org/10.5194/egusphere-egu24-15907, 2024.

EGU24-16320 | PICO | CR5.1

Quieting of hydraulic tremor: sudden changes in frictional conditions in subglacial channels 

Małgorzata Chmiel, Nicoletta Caldera, Fabian Walter, Gerrit Olivier, Daniel Farinotti, Alberto Guadagnini, Dominik Gräff, Manuela Köpfli, and Florent Gimbert

The state and evolution of subglacial channels strongly impact glacier motion and as a result the mass balance of flowing ice bodies. Yet, the subglacial environment is difficult to access and thus often poorly constrained over significant temporal and spatial scales. This limits our understanding of complex subglacial hydraulic processes and consequently ice dynamics.

Seismology can help overcome these observational constraints, providing new insights into fundamental processes in the cryosphere, such as frictional sliding and subglacial water flow. However, different seismogenic processes of the cryosphere often overlap in both time and space. Differentiating between them and interpreting associated seismic signals require appropriate methodological and instrumental approaches.

Here, we investigate subglacial channel dynamics at the Rhone glacier (Switzerland) over one month in the summer of 2020, focusing on periods coinciding with glacier sliding episodes. To this end, we leverage the sensitivity of near-bed borehole geophones combined with seismic interferometry and beamforming techniques.

We show that the hydraulic tremor, generated by turbulent water flow and resulting pressure variations acting against the subglacial channel bed and walls, acts as a dominant, stable, and coherent noise source. Beamforming analysis reveals the directional stability of the hydraulic tremor and points toward the junction of two subglacial hydraulic channels from which stick-slip asperities originate. The analysis also reveals instances of sudden hydraulic tremor quieting, in agreement with previous observations before and after seismogenic sliding episodes. We explain this quieting as sudden changes in frictional conditions within the subglacial channel corresponding to a rapid transition between a fully and partially filled channel. We discuss channel properties (geometry and bed conditions) that are needed to satisfy the physical conditions for the frictional quieting mechanism. Our analysis offers new insights into the complex mechanical interactions between ice, water, and bed properties and the hydraulic control of glacier sliding.

How to cite: Chmiel, M., Caldera, N., Walter, F., Olivier, G., Farinotti, D., Guadagnini, A., Gräff, D., Köpfli, M., and Gimbert, F.: Quieting of hydraulic tremor: sudden changes in frictional conditions in subglacial channels, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16320, https://doi.org/10.5194/egusphere-egu24-16320, 2024.

EGU24-17134 | ECS | PICO | CR5.1

Lightweight In-Situ Analysis of snow density and accumulation 

Johanna von Drachenfels, Helle Astrid Kjær, and Josephine Lindsey-Clark

A critical factor in accurate Surface Mass Balance predictions of the Greenland Ice Sheet is the availability of spatially and temporally extensive snow accumulation data (Montgomery et al., 2018). Currently, this data remains deficient due to incomplete geographical coverage and poor temporal resolution (Sheperd et al., 2012).

An innovative approach to expanding the existing dataset is the utilization of the LISA box: a portable Lightweight In-Situ Analysis system designed for fast and straightforward snow and ice core measurements (Kjær et al., 2021), which speeds up the delivery of the results. With the LISA box, the sample cores are melted, and continuous flow analysis of chemical impurities and conductivity in the meltwater reveals annual peaks and climatic horizons. This information allows for dating of the single ice and snow layers. The registration of the melt speed furthermore permits the determination of the layer thickness, while the layer density can be inferred with an additional measurement of the meltwater flowrate. By combining these insights, past accumulation rates, as indicated by the volume of annually deposited snow, can be reconstructed.

Here we present updates to the existing LISA box enhancing its abilities to further analyse for density variations in snow and firn cores.

How to cite: von Drachenfels, J., Kjær, H. A., and Lindsey-Clark, J.: Lightweight In-Situ Analysis of snow density and accumulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17134, https://doi.org/10.5194/egusphere-egu24-17134, 2024.

EGU24-17421 | PICO | CR5.1

Lake ice seismicity: seismic and acoustic observations 

Cedric Schmelzbach, Christoph Wetter, Simon Stähler, John Clinton, Zinan Lyu, Maria Mesimeri, and Frédérick Massin

Seismic events (icequakes) associated with floating ice sheets on lakes are a frequently observed phenomenon. We find at our study site on the frozen Lake St. Moritz in the Swiss Alps typically a clear diurnal pattern with hundreds to thousands of icequake signals per hour during night time, while the rate of observed events during daytime is about two orders of magnitude smaller. The seismicity rate shows a significant correlation with temperature changes. It is therefore assumed that the generation of the ice quakes is related to melting and freezing processes as well as the extension and contraction of the ice. Potentially the seismicity rate is also moderated by loading and unloading due to human activities on the ice and/or lake level changes.

These ice quakes generate seismic waves that propagate through the thin ice sheet as plate waves modulated by the air and water half-spaces above and below the ice (quasi-guided waves). One member of this wave-type family, the quasi-Scholte waves, are characterised by distinct dispersion that can be observed with seismic sensors on the ice. Furthermore, the seismic waves traveling through the ice couple into the air leading to audible seismo-acoustic signals. One particularity of the ice-air coupling is a so-called coincidence phenomenon. The particular velocity-frequency combination where the seismic wavelength in the ice matches the apparent acoustic wavelength in the air leads to a resonance phenomenon. Observation of the related coincidence frequency allows us, for example, to infer on the ice thickness from the acoustic observations with a low cost microphone above the ice only. Recording the acoustic signals with small microphone arrays enables additionally, for example, locating the source of the seismo-acoustic signal.

Combined observations of the seismic and acoustic signals provide new insights into the seismicity of lake ice which has rarely been studied in the past. The seismo-acoustic signals have the potential to provide information about the ice properties such as thickness and ice quality as well as waxing and waning processes of ice sheets. These observations are relevant for safe operations on the ice but also to complement other remote-sensing observations with autonomous in situ seismo-acoustic measurements for climate studies.

How to cite: Schmelzbach, C., Wetter, C., Stähler, S., Clinton, J., Lyu, Z., Mesimeri, M., and Massin, F.: Lake ice seismicity: seismic and acoustic observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17421, https://doi.org/10.5194/egusphere-egu24-17421, 2024.

EGU24-17767 | PICO | CR5.1

Glaciological characterization of Little Dome C: Influence of ice flow on the future Beyond Epica – Oldest Ice Core drilling project 

Robert Mulvaney, Carlos Martín, Catherine Ritz, Luca Vittuari, Massimo Frezzotti, and Olaf Eisen

An ice core is being drilled near Little Dome C, a small promontory about 30km downstream from the summit of Dome C, to extract a continuous record of climate over the last 1.5 million years. Present and past ice flow conditions are important to interpret the ice core because the surface velocity at the drilling site is about 40 mm/yr and the oldest ice in the record was deposited in the surface about 10km upstream of the drilling site. Here we explore newly acquired and existing geophysical data to describe present ice flow and investigate signs of past changes. We present new GNSS data that describes the subtle but complex local surface velocity, and ApRES radar data that provides englacial strain-rates along the flow path from the summit of Dome C and bulk englacial crystal orientation fabric. Ice currently flows from Dome C summit along the ridge to Little Dome C, even though a subtle uphill slope, but basal conditions are variable along the path due to the strong basal topography. Of special interest is an ice unit in contact with the bedrock with variable thickness up to about 300m that is vertically stagnant and produce a strong radar reflection.  This basal unit is not present in an area of strong melting about 5km upstream from the drilling site. The crystal orientation fabric reflects the ice flow horizontal extension along the path and changes with depth on ice flow properties following climatic transitions and, more intriguing, indicate a possible change in ice flow extension at the beginning of the Holocene. We aim to facilitate detailed ice flow models to better interpret the ice core data.  

How to cite: Mulvaney, R., Martín, C., Ritz, C., Vittuari, L., Frezzotti, M., and Eisen, O.: Glaciological characterization of Little Dome C: Influence of ice flow on the future Beyond Epica – Oldest Ice Core drilling project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17767, https://doi.org/10.5194/egusphere-egu24-17767, 2024.

EGU24-17917 | PICO | CR5.1

Using received laser signal intensity to measure snow and ice surface properties automatically  

Alexander Prokop, Florian Tolle, Jean-Michelle Friedt, and Eric Bernard

In the context of climate warming it is a common scientific goal to study and monitor surface and volume changes of glaciers and melting dynamics of its snow and ice. Therefore several measurement techniques exist to track permanently ice melting e.g. DGPS stations on glaciers, Smart stake, and snow and ice depth measurements via e.g. ultrasonic depth sensors to create time series of snow and ice loss or gain. None of the existing methods measure if actually liquid water is present and melting occurs, this is later concluded by interpretation of the geometric data. The capability of the laser sensor to do so via the reflectance value, in fact the received signal intensity, we consider as a big advantage and worth investigating further as a direct measure of snow or ice melt that helps not only to analyze glacier dynamics but is also important e.g. for providing reliable ground truth data for satellite remote sensing. When melting of snow and ice occurs, water changes the reflectance properties as due to absorption of the laser in water, only a portion of the laser is reflected. This allows determining if liquid water is present at the surface measured. We present the data collected in the last 2 melting seasons of the Austre Lovénbreen glacier near Ny Alesund, Svalbard. We show how we classify wet snow and wet ice hours with confidence and are able to compute melting rates. The single point measurement is put into context to area wide LiDAR measurements and melting dynamics of the glacier are analyzed. The data was verified against visual inspections from automatic cameras, data from an automatic weather station both located in the glacier catchment and ice melt was measured in close proximity with a SmartStake station.

How to cite: Prokop, A., Tolle, F., Friedt, J.-M., and Bernard, E.: Using received laser signal intensity to measure snow and ice surface properties automatically , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17917, https://doi.org/10.5194/egusphere-egu24-17917, 2024.

EGU24-18177 | ECS | PICO | CR5.1

Applying Cosmic-Ray Neutron Sensing in Highly Heterogeneous Conditions: Monitoring Snow Water Equivalent in Periods with Partial Snow Coverage 

Paul Schattan, Jan Schmieder, Markus Köhli, Christine Fey, and Martin Schrön

Cosmic-Ray Neutron Sensing (CRNS) constitutes an emerging method for monitoring soil moisture and snow dynamics at intermediate spatial scales of several hectares. In complex environments such as mountain regions, however, the presence of areas with a high contrast of hydrogen content was found to cause a hysteresis in the relationship between neutron counts and water equivalent. A simulation study using the newly developed hierarchical scenario tool YULIA (Your URANOS Layer Integration Assistant) for the Monte-Carlo neutron simulation model URANOS was conducted to quantify the effect of snow-free areas on above-ground neutron sensing of the snow water equivalent (SWE). It was found that the size and distance of the snow free patches have the largest impact on the neutron flux. The simulations also showed a sensitivity of the signal towards soil moisture and SWE. Correction functions were developed and validated with observed CRNS measurements and LiDAR based distributed SWE maps. The main aim of the correction procedure is to estimate SWE under partly snow-covered conditions. Furthermore, also the soil moisture of the snow-free areas can be inferred if the SWE distribution is known. The latter can be used for other high-contrast CRNS applications like monitoring soil moisture in the presence of ponding water.

How to cite: Schattan, P., Schmieder, J., Köhli, M., Fey, C., and Schrön, M.: Applying Cosmic-Ray Neutron Sensing in Highly Heterogeneous Conditions: Monitoring Snow Water Equivalent in Periods with Partial Snow Coverage, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18177, https://doi.org/10.5194/egusphere-egu24-18177, 2024.

EGU24-18639 | PICO | CR5.1

Stick-slip imaging through the GPR phase: Turning  temperate ice 'noise' into signal 

Johannes Aichele, Christophe Ogier, and Barthélémy Anhorn


Ground Penetrating Radar (GPR) is a major tool to investigate, map and monitor polar ice sheets and alpine glaciers. Alpine glaciers are often composed of temperate ice, which has significantly different backscatter properties from cold ice. Radar attenuation is much stronger in temperate ice than in cold ice, because the radar signal encounters strong scattering in temperate ice. 
A major candidate for this scattering is the presence of liquid water inclusions, which are much smaller than the radar wavelength. The large contrast between water and ice dielectric permittivity would explain the diffuse radar scattering in temperate ice. Indeed, recent numerical modelling of the radar signal in temperate ice confirmed the contribution of liquid water inclusions on the scattering of the radar signal (Ogier, 2023). 
Here, we investigate if the strong scattering caused by liquid water inclusions, which is usually treated as noise, can be in fact exploited to unravel dynamic processes inside the glacier. This strong scattering results in large radar phase variations in space, which remain constant over short timescales (hours - days), during which the glacial water content remains constant. During that timescale, however, the mountain glacier might experience sudden internal deformation due to intermittent sliding at the glacier base, also called glacier stick-slip.  This deformation might be resolved using difference imaging and the spatio-temporal properties of the radar phase.
We numerically model radar wave propagation throughout temperate ice (i.e. with the presence of liquid water inclusions) before and after an idealized glacier deformation and show, that through phase difference imaging the internal movement of the sub-wavelength scatterers can be mapped. 
Finally, we discuss how this novel type of monitoring could be applied in the field, which is planned for spring 2024.

 

Ogier, Christophe, Dirk-Jan van Manen, Hansruedi Maurer, Ludovic Räss, Marian Hertrich, Andreas Bauder, and Daniel Farinotti. 2023. “Ground Penetrating Radar in Temperate Ice: Englacial Water Inclusions as Limiting Factor for Data Interpretation.” Journal of Glaciology, September, 1–12. https://doi.org/10.1017/jog.2023.68.

How to cite: Aichele, J., Ogier, C., and Anhorn, B.: Stick-slip imaging through the GPR phase: Turning  temperate ice 'noise' into signal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18639, https://doi.org/10.5194/egusphere-egu24-18639, 2024.

EGU24-19098 | PICO | CR5.1

Observing glacier bed topography: the H/V spectral method applied on a dense seismic array as a simple alternative to radar 

Florent Gimbert, Neil Ross, Tifenn Le Bris, Guilhem Barruol, Tun Jan Young, Samuel Doyle, Stephen Livingstone, Andrew Sole, Adrien Gilbert, Ryan Ing, Liz Bagshaw, Mike Prior-Jones, and Laura Edwards

Accurate knowledge of glacier bed topography is critical for quantifying ice volumes and modelling ice and subglacial hydrology dynamics. Bed topography observations are traditionally obtained from airborne and ice penetrating radar, which offers the crucial advantage of recovering the detailed glacier structure over a range of scales. A main difficulty with radar, however, is that waves can be strongly scattered and attenuated by englacial heterogeneities, in particular by water inclusions, which can potentially limit the applicability of the technique under certain conditions.

Here we present a case study on Isunguata Sermia, West Greenland, where we conducted an ice penetrating radar survey together with dense seismic array acquisitions from 87 nodes spread over a 1 km2 area. We show that, in the area of investigation, radar observations were only partially successful in identifying the ice-bed interface, likely due to the thick warm ice, presence of some surface water and near-surfacing crevassing and other englacial structures. The H/V analysis performed over the seismic array yielded surprisingly coherent estimates of ice thickness, along with its spatial variation along and across the glacier. These findings raise questions about the interpretation of traditional radar measurements under certain glacier conditions, and how dense seismic arrays could retrieve bed topography more systematically. 

How to cite: Gimbert, F., Ross, N., Le Bris, T., Barruol, G., Young, T. J., Doyle, S., Livingstone, S., Sole, A., Gilbert, A., Ing, R., Bagshaw, L., Prior-Jones, M., and Edwards, L.: Observing glacier bed topography: the H/V spectral method applied on a dense seismic array as a simple alternative to radar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19098, https://doi.org/10.5194/egusphere-egu24-19098, 2024.

EGU24-20308 | ECS | PICO | CR5.1

“Determination of Hydric Potencial through Geoelectric and Piezometric methods in the Ichickcollcococha Wetland, Pachacoto Hydrographic Unit, Cordillera Blanca, Perú.”  

Leila Maribel Mamani, W. Harrinson Jara, Velnia Chacca Luna, Juan C. Torres, Helder Mallqui, Manuel Cosi, Cristian Quispe, and Milagros Aquino

Abstracts

High-Andean bofedales are vegetated wetlands that play a crucial role in the context of climate change by facilitating the capture of carbon dioxide and regulating water. However, global warming has led to the glacial retreat of major snow-capped peaks, such as the Pastoruri Glacier, resulting in water scarcity that directly impacts these ecosystems. Hence, there is a pressing need to study them. This research aims to characterize the physical structure of the Ichickcollcococha bofedal, located in the Pachacoto Hydrographic Unit in the southern sector of the Cordillera Blanca, Peru. The objective is to determine its water storage potential during periods of high precipitation and drought. The study employs the Vertical Electrical Sounding (VES) geophysical prospecting method, corroborated by vibrating wire piezometers installed in the Ichickcollcococha bofedal. This method allows for a detailed analysis of the subsurface resistive properties, generating geo-electric profiles that detail the internal structure of the bofedal.

Three horizons have been identified: the upper layer is loosely composed of organic material (vegetation, cushioned bofedales) with high moisture content, reaching a depth of approximately 1.5 meters and average resistivity values around 431 Ohm.m. The second layer extends to a depth of 11 meters with resistivities of 67 Ohm.m, corresponding to organic materials such as peat and saturated sands. The third horizon, with estimated depths of 80 meters and resistivities around 1301 Ohm.m, corresponds to underlying limestone rock. The data obtained from the Ichickcollcococha bofedal align with characteristic values of glacial-origin peat bogs.

The findings of this study provide a comprehensive understanding of the internal characteristics of the Ichickcollcococha bofedal, highlighting its contribution to the knowledge of its internal dynamics and its implications for the water potential of high-Andean bofedales. Furthermore, the results offer valuable information for modeling and water resource management.

Keywords: Bofedal, Hydric potential, geoelectric method, VES.

How to cite: Mamani, L. M., Jara, W. H., Chacca Luna, V., Torres, J. C., Mallqui, H., Cosi, M., Quispe, C., and Aquino, M.: “Determination of Hydric Potencial through Geoelectric and Piezometric methods in the Ichickcollcococha Wetland, Pachacoto Hydrographic Unit, Cordillera Blanca, Perú.” , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20308, https://doi.org/10.5194/egusphere-egu24-20308, 2024.

EGU24-21232 | ECS | PICO | CR5.1

Quantifying Ground Ice in Tien Shan and Pamir Permafrost: A Comprehensive Petrophysical Joint Inversion Study Applying the electrical Geometric Mean Model  

Tamara Mathys, Christin Hilbich, Coline Mollaret, Christian Hauck, Tomas Saks, Ryksul Usubaliev, Bolot Moldobekov, Zhoodarbeshim Bektursunov, Muslim Azimshoev, Hofiz Navruzshoev, and Martin Hoelzle

Central Asian Mountain regions (Tien Shan and Pamir) are expected to be significantly impacted by climate change, affecting water availability and natural hazards. The cryosphere plays a crucial role in many watersheds of the region by providing water for hydropower station, irrigation, and domestic use downstream. At the same time, retreating glaciers and thawing permafrost increase the risk of natural hazards. Therefore, cryosphere monitoring systems are necessary to provide baseline data for estimating future water availability and detecting dangerous hazard zones. Despite the large areas underlain by permafrost in the Tien Shan and Pamir Mountain ranges, data on permafrost distribution, characteristics and evolution are scarce. However, quantitative estimations of permafrost subsurface components, especially water and ice contents, are needed to evaluate the consequences of current climate change on mountain permafrost environments.

Recent field-based investigations have emphasised the coupled use of geophysical techniques, e.g., by employing the Petrophysical Joint Inversion scheme (PJI, Wagner et al., 2019) that combines electrical resistivity and seismic refraction p-wave velocity data to estimate the four phases present in the subsurface (volumetric contents of air, water, ice, and rock). The traditional PJI implementation relies on Archie’s law (Archie, 1942) as one of the primary petrophysical equation to link resistivity to porosity and water content. Archie's law is generally considered valid when electrolytic conduction dominates, a condition that is not universally justified for dry and coarse blocky substrates and landforms in mountainous terrain. Recognizing this limitation, Mollaret et al. (2020) introduced the electrical Geometric Mean Model as an alternative implementation in the PJI. The Geometric Mean Model  assumes random distributions of the four phases and offers the advantage of including the fractions of ice and air in the petrophysical equation for resistivity, which are not present in Archie’s law. In this study, we assess the feasibility and effectiveness of using the Geometric Mean Model within the PJI framework across an extensive geophysical dataset comprising 22 profiles in Central Asia (Kyrgyzstan and Tajikistan). Our research encompasses diverse landforms, including moraines, rock glaciers, talus slopes, and fine-grained sediments. Our goals are to (i) evaluate the performance of the Geometric Mean Model in comparison to Archies law across different landforms and (ii) address the existing data gap concerning mountain permafrost and ground ice contents in the Central Asian region.

References

Archie, G. E. (1942). The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics. Transactions of the AIME, 146(01), 54–62. https://doi.org/10.2118/942054-G

Mollaret, C., Wagner, F. M., Hilbich, C., Scapozza, C., & Hauck, C. (2020). Petrophysical Joint Inversion Applied to Alpine Permafrost Field Sites to Image Subsurface Ice, Water, Air, and Rock Contents. Frontiers in Earth Science, 8, 85. https://doi.org/10.3389/feart.2020.00085

Wagner, F. M., Mollaret, C., Günther, T., Kemna, A., & Hauck, C. (2019). Quantitative imaging of water, ice and air in permafrost systems through petrophysical joint inversion of seismic refraction and electrical resistivity data. Geophysical Journal International, 219(3), 1866–1875. https://doi.org/10.1093/gji/ggz402

How to cite: Mathys, T., Hilbich, C., Mollaret, C., Hauck, C., Saks, T., Usubaliev, R., Moldobekov, B., Bektursunov, Z., Azimshoev, M., Navruzshoev, H., and Hoelzle, M.: Quantifying Ground Ice in Tien Shan and Pamir Permafrost: A Comprehensive Petrophysical Joint Inversion Study Applying the electrical Geometric Mean Model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21232, https://doi.org/10.5194/egusphere-egu24-21232, 2024.

EGU24-1198 | ECS | PICO | ESSI1.3

Satellite-Driven Traffic Volume Estimation: Harnessing Hybrid Machine Learning for Sustainable Urban Planning and Pollution Control 

Bilal Aslam, Toby Hocking, Pawlok Dass, Anna Kato, and Kevin Gurney

As cities grow and more cars occupying the roads, greenhouse gas emissions and air pollution in urban areas are going up. To better understand the emissions and pollutions, and help effective urban environmental mitigation, an accurate estimation of traffic volume is crucial. This study delves into the application of Hybrid Machine Learning models to estimate and predict traffic volume by utilizing satellite data and other datasets in both the USA and Europe. The research investigates the predictive capabilities of machine learning models employing freely accessible global datasets, including Sentinel 2, Night-time light data, population, and road density. Neural Network, nearest neighbours, random forest and XGBoost regression models were employed for traffic volume prediction, and their accuracy was enhanced using a hyperparameter-tuned K-Fold Cross-validation technique. Model accuracy, evaluated through Mean Percentage Error (MPE%) and R-square, revealed that XGBoost Regression model yielding an R2 accuracy of 0.81 and MPE of 13%. The low error (and therefore high accuracy) as well as the model's versatility allows its application worldwide for traffic volume computation utilizing readily available datasets. Machine learning models, particularly the XGBoost Regression model, prove valuable for on-road traffic volume prediction, offering a dataset applicable to town planning, urban transportation, and combating urban air pollution.

How to cite: Aslam, B., Hocking, T., Dass, P., Kato, A., and Gurney, K.: Satellite-Driven Traffic Volume Estimation: Harnessing Hybrid Machine Learning for Sustainable Urban Planning and Pollution Control, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1198, https://doi.org/10.5194/egusphere-egu24-1198, 2024.

Long-term satellite-based imagery provides fundamental data support for identifying and analyzing land surface dynamics. Although moderate-spatial-resolution data, like the Moderate Resolution Imaging Spectroradiometer (MODIS), were widely used for large-scale regional studies, their limited availability before 2000 restricts their usage in long-term investigations. To reconstruct retrospective MODIS-like data, this study proposes a novel deep learning-based model, named the Land-Cover-assisted SpatioTemporal Fusion model (LCSTF). LCSTF leverages medium-grained spatial class features from Landcover300m and temporal seasonal fluctuations from the Global Inventory Modelling and Mapping Studies (GIMMS) NDVI3g time series data to generate 500-meter MODIS-like data from 1992 to 2010 over the continental United States. The model also implements the Long Short-Term Memory (LSTM) sensor-bias correction method to mitigate systematic differences between sensors. Validation against actual MODIS images confirms the model’s ability to produce accurate MODIS-like data. Additionally, when assessed with Landsat data prior to 2000, the model demonstrates excellent performance in reconstructing retrospective data. The developed model and the reconstructed biweekly MODIS-like dataset offer significant potential for extending the temporal coverage of moderate-spatial-resolution data, enabling comprehensive long-term and large-scale studies of land surface dynamics.

How to cite: Zhang, Z., Xiong, Z., Pan, X., and Xin, Q.: Developing a land-cover-assisted spatiotemporal fusion model for producing pre-2000 MODIS-like data over the continental United States, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2021, https://doi.org/10.5194/egusphere-egu24-2021, 2024.

EGU24-4445 | PICO | ESSI1.3

Fully Differentiable Physics-informed Lagrangian Convolutional Neural Network for Precipitation Nowcasting 

Peter Pavlík, Martin Výboh, Anna Bou Ezzeddine, and Viera Rozinajová

The task of precipitation nowcasting is often perceived as a computer vision problem. It is analogous to next frame video prediction - i.e. processing consecutive radar precipitation map frames and predicting the future ones. This makes convolutional neural networks (CNNs) a great fit for this task. In the recent years, the CNNs have become the de-facto state-of-the-art model for precipitation nowcasts.

However, a pure machine learning model has difficulties to capture accurately the underlying patterns in the data. Since the data behaves according to the known physical laws, we can incorporate this knowledge to train more accurate and trustworthy models.

We present a double U-Net model, combining a continuity-constrained Lagrangian persistence U-Net with an advection-free U-Net dedicated to capturing the precipitation growth and decay. In contrast to previous works, the combined model is fully differentiable, allowing us to fine-tune these models together in a data-driven way. We examine the learned Lagrangian mappings, along with a thorough quantitative and qualitative evaluation. The results of the evaluation will be provided in the presentation.

How to cite: Pavlík, P., Výboh, M., Bou Ezzeddine, A., and Rozinajová, V.: Fully Differentiable Physics-informed Lagrangian Convolutional Neural Network for Precipitation Nowcasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4445, https://doi.org/10.5194/egusphere-egu24-4445, 2024.

EGU24-10278 | ECS | PICO | ESSI1.3

Assessing the area of applicability of spatial prediction models through a local data point density approach 

Fabian Schumacher, Christian Knoth, Marvin Ludwig, and Hanna Meyer

Machine learning is frequently used in the field of earth and environmental sciences to produce spatial or spatio-temporal predictions of environmental variables based on limited field samples - increasingly even on a global scale and far beyond the extent of available training data. Since new geographic space often goes along with new environmental properties, the spatial applicability and transferability of models is often questionable. Predictions should be constrained to environments that exhibit properties the model has been enabled to learn.

Meyer and Pebesma (2021) have made a first proposal to estimate the area of applicability (AOA) of spatial prediction models. Their method is based on distances - in the predictor space - of the prediction data point to the nearest reference data point to derive a dissimilarity Index (DI). Prediction locations with a DI larger than DI values observed through cross-validation during model training are considered outside of the AOA. As a consequence, the AOA is defined as the area where the model has been enabled to learn about relationships between predictors and target variables and where, on average, the cross-validation performance applies. The method, however, is only based on the distance - in the predictor space - to the nearest reference data point. Hence, a single data point in an environment may define a model as “applicable” in this environment. Here we suggest extending this approach by considering the densitiy of reference data points in the predictor space, as we assume that this is highly decisive for the prediction quality.

We suggest extending the methodology with a newly developed local data point density (LPD) approach based on the given concepts of the original method to allow for a better assessment of the applicability of a model. The LPD is a quantitative measure for a new data point that indicates how many similar (in terms of predictor values) reference data points have been included in the model training, assuming a positive relationship between LPD values and prediction performance. A reference data point is considered similar if it defines a new data point as being within the AOA, i.e. the model is considered applicable for the corresponding prediction location. We implemented the LPD approach in the R package CAST. Here we explain the method and show its applicability in simulation studies as well as real-world applications.

Reference:

Meyer, H; Pebesma, E. 2021. ‘Predicting into unknown space? Estimating the area of applicability of spatial prediction models.’ Methods in Ecology and Evolution 12: 1620–1633. doi: 10.1111/2041-210X.13650.

How to cite: Schumacher, F., Knoth, C., Ludwig, M., and Meyer, H.: Assessing the area of applicability of spatial prediction models through a local data point density approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10278, https://doi.org/10.5194/egusphere-egu24-10278, 2024.

With the rapid growth in global trade, the demand for efficient route planning and resource utilization in logistics and transportation mirrors the Travelling Salesman Problem (TSP). TSP refers to finding the shortest route possible of N destinations by visiting each destination once and returning to the starting point. Moreover, the computational complexity of TSP increases exponentially with the number of destinations, where finding an exact solution is not practical in larger instance. It has long been a challenging optimization problem, prompting the development of various methodologies to seek for more efficient solution, especially towards metaheuristics in recent research. Therefore, this research proposes an optimization algorithm with the implementation of the Swarm Intelligence-based method for solving TSP, providing an approximate solution. The proposed algorithm is evaluated by comparing its performance in terms of solution quality and computation time to well-known optimization methods, namely the Genetic Algorithm and the Ant Colony Optimization. 47 cities and 50 landmarks in the U.S. are selected as the destinations for two experimental datasets respectively with geospatial data retrieved from Google Maps Platform API. The experiment result suggests that the proposed algorithm has computed a near-optimal solution along with the shortest computation time among the three optimization methods. Solving the TSP efficiently contributes significantly to route planning for transportation and logistics. By shortening the travelling time, optimizing resource utilization, and minimizing fuel and energy consumption, this research further aligns with the global goal of carbon reduction for transportation and logistics systems.

How to cite: Wong, K. T.: Solving the Travelling Salesman Problem for Efficient Route Planning through Swarm Intelligence-Based Optimization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13452, https://doi.org/10.5194/egusphere-egu24-13452, 2024.

Land surface temperature (LST) is a critical parameter for understanding the physical properties of the boundary between the earth's surface and the atmosphere, and it has a significant impact on various research areas, including agriculture, climate, hydrology, and the environment. However, the thermal infrared band of remote sensing is often hindered by clouds and aerosols, resulting in gaps in LST data products, which hinders the practical application of these products. Therefore, reconstruction of cloud-covered thermal infrared LST is vital for the measurement of physical properties in land surface at regional and global scales. In this paper, a novel reconstruction method for Moderate Resolution Imaging Spectroradiometer (MODIS) LST data with a 1-km spatial resolution is proposed by a spatiotemporal consistency constraint network (STCCN) model fusing reanalysis and thermal infrared data. Firstly, a new spatio-temporal consistency loss function was developed to minimize the discrepancies between the reconstructed LST and the actual LST, by using a non-local reinforced convolutional neural network. Secondly, ERA5 surface net solar radiation (SSR) data was applied as one of the important factors for network inputs, it can characterize the influence of the Sun on surface warming and correct the LST reconstruction results. The experimental results show that (1) the STCCN model can precisely reconstruct cloud-covered LST, the coefficient of determination (R) is 0.8973 and the mean absolute error (MAE) is 0.8070 K; (2) with the introduction of ERA5 SSR data, the MAE of reconstructed LST decreases by 17.15% while the R is kept close, indicating that it is necessary and beneficial to consider the effects of radiation data on LST; (3) the analysis of spatial and temporal adaptability indicates that the proposed method exhibits strong resilience and flexibility in accommodating variations across different spatial and temporal scales, suggesting its potential for effective and reliable application in different scenarios; (4) referring to the SURFRAD station observations, the reconstructed R ranges from 0.8 to 0.9, and MAE ranges from 1 to 3 K, demonstrating the high effectiveness and validity of the proposed model for reconstructing regional cloud-covered LST.

How to cite: Gong, Y., Li, H., and Li, J.: STCCN: A spatiotemporal consistency constraint network for all-weather MODIS LST reconstruction by fusing reanalysis and thermal infrared data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13833, https://doi.org/10.5194/egusphere-egu24-13833, 2024.

EGU24-16841 | PICO | ESSI1.3

Photovoltaic Farms Mapping using openEO Platform 

Mohammad Alasawedah, Michele Claus, Alexander Jacob, Patrick Griffiths, Jeroen Dries, and Stefaan Lippens

Photovoltaic farms (PV farms) mapping is essential for establishing valid policies regarding natural resources management and clean energy. As evidenced by the recent COP28 summit, where almost 120 global leaders pledged to triple the world’s renewable energy capacity before 2030, it is crucial to make these mapping efforts scalable and reproducible. Recently, there were efforts towards the global mapping of PV farms [1], but these were limited to fixed time periods of the analyzed satellite imagery and not openly reproducible.  Building on this effort, we propose the use of openEO [2] User Defined Processes (UDP) implemented in openEO platform for mapping solar farms using Sentinel-2 imagery, emphasizing the four foundational FAIR data principles: Findability, Accessibility, Interoperability, and Reusability. The UDPs encapsulate the entire workflow including solar farms mapping, starting from data preprocessing and analysis to model training and prediction. The use of openEO UDPs enables easy reuse and parametrization for future PV farms mapping.  

Open-source data is used to construct the training dataset, leveraging OpenStreetMap (OSM) to gather PV farms polygons across different countries. Different filtering techniques are involved in the creation of the training set, in particular land cover and terrain. To ensure model robustness, we leveraged the temporal resolution of Sentinel-2 L2A data and utilized openEO to create a reusable workflow that simplifies the data access in the cloud, allowing the collection of training samples over Europe efficiently. This workflow includes preprocessing steps such as cloud masking, gap filling, outliers filtering as well as feature extraction. Alot of effort is put in the best training samples generation, ensuring an optimal starting point for the subsequent steps. After compiling the training dataset, we conducted a statistical discrimination analysis of different pixel-level models to determine the most effective one. Our goal is to compare time-series machine learning (ML) models like InceptionTime, which uses 3D data as input, with tree-based models like Random Forest (RF), which employs 2D data along with feature engineering. An openEO process graph is then constructed to organize and automate the execution of the inference phase, encapsulating all necessary processes from the preprocessing to the prediction stage. Finally, the process graph is transformed into a reusable UDP that can be reused by others for replicable PV farms mapping, from single farm to country scale. The use of the openEO UDP enables replications of the workflow to map new temporal assessments of PV farms distribution. The UDP process for the PV farms mapping is integrated with the ESA Green Transition Information Factory (GTIF, https://gtif.esa.int/), providing the ability for streamlined and FAIR compliant updates of related energy infrastructure mapping efforts. 

[1] Kruitwagen, L., et al. A global inventory of photovoltaic solar energy generating units. Nature 598, 604–610 (2021). https://doi.org/10.1038/s41586-021-03957-7 

[2] Schramm, M, et al. The openEO API–Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities. Remote Sens. 2021, 13, 1125. https://doi.org/10.3390/rs13061125 

How to cite: Alasawedah, M., Claus, M., Jacob, A., Griffiths, P., Dries, J., and Lippens, S.: Photovoltaic Farms Mapping using openEO Platform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16841, https://doi.org/10.5194/egusphere-egu24-16841, 2024.

EGU24-17458 | PICO | ESSI1.3

Spatially explicit active learning for crop-type mapping from satellite image time series 

Mariana Belgiu, Beatrice Kaijage, and Wietske Bijker

The availability of sufficient annotated samples is one of the main challenges of the supervised methods used to classify crop types from remote sensing images. Generating a large number of annotated samples is a time-consuming and expensive task. Active Learning (AL) is one of the solutions that can be used to optimize the sample annotation, resulting in an efficiently trained supervised method with less effort. Unfortunately, most of the developed AL methods do not account for the spatial information inherent in remote-sensing images. We propose a novel spatially-explicit AL that uses a semi-variogram to identify and discard the spatially adjacent and, consequently, redundant samples. It was evaluated using Random Forest (RF) and Sentinel-2 Satellite Image Time Series (SITS) in two study areas from the Netherlands and Belgium. In the Netherlands, the spatially explicit AL selected a total number of 97 samples as being relevant for the classification task which led to an overall accuracy of 80%, while the traditional AL method selected a total number of 169 samples achieving an accuracy of 82%. In Belgium, spatially explicit AL selected 223 samples and obtained an overall accuracy of 60%, compared to the traditional AL that selected 327 samples which yielded an accuracy of 63%. We concluded that the developed AL method helped RF achieve a good performance mostly for the classes consisting of individual crops with a relatively distinctive growth pattern such as sugar beets or cereals. Aggregated classes such as ‘fruits and nuts’ represented, however, a challenge. The proposed AL method reveals that accounting for spatial information is an efficient solution to map target crops since it facilitates high accuracy with a low number of samples and, consequently, lower computational resources and time and financial resources for annotation.

How to cite: Belgiu, M., Kaijage, B., and Bijker, W.: Spatially explicit active learning for crop-type mapping from satellite image time series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17458, https://doi.org/10.5194/egusphere-egu24-17458, 2024.

EGU24-19275 | PICO | ESSI1.3

Artificial Intelligence Reconstructs Historical Climate Extremes 

Étienne Plésiat, Robert Dunn, Markus Donat, Thomas Ludwig, and Christopher Kadow

The year 2023 represents a significant milestone in climate history: it was indeed confirmed by the Copernicus Climate Change Service (C3S) as the warmest calendar year in global temperature data records since 1850. With a deviation of 1.48ºC from the 1850-1900 pre-industrial level, 2023 largely surpasses 2016, 2019, 2020, previously identified as the warmest years on record. As expected, this sustained warmth leads to an increase in frequency and intensity of Extreme Events (EE) with dramatic environmental and societal consequences.

To assess the evolution of these EE and establish adaptation and mitigation strategies, it is crucial to evaluate the trends of extreme indices (EI). However, the observational climate data that are commonly used for the calculation of these indices frequently contains missing values, resulting in partial and inaccurate EI. As we delve deeper into the past, this issue becomes more pronounced due to the scarcity of historical measurements.

To circumvent the lack of information, we are using a deep learning technique based on a U-Net made of partial convolutional layers [1]. Models are trained with Earth system model data from CMIP6 and has the capability to reconstruct large and irregular regions of missing data using minimal computational resources. This approach has shown its ability to outperform traditional statistical methods such as Kriging by learning intricate patterns in climate data [2].

In this study, we have applied our technique to the reconstruction of gridded land surface EI from an intermediate product of the HadEX3 dataset [3]. This intermediate product is obtained by combining station measurements without interpolation, resulting in numerous missing values that varies in both space and time. These missing values affect significantly the calculation of the long-term linear trend (1901-2018), especially if we consider solely the grid boxes containing values for the whole time period. The trend calculated for the TX90p index that measures the monthly (or annual) frequency of warm days (defined as a percentage of days where daily maximum temperature is above the 90th percentile) is presented for the European continent on the left panel of the figure. It illustrates the resulting amount of missing values indicated by the gray pixels. With our AI method, we have been able to reconstruct the TX90p values for all the time steps and calculate the long-term trend shown on the right panel of the figure. The reconstructed dataset is being prepared for the community in the framework of the H2020 CLINT project [4] for further detection and attribution studies.

[1] Liu G. et al., Lecture Notes in Computer Science, 11215, 19-35 (2018)
[2] Kadow C. et al., Nat. Geosci., 13, 408-413 (2020)
[3] Dunn R. J. H. et al., J. Geophys. Res. Atmos., 125, 1 (2020)
[4] https://climateintelligence.eu/

How to cite: Plésiat, É., Dunn, R., Donat, M., Ludwig, T., and Kadow, C.: Artificial Intelligence Reconstructs Historical Climate Extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19275, https://doi.org/10.5194/egusphere-egu24-19275, 2024.

EGU24-19394 | PICO | ESSI1.3

Comparing the Role of Spatially and Temporally capable Deep Learning Architectures in Rainfall Estimation: A Case Study over North East India 

Aditya Handur-Kulkarni, Shanay Mehta, Ayush Ghatalia, and Ritu Anilkumar

The northeastern states of India are faced with heavy-precipitation related disasters such as floods and landslides every monsoon. Further, the region's economy is predominantly dependent on agriculture. Thus, accurate prediction of rainfall plays a vital role in the planning and disaster management programs in the region. Existing methods used for rainfall prediction include Automatic Weather Stations that provide real-time rainfall measurements at specific locations. However, these are point-based estimates. For distributed measurements, a satellite-based estimation can be used. While these methods provide vital information on the spatial distribution of precipitation, they face the caveat that they provide only real-time estimates. Numerical weather forecast models are used for encoding forecasting capabilities by simulating the atmosphere's physical processes through data assimilation of observational data from various sources, including weather stations and satellites. However, these models are incredibly complex and require immense computational strength. The veracity of the numerical models is limited by available computing architecture. Recently, a host of data-driven models, including random forest regression, support vector machine regression and deep learning architectures, have been used to provide distributed rainfall forecasts. However, the relative performance of such models in an orographically complex terrain has not been ascertained via a disciplined study. Through this study, we aim to systematically assess the role of convolutional and recurrent neural network architectures in estimating rainfall. We have used rainfall data from the ERA5 Land reanalysis dataset and data from the following additional meteorological variables that can impact rainfall: dew point temperature, skin temperature, amount of solar radiation, wind components, surface pressure and total precipitation. The data aggregated on a daily scale and spanning three decades was selected for this study. We have used the following architectures of neural network algorithms: U-Net architecture modified for regression representing convolutional neural networks and Long Short-Term Memory (LSTM) architecture representing the recurrent neural networks. Various settings of each architecture, such as the number of layers, optimizers and initialization, are validated to assess their performance on rainfall estimation. The developed rainfall estimation models were validated and evaluated using rigorous statistical metrics, such as root mean square error (RMSE) and coefficient of determination (R-squared). The results of this research are expected to provide valuable insights for local governments, farmers, and other stakeholders in the northeastern states of India. Moreover, the study's methodology can be extended to other regions facing similar climate challenges, thus contributing to advancements in the field of rainfall estimation and climate modelling.

How to cite: Handur-Kulkarni, A., Mehta, S., Ghatalia, A., and Anilkumar, R.: Comparing the Role of Spatially and Temporally capable Deep Learning Architectures in Rainfall Estimation: A Case Study over North East India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19394, https://doi.org/10.5194/egusphere-egu24-19394, 2024.

EGU24-19531 | PICO | ESSI1.3

Gradient-Based Optimisers Versus Genetic Algorithms in Deep Learning Architectures: A Case Study on Rainfall Estimation Over Complex Terrain 

Yash Bhisikar, Nirmal Govindaraj, Venkatavihan Devaki, and Ritu Anilkumar

Gradient-Based Optimisers Versus Genetic Algorithms in Deep Learning Architectures:

A Case Study on Rainfall Estimation Over Complex Terrain

 

Yash Bhisikar1*, Nirmal Govindaraj1*, Venkatavihan Devaki2*, Ritu Anilkumar3

1Birla Institute of Technology And Science, Pilani, K K Birla Goa Campus 

2Birla Institute of Technology And Science, Pilani, Pilani Campus 

3North Eastern Space Applications Centre, Department of Space, Umiam

E-mail: f20210483@goa.bits-pilani.ac.in

* Authors have contributed equally to this study.

Rainfall is a crucial factor that affects planning processes at various scales, ranging from agricultural activities at the village or residence level to governmental initiatives in the domains of water resource management, disaster preparedness, and infrastructural planning. Thus, a reliable estimate of rainfall and a systematic assessment of variations in rainfall patterns is the need of the hour. Recently, several studies have attempted to predict rainfall over various locations using deep learning architectures, including but not limited to artificial neural networks, convolutional neural networks, recurrent neural networks, or a combination of these. However, a major challenge in the estimation of rainfall is the chaotic nature of rainfall, especially the interplay of spatio-temporal components over orographically complex terrain. For complex computer vision challenges, studies have suggested that population search-driven optimisation techniques such as genetic algorithms may be used in the optimisation as an alternative to traditional gradient-based techniques such as Adam, Adadelta and SGD. Through this study, we aim to extend this hypothesis to the case of rainfall estimation. We integrate the use of population search-based techniques, namely genetic algorithms, to optimise a convolutional neural network architecture built using PyTorch. We have chosen the study area of North-East India for this study as it receives significant monsoon rainfall and is impacted by the undulating terrain that adds complexity to the rainfall estimation. We have used 30 years of rainfall data from the ERA5 Land daily reanalysis dataset with a spatial resolution of 11,132 m for the months of June, July, August and September. Additionally, datasets of the following meteorological variables that can impact rainfall were utilised as input features: dew point temperature, skin temperature, net incoming short-wave radiation received at the surface, wind components and surface pressure. All the datasets are aggregated to daily time steps. Several configurations of the U-Net architecture, such as the number of hidden layers, initialisation techniques and optimisation algorithms, have been used to identify the best configuration in the estimation of rainfall for North-East India. Genetic algorithms were used in initialisation and optimisation to assess the ability of population search heuristics using the PyGAD library. The developed rainfall prediction models were validated at different time steps (0-day, 1-day, 2-day and 3-day latency) on a 7:1:2 train, validation, test dataset split for evaluation metrics such as root mean square error (RMSE) and coefficient of determination (R-squared). The evaluation was performed on a pixel-by-pixel basis as well as an image-by-image basis in order to take magnitude and spatial correlations into consideration. Our study emphasises the importance of considering alternate optimising functions and hyperparameter tuning approaches for complex earth observation challenges such as rainfall prediction.

How to cite: Bhisikar, Y., Govindaraj, N., Devaki, V., and Anilkumar, R.: Gradient-Based Optimisers Versus Genetic Algorithms in Deep Learning Architectures: A Case Study on Rainfall Estimation Over Complex Terrain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19531, https://doi.org/10.5194/egusphere-egu24-19531, 2024.

EGU24-20025 | ECS | PICO | ESSI1.3

Vineyard detection from multitemporal Sentinel-2 images with a Transformer model 

Weiying Zhao, Alexey Unagaev, and Natalia Efremova

This study introduces an innovative method for vineyard detection by integrating advanced machine learning techniques with high-resolution satellite imagery, particularly focusing on the use of preprocessed multitemporal Sentinel-2 images combined with a Transformer-based model.

We collected a series of Sentinel-2 images over an entire seasonal cycle from eight distinct locations in Oregon, United States, all within similar climatic zones. The training and validation database sizes are 403612 and 100903, respectively. To reduce the cloud effect, we used the monthly median band values derived from initially cloud-filtered images.  The multispectral (12 bands) and multiscale (10m, 20m, and 60m) time series were effective in capturing both the phenological patterns of the land covers and the overall management activities.

The Transformer model, primarily recognized for its successes in natural language processing tasks, was adapted for our time series identification scenario. Then, we transferred the object detection into a binary classification task. Our findings demonstrate that the Transformer model significantly surpasses traditional 1D convolutional neural networks (CNNs) in detecting vineyards across 16 new areas within similar climatic zones, boasting an impressive accuracy of 87.77% and an F1 score of 0.876. In the majority of these new test locations, the accuracy exceeded 92%, except for two areas that experienced significant cloud interference and presented numerous missing values in their time series data. This model proved its capability to differentiate between land covers with similar characteristics during various stages of growth throughout the season. Compared with attention LSTM and BiLSTM, it has less trainable parameters when getting a similar performance. The model was especially adept at handling temporal variations, elucidating the dynamic changes in vineyard phenology over time. This research underscores the potential of combining advanced machine learning techniques with high-resolution satellite imagery for crop type detection and suggests broader applications in land cover classification tasks. Future research will pay more attention to the missing value problem.

How to cite: Zhao, W., Unagaev, A., and Efremova, N.: Vineyard detection from multitemporal Sentinel-2 images with a Transformer model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20025, https://doi.org/10.5194/egusphere-egu24-20025, 2024.

EGU24-22153 | PICO | ESSI1.3

Spatial cross-validation of wheat yield estimations using remote sensing and machine learning 

Keltoum Khechba, Mariana Belgiu, Ahmed Laamrani, Qi Dong, Alfred Stein, and Abdelghani Chehbouni

Integration of Machine Learning (ML) with remote sensing data has been successfully used to create detailed agricultural yield maps at both local and global scales. Despite this advancement, a critical issue often overlooked is the presence of spatial autocorrelation in geospatial data used for training and validating ML models. Usually random cross-validation (CV) methods are employed that fail to account for this aspect. This study aimed to assess wheat yield estimations using both random and spatial CV. In contrast to random CV where the data is split randomly, spatial CV involves splitting the data based on spatial locations, to ensure that spatially close data points are grouped together, either entirely in the training or in the test set, but not both. Conducted in Northern Morocco during the 2020-2021 agricultural season, our research uses Sentinel 1 and Sentinel 2 satellite images as input variables as well as 1329 field data locations to estimate wheat yield. Three ML models were employed: Random Forest, XGBoost, and Multiple Linear Regression. Spatial CV was employed across varying spatial scales. The province represents predefined administrative division, while grid2 and grid1 are equally sized spatial blocks, with a spatial resolution of 20x20km and 10x10 km respectively. Our findings show that when estimating yield with Random CV, all models achieve higher accuracies (R² = 0.58 and RMSE = 840 kg ha-1 for the XGBoost model) as compared to the performance reported when using spatial CV. The10x10 km spatial CV led to the highest R² value equal to 0.23 and an RMSE value equal to 1140 kg ha-1 for the XGBoost model, followed by the 20x20 km grid-based strategy (R² = 0.11 and RMSE = 1227 kg ha-1 for the XGBoost model). Province-based spatial CV resulted in the lowest accuracy with an R² value equal to 0.032 and an RMSE value of 1282 kg ha-1. These results confirm that spatial CV is essential in preventing overoptimistic model performance. The study further highlights the importance of selecting an appropriate CV method to ensure realistic and reliable results in wheat yield predictions as increased accuracy can deviate from real-world conditions due to the effects of spatial autocorrelation.  

How to cite: Khechba, K., Belgiu, M., Laamrani, A., Dong, Q., Stein, A., and Chehbouni, A.: Spatial cross-validation of wheat yield estimations using remote sensing and machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22153, https://doi.org/10.5194/egusphere-egu24-22153, 2024.

The aim of this study conducted in Tavira - Portugal, is to show the ability to determine depths without relying on in-situ data. To achieve this goal, a model previously trained with depth data and multispectral images from 2018 was used. This model enables depth determination for any period, providing multispectral images.

For this study, Cube satellite images from the PlanetScope constellation with a spatial resolution of 3.0 m and four spectral bands (blue, green, red, and near-infrared) were used. Corrections due to tidal height were obtained through modeled data provided by the Portuguese Hydrographic Institute for the tide gauge of Faro – Olhão. In-situ depths were obtained through the Digital Elevation Model of Reference (MDER) from the Coastal Monitoring Program of Continental Portugal of the Portuguese Environmental Agency.

The model used to determine depths was previously obtained using the Random Forest (RF) algorithm, trained with a set of reflectances from 15 images acquired between August and October 2018 by the PlanetScope constellation, and a set of depths from the MDER, referring to October 2018.

This RF model allowed the depth determination for a set of 7 images from the same constellation, acquired between August and October 2019. The results were corrected for tidal height to obtain all values in relation to the Hydrographic Zero reference. The Savitzky-Golay filter was applied to smooth the results, and then the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm was applied to eliminate outliers. Finally, the median depth value was determined, resulting in a bathymetric surface morphologically similar to the MDER (2019).

This final surface was compared with the 2019 MDER through differences between the two surfaces (residuals) and the respective statistics were calculated (mean, median, standard deviation, and histogram). A vertical profile between 0.0 and 10.0 meters of depth was also generated. The statistical results of the differences reveal a median of 0.5 meters, a mean of 0.7 meters, and a standard deviation of 1.3 meters. The histogram of differences between the two surfaces follows a normal distribution, with its center located at the median value, which is offset from zero.

The results obtained in this study are promising for obtaining depths in coastal regions through multispectral images without the need for in-situ data. However, we are aware that improving the current model is important to reduce the median and standard deviation of the differences between the determined depth and the reference. Enhancing the model will lead to more accurate results, enabling the determination of seasonal variations and changes caused by extreme events or climate alterations without in-situ data.

How to cite: Santos, R. and Quartau, R.: Predicting bathymetry in shallow regions using a machine learning model and a time series of PlanetScope images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22165, https://doi.org/10.5194/egusphere-egu24-22165, 2024.

GI4 – Earth Observation systems & instrumentation

EGU24-3097 | Posters on site | GI4.1

Latent Heat Flux by Raman Lidar and Wind Lidar system during Walineas Campaign. 

Donato Summa, Giuseppe D'amico, Ilaria Gandolfi, Noemi Franco, Marco Di Paolantonio, Marco Rosoldi, Benedetto De Rosa, and Paolo Di Girolamo

The crucial parameter for characterizing the energy exchange between the Earth's surface and the atmosphere within the Atmospheric Boundary Layer (ABL) is the latent heat flux (LHF). This represents the speed at which energy stored as latent heat in water vapor molecules is transported into the ABL due to the turbulent convective movement of the air.

The integration of both lidar measurements provides a comprehensive perspective on atmospheric processes related to latent heat flux, significantly contributing to improving the understanding of the water cycle and associated meteorological phenomena. During the WaLiNeAs campaign (Water vapor Lidar Network Assimilation), a consortium of French, German, Italian, and Spanish research groups deployed a network of 6 autonomous Water Vapor (WV) Lidars in the French territory. This network delivers measurements with high vertical resolution and accuracy throughout the Western Mediterranean, starting in the fall of 2022 and addressing critical gaps in water vapor observations in the lower troposphere from current operational networks and satellites.

As part of the WaLiNeAs initiative, a Lidar system developed by the University of Basilicata was positioned near a Wind Lidar with the goal of collecting measurements of heat flux and turbulent kinetic energy (TKE). These two systems operated continuously for three months starting from the end of September 2022, covering the most favorable period in southern France and acquiring high-resolution measurements (10 seconds, 30 meters).

Acknowledgment

The authors acknowledge Next Generation EU Mission 4 “Education and Research” - Component 2: “From research to business” - Investment 3.1: “Fund for the realization of an integrated system of research and innovation infrastructures” - Project IR0000032 – ITINERIS.

This work was supported by the Agence Nationale de la Recherche (WaLiNeAs, Grant ANR-20-CE04-0001). This research was also funded by the Italian Ministry for Education, University and Research (grants STAC-UP and FISR2019-CONCERNING) and the Italian Space Agency (grants As-ATLAS and CALIGOLA).

References

[1] Flamant, C., Chazette, P., Caumont, O. et al. (2021) A network of water vapor Raman lidars for improving heavy precipitation forecasting in  southern      France: introducing the WaLiNeAs initiative. Bull. of Atmos. Sci.& Technol2, 10.

[2] Kiemle, W. A. Brewer, G. Ehret, R. M. Hardesty, A. Fix, C. Senff,  M. Wirtg, G. Poberaj and M. A. Lemone. (2007) Latent Heat Flux Profiles from Collocated Airborne Water Vapor and Wind Lidars during IHOP_2002. American Meteorological Society pp:627-639.

[3] Behrendt , V. Wulfmeyer1 , C. Senff , S. K. Muppa, F. Späth , D. Lange , N. Kalthoff , and A. Wieser. (2020). Observation of sensible and latent heat flux profiles with lidar Atmos. Meas. Tech., 13, 3221–3233.

 

How to cite: Summa, D., D'amico, G., Gandolfi, I., Franco, N., Di Paolantonio, M., Rosoldi, M., De Rosa, B., and Di Girolamo, P.: Latent Heat Flux by Raman Lidar and Wind Lidar system during Walineas Campaign., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3097, https://doi.org/10.5194/egusphere-egu24-3097, 2024.

EGU24-4039 | Posters on site | GI4.1

An overview of the Cloud and Aerosol Lidar for Global Scale Observations of the Ocean-Land-Atmosphere System 

Paolo Di Girolamo, Noemi Franco, Davide Dionisi, Marco Di Paolantonio, Donato Summa, Simone Lolli, Lucia Mona, Rosalia Santoleri, Simona Zoffoli, Francesco Tataranni, Tiziana Scopa, Francesco Longo, Valentina Sacchieri, Alessandro Perna, Alberto Cosentino, Yongxiang Hu, Michael J. Behrenfeld, Chris A. Hostetler, Stephen R. Hall, and Charles R. Trepte

The Cloud and Aerosol Lidar for Global Scale Observations of the Ocean-Land-Atmosphere System (CALIGOLA) is an advanced multi-purpose space lidar mission with a focus on atmospheric and oceanic observation aimed at characterizing the Ocean-Earth-Atmosphere system and the mutual interactions within it. This mission has been conceived by the Italian Space Agency (ASI) with the aim to provide the international atmospheric and ocean science communities with an unprecedented dataset of geophysical parameters capable to increase scientific knowledge in the areas of atmospheric, aquatic, terrestrial, cryospheric and hydrological sciences. The mission is planned to be launched in the time frame 2030-2031, with an expected lifetime of 3-5.

Exploiting the three Nd:YAG laser emissions at 354.7, 532 and 1064 nm and the elastic (Rayleigh-Mie), depolarized and Raman lidar echoes from atmospheric constituents, CALIGOLA will carry out 3λ profile measurements of the particle backscatter coefficient and depolarization ratio and 1-2λ (354.7 and 532 nm) profile measurements of the particle extinction coefficient from aerosols and clouds. These measurements allow for aerosol typing and the determination of aerosol size and microphysical properties. Furthermore, measurements of the elastic and depolarized backscattered echoes from the sea surface and the underlying layers will allow characterizing the optical properties of the marine surface (ocean color) and the suspended particulate matter in terms of oceanic particulate backscattering coefficient, while diffuse attenuation for downwelling irradiance at 1-2λ will be determined from the H2O roto-vibrational Raman signals. These measurements will allow characterizing phytoplankton seasonal and inter-annual dynamics. Additionally, fluorescent scattering measurements at 1-3λ (450, 685 and 735 nm) from marine chlorophyll and atmospheric aerosols will be exploited to characterize ocean primary production and for atmospheric aerosol typing, respectively. CALIGOLA will also allow for accurate measurements of the small-scale variability of the earth's surface elevation, primarily associated with variations in the ice and snow, terrain, vegetation and forest canopy height.

The space mission CALIGOLA is explicitly included in the on-going ASI 2021-2023 Activity Plan. A Phase-A study focusing on the technological feasibility of the major sub-systems is on-going, commissioned by ASI to Leonardo S.p.A. (LDO). Scientific studies in support of the mission are also on-going, with the University of Basilicata (UNIBAS) being the leading scientific institution. In September 2023 NASA-LARC initiated a pre-formulation study to assess the feasibility of a possible contribution to CALIGOLA based on the development of the receiver detection chain and data down link capabilities. In September 2024 NASA will decide if proceed or not with the cooperation.

This conference contribution aims at illustrating the different atmospheric and ocean sciences’ objectives and a preliminary assessment of the mission observational requirements in terms of observable quantities, their vertical/horizontal resolution and precision/accuracy. The contribution also aims at illustrating the technical and technological solutions identified in the design of the instrument during the pre-feasibility and feasibility studies carried out by LDO, in cooperation with UNIBAS and other Italian research institutions. Expected system performance in a variety of environmental conditions will be provided based on the application of an end-to-end simulator developed at UNIBAS.

How to cite: Di Girolamo, P., Franco, N., Dionisi, D., Di Paolantonio, M., Summa, D., Lolli, S., Mona, L., Santoleri, R., Zoffoli, S., Tataranni, F., Scopa, T., Longo, F., Sacchieri, V., Perna, A., Cosentino, A., Hu, Y., Behrenfeld, M. J., Hostetler, C. A., Hall, S. R., and Trepte, C. R.: An overview of the Cloud and Aerosol Lidar for Global Scale Observations of the Ocean-Land-Atmosphere System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4039, https://doi.org/10.5194/egusphere-egu24-4039, 2024.

EGU24-8596 | Posters on site | GI4.1

Spaceborne Water Vapor DIAL: Has the time come now? 

Martin Wirth, Silke Groß, and Andreas Fix

Water vapor is the key trace gas component of the air and involved in virtually all relevant atmospheric processes. To know the vertical profile with decent resolution is crucial in all cases. For example, there are several regions of the atmosphere where numerical weather prediction models show biases which are not understood. So, after aerosol/cloud and wind lidars have been very successfully applied within space missions, the natural next step would be the profiling of water vapor by a Differential Absorption Lidar (DIAL) from a satellite in a low Earth orbit. About 20 years ago the ESA EarthExplorer Proposal WALES went through phase A, but was not further selected due to the identified technological risks and the corresponding financial efforts. Thanks to the European spaceborne lidar missions Aeolus/2, EarthCare, and MERLIN now the major building blocks for a such water vapor DIAL have reached the necessary technological readiness to realize such a program within the financial limits of a typical Earth observation mission. We will review the benefits of water vapor profiling by lidar as compared to passive sensors for different applications and then present an updated system design based on the current European space lidar component pool. Finally, results from end-to-end performance simulations will be presented. This presentation is thought as an invitation to the community to think about possible applications of space-borne H2O-lidar data and the corresponding observational requirements.

How to cite: Wirth, M., Groß, S., and Fix, A.: Spaceborne Water Vapor DIAL: Has the time come now?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8596, https://doi.org/10.5194/egusphere-egu24-8596, 2024.

EGU24-9219 | ECS | Posters on site | GI4.1

Measurements of CO2 Profiles in the Lower Troposphere with the new Raman Lidar Channel of ARTHUS 

Moritz Schumacher, Diego Lange, Andreas Behrendt, and Volker Wulfmeyer

The variability of CO2 in the atmosphere is still not well understood. Key to improve this understanding are continuous measurements of the CO2 concentration over long periods of time as well as in different altitudes. At the “Land-Atmosphere Feedback Observatory” (LAFO) [1] of the University of Hohenheim, Stuttgart, Germany, we are operating the ground based Raman lidar system ARTHUS. ARTHUS stands for "Atmospheric Raman Temperature and HUmidity Sounder" [2]. This automatic system provides high resolution measurements up to the turbulent scale of temperature, water vapor mixing ratio as well as extinction and backscatter data continuously. But measuring CO2concentrations with Raman lidar is quite challenging because of its comparatively low concentrationresulting in an overall weak backscatter signal and thus a low signal-to-noise ratio. To investigate the capabilities of our system for capturing CO2 profiles, we developed and incorporated a new channel. For the measurements we utilize the 2ν2 CO2 Raman line, which is well separated from relevant Raman lines of other constituents of the atmosphere (e.g. O2). At the conference we will present and discuss the first results of the first measurements at the LAFO site between August and October 2023. Comparison of the measured with expected profiles show good agreement. The latter where obtained by appropriately scaling profiles of the water vapor mixing ratio channel of the same system. In the near future, we will add a scanning unit to the system. This will enable us to calibrate and compare the CO2 lidar data with in-situ instruments located at the ground. Furthermore, the identification and quantification of carbon sources and sinks along the surface will then be possible.

 

References:

[1] Späth, F., S. Morandage, A. Behrendt, T. Streck, and V. Wulfmeyer, 2021: The Land-Atmosphere Feedback Observatory (LAFO). EGU21-7693 (2021). DOI:10.5194/egusphere-egu21-7693

[2] Lange, D. et al.: Compact Operational Tropospheric Water Vapor and Temperature Raman Lidar with Turbulence Resolution. Geophys. Res. Lett. (2019). DOI:10.1029/2019GL085774

How to cite: Schumacher, M., Lange, D., Behrendt, A., and Wulfmeyer, V.: Measurements of CO2 Profiles in the Lower Troposphere with the new Raman Lidar Channel of ARTHUS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9219, https://doi.org/10.5194/egusphere-egu24-9219, 2024.

EGU24-10293 | Posters on site | GI4.1

Analyzing the Efficacy of Precipitation in Aerosol Clearance Using Lidar, Micro Rain Radar, and Disdrometer Observations. 

Simone Lolli, Jasper R. Lewis, Erica K. Dolinar, James R. Campbell, and Ellsworth J. Welton

We quantitatively assess the aerosol removal of aerosols by precipitation, using lidar, micro rain radar, and disdrometer observations. Precipitation acts as an effective means of cleansing the atmosphere of aerosols through several processes. Fine and coarse aerosol particles are each subject to below-cloud scavenging, characterized by distinct coefficients for each particle category. Data from lidar, micro rain radar, and disdrometers have revealed aerosol depletion at the melting layer, where the wet scavenging coefficient (WSC) is influenced by the rainfall intensity and the interaction efficacy between raindrops and aerosol particles. The synergy of cloud dynamics and precipitation is pivotal in aerosol removal, with lidar data indicating the influence of evaporation and the modulation of latent heat in the process. Precipitation is found to markedly expedite the clearance of aerosols from the air, accounting for up to 80% of the total removal under specific scenarios. This investigation underscores the vital function of precipitation in the dynamics of atmospheric aerosols and sheds light on the consequential environmental and climate-related impacts.

How to cite: Lolli, S., Lewis, J. R., Dolinar, E. K., Campbell, J. R., and Welton, E. J.: Analyzing the Efficacy of Precipitation in Aerosol Clearance Using Lidar, Micro Rain Radar, and Disdrometer Observations., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10293, https://doi.org/10.5194/egusphere-egu24-10293, 2024.

EGU24-11936 | Posters on site | GI4.1

Lidars at University of Hohenheim 

Andreas Behrendt, Diego Lange, Oliver Branch, Syed Abbas, Moritz Schumacher, Osama Alnayef, and Volker Wulfmeyer

In this contribution, we will give an update of recent lidar activities at University of Hohenheim. Two of the lidars have been developed at our institute: The scanning water vapor differential absorption lidar (WVDIAL) and the Raman lidar ARTHUS (Atmospheric Raman Temperature and HUmidity Sounder). In addition, two scanning Doppler lidars are used since a few years while a third one will be added soon. All these lidars are located at LAFO (Land Atmospheric Feedback Observatory; Branch et al., this conference). Here, also a scanning Doppler cloud radar, meteorological towers, Eddy-covariance stations, surface and sub-surface sensors are collecting routinely data. These data are combined with detailed vegetation analyses.

The WVDIAL is embedded into large truck. Its transmitter consists of an injection-seeded titanium-sapphire laser that is pumped with a diode-pumped Nd:YAG laser. The maximum laser power is 10 W at 200 Hz. This laser power can be used for vertical measurements for which the laser beam is directly emitted vertically into the atmosphere. For scanning measurements, 2 W laser power are transmitted with a fiber into the atmosphere after being expanded with a small telescope. The atmospheric backscatter signals are collected with a 80-cm telescope offering high detection efficiency. The resolution of the stored raw data is up to several Hz and a few meters. The typical resolution of the data products is 1 s and 30 m.

While the large WVDIAL needs supporting personal for its operation, our second lidar ARTHUS is an automated instrument with continuous operation (Lange et al., 2019; Wulfmeyer and Behrendt, 2022). This eyesafe Raman lidar uses a diode-pumped Nd:YAG laser as transmitter. Only the third-harmonic radiation at 355 nm is – after beam expansion – transmitted into the atmosphere. The laser power is about 15 W at 200 Hz repetition rate. The receiving telescope has a diameter of 40 cm. 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 raw data is stored with a resolution of 7.5 m and typically 10 s (while higher temporal resolution is possible). 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. Primary data products are temperature, water vapor mixing ratio, particle backscatter coefficient and particle extinction coefficient. The high resolution allows studies of boundary layer turbulence (Behrendt et al, 2015) and - in combination with the vertical pointing Doppler lidar - sensible and latent heat fluxes (Behrendt et al, 2020). Similar lidars like ARTHUS are meanwhile also available at the company Purple Pulse Lidar Systems (www.purplepulselidar.com). In 2023, a CO2 channel was implemented into ARTHUS allowing now in addition also measurements of the CO2 mixing ratio (Schumann et al., this conference).

 

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., Branch, O., Abbas, S., Schumacher, M., Alnayef, O., and Wulfmeyer, V.: Lidars at University of Hohenheim, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11936, https://doi.org/10.5194/egusphere-egu24-11936, 2024.

EGU24-14294 | ECS | Posters on site | GI4.1

Study of the Relationship Between Surface Fluxes and Convective Boundary Layer Dynamics with Lidars.  

Syed Saqlain Abbas, Oliver Branch, Andreas Behrendt, Diego Lange, and Volker Wulfmeyer

The atmospheric boundary layer (ABL) is the lowest part of atmosphere. It is directly influenced by the Earth's surface. To understand the influence of surface fluxes on ABL turbulence processes during daytime in convective conditions, the use of lidars and Eddy covariance stations are essential. Such better understanding will then help to improve weather and climate models. The Land-Atmosphere Feedback Observatory (LAFO) at the University of Hohenheim, Stuttgart, Germany is a designated study site for agricultural experiments equipped with various sensors to analyze state variables from the soil to the lower free troposphere (Späth et al., 2023). To investigate boundary layer turbulence, two Doppler lidars, a Doppler Cloud Radar, the lidar Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) (Lange et al., 2019), and two Eddy covariance stations are deployed at LAFO to capture high-resolution data. Two Doppler lidars are continuously operated, one in vertical pointing mode and the second in six-beam scanning mode (Bonin et al., 2017) to measure high spatial and temporal resolution vertical and horizontal wind data. The turbulent surface fluxes significantly impact the ABL exchange processes. Therefore, it is very interesting to integrate the continuous high temporal resolution measurements of Eddy covariance sensors with lidars measurement. The key turbulent variables are retrieved from high frequency vertical wind data. These turbulence statistics are transversal temporal autocovariance functions, its coefficients in the inertial subrange using appropriate fit lags, atmospheric vertical wind variance, integral time scale, turbulence kinetic energy dissipation (Wulfmeyer et al., 2023), cloud base height and ABL depth. We have used two methods to determine the ABL depth. The first retrieval method is based on fuzzy logic (Bonin et al., 2018) which uses atmospheric vertical velocity variance profiles. The second method employs Haar wavelet transform (Pal et al., 2010) on water vapor mixing ratio and potential temperature profiles.

In this contribution, we are presenting our analyses on correlation statistics between surface fluxes and ABL depth and influence of these surface fluxes on turbulence variables covering different daytime weather conditions from June to August in 2021.

Bonin et al, 2017,  https://doi.org/10.5194/amt-10-3021-2017

Bonin et al, 2018,  https://doi.org/10.1175/JTECH-D-17-0159.1

Lange et al, 2019, https://doi.org/10.5194/egusphere-egu22-3275

Pal et al, 2010, https://doi.org/10.5194/angeo-28-825-2010

Späth et al, 2023, https://doi.org/10.5194/gi-12-25-2023

Wulfmeyer et al, 2023, https://doi.org/10.5194/amt-2023-183

How to cite: Abbas, S. S., Branch, O., Behrendt, A., Lange, D., and Wulfmeyer, V.: Study of the Relationship Between Surface Fluxes and Convective Boundary Layer Dynamics with Lidars. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14294, https://doi.org/10.5194/egusphere-egu24-14294, 2024.

EGU24-15570 | Posters on site | GI4.1

Data assimilation of temperature and water-vapor mixing-ratio lidar profiles in WRF 

Diego Lange Vega and the WaLiNeAs (Water vapor Lidar Network Assimilation) Team

The lack of accurate observations affects the initial conditions of numerical weather prediction (NWP) models resulting in suboptimal forecasts. The assimilation of temperature and moisture profiles obtained from active remote-sensing lidar systems offers great potential for improving the predictive skills of NWP models (Thundathil et al., 2021, Bauer et al. 2023). Advanced data assimilation (DA) techniques, with suitable observational forward operators, enable the model to make use of such observations efficiently.

New lidar systems provide temperature and humidity observations with high accuracy and resolution, which is highly beneficial for DA. The high accuracy avoids the need for a challenging bias correction of the data. It also simplifies operational use and minimizes the latency of the lidar data available for DA.

In this regard, we make use of lidar observations to investigate the extent to which the assimilation of these data through advanced DA systems improves the analyses and corresponding forecasts.

Our automated thermodynamic profiler based on the Raman lidar technique, the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) (Lange et al. 2019) was deployed in the framework of the WaLiNeAs (Water vapor Lidar Network Assimilation) (Flamant et al. 2021) initiative at the west coast of Corsica between 15 September and 10 December 2022. The participation of ARTHUS was possible due to a project funded by the German Research Foundation (DFG).

Together with ARTHUS, a network of several other autonomous water-vapor lidars was deployed for providing more thermodynamic data across the Western Mediterranean. We expect that this network during its operation closed critical gaps present in lower tropospheric observations of current operational networks and satellite observations.

We will present the first results of the impact of high-resolution temperature and water vapour mixing ratio lidar profiles in our data assimilation studies on heavy precipitation events, using  the WRF 3DVAR-ETKF approach on the kilometer-scale.

How to cite: Lange Vega, D. and the WaLiNeAs (Water vapor Lidar Network Assimilation) Team: Data assimilation of temperature and water-vapor mixing-ratio lidar profiles in WRF, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15570, https://doi.org/10.5194/egusphere-egu24-15570, 2024.

EGU24-16371 | ECS | Posters on site | GI4.1

Investigation of Cloud Formation in the Atmospheric Boundary Layer with a Synergy of Radar and Lidar  

Osama Alnayef, Andreas Behrendt, Diego Lange, Oliver Branch, and Volker Wulfmeyer

This research focuses on investigating the influence of dynamics and thermodynamics on cloud formation. The properties of the particles in dependence on relative humidity in the atmospheric boundary layer during cloud formation are investigated. For this, we use the synergy of Raman and Doppler lidars as well as of cloud radar operated during the Land-Atmosphere Feedback Experiment (LAFE) (see https://www.arm.gov/research/campaigns/sgp2017lafe). 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.

The particle backscatter coefficients are measured with Raman lidar, vertical wind velocity with Doppler lidar, and Doppler cloud radar. This instrument combination is also particularly advantageous for investigating the vertical structure of clouds, providing details about cloud height and thickness.

In consequence, the combined measurements allow detailed insights into the relative humidity dependencies on the growth of particles to investigate the influence of dynamics and thermodynamics on cloud formation.

How to cite: Alnayef, O., Behrendt, A., Lange, D., Branch, O., and Wulfmeyer, V.: Investigation of Cloud Formation in the Atmospheric Boundary Layer with a Synergy of Radar and Lidar , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16371, https://doi.org/10.5194/egusphere-egu24-16371, 2024.

EGU24-18096 | Posters on site | GI4.1

A New Land-Atmosphere Feedback Observatory (LAFO) 

Oliver Branch, Andreas Behrendt, Diego Lange, Syed Abbas, Moritz Schumacher, Thilo Streck, and Volker Wulfmeyer

Studies of land-atmosphere (L-A) feedbacks are essential for understanding the Earth system. These feedbacks are the result of an interaction of processes related to exchanges of momentum, energy, and mass in the soil-vegetation-surface layer (SL)-atmospheric boundary layer (ABL) continuum. Quantification of feedbacks are often made using L-A feedback metrics. Inaccurate representation/parameterization of feedbacks are a weakness of current weather models, and their improvement will thus contribute to better simulations over all spatiotemporal scales. Improving feedback representation requires simultaneous measurements in all L-A compartments using a synergy of in-situ and active remote sensing instruments. To that end, a new Land-Atmosphere Feedback Observatory (LAFO) was established at the University of Hohenheim, Stuttgart, Germany funded by the Carl Zeiss Foundation. It was developed as a prototype for a future network of GEWEX LAFOs (GLAFOs), proposed by the Global Energy and Water Exchanges (GEWEX) program and GEWEX Global Land/Atmosphere System Study (GLASS) panel (Wulfmeyer et al. 2020). The main goals are to:

1) investigate the diurnal cycle and statistics of ABL temperature, humidity and wind profiles,

2) characterize L-A feedback by suitable metrics.

3) improve parameterizations of vegetation, surface and ABL fluxes,

4) verify mesoscale and turbulence permitting models,

LAFO brings together a sensor synergy with fine spatiotemporal resolution. An extended set of soil physical, plant dynamic as well as meteorological variables throughout the ABL are measured, focusing on evapotranspiration and other exchanges over agricultural landscapes. The LAFO observations with current instruments are continuously archived, according to FAIR data principles (Findable, Accessible, Interoperable, Reusable) and are complemented by additional field campaign measurements.

The first key component of the current LAFO sensor synergy consists of four 3D scanning lidar systems: A scanning water vapor Differential Absorption Lidar (DIAL, Muppa et al. 2016, Späth et al. 2016) and the Atmospheric Rotational-Raman Temperature and Humidity Sounder (ARTHUS, Lange et al. 2019), both developed at the Institute of Physics and Meteorology. Both these systems are unique and provide water vapor and temperature profiles from the surface layer to the free troposphere with fine resolution down to turbulence scales (Behrendt et al. 2015, Wulfmeyer et al. 2015). These lidars are complemented by a scanning Doppler cloud radar and two Doppler lidars for measuring horizontal and vertical wind profiles and turbulent fluctuations. This combination allows determination of sensible and latent heat flux profiles. The second key component is a soil moisture and temperature sensor network distributed over agricultural land and two 10-m towers, measuring turbulent fluxes at two heights.

LAFO will soon form part of a new Research Unit, funded by the German Research Foundation (DFG), called the Land-Atmosphere-Feedback-Initiative (LAFI) which begins in 2024, and incorporates novel crop, hydrology and atmospheric instruments, operated by several research partners within Germany. Here, we present measurement examples from the LAFO and show how these can be used to reach our research goals.

 

References

Wulfmeyer et al. 2020, GEWEX Quarterly Vol. 30, No. 1.

Behrendt et al. 2015, doi:10.5194/acp-15-5485-2015

Wulfmeyer et al. 2015, doi:10.1002/2014RG000476

Muppa et al. 2016, doi:10.1007/s10546-015-0078-9

Späth et al. 2016, doi:10.5194/amt-9-1701-2016

Lange et al. 2019, doi:10.1029/2019GL085774

How to cite: Branch, O., Behrendt, A., Lange, D., Abbas, S., Schumacher, M., Streck, T., and Wulfmeyer, V.: A New Land-Atmosphere Feedback Observatory (LAFO), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18096, https://doi.org/10.5194/egusphere-egu24-18096, 2024.

EGU24-20443 | Posters on site | GI4.1

Temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique 

Adolfo Comerón, José Alex Zenteno-Hernández, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo

The Raman lidar technique to measure atmospheric temperature profiles is based on the dependence on temperature of the intensity of the atmospheric N2 and O2 rotational Raman lines [1]. The technique requires very good stability of the laser wavelength, or frequent recalibrations, to avoid errors in the retrieved temperature produced by wavelength drifts.  Frequency doubled or tripled Nd:YAG lasers are usually employed to implement this technique. To achieve laser wavelength stability, injection-seeded lasers are used that transfer the wavelength stability of the seeder to the high-power laser [2]; this has also the consequence of narrowing the spectrum of the transmitted radiation. Temperature profiling using free-running lasers are also reported in the literature [3]. In this case wavelength stability must be obtained by keeping the laser operating conditions, and in particular the Nd:YAG rod temperature, very stable.

We have assessed the effects on the atmospheric temperature retrieval of the spectral width and temperature-induced wavelength drift of the 3rd harmonic of a free-running Nd:YAG laser. We have found that the spectral width has a negligible effect, as compared with the negligible spectral width of an injection-seeded laser, in the receiving filters that are part of the lidar. However, slight temperature-induced drifts on the central wavelength of the laser emitted spectrum entail small changes in the filter responses that impair the calibration and cause an uncertainty in the retrieved atmosphere temperature. We have estimated that to keep the retrieved temperature uncertainty below 1 K, the rod temperature must also to be kept within a ±1 K range. This is also the temperature stability that would be needed in the seeder of an injection seeded laser, as changes of temperature in the seeder will also cause wavelength drifts, hence uncontrolled biases in the atmosphere temperature measurements that would add to their uncertainty.   

[1] J. Cooney, Measurement of Atmospheric Temperature Profiles by Raman Backscatter, J Appl Meteorol Climatol. 11 (1972) 108–112. https://doi.org/10.1175/1520-0450(1972)011<0108:MOATPB>2.0.CO;2

[2] E. Hammann, A. Behrendt, F. Le Mounier, V. Wulfmeyer, Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD(CP)2 Observational Prototype Experiment, Atmos Chem Phys. 15 (2015) 2867–2881. https://doi.org/10.5194/acp-15-2867-2015.

[3] P. Di Girolamo, R. Marchese, D.N. Whiteman, B.B. Demoz, Rotational Raman Lidar measurements of atmospheric temperature in the UV, Geophys Res Lett. 31 (2004) 1–5. https://doi.org/10.1029/2003GL018342.

How to cite: Comerón, A., Zenteno-Hernández, J. A., Dios, F., Rodríguez-Gómez, A., Muñoz-Porcar, C., Sicard, M., Franco, N., Behrendt, A., and Di Girolamo, P.: Temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20443, https://doi.org/10.5194/egusphere-egu24-20443, 2024.

EGU24-2136 | Orals | GI4.3

Characterizing volcano deformation with DInSAR and GNSS data: the Sotará Volcano case study.  

Pablo Andres Euillades, Rosa Liliana Alpala, Leonardo Daniel Euillades, Jorge Alpala, Patricia Rosell, Yenni Roa, and Maurizio Battaglia

Sotará is a stratovolcano located at a remote region of the Southern Cordillera Central, in Colombia.  It presents signs of unrest since 2011, evidenced by increased seismicity and crustal deformation formerly detected by tilt-meters, and later by inflation measured at several GNSS permanent stations operated by the Colombian Geological Survey.  In this contribution we processed a set of ascending and descending SAR scenes acquired by the Sentinel-1 Mission by using the Small Baseline Subsets (SBAS) multi temporal DInSAR approach. The region is challenging for DInSAR processing using C-Band data, because it is covered by thick forest causing temporal decorrelation, except for the peaks higher than 3500 m above sea level. As deformation in the site is subtle, i.e. in the order of 2cm/year, atmospheric contamination can potentially hide the geophysical signal, leading to misleading conclusions. To decide if atmospheric corrections should be applied, we analyzed the correlation between the unwrapped phase and topography at each interferogram before and after applying atmospheric corrections provided by the Generic Atmospheric Correction Online Service for InSAR (GACOS). We search for data clustering in the plane correlation coefficient vs. time, which allow for detecting atmospheric stratification signals and evaluating the convenience of applying corrections or not. As a result, we decided not applying atmospheric corrections, and the deformation time series without them show a good agreement with the LOS projected GNSS ones. The results were used for estimating the source parameters through inverse modelling of ascending, descending SAR data and GNSS data using the DMODELS inversion software. We detect migration of the deformation source in the Sotará volcano towards shallower positions between 2011 and 2020. This work is an example of the capability of Sentinel-1 long data series for measuring subtle deformation even in though environment conditions.

How to cite: Euillades, P. A., Alpala, R. L., Euillades, L. D., Alpala, J., Rosell, P., Roa, Y., and Battaglia, M.: Characterizing volcano deformation with DInSAR and GNSS data: the Sotará Volcano case study. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2136, https://doi.org/10.5194/egusphere-egu24-2136, 2024.

EGU24-2885 | Orals | GI4.3

Rapid geomorphological changes on Stromboli volcano monitored by multi-platform remote sensing data 

Federico Di Traglia and the Stromboli 2022 research group

Steep-slopes volcanoes are susceptible to rapid geomorphological changes resulting from frequent eruptive activity, leading to non-equilibrium slope conditions. Stromboli, among other volcanoes, undergoes significant geomorphological alterations within short time frames (days to months) due to the accumulation of eruptive deposits, lava flows, and various processes including erosion, transportation, and re-sedimentation of volcaniclastic material. These changes are activated by mass-flows and exogenous phenomena, primarily the action of sea waves.

To comprehend the complex interplay between eruptive activity and the morphological response of the volcanic slope, a comprehensive investigation was conducted on events occurring at Stromboli between October and December 2022. This study employed a range of methodologies, including multiplatform remote sensing data, bathymetric surveys, geophysical-volcanological monitoring data, slope stability modeling, and direct observations. The remote sensing data encompassed satellite imagery, airborne single-pass Interferometric Synthetic Aperture Radar (InSAR) data, and Unmanned Aerial System (UAS) topographic data, complemented by ground-based and spaceborne InSAR displacement measurements, and very-high-resolution visible optical orthophotographs.

The primary objective of this study is to elucidate the mutual influences between eruptive activity and the morphological response of the volcano slope. Stromboli, with its persistent eruptive activity and dynamic, steep-slope volcanic flank, serves as an ideal case for such investigations.

The findings of this study illustrate how the inherent characteristics of the material comprising the slope (a heterogeneous accumulation of volcanic deposits and thin lava flows), along with the steep slope angle, constitute crucial factors affecting slope stability, particularly in coastal regions. The impact of overloading from lava flows and mass-flows, combined with undercutting effects resulting from erosion, especially along the coast, acts as triggers for mass-flow phenomena. The formation of mixtures between lava flows and volcaniclastic deposits plays a role in generating glowing mass-flows, attributing them to what is commonly known as deposit-derived Pyroclastic Density Currents (PDCs).

The findings aim to enhance our understanding of the mechanisms leading to the instability of volcaniclastic deposits, resulting from the interaction between erosive phenomena and the overloading of slopes by lava flows and mass-flows. The obtained results can be helpful in estimating the hazard induced by geomorphological processes in contexts like Stromboli, including the potential triggering of landslides and deposit-derived PDCs that may, in turn, lead to tsunamis.

How to cite: Di Traglia, F. and the Stromboli 2022 research group: Rapid geomorphological changes on Stromboli volcano monitored by multi-platform remote sensing data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2885, https://doi.org/10.5194/egusphere-egu24-2885, 2024.

Recent developments in InSAR (Interferometric Synthetic Aperture Radar) during the past decades allow to obtain high-precision, high-resolution ground deformation data with a broad spatio-temporal coverage. These large new datasets offer comprehensive insights into the deformation field and its time-evolution. Unfortunately, these new data sets cannot be fully exploited using the classical approaches for interpretation. In particular if we look for the most detailed estimation of the processes occurring in geologically active areas. Normally these classical approaches assume a priori geometries (e.g., point sources, disks, prolate or oblate spheroids, etc.) and nature of the source, and invert separately for the different sources when more than one is considered. Also, many time-series deformations in active regions are characterized by complicated patterns of ground deformation resulting from multiple natural and anthropogenic sources. In response to these challenges, we consider a new interpretation methodology which employs a combination of 3-D arbitrary sources for pressure and dislocations (including strike-slip, dip-slip, and tensile) simultaneously. This approach does not assume any a priori hypotheses regarding the deformation source’s number, nature, shape or location, providing deformation sources as 3D cell aggregations for which the inversion process automatically assigns a source type, magnitude values (MPa for pressure and cm for dislocations), position and orientation (angles of dislocation planes). The methodology inverts simultaneously ascending and descending LOS displacement time series data from InSAR, assuming the possible existence of offset values in the data sets. We show, as a way of example, a summary of the obtained results using last generation InSAR observation techniques and the new interpretation modeling to study the recent volcanic unrest and eruption in La Palma, Canary Islands, showing the obtained results.

How to cite: Fernandez, J. and Camacho, A. G.: New perspectives and challenges on geodetic volcano monitoring using InSAR and last generation interpretation tools, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3425, https://doi.org/10.5194/egusphere-egu24-3425, 2024.

EGU24-4759 | ECS | Orals | GI4.3

Monitoring Based on Differential Radar Interferometry (DInSAR) of the Activity of San Miguel Volcano, El Salvador 

Ana Mirian Villalobos, Cristiano Tolomei, Pablo Euillades, Christian Bignami, Leonardo Euillades, and Elisa Trasatti

The present study demonstrates the application of time series techniques with Differential Interferometry Radar (MT-InSAR) using images from the Sentinel-1 (C-band) and SAOCOM (L-band) radar sensors. The main objective was to identify and assess ground deformation at the San Miguel volcano, one of the most active volcanoes in El Salvador, for study and monitoring purposes. Various approaches were employed to enhance phase signal quality, including the use of Small Baseline Subset (SBAS) and Persistent Scatterers (PS) MT-InSAR methodologies, as well as atmospheric corrections using both the GACOS (Generic Atmospheric Correction Online Service for InSAR) data and an altitude-dependent linear model able to estimate and then remove the stratified component of the troposphere. Additionally, orbital corrections were performed, and the impact of Digital Elevation Model (DEM) accuracy and updates of the topography on phase, especially for SAOCOM L-band images, were evaluated.

The InSAR results revealed subsidence in the volcano crater showing a maximum rate of -25 mm per year, then we modeled the retrieved deformation patterns as a system of normal faults simulating two concentric craters. Moreover, limited deformation was detected in the western upper flank of the volcano during the 2023 period using SAOCOM data. We also observed that the volcano was strongly affected by atmospheric disturbances, although the performed corrections by using GACOS information did not yield to fully satisfactory results. In our work, the importance of using updated and accurate DEMs when processing L-band images has been emphasized.

Finally, our study suggests to continue using SAR images for monitoring San Miguel volcano activity, implementing longer time series with SAOCOM, and performing comparisons between SAR data acquired from both C- and L-band, possibly covering the same period, to gain a more comprehensive understanding of the deformation occurring at San Miguel volcano, and to improve the understanding of the volcanic activity.

How to cite: Villalobos, A. M., Tolomei, C., Euillades, P., Bignami, C., Euillades, L., and Trasatti, E.: Monitoring Based on Differential Radar Interferometry (DInSAR) of the Activity of San Miguel Volcano, El Salvador, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4759, https://doi.org/10.5194/egusphere-egu24-4759, 2024.

EGU24-6179 | ECS | Posters on site | GI4.3

Detailed Slip Distribution Model of the Türkiye-Syria 2023 Seismic Event exploiting SAOCOM-1, Sentinel-1 and ALOS-2 Satellite Imagery. 

Nikos Svigkas, Pasquale Striano, Simone Atzori, Manuela Bonano, Cristiano Tolomei, Nikolaos Vavlas, Anastasia Kiratzi, Francesco Casu, Christian Bignami, Claudio De Luca, Marco Polcari, Marianna Franzese, Andrea Antonioli, Michele Manunta, Fernando Monterroso, Yenni Lorena Belen Roa, and Riccardo Lanari

In 2023, seismic activity of considerable magnitude occurred along the Türkiye-Syria border, characterised by an Mw 7.8 earthquake on the 6th of February and was followed by an Mw 7.5 event, nine hours later. These earthquakes, which are the strongest recorded in recent years, resulted in over 50,000 casualties and are related with the activity of the East Anatolian Fault Zone —a 600 km-long plate boundary where the Arabian and Anatolian plates meet. To analyse these seismic events, we leveraged data from diverse satellites, including SAOCOM-1, Sentinel-1, and ALOS-2. Employing InSAR techniques, such as conventional interferometry and Pixel Offset tracking, we assessed surface deformations caused by the events. The high-resolution Synthetic Aperture Radar displacement results underwent non-linear and linear inversions, enabling the creation of detailed variable slip fault models. A meticulous multiscale sampling approach was applied, that facilitated a comprehensive examination of the tectonic structures triggering these events. The fault zone exhibited a pronounced left-lateral strike-slip character, with components of dip-slip movements observed in specific segments. Additionally, we capitalised the detailed slip models, to estimate the distribution of the intensity of ground motions in the affected region.

How to cite: Svigkas, N., Striano, P., Atzori, S., Bonano, M., Tolomei, C., Vavlas, N., Kiratzi, A., Casu, F., Bignami, C., De Luca, C., Polcari, M., Franzese, M., Antonioli, A., Manunta, M., Monterroso, F., Roa, Y. L. B., and Lanari, R.: Detailed Slip Distribution Model of the Türkiye-Syria 2023 Seismic Event exploiting SAOCOM-1, Sentinel-1 and ALOS-2 Satellite Imagery., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6179, https://doi.org/10.5194/egusphere-egu24-6179, 2024.

EGU24-6375 | Orals | GI4.3

Enabling the Forthcoming ROSE-L Sensor for Global Scale 3-D Earth Surface Deformation Retrieval Through a Two-Look ScanSAR Mode Configuration 

Stefano Perna, Francesco Longo, Simona Zoffoli, Malcolm Davidson, Lorenzo Iannini, and Riccardo Lanari

This work is focused on the possibility to enhance the observation capabilities of the forthcoming Synthetic Aperture Radar (SAR) ROSE-L (which stands for Radar Observation System for Europe at L-band) mission [1], [2], supported by the European Space Agency (ESA) as part of the Copernicus Expansion Programme.

Specifically, we propose a solution aimed at enabling the currently designed ROSE-L system for a two-look ScanSAR mode

configuration, without impairing key parameters, namely, the azimuth resolution and the range swath, of the original system, which is instead designed to basically achieve only a one-look ScanSAR mode configuration. In particular, following the analysis presented in [3], we propose to properly shape the radiated azimuth beam, doubling its width, without upsetting the original design of the ROSE-L radar antenna and taking advantage of the degrees of freedom offered by its current layout.

The proposed ROSE-L two-look ScanSAR mode configuration presents several valuable advantages in different applications, among which we focus on the possibility to retrieve, at global scale and without azimuth gaps, the North-South deformation components of the displacement phenomena occurred on the ground through the so called Burst overlap interferometry technique [4].

 

 

[1] M. Zimmermanns and C. Roemer, “Copernicus HPCM: ROSE-L SAR Instrument and Performance Overview,” in EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, Leipzig, Germany, 2022, pp. 1-6.

[2] M. Davidson and R. Furnell, “ROSE-L: Copernicus L-Band SAR Mission,” in IGARSS 2021; IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021, pp. 872-873.

[3] S. Perna, F. Longo, S. Zoffoli, M. Davidson, L. Lannini and R. Lanari, “ A conceptual performance study on a two-look ScanSAR mode configuration for the forthcoming ROSE-L mission,” in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2023.3344537.

[4] R. Grandin, E. Klein, M. Métois, C. Vigny, “Three-dimensional displacement field of the 2015 8.3 Illapel earthquake (Chile) from across- and along-track Sentinel-1 TOPS interferometry,” in Geophys.Res. Lett., vol. 43, pp. 2552-2561, 2016.

How to cite: Perna, S., Longo, F., Zoffoli, S., Davidson, M., Iannini, L., and Lanari, R.: Enabling the Forthcoming ROSE-L Sensor for Global Scale 3-D Earth Surface Deformation Retrieval Through a Two-Look ScanSAR Mode Configuration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6375, https://doi.org/10.5194/egusphere-egu24-6375, 2024.

EGU24-7688 | Orals | GI4.3

Investigating surface deformation with C-Band satellite interferometry in landslide complexes: insights from the Brienz/Brinzauls slope instability, Swiss Alps  

Andrea Manconi, Nina Jones, Simon Loew, Tazio Strozzi, Rafael Caduff, and Urs Wegmueller

The analysis of multi-temporal Synthetic Aperture Radar (SAR) datasets using specific algorithms, such as Persistent Scatterer Interferometry (PSI) or Small-Baseline Interferometry (SBAS), enables the generation of ground velocity maps and displacement time series, achieving sub-centimetric accuracies in ideal cases. These applications have significantly transformed the approach to investigating landslide processes and surface deformation measurements can now be obtained at relatively high spatial and temporal resolutions without the need for costly instrumentation. The current availability of regional, country-scale, and even continental-scale datasets has not only impacted research activities but has also influenced the daily practices of practitioners and civil protection strategies.

In mountainous areas, intrinsic limitations of satellite SAR imagery can hinder the nominal performance of PSI and SBAS results. In this contribution, we present a comprehensive analysis of C-Band SAR datasets from the European Space Agency (ESA) satellites ERS-1/2, Envisat ASAR, and Sentinel-1 spanning the period 1992-2020. Our goal is to reconstruct the multi-decadal spatial and temporal evolution of surface displacements at the Brienz/Brinzauls landslide complex, located in canton Graubünden, Switzerland. To achieve this, we analyzed approximately 1,000 SAR images using standard differential interferometry (DInSAR), multitemporal stacking, PSI, and SBAS approaches. The extensive network of Global Navigation Satellite System (GNSS) stations on the Brienz landslide complex allowed us to validate the deformation results.

Our analysis sheds light on the limitations that arise when relying on satellite radar measurements for the analysis and interpretation of complex landslide scenarios, particularly in cases of significant spatial and temporal heterogeneities in the deformation field. Satellite radar interferometry measurements are now routinely employed in local investigations, as well as in regional, national, and continental monitoring programs. Therefore, our results hold significant relevance for users seeking a comprehensive understanding of such datasets in complex scenarios.

How to cite: Manconi, A., Jones, N., Loew, S., Strozzi, T., Caduff, R., and Wegmueller, U.: Investigating surface deformation with C-Band satellite interferometry in landslide complexes: insights from the Brienz/Brinzauls slope instability, Swiss Alps , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7688, https://doi.org/10.5194/egusphere-egu24-7688, 2024.

EGU24-8542 | ECS | Posters on site | GI4.3

SNAP2DQuake: an implemented and automatic tool of ESA SNAP's Python module for DInSAR technique on ground deformation estimation from Sentinel-1 data 

Martina Occhipinti, Filippo Carboni, Shaila Amorini, Carlos López-Martinez, Nicola Paltriccia, and Massimiliano Porreca

Differential SAR Interferometry (DInSAR) is a largely exploited technique applicable to different case studies involving ground deformation on Earth. A key application is the detection of the effects promoted by large earthquakes, comprising detailed variations in ground deformations at large an local scales. Since one limit of this technique relies on the costs that may be present for the access of some satellitary imagery or software licenses for the data processing, this latter problematic can be solved with the adoption of an alternative processing performed via scripts. In this work, an automatic open-source implemented Python script (Snap2DQuake) based on the “snappy” module by SNAP software 9.0.8 (ESA) for the processing of Sentinel-1 images is presented. The main feature of the script is the reproduction of all the operators contained in SNAP software using the tools of “snappy”, in order to avoid some issues that can occurr using the software, and to build a complete, simple and automatic workflow to obtain LOS deformation maps and the derived Horizontal (E-W) and Vertical deformation maps. The automatization of the processing makes Snap2DQuake easy to use and suitable with basic users of programming. The proposed tool has been tested on two case studies referred two different tectonic contexts: the M6.4 Petrinja earthquake (Croatia, December 2020) and the Mw 5.7 to Mw 6.3 seismic sequence occured near Tyrnavós (Greece, March 2021). The output maps of Snap2DQuake, in agreement with field observations and previous work, furnish new insights insights into the deformation pattern linked to earthquakes, demonstrating the reliability of Snap2DQuake as an alternative tool for users working on different applications, even with basic coding skills. 

How to cite: Occhipinti, M., Carboni, F., Amorini, S., López-Martinez, C., Paltriccia, N., and Porreca, M.: SNAP2DQuake: an implemented and automatic tool of ESA SNAP's Python module for DInSAR technique on ground deformation estimation from Sentinel-1 data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8542, https://doi.org/10.5194/egusphere-egu24-8542, 2024.

EGU24-11867 | Orals | GI4.3

DInSAR analysis to detect local and regional coseismic ground deformation: insights from the 2016 central Italy earthquake 

Massimiliano Porreca, Filippo Carboni, Mariarosaria Manzo, Emanuela Valerio, Claudio De Luca, Martina Occhipinti, and Maurizio Ercoli

Over the past three decades, remote sensing techniques, particularly Differential Synthetic Aperture Radar Interferometry (DInSAR), have been used to investigate ground deformation phenomena accurately. The DInSAR method is extensively adopted for reconstructing the deformation pattern induced by earthquakes and for discerning the seismogenic fault, particularly in cases where field evidence are not comprehensive.

This study focuses on the application of DInSAR method to the 2016 Mw 6.5 mainshock occurred in the Apennines, central Italy. The earthquake produced a complex surface rupture distribution in a wide area which was meticulously examined by field geologists for a long time after the seismic sequence.

Here, we present detailed maps of the surface deformation pattern produced by the M. Vettore Fault System (VFS) during the October 2016 earthquakes, derived from ALOS-2 SAR data via DInSAR technique. On these maps, we trace a set of cross-sections to analyse the coseismic vertical displacement, essential to identify both surface fault ruptures and off-fault deformations. At a local scale, several coseismic ruptures are identified in agreement with previous field observations. On a larger scale, the VFS hanging-wall displays a long-wavelength upward-convex curvature, less evident toward the south and interrupted by the presence of an antithetic NE-dipping fault. The quantitative comparison between DInSAR- and field-derived vertical displacement highlights the reliability of the approach for constraining ruptures with vertical displacement up to 50-60 cm. The rapid detection of deformation patterns using DInSAR provides crucial information on activated fault segments, their distribution, and interaction shortly after seismic events. The proposed workflow, applicable globally with satellite SAR data, can support geological field surveys during seismic crises and offer rapid insights into surface ruptures essential for emergency management in not easily accessible areas.

How to cite: Porreca, M., Carboni, F., Manzo, M., Valerio, E., De Luca, C., Occhipinti, M., and Ercoli, M.: DInSAR analysis to detect local and regional coseismic ground deformation: insights from the 2016 central Italy earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11867, https://doi.org/10.5194/egusphere-egu24-11867, 2024.

EGU24-12268 | Orals | GI4.3

National programs, achievements and current perspectives at the Italian Space Agency to promote SAR missions, InSAR scientific research and downstream applications 

Deodato Tapete, Antonio Montuori, Maria Virelli, Alessandro Coletta, Francesco Longo, and Simona Zoffoli

Italy is world leader in Synthetic Aperture Radar (SAR) and SAR Interferometry (InSAR), owing to a complete in-house supply and value-added chain. To consolidate this strength, the Italian Space Agency (ASI) run national programs promoting new SAR missions [1], development of SAR/InSAR-based scientific research, and demonstration of novel downstream applications [2-3].

W.r.t. space upstream, in 2019-2022 the flagship COSMO-SkyMed constellation was ensured operational continuity with the launch of two Second Generation satellites. COSMO-SkyMed efficiently addresses users’ needs via provision of interferometric SAR time series through: a) regular observation plans, e.g. the MapItaly project over the national territory and the Background Mission across the globe; b) on-demand tasking; c) specific coverages, e.g. in 2023 during emergencies like Turkey and Syria earthquake [4] and floods in Emilia-Romagna and Tuscany regions, Italy [5]; d) within international initiatives, e.g. the Committee on Earth Observation Satellites (CEOS) [6].

COSMO-SkyMed is also exploited in bilateral cooperation with other space agencies, e.g. JAXA on disaster management [7] and CONAE through SIASGE program [8]. In this respect, ASI promotes multi-mission/multi-frequency approach to investigate synergy between radar bands.

Within PLATiNO national program [9], PLT-1 will embark a compact X-band SAR payload, with metrical resolution, and operate in both monostatic and bistatic mode with COSMO‐SkyMed. Several long-baseline bistatic SAR techniques are currently being evaluated.

Moreover, the current study for a national L-band SAR mission focuses on the assessment of L-band application scenarios, exploitation of monostatic and bistatic configurations, and the analysis of synergies with respect to ROSE-L system and Sentinel-1 constellation.

W.r.t. midstream/ground-segment, ASI not only implemented a new portal to facilitate access to and tasking of COSMO-SkyMed data by institutional users, but also has recently announced the new MapItaly Portal, equipped with user-oriented interface, high-performance processing capability, and download speed [10]. While MapItaly Portal will be expanded to other SAR missions, since 2021 ASI is distributing SAOCOM data collected within ASI’s Zone of Exclusivity through a dedicated portal [11].

All these investments are capitalised in national R&D programs aiming to develop novel algorithms up to at least a Scientific Readiness Level (SRL) of 4, i.e. “Proof of concept”. The most recent was the “Multi-mission and multi-frequency SAR” program [2-3]. In 2021-2023, national public research bodies and industry developed and tested innovative algorithms to process multi-mission/multi-frequency SAR data. InSAR and SAR tomography were among the main techniques that were improved, e.g. for natural hazards applications in DInSAR-3M, MUSAR and MEFISTO projects [12-14].

Perspectives for testing these algorithms in a pre-operational context and input into final users’ workflows are now offered by the Innovation for Downstream Preparation (I4DP) program. Launched in late 2021, I4DP implements the ASI’s roadmap for downstream [15]. Some of the current projects deploys InSAR to address multi-risk assessment in urban areas, infrastructure monitoring, cultural heritage conservation.

A selection of results from the above-mentioned initiatives will be presented in order to share and give evidence of the main achievements and current perspectives.

[1] https://doi.org/10.1109/IGARSS47720.2021.9554834

[2] https://doi.org/10.1109/IGARSS46834.2022.9884937

[3] https://doi.org/10.1109/IGARSS52108.2023.10282854

[4] http://geo-gsnl.org/supersites/event-supersites/active-event-supersites/kahramanmaras-event-supersite/eo-data-access-for-the-kahramanmaras-event-supersite/

[5] https://emergency.copernicus.eu/mapping/sites/default/files/files/IB167%20-%20The%20CEMS%20activities%20for%20the%20floods%20in%20Emilia%20Romagna.pdf

[6] https://meetingorganizer.copernicus.org/EGU22/EGU22-5803.html

[7] https://doi.org/10.1109/IGARSS52108.2023.10282884

[8] https://www.argentina.gob.ar/ciencia/conae/misiones-espaciales/siasge

[9] https://iafastro.directory/iac/paper/id/47097/summary/

[10] https://www.asi.it/en/2023/12/asi-italian-space-agency-upgrades-access-to-mapitaly-data/

[11] https://www.asi.it/en/earth-science/saocom/

[12] https://doi.org/10.1109/IGARSS46834.2022.9884715

[13] https://doi.org/10.1109/IGARSS46834.2022.9883325

[14] https://doi.org/10.1109/IGARSS52108.2023.10282735

[15] https://meetingorganizer.copernicus.org/EGU22/EGU22-5643.html

How to cite: Tapete, D., Montuori, A., Virelli, M., Coletta, A., Longo, F., and Zoffoli, S.: National programs, achievements and current perspectives at the Italian Space Agency to promote SAR missions, InSAR scientific research and downstream applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12268, https://doi.org/10.5194/egusphere-egu24-12268, 2024.

This work has the objective to introduce the session dedicated to the memory of my colleague and friend Mariarosaria Manzo.

In particular, the session has been inspired by the themes that have characterized Mariarosaria’s 20-year research activity. Indeed, her main scientific contributions have been concentrated on the exploitation of Synthetic Aperture Radar (SAR) data for Earth surface deformation retrieval and investigation through the application of the original Differential SAR Interferometry (DInSAR) technique and the development of advanced DInSAR methods focused on the generation of deformation time-series, as for the Small BAseline Subset (SBAS) approach [1].

Therefore, the session is intended to focus on the latest analyses achieved through the development and/or the exploitation of DInSAR methods for Earth observation, as well as on their possible future applications.

Instead, this contribution will provide a brief overview of Mariarosaria’s main findings, achieved through the DInSAR analysis focused on Earth deformations induced by: earthquakes [2-4], volcanic activities [5-7], anthropic actions [8], and on her contribution to the performance assessment of advanced DInSAR techniques [9] and to the development of new algorithmic solutions [10].

But, above all, this work aims to keep the memory alive of Mariarosaria’s intelligence, balance, courage and passion she has always put into everything she did.

 

[1] R. Lanari et al., “An Overview of the Small BAseline Subset Algorithm: A DInSAR Technique for Surface Deformation Analysis,” Wolf, D., Fernández, J. (eds) Deformation and Gravity Change: Indicators of Isostasy, Tectonics, Volcanism, and Climate Change. Pageoph Topical Volumes. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-8417-3_2, 2007

[2] R. Lanari et al., “Surface displacements associated with the L'Aquila 2009 Mw 6.3 earthquake (central Italy): New evidence from SBAS‐DInSAR time series analysis,” Geophys. Res. Lett. 37 (20), 2010

[3] M. Manzo et al., “A quantitative assessment of DInSAR measurements of interseismic deformation: the southern San Andreas Fault case study,” Pure and Applied Geophysics 69, 1463-1482, 2012

[4] D. Cheloni et al., “Geodetic model of the 2016 Central Italy earthquake sequence inferred from InSAR and GPS data,” Geophys. Res. Lett. 44 (13), 6778-6787, 2017

[5] A. Borgia et al., “Volcanic spreading of Vesuvius, a new paradigm for interpreting its volcanic activity, Geophys. Res. Lett. 32 (3), L03303, 2005

[6] M. Manzo et al., “Surface deformation analysis in the Ischia Island (Italy) based on spaceborne radar interferometry,” Journal of Volcanology and Geothermal Research 151 (4), 399-416, 2006

[7] P. Tizzani et al., “Surface deformation of Long Valley caldera and Mono Basin, California, investigated with the SBAS-InSAR approach,” Remote Sens. Environ., 108 (3), 277-289, 2007

[8] R. Lanari et al., “Satellite radar interferometry time series analysis of surface deformation for Los Angeles, California,” Geophys. Res. Lett. 31 (23), L23613, 2004

[9] F. Casu et al., “A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from DInSAR data”, Remote Sens. Environ., doi: 10.1016/j.rse.2006.01.023, 2006

[10] A. Pepe et al., “Improved EMCF-SBAS Processing Chain Based on Advanced Techniques for the Noise-Filtering and Selection of Small Baseline Multi-Look DInSAR Interferograms”, IEEE Trans. Geosci. Remote. Sens., 53 (8), 4394-4417, doi: 10.1109/TGRS.2015.2396875, 2015.

How to cite: Lanari, R.: A brief overview of the 20-year research activity of Mariarosaria Manzo on Differential SAR Interferometry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12612, https://doi.org/10.5194/egusphere-egu24-12612, 2024.

EGU24-18281 | ECS | Posters on site | GI4.3

Three-dimensional InSAR displacement profiles exploiting multi-platform SAR acquisitions: Application to the slow-varying landslide of Gorgoglione (Italy)  

Francesco Falabella, Angela Perrone, Tony Alfredo Stabile, and Antonio Pepe

Ground displacement time-series are standard outputs of consolidated multi-temporal Synthetic Aperture Radar Interferometric (InSAR) algorithms. These products make it possible to remotely detect the spatial and temporal evolution of the deformation field relative to investigated stable targets on the ground with centimeter or even millimeter precision. The occurred deformation is perceived as a change in the round-trip Line-Of-Sight (LOS) path from the sensor to the target; therefore, unambiguous projection in three-dimensional (3-D) space is an undetermined problem. Instead, discerning the vertical [up-down (UD)] and horizontal [east-west (EW)] profiles can be achieved using complementary ascending and descending satellite orbits, assuming however the north-south (NS) profile is negligible. Furthermore, the addition of other independent ascending and descending observations is valuable in order to get bidimensional estimates with greater precisions, but at the same time it is not sufficient to recover the NS profiles due to the lack of sensitivity of the polar orbits to that component. In this context, multi-platform SAR acquisitions from complementary views can be used with the polar-orbiting satellite counterpart to resolve full 3-D displacement profiles.

In this work, we propose a multi-platform procedure to integrate satellite SAR data collected from ascending and descending orbits with data collected from ground-based SAR (GB-SAR) systems to compute 3-D InSAR ground displacement maps and time-series. At this aim, the multi-platform data are first processed independently in order to obtain single-look georeferenced InSAR LOS products, using advanced or canonical multi-temporal InSAR processors and, then, the data are integrated by solving a determined system of linear equations where the unknowns are the temporal samples common to all multiplatform datasets. Note that, as not all data are acquired in the same temporal instant, a quasi-synchronous temporal matching procedure is applied. Also, a theoretical variance-covariance-based framework is proposed to assess the precision of the 3-D estimates.

The developed algorithm was applied to the slow-varying landslide of Gorgoglione in the south-western part of Matera Province (Basilicata Region, southern Italy) on a hilly area at about 800 m a.s.l. by processing ascending and descending Copernicus Sentinel-1 A/B C-Band acquisitions, and a set of GB-SAR IBIS-L Ku-Band images; the results shown that during the analyzed period (September 2016 - July 2017) the landslide area was subject to a deformational trend along the southern profile and to a vertical subsidence trend in accordance with the morphology of the landslide itself.

How to cite: Falabella, F., Perrone, A., Stabile, T. A., and Pepe, A.: Three-dimensional InSAR displacement profiles exploiting multi-platform SAR acquisitions: Application to the slow-varying landslide of Gorgoglione (Italy) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18281, https://doi.org/10.5194/egusphere-egu24-18281, 2024.

EGU24-21119 | Posters on site | GI4.3

Mauna Loa and Kīlauea Elastic volcanic interaction detected via independent component  analysis 

Pietro Tizzani, Monika Przeor, Luca D’Auria Luca D’Auria, Susi Pepe Susi Pepe, and Iván Cabrera‐Pérez

The interaction processes between the two most active Hawaiian volcanoes are still controversial, and despite multiple studies carried out over more than a century, an unambiguous model has yet to be identified. In order to provide new insights we compared the ground deformation patterns in both volcanoes using DInSAR SBAS and Global Positioning System (GPS)datasets. In this work, we processed 10 tracks of ENVISAT ASAR satellite images from 20032010, together with available GPS data from 15 stations located around the two summit calderas of Mauna Loa and Kīlauea. We applied the Independent Component Analysis (ICA) to the DInSAR SBAS ground deformation data to reveal relationships between the spatio-temporal patterns of the ground deformation of the two volcanoes. ICA is widely used Data Mining technique, which allows detecting, separating and characterizing hidden patterns into a spatio-temporal dataset. We performed inverse modelling of the observed ground deformation pattern using analytical source models. The results indicate that the ground deformation of Mauna Loa is associated with a dike‐shaped source located at 6.2 km depth. In comparison, the anticorrelated ground deformation of Kīlauea is associated with a volumetric source at 1.2 km depth. This excludes a hydraulic connection as a possible mechanism to explain the anticorrelated behaviour; instead, we postulate a stress‐transfer mechanism. To support this hypothesis, we performed a 3D numerical modelling of stress and strain fields in the study area, determining the elastic interaction of each source over the others. The most relevant finding is that the Mauna Loa shallow plumbing system can affect the shallowest magmatic reservoir of Kīlauea.

How to cite: Tizzani, P., Przeor, M., Luca D’Auria, L. D., Susi Pepe, S. P., and Cabrera‐Pérez, I.: Mauna Loa and Kīlauea Elastic volcanic interaction detected via independent component  analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21119, https://doi.org/10.5194/egusphere-egu24-21119, 2024.

EGU24-21121 | Posters on site | GI4.3

Analysis of DInSAR measurements in volcanic framework through an integrated multiscale approach: the Yellowstone caldera case-study. 

Andrea Barone, Maurizio Fedi, Antonio Pepe, Pietro Tizzani, and Raffaele Castaldo

The topic of this contribution is the use of the integrated multiscale approach to model the deformation field in volcanic framework retrieved through Differential Interferometric Synthetic Aperture Radar (DInSAR) technique. Specifically, the proposed approach is based on the properties of the harmonic elastic fields satisfying the homogeneity laws and involves multi-scale procedures, such as the Multiridge and ScalFun methods, and boundary analysis techniques, such as the Total Horizontal Derivative (THD). These methodologies allow an unambiguous estimate of the geometrical parameters of the deformation sources, which are the depth, the horizontal position, its shape and horizontal extent, and have turned out to be valid tools for studying simple field sources.

We now show the application of the integrated multiscale approach to model sources with any geometry, also irregular. To do this, we perform several synthetic data tests based on simulated deformation field through COMSOL Multiphysics software package; the results show that we are able to estimate geometrical parameters of geometrically irregular bodies without using any reference model. Finally, we propose an application to real ground deformation dataset, that is the case of the 2004 – 2010 uplift episode occurred at Yellowstone caldera resurgent domes area. We conclude by highlighting the advantages of the proposed methodology and the future developments (in progress) arising from the harmonic properties of elastic deformation fields.

How to cite: Barone, A., Fedi, M., Pepe, A., Tizzani, P., and Castaldo, R.: Analysis of DInSAR measurements in volcanic framework through an integrated multiscale approach: the Yellowstone caldera case-study., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21121, https://doi.org/10.5194/egusphere-egu24-21121, 2024.

EGU24-21176 | Posters on site | GI4.3

Monitoring volcanic areas through the IREA-CNR airborne SAR infrastructure 

Antonio Natale, Paolo Berardino, Alessandro Di Vincenzo, Carmen Esposito, Riccardo Lanari, and Stefano Perna

This contribution is aimed at describing the airborne Synthetic Aperture Radar (SAR) infrastructure developed at the Institute for Electromagnetic Sensing of the Environment (IREA) - National Research Council of Italy (CNR), Naples, Italy.

The infrastructure consists of a flight and a ground segment.

Specifically, the flight segment includes an airborne SAR system, that is, the Multiband Interferometric and Polarimetric SAR (MIPS) sensor [1] owned by IREA-CNR. This is based on the Frequency Modulated Continuous Wave (FMCW) technology, operates at X- and L-band and it can be easily mounted onboard (and unmounted from) different types of aircrafts.

The ground segment includes an IT platform for data storage and processing, located at the IREA-CNR laboratories, and the airborne SAR data processing chain, jointly developed by IREA-CNR and University Parthenope, Naples, Italy [2]. Related to the infrastructure, there are also those activities carried out before and during the airborne campaign to guarantee the proper planning and the successful execution of the campaign itself.

To show the current capabilities of this infrastructure, in terms of characteristics of the final products as well as of the timely response in emergency scenarios, by way of example we present a case study relevant to a MIPS campaign carried out in the frame of the agreement between IREA-CNR and the Department of Civil Protection of the Presidency of the Council of Ministers. In particular, the considered case study has been picked up from a set of airborne SAR campaigns carried out from 2019 to 2022 with the aim of generating multi-temporal single-pass X-Band interferometric Digital Elevation Models of the Stromboli Volcano, in order to perform long-term analyses of the topographic changes related to its eruptive activity [3].

 

[1] A. Natale, P. Berardino, C. Esposito, G. Palmese, R. Lanari, and S. Perna, “The New Italian Airborne Multiband Interferometric and Polarimetric SAR (MIPS) System: First Flight Test Results,” Int. Geosci. Remote Sens. Symp., vol. 2022-July, pp. 4506–4509, 2022, doi: 10.1109/IGARSS46834.2022.9884189.

 

[2] P. Berardino, A. Natale, C. Esposito, R. Lanari, and S. Perna, “On the Time-Domain Airborne SAR Focusing in the Presence of Strong Azimuth Variations of the Squint Angle,” IEEE Trans. Geosci. Remote Sens., vol. 61, pp. 1–18, 2023, doi: 10.1109/TGRS.2023.3289593.

 

[3] R. Lanari, C. Esposito, P. Berardino, A. Natale, G. Palmese, and S. Perna, “Stromboli volcano monitoring with airborne SAR systems,” in EGU General Assembly 2023, doi: https://doi.org/10.5194/egusphere-egu23-10047.

 

How to cite: Natale, A., Berardino, P., Di Vincenzo, A., Esposito, C., Lanari, R., and Perna, S.: Monitoring volcanic areas through the IREA-CNR airborne SAR infrastructure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21176, https://doi.org/10.5194/egusphere-egu24-21176, 2024.

EGU24-21319 | Posters on site | GI4.3

Identification of phase unwrapping errors through the extension of the temporal coherence factor for redundant sequences of small baseline DInSAR interferograms 

Giovanni Onorato, Claudio De Luca, Francesco Casu, Michele Manunta, Muhammad Yasir, and Riccardo Lanari

Advanced DInSAR techniques are used to investigate the temporal evolution of the deformations through the retrieval of the displacement time series, achieved through the inversion of an appropriate set of multi-temporal interferograms. Among them, the Small BAseline Subset (SBAS) is a well-established approach which has been widely used for the analysis of several deformation phenomena.

In this context, an effective and robust Phase Unwrapping (PhU) algorithm must be typically implemented and exploited in order to accurately retrieve the ground deformation signals. This operation represents a critical step because of the intrinsically ill-posed nature of the problem which may lead to solutions that, despite being mathematically correct, do not reproduce the actual unwrapped phase profile.

A common indicator for the quality of the PhU solution within advanced DInSAR methods like SBAS is the temporal coherence. This is a point-like parameter available for methods where the displacement time-series are retrieved through the inversion of an overdetermined linear equation system [M, N], with M>N, where M is the number of the generated (redundant) interferograms and N represents the exploited SAR images, whose solution can be obtained in the LS sense.

We present in the following a simple solution to identify and correct possible PhU errors, based on a different and innovative use of the temporal coherence parameter.

In principle, the higher the value of the temporal coherence, the better the quality of the PhU solution; however, unfortunately, the temporal coherence sensitivity decreases when the number of interferograms increases. To overcome this issue we propose to compute for each point a time series of local temporal coherences, computed by exploiting a limited number of interferograms. To do this, starting from the first acquisition date of the analysed dataset, we define a time window range, say Δw, and a time sampling, say ti , where the step size Δt= ti+1 -ti  is selected in agreement with the satellite revisiting time. Accordingly, for the generic i-th step, we consider the time window centred around the ti value and we calculate the temporal coherence by on a limited subset of interferograms whose master and/or slave images are included in the selected time window [tiw/2 , tiw/2]

This solution is computationally efficient and allows us to regain sensitivity on possible PhU errors. Indeed, by doing so, the number of interferograms to be analysed in order to identify those characterized by PhU errors has been drastically reduced, making the local temporal coherence more sensitive to small variations in a single interferogram. A subsequent algorithm of PhU errors correction can be then applied only to the involved interferograms, reducing the time computing and increasing the ability to spot and correct the wrong interferogram.

How to cite: Onorato, G., De Luca, C., Casu, F., Manunta, M., Yasir, M., and Lanari, R.: Identification of phase unwrapping errors through the extension of the temporal coherence factor for redundant sequences of small baseline DInSAR interferograms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21319, https://doi.org/10.5194/egusphere-egu24-21319, 2024.

EGU24-21611 | Posters on site | GI4.3

National scale full-resolution P-SBAS processing for the investigation of critical infrastructure deformations related to the built-up environment  

Pasquale Striano, Sabatino Buonanno, Francesco Casu, Claudio De Luca, Federica Cotugno, Marianna Franzese, Adele Fusco, Michele Manunta, Giovanni Onorato, Yenni Lorena Belen Roa, Maria Virelli, Muhammad Yasir, Giovanni Zeni, Ivana Zinno, Riccardo Lanari, and Manuela bonano

Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques have emerged as powerful tools for monitoring and surveillance at both single-building and territorial levels, offering sub-centimetric accuracy with manageable costs. Among these techniques, the DInSAR method known as Small BAseline Subset (SBAS) and its parallel algorithmic implementation, referred to as the Parallel SBAS (P-SBAS) approach, stand out for their ability to provide systematic displacement measurements at both regional, national and continental scales through the generation of spatially and temporally dense deformation time series, contributing to investigate various hazard scenarios related to the natural and the built-up environments. Moreover, by exploiting the full-resolution extension of the P-SBAS approach, it is also possible to generate long-term deformation time series at different spatial resolution scales for regional and local displacement investigations.

This work focuses on the extensive use of the full-resolution P-SBAS approach for local-scale DInSAR analyses aimed at detecting localized deformation phenomena in wide urban areas, with a particular interest in infrastructure and individual building displacements. To this aim, we can profitably capitalize on the highest spatial resolution of the SAR images collected by the currently available and future advanced satellite SAR systems characterized by different operational modes (Stripmap, TOPSAR, ScanSAR) and frequency bandwidths (L-, C-, and X-band).

Among these, we leverage the extensive archives of X-band (about 3 cm wavelength) SAR data acquired since 2009 along the overall Italian territory by the sensors of the Italian COSMO-SkyMed constellation of the first (CSK) and second (CSG) generation, operated through the Stripmap mode (about 3 m x 3 m spatial resolution) within the so-called Map Italy program. This huge SAR dataset makes it possible to monitor the surface deformations affecting the built-up environment with a very high spatial and temporal measurement density. In this work, we perform a full-resolution P-SBAS analysis over some Italian cities (e.g., Roma, Napoli, Bologna, Catania), where large sequences of ascending and descending CSK/CSG SAR data are available, in order to assess the health conditions of critical infrastructures and buildings related to extended built-up environments. Moreover, we also present the preliminary full-resolution P-SBAS results achieved by processing the available L-band SAR data acquired by the new twin sensors of the Argentinian SAOCOM-1 constellation of CONAE (spatial resolution about 5x5 m). Thanks to the longer wavelength characterizing the L-Band data, we can investigate the possibilities of overcoming some of the typical limitations of X-band SAR systems (e.g., the occurrence of phase unwrapping problems). Our approach involves the use of parallel hardware and software solutions, including GPU parallel programming techniques, which prove to be highly effective in rapidly generating full-resolution P-SBAS deformation time series over large urbanized areas. These measurements can help to define a roadmap for identifying and preventing critical conditions in buildings and infrastructures.

How to cite: Striano, P., Buonanno, S., Casu, F., De Luca, C., Cotugno, F., Franzese, M., Fusco, A., Manunta, M., Onorato, G., Roa, Y. L. B., Virelli, M., Yasir, M., Zeni, G., Zinno, I., Lanari, R., and bonano, M.: National scale full-resolution P-SBAS processing for the investigation of critical infrastructure deformations related to the built-up environment , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21611, https://doi.org/10.5194/egusphere-egu24-21611, 2024.

EGU24-21852 | Posters on site | GI4.3

10 Years of Sentinel-1 data exploitation to monitor volcanic and seismic areas through DInSAR techniques 

Francesco Casu and the IREA-CNR Team

Since 2014, the Sentinel-1 satellite constellation has provided a huge amount of Synthetic Aperture Radar (SAR) data across the Earth with an unprecedent continuous and high acquisition rate. These characteristics, together with the free and open access Copernicus data policy, have made possible the development of operational services aimed at monitoring the millimetric displacements of Earth surface, with particular reference to volcanic and seismic phenomena. The services are based on the Differential SAR Interferometry (DInSAR) technique, which permits measuring the crustal displacements from a multi-temporal set of SAR data acquisitions.

The services herein presented are part of the tasks of the Institute for the Electromagnetic Sensing of the Environment of National Research Council of Italy (IREA-CNR) to support the Italian Department of Civil Protection (DPC) for volcanoes and seismic areas monitoring.

One of the implemented services starts from the occurrence of an earthquake, once published in the main global seismic catalogues, and generates the relevant DInSAR co-seismic displacement maps with the available Sentinel-1 data. This tool is fully operative and generates products dating back to 2015, thus allowing us to investigate the ground displacement associated to more than 600 earthquakes. More recently, the tool has been extended to provide not only the measure of the displacement, but also a speditive model of the seismic source and it is under development a machine learning based solution to further extend the retrieved information. All the generated products are freely available to the scientific community through the European Plate Observing System Research Infrastructure (EPOS-RI).

A second service is dedicated to volcano ground displacement monitoring. In this case, every time a new SAR data in the Sentinel-1 catalogues is available over a monitored volcano, the DInSAR processing, based on the Parallel Small BAseline Subset (P-SBAS) approach, starts and allows updating the ground displacement time series for both the ascending and descending passes. The so-retrieved Line of Sight (LOS) measurements are then combined to compute the Vertical and East-West components of the computed displacements, which are straightforwardly understandable by most of the end users. This service is currently running for the main active Italian volcanoes (Campi Flegrei caldera, Mt. Vesuvius, Ischia, Mt. Etna, Stromboli and Vulcano), making us able to continuously follow the temporal evolution of the ground displacement since 2015. Are currently under development automatic and semi-automatic techniques to investigate the detected ground displacements.

 

This work is supported by: the CNR-IREA and Italian DPC agreement; the EPOS-RI, including the one obtained through the EPOS-Italia JRU; the European Union - NextGeneratonEU through the projects: NRRP - MEET (Monitoring Earth's Evolution and Tectonics); ICSC - CN-HPC - PNRR M4C2 Investimento 1.4 - CN00000013; GeoSciences IR - PNRR M4C2 Investimento 3.1 - IR0000037; Sustainable Mobility Center - MOST - PNRR M4C2 Investimento 1.4 - CN00000023.

How to cite: Casu, F. and the IREA-CNR Team: 10 Years of Sentinel-1 data exploitation to monitor volcanic and seismic areas through DInSAR techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21852, https://doi.org/10.5194/egusphere-egu24-21852, 2024.

EGU24-21873 | Posters on site | GI4.3

The legacy of Mariarosaria Manzo 

Michele Manunta, Paolo Berardino, Manuela Bonano, Francesco Casu, Claudio De Luca, Riccardo Lanari, Antonio Pepe, Susi Pepe, Stefano Perna, Pietro Tizzani, and Giovanni Zeni

This contribution is aimed at drawing the professional and human profile of our colleague and friend Mariarosaria, based on the memories and materials that we have collected during her 20 years’ activity at the Institute for Electromagnetic Sensing of the Environment (IREA) of the National Research Council (CNR), Naples, Italy.

Beside a short overview of her professional contribution at IREA-CNR, we intend to provide also our personal memories picked up from 20 years of co-workership and friendship. Anecdotes, stories and facts will be also provided, with the objective to transmit Mariarosaria’s intelligence, competence, passion, courage, poise, firmness, gentleness, determination and sweetness, all enclosed in her wonderful smile and amazing blue eyes.

All this represents her legacy that we want to pass on.

How to cite: Manunta, M., Berardino, P., Bonano, M., Casu, F., De Luca, C., Lanari, R., Pepe, A., Pepe, S., Perna, S., Tizzani, P., and Zeni, G.: The legacy of Mariarosaria Manzo, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21873, https://doi.org/10.5194/egusphere-egu24-21873, 2024.

EGU24-22212 | Orals | GI4.3

Cluster analysis of InSAR data for the investigation of groundwater production effects 

Celine Eid, Alberto Manuel Garcia Navarro, Christoforos Benetatos, and Vera Rocca

InSAR time series analysis is a powerful tool used in remote sensing to monitor ground deformation over time. In recent years, advanced techniques and algorithms have been developed for the application of InSAR in a more accurate manner along with the continuous availability of new satellite data. In this research, we propose the use of a developed clustering algorithm for analyzing InSAR time-series data and face the superposition of effects inducing ground movements. The investigated area is in the Po Plain in northern Italy and it is characterized by massive groundwater production for various purposes and it also hosts an underground gas storage system. The focus of the research is the identification and the quantification of the seasonal and trend behavior related to aquifer exploitation. We selected the additive approach for decomposing the time-series obtained from InSAR and applied the k-means clustering algorithm (Morissette and Chartier, 2013) over the seasonal and trend components. The results showed different seasonal behaviors attributed to areas with varying water production, rainfall precipitation and structural geology. The trend was analyzed and compared to the existing literature proving the reliability of this method.

The quantification of ground deformation due to each main source is of paramount importance for a reliable prevision of each phenomenon via the calibration of dedicated numerical models. The results of the research will be used to discriminate and quantify the effects of water production from the effects of gas storage operations and they will allow the calibration of dedicated 3D numerical fluid-flow and stress-strains models.

Reference:

Morissette, L. & Chartier, S. (2013). The k-means clustering technique: General considerations and implementation in Mathematica. Tutorials in Quantitative Methods for Psychology, 9, 15-24. https://doi.org/10.20982/tqmp.09.1.p015.

How to cite: Eid, C., Garcia Navarro, A. M., Benetatos, C., and Rocca, V.: Cluster analysis of InSAR data for the investigation of groundwater production effects, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22212, https://doi.org/10.5194/egusphere-egu24-22212, 2024.

EGU24-1385 | ECS | Posters on site | GI4.4

Deep Learning based Automation for Rooftop Solar Potential Estimation using high-resolution UAV data  

Apratim Bhattacharya, Aniruddha Khatua, and Bharath H. Aithal

The acquisition of data pertaining to built-up areas and the accessibility of their suitable vector format are crucial in a multitude of remote sensing applications. The adoption of a renewable energy generation method is inevitable in response to the escalating energy demand and to fulfill Sustainable Development Goals. Rooftop solar photovoltaic energy generating optimizes panel installation area efficiently and minimizes transmission losses. The process of identifying a suitable rooftop area for solar photovoltaic (PV) systems using a conventional approach to digitizing buildings through vectorization is not only laborious but also consumes a significant amount of time. The accurate and efficient creation of building rooftop extraction has posed a substantial and intricate challenge within the field of remote sensing. Though many strategies have been developed and these demonstrate a high level of efficacy in feature recognition and extraction but lack the integrity of geospatial information. This research introduces a model pipeline that aims to facilitate the transfer of geospatial information from the input image. Additionally, the proposed process has the capability to generate vector shapefiles representing the building rooftops and the capability of estimating the solar rooftop potential utilizing the extracted rooftop in a suitable format. This is developed as an open-source GUI to help decision makers and planners to easily utilize the developed pipeline.

 

Keywords: Remote sensing, GIS, Deep Learning, Automation, UAV data processing, Rooftop solar potential

How to cite: Bhattacharya, A., Khatua, A., and Aithal, B. H.: Deep Learning based Automation for Rooftop Solar Potential Estimation using high-resolution UAV data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1385, https://doi.org/10.5194/egusphere-egu24-1385, 2024.

EGU24-2709 | Posters on site | GI4.4

The combined time-depth conversion as a method for a better imaging of complex scenarios 

Raffaele Persico, Ilaria Catapano, Giuseppe Esposito, Gianfranco Morelli, Gregory De Martino, and Luigi Capozzoli

In this contribution we will propose a resume regarding the technique of the combined time depth conversion, which is relevant to particular cases in the framework of the GPR prospecting, that are of interest when layered scenarios are met, or in cases when electrically large cavities are likely found [1]. These cases are particularly relevant for the urban geophysics, because of the intrinsic layered structure of many engineering works and for the risk of subsidence due to unknown buried cavities.

In these cases, the problem is often computationally too cumbersome to be afforded in its entire complexity [2]. On the other hand, a common GPR processing [3] might not provide a correct imaging of the buried scenario, because in layered media the first (shallower) layer would result spuriously compressed or spuriously dilatated with respect to the other ones, whereas a buried cavity would (and does) appear all the times incorrectly compressed.

These well-known problems are due to the different propagation velocity of the electromagnetic waves within the different media.

However, if one of these cases is recognizable from the data, it can be possible to operate a suitable localized expansion of the compressed parts of the image, that can be -let say- ironed up to its correct vertical size [4].

This makes it possible to represent the different buried targets in more realistic reciprocal positions and proportions, so making clearer the image. In particular when a slicing is applied or (in some cases) a pseudo 3D perspective imaging, the combined time-depth conversion can meaningfully improve the interpretation of the buried scenario.

At the conference, both simulated and experimental results in controlled condition will backup these reasoning.

 

References

[1] R. Persico, S. D'Amico, L. Matera, E. Colica, C. De, Giorgio, A. Alescio, C. Sammut and P. Galea, GPR Investigations at St John's Co‐Cathedral in Valletta. Near Surface Geophysics, vol. 17 n. 3, pp. 213-229. doi:10.1002/nsg.12046, 2019.

[2] I. Catapano, L. Crocco, R. Persico, M. Pieraccini, F. Soldovieri, “Linear and Nonlinear Microwave Tomography Approaches for Subsurface Prospecting: Validation on Real Data”, IEEE Trans. on Antennas and Wireless Propagation Letters, vol. 5, pp. 49-53, 2006.

[3] A. Calia, G. Leucci, M. T. Lettieri, L. Matera, R. Persico, M. Sileo, The mosaic of the crypt of St. Nicholas in Bari (Italy): Integrated GPR and laboratory diagnostic study, Journal of Archaeological Science, vol. 40, n. 12, pp. 4162-4169, December 2013.

[4] R. Persico, F. Marasco, G. Morelli, G. Esposito, I. Catapano, “A posteriori insertion of information for focusing and time–depth conversion of ground-penetrating radar data”, Geophysical Prospecting, open access, https://doi.org/10.1111/1365-2478.13369, 2023.

How to cite: Persico, R., Catapano, I., Esposito, G., Morelli, G., De Martino, G., and Capozzoli, L.: The combined time-depth conversion as a method for a better imaging of complex scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2709, https://doi.org/10.5194/egusphere-egu24-2709, 2024.

EGU24-3536 | Orals | GI4.4

Low-altitude measurement of CRCS Dunhuang surface reflectance based on multi-rotor electric UAV 

Yong Zhang, Hanlie Xu, Lijun Zhang, Danyu Qin, and Zhiguo Rong

The CRCS Dunhuang site (40.1821°N, 94.3244°E) is located in the Gobi Desert in northwest China, about 35 km west of Dunhuang City, Gansu Province. Covering approximately 30 km × 30 km, the entire site is formed on a stable alluvial fan of the Danghe River and its surface consists of cemented gravel without vegetation. Dunhuang was chosen as a CRCS site due to its extremely homogeneous surface conditions. The central area (600 m × 600 m) of the site is designed for high spatial resolution visible/near-infrared (VIS/NIR) sensors such as the China-Brazil Earth Resources Satellite (CBERS) series. An extended large area (20 km × 20 km) is used for low spatial resolution sensors such as the Multichannel Visible and Infrared Scanning Radiometer, Visible and Infrared Radiometer, and Medium Resolution Spectral Imager on board the Fengyun-1 and 3 (FY-1/3) series of polar-orbiting satellites. It is also used for the field calibration of the VIS/NIR channels on Chinese geostationary weather satellites (Fengyun-2 or FY-2 series). Field calibration of the FY series of satellites has been conducted operationally since 2001 for only the VIS/NIR channels.

Due to the lack of onboard VIS/NIR calibrators, the in-orbit field calibration based on the CRCS Dunhuang site is still the primary method for China’s satellite sensors’ VIS/NIR channels, such as the FY series satellites, Haiyang (HY) series of Ocean Satellites, Disaster and Environmental Monitoring Satellites (HJ), and CBERS series satellites. However, the traditional satellite-ground synchronous measurement method of surface reflectance is based on car running field observation, which not only consumes a lot of manpower and material resources, easily causes damage to the site surface, but also lacks regional representativeness of the obtained measurement data.

In view of this, CRCS Dunhuang 2016 satellite-ground synchronous observation experiment mainly based on low-altitude surface reflectance measurement by rotor drones, supplemented by car running field measurements, and completed all aspects of whole process test including route design, altitude selection, instrument parameter configuration, sampling strategy, and aviation data processing.

Through this flight test, it can be proved that the use of multi-rotor drones to fly at low altitudes instead of the traditional car running satellite-ground synchronous measurement of surface reflectance not only improves the spatial consistency and representativeness of the ground reflection characteristics, but also improves the measurement efficiency of the ground reflectivity. Using flight measurement method can effectively protect the surface of the precious CRCS Dunhuang Gobi site and greatly save manpower and material resources.

Through the comparisons and analysis of the surface reflectance data measured by aerial flight method and traditional car running field observations, it can be found that the mean values of multiple surface reflectance measurement data are relatively close, and the standard deviation of the airborne measurement data is smaller. The airborne data can replace the car running field data to complete the radiometric calibrations.

 

How to cite: Zhang, Y., Xu, H., Zhang, L., Qin, D., and Rong, Z.: Low-altitude measurement of CRCS Dunhuang surface reflectance based on multi-rotor electric UAV, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3536, https://doi.org/10.5194/egusphere-egu24-3536, 2024.

There is a visible link between climate change and increased frequency of natural hazards. Avalanches are of particular concern within mountainous and arctic regions. Local snow characterization and mapping is an important first step to forecasting a hazardous event and identify vulnerable regions during risk management assessment of critical infrastructure, such as roadways and tunnels. Information on snow cover and snow properties is also crucial for flood management, hydropower industry and glacier mass balance calculations. 

Uncrewed aerial systems (UASs) play a critical role in safely and efficiently obtaining high-resolution data to characterize snow and ice for avalanche and glacier studies. UASs provide controlled flight altitude and speed and high positioning accuracy resulting in repeatable surveys. Surficial and subsurface information on the snow layers can be obtained depending on the sensor equipped onboard the UAS. Lidar measurements collected prior to and after snow accumulation provide a ground and snow surface maps from which an estimate is derived on snowpack thickness. However, the lidar method does not provide information on internal snowpack structure neither on snow properties. Ground penetrating radar (GPR) allows mapping of the snow surface and insight into subsurface snow layers, depending on the snow characteristics such as snow water equivalent (SWE) and density.  

In March 2023, GPR measurements using a 1GHz antenna were acquired from a commercial off the shelf quadcopter at Fonnbu along the Grasdalen alpine valley, western Norway. Following in-house data processing workflow, two main interfaces are identified through 2D profile picking: rock to snow and snow to air. Intermittent layers are also identified increasing detailed understanding of the snowpack structure. Snow density and velocity are determined using local snowpit logs from which snow thickness is calculated. These snowpack depth estimates are compared with the lidar thickness estimates enabling a multi-scale and -parameter analysis of the Fonnbu snow study site. Methods developed in this study will be implemented for snowpack characterization using UAS-mounted sensors to other study sites within Norway. 

How to cite: Lee, M., Dupuy, B., and Grøver, A.: Snowpack characterization and depth estimates using UAS-mounted ground penetrating radar: A case study from Western Norway , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6730, https://doi.org/10.5194/egusphere-egu24-6730, 2024.

EGU24-7638 | Orals | GI4.4

A new multiscale and multisensory strategy for the characterization of groundwater discharge in coastal areas – the SUBGEO project 

Gerardo Romano, Luigi Capozzoli, Vincenzo Lapenna, and Maurizio Polemio

The monitoring of groundwater resources and the identification of energy resources play a crucial role in the sustainable development and management of coastal areas. This is a fundamental aspect considering the climate changes occurring in areas particularly exposed to physical hazards resulting from extreme weather events and higher are the risks of coastal erosion, groundwater salinization, flooding and other hazards in low-elevation coastal zones (Oppenheimer et al., 2019).  Currently, 2.15 billion people live in the near-coastal zone and 898 million in the low-elevation coastal zone globally (Reiman and al, 2023). Moreover, coastal freshwater reservoirs can represent a fundamental resource to address water shortages. The hydro-geological potential and economic factors linked to the submarine groundwater are the starting point of the two-year Italian Research Project of National Relevance (PRIN-2022) SUBGEO where the University of Bari (UNIBA) and the two Institutes (IMAA and IRPI) of the National Research Council are involved. The project is focused on the submarine groundwater discharge analysis with an innovative and integrated geophysical approach based on the use of electric and electromagnetic methods for the twofold targets of coastal underground freshwater reservoir non-invasive characterization and to gain useful tools for the optimal and sustainable management of the coastal areas and resources.

Subgeo will develop an innovative geophysical approach to provide spatially continuous and high-resolution information on the subsoil structure from the offshore areas, where the outward fluxes mix with the seawater, to the onshore ones including the urban areas.

The proposed strategy will be tuned by small-scale laboratory experiments and by numerical simulations to define the best acquisition procedures and check the sensitivity of the strategy for different subsurface conditions. The final goal of the project consists of reproducing a high-resolution and detailed hydrogeophysical model for managing the water resources in coastal areas.

 

References

Oppenheimer M., Hinkel J. et al.: Sea Level Rise and Implications for Low Lying Islands, Coasts and Communities Supplementary Material, http://hdl.handle.net/11554/9280, 2019.

Reimann L, Vafeidis AT, Honsel LE. Population development as a driver of coastal risk: Current trends and future pathways. Cambridge Prisms: Coastal Futures. doi:10.1017/cft.2023.3, 2023;1:e14.

How to cite: Romano, G., Capozzoli, L., Lapenna, V., and Polemio, M.: A new multiscale and multisensory strategy for the characterization of groundwater discharge in coastal areas – the SUBGEO project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7638, https://doi.org/10.5194/egusphere-egu24-7638, 2024.

EGU24-8011 | Orals | GI4.4

Geophysical monitoring of engineering infrastructure foundations 

Enzo Rizzo, Paola Boldrin, Lorenzo Andreotti, and Giacomo Fornasari

The geophysical methodologies can give for providing useful information about the subsoil, environment, buildings, and civil infrastructures and supporting the public administrations in planning interventions in urban scenarios. In the past years, the geophysical prospection methods have been improved for the inspection of foundation soils, civil structure, and engineering infrastructures. Anyway, the potential of geophysical techniques in urban sites is mainly known in characterisation contexts, while a monitoring use has not yet been developed. Therefore, new applications and laboratory experiments are needed to enhance their capability and development.

This work introduces a time lapse three-dimensional Electrical Resistivity Tomography (3D ERT) monitoring on the effects of the standard practice of shallow polyurethane resin injected below the settled foundations of a villa. The application was performed to monitor the effectiveness of the consolidation beneath the building with time. The 3D ERT was applied before and after the injection phase. The geoelectrical acquisitions were performed with electrodes arranged close the external walls with an electrode space of about 1m. Therefore, non-conventional setting of the electrode layout was adopted permitting to obtain a 3D model of the geophysical parameter distribution close the foundations. The time-lapse 3D ERT highlighted the effects of the resin injections. In addition, an experiment was carried out in the laboratory through the creation of a physical model of a foundation placed in a sandbox in which the conditions of resin injection after a subsidence are simulated.

How to cite: Rizzo, E., Boldrin, P., Andreotti, L., and Fornasari, G.: Geophysical monitoring of engineering infrastructure foundations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8011, https://doi.org/10.5194/egusphere-egu24-8011, 2024.

EGU24-8467 | Posters on site | GI4.4

Multi-instrumental approach for aerosol profiling in the lower troposphere, use of UAV-based instrumentation. 

Aleksander Pietruczuk, Ilya Bruchkouski, and Artur Szkop

This study presents a multi-instrumental approach to studying aerosol properties in the lower troposphere. It focuses on a combination of in-situ techniques with remote sensing measurements utilizing model-based study. Measurements taken at the suburban site of Raciborz in the highly industrialized region of Silesia will be used. We will apply ground-based in-situ measurements, retrieval of aerosol optical properties profile utilizing the synergy of collocated CIMEL Sun-photometer and Lufht’s CHM-15k Nimbus ceilometer, and UAV (Unmanned Aerial Vehicle) based measurements in the lowermost part of the troposphere.

Aerosol size distribution will be measured by tandem Aerodynamic Particle Sizer and Scanning Mobility Particle Sizer spectrometers that will serve as the starting point of GRASP retrieval of aerosol microphysical and optical properties based on Aurora 4000 polar nephelometer measurements. These retrievals will be used to normalize UAV-based instruments that include OPC (Optical Particle Counter) and LED-based COBOLT instruments for aerosol backscatter measurements during the night. OPC instrument will provide a profile of Particulate Matter concentration (PM) at certain altitudes while COBOLT instrument will provide a profile that is proportional to the aerosol backscattering coefficient. Whilst typical COBOLT operation requires normalization in the upper troposphere or lower stratosphere where aerosol effects are neglected we will normalize it close to the ground by GRASP retrieval. Supplementary measurements of atmospheric pressure and temperature profiles will be used to determine Rayleigh scattering.

Obtained UAV-based profiles of aerosol properties will be calibrated to the in-situ ground measurements while also being compared and adjusted to the lowermost part of the aerosol profile obtained by the synergy of remote measurements (GRASP) thus providing means for estimating continuous profile of aerosol properties from the ground to the mid-troposphere.

This work is supported by the National Science Centre under grant 2021/41/B/ST10/03660.

How to cite: Pietruczuk, A., Bruchkouski, I., and Szkop, A.: Multi-instrumental approach for aerosol profiling in the lower troposphere, use of UAV-based instrumentation., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8467, https://doi.org/10.5194/egusphere-egu24-8467, 2024.

EGU24-8611 | ECS | Orals | GI4.4

UAV digital photogrammetry as support tool for transmission-based muography 

Tommaso Beni, Diletta Borselli, Lorenzo Bonechi, Luca Lombardi, Sandro Gonzi, Laura Melelli, Maria Angela Turchetti, Livio Fanò, Raffaello D'Alessandro, Giovanni Gigli, and Nicola Casagli

The employment of unmanned aerial vehicles (UAVs) for digital photogrammetry applications (UAV-DP), together with satellite data, has emerged as a pivotal tool for conducting reliable muographic campaigns. This study aims to present a comprehensive workflow designed specifically to plan and support UAV-derived data for muon radiography objectives. Through a real case study conducted at the Etruscan necropolis of Palazzone (Umbria, Italy), this study shows the creation of high-resolution three-dimensional models of the ground surface/sub-surface by integrating UAV-DP, laser scanner and GPS-acquired data. The accuracy of these three-dimensional environment significantly influences the reliability of the simulated muon flux transmission, which is crucial for inferring the relative transmission values and estimating the density distributions. This study highlights the importance of UAV-derived data in the muography process and their potential to enhance or affect the outcomes of muon imaging results. Furthermore, it emphasizes the need for a multidisciplinary approach in muography applications, particularly focusing on the integration and utilization of UAV-based data to improve spatial environment reconstruction.

How to cite: Beni, T., Borselli, D., Bonechi, L., Lombardi, L., Gonzi, S., Melelli, L., Turchetti, M. A., Fanò, L., D'Alessandro, R., Gigli, G., and Casagli, N.: UAV digital photogrammetry as support tool for transmission-based muography, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8611, https://doi.org/10.5194/egusphere-egu24-8611, 2024.

During the last decades, the introduction of Unmanned Aerial Systems (UASs) in civil applications has exponentially grown. Environmental monitoring, mapping, and surveying, agriculture and precision farming, (infra)structure inspection, and medical supplies delivery are some clear examples. For many of these applications, the organization and planning of the missions are very similar: the variables or phenomena are clearly identified, the area of interest is previously defined, the flight plans are meticulously prepared to extract the features of interest (e.g. overlap and constant elevation for high-quality orthomosaics), the payload and on-board instrumentation is previously configured, the crew is informed in advanced about the objective of the missions, and in general, all these missions are executed in really good weather conditions. However, for some applications, like UAS-assisted Mountain Emergency Medicine, these protocols are totally different, because of the type of emergency (search and rescue operation, first kit provision, avalanche search) resulting in a quick and efficient configuration of payloads, accuracy of the reported incident (accuracy of GPS and distress call), preparation and level of stress for the rescue teams operators and adverse weather conditions (poor visibility, unknown terrain, wind, snow, rain). In addition, the physical localization of the UASs is in regional stations, so it is necessary to mobilize equipment and crew in a very short time to guarantee the success of the missions or, ideally, standby at distributed sites for autonomous operation if cleared for take-off from remote. In order to attend any mountain emergency that requires the use of UASs inside of the Province of South Tyrol, Italy (alpine region) to identify the most suitable operations area (vertical port), to elaborate an efficient point-to-point flight plan maximizing the use of its batteries (considering changes of terrain, elevation, and possible obstacles), and delivering a defibrillator (specific use case), here we propose a basic data management system based on Geographic Information Systems (GIS) that create a distributed vertical port stations in the Province and identify the closest point to the distress call. The system is able to plan an efficient flight plan in a mountainous area using a sensor-based data model based on a commercial UAS system (MAVTech Q4X) to provide a dedicated payload (defibrillator). We used the system in two scenarios (winter and summer) and they showed a reduction of nearly 50% of the delivery time of the defibrillator by traditional means.

How to cite: Mejia-Aguilar, A., Parin, R., Ristorto, G., Mayrguendter, S., and van Veelen, M.: How GIS tools and sensor-based data models are impacting the UAS civil missions: Identification of suitable vertical ports and optimal flight planning to quickly deliver defibrillators in alpine terrains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9130, https://doi.org/10.5194/egusphere-egu24-9130, 2024.

EGU24-10049 | Posters on site | GI4.4 | Highlight

Contactless and microwave tomography based radar imaging for surveying reinforced concrete structures 

Ilaria Catapano, Giovanni Ludeno, Gianluca Gennarelli, Giuseppe Esposito, and Adriana Brancaccio

Since the beginning of the 19th century, reinforced concrete has been used to build infrastructures and urban buildings and nowadays is the main material employed in the construction industry. Although reinforced concrete structures are designed in such a way to maximize their life cycle, discrepancies between design and executive phases as well as the joint action of mechanical and environmental effects may cause damages or serious and even fatal accidents. Accordingly, there is a constant attention towards the development of non-destructive technologies (NDTs) capable of improving knowledge about the structure health state while reducing times and costs of the inspections. Among NDTs, ground penetrating radar (GPR) [1] is widely used to perform on-demand high-resolution subsurface surveys and continuous efforts are made to improve the effectiveness of GPR investigations. In this frame, a current open challenge is the design of systems capable of coupling the potentialities offered by GPR systems and autonomous vehicles.

As a contribute to such an issue, this communication aims at presenting the preliminary results achieved in the frame of the Italian PRIN 2022 Project ARACNE - A RAdar system for Contactless surveys of reiNforced concrEte, whose goal is the design of a compact and lightweight GPR system able to perform contactless analysis and provide as output an image that is easily interpretable by non-expert users. The project started at October 2023 and the initial months have been focused on the definition of the system requirements and on the data processing. Specifically, a study aimed at evaluating the influence of the parameters like frequency bandwidth, polarization and radiation pattern of the antennas has been performed. Moreover, microwave tomography (MWT) [2], [3] has been exploited as an effective and flexible tool to achieve high-resolution focused images from contactless, as well as contact, GPR data. In this regard, an analysis devoted to investigating how the distance between the GPR antennas and the structure under test affects the achievable performance has been carried out. Further details on the ARACNE project and its initial results will be provided at the conference.

[1]. Daniels, Ground penetrating radar. Vol. 1. Iet, 2004.

[2] Catapano et al., “Ground‐Penetrating Radar: Operation Principle and Data Processing,” Wiley Encyclopedia of Electrical and Electronics Engineering: 1-23.

[3] 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, 2021.

Acknowledgment: This work has been supported by ARACNE - A RAdar system for Contactless surveys of reinforced concrEte (grant n. 202225CSP2)

How to cite: Catapano, I., Ludeno, G., Gennarelli, G., Esposito, G., and Brancaccio, A.: Contactless and microwave tomography based radar imaging for surveying reinforced concrete structures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10049, https://doi.org/10.5194/egusphere-egu24-10049, 2024.

The study of soil-structure or even city-soil interaction is attracting the attention of many researchers, as both numerical simulation results and preliminary results from empirical data indicate their significant effect in determining the level of seismic hazard.

In this study, the wave field radiated from a building to its surroundings, which is due to the interaction of the building with the ground, is identified and extracted using a novel approach. The proposed approach, which is valid for seismic data analysis, combines deconvolution and polarization analysis. It consists of four steps: (1) estimation of building resonance frequencies, (2) deconvolution of seismic recordings of sensors installed in a building and in the surrounding environment, (3) identification of seismic phases, reconstruction of seismic phases, reconstruction of the signal transmitted from the building to the surrounding environment and estimation of its energy, and (4) polarization analysis.

The application of the approach to recordings of an M4.6 earthquake collected by sensors installed in a building and on a nearby athletic field in Matera, Italy, showed that the particle motion of the wave field radiated from the building to the ground was mostly linearly polarized in the radial and transverse planes, while a clear elliptical polarization was observed only in the horizontal plane.

The analysis showed that the wave field radiated from the building and recorded on the ground could be dominated by unconventionally polarized surface waves, i.e. quasi-Rayleigh waves or a combination of quasi-Rayleigh and quasi-Love waves. The results indicated that the energy transmitted from the analyzed vibrating building to the surrounding environment was significant and decreased ground shaking due to the out-of-phase motion between the incoming seismic wave field and that radiated from the building.

How to cite: Parolai, S., Sklodowska, A. M., Petrovic, B., and Romanelli, F.: Evaluation of soil-structure interaction by combining deconvolution of building and field earthquake recordings with polarization analysis: application to the Matera experiment (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10254, https://doi.org/10.5194/egusphere-egu24-10254, 2024.

EGU24-10284 | ECS | Orals | GI4.4

U-NET for Quantitative GPR Imaging 

Giuseppe Esposito, Ilaria Catapano, Francesco Soldovieri, and Gianluca Gennarelli

Ground penetrating radar (GPR) imaging [1] is a well assessed non-destructive technology exploited in many applicative contexts such as structural assessment [2], cultural heritage [3], and others. However, GPR raw data are difficult to interpret since targets do not appear with their geometrical shape but as diffraction hyperbolas because of the probe-target relative motion during the measurement. Linearized Microwave Tomography (MWT) approaches allow retrieving qualitative maps of the probed scene in terms of position and approximate geometry of the targets, thus providing more easily interpretable image of the investigated scenario. Unfortunately, they do not provide quantitative information about the targets in terms of permittivity/conductivity profiles. Recently, deep learning (DL) techniques have been proposed to face this problem. DL approaches are data-driven methods that use proper training data to learn mapping the input data into the desired output. As regards quantitative GPR imaging, different approaches have been proposed in literature, e.g. see [4], [5]. In this contribution, we adopt the well-known Convolutional Neural Network (CNN) U-NET to tackle the quantitative GPR imaging problem. As a novel point compared to the previous works on DL-based quantitative GPR imaging, the network takes in input the linear MWT images instead of the GPR raw data. Such an approach is expected to simplify the learning process as pointed out in [6]. Full-wave simulated data are used for the training of the network and numerical experiments are reported as preliminary assessment of the effectiveness of the proposed strategy.

References

[1] I. Catapano, G. Gennarelli, G. Ludeno, F. Soldovieri, and R. Persico, "Ground-penetrating radar: Operation principle and data processing," in Wiley Encyclopedia of Electrical and Electronics Engineering. Hoboken, NJ: Wiley, 2019, pp. 1–23.

[2] Esposito, G. Gennarelli, G. Ludeno, F. Soldovieri and I. Catapano, "Contactless vs. contact GPR for the inspection of vertical structures," 2023 IEEE Conference on Antenna Measurements and Applications (CAMA), Genoa, Italy, 2023, pp. 164-168, doi: 10.1109/CAMA57522.2023.10352894.

[3] Esposito et al., "The UAV radar imaging prototype developed in the frame of the VESTA project," 2020 IEEE Radar Conference (RadarConf20), Florence, Italy, 2020, pp. 1-5, doi: 10.1109/RadarConf2043947.2020.9266690.

[4] J. K. Alvarez and S. Kodagoda, "Application of deep learning image-to-image transformation networks to GPR radargrams for sub-surface imaging in infrastructure monitoring," 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), Wuhan, China, 2018, pp. 611-616, doi: 10.1109/ICIEA.2018.8397788.

[5] Xie, Q. Zhao, C. Ma, B. Liao, and J. Huo, “U-Net: deep-learning schemes for ground penetrating radar data inversion,” Journal of Environmental and Engineering Geophysics, vol. 25, no. 2, pp.287-292, 2020.

[6] Wei and X. Chen, "Deep-Learning Schemes for Full-Wave Nonlinear Inverse Scattering Problems," in IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 4, pp. 1849-1860, April 2019, doi: 10.1109/TGRS.2018.2869221

How to cite: Esposito, G., Catapano, I., Soldovieri, F., and Gennarelli, G.: U-NET for Quantitative GPR Imaging, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10284, https://doi.org/10.5194/egusphere-egu24-10284, 2024.

EGU24-11196 | ECS | Orals | GI4.4

Combined DAS and seismic nodes acquisition for shallow geophysics purposes around the Scrovegni Chapel in Padua, Italy 

Olga Nesterova, Ilaria Barone, Giorgio Cassiani, Alessandro Brovelli, Verónica Rodríguez Tribaldos, Andrea Galtarossa, Luca Schenato, Luca Palmieri, Luca Peruzzo, Jacopo Boaga, Mirko Pavoni, Haleh Karbala Ali, and Rita Deiana

Active and passive seismic measurements using conventional point sensors (geophones or seismometers) are usually performed to characterize the near surface in urban areas. However, high-resolution studies depending on the measurement scale, require hundreds to thousands of seismic sensors, which involves costly and time-consuming deployments. In recent years, DAS (Distributed Acoustic Sensing) has enabled standard optical fibers to be used as a continuous streamer of seismic sensors, allowing low-cost, high-resolution seismic surveys. The use of DAS technology has become standardized in the oil and gas industry. However, it is still under-exploited in shallow geophysics, where mainly dark fibers (unused telecom fibers) are exploited.
Here, we show preliminary results from a seismic investigation using a combination of DAS and seismic nodes conducted in the vicinity of the Scrovegni Chapel in Padua, Italy. As the site includes buried archaeological remains from various eras, including a Roman amphitheatre, seismic measurements can be used for archaeological prospection. Moreover, to ensure the preservation of this cultural heritage, understanding the mechanical properties of the underlying soil is key for seismic risk assessment.
Active seismic measurements were conducted on November 15, 2023 using a sledgehummer as the active source. Data were recorded using a Silixa iDAS interrogator unit along a 440 m long fiber optic tactic cable deployed in loop configuration inside three 20 m deep boreholes drilled around the chapel connected through a shallow (few cm) horizontal trench. A combination of 1C and 3C seismic nodes were also utilized as surface receivers along six receiver lines, deployed from the well heads and covering different azimuths. Shot points were located every second receiver position along each line. The acquired in-well DAS and surface node data was integrated for a first-arrival travel-time tomography study, allowing the retrieval of compressional-wave velocity vertical sections.

The present study represents the initial phase of our research efforts, which are being conducted partially within the framework of the USES2 project, which receives funding from from the EUROPEAN RESEARCH EXECUTIVE AGENCY (REA) under the Marie Skłodowska-Curie grant agreement No 101072599.

How to cite: Nesterova, O., Barone, I., Cassiani, G., Brovelli, A., Rodríguez Tribaldos, V., Galtarossa, A., Schenato, L., Palmieri, L., Peruzzo, L., Boaga, J., Pavoni, M., Karbala Ali, H., and Deiana, R.: Combined DAS and seismic nodes acquisition for shallow geophysics purposes around the Scrovegni Chapel in Padua, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11196, https://doi.org/10.5194/egusphere-egu24-11196, 2024.

EGU24-13044 | Posters on site | GI4.4

Lava flow magnetic anomaly mapping with UAVs 

Rocco Malservisi, Mel Rodgers, Robert Van Alphen, Charles Connor, Troy Berkey, Rachel Bakowski, and Elisabeth Gallant

Mapping of magnetic anomalies in volcanic areas is a valuable tool to better understand lava flow geometries and dynamics. The high magnetization of basaltic lava allows us to easily identify buried lava flows, providing constraints on the total volume of old erupted material and the flow geometry, while magnetic mapping of volcanic intrusions in country rock enables us to model feeder dike geometry. The low magnetic signals within recent lava flows can identify areas that are still above the Curie temperature, constraining the dynamic of recent flow, and negative anomalies above old empty lava tubes can allow us to identify these hidden conduits.

Traditionally, magnetic anomaly mapping for small regions is performed by walking through the survey area and for larger regions using crewed aircraft. Walking is often daunting, labor-intensive, and potentially dangerous. On the other hand, crewed aircraft are normally expensive and require a significant logistical organization before the survey. Uncrewed aerial vehicles (UAVs) have the potential to bridge the gap and collect a significant amount of high-resolution data in a relatively short time, possibly in areas not easily accessible. UAVs also provide the opportunity to collect data at multiple altitudes, providing a full gradient of the measured field.

Here we present the results from both old and recent lava flows. Little Cones in Nevada (USA) consists of two visible cones erupted ~0.8Ma in the vicinity of the proposed nuclear repository of Yucca Mountain, Nevada. The lava flows from the two cones are partially buried by alluvium and not visible above ground. Our UAV data collection and data inversion allowed us to map the full extent of the lava flow and estimate the total volume of effused material. Our surveys of Hell’s Half Acre (~3000 BCE) lava flow, and Kings’ Bowl (~300 BCE) flow in Idaho (USA) are examples of the use of magnetic anomalies to identify lava tubes, feeding dikes, and flow morphology. Our 2022 survey of the 2018 Pacaya (Guatemala) lava flow is an example of a hard-to-access flow in which we can identify the warmer core that has not yet cooled below the Curie temperature. A survey of the 2018 Lower East Rift Zone eruption of Kīlauea in Hawaiʻi (USA) conducted in 2022 is another example of a negative anomaly possibly associated with areas that are still hot, or lava tubes. In all the surveys we collected a few hundred line kms of data in a few days using two 200 Hz triaxial fluxgate magnetometers mounted on a medium-lift drone. UAV magnetic surveys in volcanic regions are a powerful tool for understanding old and recent volcanic processes.

How to cite: Malservisi, R., Rodgers, M., Van Alphen, R., Connor, C., Berkey, T., Bakowski, R., and Gallant, E.: Lava flow magnetic anomaly mapping with UAVs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13044, https://doi.org/10.5194/egusphere-egu24-13044, 2024.

EGU24-13156 | ECS | Orals | GI4.4

Geophysical surveys to reconstruct the geological model of the urban area of Palermo, Italy. 

Alessandro Canzoneri, Raffaele Martorana, Mauro Agate, Patrizia Capizzi, Maurizio Gasparo Morticelli, and Carollo Alessandra

The plain of Palermo, located along the coastal belt of North-West Sicily, hosts one of the largest and most populous Italian cities. The city experienced a continuous expansion from the 8th century BC, increasing, over time, its population and extent under the control of different dominations; the expansion took place firstly within the historic walls, subsequently outside them. Finally, during the 20th century, the urban area covered most of the plain. The succession of different dominations has produced a clear mutation of the original urban landscape. Numerous streams that once dominated the plain have undergone changes in path, reduced flow, or have been partially embedded or drained.  In addition, after the Second World War, many ruins were accumulated in areas close to the sea causing a deep morphological variation of the coast. Considering that it was only in 1962 that the city had a master plan, the expansion has led to the exacerbation of the natural hazards related to the geological with extensive damage in the neighborhoods where ancient watercourse originally flowed. Moreover, the intense extraction of building stones from underground, which lasted for centuries, has determined the widespread presence of underground cavities in many areas of the city, with negative effects on the stability and safety of buildings. Finally, both because of the uncontrolled urbanization and the geomorphological and geological features of the plain, characterized by important lateral variations of facies, many residential buildings and infrastructure are located in areas subject to seismic risk related to site effects. For all those reasons, defining a geological and geophysical model as much detail as possible is a tool that helps both in the definition of the geological hazard and the associated risk and in planning, design and construction of important civil works. The Department of Earth and Sea Sciences of the University of Palermo is working on the 3D geological modelling of the area of Palermo Plain. The model was built by integrating the numerous borehole data collected in a database and several geophysical acquisitions. The interpolation of the lithological data has allowed to define an initial subsurface model, characterized by strips of alluvial deposits filling incised valleys scoured in a Pleistocene coastal to neritic bioclastic succession.  The model has been integrated using non-invasive geophysical methodologies: recordings of seismic microtremors analyzed according to the Horizontal to Vertical Spectral Ratio technique (HVSR) and Multichannel Analysis of Surface Waves (MASW). These techniques allow to estimate important physical parameters of the subsoil detailing the model without necessarily having to use new drilling and excavations. Indeed, the HVSR data have been inverted in seismographic columns constraining the inversion by means of the S-wave velocities obtained by MASW carried out for the main lithologies outcropping in the plain. The integration of stratigraphic and geophysical data has provided a useful tool for the reconstruction of the geometry and thickness of the geological bodies of the subsoil of Palermo and to define the depth of the seismic bedrock, highlighting the areas subject to geological and seismic risk.

How to cite: Canzoneri, A., Martorana, R., Agate, M., Capizzi, P., Gasparo Morticelli, M., and Alessandra, C.: Geophysical surveys to reconstruct the geological model of the urban area of Palermo, Italy., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13156, https://doi.org/10.5194/egusphere-egu24-13156, 2024.

EGU24-13326 | ECS | Orals | GI4.4

Towards new frontiers for environmental sensing: a UAV-based Active Laser Fluorescence Imaging System  

Chenglong Zhang, Hasib Mustafa, Harm Bartholomeus, and Lammert Kooistra

Sustainable solutions are key in dealing with challenges attributed to food security and climate change. The I-Seed project, funded by H2020, strives to pioneer a novel generation of self-deployable and biodegradable soft miniaturized robots. Drawing inspiration from the morphology and dispersion abilities of plant seeds, these robots are designed for cost-effective, environmentally responsible, in-situ detection of crucial environmental parameters in both air and topsoil. In this concept, Unmanned Aerial Vehicles (UAVs), will be utilized to distribute, localize, and capture the fluorescence signal emitted by the artificial seeds. For the aerial read-out of the fluorescence signal, a prototype of UAV-based Active Laser Fluorescence (ALF) Imaging System was designed. It comprises an RGB camera, a spectral and hyperspectral camera, a laser, and a Time-of-Flight (ToF) Lidar. The integrated setup was evaluated in an optical laboratory. The fluorescence emission from the artificial seeds was measured at a distance of 4m, utilizing varying excitation intensities with an integration time of 3s and temperatures ranging from 5 to 40°C. Results showed that as the sample temperature increased, the peak ratio exhibited changes, making it a valuable indicator for temperature estimation. A similar behavior was observed in modulated excitation, where the fluorescence lifetime varied with temperature. Within the constraints of exposure time for non-saturated pixels, data from RGB pixels also provided insights into the sample temperature. In addition, the developed system was also tested on a linear stage mimicking a flight under field conditions. Present work reveals potential for a revolution in the use of UAVs in environmental sensing.

How to cite: Zhang, C., Mustafa, H., Bartholomeus, H., and Kooistra, L.: Towards new frontiers for environmental sensing: a UAV-based Active Laser Fluorescence Imaging System , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13326, https://doi.org/10.5194/egusphere-egu24-13326, 2024.

EGU24-13716 | Orals | GI4.4 | Highlight

UAV lidar: from volcanoes to forests 

Mel Rodgers, Robert Van Alphen, Rachel Bakowski, Troy Berkey, Taha Sadeghi Chorsi, Rocco Malservisi, Charles. B. Connor, and Timothy. H. Dixon

Improvements in miniaturization and affordability of lidar technology, mainly due to innovation in self-driving cars, means that UAV lidar is now an accessible option for geoscience research. We present applications in which UAV lidar contributes to data collection in ways that would otherwise not be possible in the time frame, budget, and/or with the resolution required.

Volcanoes: Lava flow surface texture can provide information on lava flow dynamics and emplacement. The transition between pahoehoe and a’a flow textures can indicate changes in flow rates and flow thickness, and the morphology of ripples in ropey pahoehoe flows can indicate flow direction. Hell’s Half Acre, Idaho, USA, is a basaltic lava flow that was erupted ~5000 y.a. Analysis of UAV lidar data at this lava field shows lava flow surface texture in sufficient resolution to define cm-scale pahoehoe ripples. In addition, larger scale lava features such as channels and inflation/deflation ridges can be mapped which allows us to understand the dynamics of the lava flow emplacement.

Vegetation: UAV Lidar can be useful for analysis of vegetation canopy, both in stripping canopy (lidar last return) and in using it for tree height (lidar first return). By combining UAV lidar with other airborne data, e.g. multispectral imaging, we can identify and map tree species at Ft de Soto Park, in Florida, USA.

Permafrost: Permafrost thermokarst features can develop rapidly and climate change will cause an increase in these rapid thaw events. With UAV lidar we can strip the vegetation to reveal the underlying ground surface which can then be used to assess and model permafrost processes. UAV surveys are quick and relatively inexpensive (as compared to crewed aviation) and data can be collected in response to a thaw event. We present data from Alaska, USA, at known sites of rapid thermokarst thaw.

UAV lidar, both as a stand-alone dataset, and when integrated with other data streams e.g. multispectral and visible imagery, can provide high-resolution data (both spatial and temporal) on a platform that is relatively low-cost and logistically straightforward to deploy.

How to cite: Rodgers, M., Van Alphen, R., Bakowski, R., Berkey, T., Sadeghi Chorsi, T., Malservisi, R., Connor, C. B., and Dixon, T. H.: UAV lidar: from volcanoes to forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13716, https://doi.org/10.5194/egusphere-egu24-13716, 2024.

EGU24-13974 | ECS | Posters on site | GI4.4

UAV-based Wetland Monitoring: Mapping Coastal Habitats and Changes in Vegetation Height with Digital Terrain Models  

Robert Van Alphen, Kai Rains, Mel Rodgers, Rocco Malservisi, and Timothy Dixon

Monitoring coastal wetlands, particularly mangroves, is increasingly important as the impacts of climate change increase. As sea levels rise and temperature increase, vegetation communities traditionally associated with tropical and sub-tropical coastlines will migrate northward and also inland, along waterways. The transition from coastal marshes and subshrubs to woody mangroves is a fundamental change to coastal community structure and species composition, requiring monitoring. However, this transition is likely to be episodic, complicating monitoring efforts, as mangrove advances are countered by dieback resulting from increasingly impactful storms. Coastal habitat monitoring has traditionally been done through satellite and ground-based surveys. This project investigates the use of UAV lidar and multispectral photogrammetry which can be obtained routinely at higher resolution than satellite derived data, and cheaper and faster than ground-surveys. Using UAV-based methods we monitor and classify coastal habitats, including mangroves, using simple machine learning methods. Between 2020 and 2022 we investigated the use of remote sensing to monitor a multiple use Florida coastal ecosystem. Using UAV lidar we mapped vegetation communities and detected sections of significant canopy loss. Ground truthing verified the occurrence of recent canopy loss at the scale of individual snag remnants of woody mangrove associates, i.e., buttonwood trees (Conocarpus erectus). Using UAV lidar and multispectral photogrammetry data as inputs into a random forest model, we created several models of habitat classification. Training inputs included 2000-pixel and 5000-pixel data subsets. Initial results were resampled to match the size of tree crown in the field area creating four classification schemes. All classifications were validated using standard metrics. Mangrove habitat identification using the resampled 2000-pixel model has 85% producer’s accuracy and 80% user’s accuracy.  UAV surveys combined with machine-learning streamline coastal habitat monitoring and facilitate repeat surveys to assess the effects of climate change.

How to cite: Van Alphen, R., Rains, K., Rodgers, M., Malservisi, R., and Dixon, T.: UAV-based Wetland Monitoring: Mapping Coastal Habitats and Changes in Vegetation Height with Digital Terrain Models , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13974, https://doi.org/10.5194/egusphere-egu24-13974, 2024.

EGU24-14275 | Posters on site | GI4.4

Enhancing UAS-based Earth Science Through Coordinated Facility Support 

Christopher Crosby, Scott Tyler, Glen Mattioli, Adrian Harpold, Craig Glennie, Joe Wartman, and Christopher Kratt

Uncrewed Aircraft Systems (UAS) represent an evolving and important set of tools for earth science and engineering. While low-cost uncrewed aircraft systems (UAS) can be acquired and operated by individual researchers for simple surveying or photography, very high-resolution observations using advanced sensors are often out of reach for most researchers. Over the past 5 years, U.S. National Science Foundation (NSF)-supported facilities have developed specialized UAS and UAS sensor capacity; however, this has largely been done independently and at very modest levels of support. Nevertheless, there has been growing success in supporting NSF and other federal researchers’ needs in the areas of topographic mapping, geothermal imaging, wildlife inventories, post-disaster monitoring and critical zone observations. 

To help make UAS resources more widely available, five NSF-supported Earth science facilities (NCALM, the GAGE Facility operated by the EarthScope Consortium, NHERI-RAPID, OpenTopography, and CTEMPs) have joined together to create the UAS Federation (UASFederation.org). Each of these facilities have supported UAS activities in the past, but they were generally small components of each facility, and often not well advertised or subscribed. Through formal coordination and a common portal, this new federation effort will enable Earth science researchers to access a much broader suite of sensors, aircraft, ​​FAIR data archiving resources, and expertise.

The UAS Federation currently manages over 35 aircraft (6 heavy lift airframes, 7 medium lift, and at least 23 light duty airframes) along with remote-sensing systems that collect a broad range of data, including lidar; airborne magnetics; hyperspectral, multispectral, and thermal images, and albedo. Numerous cameras with RGB capacity are also available. In addition, we can provide access to software and over 140 archived UAS data sets. In the future, the UAS Federation will be developing and distributing training and instruction support. 

How to cite: Crosby, C., Tyler, S., Mattioli, G., Harpold, A., Glennie, C., Wartman, J., and Kratt, C.: Enhancing UAS-based Earth Science Through Coordinated Facility Support, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14275, https://doi.org/10.5194/egusphere-egu24-14275, 2024.

EGU24-15113 | Orals | GI4.4 | Highlight

Long-term geophysical monitoring of safety critical geotechnical infrastructure slopes 

Jonathan Chambers, Paul Wilkinson, Phil Meldrum, Oliver Kuras, Russell Swift, Jason Ngui, Adrian White, Mihai Cimpoiasu, Harry Harrison, Rosa Maleki, James Boyd, Ben Dashwood, Edward Bruce, Shane Donohue, Jessica Holmes, Ross Stirling, Jim Whiteley, and Andrew Binley

Robust and timely assessment of the condition of geotechnical infrastructure assets (e.g. cuttings, embankments, dams) is essential for cost effective maintenance and engineering interventions to prevent failure events. Infrastructure slopes (in transportation, utilities and water management) are experiencing increasingly high levels of failure and require considerable resources to maintain; in the order of hundreds of millions of pounds per year in the UK alone. The issue of accelerating asset deterioration is being exacerbated by the greater prevalence of extreme weather events. Conventional monitoring techniques are still dominated by surface observations, which provide infrequent information and deliver very few insights into subsurface deterioration processes which typically precede surface expressions of deterioration. Here we describe the development of novel geoelectrical imaging technology to monitor and assess the internal condition of infrastructure slopes in four-dimensions. In particular, we outline a workflow in which time-lapse geophysical models are used to inform estimates of soil moisture and suction distributions, and we consider the challenges associated with the deployment of geophysical monitoring systems on operational geotechnical assets. Examples are given from long-term field experiments on transportation and water management earthworks. We propose that novel geophysical monitoring complements more traditional forms of asset assessment to significantly enhance the resilience of safety critical infrastructure through improved subsurface information provision and decision support.

How to cite: Chambers, J., Wilkinson, P., Meldrum, P., Kuras, O., Swift, R., Ngui, J., White, A., Cimpoiasu, M., Harrison, H., Maleki, R., Boyd, J., Dashwood, B., Bruce, E., Donohue, S., Holmes, J., Stirling, R., Whiteley, J., and Binley, A.: Long-term geophysical monitoring of safety critical geotechnical infrastructure slopes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15113, https://doi.org/10.5194/egusphere-egu24-15113, 2024.

EGU24-15700 | Orals | GI4.4

Selection of bundle block adjustment parameters in UAV surveys of underground mining-induced displacements 

Paweł Ćwiąkała, Elzbieta Pastucha, Edyta Puniach, and Wojciech Gruszczyński

Measurements for determining terrain surface deformations that are caused by underground mining require high measurement accuracies to be achieved. Uncrewed aerial vehicles (UAVs) have not been widely used for this purpose. The presentation presents the process of selecting optimal bundle block adjustment (BBA) parameters for UAV-acquired data. The analyses were carried out for 25 measurement series on a test field of 2 km2. A total of 59 ground control points (GCP) and check points (CP) were used in the study. The analyzed parameters included: 

  • the GCP accuracy: 15mm or 25mm, 
  • the GCP number: 9 or 23, 
  • the tie point accuracy: 1px or 2px,
  • the impact of the tie point filtration, 
  • the impact of the additional corrections of camera calibration (based on the 96-parameter Fourier series) not included in Brown’s model,
  • the accuracy of the coordinates of the projection centers of the images: the values estimated by the GNSS receiver, or 50mm or 100mm.

The final result of the study is the identification of BBA parameters that allow the highest accuracy of UAV photogrammetry products to be achieved.

How to cite: Ćwiąkała, P., Pastucha, E., Puniach, E., and Gruszczyński, W.: Selection of bundle block adjustment parameters in UAV surveys of underground mining-induced displacements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15700, https://doi.org/10.5194/egusphere-egu24-15700, 2024.

EGU24-16127 | Orals | GI4.4

Determination of land deformation indices based on UAV-derived very-high-resolution images 

Edyta Puniach, Wojciech Gruszczyński, Paweł Ćwiąkała, Wojciech Matwij, and Katarzyna Strząbała

In recent years, uncrewed aerial vehicle (UAV)-based photogrammetry has developed rapidly and is increasingly used for monitoring and determining displacements. The presentation discusses the author's solutions for the automatic determination of horizontal and vertical displacements of land surface in urban areas, dedicated to very-high-resolution UAV-photogrammetry products. The processing path is based on orthomosaics and digital elevation models and implements normalized cross-correlation for matching multi-temporal images. Its integral part is the process of semi-automatic removal of outliers. As a result of data processing, displacement vectors are determined in a regular grid, which constitute the basis for determining other indices of terrain deformation, such as ground tilts and horizontal deformations. Based on a comparison with reference data, it was estimated that the root mean square error of determining the displacements is 1-2 pixels for the horizontal components and 2-3 pixels for the vertical component. Therefore, the components of ground tilt and horizontal deformation can be determined based on UAV photogrammetry with a root mean square error of 0.3 pixels.

How to cite: Puniach, E., Gruszczyński, W., Ćwiąkała, P., Matwij, W., and Strząbała, K.: Determination of land deformation indices based on UAV-derived very-high-resolution images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16127, https://doi.org/10.5194/egusphere-egu24-16127, 2024.

EGU24-16206 | Posters on site | GI4.4

Integrated geophysical approaches for geo-hazards evaluation in urban areas: first activities in urban pilot sites of Basilicata region (southern Italy) 

Valeria Giampaolo, Gregory De Martino, Maria Rosaria Gallipoli, Giovanni Gangone, Luigi Martino, Angela Perrone, Vincenzo Serlenga, Tony Alfredo Stabile, and Vincenzo Lapenna

This work describes first activities carried out in the frame of WP7-7.4 task of the ITINERIS “Italian Integrated Environmental Research Infrastructures System” project (PNRR M4C2 Inv.3.1 IR), financed by European Union – Next Generation EU.

An innovative integrated geophysical approach for geohazard evaluation in urban areas has been proposed with the aim of providing scientific and open digital data of multi-scale and multi-resolution near-surface geophysical observations to the scientific community, practitioners, and decision-makers according to the Digital Earth concept. This will be achieved by: a) acquiring cutting-edge geophysical equipment suites to enhance the existing ones; b) establishing a service aimed at integrating the data from a variety of geophysical sensors; c) investing in the next-generation technologies and enabling FAIR data access.

One of the three pilot sites of this project is the Basilicata region (southern Italy), that is a predominantly mountainous zone affected by high seismic and hydrogeological risks. Therefore, it is well-suited to test and integrate the different geophysical methodologies, with particular attention to the seismic and electromagnetic methods. Geophysical data collected by each experiment will be integrated into the ICT project platform and made available to the scientific community.

In detail, a part of Activity 7.4 focuses on the innovative use of the ERT method as an advanced observing system, able to describe the spatio-temporal changes of the resistivity patterns within the depth range 0-1 km. Preliminary tests have been conducted in some urban areas affected by landslide phenomena. The planned activity will also leverage machine learning technologies for geophysical data processing and analysis.

Another action aims at enhancing the suitability of geophysical infrastructures for the characterization of urban areas, specifically for seismic risk mitigation purposes. Great attention is placed on the characterization of the urban subsoil, the overlying-built environment, and their mutual interaction to identify areas of cities where the possible resonance effect between the soil and the built environment during earthquakes may cause increased damage; this aspect is being studied and evaluated for the city of Potenza (southern Italy).

The last part of the activity is devoted to designing an experiment aimed at integrating DAS measurements (to be carried out using a 4 km long fiber-optic cable already installed in the industrial area of Tito, located close to the urban area of Potenza), ERT surveys, and seismic array data for a multi-parametric characterization of the near surface and monitoring its changes over time. This will offer unique opportunities for the scientific community to test and improve different methods in a controlled environment, while also assessing the effectiveness of monitoring the near-surface through DAS-recorded ambient noise.

How to cite: Giampaolo, V., De Martino, G., Gallipoli, M. R., Gangone, G., Martino, L., Perrone, A., Serlenga, V., Stabile, T. A., and Lapenna, V.: Integrated geophysical approaches for geo-hazards evaluation in urban areas: first activities in urban pilot sites of Basilicata region (southern Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16206, https://doi.org/10.5194/egusphere-egu24-16206, 2024.

EGU24-16764 | Posters on site | GI4.4 | Highlight

Combined geological and UAS aerial photogrammetric surveys for a better understanding of volcanic phenomena: the Ischia island (Italy) case study. 

Enrica Marotta, Sandro de Vita, Rosario Avino, Gala Avvisati, Pasquale Belviso, Antonio Carandente, Orazio Colucci, Eugenio Di Meglio, Mauro Antonio Di Vito, Silvia Fabbrocino, and Rosario Peluso

Integrating geological field with drone remote sensing surveys is becoming a common methodology to estimate some volcanological parameters. For example, knowing the volumes of domes and lava flows in volcanic areas is important to infer the magnitude of an eruption and the potential volcanic hazards in a defined area. It is not always possible to define the correct geometry of these bodies only from field surveys, as they often occur in remote and inaccessible areas.

One possible way to overcome these difficulties is to use drone aerophotogrammetric surveys, with a drone equipped with a high-resolution camera, and then processing the images with digital photogrammetric techniques to create a three-dimensional model of the terrain. At the same time, UAS aerophotogrammetric surveys alone are not sufficient to fully characterize the volume of domes and lava flows, as they do not provide information on their basal surface geometry.

Therefore, it is necessary to combine geological and drone aerophotogrammetric surveys. Integrating data from both methods allows to obtain a more comprehensive and reliable estimation of the volume of domes and lava flows, as well as a better understanding of their formation and evolution processes.

A similar integrated approach is being carried out on the island of Ischia where, in the last period of activity (13/10 ka – 1302 CE), at least 22 effusive eruptions produced lava flows and domes. A first attempt to estimate the volume of the erupted lavas was made some years ago superimposing a mask representative of the extension of the lava bodies on a Digital Elevation Model and then calculating the difference with respect to a set of flat theoretical base surfaces. A detailed geological survey, combined with geomorphological analysis, has been performed on some selected lava bodies obtaining a better definition of their base surfaces geometry.

Aerial photogrammetric surveys, obtained from aerial photographs taken with the use of UAS equipped with a visible-range camera, was used to obtain the geomorphological features. It was possible to produce the points cloud of the areas of interest and orthorectify and georefer the data.

Later the different constituent elements of the points cloud were classified separately, distinguishing anthropogenic vs. natural elements.

Volumes of the lava bodies were determined by operating profiles and sections along crossed directions, defined on the basis of the assessment of the underground pattern of the volcanic deposits. A high-resolution digital terrain model of the entire volcanic body was obtained this way.

This result was achieved through the use of specific software (Pix4D and Agisoft).

The methodology was verified by overlaying the DTM (5m) and DSM (1m) of the Campania Region and the Metropolitan City of Naples respectively.

Previous estimations revealed a widespread volume underestimation especially where basal geometry differs significantly from that of a horizontal or simply tilted plane. This led to a recalculation of the volumes and suggests to apply the tested methodology to all lava bodies of the last period of volcanic activity at Ischia.

How to cite: Marotta, E., de Vita, S., Avino, R., Avvisati, G., Belviso, P., Carandente, A., Colucci, O., Di Meglio, E., Di Vito, M. A., Fabbrocino, S., and Peluso, R.: Combined geological and UAS aerial photogrammetric surveys for a better understanding of volcanic phenomena: the Ischia island (Italy) case study., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16764, https://doi.org/10.5194/egusphere-egu24-16764, 2024.

EGU24-18861 | Orals | GI4.4 | Highlight

The hidden eruption: 21 may 2023 Etna (Italy)  

Emanuela De Beni, Massimo Cantarero, Luigi Mereu, Laura Pioli, Cristina Proietti, Francesco Romeo, Simona Scollo, and Salvatore Alparone

We report the results of field and Unoccupied Aerial System (UAS) surveys carried out after the 21 May 2023 eruption of Etna (Italy). This event occurred under terrible weather conditions that prevented its observation by the INGV-OE (Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo) surveillance video and thermal camera network. After some weeks of Strombolian activity at the South-East Crater (SEC), which started on the 4th of May, a dramatic increase in the volcanic tremor, localized underneath the SEC, marked the onset of lava fountain at 5.30 UTC on the 21st of May. The lava fountain, lasting at least 4 hours, formed a lava flow and a plume about 10 km high, while ash fell on the southwest flank of the volcano. The bad weather condition, that consisted in strong storm and dense clouds covering the summit of Etna, did not permit to observe the phenomenon. Luckily the multi-parameter monitoring stations scattered around the volcano were working. In particular, the volcanic tremor, the clinometric and the borehole dilatometer signals clearly indicated the onset of a lava fountains. An unusual snow fall (considering it was springtime) did not allow any direct survey of the area until two weeks later, and the continuing cloud cover hindered remote observation. When MapLAB staff, of the INGV-OE, finally reached the eruptive scenario to perform a UAS survey, they realized that a volcanoclastic deposit overlapped the middle portion of the lava flow. During the survey, the deposit has been also studied and sampled along its extension. Thanks to a Structure from Motion software a 3D reconstruction of the SEC, the lava flows and the deposit has been done. The data collected allowed for detailed mapping, quantification and characterization of the proximal and distal products (300 m and more than 800 m away from the vent, respectively). The presented results increase knowledge about the SEC instability and collapse phenomena, of which we have become increasingly aware over the past two decades. These hazards could present a significant threat for people walking along touristic path ways near Etna summit craters.

How to cite: De Beni, E., Cantarero, M., Mereu, L., Pioli, L., Proietti, C., Romeo, F., Scollo, S., and Alparone, S.: The hidden eruption: 21 may 2023 Etna (Italy) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18861, https://doi.org/10.5194/egusphere-egu24-18861, 2024.

EGU24-19527 | Posters on site | GI4.4 | Highlight

Development of a drone-based measurement system for real-time monitoring of volcanic gas composition 

Thorsten Hoffmann, Nicole Bobrowski, and Niklas Karbach

Studying volcanic gas emissions is an important method to obtain information about volcanic systems and providing insight into magmatic processes. MultiGAS instruments allow to measure SO2 and CO2, alongside meteorological data which are important parameters in volcanic monitoring. In the past decade, these MultiGAS instruments have been adapted to be carried on drones, which enables the researchers to measure the gas composition from a safe distance as the drone operator can operate from farther away, probably even from a parking lot, therefore eliminating the need to reach the sampling site by foot. Additional, drone based measurements improve the possibility to undertake source specific measurements with a negligible influence of soil - as well as fumarole degassing. 

Frequent calibrations, preferably with the same environmental parameters (T, RH, p) that prevail during the measurement, are important to measure correct concentrations. However, as calibration equipment can be quite heavy and takes a long time to set up, it is not practical to carry calibration equipment to a regular used measurement site.

We therefore propose to build a stationary measurement station with the aim of quickly taking correct measurements with minimal preparation and operating effort. The station will contain the aforementioned calibration equipment, a solar power supply for charging, a base station for all radio communications with the drone and sensors, and a data server with internet access to view the measurement data remotely. In addition to a typical MultiGAS instrument, a drone-based DOAS system will further expand the station’s capabilities. The two instruments will be easily exchangeable by attaching the sensors with rails to the main body of the drone.

How to cite: Hoffmann, T., Bobrowski, N., and Karbach, N.: Development of a drone-based measurement system for real-time monitoring of volcanic gas composition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19527, https://doi.org/10.5194/egusphere-egu24-19527, 2024.

EGU24-19790 | Posters on site | GI4.4

Multi scale surface temperature monitoring (by UAS and Satellite) on quiescent Volcanoes. 

Eliana Bellucci Sessa, Rosario Avino, Gala Avvisati, Pasquale Belviso, Maria Fabrizia Buongiorno, Teresa Caputo, Antonio Carandente, Silvia Fabbrocino, Federico Rabuffi, Malvina Silvestri, Rosario Peluso, and Enrica Marotta

The study of thermal anomalies linked to volcanic activity is an indispensable tool to understand the state of volcanoes and for their monitoring. Over time, the tools for studying anomalies have improved over time and from this perspective, unmanned aerial systems (UAS) have made it possible to bridge the gap between space-based and terrestrial remote sensing data. UAS provide very high resolution spatial data, which allows the detection of thermal anomalies of even smaller extent and with lower temperatures.We made a comparison in different areas between UAS and satellites such as Pisciarelli, Monte Nuovo, Biancane and Solfatara.Furthermore, the continuous monitoring of the Pisciarelli area has allowed us to understand the best method for acquiring data such as the flight plan, mosaicking, analyzes for comparisons with other satellite systems and for the future calculation of the heat flow.

How to cite: Bellucci Sessa, E., Avino, R., Avvisati, G., Belviso, P., Buongiorno, M. F., Caputo, T., Carandente, A., Fabbrocino, S., Rabuffi, F., Silvestri, M., Peluso, R., and Marotta, E.: Multi scale surface temperature monitoring (by UAS and Satellite) on quiescent Volcanoes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19790, https://doi.org/10.5194/egusphere-egu24-19790, 2024.

EGU24-19909 | Orals | GI4.4

The new urban strong motion array along the Crati Valley. 

Elisa Zambonelli, Daniele Cirillo, Donato Talone, Luisa Filippi, Alfredo Ammirati, Sebastiano Sirignano, Giovanni Costa, Veronica Pazzi, Simone Francesco Fornasari, Federica Ferrarini, Francesco Brozzetti, Giusy Lavecchia, and Rita de Nardis

The Italian Strong Motion Network (RAN Rete Accelerometrica Nazionale) currently comprises 705 stations strategically distributed throughout Italy. Following the seismic events in L'Aquila in 2009, the Civil Protection Department is also working on a project for the implementation of new accelerometric arrays in urban and sub-urban areas along the main Italian basins.

Presently, operational arrays include those in Central and Southern Italy, such as the Aterno Valley Array, Sulmona Basin Array, and in-hole accelerometers in San Giuliano di Puglia. In December 2023, a new accelerometric array was installed in the Crati Valley.

Crati Valley is located in high seismic area of northwestern Calabria, between Cosenza and Rende, and it is recognized as the Crati Basin—an extensional basin dating back to the Plio-Olocene period. The valley is delineated by north-south-trending normal faults (Brozzetti et al., 2017; Tortorici et al., 1995), serving as the boundary between the Sila and Coastal Range Mountain ranges. The Crati Basin, stretching over 60 km, is flanked by the Catena Costiera ridge to the west and the Sila Massif to the east.

In instrumental time the area is characterized by meager seismicity, but historically, the Crati Basin experienced moderate-to large M >~6.0 (1870, Io =10 MCS; 1854, Io =10 MCS; 1184, Io =9 MCS) and moderate earthquakes (1767, Io =8 MCS; 1835, Io =10 MCS; 1886, Io =7 MCS; 1913, Io=8 MCS).

The array in the Crati Valley is composed of 7 stations arranged linearly both longitudinally and transversely along the valley, covering a total extension of 5 km. The average spacing between seismic stations is approximately 2 km. The reference site is located in the old part of the city of Cosenza and was already a part of the national accelerometric network.

The new accelerometric array in the Crati Valley contributes to ongoing seismic monitoring efforts, enhancing our understanding of site response and seismic hazards in the region.

How to cite: Zambonelli, E., Cirillo, D., Talone, D., Filippi, L., Ammirati, A., Sirignano, S., Costa, G., Pazzi, V., Fornasari, S. F., Ferrarini, F., Brozzetti, F., Lavecchia, G., and de Nardis, R.: The new urban strong motion array along the Crati Valley., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19909, https://doi.org/10.5194/egusphere-egu24-19909, 2024.

EGU24-20436 | ECS | Posters on site | GI4.4 | Highlight

Assessment of railway infrastructure slope failure by automated time-lapse ERT monitoring 

Zeynab Rosa Maleki, Paul Wilkinson, Russell Swift, Philip Meldrum, Harry Harrison, Ximena Katherine Capa Camacho, Jason Ngui, Oliver Kuras, Julian Harms, Gavin Jessamy, Shane Donohue, Jessica Holmes, Ross Stirling, and Jonathan Chambers

This study underscores the need for subsurface imaging and monitoring techniques to offer timely information on railway embankment condition and to contribute to the decision-making processes needed to minimise the risks of catastrophic slope failure. We investigate electrical resistivity tomography (ERT) as a means of providing railway earthwork asset condition assessment information through the deployment of a bespoke ERT monitoring system (PRIME – the Proactive Infrastructure Monitoring and Evaluation system), which has been specifically developed for geotechnical monitoring applications.

We focus on two test sites, Botley and Withy Beds, which are situated on mainline railway embankments in the UK near Southampton and London respectively. Both embankments have long histories of slope instability and are constructed from London Clay (a high plasticity clay widely associated with ground deformation problems). Long-term ERT monitoring infrastructure has been deployed across both sites to enable imaging of subsurface heterogeneity and to monitor subsurface moisture content variations. At Botley a grid of electrodes extending from the embankment shoulder to toe, over an area of ~20 by 30 m, was deployed to enable time-lapse 3D imaging of a progressive rotational failure at the site, whilst at Withy Beds a line of electrodes was deployed along the embankment toe to enable time-lapse 2D imaging for a ~300m length of susceptible embankment.  Manual geodetic (total station and LiDAR) monitoring of the slope geometry and electrode positions, and conventional geotechnical monitoring using temperature, soil moisture and matric suction sensors have also been used at the sites to validate the results of the ERT monitoring. In additional, laboratory petrophysical testing of samples from the sites has been used to establish relationships between resistivity, moisture content and matric suction.

More than three-years of ERT monitoring data have been collected from the sites. Initial analyses of the results have shown strong correlations between the conventional geotechnical monitoring results and ERT derived estimates of soil moisture. At the site scale, a remarkably clear low-resistivity layer can be seen in the middle embankment segment of Botley, which suggests a high clay content and likely limited hydraulic permeability. The properties of this layer, in conjunction with time-lapse ERT observations made during periods of heavy rainfall, have revealed the hydrological functioning of the slope and the strong influence of evapotranspiration associated with clusters of mature trees. On the other hand, the Withy Beds embankment shows less intense drying and wetting patterns, even though noticeable fluctuations in resistivity suggest the presence of localised zones of moisture build-up. The sandy sections at the Withy Beds site are consistently dry even after rainfall, which permits water to seep into the clay layer beneath. On the other hand, the clay lands have higher moisture content and exhibit summertime surface drying.

In this study we have provided unprecedented insights, in terms of ERT monitoring duration and spatiotemporal resolution, into the structure and moisture dynamics of mainline railway embankments. ERT has been demonstrated as novel means of providing operationally relevant condition monitoring information to support the management of vulnerable railway earthworks associated with complex ground conditions.

How to cite: Maleki, Z. R., Wilkinson, P., Swift, R., Meldrum, P., Harrison, H., Capa Camacho, X. K., Ngui, J., Kuras, O., Harms, J., Jessamy, G., Donohue, S., Holmes, J., Stirling, R., and Chambers, J.: Assessment of railway infrastructure slope failure by automated time-lapse ERT monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20436, https://doi.org/10.5194/egusphere-egu24-20436, 2024.

EGU24-21488 | Orals | GI4.4 | Highlight

Remote sensing and in situ geophysical techniques for the hydrogeological hazard assessmnet in urban area: the Gorgoglione (Basilicata region, Southern Italy) case study. 

Angela Perrone, Jessica Bellanova, Giuseppe Calamita, Francesco Falabella, Maria Rosaria Gallipoli, Erwan Gueguen, Antonio Pepe, Sabatino Piscitelli, Vincenzo Serlenga, and Tony Stabile

The vulnerability to landslides of the Basilicata territory (southern Italy) depends on different causes such as the outcropping lithologies, the morphology of the reliefs, neotectonics, seismicity, etc. Currently all 131 municipalities in this region are involved by landslides (IFFI Project 2020) that very often have affected the continuous and discontinuous urban fabric as well as industrial or commercial areas. In many cases, as for example in the Gorgoglione test site, the state of emergency has been declared with evacuation orders for residential buildings and commercial activities (Perrone et al., 2021; Calamita et al., 2023).

Traditional direct techniques, such as geotechnical boreholes, offer point-specific information but can be highly invasive, leading to potential damage to economic and cultural resources such as archaeological sites and underground utilities in the upper layers of the subsoil. In the context of investigating landslides in urban areas, alternative approaches may be more suitable. A significant contribution can be achieved through the combined utilization of remote sensing and in situ geophysical techniques. (Perrone et al., 2006).

In this work, satellite and ground based SAR interferometry, electrical resistivity tomography (ERT) and single-station seismic ambient noise measurements (HVSR) have been integrated for investigating the phenomenon affecting the Gorgoglione urban area (Fig.1), located in the south-western part of Matera Province (Basilicata Region). SAR interferometry results provided information on the activity status of the phenomenon. The ERT and the HVSR allowed the reconstruction of the subsoil geological setting, the identification of physical discontinuities correlated with lithological boundaries and sliding surfaces and the location of high water content areas. This information was used to assess the landslide residual risk, to plan and implement the risk mitigation actions and to correctly design the remediation works.

References

Calamita G., Gallipoli M.R., Gueguen E., Sinisi R., Summa V., Vignola L., Stabile T.A., Bellanova J., Piscitelli S., Perrone A.; 2023: Integrated geophysical and geological surveys reveal new details of the large Montescaglioso (southern Italy) landslide of December 2013. Engineering geology 313 , pp. Art.n.106984-1–Art.n.106984-16.

IFFI Project (Inventario dei Fenomeni Franosi in Italia). ISPRA, Dipartimento Difesa del Suolo, Servizio Geologico d’Italia. Available online: http://www.progettoiffi.isprambiente.it/cartanetiffi/ (accessed on May 2020)

Perrone A., Canora F., Calamita G., Bellanova J., Serlenga V., Panebianco S., Tragni N., Piscitelli S., Vignola L., Doglioni A., Simeone V., Sdao F., Lapenna V.; 2021: A multidisciplinary approach for landslide residual risk assessment: the Pomarico landslide (Basilicata Region, Southern Italy) case study. Landslides 18, 353–365.

Perrone A., Zeni G., Piscitelli S., Pepe A., Loperte A., Lapenna V., Lanari R.; 2006: Joint analysis of SAR interferometry and electrical resistivity tomography surveys for investigating ground deformation: the case-study of Satriano di Lucania (Potenza, Italy). Engineering Geology 88, 260–273.

How to cite: Perrone, A., Bellanova, J., Calamita, G., Falabella, F., Gallipoli, M. R., Gueguen, E., Pepe, A., Piscitelli, S., Serlenga, V., and Stabile, T.: Remote sensing and in situ geophysical techniques for the hydrogeological hazard assessmnet in urban area: the Gorgoglione (Basilicata region, Southern Italy) case study., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21488, https://doi.org/10.5194/egusphere-egu24-21488, 2024.

EGU24-1085 | ECS | Posters on site | GM2.6

Quantifying the Importance of Wind Erosion of Bare Peat: Initial Insights from Field Measurements and Wind Tunnel Modelling 

Yuzhe Zang, Jeff Warburton, Lian Gan, and Richard Hardy

Peat erosion and degradation contribute to 2-6% of total global emissions of carbon each year. Wind erosion of bare peat surfaces, is a significant component of erosion. However, how rapidly-changing bare peat surface aerodynamic properties affect erosion processes have not been fully quantified. This study investigates how the spatial and temporal characteristics of peatland wind erosion are controlled by the aerodynamic properties of the bare peat surface. Field measurements of local meteorology, peat surface properties and peat flux from a 3-ha bare area of upland blanket peat (North Pennines, UK), have been analysed during a sustained period of strong winds and rainfall (November to April 2023). Results demonstrate that the eroded peat flux is correlated with the southwest prevailing wind direction and as velocity increases, the flux becomes more focussed to the southwest (225°). Windward-facing peat fluxes are 4-9 times higher than those in the leeward direction. The vertical wind velocity profile over the bare peat shows a logarithmic pattern with height which is mirrored in the peat flux profile. Average friction velocity is only partially correlated to the peat flux during the strongest wind events suggesting that peat surface aerodynamic characteristics (roughness) also affect the pattern and magnitude of eroded peat flux. To investigate this hypothesis in greater detail wind tunnel experiments with a 3-D printed 1:1 rough peat surface model (0.5 x 0.7 m, average geometric roughness height 0.0345 m) in a large recirculating wind tunnel (2 x 0.6 x 0.6 m) are conducted to acquire the wind velocity profile over the peat boundary surface at 12 carefully selected characteristic locations. Experiments are conducted under free stream wind velocities at 2, 4, 6, 8, 10 m s-1 which are representative to the wind velocities observed in the field. Velocity measurements are taken by traversing a 5-hole probe in a normal direction with a spatial resolution of 2 mm within the boundary layer. Velocity signals are sampled at 500 Hz over 12 seconds at each sampling location. Flow properties including time-mean velocity, turbulence kinetic energy and wall shear stresses over the rough peat surface are analysed. These provide details of the wind flow field over the peat microtopography and allow us to investigate spatially and temporally resolved airflow dynamics. Further work using numerical modelling is planned to test the field observations and wind tunnel experiments and define in detail how surface roughness influences erosion of bare peat.

How to cite: Zang, Y., Warburton, J., Gan, L., and Hardy, R.: Quantifying the Importance of Wind Erosion of Bare Peat: Initial Insights from Field Measurements and Wind Tunnel Modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1085, https://doi.org/10.5194/egusphere-egu24-1085, 2024.

EGU24-3160 | ECS | Orals | GM2.6

Instability of Antidune Incipience under Low Submergence Conditions  

Sofi Farazande, Ivan Pascal, and Christophe Ancey

Investigating the stability of river bedforms is essential for understanding their occurrence and evolution over time. Whereas the formation of ripples and dunes has been extensively studied [1, 2], little is known about antidune stability in the early stages. Our research aims to fill this gap by focusing on antidune incipience in gravel-bed streams under low submergence conditions. Based on Vesipa et al. (2014), who distinguished between convective and absolute instabilities of bedforms [3], we investigated the behavior of the antidunes in the early stages of their formation. We conducted experiments in a narrow flume and studied how key flow factors (e.g., the Froude number, relative submergence, and initial perturbation) affect antidune dynamics. By filming the bed evolution from the sidewall, we determined the antidune wavelength and amplitude as a function of space and time in order to provide empirical insights that complement the theoretical framework.

 

[1] Colombini, M., and Stocchino, A. (2011). Ripple and dune formation in rivers. Journal of Fluid Mechanics, 673, pp. 121-131.

[2] Fourrière, A., Claudin, P., and Andreotti, B. (2010). Bedforms in a turbulent stream: formation of ripples by primary linear instability and of dunes by nonlinear pattern coarsening. Journal of Fluid Mechanics, 649, pp. 287-328.

[3] Vesipa, R., Camporeale, C., Ridolfi, L., and Chomaz, J. M. (2014). On the convective-absolute nature of river bedform instabilities. Physics of Fluids, 26, 124104

How to cite: Farazande, S., Pascal, I., and Ancey, C.: Instability of Antidune Incipience under Low Submergence Conditions , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3160, https://doi.org/10.5194/egusphere-egu24-3160, 2024.

Debris flows are classical two-phase flows that can be enhanced by entraining multi-grain sizes of sediments from the bed as they rush down steep slopes, in which particle segregation is related to assessing the potential hazards. However, understanding the characteristics and fluid-particle interaction mechanisms remains challenging. Here an existing depth-averaged two-phase continuum flow model is further improved by incorporating the effects of pore-fluid pressure and bed sediment conditions on erosion. To demonstrate its reliability, we compare numerical solutions with measurements of thickness, front location, and bed deformation in two sets of USGS large-scale experimental debris flows over erodible beds. The following physical understandings are obtained. First, the positive effects of pore-fluid pressure and coarse bed materials on erosion rates are numerically reproduced. Moreover, an additional mechanism for this phenomenon has been revealed. Specifically, debris flows on steep slopes are likely to fall into a high shear stress regime, under which conditions the sediment transport capacity always takes a maximum value and is independent of the sediment size. Therefore, the sediment settling velocity that is proportional to the sediment size affects the erosion rate directly. Second, we probe into the non-dimension number and energetics of the debris flows to find it necessary to incorporate water-sediment and particle-particle interactions into reproducing the debris flow processes. Third, two kinds of mechanisms for particle size coarsening in the head region of the debris flow are resolved: on the one hand, they can be incorporated and retained there if the debris flow acquires sediment from the bed in transit due to considering the hiding/exposure mechanisms and on the other hand, they can migrate to the head by preferential transport. Furthermore, a series of idealized tests were conducted to explore the factors contributing to the segregation of particles within a debris flow. The longitudinal particle segregation was reproduced by incorporating the shear-induced non-uniform vertical distributions of velocity and sediment concentrations, the visco-inertial rheology, as well as the grain-size heterogeneity into the modelling. Sensitive analysis shows that the transport of fine particles is more inhibited by the interaction of the flow, contributing to the larger transportation velocity of the coarse particle. We further observed that the water content, the slope, and the particle size would have positive effects on the longitudinal size segregation in the head region, contrasting with the negative effects of the flow viscosity. These factors affecting the segregation ratio are attributed to the changes in the ratio of the Reynolds Number of the flow between fine and coarse particle.

How to cite: Hu, P., Lyu, B., Li, J., Li, W., and Cao, Z.: Numerical investigation about propagation characteristics and hydro-sediment-morphodynamic interactions of multi-sized debris flow with a two-phase continuum model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4798, https://doi.org/10.5194/egusphere-egu24-4798, 2024.

EGU24-6100 | Posters on site | GM2.6

Measured distributions of velocity and concentration for intense transport of bimodal lightweight sediment in tilting flume 

Vaclav Matousek, Jan Krupicka, Tomas Picek, and Lukas Svoboda

The laboratory experiments on the intense transport of bimodal sediment were conducted in a tilted, glass-sided flume with a variable longitudinal slope. Two fractions of lightweight solids were used, primarily differing in particle size, and each had a distinct color. The observed solid-liquid flow exhibited characteristics of being steady, uniform, turbulent, and supercritical. The bimodal sediment was transported as a combined load, with the finer fraction primarily supported by carrier turbulence, and the coarser fraction supported by interparticle contacts in the transport layer above a plane surface of the bimodal stationary bed. Distributions of solids velocity and concentration were measured for each of the two fractions across the transport layer above the bed using optical methods employing high-speed cameras. Additionally, the distribution of carrier velocity was measured across the flow depth. The measurements revealed a non-uniform distribution of solids for both fractions, with the maximum concentrations at the top of the bed for the coarser fraction and within the transport layer for the finer fraction at the highest bed shear. The results of the measurements allowed for the identification of the degree of stratification in the high-concentration sediment-laden flow and facilitated the evaluation of the interaction between particles of different fractions in the transport layer at various elevations above the bed. Furthermore, they enabled the quantification of the proportion of particles of the two fractions in the total discharge of solids through the channel.

How to cite: Matousek, V., Krupicka, J., Picek, T., and Svoboda, L.: Measured distributions of velocity and concentration for intense transport of bimodal lightweight sediment in tilting flume, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6100, https://doi.org/10.5194/egusphere-egu24-6100, 2024.

Consecutive floods combined with hyperconcentrated floods and moderate/low sediment-laden floods have always been observed in the Lower Yellow River (LYR) characterized by complex channel-floodplain systems of alternated meandering and straight segments. Interactions between those floods and sophisticated morphological segments are much more complicated than normal low-sediment laden rivers of relatively simple geometry. In this regard, we numerically investigate the 92.8 consecutive floods in the natural channel-floodplain reach of Xiaolangdi-Jiahetan in the LYR by deploying a 2-D depth-averaged fully coupled morphological model. The major focus includes (1) the unusual phenomenon of downstream peak discharge increase and (2) the different hydro-morphodynamic behaviors between meandering and straight channel-floodplain systems. For the former, the peak discharge increase of hyperconcentrated floods could be satisfactorily reproduced when the effects of bed roughness reduction and bed deformation are considered simultaneously. For the latter, the water-sediment exchange between channels and floodplains is relatively strong in hyperconcentrated floods and exhibits distinct features in meandering and straight segments. The straight one is featured by lateral channel-floodplain diffusion while the meandering one is characterized by the transition from lateral diffusion at the meander apex to streamwise advection. Consequently, the deposition at the meanders (especially on the floodplains) is much larger than that at the straight reach floodplains resulting in a remarkable uneven deposition pattern along the streamwise direction.

 

Key words: Lower Yellow River; Hyperconcentrated floods; Channel-floodplain interactions; Morphological modelling; Sediment transport

 

Acknowledgements: National Natural Science Foundation of China (No. 12272349, 52339005).

How to cite: Li, W., Zhu, L., and Hu, P.: Modelling interactions between consecutive floods and channel-floodplain systems in the Lower Yellow River, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7028, https://doi.org/10.5194/egusphere-egu24-7028, 2024.

EGU24-9106 | ECS | Orals | GM2.6

Formation and Kinematics of Basal Layer in Granular Flows Down Smooth and Rough Inclines 

Teng Wang, Lu Jing, and Fiona Kwok

Granular flow down a rough incline is a typical model case for geophysical mass flows. For insufficiently rough inclines, a strongly sheared basal layer can form below the less agitated bulk layer due to basal slip and particle collisions. However, the thickness and kinematic characteristics of the basal layer has not been well understood. Here, discrete element method (DEM) simulations are carried out to investigate the effects of base roughness on various kinematics profiles (i.e., velocity, shear rate and granular temperature) of the basal layer. The base roughness is varied systematically from geometrically smooth (i.e., a flat frictional plane) to moderately and sufficiently rough (formed by a layer of stationary particles). The base roughness is quantified by a dimensionless parameter, Ra, varying from 0 to 1, which has previously been found to control the transition from slip to non-slip regimes at around Ra=0.6. The present results show that, when basal slip occurs, the velocity profile deviates from the standard Bagnold’s profile, with an apparent basal slip and a basal layer where particles are highly agitated. The thickness of the basal layer, the slip velocity, and the level of velocity fluctuations (granular temperature) in the basal layer are all controlled by Ra. Intriguingly, the thickness of the basal layer, which is about several particle diameters, is insignificantly affected by other simulation conditions including the flow thickness and slope angle. Finally, the velocity profile is accurately described by a semi-empirical function based on the strong association between granular temperature and shear rate. Future work will focus on the rheology of the basal layer, which will potentially lead to more accurate predictions of geophysical granular flows.

How to cite: Wang, T., Jing, L., and Kwok, F.: Formation and Kinematics of Basal Layer in Granular Flows Down Smooth and Rough Inclines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9106, https://doi.org/10.5194/egusphere-egu24-9106, 2024.

EGU24-9390 | ECS | Orals | GM2.6

Assessment and evaluation of the utility of hydrokinetic technologies in low head streams 

Mohamad Anas El Mir and Manousos Valyrakis

Large dams exploiting hydropower have been marvels of engineering practice, but over the decades their accrued environmental effects, such as sediment budget balances (due to upstream aggregation and downstream erosion) and water quality and fish biota degradation, were visible. Moreover, large centralised hydropower systems present the challenge of grid connectivity, as it can be challenging to connect large electricity grids to remote and inaccessible rural areas, not only due to costs but also due to the loss of energy due to high distances. Scotland having many small rural communities and thousands of small low-head streams, is a prime example for efficiently demonstrating tackling the above crucial challenges of small scale decentralised power generation, with alternative schemes such as micro-hydropower and hydro-kinetic systems. These flexible to install and operate systems, can help prevent grid connectivity problems and electricity loss. They can be installed in several locations due to their small assembly and easy construction process compared to large hydropower plants. They can also be installed at wastewater plants to exploit outlet flows. In this study several criteria were analysed to assess the new technologies based on data collected from various suppliers. The criteria covered several aspects of the technologies: health and safety, design, environmental constraints, employability, and financial viability. The selection process started to classify the viability of the technologies according to the score they achieved. The technologies are assessed, and optimal use sometimes based on the location and real world application, are offered.

How to cite: El Mir, M. A. and Valyrakis, M.: Assessment and evaluation of the utility of hydrokinetic technologies in low head streams, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9390, https://doi.org/10.5194/egusphere-egu24-9390, 2024.

EGU24-9559 | ECS | Orals | GM2.6

Vegetation Submergence Effects on Bedload Transport Rate 

Yesheng Lu, Nian-Sheng Cheng, Maoxing Wei, and Christophe Ancey

We conducted a series of laboratory experiments to investigate the impact of vegetation on bedload transport rates depending on submergence. In the experiments, we used aluminum rods to simulate rigid vegetation, with vegetation submergence ratios (i.e., the ratio of water depth to vegetation height) ranging from 1 to 2. The bedload transport rates were measured by collecting sediment at the end of the vegetated area. The findings indicate that, with a constant bulk-averaged flow velocity, bedload transport rates decrease as the submergence ratio increases. This decrease is attributed to changes in the flow velocity distribution resulting from the flow resistance exerted by submerged vegetation. Indeed, water flows more easily through the top of the vegetation, and concurrently water velocity decreases significantly in the bottom region occupied by the vegetation. Building upon the phenomenological theory of turbulence, we propose a hydraulic radius-based method for estimating bed shear stress by incorporating the submergence ratio effect. This model enables the application of Cheng’s (2002) bedload formula, originally developed for bare beds, to predict bedload transport rates in both emergent and submerged vegetated flows. The present model, calibrated with a single parameter from experimental data, exhibited an average relative error of about 400% when validated with using experimental data (275 data in all) from our study and the relevant literature.

How to cite: Lu, Y., Cheng, N.-S., Wei, M., and Ancey, C.: Vegetation Submergence Effects on Bedload Transport Rate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9559, https://doi.org/10.5194/egusphere-egu24-9559, 2024.

EGU24-9650 | ECS | Orals | GM2.6

Segregation of granular mixtures in an annular shear cell under shear, gravity, and convection 

Yanan Chen, Christophe Ancey, and Nico Gray

Particle-size segregation is a widespread process that affects granular materials. Under the influence of gravity and shear, particles segregate into distinct regions according to their size. To date, most experimental investigations have studied granular flows induced by gravity and shear. Less studied is the special case where the granular material is segregated under convection. We are concerned with this particular case. We conducted experiments by shearing bi-dispersed granular mixtures in an annular shear cell. Refractive-index matching (RIM) was achieved between particles and the surrounding fluid, which made it possible to visualize the granular flow when illuminated by a laser sheet. We reconstructed the particle spatial arrangement by applying the Hough Transformation to a continuous series of scans. Both axial and radial segregation was observed in experiments, i.e., small particles tended to percolate downwards and accumulated radially to the center region, while large particles were squeezed upwards and gathered in the exterior region. We found that axial segregation was related to gravity and shear, while the radial convection was related to the shear and convection. Solids volume fractions were computed as a function of time from three-dimensional scans of granular mixtures, from which segregation velocity was then derived. The experimental data provides interesting insights into segregation produced simultaneously in two directions.

How to cite: Chen, Y., Ancey, C., and Gray, N.: Segregation of granular mixtures in an annular shear cell under shear, gravity, and convection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9650, https://doi.org/10.5194/egusphere-egu24-9650, 2024.

EGU24-9765 | ECS | Orals | GM2.6

Impact of sediment transport on newly constructed embankments and flooding in the Nakkhu River, Kathmandu, Nepal 

Saraswati Thapa, Hugh D. Sinclair, Maggie J. Creed, Simon M. Mudd, Mikael Attal, Alistair G. L. Borthwick, and Bhola N. Ghimire

In Nepal, urbanization has significantly accelerated since 2017 due to the conversion of numerous rural administrative units into urban ones by the government. This trend is particularly pronounced in the Kathmandu Valley where development is taking place on a large scale, including the building of four smart satellite cities, an outer ring road and river corridor roads flanked by green belts. The result is increased urban sprawl, river channelization, and floodplain encroachment, accompanied by sand and gravel mining activities. Many embankments have been constructed for flood protection along the rivers in the Kathmandu valley, including the Nakkhu River. However, the increasing number of settlements in low-lying floodplain areas and associated infrastructure damage caused by overtopping, breaching, or seepage of embankments, raise questions about the long-term sustainability of embankments as a solution to prevent future floods.

Using numerical simulations in a coupled hydrodynamic and landscape evolution model, CAESAR-Lisflood, we investigate how such embankments affect sediment transport, channel geometry, conveyance capacity, and flood inundation along the Nakkhu River. Each simulation is based on a high-resolution digital elevation model (2 m pixels, acquired in 2019-2020). Input sediment grain sizes are derived from field measurements, and we drive the model for different flood scenarios using maximum daily discharge data provided from the Department of Hydrology and Meteorology, Nepal.

The results suggest that changes in channel geometry caused by sedimentation increase flood risk downstream, particularly where embankments have been built to replicate sinuous channel courses. Inundation area is significantly higher in a scenario that includes sediment transport compared to a flood event modelled without sediment. It is recommended that sediment transport analysis be undertaken in the routine design of embankments and planned developments for river floodplains to minimize flood risk. Our study indicates that the construction of embankments alone may not provide sustainable long-term protection against future floods in rivers carrying high sediment loads.

Keywords: River embankment; Sediment transport; River morphology; Flood modelling; Nepal

How to cite: Thapa, S., Sinclair, H. D., Creed, M. J., Mudd, S. M., Attal, M., Borthwick, A. G. L., and Ghimire, B. N.: Impact of sediment transport on newly constructed embankments and flooding in the Nakkhu River, Kathmandu, Nepal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9765, https://doi.org/10.5194/egusphere-egu24-9765, 2024.

EGU24-9774 | ECS | Posters virtual | GM2.6

Subaqueous bedform morphology and migration in a mountainous macrotidal estuary 

Ruiqing Liu, Heqin Cheng, Lizhi Teng, Zhongda Ren, Jinfeng Chen, Qian Yang, and Heshan Fan

Abstract: The subaqueous bedforms in mountainous macrotidal estuaries, distinguished by their large tidal range and strong tidal and river flow dynamics, exhibit complex interactions among hydrodynamics, sediment transport, and bedform morphology, setting them apart from river and marine bedforms. However, there is currently a lack of research on the development characteristics and mechanisms of bedforms in such estuaries. To address this gap, field observations were conducted in the Minjiang Estuary of the East China Sea in December 2021 and August 2023, utilizing multibeam echosounders, shallow seismic profilers, and Acoustic Doppler Current Profilers (ADCP). Field measurements, including bedform morphology, surface sediment grain size, and hydrodynamics, were collected during both flood and ebb seasons. The study aims to explore the development characteristics and evolutionary patterns of bedforms in mountainous macrotidal estuaries, using the Minjiang Estuary as a representative case. The results indicate that the surface sediments in the subaqueous delta plain to the delta front channel of the Minjiang Estuary are predominantly composed of gravelly sand, with a median grain size ranging from 12.77 to 724.51 µm. Large compound bedforms are prevalent, with wavelengths ranging from 7.23 to 233 m and heights from 0.1 to 11.42 m. Bedform size is positively correlated with sediment grain size in the respective regions, and bedform morphology is related to sediment composition and water depth. Bedforms in different regions of the Minjiang Estuary exhibit varying degrees of symmetry, with asymmetry being more common, occasionally interspersed with cosinusoidal bedforms exhibiting better symmetry, which correlates with the strength of regional tidal dynamics. This study is of significant importance for understanding and simulating estuarine hydrodynamics and sediment transport.

Keywords: Mountainous Macrotidal Estuary, Minjiang Estuary, Bedform Morphology, Subaqueous Bedforms, Tidal Currents

How to cite: Liu, R., Cheng, H., Teng, L., Ren, Z., Chen, J., Yang, Q., and Fan, H.: Subaqueous bedform morphology and migration in a mountainous macrotidal estuary, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9774, https://doi.org/10.5194/egusphere-egu24-9774, 2024.

The mechanics of geophysical granular flow has been widely studied using spherical particles. However, natural granular materials are nearly always non-spherical, and a fundamental understanding of how particle shape affects the dynamics of granular flow remains elusive. Here, we use the discrete element method to simulate dense granular flows down a rough incline with systematically varied particle elongation (indicated by the length-to-diameter aspect ratio, AR). For each value of AR, we first determine the well-known hstop curve delimiting no-flow and steady flow regimes and then carry out steady flow simulations above the hstop curve to extract Pouliquen’s flow rule relations between the Froude number (Fr=u/(gh)0.5) and the normalized flow thickness h/hstop, where u is the mean flow velocity, h is the flow thickness and g is the gravitational acceleration. Our results show that the Fr-h/hstop relations have a nonlinear dependence on AR (data collapse is not immediately achieved). Next, we analyze the statistics of particle orientation during the flow using a microscopic order parameter and find that more elongated particles tend to align better along a certain orientation, thus hindering the particle rotation. The dependence of the measured order parameter on AR seems to explain the trend in the Fr-h/hstop relations, but further investigations are needed to quantitatively connect this micromechanical understanding with the macroscopic flow behaviors. Finally, the effects of other shape parameters, such as particle flatness and angularity, will be studied to draw a fuller picture of how the particle shape affects the mobility of geophysical granular flows.

How to cite: Jing, L. and Liu, J.: Effects of particle elongation on dense granular flows down a rough inclined plane, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9977, https://doi.org/10.5194/egusphere-egu24-9977, 2024.

EGU24-10063 | ECS | Posters virtual | GM2.6

Incipient particle entraiment prediction with the use of machine learning methods 

Manousos Valyrakis and Taiwo Ojo

In natural water bodies, sheared turbulent flows are the forcing agent responsible for particle mobilization near the river bed surface. Several analytical approaches have been used to describe this phenomenon, with ambiguities in the analytical methods employed, resulting in methodological biases. The application of a machine learning technique, namely, Adaptive Neuro-Fuzzy Inference System (ANFIS), is proposed here to model sediment transport dynamics. It is hypothesized that turbulent flow of different magnitudes and sufficient duration or near bed instantaneous flow power is responsible for particle displacement. The entrainment of sediment is modeled using the dynamic incipient motion criteria of impulse and energetic turbulent flow events. Several ANFIS architectures have been developed to relate the hydrodynamic vectorial quantities to particle displacement. ANFIS combines artificial neural networks' adaptation and learning power with the advantage of fuzzy inference (IF-THEN) rules for knowledge representation. To demonstrate ANFIS applicability for near bed threshold conditions, streamwise velocity [1], and particle dislodgement [2], flume-based experimental data sets are obtained as input and output signals to train the ANFIS model of various architecture complexities. The energy-based criterion and impulse criterion are obtained as cubic and quadratic expressions of streamwise velocity, respectively, and they are also used as inputs to train the ANFIS model [3]. Following a trial and error approach, the models developed with these criteria are analyzed and compared in terms of their efficiency and predictability using several performance indices. The optimum performing model is found capable of replicating the complex dynamics of sediment transport.

References
[1] Liu, D., AlObaidi, K., Valyrakis, M.* (2022). The assessment of an Acoustic Doppler Velocimetry profiler from a user’s perspective, Acta Geophysica, 70, pp. 2297-2310. DOI: 10.1007/s11600-022-00896-3.
[2] AlObaidi, K., Valyrakis, M. (2021). Linking the explicit probability of entrainment of instrumented particles to flow hydrodynamics, Earth Surface Processes and Landforms, 46(12), pp. 2448-2465 DOI: 10.1002/esp.5188.
[3] Valyrakis, M., Diplas, P., Dancey, C.L. (2011). Prediction of coarse particle movement with adaptive neuro-fuzzy inference systems, Hydrological Processes, 25(22). pp.3513-3524, DOI:10.1002/hyp.8228.

How to cite: Valyrakis, M. and Ojo, T.: Incipient particle entraiment prediction with the use of machine learning methods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10063, https://doi.org/10.5194/egusphere-egu24-10063, 2024.

EGU24-10349 | ECS | Posters on site | GM2.6

Temporal development of the scour hole next to the riprap sloping structure 

Antonija Harasti, Gordon Gilja, Josip Vuco, Jelena Boban, and Manousos Valyrakis

Riprap sloping structure is effective as bridge pier scour protection in the immediate vicinity of piers. In turn, riprap disrupts the flow conditions in a larger area than is the case with piers without scour protection in place. While these structures effectively dissipate the turbulent energy around piers, scouring occurs at the toe of the riprap and threatens the stability of the riprap and adjacent riverbed or hydraulic structures in proximity. This research presents the temporal evolution of the scour hole forming next to the riprap sloping structure. The research combines flume experiments with a physical model and numerical simulations using FLOW-3D software calibrated with experimental data measured with an optical surface scanner. Investigating the change in the scour hole dimensions over time provides valuable insights into the understanding of scour development and the associated undermining of the riprap toe during flood events that can jeopardize the bridge stability. The results show that, while scour generally increases with the duration of the flood, there are also evident backfilling events that need to be recognized and accounted for during the bridge design.

References:
[1] Harasti, A.; Gilja, G.; Potočki, K.; Lacko, M. Scour at Bridge Piers Protected by the Riprap Sloping Structure: A Review. Water 2021, 13, 3606. https://doi.org/10.3390/w13243606
[2] Harasti, A.; Gilja, G.; Adžaga, N.; Žic, M. Analysis of Variables Influencing Scour on Large Sand-Bed Rivers Conducted Using Field Data. Appl. Sci. 2023, 13, 5365. https://doi.org/10.3390/app13095365

Acknowledgments
This work has been supported in part by Croatian Science Foundation under the project R3PEAT (UIP-2019-04-4046).

How to cite: Harasti, A., Gilja, G., Vuco, J., Boban, J., and Valyrakis, M.: Temporal development of the scour hole next to the riprap sloping structure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10349, https://doi.org/10.5194/egusphere-egu24-10349, 2024.

EGU24-10417 | Posters on site | GM2.6

Change in flow field next to riprap sloping structure caused by variability of scoured bathymetry 

Gordon Gilja, Antonija Harasti, Dea Delija, Iva Mejašić, and Manousos Valyrakis

One approach to scour protection for bridge piers is constructing riprap sloping structure around the pier. To maintain its designated function, riprap must remain stable throughout the service life of the bridge, often exceeding 100 years and thus being vulnerable to more extreme hydrological events driven by climate change. The riprap sloping structure increases the size of the recirculation zone and turbulence downstream compared to a single pier. This paper presents the results of a detailed investigation of flow field dynamics over the scoured riverbed downstream of the riprap sloping structure. The research combines flume experiments with a physical model and numerical simulations using FLOW-3D software calibrated with experimental data measured with an acoustic Doppler velocimetry profiler, Vectrino ADVP. Investigating the complexities of the flow field resulting from the presence of riprap and interactions between the flow and scour development is essential for enhancing the design and performance of riprap structures in various hydraulic conditions. The results show that the change in scour geometry over time influences the flow direction in the zone downstream of the pier.

 

References

[1]    Gilja, G.; Fliszar, R.; Harasti, A.; Valyrakis, M. Calibration and Verification of Operation Parameters for an Array of Vectrino Profilers Configured for Turbulent Flow Field Measurement around Bridge Piers—Part I. Fluids 2022, 7, 315. https://doi.org/10.3390/fluids7100315

[2]    Gilja, G.; Fliszar, R.; Harasti, A.; Valyrakis, M. Calibration and Verification of Operation Parameters for an Array of Vectrino Profilers Configured for Turbulent Flow Field Measurement around Bridge Piers—Part II. Fluids 2023, 8, 199. https://doi.org/10.3390/fluids8070199

 

Acknowledgments

This work has been supported in part by the Croatian Science Foundation under the project R3PEAT (UIP-2019-04-4046)

How to cite: Gilja, G., Harasti, A., Delija, D., Mejašić, I., and Valyrakis, M.: Change in flow field next to riprap sloping structure caused by variability of scoured bathymetry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10417, https://doi.org/10.5194/egusphere-egu24-10417, 2024.

EGU24-11224 | ECS | Posters on site | GM2.6

Measuring flow resistance in rough-bed rivers using flume and CFD approaches 

Taís Yamasaki, Robert Houseago, Rebecca Hodge, Richard Hardy, Stephen Rice, Robert Ferguson, Christopher Hackney, Elowyn Yager, Joel Johnson, and Trevor Hoey

Accurate predictions of river channel flow resistance are necessary for estimating flow depth and/or velocity, and so are needed for predicting sediment transport and flood risk, river restoration and in-channel engineering. Standard approaches typically predict resistance as a function of the channel bed grain size distribution (GSD). However, in rough-bed rivers that comprise much of the river network (i.e. rivers where flow depth is not much greater than channel roughness elements), the sediment GSD is not the main factor that controls the channel shape, and so GSD does not provide a good predictor of flow resistance. In these channels, predictions need to instead account for the influence of multiple scales and shapes of roughness, including boulders, sediment patches, exposed bedrock and irregular banks, but we do not yet have suitable methods for making these predictions.  

We present initial results from flume and CFD modelling experiments that have been designed to identify how irregular river-beds affects the spatial pattern of form drag and determine overall flow resistance. Both experiments take advantage of high-resolution topographic data that has been collected from field locations using new survey techniques (terrestrial laser scanning and structure from motion photogrammetry). In the flume experiments, we used the data to create 1:10 scale 3D reproductions of three different river beds. For each bed we incrementally add sediment cover, boulders, and rough walls, and measured changes in channel topography. For each configuration we then measure how water depth varied across a range of discharges to evaluate bulk flow resistance. In the CFD experiments, we simulate a range of flows over the field topography to evaluate the spatial pattern of form drag across the bed. In subsequent experiments the topography will be manipulated to retain specific topographic scales, in order to assess how form drag changes. From both sets of experiments, we will identify which topographic (surface roughness) metrics best represent the effect of the differing river bed properties on bulk flow resistance, and hence offer most promise for improved predictive equations. 

How to cite: Yamasaki, T., Houseago, R., Hodge, R., Hardy, R., Rice, S., Ferguson, R., Hackney, C., Yager, E., Johnson, J., and Hoey, T.: Measuring flow resistance in rough-bed rivers using flume and CFD approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11224, https://doi.org/10.5194/egusphere-egu24-11224, 2024.

EGU24-11293 | ECS | Orals | GM2.6

How do supercritical turbidity-current bedforms transition? Insights from seismic data interpretation in the South China Sea 

Biwen Wang, Guangfa Zhong, Liaoliang Wang, and Zenggui Kuang

The transition of supercritical turbidity-current bedforms has been studied in the flume experiments and outcrops, whereas similar bedform transitions in deep-sea cases are rare. To better understand the mechanism behind bedform transitions in natural environments, we investigated the tempo-spatial transition of supercritical turbidity-current bedforms in the lower continental slope to abyssal plain in the northeastern South China Sea, by high-quality single-channel seismic data analysis coupled with simple numerical modeling. Quaternary bedforms were delineated at >3400 m water depth, covering an area of ~20000 km2. These bedforms are characterized by long wavelength (0.4-5 km), low wave height (1-15 m), and large aspect ratio (80-730), which are identified as supercritical-flow bedforms. Four types of bedforms were further identified based on the morphology and internal structure, which are (I) upslope-migrating cyclic steps characterized by asymmetrical morphology with thick backsets and long wavelength; (II) upslope-migrating antidunes (UMAs) featured by nearly symmetrical morphology and relatively short wavelength; (III) downslope-migrating antidunes (DMAs) typified by gentle and sigmoid foresets and large aspect ratios; (IV) upper-stage plane beds (UPBs) consisting of low-relief wavy to subhorizontal reflections. Slope variations are highlighted to induce flow energy changes and facilitate bedform transitions. A slight slope decrease from 0.5 to 0.1° and 0.3 to 0.1-0.2° would respectively lead to the transition from UMAs to UPBs and from cyclic steps to UMAs, due to the hydraulic jump and flow acceleration. In contrast, an increased slope from 0.1 to 0.2° can contribute to the transition from UMAs to cyclic steps or DMAs by re-accelerating flows. Over time, the bedforms evolve from DMAs to UMAs and cyclic steps with growing wavelengths and wave heights, possibly caused by the inherited development of bedforms and increasing aggradation rates linked with progressively rising Taiwan uplifting rates. These bedforms consist of three contiguous fields fed by inter-seamount pathways and Manila Trench, comprising a supercritical-flow submarine fan apron that is far from the shelf edge and lacks submarine channels. This research was supported by the National Key Research and Development Program of China (Grant Number 2022YFF0800503).

How to cite: Wang, B., Zhong, G., Wang, L., and Kuang, Z.: How do supercritical turbidity-current bedforms transition? Insights from seismic data interpretation in the South China Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11293, https://doi.org/10.5194/egusphere-egu24-11293, 2024.

EGU24-12742 | Orals | GM2.6

Background Topography Affects the Degree of Three-Dimensionality of Tidal Sand Waves 

Abdel Nnafie, Janneke Krabbendam, Bas Borsje, and Huib de Swart

Offshore tidal sand waves on the sandy bed of shallow continental shelf seas are more three-dimensional (3D) in some places than others, where 3D refers to a pattern that shows variations in three spatial directions. These sand waves often display meandering, splitting, or merging crestlines. The degree of three-dimensionality seems to vary especially when large-scale bedforms, such as tidal sand banks, are present underneath the sand waves. Understanding this behavior is important for offshore activities, such as offshore wind farm construction or the maintenance of navigation channels. In this study, the degree of three-dimensionality of sand waves at five sites in the North Sea is quantified with a new measure. Results show that tidal sand waves on top of tidal sand banks are more two-dimensional (2D) than those on bank slopes or in open areas. Numerical simulations performed with a new long-term sand wave model support these differences in sand wave patterns. The primary cause of these differences is attributed to the deflection of tidal flow over a sand bank, which causes sand wave crests to be more aligned with the bank at its top than at its slopes. It is subsequently made plausible that the different patterns result from the competition between two known mechanisms. These mechanisms are nonlinear interactions between sand waves themselves (SW-SW interactions) and nonlinear interactions between sand banks and sand waves (SB-SW interactions). On bank tops, SB-SW interactions favor a 2D pattern, while SW-SW interactions, which produce a 3D pattern elsewhere, are less effective.

How to cite: Nnafie, A., Krabbendam, J., Borsje, B., and de Swart, H.: Background Topography Affects the Degree of Three-Dimensionality of Tidal Sand Waves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12742, https://doi.org/10.5194/egusphere-egu24-12742, 2024.

EGU24-13532 | ECS | Posters virtual | GM2.6

Research on nearshore subaqueous geomorphology stability detection based on few-shot learning 

Zhongda Ren, Peng Zhang, Heqin Cheng, Lizhi Teng, Jinfeng Chen, Yang Jin, Ruiqing Liu, Zhengyang Jia, and Hong Zhang

Detecting the stability of nearshore subaqueous geomorphology is a crucial challenge for ensuring early warning and controlling the stability of riverbank slopes. Acquiring nearshore subaqueous geomorphology data using unmanned ship-mounted acoustic multibeam systems is difficult, costly, and time-consuming. Moreover, it is often influenced by weather conditions. The limited availability of nearshore subaqueous geomorphology samples suitable for model training, combined with the high similarity between targets of nearshore unstable geomorphology and the background, poses significant challenges for traditional detection methods. In response to issues such as high similarity in subaqueous geomorphology images, large-scale variations in target size, and a scarcity of samples, this study proposes a nearshore subaqueous geomorphology instability detection framework based on Few-shot learning. Firstly, a feature extraction network is designed, replacing the backbone network with a Swin Transformer network. This network employs a feature pyramid network to extract multi-scale geomorphology features containing global information from the query set, facilitating the fusion of features across deep and shallow layers. Secondly, a weight adjustment module is devised to transform the support set into weight coefficients with class attributes. This adjustment helps in adapting the distribution of geomorphology features for detecting new class objects. Experimental results demonstrate that the proposed detection framework achieves desirable performance in terms of average precision and average recall indicators.
Keywords: Subaqueous Geomorphology; Stability Detection; Few-shot learning

How to cite: Ren, Z., Zhang, P., Cheng, H., Teng, L., Chen, J., Jin, Y., Liu, R., Jia, Z., and Zhang, H.: Research on nearshore subaqueous geomorphology stability detection based on few-shot learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13532, https://doi.org/10.5194/egusphere-egu24-13532, 2024.

EGU24-15069 | Orals | GM2.6

Modeling particle impacts on granular media for the analysis of aeolian saltation 

Provence Mahjoub-Bonnaire, Franck Bourrier, Luc Oger, and Guillaume Chambon

Grain transport by saltation is involved in numerous geophysical phenomena such as wind-blown sand, snow drift, aeolian soil erosion, dust emission, etc. Particle impacts on a granular bed trigger rebound and ejections processes, which can lead in certain conditions to a steady state of solid transport. The present work is dedicated to the analysis of the impact processes at the grain scale, with the objectives of inferring robust statistical laws and better understanding granular transport, accounting for the possible role played by adhesion between the grains.

The study is based on numerical simulations with the DEM (Discrete Element Method). The numerical experiments consist in throwing a spherical particle on a granular packing with controlled velocity (Froude number between 0 and 200) and impact angle (between 10° and 90°). The contact model (friction, cohesion) between the grains is varied to represent different types of granular materials (e.g., dry sand, wet sand, snow).
We investigated the influence of incident parameters on the impact process, focusing on the incident particle rebound and on the number and velocities of ejected particles. For non-cohesive granular beds, the simulations were compared to laboratory experiments of impacts of spherical particles on granular packings in order to validate the model . In particular, the restitution coefficient of the incident particles and the number of ejected particles were found in good agreement with experimental results. The simulations also give access to quantities that cannot be easily measured in the experiments. Hence, we could observe an anisotropy of ejected particles velocities for grazing impact angles, which is more pronounced when the incident velocity decreases.
Preliminary results concerning cohesive granular beds will also be presented, considering contact laws representative of liquid (capillary) and solid cohesion processes. Effect of cohesion on the number of ejected particles, and energy dissipation processes within the cohesive granular beds, will be discussed.

How to cite: Mahjoub-Bonnaire, P., Bourrier, F., Oger, L., and Chambon, G.: Modeling particle impacts on granular media for the analysis of aeolian saltation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15069, https://doi.org/10.5194/egusphere-egu24-15069, 2024.

EGU24-15693 | Orals | GM2.6

Classification of underwater flow-transverse sedimentary bedforms 

Alice Lefebvre, Robert W Dalrymple, Julia Cisneros, Leon Scheiber, Suzanne Hulscher, Arnoud Slootman, Maarten G. Kleinhans, and Elda Miramontes

Despite the recommendations given in Ashley (1990), a plethora of terms continues to be used to describe flow-scale flow-transverse sedimentary bedforms, often without clear definition or distinction between the different nomenclatures. For example, (marine) dunes and sand waves are used interchangeably in many contexts. Smaller bedforms superimposed on larger ones may be referred to as megaripples or secondary dunes. It is currently unclear if different terms are used due to intrinsic morphological or genetic differences or due to the traditions of different scientific communities. Ashley (1990) already noted that the “poor communication among scientists and engineers has perpetuated the multiplicity of terms”. Researchers from fluvial, coastal or deep-marine environments, from industry or academia, from various disciplines, such as sedimentology, oceanography, coastal and offshore engineering or geomorphology may use a specific vocabulary. Furthermore, terminology may differ depending on the country or research group in which they work. All this makes communication difficult and may cause misinterpretations, hindering progress in understanding and cross-disciplinary collaborative pursuits.

The aim of the present contribution is to provide an updated classification of the different types of underwater flow-transverse sedimentary bedforms. The intent is to homogenise the nomenclature for researchers coming from different disciplines and working in varied environments, to enable the use of a common classification and terminology to improve knowledge exchange, comparison and dialogue.

We propose a description table, which can be used by scientists and practitioners to describe the sedimentary bedforms with which they are working. Importantly, each bedform characteristic is described and the way to calculate the quantitative descriptive parameters is detailed. The description table aims at providing a standard and consistent way to describe the bedforms and their environmental setting prior to classifying them. The description table can be used independently of bedform type and further classification, which should overcome communication issues.

Two classification schemes are then proposed. The first is based on an understanding of the genetic processes. This should be used whenever possible because it informs about the underlying processes which formed the bedform. In order to complement the process-based classification, or in situations where the genetic processes are unknown, a second, geomorphological classification is introduced. Thus, we urge the bedform community to consider deploying these descriptor and classification tools and hope our contribution leads to a much more transparent and cohesive future in bedform research.

How to cite: Lefebvre, A., Dalrymple, R. W., Cisneros, J., Scheiber, L., Hulscher, S., Slootman, A., Kleinhans, M. G., and Miramontes, E.: Classification of underwater flow-transverse sedimentary bedforms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15693, https://doi.org/10.5194/egusphere-egu24-15693, 2024.

The study of the geomorphic dynamics of consecutive bends in Yangtze River under controlled conditions, i.e., the regulated water and sediment process, and the bank protection project, contributes to the further understanding of the meandering river theory. In this study, by combining the topographic data and remote sensing data, the morphological adjustment of typical consecutive bends in Yangtze River in response to upstream damming are analyzed. The results show that during 2006-2021, the riverbed is scoured generally. The consecutive bends are generally characterized by inner-bank scouring and outer-bank sedimentation. Besides, the evolution of the front and back bends shows good correlation, and the longer the length of the transition section, the weaker the correlation between the evolution of the front and back bends. The results of the study may serve as a rational reference for managing natural meandering rivers with multiple hydrological, geomorphological, and ecological goals.

How to cite: He, X. and Yu, M.: The morphological adjustment of typical consecutive bends in Yangtze River in response to upstream damming, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15932, https://doi.org/10.5194/egusphere-egu24-15932, 2024.

EGU24-16292 | ECS | Orals | GM2.6

Flow rule for unsteady flows of spherical and non-spherical grains down rough inclined planes 

Yanbin Wu, Zixiao Guo, Thomas Pähtz, and Zhiguo He

Based on laboratory experiments, Pouliquen (1999) uncovered a universal scaling law for the average velocity v of homogeneous flows of spherical grains down rough inclines [1]: , where g is the gravitational acceleration, h the flow thickness, and hs(θ) the thickness below which the flow stops depending on the inclination angle θ. Today, this so-called “flow rule” is well established in the field and has served as a critical test for continuum granular flow models [2]. However, based on more accurate measurements for granular materials composed of either spherical or non-spherical grains, Börzsönyi and Ecke (2007) found and pointed out that this revised flow rule was predicted by a two-dimensional granular kinetic theory [3, 4]. In addition, for non-spherical grains, they noticed deviations from this rule at large h/hs. Both Pouliquen and Börzsönyi and Ecke assumed that the granular flows in their experiments were steady.

Here, we report on new systematic experiments for granular materials composed of spherical glass beads, different kinds of non-spherical sands, and grain-size-equivalent mixtures of these. Their careful analysis reveals a new grain-shape-dependent flow rule that resolves the above contradictions in the current literature and provides quantitative evidence for the statement that the deviations observed by Börzsönyi and Ecke can be attributed to the flows not having reached the steady state.

[1] Pouliquen O. Scaling laws in granular flows down rough inclined planes[J]. Physics of fluids, 1999, 11(3): 542-548.

[2] Kamrin K, Henann D L. Nonlocal modeling of granular flows down inclines[J]. Soft matter, 2015, 11(1): 179-185.

[3] Börzsönyi T, Ecke R E. Flow rule of dense granular flows down a rough incline[J]. Physical Review E, 2007, 76(3): 031301.

[4] Jenkins J T. Dense shearing flows of inelastic disks[J]. Physics of Fluids, 2006, 18(10).

How to cite: Wu, Y., Guo, Z., Pähtz, T., and He, Z.: Flow rule for unsteady flows of spherical and non-spherical grains down rough inclined planes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16292, https://doi.org/10.5194/egusphere-egu24-16292, 2024.

EGU24-17522 | ECS | Orals | GM2.6

Experimental modelling of local scour phenomenon at a series of repelling emergent spur dikes  

Sandeep Kumar and Prashanth Reddy Hanmaiahgari

A spur dike is an elongated artificial structure with one end on the bank of a stream and the other end projecting into the current, and it is the most cost-effective river training structure that can be built at the channel’s banks. A series of spur dikes are usually more efficient in stabilizing the alluvial shores, whereas single spur dikes alter the local field. Thus, analyzing the local scour phenomena surrounding hydraulic structures in rivers is crucial to minimize the hazard of foundation collapse.

Therefore, experiments have been conducted to study the phenomenon of local scouring around the series of repelling spur dikes under clear water conditions, analysis of flow behavior & alterations in the morphology of sediment bed, and turbulent fluctuation. The inclination angle of the non-submerged spur dike with the vertical wall was kept 600 during the study in the straight rectangular flume of length, width, and depth are 15 m, 0.91 m, and 0.70 m. While the projected length of spur dikes was 1/5 of the width of the channel, and the spacing between spur dikes was 2.5 * the projected length of spur dike. In laboratory experiments, the flow velocities and bed deformation around the series of repelling spur dikes were measured using an Acoustic Doppler velocimeter, a high-resolution laser displacement meter, and a point gauge.

The test section consists of uniform sediment particles, the experiment was initiated with a leveled sediment bed, and a scouring phenomenon was observed throughout the experiment at the head, middle, and end of each spur dike in the u/s and d/s. The 3D velocity measurement is done at the head of the spur dike from u/s of the first spur dike till downstream of the third spur dike. Velocity measurements provide information on dominant agents responsible for the local scour.

It was concluded that the maximum depth of the scour hole 14.47 cm at 1st spur dike head. Digging and siltation was a cyclic process till equilibrium was achieved during the experiment, and the flow was classified as subcritical and turbulent. The approaching flow has less strength between the 1st and 2nd spur dike as it moves upward mostly in the top section.  The negative values of  over some length was observed in the scoring zone near the bed. While comparing the value of non-dimensional Reynolds Shear Stress -uv/u*2,  -uw/u*2,  -vw/u*2, it was observed that -uw/u*2, had a much greater both positive and negative value compared to the other. The Turbulent Kinetic Energy distribution shows that there is relatively more turbulence surrounding the 1st spur dike.

How to cite: Kumar, S. and Hanmaiahgari, P. R.: Experimental modelling of local scour phenomenon at a series of repelling emergent spur dikes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17522, https://doi.org/10.5194/egusphere-egu24-17522, 2024.

EGU24-17681 | ECS | Orals | GM2.6

Typical design hydrograph method based on a joint distribution approach combining flood peak discharge, volume and duration 

Martina Lacko, Kristina Potočki, Kristina Ana Škreb, Nejc Bezak, and Gordon Gilja

Determination of flood magnitude and shape characteristics are necessary to provide a more complete assessment of flood severity and its impact in scour development analysis. Our recent research has focused on a joint distribution approach to account for the multivariate nature of flood characteristics, resulting in probability of occurrence of different pairs of flood variables: flood peak (Q), volume (V) and duration (D). To extend the results of this research, a method for deriving a design hydrograph is applied to the study area by using the typical hydrograph method. As it is recommended to test multiple scenarios in a scour analysis, different typical flood hydrographs were selected at several gauging stations on the Sava and Drava rivers in Croatia and multiplied by the design discharge values. The aim of this study is to complement the ongoing research of the relationship between climate change indicators, flood wave characteristics and scour development next to the bridges crossing large rivers in Croatia with installed scour countermeasures by preparing hydrological input data for a hydraulic scour analysis.

How to cite: Lacko, M., Potočki, K., Škreb, K. A., Bezak, N., and Gilja, G.: Typical design hydrograph method based on a joint distribution approach combining flood peak discharge, volume and duration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17681, https://doi.org/10.5194/egusphere-egu24-17681, 2024.

Granular media has near omnipresence in nature and is the second most processed substance in industry, after water. It is well accepted that it exhibits a wide spectrum of macro-scale behaviour which is ultimately determined by the grain-scale interactions of its constituent particles [1][2][3]; but there is still much to be discovered about those grain-scale interactions themselves. Away from the free surface of an agitated granular bed, the dominant grain-scale interactions are relative sliding and rolling between neighbouring particles [4], and it is this sliding and rolling which is the subject of this research.

In these experimental lab-based tests, ‘dry’ and ‘wet’ ideal granular beds are harmonically compressed via a moving side-wall and their responses captured via high-speed imaging. The granular media itself is a quasi-2D bed of polydisperse discs consisting of an even mixture of five different disc diameters ranging from 11mm to 36mm. The cyclic compressions are specifically designed to impose a jamming effect within the granular beds, before subsequent relaxation and deformation.

Use of the photo-elastic technique provides a window through which the grain-scale behaviour of the beds can be examined, as networks of inter-particle contact forces, known as force chains, become visible. Disc rotation is measured by tracking lines drawn onto each disc, providing useful insight into the sliding and rolling inter-particle interactions at the grain-scale. First, the behaviour of a ‘dry’ granular bed is examined, and then a thin layer of glycerol is spread onto the edges of each individual disc in order for the behaviour of an equivalent ‘wet’ granular bed – or at least, a bed with reduced inter-particle friction – to be examined. The behaviour of these beds are then compared to one another, and the results used to discuss how changes to friction at the grain scale affects the behaviour of granular bodies.

 

 

[1] Singh, S., Murthy, T.G.: Evolution of structure of cohesive granular ensembles in compression. International Journal of Solids and Structures 238(1), 111359 (2022)

[2] Jiang, M., Yu, H., Harris, D.: A novel discrete model for granular material incorporating rolling resistance. Computers and Geotechnics 32(5), 340–357 (2005)

[3] Oda, M., Konishi, J., Nemat-Nasser, S.: Experimental micromechanical evaluation of strength of granular materials: effects of particle rolling. Mechanics of Materials 1(4), 269–283 (1982)

[4] Moss, J., Glovnea, R.: Behavioural responses to horizontal vibrations of quasi-2D ideal granular beds: an experimental approach. Granular Matter 25(4), 63 (2023).

How to cite: Moss, J. and Glovnea, R.: Friction at the grain-scale: the role of inter-particle friction in granular media and its influence on grain-scale bed behaviour, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18798, https://doi.org/10.5194/egusphere-egu24-18798, 2024.

EGU24-19002 | ECS | Orals | GM2.6

A three-species model of aeolian saltation incorporating cooperative splash 

Yulan Chen, Thomas Pähtz, Katharina Tholen, and Klaus Kroy

Most aeolian sand transport models incorporate a so-called splash function that describes the number and velocity of particles ejected by the splash of an impacting particle. It is usually obtained from experiments or simulations in which an incident grain is shot onto a static granular packing. However, it has recently been discovered that, during aeolian sand transport, the bed cannot be considered as static, since it cannot completely recover between successive impacts. This led to a correction of the splash function accounting for cooperative effects [1], which were shown to be responsible for an anomalous third-root scaling of the sand flux with the particle-fluid density ratio s, observed in discrete-element-method-based simulations of aeolian sand transport across six orders of magnitude of s [2]. The model by [1] represents the aeolian transport layer by two species: high-energy saltons that eject low-energy reptons upon impact. While it quantitatively captures measurements and the simulated sand flux scaling, it does not recover the scaling laws of the simulated transport threshold and vertical flux at the bed. Here, we improve the model by [1] by means of a three-species saltation model. The additional species, called leapers, represent the fastest reptons, ejected by saltons in rare extreme ejection events. Together, saltons and leapers quantitatively reproduce the threshold and sand flux scaling behaviors, whereas reptons are predominantly responsible for the vertical bed surface fluxes seen in the simulations.

[1] Tholen, Pähtz, Kamath, Parteli, Kroy, Anomalous scaling of aeolian sand transport reveals coupling to bed rheology, Physical Review Letters 130 (5), 058204 (2023). https://doi.org/10.1103/PhysRevLett.130.058204

[2] Pähtz, Durán, Scaling laws for planetary sediment transport from DEM-RANS numerical simulations, Journal of Fluid Mechanics 963, A20 (2023). https://doi.org/10.1017/jfm.2023.343

How to cite: Chen, Y., Pähtz, T., Tholen, K., and Kroy, K.: A three-species model of aeolian saltation incorporating cooperative splash, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19002, https://doi.org/10.5194/egusphere-egu24-19002, 2024.

EGU24-20911 | Posters on site | GM2.6

Kinematics of the jamming front resulting from the clogging of the flow of monodisperse inelastic particles in a partially obstructed chute 

Rui M L Ferreira, Solange Mendes, Rui Aleixo, Amaral Amaral, and Michele Larcher

We characterize experimentally the upstream-progressing jamming wave triggered by the clogging of a granular flow down a partially obstructed chute. We generated dry granular flows in a sloping chute whose outlet was obstructed by a wall with two vertical gaps, twice the diameter of the granular material. We conducted 31 repetitions of the same test to obtain stable statistics. We employed Particle Tracking Velocimetry (PTV) to determine particle velocities at the sidewall and estimated fields of mean velocity and granular temperature by ensemble-averaging. Each ensemble is a set of valid grain velocities collected in space-time bins, that map the entire domain, over all test repetitions. The system is highly dissipative due to collisions and enduring contacts among inelastic particles, resulting in generalised cooling. Clogging occurs as a consequence of the formation of stable arch-like structures at the outlet, while the flow cools down. We observe that the jamming wave propagates against the flow at different values of granular temperature and mean velocity. There is no triple point in the system in the sense that jamming is always preceded by gas-liquid transition. For the tested conditions, jamming can be described as an accretion problem, leading to a granular solid state from liquid state and never from the gaseous state. The jamming wavefront progresses faster as the values of the granular temperature decrease. Flow cooling, including gas-fluid transitions, seem independent of jamming, which is compatible with the range of observed granular Froude and Mach numbers. The jamming wavefront becomes faster than the adiabatic speed of sound of the granular material moving towards the jammed region.

 

Acknowledgements: This work was partially funded by the Portuguese Foundation for Science and Technology (FCT) through Project DikesFPro PTDC/ECI-EGC/7739/2020 and through CERIS funding UIDB/04625/2020

How to cite: L Ferreira, R. M., Mendes, S., Aleixo, R., Amaral, A., and Larcher, M.: Kinematics of the jamming front resulting from the clogging of the flow of monodisperse inelastic particles in a partially obstructed chute, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20911, https://doi.org/10.5194/egusphere-egu24-20911, 2024.

EGU24-22239 | ECS | Posters on site | GM2.6

Numerical simulation of dike breaching by overtopping. Influence of the bank erosion operator.  

Ricardo Jonatas, Rui M L Ferreira, Ana M Ricardo, and Sílvia Amaral

We employ a physically-based in-house 2D multi-layered depth and time averaged shallow water model with the capacity to simulate morphology and sediment transport (HiSTAV) to model the erosion of dikes subjected to overtopping. Its conceptual model is based on conservation laws for shallow flows and requires closures for flow resistance, and sources and sinks of transported substances. The conservation laws are discretized within a Godunov-type Finite Volume scheme. HiSTAV design is entirely cross-compatible between CPUs and GPUs, through an intuitive object-oriented approach. HiSTAV requires the parametrization of the processes expressing hydraulic erosion, slope failure and mass detachment. The latter are modelled as sudden collapses of cells of dam body, dry but adjacent to the flow, a process akin to river bank collapse. A secondary mesh is defined to group the cells that form the detached mass. We investigate the effects of the dimension of the group and the values of the parameters (velocity and shear stress) that trigger the collapse. As expected, the bulk erosion rate increases with the size of the detached group. The results of the model were compared with data from laboratory models. Three laboratory tests were carried out in a medium-scale facility located at the Fluvial Facilities of the Hydraulics and Environment Department (DHA) of LNEC. The facility operates in closed circuit and is composed by a 1.40 m wide and 19 m long channel where the river stream is simulated. It allows testing dikes up to 0.50 m height and 2.0 m long. The water level upstream the dike is controlled by a sluice gate placed at the downstream end of the channel. The dike site and the main channel where constructed in an elevated platform, after which there a settling basin (2.10W x 4.5L (m)) where the eroded soil from the failure tests is deposited. A Bazin spillway exists at the end of this structure to measure the dike outflow discharge. We performed 3-D reconstructions of the evolving dike geometry, monitored the water levels in the main channel, the flow discharges in the main channel and across the breach and calculated the surface velocity fields in the vicinity and breach (LSPIV). The rate of breach erosion and the velocities near the breach were compared with the results of the model. It was observed that the size of the detachment group should scale with the breach crest and is influenced by the type of soil.

Acknowledgements: This work was partially funded by the Portuguese Foundation for Science and Technology (FCT) through Project DikesFPro PTDC/ECI-EGC/7739/2020 and through CERIS funding UIDB/04625/2020

How to cite: Jonatas, R., L Ferreira, R. M., Ricardo, A. M., and Amaral, S.: Numerical simulation of dike breaching by overtopping. Influence of the bank erosion operator. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22239, https://doi.org/10.5194/egusphere-egu24-22239, 2024.

EGU24-196 | ECS | Posters on site | GM3.2

Remote sensing and geomorphometry application in riverscapes evolution in the south-eastern Arabian Peninsula (Sultanate of Oman) 

Andrea Pezzotta, Alessia Marinoni, Mohammed Al Kindi, Michele Zucali, and Andrea Zerboni

Riverscapes in arid and semi-arid environments serve as crucial archives, enabling us to understand the landscape evolution and the active and fossil geomorphological processes that shape the Earth's surface. Such environmental contexts are generally wide, and these settings are routinely investigated with remote sensing tools. We selected two distinct study areas from the south-eastern margin of the Arabian Peninsula (Sultanate of Oman) to detect climate and tectonic imprints over landform development: 1) Jebel Akhdar (JAK), and its surrounding areas, located in the Al-Hajar Mountains (to the North), is a wide anticline formed by the Late Cretaceous obduction of the Semail Ophiolite and the associated time-equivalent tectonics, followed by the Cenozoic tectonic events; and 2) Jebel Qara (JQA), situated in the Dhofar Mountains (to the South), is placed along the Gulf of Aden transform margin, featuring transtensional faults giving rise to stepped escarpments and grabens. The extant landscapes of both regions are characterized by a network of narrow and deep canyons that incised limestone massifs, while the surrounding plain areas show the development of important alluvial fan systems.

The application of remote sensing is essential for investigating the development of fluvial systems at a regional scale, combined with field survey to validate specific sites of interest, thereby understanding the geomorphological evolution at various scales. Specifically, remote sensing techniques include the processing of satellite imagery and the comparison with the available historical imagery and maps to detect changes in geomorphic processes. Remote sensing and field survey allow the recognizing of different geomorphological features; the dominant ones are represented by elements and landforms related to structural setting, fluvial activity, and karst processes. The associations of the abovementioned landforms make it possible to assess the structural influence on drainage and karstic network development. Data collected from remote sensing implements the geomorphometric quantification of geomorphological processes, mostly considering changes in topography and river network analyses. The most meaningful morphometric indices applied (such as drainage divide stability, normalized steepness index, knickpoint detection, and swath profiles…) suggest their values strongly vary along faults in JAK, highlighted even with the alignment of knickpoints; while, in JQA, values show little changes in correspondence of faults and knickpoints are controlled both by karst and structural settings. In this way, the combination of remote sensing and morphometrical analyses permits to quantify the central role of litho-structural influence on the development of riverscapes in the south-eastern Arabian Peninsula. This approach facilitates the identification of the primary geomorphological processes that have shaped the landscape in arid and semi-arid contexts of the Sultanate of Oman, making it a versatile method that can be applied to understand the riverscapes evolution processes in analogous regions.

How to cite: Pezzotta, A., Marinoni, A., Al Kindi, M., Zucali, M., and Zerboni, A.: Remote sensing and geomorphometry application in riverscapes evolution in the south-eastern Arabian Peninsula (Sultanate of Oman), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-196, https://doi.org/10.5194/egusphere-egu24-196, 2024.

EGU24-1613 | ECS | Posters on site | GM3.2

Simulating 4D scenes of rockfall and landslide activity for improved 3D point cloud-based change detection using machine learning 

Ronald Tabernig, Vivien Zahs, Hannah Weiser, and Bernhard Höfle

Terrestrial Laser Scanning (TLS) systems have been refined to automatically and continuously scan defined areas with high temporal resolution (sub-hourly), leading to the development of Permanent Laser Scanning (PLS). This temporal resolution requires the development of new methods for efficient extraction of change information. The creation of labeled 4D point clouds (3D+time), classified by surface change type, remains time-consuming. This hinders the evaluation of change detection methods and the training of machine learning (ML) and deep learning (DL) models.

This study explores how synthetic 4D point clouds can be effectively utilized for detecting and classifying spatiotemporal changes. We combine simplified process path simulations, simulated PLS, and change detection methods (e.g. M3C2) [1]. This combination is used to automatically evaluate calculated distances compared to a pre-defined reference. It also generates labeled 4D training datasets for ML/DL approaches.

We adapted the Gravitational Process Path model (GPP) [2] to create gravity-influenced process paths for our PLS simulations. Utilizing these paths, we simulate two different scenarios, 1) including a forest situated on top of a large landslide and 2) an outcrop with rockfall activity. For the forest scenario, a constant velocity is applied to each tree to simulate slope movement. The velocity of the objects in the rockfall scene is determined by the GPP model. Dynamic 3D scenes are generated from these scenarios and used as input for Virtual Laser Scanning (VLS). Realistic simulation of LiDAR surveys (of these virtual scenes) is achieved by using the open-source simulator HELIOS++ [3]. This workflow allows for the determination of the accurate position of each object at any given time. It provides reference data that is usually unavailable in real data acquisitions. In the rockfall scenario, M3C2 distances are calculated, and areas of similar change are clustered. For the forest located on the landslide, 2D and 3D displacement vectors are derived from the displacement of the tree trunks. These changes are then compared to the actual change occurring between epochs. Furthermore, the time steps between each epoch can be chosen arbitrarily, enabling the exploration of various scenarios and processes using labeled point clouds at any temporal resolution.

Preliminary results suggest that this workflow can assist in determining the scan resolution required to detect changes of a specific size and magnitude. We establish a simulation-based error margin for each method used by comparing the results to the reference data. This enables direct evaluation of method performance during implementation.

We demonstrate the potential of combining process simulation and laser scanning simulation for resource efficient planning of TLS and PLS campaigns, geographically sound generation of dynamic point clouds, the evaluation of change detection and quantification methods, and generating labeled point clouds as training data for 4D ML/DL methods. 

References:
[1] py4dgeo: https://github.com/3dgeo-heidelberg/py4dgeo
[2] Wichmann, V. (2017): https://doi.org/10.5194/gmd-10-3309-2017.
[3] Winiwarter, L. et al. (2022): https://doi.org/10.1016/j.rse.2021.112772. 

How to cite: Tabernig, R., Zahs, V., Weiser, H., and Höfle, B.: Simulating 4D scenes of rockfall and landslide activity for improved 3D point cloud-based change detection using machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1613, https://doi.org/10.5194/egusphere-egu24-1613, 2024.

EGU24-4207 | Orals | GM3.2

Incorporating ontological characteristics for global landform classification based on 30 meters DEM 

Xin Yang, Chenghu Zhou, Sijin Li, Junfei Ma, Yang Chen, Xingyu Zhou, Fayuan Li, Liyang Xiong, Guoan Tang, and Michael Meadows

Landform classification and mapping provide fundamental data for Earth science research, natural resource management, environmental monitoring, urban planning, and various other domains. Despite the availability of DEMs with 1-arc second resolution, global-scale studies on landform classification and mapping are inconsistent in terms of general classification systems and methods.

Landforms represent not only assemblages of morphological characteristics but also encompass the human understanding of the Earth, which is constrained by the nature and scale of quantitative analysis. Here, we propose a novel framework for global landform mapping to significantly improve the quantitative evaluation of geomorphological features.

The proposed framework incorporates geomorphological ontology that takes account of their conceptualization to construct classified objects. We propose the accumulated slope (AS) and mountain uplift index (MUI) to emphasize the integrity and continuity of geomorphological units, providing more precise results compared to traditional methods. Aggregating local terrain features into global metrics, AS effectively overcomes the potential negative influence of increased resolution on landform integrity. MUI aligns better with human perception of mountainous morphology and surpasses the limitations of window-based computing.

In presenting the new framework, we have developed and made available a public dataset, Global Basic Landform Unit (GBLU), which incorporates a comprehensive set of objects that constitute the range of landforms on Earth. In emphasizing the integration of classification with quantitative analysis, GBLU highlights the connection between natural objects and human understanding in geomorphology and the Earth sciences. The GBLU outperforms previous datasets (the basic landform classification and global mountain assessment) in expressing landform details. GBLU can be downloaded at https://geomorph.deep-time.org. It serves as a valuable resource in facilitating a deeper understanding of landform spatial distribution and evolution, and supporting research in a diverse range of fields.

How to cite: Yang, X., Zhou, C., Li, S., Ma, J., Chen, Y., Zhou, X., Li, F., Xiong, L., Tang, G., and Meadows, M.: Incorporating ontological characteristics for global landform classification based on 30 meters DEM, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4207, https://doi.org/10.5194/egusphere-egu24-4207, 2024.

The influence of temperature as a key factor in slope stability, particularly in temperate regions, remains insufficiently explored. This study investigates the thermo-hydro-mechanical (THM) response of expansive soils, focusing on the thermally-induced activity in clay landslides.

Establishing a representative thermal variable for broad-scale assessments poses challenges due to material heterogeneities and the intricate nature of THM processes. Our research employs landslide spatial modelling in Italy, concentrating on clay-rich areas with shallow landslides on gentle slopes. Utilizing geo-lithological and geological maps and the Italian National Inventory (IFFI), we apply a Generalized Additive Model (GAM) based on slope units to capture nonlinearities in the temperature-shear strength relationship. A decade-long dataset of Land Surface Temperature (LST) from MODIS, accessible in Google Earth Engine, serves as a key input.

The study produces spatial probability maps for clay deposits across Italy, revealing a positive correlation between landslide occurrence and LST on warmer, gentle slopes, especially in Southern Italy. This aligns with the observation that higher temperatures reduce soil and water viscosity, amplifying shear creep rates in clay-rich materials. By elucidating the temperature-slope stability relationship, this study contributes to understanding landslide dynamics in temperate climates, facilitating the development of effective risk recognition strategies.

How to cite: Loche, M. and Scaringi, G.: Exploring Temperature-Shear Strength Dynamics: A Spatial Modelling Approach for Clay Landslide Susceptibility in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5190, https://doi.org/10.5194/egusphere-egu24-5190, 2024.

EGU24-6250 | ECS | Orals | GM3.2

Three-Dimensional Stress Analysis of Mountain Ranges: A Novel Approach Using Marching Volume Polytopes Algorithm and Finite Cell Method  

Viktor Haunsperger, Jörg Robl, Andreas Schröder, and Stefan Hergarten

The negative feedback between relief formation due to valley incision, increasing topographic stress towards a critical stress state dependent on rock strength, and consequently relief-destroying (and stress-reducing) landslides determines the geometry of alpine landscapes. Hence, the computation of topographic stresses for entire mountain massifs is crucial to identify potential landslide hotspots at steep landforms close to rock failure, determining the maximum strength of rocks and rock sequences at the mountain scale, and explaining contrasting geometries of alpine landscapes in dependence on the prevailing rock types. Traditional 2D stress and displacement calculations on valley cross-sections tend to oversimplify the complicated stress pattern, particularly where valleys converge or around ridges and peaks. 3D stress calculations based on standard finite element methods are computationally expensive and not feasible for entire mountain massifs at a reasonable expense.

Our study addresses this limitation by employing a novel three-dimensional approach, utilizing the Marching Volume Polytopes Algorithm for mesh generation and the Finite Cell Method as an alternative to the widely used finite element method. Incorporating an octree-like structure and advancing-front meshing techniques, the Marching Volume Polytopes Algorithm accurately represents given surface data through a tetrahedral mesh. In the Finite Cell Method representing a fictitious domain approach, the difficulty of generating adequate grids for physical domains with complicated geometry is transformed into the problem of specifying an adequate integration scheme for the finite cells and thus saving degrees of freedom. The computational efficiency of our approach is particularly advantageous when dealing with equidistant grids such as digital elevation models for mesh generation.

In a first study, we use our model to compute the 3D topographic stress distribution for the three Austrian UNESCO Global Geoparks known for over-steepened valley flanks and high landslide activity. Initial results show high shear stress maxima occurring predominantly at over-deepened glacial valleys bordered by rock faces, with stress maxima at valley flanks but also at or slightly below the valley floors. Unexpected stress patterns occur in areas with a complicated landscape geometry, where valleys converge, or intersecting ridge lines form pyramid peaks. Lithological contrasts of the investigated mountain massifs are reflected in very different stress patterns, with shear stress maxima showing the highest values in carbonate-dominated units.

In addition to local topographic metrics, the spatial distribution of observed landslides and the rock types that occur, modelled topographic stresses provide a new data set for assessing landslide potential. Beyond that, modeling topographic stresses of entire mountain massifs offers new insights into the evolution of alpine landscapes in the competition between relief-forming and relief-destroying processes.

How to cite: Haunsperger, V., Robl, J., Schröder, A., and Hergarten, S.: Three-Dimensional Stress Analysis of Mountain Ranges: A Novel Approach Using Marching Volume Polytopes Algorithm and Finite Cell Method , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6250, https://doi.org/10.5194/egusphere-egu24-6250, 2024.

Mapping benthic reefs at high resolution and accuracy is vital for the management and conservation of coral habitats. Optical remote sensing data has emerged as a valuable tool for large-scale reef mapping in the past decades, with numerous data sets and methods being utilised and developed. In this study, we present a comprehensive comparison of optical remote sensing based bathymetry and benthic mapping methods. We use different optical data including WorldView-2 stereo and Sentinel-2 imagery to map the water depths of coral reef areas in the Xisha region of the South China Sea. Bathymetry data derived from photogrammetric and linear regression methods are compared to the reprocessed Ice, Cloud and land Elevation Satellite-2 (ICESat-2) data. We find that the linear regression method (root-mean-square-error, RMSE=0.60 m) outperforms photogrammetry (RMSE=1.02 m), and the higher resolution WorldView-2 data yields less systematic biases than Sentinel-2 data. Considering that water depths reflect changes in temperature and light, which are critical factors influencing coral reef distribution, we propose to use satellite-derived bathymetry as a feature for coral reef classification. We demonstrate that combining topography and spectral information can improve the overall mapping accuracy, particularly for compositions characterised by sharp boundaries.

How to cite: Liu, Y., Zhou, Y., and Yang, X.: Bathymetry derivation and slope-assisted benthic mapping using optical satellite imagery in combination with ICESat-2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7114, https://doi.org/10.5194/egusphere-egu24-7114, 2024.

EGU24-7859 | Posters on site | GM3.2

The Performance of the Man-Kendall Test in the Analysis of Coastal Changes along Cliff Sections on the Baltic Sea 

Michael Fuchs, Lars Tiepolt, Karsten Schütze, and Jewgenij Torizin

Airborne Light Detecting and Ranging (LiDAR) surveys became essential in tracking the evolving coastal landscapes of Mecklenburg-Vorpommern on the Baltic Sea for more than one decade, producing a data series of Digital Terrain Models (DTMs) crucial for estimating coastal erosion along the exposed cliffs. Although change detection based on differences between these DTMs is supposed to represent erosion and deposition accurately, a detailed analysis indicates that the initial and final DTMs in the data series sometimes fail to capture the full extent of changes due to various factors. So, natural phenomena, such as the movement of cliff materials (rolling, sliding, creeping), human activities aimed at coastal protection, and errors in DTM processing may disturb clear trends, introducing uncertainties and, in particular, making the data series appear alternating.

To address these issues, we proposed to apply the robust Mann-Kendall test, a non-parametric statistical method used to identify trends in a data series without assuming any particular data distribution. It focuses on determining the direction and consistency of trends (ascending or descending), rather than the change’s magnitude. By implementing this approach, we can pinpoint areas that exhibit clear trends, thereby significantly improving the accuracy of coastal retreat estimations. In regions where trends are not readily apparent, it becomes crucial to investigate potential contributing factors thoroughly by exploring natural environmental dynamics, assessing the impact of human activities, and scrutinizing any errors in data processing. Such a comprehensive analysis ensures a more holistic understanding of the factors influencing these zones.

We employed the proposed approach across four distinguished shore areas characterized by the distinct geological composition of the cliffs, delving into the trends of coastal retreat over the past ten years. As expected for areas with clear trends, the estimation of the dimensions of the recent coastal retreat was in good agreement with historically recorded data. Additionally, in areas exhibiting no discernible trends, we were able to identify the underlying reasons, shedding light on the intricacies of coastal dynamics.

How to cite: Fuchs, M., Tiepolt, L., Schütze, K., and Torizin, J.: The Performance of the Man-Kendall Test in the Analysis of Coastal Changes along Cliff Sections on the Baltic Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7859, https://doi.org/10.5194/egusphere-egu24-7859, 2024.

EGU24-8222 | ECS | Posters on site | GM3.2

Automated and flexible measuring of grain size and shape in images of sediment with deep learning 

David Mair, Guillaume Witz, Ariel Henrique Do Prado, Philippos Garefalakis, and Fritz Schlunegger

The size and shape of sediment particles record crucial information on erosion, transport, and deposition mechanisms during sedimentary processes. Therefore, data on grain morphometry is a critical component in understanding sediment production and transport dynamics in various environments, such as fluvial or hillslope settings. However, traditional field methods are labor-intensive, and results may suffer from a limited number of observations. At the same time, remote measurements in images or point clouds still need improvements to counter low accuracy or the need for time-consuming manual corrections (e.g., Steer et al., 2022). These persisting challenges impede the capability of routinely obtaining size and shape information.

Here, we present a new and automated approach (Mair et al., 2023) for obtaining morphometric information on coarse sediment particles from segmented images. To do so, we tap into the capability for transfer learning of deep neural networks. In particular, we use state-of-the-art deep learning, developed to find cells in biomedical images, to segment individual grains in pictures of various sediments and image types. Our method validation includes assessing segmentation performance against ground truth from annotated images and evaluating the measurement quality by comparing results to independent measurements in the field and in images. This approach facilitates precise and rapid grain segmentation and outperforms existing methods. In addition, we observe that higher segmentation quality directly leads to improved precision and accuracy for grain size and shape data. Furthermore, any model of the used architecture can easily be re-trained for new image conditions, which we successfully did for several different settings. This highlights the potential for easy adapting to different environments and scales with comparatively small datasets.

References

Mair, D., Witz, G., Do Prado, A. H., Garefalakis, P., and Schlunegger, F.: Automated detecting, segmenting and measuring of grains in images of fluvial sediments: The potential for large and precise data from specialist deep learning models and transfer learning, Earth Surf. Process. Landforms, 1–18, https://doi.org/10.1002/esp.5755, 2023.

Steer, P., Guerit, L., Lague, D., Crave, A., and Gourdon, A.: Size, shape and orientation matter: fast and semi-automatic measurement of grain geometries from 3D point clouds, Earth Surf. Dyn., 10, 1211–1232, https://doi.org/10.5194/esurf-10-1211-2022, 2022.

How to cite: Mair, D., Witz, G., Do Prado, A. H., Garefalakis, P., and Schlunegger, F.: Automated and flexible measuring of grain size and shape in images of sediment with deep learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8222, https://doi.org/10.5194/egusphere-egu24-8222, 2024.

EGU24-10314 | ECS | Posters on site | GM3.2

A deep learning-based super-resolution DEM model for pluvial flood simulation 

Yue Zhu, Paolo Burlando, Pauy Yok Tan, Christian Geiß, and Simone Fatichi

High-resolution Digital Elevation Model (DEM) data provides essential information for pluvial flood simulation. Although the increased accessibility and quality of publicly available DEM datasets can facilitate geospatial analysis at various scales, existing DEM datasets with global coverage mostly lack sufficient spatial resolution for pluvial flood simulations, which require detailed topographic information to be included in the simulation. Simulating flood scenarios with low-resolution DEMs (>30m) can result in substantial deviations from real cases. This issue becomes even more severe for flood-prone areas in data-scarce developing countries.

Image super-resolution is a technique for reconstructing low-resolution information into high-resolution data. Various deep-learning models have been employed for this task, primarily focusing on generating high-resolution natural-colour images. However, the effects of these deep learning models on enhancing the resolution of DEM data have not been extensively investigated. One of the state-of-the-art super-resolution models, the Residual Channel Attention Network (RCAN), has gained popularity due to its accuracy and efficiency. Leveraging publicly available low-resolution global DEM data and high-resolution regional DEM data, this study assesses the performance of RCAN models in a DEM super-resolution task. The experimental results suggest that, compared to conventional interpolation methods, the tested RCAN model exhibits superior performance in constructing high-resolution DEM data. The generated super-resolution DEM data were then tested in pluvial flood simulations and achieved substantially higher realism in modelling floodwater distribution. The proposed method for constructing super-resolution DEMs opens up the possibility of simulating flooding at hyper-resolution globally.

How to cite: Zhu, Y., Burlando, P., Tan, P. Y., Geiß, C., and Fatichi, S.: A deep learning-based super-resolution DEM model for pluvial flood simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10314, https://doi.org/10.5194/egusphere-egu24-10314, 2024.

EGU24-11527 | ECS | Orals | GM3.2

Identification of river channel bankfull geometry from topographic indicators extracted from high-resolution digital elevation datasets  

Valeria Ruscitto, Michele Delchiaro, Wolfgang Schwanghart, Eleonora Brignone, Daniela Piacentini, and Francesco Troiani

River channel bankfull geometry and discharge are important features providing valuable insights into fluvial monitoring and flood recurrency. The bankfull stage represents the riverbank position that approximates the level at which water overflows onto the floodplain. Bankfull discharge is considered the channel-forming discharge, with a recurrence interval of approximately 1.5 years. Bankfull floods are significant, as they are highly effective in changing channel shape and characteristics. Their recurrence intervals can be used for stream assessment and have implications for infrastructure design and flood mapping. Additionally, gaining insights into the factors influencing floodplain inundation across various time periods is crucial, as the frequency of flood events is predicted to rise with the increase in global temperatures.

In this contribution, we present a novel approach to identify the bankfull geometry through a set of dedicated MATLAB functions. A Digital Elevation Model (DEM) with ground resolution of 1 m/pixel is used as input elevation dataset, obtained with airborne LiDAR (Light Detection and Ranging) survey. The selected river channels are divided in regularly spaced sampling sections, where the bankfull geometry is extracted. Then, the hydraulic depth function that plots the elevation above the river thalweg vs. the ratio between the area and the width is computed for every section. Then, the elevation above river associated to the lowest and the most prominent peaks of the function, corresponding respectively to the bankfull stage or bankfull/floodplain inflection point and to the floodplain, are automatically extracted for each section. Manning’s equation is then applied to the hydraulic geometry corresponding to the lowest peaks elevation to compute the bankfull discharge at every river channel section. The validation process includes the comparison between the results obtained through the automatic bankfull geometry and discharge estimation and discharge data available from river hydrological gauges. Results demonstrate that the developed approach is effective to delineate the bankfull geometry from high-resolution DEMs and complements traditional qualitative field observations. Thus, our approach represents a cost-effective alternative for mapping detailed spatial variations over large spatial extents that are difficult to cover with traditional fieldwork.

How to cite: Ruscitto, V., Delchiaro, M., Schwanghart, W., Brignone, E., Piacentini, D., and Troiani, F.: Identification of river channel bankfull geometry from topographic indicators extracted from high-resolution digital elevation datasets , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11527, https://doi.org/10.5194/egusphere-egu24-11527, 2024.

EGU24-12288 | Posters on site | GM3.2

TopoToolbox 3 – avenues for the future development of a software for terrain analysis 

Wolfgang Schwanghart, William Kearney, Anna-Lena Lamprecht, and Dirk Scherler

The Earth’s surface results from the interplay of tectonic and erosive forces, and the action of organisms and humans. To gain a deeper understanding of these interactions, accurate monitoring and analysis of topography is essential. Digital elevation models (DEMs) are powerful tools for achieving this goal and are available at ever increasing spatial resolution. TopoToolbox is a research software that provides a “laboratory” for the analysis of DEMs, enabling customized, automated analysis, prototyping and creative method development. Its high computational efficiency, ease-of-use and extensive documentation have attracted a worldwide user base across multiple research disciplines.

Over the last ten years, TopoToolbox, now in version 2, has undergone numerous changes and additions. The development of version 3 of TopoToolbox seeks to build on those past successes and take the software to the next level. Specifically, our goals are (1) to improve usability and accessibility, (2) to enhance quality assurance in the software’s development process, and (3) to increase community involvement in the ongoing development of TopoToolbox. We strive to achieve these goals in a recently funded 2-year project, in which community involvement is a key aspect. In this presentation, we aim to interact with other researchers interested in terrain analysis to discuss avenues for future developments and activities that improve TopoToolbox's usability, expand its usage, and increase its impact in a new version 3.

How to cite: Schwanghart, W., Kearney, W., Lamprecht, A.-L., and Scherler, D.: TopoToolbox 3 – avenues for the future development of a software for terrain analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12288, https://doi.org/10.5194/egusphere-egu24-12288, 2024.

After successfully applying segmentation and machine learning for landform identification and delineation for concave, convex, and generic landforms (landslides, floodplains), the used approach is generalized as a framework. The approach can be implemented in any GIS software that allows scripting and is based on four steps: (i) object-based segmentation based on a specific geomorphometric variable, (ii) contextual merging if the landform is composed of multiple shapes, (iii) selection of the training data segments, (iv) statistical classification by machine learning. The framework refers to creating a set of rules for various scenarios of landform types to allow the implementation of the approach for various landforms and areas around the globe. One of the main requirements regarding the DEM is that its feature resolution be high enough to allow at least a segment to cover the target landform spatially. This requires either LiDAR or RADAR DEMs, with medium or high resolution. We tested COPDEM in areas where there is no vegetation cover and the results show that landslides, floodplains, gullies, sinkholes, and closed depressions can be depicted by the approach.

How to cite: Niculita, M.: A generic framework for the identification and delineation of landforms from high-for DEMs using segmentation, contextual merging, and machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13034, https://doi.org/10.5194/egusphere-egu24-13034, 2024.

EGU24-13135 | Posters on site | GM3.2

Spectral analysis as proxy for lineament spatial distribution: validation and case study 

Anna Maria Dichiarante, Tim Redfield, Espen Torgersen, Anne Kathrine Svendby, and Volker Oye

Spectral analysis (SA) is a technique commonly used in signal and image processing that makes use of the Fast Fourier Transform to compute the 2D power spectrum, which is a representation of the magnitude of each frequency component of the signal or image. SA can be similarly performed on a topographic map, and the orientation, frequency and magnitude (or power) of general topographic trends can be automatically retrieved and displayed in the 2D power spectrum. Recent studies have shown that spectral analysis can be successfully used to characterize repetitive and spatially homogeneous features or landforms, such as ridge and valley or glacial lineations. However, although these repetitive features dominate the 2D power spectrum, all the topographic information of the map is still present. Therefore, SA can be used on heterogenous and complex topographic map as a proxy for lineament analysis.

Lineament analysis is broadly used in a wide number of applications which include tectonic studies, exploration for groundwater, hazard evaluation for tunnel excavation, rockfalls or waste repository etc. Here, we propose a new methodology for lineament analysis based on spectral analysis and we demonstrate that this is a fast and effective way to derive lineament spatial distribution from images that can be visualized as rose diagrams. To validate our methodology, we stochastically generated 1000 synthetic lineament networks and numerically compared the rose diagrams derived from the power spectra to known lineament distribution. The comparison held a similarity of 94%.

The methodology was also applied to the Oslo region and compared to automatically extracted lineaments from OttoDetect software (developed by the Geological Survey of Norway). Results on three pre-selected areas characterized by different topographic patterns showed similarity of 97%, 95%, and 90%, respectively.

One of the pitfalls of spectral analysis is the lack of positioning on the original map of the signatures in the power spectrum. To locate the main signature on the map, we used the orientation of the main signatures from the power spectrum and used cross-correlation and clustering methods on topographic profiles.

How to cite: Dichiarante, A. M., Redfield, T., Torgersen, E., Svendby, A. K., and Oye, V.: Spectral analysis as proxy for lineament spatial distribution: validation and case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13135, https://doi.org/10.5194/egusphere-egu24-13135, 2024.

EGU24-13867 | ECS | Orals | GM3.2

The effect of correcting the projection error in Digital Terrain Models on Earth surface processes 

Anne Voigtländer, Aljoscha Rheinwalt, and Stefanie Tofelde

Hiking up a steep mountain, in comparison to walking on a flat beach, is unarguably different. But the horizontal distance made, estimated using a Digital Terrain Model (DTM), might be the same. The projection of 3D landscapes onto 2D grids in DTMs leads to a slope-dependent, inhomogeneous sampling of the surfaces, and a first-order error in topographic metrics. Using the slope dependency of this error, we can quantify and revert it. Foremost, correcting the projection error allows for more accurate estimates of area and volume, e.g., to quantify natural hazards; and enables the use of the full slope distribution to define the physical space of surface processes at any scale.

We quantify the projection error using synthetic landscapes for which analytical solutions of slope angles and surface area are known. In applying the correction to DTM data of a real landscapes, we can address geomorphological processes in physically more meaningful ways. The corrected extracted topographic proxies, here exemplary, the erosional response to uplift in the Mendocino Triple Junction (MTJ) area, California, USA, provide two aspects for interpretation of geomorphic processes. First, as all slope angles are now represented equally, the variations in slope distribution by region of uplift rate is more pronounced. Second, the erosional response causes not only a steepening but narrow slope distribution in the regions of high uplift. The transient response is visible in a broadening of the distribution towards the lower slope angles, as deposition becomes more prevalent. In this example, we also find that the surface area ratio, enables determining the effectiveness of Earth surface processes, by increasing or decreasing the differential between the standard-planform and the surface area. Earth surface processes, that involve transport and volume along the surfaces, if not referenced in time, the ratio between the planform and surface area can provide a spatial reference and could be explored further. Correcting topographic metrics also allows addressing additional questions, like, which slope angles characterize which process domains, which processes create steepening, which lowering of slopes, where, and to what extent? Or, which parts of landscapes, maybe not the steepest, correlate to the highest potential to erode?

 

How to cite: Voigtländer, A., Rheinwalt, A., and Tofelde, S.: The effect of correcting the projection error in Digital Terrain Models on Earth surface processes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13867, https://doi.org/10.5194/egusphere-egu24-13867, 2024.

The integration of point-cloud data in geo- and environmental sciences has become increasingly pivotal, with applications ranging from UAVs, spaceborne and airborne lidars to ground-based lidars and stereo-photogrammetric techniques. This session seeks contributions that delve into challenges related to classification, segmentation, and noise removal in the context of point-cloud data, crucial for facilitating change detection studies. Our study focuses on the Navigational Branch of the ERDC Coastal Hydraulics Laboratory tasked with developing a Digital Twin model for a Dam, exemplifying the complexities involved in creating CAD models of terrain and structures.

To address the intricacies of point-cloud data processing, we employed both open-source and proprietary software solutions—Cloud Compare and Autodesk ReCAP— for noise reduction, ensuring the prepared data is seamlessly integrated into CAD modeling software, specifically Inventor. Surface modeling involved the strategic application of planes on cloud points to generate a foundation for sketching and subsequent solid surface extrusion.

Classification of data points was initiated through the implementation of regions in the noise removal software, facilitating the depiction of various areas on the model. Further, color and material assignment in the CAD software enhanced the identification of distinct part areas. Microstation TopoDOT played a pivotal role in creating a detailed terrain model, complete with physical landmarks and water bodies specific to the Dalles dam site.

The resulting models were exported in the desired file format, ensuring compatibility with sponsor requirements. This case study not only showcases the practical challenges encountered in working with point-cloud data but also highlights effective strategies for noise reduction, classification, and model exportation. The presented methodologies contribute to the broader spectrum of geo- and environmental sciences, emphasizing the significance of accurate point-cloud processing for comprehensive modeling endeavors.

How to cite: Krapac, M.: Advancements in Point-Cloud Processing for Geo-Environmental Modeling: A Case Study of The Dalles Dam Digital Twin Creation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14080, https://doi.org/10.5194/egusphere-egu24-14080, 2024.

EGU24-14955 | Posters on site | GM3.2

Multi-Technique Analysis and Landscape Evolution: Implications for Landslide-Fluvial Cascading Hazards Assessment 

Marta Guinau, Celeste Fernández-Jiménez, Anna Barra, Marc Viaplana-Muzas, Ariadna Flores, Maria Ortuño, Marta González, Jordi Pinyol, and Clàudia Abancó

The interaction between slope instability processes and river dynamics often triggers a cascade effect. Sediment influx from slopes can obstruct rivers, leading to upstream flooding and potential catastrophic flash floods downstream upon dam breakage. In addition, the incision of the drainage network steepens the valley hillslopes, further exacerbating slope instability processes, modifying the geomorphology and the sedimentary fluxes and increasing the occurrence of landslide-derived hazards.

In this regard, a comprehensive and updated landslide inventory, especially focusing on the interconnection between landslides and drainage networks, is crucial for effective hazard assessment considering these cascading effects induced by slope and fluvial processes.

This study presents advancements in landslide mapping by integrating data from Multi-Temporal Synthetic Aperture Radar (MT-InSAR) and landscape evolution analysis through geomorphological indices such as Chi, Normalized Channel Steepness Index (Ksn) and Stream Length-Gradient Index (SL). Identification of anomalies along rivers using Ksn and SL (knickpoints or knickzones) aided in pinpointing abnormal slopes due to sediment influx from landslides. Additionally, active areas were delineated using the ADAfinder tool, extracting data from MT-InSAR provided by the European Ground Motion Service (EGMS). This multi-technique analysis highlighted the slopes of interest. Landslides identified with these techniques were delimited and characterized in terms of type assignment, using 2x2 m DTM hillshades derived from airborne LiDAR data and field observations.

The upper catchments of the Garona and Noguera Pallaresa rivers (central Pyrenees-NE Spain) were selected as study cases. The study highlights the disequilibrium in the watershed divide between Noguera Pallaresa and Garona basins, suggesting a transition toward equilibrium favouring a main divide migration towards the Noguera Pallaresa due to hillslope processes. The assessment of the equilibrium profile geometry of the Noguera Pallaresa river at a regional scale suggests at least two main knickpoints. The river sections downstream of the knickpoints are associated with landslides triggered by post-glacial dynamics and incision wave effects. Combining SL and Ksn curves with Active Deformation Areas (ADA) underscores areas with potentially reactivating deep-seated landslides, signifying potential high damages in case of low-probability but catastrophic reactivations.

In conclusion, the integration of diverse methodologies shed light on the spatial relationship between transient features in the landscape (knickpoints) and landslide occurrence, emphasizing the need for a comprehensive approach to mitigate landslide and fluvial risks in the Noguera Pallaresa and Garona river basins.

How to cite: Guinau, M., Fernández-Jiménez, C., Barra, A., Viaplana-Muzas, M., Flores, A., Ortuño, M., González, M., Pinyol, J., and Abancó, C.: Multi-Technique Analysis and Landscape Evolution: Implications for Landslide-Fluvial Cascading Hazards Assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14955, https://doi.org/10.5194/egusphere-egu24-14955, 2024.

EGU24-15001 | Orals | GM3.2 | Highlight

Applying photogrammetry to time-lapse imagery for geomorphological change detection 

Anette Eltner, Xabier Blanch, Oliver Grothum, Lea Epple, Eliisa Lotsari, Katharina Anders, and Melanie Elias

Cameras that capture images in time-lapse mode of the earth surface enable great opportunities for change detection and thus potential process identification and understanding. The camera systems can range from simple and robust game cameras to complex and synchronised full frame cameras. The main workflow of calculating digital elevation models from overlapping images is similar for the different types of systems; automatically matching the images, performing bundle adjustment considering either calibrated or non-calibrated cameras, geo-referencing the data by automatic ground control point (GCP) measurement, densifying the point cloud and eventually calculating point cloud differences. However, adapted pre-and post-processing steps are needed due to the varying observation conditions considering the camera qualities and the objects of interest. The time-series of point cloud-based change information can be further processed, for example, with time-series clustering approaches to disentangle overlapping processes.

We will introduce three different case studies in the field of fluvial geomorphology, soil erosion research and rockfall assessment. Thereby, different camera systems are utilized. Four low-cost time-lapse cameras are applied in arctic environments to study changes of a river bank at a distance of about 60 m. The high robustness of the cameras encompasses the trade-off of low quality images. In addition, challenging lighting conditions and enduring snow cover complicate the photogrammetric processing. The images are captured with a frequency of two hours, and six permanent GCPs are used to geo-reference the measurements.

Digital SLR cameras are used in moderate climate to measure soil surface changes either due to rainfall simulations or due to natural rainfall events. During the rainfall simulation we use images that are captured by up to ten cameras with a frequency of 10 to 20 seconds and at an object distance between 3 to 4 m. And at the field plot we installed three special camera rigs that encompass five cameras each that are event-controlled by a micro-controller and single board computer solution, which trigger the cameras each time a rain collector bucket is tipping in addition to daily captured images. Challenges for change detection arise from vegetation present at the plots and from runoff water covering the soil surface. Eventually, the derived models of change are used to validate physical based soil erosion models.

The last case study utilizes five full-frame system cameras in the Mediterranean to detect single rockfall events. Images are captured three times a day by an ad-hoc system at a distance of about 100 m. The data is transferred via a locally installed network module. Many areas within the field of view remain stable throughout the measurement period allowing for a time-SIFT approach that matches the images from different points in time. Machine learning algorithms are applied to automatically identify rockfalls in the final 4D dataset. Thereby, we showcase the great potential of time-lapse photogrammetry for different applications of geomorphological change detection.

How to cite: Eltner, A., Blanch, X., Grothum, O., Epple, L., Lotsari, E., Anders, K., and Elias, M.: Applying photogrammetry to time-lapse imagery for geomorphological change detection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15001, https://doi.org/10.5194/egusphere-egu24-15001, 2024.

EGU24-15418 | ECS | Posters on site | GM3.2 | Highlight

A definition of land surface geomorphodiversity across different scales 

Martina Burnelli, Laura Melelli, Francesco Bucci, Michele Santangelo, Federica Fiorucci, and Massimiliano Alvioli

Geodiversity is “the variety of abiotic features and processes of the land surface and subsurface” [1,2]. Consensus is growing that geodiversity is the geosphere counterpart of what biodiversity represents within the biosphere, atmosphere, and hydrosphere [2]. Thus, it is potentially relevant to ecosystem functions and services [2]. Since the introduction of geodiversity, several scholars studied it from the theoretical and practical points of view, with different approaches, assumptions and purposes. Methods to define diversity of the geosphere are quantitative, qualitative, or a combination of the twos, with the occasional addition of heuristics [3].

Here, we describe a quantitative derivation of a subset of geodiversity, namely, geomorphodiversity. The effort stems from the need of an objective method, apt to providing easy to understand results, readily available for subsequent applications. To that end, requirements are in order about the data included in the analysis: they should be widely available, to allow reproduction of the analysis in most geographical locations, and they should contain enough information to approximate real-world geodiversity.

Geomorphodiversity is one implementation fulfilling the requirements, obtained in the literature by different groups, for different locations [4,5], using simple geomorphometry. Data for the method implemented in Italy [6] are a digital elevation model (EUDEM, 25 m resolution), and a lithological map at 1:100,000 scale [7]. DEM provides derived quantities such as slope, drainage network, landforms [8] and slope units [9], all of which contribute in different ways to produce partial diversity maps. We eventually combine partials into an overall geomorphodiversity raster index, GmI, distinguishing five classes of land surface diversity.

The inherent parameter dependence in the existing implementations of GmI, partially resolved in [6], is one issue to overcome. Free parameters are embedded in the size of neighborhoods (moving windows, or focal statistics) used to calculate the variety, the arbitrary output resolution, and procedures to polish the final raster diversity map from artifacts. We suggest a multiple assessment of the variety of partial abiotic parameters with a full range of different neighborhood sizes, and a-posteriori statistical selection of local values of diversity. This results in a parameter-free approach to GmI, also allowing a custom resolution of the output, with the lower bound of DEM resolution.

We consider a parameter-free geomorphodiversity as a measure of the potential of morphological evolution of the landscape, useful to investigate natural and human-induced diversity in urban areas [10], in combination with accurate, local mapping of geomorphological landforms [11].

 

References

[1] Gray, (2004) Geodiversity: valuing and conserving abiotic nature. ISBN 978–0–470-74215-0

[2] Schrodt et al., PNAS (2019) https://doi.org/10.1073/pnas.1911799116

[3] Zwoliński et al., Geoheritage (2018) https://doi.org/10.1016/B978-0-12-809531-7.00002-2

[4] Benito-Calvo et al, Earth Surf Proc Land (2009) https://doi.org/10.1002/esp.1840

[5] Melelli et al., Sci Tot Env (2017) https://doi.org/10.1016/j.scitotenv.2017.01.101

[6] Burnelli et al., Earth Surf Proc Land (2023) https://doi.org/10.1002/esp.5679

[7] Bucci et al., Earth System Science Data (2022) https://doi.org/10.5194/essd-14-4129-2022

[8] Jasiewicz et al., Geomorphology (2013) https://doi.org/10.1016/j.geomorph.2012.11.005

[9] Alvioli et al., Geomorphology (2020) https://doi.org/10.1016/j.geomorph.2020.107124

[10] Alvioli, Landscape and Urban Planning (2020) https://doi.org/10.1016/j.landurbplan.2020.103906

[11] Del Monte et al., Journal of Maps (2016) https://doi.org/10.1080/17445647.2016.1187977

How to cite: Burnelli, M., Melelli, L., Bucci, F., Santangelo, M., Fiorucci, F., and Alvioli, M.: A definition of land surface geomorphodiversity across different scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15418, https://doi.org/10.5194/egusphere-egu24-15418, 2024.

EGU24-15904 | Orals | GM3.2

Mapping gold mines under the French Guiana rainforest: return of experience with different mobile lidar systems 

Thomas Dewez, Sébastien Linares, Silvain Yart, Florian Masson, Marie Collignon, Lucas Rivera, Caroline Bedeau, and Matthieu Chevillard

Gold is abundant in the greenstone belts of the Guiana shield, in South America, leading to alluvial mining in river sediments and in in-situ rocks. In French Guiana, legal mining takes place under strict environmental regulations and controls, but illegal operations also occur uncontrolled in the vast expanses of the rainforest. Here we describe a successful range of mobile lidar systems, acquisition schemes and processes to map the ground and underground mining operations in a rainforest context. We seek to detect illegal operations, supply and transportation pathways and base camps, using crewed planes and helicopters, uncrewed fixed-wing and multi-copter vehicles (UAV) and handheld lidar systems.

To sense ground elevation below the canopy, airborne lidar systems face three challenges: tree heights (some trees exceed 70 m in height), incised topography (requires performant terrain following capabilities), dark and wet ground surface largely absorbs lidar pulses requiring powerful sources. Tested uncrewed airborne vehicles (UAV) did not yet meet all of the flying autonomy, terrain-following capability, lidar range and on-board decision systems. At present, crewed systems adapt better to conditions and achieve mission objectives.

Over forested areas, observed canopy penetration rates is of the order of 1 ground point for 250 lidar pulses (0.4%). To generate a 1-m/pixel Digital Terrain Model (DTM) with a minimum of occluded pixels, acquisition density should exceed 250 pts/m² at canopy level everywhere. In Dorlin (central French Guiana), a helicopter flew 85-m-above ground-level, 70 % side-lap and 90° cross-lines, using a Riegl VUX-1LR lidar. Targeting 400 pts/m² at canopy-top for 95 % of the 220 ha territory, it reached a canopy-top density of 1400 +/- 750 pts/m² and 43 pts/m² ground density overall. On fully forested areas, ground density dropped to 22.4+/-22.6 pts/m² with 5% of the surface never receiving points at 1 m² level. This enabled interpolation of a 25cm/pixel DTM, which revealed narrow paths, quad tracks, and shaft platforms and head frames under the forest. 2-m kernel high-pass filtering enhanced features better than a standard hill shading. Base camp hut structures, invisible in DTM, are retrievable from native point clouds in a 4 to 5 m-above-ground elevation range. Huts covered in black tarpaulins stand out as rectangular hollow patches due to lidar photon absorption. But even without tarpaulin, hut wooden frames stand out particularly well when point cloud subsets are lit up with the PCV filter of Cloud Compare. Ore-bearing quartz stockpiles however are too small and occluded for a reliable detection and volume computation.

Instead, SLAM-based handheld lidar systems (GeoSLAM Zeb-Revo and Zeb-Horizon) complement the detailed mapping of quartz stockpiles volume, shaft conduit geometry and gallery entrances. Then real-time, SLAM-based quadcopter UAV lidar (Flyability Elios 3) safely penetrates shafts from the surface to explore the undergound gallery network. These new millimetre-scale density point clouds critically reveal spacing, orientation and dimensions of ore-bearing veins, which improves the metallogical understanding of the site and uniquely documents the way artisanal illegal miners operate.

Lidar acquisitions and processing are now being streamlined for systematic use in law enforcement operations and environmental protection actions.

How to cite: Dewez, T., Linares, S., Yart, S., Masson, F., Collignon, M., Rivera, L., Bedeau, C., and Chevillard, M.: Mapping gold mines under the French Guiana rainforest: return of experience with different mobile lidar systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15904, https://doi.org/10.5194/egusphere-egu24-15904, 2024.

EGU24-16317 | Orals | GM3.2

Debris flow catchments and landscape evolution in the northern Colombian Andes 

Edier Vicente Aristizábal Giraldo and Oliver Korup

Fans are cone-shaped depositional landforms composed of a mixture of sediments, mainly derived from debris flow processes at the catchment scale. In mountainous terrains located in humid climates, debris flows are fundamental agents of landscape evolution and a highly destructive natural hazard. In the northern Colombian Andes, fans have been traditionally occupied by human settlements, which has also produced a long history of disasters in many settlements located on fans. For example, a debris flow on November 13, 1985, devastated the city of Armero, killing approximately 22,000 people and causing economic losses totaling over $US 339 million. In 2017, the city of Mocoa was affected by a debris flow where 333 people died, 130 houses were destroyed, and 1461 were partially affected.

Debris-flow risk is likely to increase as a consequence of the increasing magnitude and frequency of extreme weather and rapid population growth over the past few decades. Hence, identifying fan spatial distribution and debris flow occurrences is important for land use planning. In this study, we implemented geomorphometric analyses in the northern Colombian Andes to understand debris flow occurrence in terms of landscape evolution. Using digital elevation models, fan inventory, morphometric parameters, and geomorphic indices associated with the drainage network at the catchment scale, the close interconnection between debris-flow hazards and landscape evolution is explained.

The results show a clear spatial pattern of fans location and debris-flow-prone basins with knickpoint upstream migration and transient-state catchments, those characterized by high values of Ksn, hypsometric index and constraint values of 𝛘. Those findings suggest that landscape evolution indexes could improve debris flow susceptibility assessment at regional scale.

How to cite: Aristizábal Giraldo, E. V. and Korup, O.: Debris flow catchments and landscape evolution in the northern Colombian Andes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16317, https://doi.org/10.5194/egusphere-egu24-16317, 2024.

EGU24-16412 | ECS | Orals | GM3.2

Deep-Image-Matching: an open-source toolbox for multi-view image matching of complex geomorphological scenarios 

Francesco Ioli, Luca Morelli, Livio Pinto, and Fabio Remondino

Geomorphometry and geomorphological mapping are essential tools for understanding landscape changes. The recent availability of 3D imaging sensors and processing techniques, including Artificial Intelligence, is offering interesting solutions for gemorphometric analyses and processes understanding. Photogrammetry stands as a pivotal image-based tool in geomorphology, enabling accurate 3D reconstruction of complex natural environments and effective tackling of multi-temporal monitoring challenges. A key step in photogrammetry is the identification of corresponding points between different images, traditionally achieved through the extraction and matching of local features such as SIFT and ORB. However, these methods face difficulties when using images of complex environments scenarios. Deep Learning (DL) methods have recently emerged as powerful tools to address challenges such as strong radiometric variations and viewpoint changes (Morelli et al., 2022; Ioli et al., 2023). However, their practical application in photogrammetry is hindered by the lack of libraries integrating DL matching into standard SfM pipelines.

The presentation will introduce the recently developed Deep-Image-Matching, an open-source toolbox designed for multi-view image matching using DL approaches, specifically tailored for 3D reconstruction in complex scenarios (https://github.com/3DOM-FBK/deep-image-matching). This tool can be used to achieve a 3D reconstruction with wide camera baselines and strongly varying viewpoints (e.g., with ground-based monitoring cameras), with datasets involving varying illumination or weather conditions typical of multi-temporal monitoring, with historical images, or in low-texture situations (e.g., snow or bare ice).

Deep-Image-Matching provides the flexibility to choose from a variety of local feature extractors and matchers. Supported methods include traditional local feature extractors, such as ORB or SIFT, as well as learning-based methods, such as SuperPoint, ALIKE, ALIKED, DISK, KeyNet + OriNet + HardNet, and DeDoDe. Matcher choices range from traditional nearest neighbor algorithms to state-of-the-art options like SuperGlue and LightGlue. Available semi-dense matching solutions include the detector-free matchers LoFTR and RoMa.

To handle high-resolution images, the tool offers a tiling process. In case of strong image rotations, such as aerial stripes, images are automatically rotated before matching. Image pairs for matching can be selected by exhaustive brute-force matching, sequential matching, low-resolution guided pairs selection, or global descriptor-based image retrieval. Geometric verification is used to discard outliers among matched features. The extracted image correspondences are stored in a COLMAP database for further processing (i.e. bundle adjustment and dense reconstruction) or can be exported in other formats useful for other open-source and commercial software.

The presentation will highlight how image-based geomorphometry and geomorphological mapping could benefit of the realized tool and how complex environmental scenarios (landslides, glaciers, etc.) could be analysed and monitored with the support of deep learning.

References:

Ioli, F., Bruno, E., Calzolari, D., Galbiati, M., Mannocchi, A., Manzoni, P., Martini, M., Bianchi, A., Cina, A., De Michele, C. & Pinto, L. (2023). A Replicable Open-Source Multi-Camera System for Low-Cost 4D Glacier Monitoring. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., 48, 137-144

Morelli, L., Bellavia, F., Menna, F., & Remondino, F. (2022). Photogrammetry Now and Then - From Hand-Crafted to Deep Learning Tie Points. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2/W1-2022, 163–170

How to cite: Ioli, F., Morelli, L., Pinto, L., and Remondino, F.: Deep-Image-Matching: an open-source toolbox for multi-view image matching of complex geomorphological scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16412, https://doi.org/10.5194/egusphere-egu24-16412, 2024.

EGU24-18657 | ECS | Posters on site | GM3.2

Tailoring slope units delineation according to different natural phenomena for institutional land use planning at the regional scale 

Rossana Napolitano, Michele Delchiaro, Leonardo Maria Giannini, Claudia Masciulli, Giandomenico Mastrantoni, Marta Zocchi, Massimiliano Alvioli, Paolo Mazzanti, and Carlo Esposito

The Latium region (Central Italy) is currently updating the institutional hydro-geological plan, one of the main planning tools to prevent geo-hydrological hazard at regional scale. The plan focuses on landslides, erosion and hydraulic hazard assessment using both conventional and innovative approaches. This analysis required different scales of study, according to the different processes acting on slopes, and their broader physiographic context. In this multiscale approach, slope units represent the most suitable territorial units of analysis and mapping, considering their morpho-hydrological representativeness and scalability.

Slope units are a particular type of terrain units, characterized by internal homogeneity and external heterogeneity, delineated from a digital elevation model considering the natural setting of the territory. A widely used tool for slope unit delineation is the software ‘’r.slopeunits’’ [1,2]. The parameters controlling the delineation are both morphological and hydrological, derived from a digital elevation model. The software implements an iterative and adaptive process, depending on the aforementioned parameters, resulting in slope unit sets optimized for the local morphology. The accurate selection of input parameters requires careful consideration, but it also allows extra flexibility in defining the proper scale of the output slope unit map.

Here, we aim at obtaining a new way to select the values of the software’s input parameters, considering their relations with the different processes, to single out the proper scale of analysis. Specifically, we provide additional terrain analysis methods to find “good” parameter ranges, implemented in simple computer scripts that make use of r.slopeunits. The workflow is organized as follow. First, the geomorphological domains (i.e. hillslope, unchanneled, and fluvial domain) are discriminated by the implementation of the slope – area function, with the area weighed by the runoff values available from the GIS-based model BIGBANG [3]. Next, the flow paths related to the hillslope and unchanneled domains and related basins are hierarchized using Strahler ordering. Then, delineation of basins and half-basins for every path order is computed. Finally, implementation of zonal statistics functions on the half-basins of every path order and calculation of the parameters ranges that for slope unit delineation is performed.

Implementation of a multi – scale derivation of slope units with a range of input parameters, customized according to the type of natural phenomena (landslide, flooding, erosion etc.), allows an adaptive multi – scale approach, specific for each process, for a comprehensive multi-hazard evaluation. One of the future applications of the research is the application of this approach for the definition of ‘’buffer zones’’ covered by natural or semi-natural vegetation, capable of counteracting slope instabilities. In the context of the hazard and risk mitigation management, these outcomes could represent an efficient aid for regulating urban development in a proper and secure manner.

 

References

[1] Alvioli et al. (2016). Geosci Mod Dev, https://doi.org/10.5194/gmd-9-3975-2016

[2] Alvioli et al. (2020). Geomorphology, https://doi.org/10.1016/j.geomorph.2020.107124

[3] BIGBANG model, https://www.isprambiente.gov.it/pre_meteo/idro/BIGBANG_ISPRA.html

 

How to cite: Napolitano, R., Delchiaro, M., Giannini, L. M., Masciulli, C., Mastrantoni, G., Zocchi, M., Alvioli, M., Mazzanti, P., and Esposito, C.: Tailoring slope units delineation according to different natural phenomena for institutional land use planning at the regional scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18657, https://doi.org/10.5194/egusphere-egu24-18657, 2024.

EGU24-18943 | ECS | Posters on site | GM3.2

Reconstructing ancient coastal landscapes and sea-level stands in Southern Italy (Cilento coast): a geostatistical approach 

Alessia Sorrentino, Gaia Mattei, and Pietro Patrizio Ciro Aucelli

This research aims to obtain coastal paleo-environmental reconstructions through the analysis of direct and indirect paleo sea-level markers (SLMs, i.e., SLIPs, TLPs, MLPs) by GIS-aided geostatistics.  

In this work, we used classical SLMs combined with a caves inventory in the Cilento area in the Campania Region (Southern Italy). In this area, mainly characterized by carbonatic rocks, numerous emerged and submerged caves are present along active and fossil cliffs as evidenced in the papers of Antonioli et al., 1994 and Esposito et al., 2002.  

As reported in Ferranti, 1998 and Florea et al., 2007, coastal caves can be considered positively correlated to the glacial-hydro-eustatic sea-level oscillations, especially on the carbonatic substratum.  

Therefore, caves cannot be classified as sea-level markers (SLMs) strictu sensu, anyway, they can be considered as a mark of ancient sea-level position, especially when the occurrence of floor elevation is well-distributed all along the coast (in the case of areas characterised by homogeneous tectonic behaviour). In detail, in this work, the floor elevation of the cave entrances was correlated with tidal notches, wave-cut platforms, Lithophaga burrows, and marine deposits deriving both from previous knowledge and new direct and indirect surveys carried out through classic geomorphological investigations and using robotic technologies and remote sensing.  

All collected data were used to produce a specific geodatabase “PALEOScape (PALEO SeasCAPE)” (Sorrentino et al., 2023) structured based on international standards for sea-level studies. Caves information was obtained from an existing caves’ Inventory (Federazione Speleologica Campana; Russo et al., 2005) integrated by field surveys. Thanks to the well-documented tectonic stability of the area, it was possible to ascribe at the same age SLMs having the equal altimetric position.

These records were analysed by a geostatistical approach by correlating the cave entrances to known sea-level stands increasing the information available on paleo sea-level stands along the examined coast.

By integrating this approach with a new method for semi-automatic landform recognition and classification, it was possible to reconstruct ancient coastal landscapes related to known sea level stands, but also to some new altimetric positions not previously reported in the area.

REFERENCES

Antonioli, F., Cinque, A., Ferranti, L., & Romano, P. 1994. Emerged and Submerged Quaternary Marine Terraces of Palinuro Cape (Southern Italy). Memorie Descrittive Carta Geologica d’Italia, 52, 237–260.

Federazione Speleologica Campana https://www.fscampania.it/catasto-2/catasto/  

Ferranti, L. 1998. Underwater cave systems in carbonate rocks as semi-proxy indicators of paleo-sea levels. Il Quaternario-Italian Journal of Quaternary Sciences, 11(1), 41-52.

Florea, L. J., Vacher, H. L., Donahue, B., Naar, D. 2007. Quaternary cave levels in peninsular Florida. Quaternary Science Reviews, 26(9-10), 1344-1361.

Russo, N., Del Prete, S., Giulivo, I., Santo, A. 2005. Grotte e speleologia della Campania : atlante delle cavità naturali. Elio Sellino Editore.

Sorrentino, A., Maratea, A., Mattei, G., Pappone, G., Tursi, M. F., Aucelli, P. P. 2023. A GIS-based geostatistical approach for palaeo-environmental reconstructions of coastal areas: the case of the Cilento promontory (southern Italy). In 2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea) (pp. 488-493). IEEE.

 

How to cite: Sorrentino, A., Mattei, G., and Aucelli, P. P. C.: Reconstructing ancient coastal landscapes and sea-level stands in Southern Italy (Cilento coast): a geostatistical approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18943, https://doi.org/10.5194/egusphere-egu24-18943, 2024.

EGU24-20335 | ECS | Posters on site | GM3.2

 Bivariate mountain definition: a case study for the turkish mountain system  

Neslihan Dal and Tolga Görüm

Türkiye, 61% of which consists of mountains, has an extremely rugged topography. Anatolia, which is located in the collision zone of plates with different characteristics, exhibits a morphological character with different stages of mountain formation due to the Paleotectonic and Neotectonic movements it has been exposed to during geological times. In Anatolia, where the main physiographic character is mountains, the proportion and boundaries of mountains and mountainous areas have not been quantitatively defined and there has not been a geomorphometric approach to this until now. In this study, the mountain definition obtained from the pixel-based and multi-scale basic data matrix was subjected to various analyzes with the modeling created in geographic information systems. In addition, how the mountain definition and classification change at varying scales and thresholds is revealed.

The characterization has two main purposes: To determine the framework of the methodology in the definition of macro landforms and to determine the most optimum model that quantitatively defines mountain and mountainous area. According to the model, mountains cover 61% of Türkiye. In this context, in addition to developing a model to geomorphometrically define mountain and mountainous area characterization, the thesis approaches mountains, which are a macro morphological landform, from an ontological perspective and approaches the questions we asked at the beginning in terms of geographical epistomology. In this respect, the thesis is a contribution to traditional geomorphology.  A bivariate map of 16 classes to visualize the relationships between morphological variables and a combination of mean elevation and topographic relief classifies mountains. The classification shows a transition from low rugged and low mountains, to moderate rugged and moderate height mountains, to high rugged and high mountains, to very high rugged and very high mountains. Within the framework of the classification, according to four different ruggedness ratios in Türkiye, low rugged mountains occupy 37%, moderate rugged mountains 33%, high rugged mountains 20% and very high rugged mountains 9%.

How to cite: Dal, N. and Görüm, T.:  Bivariate mountain definition: a case study for the turkish mountain system , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20335, https://doi.org/10.5194/egusphere-egu24-20335, 2024.

EGU24-20923 | Orals | GM3.2

Do Mature, Fluvial Landscapes Obey Hamilton's Principle? 

Scott D. Peckham

Students of physics typically take a theory course on classical mechanics in which they learn about Hamilton's Principle and how it can be used to derive many well-known physical laws that describe the motion of objects from particles, to light rays, to celestial bodies, including Newton's laws and Snell's Law from geometrical optics.  This powerful principle has also been shown to apply to fields (i.e., continuous systems) such as the electromagnetic and gravitational fields, and it is a foundational concept in quantum physics.  Hamilton's principle states that the dynamics of a physical system will optimize a functional (in our case, an integral over a spatial domain) of the system's Lagrangian, which is typically the difference between its kinetic and potential energies.  Many previous authors have postulated that fluvial landscapes may evolve in such a way that local and/or global kinetic energy dissipation or stream power is minimized, and this is the basis of the optimal channel network (OCN) simulation models that have been widely studied.  However, Hamilton's Principle suggests that these formulations are lacking an important piece, namely the global introduction of potential energy into the fluvial system by rainfall.  The author will show that by introducing this missing piece, Hamilton's Principle and the Euler-Lagrange theorem lead to a partial differential equation (PDE) for idealized, steady-state landforms.  This same PDE can also be derived from conservation of mass and an empirical slope-discharge formula.  These connections therefore point to a new theoretical framework for understanding the interplay between function and form in mature, fluvial landforms;  that is, an explanation for why these landforms take the forms we observe.  The author will also present ideas and algorithms for analyzing digital elevation models (DEMs), in an effort to test for agreement with Hamilton's principle.

How to cite: Peckham, S. D.: Do Mature, Fluvial Landscapes Obey Hamilton's Principle?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20923, https://doi.org/10.5194/egusphere-egu24-20923, 2024.

EGU24-22282 | ECS | Orals | GM3.2

A data-driven approach to understanding esker morphogenesis 

Meaghan Dinney and Tracy Brennand

Eskers are ubiquitous features on previously glaciated landscapes, recording the configuration and dynamics of the channelized meltwater system. Studies of esker composition and form have resulted in a variety of genetic interpretations surrounding the ice, water, and sediment characteristics under which they may develop. However, issues of apparent equifinality currently limit the usefulness of eskers for reconstructing broad-scale glacial hydrology. Although some authors have attempted to asses esker morphogenesis, previous studies are limited by their small sample size and/or use of qualitative morphometric indices.

This project aims to explore whether eskers have a distinct morphogenetic signature using data science techniques. Published research has been mined for empirical studies of esker composition and structure. These data were compiled into a database summarizing the genetic interpretations commonly invoked for eskers (e.g., depositional environment, meltwater flow regime) as well as the supporting evidence for such inferences (e.g., sedimentary logs). Semi-automated methods will be tested to map eskers from high resolution (1-2 metres) LiDAR digital terrain models and to extract their morphometry. A range of planform- and profile-scale morphometric indices will be employed and new indices that can more precisely quantify esker morphometry will be developed.

The resulting highly-dimensional dataset can be analyzed using machine learning techniques in order to assess the relationships between sedimentologic, morphometric, and genetic variables. Preliminary results from database development and analysis will be presented and methodological concerns will be discussed.

How to cite: Dinney, M. and Brennand, T.: A data-driven approach to understanding esker morphogenesis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22282, https://doi.org/10.5194/egusphere-egu24-22282, 2024.

EGU24-509 | ECS | Orals | NH10.5

Global Ionospheric Responses in Both Hemispheres during the 2015 St. Patrick's Day Storm 

Bhupendra Malvi and Pramod Purohit

On St. Patrick's Day, March 17, 2015, the first historical intense geomagnetic storm (Dst < −200 nT) of the 24th solar cycle occurred. This storm caused complex effects around the globe. Geomagnetic storms are a concern for society, especially the strongest storms and how they affect satellite communications, navigations and power grids. Using Global Positioning System (GPS) data to compute the Total Electron Content (TEC) of the Earth's ionosphere is one of the most common methods used to investigate perturbations in the ionosphere. GPS TEC variations may reveal ionospheric anomalies, which might endanger the continuity and availability of GPS performance metrics. Thus, the ionospheric consequences of geomagnetic storms have been researched intensively for decades but are still not fully understood. This study investigates the ionospheric behaviour during an intense geomagnetic storm that occurred from 14 - 24 March 2015. In particular, we used geomagnetic indices and GPS TEC data from various IGS stations all over the world to give a comprehensive analysis of how the ionospheric total electron content changes in both the northern and southern hemispheres at different latitude and longitude stations.

How to cite: Malvi, B. and Purohit, P.: Global Ionospheric Responses in Both Hemispheres during the 2015 St. Patrick's Day Storm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-509, https://doi.org/10.5194/egusphere-egu24-509, 2024.

Disastrous earthquakes are a permanent threat to every second resident of our planet causing a massive loss of lives and property. Understanding the nature of earthquake precursory signatures and related hazard mitigation has immense potential for scientific advancement as well as for societal benefits. To study these multidisciplinary and complicated precursory signatures, several models have been proposed in favor of the Lithosphere- Atmosphere- Ionosphere- Coupling (LAIC) mechanism by earlier workers. The major objective of this study is to investigate the short-term perturbations in land surface temperature (LST), atmospheric air temperature (AT), atmospheric relative humidity (ARH), and in ionospheric vTEC prior to the destructive shallow sheeted Turkey-Syria earthquake (Mw 7.8, Depth 10 Km, Intensity IX) on 6th February 2023 and its major aftershocks (Mw 7.5, 6.8, 6, 6). Earthquakes of such large magnitude causes synchronization changes, not only in the atmospheric parameters but also in the ionospheric TEC. The GPS and GNSS (IGS) derived ionospheric TEC data are now being used extensively to investigate seismo-ionospheric perturbations over and near the epicentral regions of earthquakes over the last two decades. To identify the perturbation in the LST and atmospheric parameters (AT and RH), we have studied the spatio-temporal variation of MODIS (Terra) derived LST data and MERRA 2 (NASA) derived atmospheric temperature and relative humidity at 2 meter height. The Terra-MODIS derived LST differential time series reveals a prominent increase ~ 6-16 ⁰C from 18th to 26th Jan, 2023 around the epicentral region. Moreover, the hourly varying atmospheric parameters (AT, RH) have shown significant and synchronous deviations from 18th Jan to 26th Jan. The highest positive (+ve) deviation in the AT is found to be 10.33 ⁰C and the lowest negative (-ve) anomaly in the RH is found to be 45.67% on 19th Jan. The observed atmospheric anomalies are identified with respect to the constructed bounds using past 5 years hourly data (m ± 2σ). The temporal variation of ionospheric vTEC of the nearest grid point, derived from both GNSS (IGS) and GPS receivers shows a series of prominent –ve anomalies from 25th Jan to 1st Feb about 5-12 days prior to the main shock. After ruling out possible contributions due to the solar terrestrial environment with respect to F10.7 Scale and Ap index, it is found that the evolved TEC anomaly is seismogenic in origin. In order to visualize the TEC anomaly in spatio-temporal domain, we have plotted 2D latitude-longitude time (LLT) maps of different epochs during those anomalous days (Max anomaly~ -15 TECu on 28th Jan at UTC 11th and 12th hour). Considering the nearest plate boundary, spatial extent of TEC conjugates and TEC gradient we have determined the probable epicenter which showed very promising correlation in comparison to actual epicenter. This multi parametric spatio-temporal analysis of the pre-seismic signature will produce some beneficial insight to understand the LAIC mechanism in detail and somehow be able to save so many lives.

How to cite: Dutta, B. and Malik, J. N.: Potential Utilization of Multi-Parametric Earthquake Precursory Signatures in Support of LAIC Mechanism: A case study on Turkey- Syria Earthquake (6th Feb, 2023)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1054, https://doi.org/10.5194/egusphere-egu24-1054, 2024.

EGU24-2380 | ECS | Posters on site | NH10.5

Modeling Equatorial Plasma Bubbles with SAMI3/SD-WACCM-X: Large-Scale Wave Structure 

Min-Yang Chou, Jia Yue, Nicholas Pedatella, Sarah McDonald, and Jennifer Tate

Large-scale wave structure (LSWS) in the bottomside F layer is pivotal in developing equatorial plasma bubbles (EPBs), potentially serving as a precursor of EPBs. Gravity waves, hypothesized to contribute through the wind dynamo mechanism, face experimental challenges. This study, utilizing the coupled SAMI3 and SD-WACCM-X models, investigates the role of gravity wave wind dynamo effect and gravity in LSWS development. We found that the gravity waves originating from the lower atmosphere induce vertical E×B drift perturbations in the nighttime ionosphere. Notably, LSWS can manifest independently of gravity, emphasizing the dominance of the gravity wave wind dynamo mechanism. However, LSWS exhibits more pronounced vertical E×B drift perturbations, indicating an additional eastward Pedersen current driven by equatorial winds (i.e., downward wind) via the gradient drift instability. Gravity-driven Pedersen current, therefore, plays a role in amplifying the LSWS and EPB development. Simulations also show the emergence of pre-dawn turbulent bubble-like irregularities in the bottomside ionosphere even without gravity, attributed to concentric gravity waves over the magnetic equator. Our findings underscore the significant influence of gravity waves on the formation of LSWS and ionospheric irregularities.    

How to cite: Chou, M.-Y., Yue, J., Pedatella, N., McDonald, S., and Tate, J.: Modeling Equatorial Plasma Bubbles with SAMI3/SD-WACCM-X: Large-Scale Wave Structure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2380, https://doi.org/10.5194/egusphere-egu24-2380, 2024.

The Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere (MVP-LAI) instrumental array was established in Sichuan, China, in 2021. The MVP-LAI station has demonstrated its efficacy in investigating the causal mechanisms of LAI coupling among multiple geophysical parameters in the vertical direction above a specific area on the Earth's surface during natural hazards such as earthquakes, volcanic eruptions, and landslides. Another MVP-LAI station will be established in Yunnan, approximately 200 km away from the first one, this year. Additionally, a high-frequency Doppler sounder array, comprising two transmitters with distinct frequencies and eight receivers, will be installed in areas covering both MVP-LAI stations to monitor vertical changes in ionospheric layers at two specific altitudes. It is noteworthy that observations from seismometers, magnetometers, and ground-based GNSS receivers in this area can be utilized to capture waves and/or perturbations propagating along the horizontal layer at the Earth's surface, at altitudes of approximately 100 km and 350 km, respectively. The two frequencies employed by the high-frequency Doppler sounder array can aid in comprehending how waves and/or perturbations propagate along the horizontal layers at approximately 200 km and 250 km in altitude. When the two MVP-LAI stations, the high-frequency Doppler sounder array, and substations are integrated, vibrations and/or perturbations propagate both vertically and along the five horizontal layers, even in slant directions, can be detected. The collaboration between MVP-LAI stations and horizontal observations forms the Greater Omnidirectional Ascertain Technology (GOAT), which enhances the understanding of the proportional mechanism for the LAI coupling.

How to cite: Chen, C.-H., Sun, Y.-Y., Lin, K., and Zhang, X.: Greater Omnidirectional Ascertain Technology (GOAT) of the Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere (MVP-LAI) Array, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2698, https://doi.org/10.5194/egusphere-egu24-2698, 2024.

The sudden cutoff of solar radiation caused by the solar eclipse could cause significant changes in the thermosphere and ionosphere, considering the fact that the solar radiation plays a significant role in their dynamical processes. In this study, the thermospheric neutral wind recorded by the Michelson Interferometer for Global High-Resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer (ICON) spacecraft and metero radar were analyzed to examine the variations in thermospheric wind during and after the 21 June 2020 annular solar eclipse over the East China area. The neutral wind observations showed direct evidences that the solar eclipse disturbed the mesosphere and low thermosphere for more than 10 hours. The clear enhancement of the meridional wind during the moon obscuration and sharply decreased meridional wind after local sunset suggested that a large-scale oscillation was caused by the solar eclipse, which persisted from daytime to nighttime.

How to cite: Wang, J. and Sun, Y.-Y.: Thermospheric wind response to the annular solar eclipse on 21 June 2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2968, https://doi.org/10.5194/egusphere-egu24-2968, 2024.

A FORMOSAT-5 satellite was launched on 25 August 2017 CST into a 98.28° inclination sun-synchronous circular orbit at 720 km altitude along the 1030/2230 local time sectors.  Advanced Ionospheric Probe (AIP), a piggyback science payload developed by National Central University for the FORMOSAT-5 satellite, has measured in-situ ionospheric plasma concentrations at a 1,024 Hz sampling rate over a wide range of spatial scales for more than 6 years.  In this poster, global plasma density irregularities in the pre-midnight sector had been seasonally selected from FORMOSAT-5/AIP data during 2018 to 2023.  Yearly variations of these irregularity patterns with solar cycle could be clearly observed.

How to cite: Chao, C.-K.: Equatorial Plasma Density Irregularities Observed by Advanced Ionospheric Probe Onboard FORMOSAT-5 Satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2985, https://doi.org/10.5194/egusphere-egu24-2985, 2024.

EGU24-2998 | ECS | Orals | NH10.5

Simulation of the atmospheric Acoustic-gravity waves caused by a finite fault 

Ting Li and Yongxin Gao

Based on the stratified lithosphere-atmosphere model, we present a semi-analytic method for calculating acoustic-gravity waves (AGWs) excited by a finite fault in the lithosphere. A finite fault is decomposed into a series of small subfaults, each treated as a point source with distinct rupture times. The fault is assumed to slide uniformly at a constant velocity along a specific direction. Simulation results reveal that both sides of the fault generate two types of AGWs when the fault rupture initiates and ceases. One type is the head AGW, generated by the P and Rayleigh waves propagating along the surface. The other one is the epicenter AGW, produced by direct seismic waves. The propagation of the AGWs is directional and related to the fault mechanism. We investigated a vertical strike-slip fault and a thrust fault, finding that the velocity amplitudes of the AGWs caused by both types of faults along the rupture direction are larger than the opposite direction. The AGWs induced by the thrust fault are stronger than those caused by the strike-slip fault. Furthermore, variations in the rupture velocity result in differences in waveform.

How to cite: Li, T. and Gao, Y.: Simulation of the atmospheric Acoustic-gravity waves caused by a finite fault, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2998, https://doi.org/10.5194/egusphere-egu24-2998, 2024.

EGU24-3089 | ECS | Orals | NH10.5

Design, Testing, and Preliminary Data Analysis of the Seafloor Absolute Pressure Gauge 

Ching-Ren Lin, Ya-Ju Hsu, Feng-Sheng Lin, and Kun-Hui Chang

Taiwan is situated in the collision zone between the Philippine Sea Plate and the Eurasian Plate, where these two plates are converging at an average rate of 8.2 centimeters per year, leading to significant crustal deformation on the island. Utilizing data from GPS (Global Positioning System) measurements processed and analyzed using Bernese software, the average velocity field of crustal movements can be estimated, providing a more comprehensive understanding of crustal deformation. The combination of GPS and seafloor geodesy observations can aid in unraveling the seismic processes along plate boundaries. Due to the inability of GPS signals to penetrate seawater, acoustic methods are employed to make ocean bottom pressure (OBP) measurements, serving as a valuable and unique tool for monitoring integrated ocean currents and observing sea level changes.

OBP measurements have been applied for various geophysical purposes, including ocean physics and marine geodesy. Seafloor Absolute Pressure Gauges (SAPG) based on quartz oscillation principles have been employed to record phenomena such as tsunamis, ocean tides and non-tidal sea level variations, as well as seafloor vertical deformations. These instruments play a crucial role in marine physics research.

In recent years, the Academia Sinica has also conducted research in the surrounding waters of Taiwan using acoustic positioning methods for seafloor geodetic observations. In conjunction with seafloor geodetic observations, ocean bottom pressure (OBP) measurement is another method employed.

The seafloor absolute pressure gauge (SAPG) developed by the Academia Sinica is composed of a Paroscientific Inc. quartz vibrating pressure sensor, integrated with an OEM data logger from RBR-Global Co. (http://www.rbr-global.com/products/bpr) and components such as the BART Boards with Regular Tuning ROUND and Acoustic Transducer that made by EdgeTech Co. The assembly of SAPG has been completed, and it has been deployed in the waters off the eastern coast of Taiwan for long-term observations. This paper will introduce the instrument assembly of SAPG, pre-deployment testing, and preliminary analysis results of the marine data.

How to cite: Lin, C.-R., Hsu, Y.-J., Lin, F.-S., and Chang, K.-H.: Design, Testing, and Preliminary Data Analysis of the Seafloor Absolute Pressure Gauge, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3089, https://doi.org/10.5194/egusphere-egu24-3089, 2024.

In fair weather, the vertical atmospheric electric field is oriented downward (positive in the earth surface ordinate system) in the global atmospheric circuit. Some researchers revealed the unique phenomenon whereby once an upward vertical atmospheric electric field is observed in fair weather, an earthquake follows within 2-48 hours regardless of the earthquake magnitude. However, the mechanism has not been explained with a suitable physical model. In this paper, a physical model is presented considering four types of forces acting on charged particles in air. It is demonstrated that the heavier positive ions and lighter negative ions are rapidly separated. Finally, a reversed fair weather electrostatic field is formed by the above charge separation process. The simulation results have instructive significance for future observations and hazard predictions and it still needs further research.

How to cite: Chen, T. and Li, L.: Atmospheric charge separation mechanism due to gas release from the crust before an earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3308, https://doi.org/10.5194/egusphere-egu24-3308, 2024.

EGU24-3330 | Orals | NH10.5

Acoustic-gravity waves generated by a point earthquake source 

Yongxin Gao and Ting Li

It is reported that earthquakes can trigger coseismic ionospheric disturbances, leading to the so called Lithosphere-atmosphere-ionosphere (LAI) coupling phenomenon. The acoustic-grave wave (AGW) is an important mechanism to induce such a phenomenon. In this study, we present a semi-analytic method to calculate AGWs excited by an earthquake source in the stratified lithosphere-atmosphere model and conduct numerical simulations to investigate characteristics of the AGWs. The results show that mainly two kinds of AGWs can be generated by the earthquake source. One is the head AGWs wave generated by the Rayleigh wave propagating along the surface, which propagates upwards nearly vertically. Another one is the epicenter AGWs generated by the direct seismic waves from the source. Both the head and epicenter AGWs are sensitive to the earthquake focal mechanism and are influenced by the structures of the atmosphere and solid earth. We also apply our method to a real earthquake event and compare the synthetic signals with the observed data.

How to cite: Gao, Y. and Li, T.: Acoustic-gravity waves generated by a point earthquake source, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3330, https://doi.org/10.5194/egusphere-egu24-3330, 2024.

EGU24-3553 | Orals | NH10.5

Differences between ionospheric infrasound induced by a strong volcanic eruption and an earthquake. 

Jaroslav Chum, Petra Koucká, Tereza Šindelářová, and Jan Rusz

 Strong earthquakes and volcano eruptions generate atmospheric waves in the infrasound range that can reach ionospheric heights and cause electron density disturbances that can be monitor remotely, e.g., using electromagnetic waves. Using infrasound measurement in the ionosphere by continuous radio Doppler sounding in Europe, the differences between ionospheric disturbances induced by earthquakes and volcano eruption are discussed on the examples of the recent M=7.7 Turkey 6 February 2023 earthquake and Hunga eruption on 15 January 2022. It will be shown that the main difference is that co-seismic (induced by seismic waves) infrasound detected in the ionosphere propagated roughly vertically and is generated locally (below the observation in the ionosphere) by vertical movement of ground surface. On the other hand, the infrasound induced by volcano eruption propagated most probably from the source (volcano) and leaked to the ionosphere from the imperfect stratospheric and thermospheric wave guide. In addition, a distinct travelling ionospheric disturbance was observed.    

How to cite: Chum, J., Koucká, P., Šindelářová, T., and Rusz, J.: Differences between ionospheric infrasound induced by a strong volcanic eruption and an earthquake., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3553, https://doi.org/10.5194/egusphere-egu24-3553, 2024.

EGU24-3948 | ECS | Orals | NH10.5

Electromagnetic response to undersea earthquakes in marine layered model 

Qianli Cheng and Yongxin Gao

In this study, we adopt a horizontally layered model which consisting of air, seawater and undersea porous rock and develop an analytically-based method to calculate the seismic and EM fields generated by undersea earthquakes. We conduct numerical simulations to investigate the characteristics of the EM response in three case (the receivers located at the seafloor, in the seawater near the sea surface and in the air, respectively). The results show that two kinds of EM signals can be identified in the EM records at these receivers. The first is the early EM wave arriving before the seismic waves and the second is the coseismic EM fields with apparent speed of the seismic waves. The EM signals observed at the seafloor are mostly stronger than those observed in the seawater and air near the sea surface. We applied this method to simulating the EM response to the 2022 Mw 7.3 earthquake that took place in the sea near Fukushima, Japan. At the receiver with 80 km epicentral distance at the seafloor, the predicted coseismic electric and magnetic signals reach the amplitudes of 2 μV/m and 2 nT, respectively. The results suggest a possibility to monitor the EM disturbances associated with marine earthquakes and use them to serve the earthquake early warning or earthquake mitigation.

How to cite: Cheng, Q. and Gao, Y.: Electromagnetic response to undersea earthquakes in marine layered model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3948, https://doi.org/10.5194/egusphere-egu24-3948, 2024.

EGU24-4579 | Orals | NH10.5

Ionospheric space weather and seismo-ionospheric precursors observed by China seismo-electromagnetic satellite 

Jann-Yenq Liu, Fu-Yuan Chang, Yun-Cheng Wen, and Xuhui Shen

The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate seismo-ionospheric precursors (SIPs) and ionospheric space weather.  The CSES probes manifest longitudinal features of 4-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs.  CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric disturbances induced by an intense storm with the Dst index of -175 nT on 26 August 2018.  Spatial analyses of GIM TEC and CSES plasma quantities discriminate SIPs from global effects and locate the epicenter of possible forthcoming large earthquakes.  CSES ion velocities are useful to derive SIP- and storm-related electric fields in the ionosphere.

How to cite: Liu, J.-Y., Chang, F.-Y., Wen, Y.-C., and Shen, X.: Ionospheric space weather and seismo-ionospheric precursors observed by China seismo-electromagnetic satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4579, https://doi.org/10.5194/egusphere-egu24-4579, 2024.

EGU24-4806 | Posters on site | NH10.5

Rapid Estimation of 2022 Tonga Erupted Volume from the Remote Seismo-Acoustic Resonance 

Cheng-Horng Lin, Min-Hung Shih, and Ya-Chuan Lai

The powerful acoustic waves generated by the major eruption on January 15, 2022 on Hunga Tonga Hunga Ha’apai (HTHH) of Tonga were unambiguously recorded in Taiwan by several infrasonic stations and Formosa array, which consists of 146 broadband seismic stations with an average spacing of ~5 km in northern Taiwan. Based on the carefully analyses of the broadband frequency-wavenumber method (BBFK) and the Fast Fourier Transform (FFT), it was interesting to see that both data sets consistently showed a resonant frequency of ~0.0117 Hz persisted for more than 25 minutes after the first major eruption. Such a long-duration resonance of the remote seismo-acoustic waves provides a rapid estimation of the erupted magma volume of 0.215 ± 0.015 if the volcanic cavity produced by the erupting magma is considered as a classic Helmholtz resonator. Thus, we may obtain that the first major eruption alone of HTHH rated a 4 on the VEI scale. But the total erupted volume could reach up VEI 5 or even 6 if we consider all of the accumulated magma from the following eruptions.

How to cite: Lin, C.-H., Shih, M.-H., and Lai, Y.-C.: Rapid Estimation of 2022 Tonga Erupted Volume from the Remote Seismo-Acoustic Resonance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4806, https://doi.org/10.5194/egusphere-egu24-4806, 2024.

EGU24-4922 | Posters on site | NH10.5

Indicators of the Activity Associated with Concealed Feeding Volcanic Fluids in the Tatun Volcano Group, Northern Taiwan 

Hsin-Chieh Pu, Cheng-Horng Lin, Hsiao-Fen Lee, Ya-Chuan Lai, Min-Hung Shih, Guo-Teng Hong, and Po-Tsun Lee

We analyzed 3,330 earthquake focal mechanisms and the fumarolic gases in the Tatun Volcano Group (TVG) during 2018–2021. Between June/2020 and June/2021, we found a concealed inflation beneath a depth of 2 km. We indicate this inflating mechanism was associated with the feeding volcanic fluids, which induced the past inflating cases in the TVG before 2018. We deliberated about the feeding features regarding this and the past cases and purpose three indicators to monitor such concealed activities, including the inflating indicator associated with the behaviors of earthquake faulting, heating indicator determined by the systematically high HCl/CO2 ratios, and discharging indicator displayed by the lasting high St/CO2 ratios. Using these indicators, we concluded that it was not rare during the last one decade that the concealed activities whose volcanic fluids were discharged occasionally.

How to cite: Pu, H.-C., Lin, C.-H., Lee, H.-F., Lai, Y.-C., Shih, M.-H., Hong, G.-T., and Lee, P.-T.: Indicators of the Activity Associated with Concealed Feeding Volcanic Fluids in the Tatun Volcano Group, Northern Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4922, https://doi.org/10.5194/egusphere-egu24-4922, 2024.

A solar storm can trigger severe geomagnetic and ionospheric disturbances, and activities originating from the Earth’s surface can do so as well. This presentation will introduce the sudden changes in the ionospheric plasma structure and electrodynamics after large lithospheric disturbances, such as earthquakes/tsunamis and volcanic eruptions. The main focus will be on the two significant events of the magnitude 9.0 Tohoku earthquake/tsunami (38.3°N 142.4°E) in the northeastern sea area of Japan on 11 March 2011, and the undersea volcanic eruption in Tonga (20.6°S 175.4°W), Central Pacific, on 15 January 2022. This presentation will also discuss the main characteristics of disturbances in ionospheric structures and electrodynamics. Investigating the two events enhances our comprehension of the sensitivity of the ionosphere response to lithospheric activities.

How to cite: Sun, Y.-Y.: Electrodynamic changes in the ionosphere due to large lithospheric disturbances, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4979, https://doi.org/10.5194/egusphere-egu24-4979, 2024.

Pre-earthquake anomalous phenomena in different geospheres have been widely reported.  Scientists found that the anomalies appear days to months prior to earthquakes from distinct geophysical parameters.  It is urgent and challengeable to investigate impending-earthquake anomalous signals for earthquake prediction.  The MVP-LAI (Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere) system was established at Leshan, Sichuan, China in 2021.  The system monitors the changes of over 20 various geophysical parameters from subsurface to ionosphere.  It aims to gain insights into the mechanisms of the lithosphere-atmosphere-lithosphere coupling (LAIC) during natural hazards.  On 5 September 2022, a M6.8 earthquake occurred at Luding, which is approximately 175 km from the MVP-LAI system.  The results show that the seven parameters from the MVP-LAI system simultaneously exhibited abnormal signal approximately 3 hours before the Luding earthquake. The parameters include ground tilts, air pressure, radon concentration, atmospheric vertical electric field, geomagnetic field, wind field, and total electron content. The enhancement in radon concentration suggests that the chemical channel could be a promising mechanism for the coupling of geospheres. On the other hand, air pressure, the geomagnetic field, and total electron content exhibit similar anomalous spectral characteristics. These anomalies may be attributed to atmospheric resonance before the earthquake. Furthermore, the reduction of the horizontal wind speed, and the increase of upward vertical wind support the resonance channel. The results demonstrate that the LAIC before earthquakes could be dominated by multiple potential mechanisms. The multi-parameter anomalies identified in this study guarantee approximately 3 hours of warning for people to prepare for the seismic event and mitigate hazards.

How to cite: Mao, Z. and Chen, C.-H.: Multi-parameter anomalies of the lithosphere, atmosphere, and ionosphere approximately three hours prior to the M6.8 Luding earthquake in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7128, https://doi.org/10.5194/egusphere-egu24-7128, 2024.

The ionosphere owns a complex electric current system mainly driven by the ionospheric electric field and thermospheric wind. Changes in current can generate geomagnetic signals that can be observed both on the ground and in space. In this study, we analyzed the ionospheric current in the Asia-Oceania region by utilizing geomagnetic data collected from magnetometers of ground-based observatories and SWARM satellites at ~450 km altitude. The results present the geomagnetic variations at the two distinct altitudes, encompassing longitudinal, latitudinal, and seasonal variations. Furthermore, the Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) was employed to simulate the associated geomagnetic signals. This study is the first to combine dense geomagnetic data from multiple altitudes and simulations to understand the ionospheric current in the Asia-Oceania region. The differences between the observational geomagnetic signals at different altitudes, along with the simulations, reveal a unique current structure that has not been previously discovered. The findings provide a new understanding of the intricate evolution of the current systems, which contributes to our knowledge of the electric dynamics within Earth's ionosphere.

How to cite: Zhang, P. and Sun, Y.-Y.: A unique structure of the ionospheric current over the Asian-Oceania region determined by the combination of the ground-based and space-borne magnetometers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8677, https://doi.org/10.5194/egusphere-egu24-8677, 2024.

The Qinling Orogenic Belt (QOB) is one of the most important orogens in Eastern Asia formed by the collision between the North China Block (NCB) and the South China Block (SCB). The evolution history of the QOB is essential to the assembly processes of the major blocks in China and the evolution history of the Proto-Tethys Ocean (Shangdan Ocean). Paleomagnetism can quantitatively restore the paleo-position of blocks, which is key to studying the related tectonic evolution. Hindered by the complex tectonic process, few paleomagnetic results have been reported from the QOB. Here we reported a primary paleomagnetic study from the northern QOB by conducting both rock magnetic and paleomagnetic experiments on the early Devonian Lajimiao pluton (~413Ma) in the North Qinling belt (NQB), to constrain its paleo-position and the evolution of the QOB during the early Paleozoic period.

253 cores from 28 sites were drilled by portable gasoline drills, and oriented by a magnetic compass and also a sun compass if possible. Rock magnetic experiments indicate that the main magnetic mineral in most of the samples is mainly magnetite in a pseudo-single domain or multi-domain state. Both thermal demagnetization and alternating-field demagnetization were applied to obtain the characteristic remanent magnetization. The Fisher-mean direction of the low-temperature/coercivity component is roughly consistent with the present geomagnetic field (PGF), suggesting that it is probably a viscous remanent magnetization caused by the PGF. The high-temperature/coercivity component yielded a Fisher-mean direction Ds/ Is = 355.8°/19.1° in stratigraphic coordinates, corresponding to a paleomagnetic pole of 65.8°N/299.9°E (A95=2.4°). It is the first Devonian paleomagnetic pole among the scarce paleomagnetic results from the QOB. This pole indicates that the NQB may have been located at a low latitude at the early Devonian, probably in proximity to both the North China and South China blocks. However, the difference between the coeval paleomagnetic poles from the three blocks (NQB, NCB, SCB) may hint the assembly process of the several major blocks is not simple and direct. Anyway, the newly obtained paleomagnetic pole from the NQB would be able to refine our understanding of the tectonic evolution of the QOB and the Proto-Tethys Ocean.

How to cite: Xu, H., Liang, Y., Lai, Y., and Li, G.: Primary Devonian paleomagnetic results from the Qinling orogenic belt and its implication for the evolution of the Proto-Tethys Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9414, https://doi.org/10.5194/egusphere-egu24-9414, 2024.

EGU24-11811 | ECS | Orals | NH10.5

Comparative analysis of recent seismic and volcanic events in the Tonga-Kermadec zone: Insights into Lithosphere-Atmosphere-Ionosphere Coupling 

Serena D'Arcangelo, Mauro Regi, Angelo De Santis, Loredana Perrone, Gianfranco Cianchini, Maurizio Soldani, Alessandro Piscini, Cristiano Fidani, Dario Sabbagh, Stefania Lepidi, and Domenico Di Mauro

The Tonga-Kermadec zone stands out as one of the most active areas in the world for continuous subduction processes characterizing the area. In the recent few years, it has been affected by two important geophysical events: first a strong earthquake of M7.2 on June 15, 2019, with the epicentre in Kermadec Islands (New Zealand), and then an exceptional eruption of Hunga Tonga-Hunga Ha’apai volcano on January 15, 2022. We focused our attention on the phenomena appearing before, during and soon after each event, employing a multi-parametric and multi-layer approach in order to analyse the geodynamics of the entire area and the involved lithosphere-atmosphere-ionosphere coupling (LAIC). In details, for the lithosphere we conducted a seismic analysis of the earthquake sequence culminating with the mainshock on June 15, 2019, and of those preceding the big eruption, within a circular area with Dobrovolsky strain radius corresponding to that of an equivalent seismic event of magnitude equal to the energy released during the eruption. Moving to the atmosphere, we considered some parameters possibly influenced by seismic and volcanic events, using the CAPRI algorithm to the ECMWF datasets to detect anomalies in their values. Finally, by observing satellite data, we analysed the magnetic field and electron burst precipitations, potentially correlated to the events. All these observations, along with their similarities and differences, provide a better insight of the complex tectonic context.

How to cite: D'Arcangelo, S., Regi, M., De Santis, A., Perrone, L., Cianchini, G., Soldani, M., Piscini, A., Fidani, C., Sabbagh, D., Lepidi, S., and Di Mauro, D.: Comparative analysis of recent seismic and volcanic events in the Tonga-Kermadec zone: Insights into Lithosphere-Atmosphere-Ionosphere Coupling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11811, https://doi.org/10.5194/egusphere-egu24-11811, 2024.

EGU24-12565 | Posters on site | NH10.5

TROPOMAG - Influence of geomagnetic storms on the TROPOsphere dynamics: Can the Earth’s MAGnetic field be considered a proxy of climate changes? Some results 

Lucia Santarelli, Valentina Bruno, Igino Coco, Sofia De Gregorio, Paola De Michelis, Fabio Giannattasio, Paolo Madonia, Michael Pezzopane, Marco Pietrella, Massimo Rossi, and Roberta Tozzi

The TROPOMAG project investigates the possible effects of changes of the Earth’s magnetic field on the atmosphere and weather conditions with the aim to better quantify the natural sources of the atmospheric variability. This need raises to assess the observed climate trends more correctly, with a consequent better understanding of manmade effects on climate. Specifically, this work explores possible connections between atmospheric pressure anomalies and the occurrence of geomagnetic storms. To accomplish this task pressure data, recorded over some Italian volcanic areas, are analysed according to different methods and considering geomagnetic indexes. This work describes and discusses corresponding preliminary results.

How to cite: Santarelli, L., Bruno, V., Coco, I., De Gregorio, S., De Michelis, P., Giannattasio, F., Madonia, P., Pezzopane, M., Pietrella, M., Rossi, M., and Tozzi, R.: TROPOMAG - Influence of geomagnetic storms on the TROPOsphere dynamics: Can the Earth’s MAGnetic field be considered a proxy of climate changes? Some results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12565, https://doi.org/10.5194/egusphere-egu24-12565, 2024.

EGU24-12791 | Orals | NH10.5

The case of the missing ionosphere: Investigating the ionospheric hole following the 2022 Tonga volcanic eruption 

Claire Gasque, Brian Harding, Thomas Immel, Yen-Jung Wu, and Colin Triplett

Following the eruption of the Hunga Tonga-Hunga Ha'apai (hereafter called ‘Tonga’) volcano just before local sunset on 15 January 2022, satellite data reveals the formation of a large-scale plasma depletion surrounding the region. This depletion persisted for roughly 14 hours, until local sunrise resumed plasma production. By combining in-situ and remote satellite observations, we seek to characterize the depletion's magnitude, spatial scale, and temporal evolution in the hours following the eruption. We will compare this to observations of ionospheric holes following previous impulsive lower atmospheric events, such as the 2011 Tohoku earthquake. Finally, we will investigate the dominant mechanism for locally depleting the plasma following this event, considering field-aligned ion drag, cross B transport due to electric fields arising from dynamo or other effects, and changing recombination rates. We aim ultimately to better understand the coupling between the lower atmosphere and ionosphere/thermosphere system following impulsive events such as this eruption. 

How to cite: Gasque, C., Harding, B., Immel, T., Wu, Y.-J., and Triplett, C.: The case of the missing ionosphere: Investigating the ionospheric hole following the 2022 Tonga volcanic eruption, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12791, https://doi.org/10.5194/egusphere-egu24-12791, 2024.

EGU24-13179 | Orals | NH10.5

Experimental data and models for radio diagnostics of extreme impacts “from above” and “from below” on ionospheric space weather: VLF, LOFAR and GNSS 

Yuriy Rapoport, Volodymyr Grimalsky, Andrzej Krankowski, Leszek Błaszkiewicz, Paweł Flisek, Kacper Kotulak, Adam Fron, Volodymyr Reshetnyk, Asen Grytsai, Vasil Ivchenko, Alex Liashchuk, and Sergei Petrishchevskii

Radio diagnostics, including scattering of electromagnetic waves (EMW) by spatiotemporal disturbances of the ionospheric plasma in the ELF (Extremely Low Frequencies, Hz), VLF (Very Low Frequencies, kHz), HF (High Frequencies, MHz) and microwaves (GHz) ranges, is one of the most effective methods for detecting and studying extreme modifications of ionospheric “space weather”. Such modifications are caused, in particular, by influences “from above” (from the Solar wind and magnetospheric storms) and “from below” (from tropical cyclones, earthquakes and volcanoes) and other Natural Hazards. Such ionospheric modifications are manifested, in particular, in the excitation of TIDs (Traveling Ionospheric Disturbances) and scintillations on various scales of the HF waves detected by LOFAR (Low Frequency Array) Radio Telescope.

In combination with other ionosphere sounding techniques (as GNSS) LOFAR can give a complementary insight to the ionospheric structures. We present LOFAR scintillation observations compared with GNSS-observed ionospheric irregularities in order to assess the ionospheric plasma structures. Classified ionospheric scintillation data will be presented. These include quasi-periodic, quasi-pulse, flare-like and other disturbances detected on the LOFAR radio telescopic systems in Poland, Great Britain, Germany and other countries. Spectral processing of LOFAR data is currently being carried out to identify various types of ionospheric disturbances, including TIDs, that characterize ionospheric space weather. We are currently developing TID modelling methods aimed at comparison with experimental data. Theoretical and experimental data on ionospheric disturbances associated with the eruption of the Hunga-Tonga-Hunga-Ha'apai volcano in January 2022 are presented and the results of their comparison are discussed. Based on the data-driven approach, effective current sources associated with lightning discharges caused by the eruption of the Hunga-Tonga-Hunga-Ha'apai volcano are identified in the ULF (Ultra-Low Frequency), ELF and VLF ranges. In particular, theoretical results are given on: (i) the excitation of the first and second modes of the Schumann resonator; (ii) the fundamental possibility of simultaneous excitation of coupled global Schumann and local Alfvén resonators. The results of applying the model for the scattering of HF electromagnetic waves (EMWs) on ionospheric disturbances such as increased and decreased plasma densities will be presented. The effects of birefringence, the dependence of EMW frequency on time in moving plasma, diffraction and dispersion of EMWs will be included, based on the advanced method of Complex Geometrical Optics.

An information is provided on the Ukrainian Ground-Based Space Weather Monitoring Network. This network includes GNSS stations, VLF receivers, Magnetotelluric stations, Ionosonde and magnetometer INTERMAGNET. Examples of corresponding measurements are presented.

Yu.R. and L.B. are grateful, for partial funding this research, by National Science Centre, Poland, grant No 2023/49/B/ST10/03465, “Modern Radio-Diagnostics of the Ionosphere using LOFAR and GNSS Data”

How to cite: Rapoport, Y., Grimalsky, V., Krankowski, A., Błaszkiewicz, L., Flisek, P., Kotulak, K., Fron, A., Reshetnyk, V., Grytsai, A., Ivchenko, V., Liashchuk, A., and Petrishchevskii, S.: Experimental data and models for radio diagnostics of extreme impacts “from above” and “from below” on ionospheric space weather: VLF, LOFAR and GNSS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13179, https://doi.org/10.5194/egusphere-egu24-13179, 2024.

The M7.8 and M7.5 earthquakes that occurred on 6 February 2023 in Turkey caused co-seismic ionospheric disturbances, and ionospheric total electron content (TEC) disturbances can be detected by Beidou geostationary satellites. The 17 GNSS continuous observation stations from IGS Net around the epicenters receive electromagnetic wave signals emitted by two Beidou geostationary satellites located above the equator at a frequency of 1 Hz. That allows us to obtain the TEC time series at fixed ionospheric piercing points (IPPs). Disturbances triggered by the M7.5 earthquake propagate farther and have a larger amplitude in general traveling at least 1600 km northwest and 800 km south and reaching the furthest area of the study with the maximum amplitude of about 2.5 TECU. For Mw 7.8 earthquake, the disturbances can be observed about 800 km northwest of the epicenter while no significant disturbances detected further away and the maximum amplitude of the disturbances is about 0.25 TECU. The TEC disturbances propagation speeds corresponding to the M7.5 and M7.8 earthquakes are 2.77 km/s and 2.60 km/s as the results of least squares fitting performed on epicentral distances and travelling times of the disturbances with the greatest amplitude. The speeds are closer to Rayleigh waves velocity of about 3 km/s at the surface rather than acoustic waves velocity of about 1 km/s in the ionosphere. The velocity of propagation for the co-seismic ionospheric disturbances, as determined by utilizing the Beidou geostationary satellites during two earthquakes, is consistent with that of the Rayleigh waves determined from the seismometers. Meanwhile, the velocity exhibits directional disparities for M7.5 earthquake.

How to cite: Rao, H. and Chen, C.-H.: Co-seismic ionospheric total electron content disturbances of Turkey earthquake doublet in 2023 detected by Beidou geostationary satellites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14108, https://doi.org/10.5194/egusphere-egu24-14108, 2024.

EGU24-14234 | Posters virtual | NH10.5

Simulation and Analysis of Disastrous earthquakes in the plains of SW Taiwan 

Strong Wen, Yulien Yeh, and Kuan-Ting Tu

There are many types of natural disasters in the world, among which earthquakes are sudden and highly uncertain, which may cause direct or indirect disasters, resulting in casualties, property losses, and infrastructure damage. Local seismic hazard analysis has been studied for a long time. This study uses historical earthquake data and virtual earthquake sources to simulate the propagation of seismic waves in urban areas in SW Taiwan. However, due to the limited number of existing free-field seismic stations and insufficient installation density, the accuracy of earthquake damage assessment is directly affected. Past research has pointed out that the use of scenario earthquake simulation can effectively simulate ground motions in local areas. Therefore, the goal of this study is to use numerical methods to construct a 3D seismic wave simulation, using numerical data and virtual seismic observation stations to simulate regional scales. However, due to limitations in computing resources and underground structure information, seismic waves calculated by 3D seismic wave propagation simulations can only cover relatively low-frequency (<1 Hz). However, for structural analysis in urban areas, in addition to inputting this relatively low-frequency signals, it is also necessary to utilize seismic waves covering high frequencies (>1 Hz) to calculate the vibration process and seismic resistance of the structure. Therefore, the goal of this study is to calculate low-frequency and high-frequency seismic waves separately, and to obtain broadband seismic waves containing low-frequency and high-frequency information through a hybrid method. The findings could be applied to future earthquake risk and building damage assessments.

How to cite: Wen, S., Yeh, Y., and Tu, K.-T.: Simulation and Analysis of Disastrous earthquakes in the plains of SW Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14234, https://doi.org/10.5194/egusphere-egu24-14234, 2024.

The magnetic storm that occurred in May 1921 ranks among the most extreme events ever observed by magnetic observatories. Some parts of this storm were also recorded in declination and vertical intensity by the variation station at the Stará Ďala observatory (present-day Hurbanovo in Slovakia). However, the magnetogram on photographic paper for this event not only contained data gaps, it also did not have a marked timeline, and the values of the divisions for the geomagnetic elements were not known. We identified timestamps using global variations observed by other observatories and estimated the values of the divisions based on data from before and after the studied event. Then, the magnetograms were digitized. To interpret the obtained data, we compared them with hourly averages from other observatories in different parts of the globe. Our results seem to confirm the expected assumption that, in the morning hours of 15 May 1921, the equatorward boundary of the auroral oval extended to the European mid-latitude observatories.

How to cite: Koči, E. and Valach, F.: The extreme geomagnetic storm on 13–15 May 1921: a study based on hourly means, including observations at Stará Ďala (Hurbanovo), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16216, https://doi.org/10.5194/egusphere-egu24-16216, 2024.

Typhoon is a key dynamic factor triggering landslides. In view of the fact that the previous susceptibility evaluation models rarely consider the interaction between typhoon and static factors, carry out research on the optimal dynamic and static factors combination of typhoon-induced landslides susceptibility. Using the interpretability of machine learning, the importance ranking of dynamic and static factors is carried out to identify key impact factors. On this basis, the importance of static factors under the influence of typhoon is compared, and the interaction between typhoon and static factors is analyzed. Finally, the optimal combination of dynamic and static factors is proposed by using k-fold cross-validation method and taking the average descent accuracy as the index. The results show that the importance of the key influencing factors of typhoon-induced landslide from high to low mainly includes: elevation, NDVI, road and other factors; the addition of typhoon and rainstorm factors significantly increased the importance of factors susceptible to typhoon, such as water system and vegetation, with an increase rate of 24.8-151.7 %. The optimal dynamic and static factors combination of typhoon rainstorm landslide includes all key static factors and four dynamic factors, among which the dynamic factors are: maximum sustained wind speed, rainfall, distance from typhoon center and near gale wind circle radius. The results of ROC curve verification show that the selection of the optimal factor combination can increase the accuracy of the evaluation model by 1.5%-3.5%, which can significantly improve the accuracy and rationality of the susceptibility mapping of typhoon-induced landslides.

Keywords: Impact factor, Typhoon, Landslides susceptibility, Interpretability of machine learning.

How to cite: Wang, F., Zhou, L., Liu, Y., and Chen, F.: Optimal factor combinations selection in typhoon-induced landslides susceptibility mapping using machine learning interpretability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16885, https://doi.org/10.5194/egusphere-egu24-16885, 2024.

EGU24-17238 | Posters on site | NH10.5

Anomalous Atmospheric Electric Field Just around the Time of Earthquakes: Case and statistical studies 

Yasuhide Hobara, Mako Watanabe, Mio Hongo, Hiroshi Kikuchi, Takuo Tsuda, and Masashi Hayakawa

In this paper, we report on the Atmospheric Electric Field (AEF) anomalies immediately before and after earthquakes (within 12 hours) in Japan. We demonstrate the results of a case study for several earthquakes that occurred close to our AEF observation network (within 100-200 km of the epicenter) under relatively fair local weather conditions. We found the common features for different earthquakes at different field sites e.g. 20~90 min period of clear anomalous signatures in wavelet spectrograms within a few hours around the main shock. Clear arrival time differences between AEF stations indicate propagating nature of observed AEF anomaly and enable us to calculate the propagation velocities and its occurrence timing. The observational results are compared with the dispersion relation of Internal Gravity Waves (IGW). Moreover, statistical results of the occurrence rate of the AEF anomalies support above mentioned results. Above-mentioned results may indicate the Lithosphere-Atmosphere Coupling, and we propose the physical mechanism of the observed electric field anomalies considering IGW originating from the epicenter region propagating over the field site and disturbing the local atmospheric electric field. 

How to cite: Hobara, Y., Watanabe, M., Hongo, M., Kikuchi, H., Tsuda, T., and Hayakawa, M.: Anomalous Atmospheric Electric Field Just around the Time of Earthquakes: Case and statistical studies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17238, https://doi.org/10.5194/egusphere-egu24-17238, 2024.

GI5 – Earth surface and subsurface methods of investigation

EGU24-61 | ECS | Orals | CR5.4

Multi-Offset Radio-Echo Sounding for Estimation of Englacial and Subglacial Thermal Conditions and Material Properties 

Daniel May, Dustin Schroeder, Paul Summers, Thomas Teisberg, Anna Broome, and Nicole Bienert

Radio-echo sounding (RES) is a widely used tool in the field of glaciology with which critical information about englacial and subglacial conditions can be derived. However, RES observations have historically been limited to zero-offset or small-offset surveys, typically employing one transmitting and one receiving antenna. The poor spatial and azimuthal coverage of the subsurface associated with these sparse geometries limits the ability to robustly constrain key englacial and subglacial properties including ice temperature, bed material composition, water content, ice fabric, and firn density. Furthermore, using radar only in zero- or small-offset configurations limits its potential to provide high resolution imaging of bed geometry. The maximum achievable offset in ground-based radar surveys is typically limited by the relatively high-loss coaxial cable which connects the radar transmitter and receiver. To overcome this limitation, two multi-offset ground-based radar systems, both built around an autonomous phase-sensitive radio-echo sounder (ApRES) as a transmitter, have been developed and deployed by the Radio Glaciology Group at Stanford. The first system forgoes cabled connection between a transmitting ApRES unit and a software-defined radio (SDR) based receiver, instead relying on a post-acquisition processing flow to ensure coherent summation of repeated measurements to achieve sufficient signal-to-noise ratios. The second system replaces the standard high-loss coaxial cable with low-loss fiber optic cable in order to extend the maximum achievable offset between transmitter and receiver. This requires outfitting the ApRES radar system with hardware to convert radio-frequency signals into optical signals that can be transmitted over fiber optic cable (RFoF). Both systems were deployed during the 2023-24 Antarctic field season as part of the Thwaites Interdisciplinary Margin Evolution project in order to collect multi-offset RES data on both floating and grounded ice. These surveys are aimed at detecting englacial temperature anomalies and the estimation of dielectric properties of englacial and subglacial materials through amplitude-versus-offset analysis of radar data. The dense multi-offset coverage in surveys described here was built up by frequent repositioning of only four SDR-based and one ApRES-based receiver; however, future surveys with these systems could have 10s or 100s of radar receivers simultaneously recording, allowing for survey geometries commonly employed in active source seismic imaging to be applied to radar imaging. 

How to cite: May, D., Schroeder, D., Summers, P., Teisberg, T., Broome, A., and Bienert, N.: Multi-Offset Radio-Echo Sounding for Estimation of Englacial and Subglacial Thermal Conditions and Material Properties, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-61, https://doi.org/10.5194/egusphere-egu24-61, 2024.

EGU24-266 | ECS | Orals | CR5.4

High resolution subglacial topography from airborne swath radar beneath the Northeast Greenland Ice Stream (NEGIS) 

Charlotte Carter, Steven Franke, Veit Helm, Daniela Jansen, Coen Hofstede, John Paden, and Olaf Eisen

Here we present an extensive swath radar dataset collected in the onset region of the Northeast Greenland Ice Stream, surrounding the East Greenland Ice Core Project site (EGRIP). We produce a new digital elevation model (DEM) of the subglacial topography at a resolution of 25 m, covering a study area of 40 km by 60 km. The data was collected using the AWI airborne ultra-wideband radar system, in profiles mainly perpendicular to the ice flow direction with a spacing of 2 km so that the swaths overlapped.

The high-resolution subglacial topography DEM shows subglacial landforms beneath an active ice stream, located approximately 600 km into the interior of the ice sheet. These landforms indicate spatially variable bed conditions which are partly reflected in the surface velocity field. Some features appear to be crag and tail formations up to 4 km in length, with steep stoss-side slopes and tapering lee-side tails which are oriented in the direction of ice flow. Megascale glacial lineations up to 7 km in length are evident, but appear restricted to the inner ice stream within the modern shear margins, where the ice flow velocity increases from approximately 11 m/a to 58 m/a. Meltwater channels curve around a high point in the topography, which are on the scale of tunnel valleys formed from subglacial meltwater incision. Seismic data located in a channel at the eastern shear margin indicates soft sedimentation inflow. In summary, differences in landform morphology can be seen within and outside of the ice stream shear margins, indicating that NEGIS ice flow may have been transitory in this region.

This survey provides a new insight into the active subglacial environment of a Greenlandic ice stream, matching in quality surveys from ice-free land surface or marine areas. Further analysis will contribute to the understanding of how glacially sculpted landscapes are formed, as well as the effects of small-scale topography on the dynamics and the surface of the overlying ice sheet, in particular ice streams. Moreover, the dataset emphasises the usage of swath radar mapping of bedforms and thus a more widespread application of this method in all radar surveys.

How to cite: Carter, C., Franke, S., Helm, V., Jansen, D., Hofstede, C., Paden, J., and Eisen, O.: High resolution subglacial topography from airborne swath radar beneath the Northeast Greenland Ice Stream (NEGIS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-266, https://doi.org/10.5194/egusphere-egu24-266, 2024.

EGU24-1096 | ECS | Orals | CR5.4

Automatic detection of cold-temperate transition surface in polythermal glaciers using GPR and machine learning 

Unai Letamendia, Iván Ramírez, Francisco Navarro, Beatriz Benjumea, and Emanuel Schiavi

Ground-penetrating radar (GPR) has been shown to be an effective tool to infer the hydrothermal structure of polythermal glaciers. Knowledge of this structure is fundamental to the study of their dynamics. The cold-temperate transition surface (CTS) is the englacial boundary between cold and temperate ice. It can be identified by GPR because of the contrast in permittivity between dry cold ice and water-rich temperate ice. However, the interpretation of the CTS using GPR has traditionally been a very time-consuming and manual process. Here we show a procedure based on machine learning for detecting CTS automatically. The data used for training a convolutional neural network were collected in both Svalbard, in the Arctic (radar with central frequency of 25 MHz), and the South Shetland Islands in the Antarctic Peninsula region (200 MHz central frequency). Various metrics revealed success rates in the classification in the order of 90%. The size of the training dataset is limited, so current work is focused on enlarging its size by using random variations of synthetic radargrams generated by forward modelling with gprMax.

How to cite: Letamendia, U., Ramírez, I., Navarro, F., Benjumea, B., and Schiavi, E.: Automatic detection of cold-temperate transition surface in polythermal glaciers using GPR and machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1096, https://doi.org/10.5194/egusphere-egu24-1096, 2024.

EGU24-1398 | ECS | Posters on site | CR5.4

Spatial and temporal changes in surface mass balance derived from airborne radio sounding for the plateau area in Dronning Maud Land 

Alexandra Zuhr, Steven Franke, Daniel Steinhage, Daniela Jansen, Olaf Eisen, and Reinhard Drews

Contrary to the rest of the Antarctic ice sheet, East Antarctica currently gains mass due to an increase in snow accumulation over the last decades. How or if this increase is linked to anthropogenic warming is not yet clear and requires better understanding of the surface mass balance history over the last centuries, and also the dependency of snow accumulation with the local surface slopes across different spatial scales.

Here, we present a novel airborne dataset using the multichannel ultra-wideband radar system from the Alfred Wegener Institute in Germany with a decadal vertical resolution for the plateau area in Dronning Maud Land. We assess the spatial and temporal variability of surface mass balance and snow accumulation for the past centuries for an area of ~200,000 km2. With this contribution, we aim to (1) show the potential to use ultra-wideband radar systems to reconstruct the recent surface mass balance and accumulation rates in low-accumulation regions, (2) present information on large spatial scales, and (3) discuss potential overlap of interests and/or data in this and/or other areas on the plateau of East Antarctica.

How to cite: Zuhr, A., Franke, S., Steinhage, D., Jansen, D., Eisen, O., and Drews, R.: Spatial and temporal changes in surface mass balance derived from airborne radio sounding for the plateau area in Dronning Maud Land, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1398, https://doi.org/10.5194/egusphere-egu24-1398, 2024.

EGU24-1721 | Posters on site | CR5.4

AIRETH 2.0 – a revamped helicopter-borne GPR for glaciological applications 

Daniel Farinotti, Raphael Moser, Barthelemy Anhorn, Christophe Ogier, Andreas Bauder, Benedikt Pohl, Benedikt Soja, and Hansruedi Maurer

The Airborne Ice Radar of ETH Zurich (AIRETH) is a dual-polarization, helicopter-borne GPR system that was developed for glaciological applications. At the core of AIRETH are two pairs of commercial, orthogonally oriented, bistatic dipole antennas operating at a center frequency of 25 HMz or higher. The system has extensively been operated in the past, e.g. for collecting close to 2,500 km of GPR data for estimating the ice thickness of glaciers across the Swiss Alps.

Here, we present a series of amendments that have recently performed to the AIRETH system in order to increase its versatility and operability. The corresponding work notably included:
1. a re-design of AIRETH’s air-frame, aiming at decreasing the system’s overall weight, as well as at increasing the system’s stability and ease of operation;
2. a newly developed positioning system, which is now based on the integration of information obtained from a set of four low-cost Global Navigation Satellite System (GNSS) sensors placed at the corners of the main air-frame in combination with an Inertial measurement unit (IMU); and
3. an experimental antenna shielding based on low-cost materials, aiming at minimizing the ringing noise caused by the proximity of the GPR system to the carrying helicopter.

The contribution will focus on the advances that were achieved compared to the previous AIRETH setup, and will point out the challenges faced during system re-design. The capabilities of the new system will, moreover, be illustrated by presenting some recent datasets acquired over Alpine glaciers.

How to cite: Farinotti, D., Moser, R., Anhorn, B., Ogier, C., Bauder, A., Pohl, B., Soja, B., and Maurer, H.: AIRETH 2.0 – a revamped helicopter-borne GPR for glaciological applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1721, https://doi.org/10.5194/egusphere-egu24-1721, 2024.

EGU24-5342 | ECS | Posters on site | CR5.4

Sediment-laden basal ice units near the onset of a fast-flowing glacier in East Antarctica 

Steven Franke, Michael Wolovick, Reinhard Drews, Daniela Jansen, Kenichi Matsuoka, and Paul Bons

Understanding the material properties and physical conditions of basal ice is crucial for a comprehensive understanding of Antarctic ice-sheet dynamics. Yet, direct data are sparse and difficult to acquire, necessitating geophysical data for analysis. We employed high-resolution ultra-wideband radar to map high-backscatter zones near the glacier bed within East Antarctica's Jutulstraumen drainage basin. In addition, we used radar forward modelling to constrain their material composition. Our results reveal along-flow oriented sediment-laden basal ice units connected to the basal substrate, extending to several hundred meters thick. Three-dimensional thermomechanical modelling suggests these units initially form via basal freeze-on of subglacial water originating upstream. We suggest that basal freeze-on and the entrainment and transport of subglacial material play a significant role in an accurate representation of the material, physical, and rheological properties of the Antarctic ice sheet's basal ice, ultimately enhancing the accuracy and reliability of ice-sheet modelling.

How to cite: Franke, S., Wolovick, M., Drews, R., Jansen, D., Matsuoka, K., and Bons, P.: Sediment-laden basal ice units near the onset of a fast-flowing glacier in East Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5342, https://doi.org/10.5194/egusphere-egu24-5342, 2024.

EGU24-6717 | ECS | Posters on site | CR5.4

Satellite-derived sea ice motion data: daily-maps (DM) and swath-to-swath (S2S) 

Tian Tian, Alexander Fraser, Petra Heil, Thomas Lavergne, Xuanji Wang, Yinghui Liu, and Jay Hoffman

Remotely sensed ice motion is a crucial component in sea, lake, or river ice research. Over the past few decades, the ice movement has been detected and retrieved predominantly through the application of the Maximum Cross-Correlation (MCC) technique by analyzing the overlapped consecutive satellite images.

Traditionally, ice motion products have been derived from daily averaged satellite imagery, commonly referred to as 'daily-map' (DM) ice motion. This DM ice motion product has gained widespread usage in sea ice studies due to its inherent timescale and extensive coverage.

Recently, a new approach known as the swath-to-swath (S2S) method has emerged, deriving ice motion from individual satellite swath pairs. The S2S ice motion product has proven valuable in sea ice kinematics research, revealing a robust relationship between ice kinematics and thickness, characterized by its diverse timescale. Consequently, these two types of satellite-derived ice motion products contribute distinct perspectives to ice kinematics research.

The latest generation of NOAA's Geostationary Operational Environmental Satellites (GOES), specifically the GOES-R Series, offers sea/lake/river ice observations at a relatively high resolution. A recent development involves the MCC approach generating a new DM ice motion product with a 2 km resolution using GOES-R reflectance imagery (0.5 km resolution). This ice motion dataset holds potential for final users engaged in analyzing small-scale sea/lake/river ice status and its changes.

How to cite: Tian, T., Fraser, A., Heil, P., Lavergne, T., Wang, X., Liu, Y., and Hoffman, J.: Satellite-derived sea ice motion data: daily-maps (DM) and swath-to-swath (S2S), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6717, https://doi.org/10.5194/egusphere-egu24-6717, 2024.

Satellite remote sensing is one of the few ways to comprehensively monitor changes in the Greenland Ice Sheet ‘s surface conditions through both time and space. From orbit, satellites can efficiently collect repeated measurements covering the entire ice sheet surface and elucidate the processes controlling how Greenland responds to a changing climate. Active radar and passive microwave measurements are especially valuable datasets, as cloud cover or illumination conditions are not limiting factors.

In this vein, recent research has shown how near-surface properties (i.e., density and roughness) across Greenland can be derived through the Radar Statistical Reconnaissance analysis of Ku-band ESA CryoSat-2 and Ka-band CNES/ISRO SARAL surface echo powers. While this approach yields densities at individual depths in the near-surface, a fuller result would include constraining a continuous density profile as a function of depth. At the same time, L-band ESA SMOS passive microwave brightness temperatures are sensitive to the entire snow-firn-ice column. However, the inversion of brightness temperatures for a property of interest in a specific layer (e.g., snow wetness, density, etc.) requires numerous assumptions regarding the subsurface conditions.

The EO4GRHO project seeks to merge these two approaches to investigate whether the inversion of SMOS brightness temperatures using a subsurface structure pre-conditioned with results derived from the analysis of radar altimetry surface echoes (i.e., density at known depth(s)) can provide a more complete picture of how Greenland Ice Sheet near-surface densities vary with depth, time, and space. Here, EO4GRHO leverages a decade (2013-2023) of contemporaneous CryoSat-2, SARAL, and SMOS measurements, makes use of modelled brightness temperatures from the Snow Microwave Radiative Transfer model software and, finally, hundreds of in-situ measurements. The ultimate aim of EO4GRHO is to operationally produce observation-based maps and time series for the near-surface density structure of the Greenland Ice Sheet that can be incorporated in future mass balance calculations.

How to cite: Scanlan, K. M. and Simonsen, S. B.: EO4GRHO: A multi-satellite synthesis constraining the near-surface density profile of the Greenland Ice Sheet through time and space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8824, https://doi.org/10.5194/egusphere-egu24-8824, 2024.

EGU24-10754 | Orals | CR5.4 | Highlight

International Mars Ice Mapper Mission: Detection, mapping and characterization of subsurface water ice and overburden on Mars with Synthetic Aperture Radar combined with VHF Sounding and High-Resolution Imaging 

Marilena Amoroso, Enrico Flamini, Eleonora Ammanito, Michele Viotti, Raffaele Mugnuolo, Timothy Haltigin, Etienne Boulais, Tomohiro Usui, David M. Hollibaugh Baker, Richard M. Davis, Michael S. Kelley, Bob Collom, Sébastien Lafrance, and Patrick Plourde

The primary goal of the International Mars Ice Mapper (I-MIM) mission concept is to identify and characterize accessible water-ice and its overburden in the upper 0-10 m of the Martian subsurface in preparation for future human-robotic exploration. The I-MIM concept mission has been developed by the Italian, Canadian, Japanese, and US space Agency Partners (ASI, CSA, JAXA, and NASA).

In 2021, the Agency Partners competitively selected a Measurement Definition Team (MDT) to define the core measurements for the mission’s primary payload, to suggest possible augmentations, and to develop a concept of operations. In August 2022, the MDT released a Final Report [1], concluding that the mission’s primary instrument, a Synthetic Aperture Radar (SAR) centred at 930 MHz, would satisfy all of the Reconnaissance Objectives (ROs) and would provide the opportunity to accomplish unique new science covering a broad range of international science priorities. In order to expand the capabilities of I-MIM to undertake high-priority science investigations, the MDT also recommended that the concept team consider the inclusion of complementary payloads identified as highest priority: a very high frequency (VHF) radar sounder, a high-resolution optical imager, and a sub-millimetre sounder for atmospheric profiling.

Based on the MDT inputs, the Agency Partners have updated the I-MIM mission architecture to consist of three spacecraft elements with complementary science payloads:

Element 1 – Ice-Mapping Orbiter: Provided by JAXA, with two radar instruments and an atmospheric sensor: a CSA-provided polarimetric L-band (930 MHz) SAR, an ASI-provided Very High Frequency (VHF) Shallow Radar Sounder (100-200 MHz), and a JAXA-provided sub-millimetre sounder. Moreover, an ASI-provided Large Deployable Reflector (LDR) would support the SAR and act as part of the ASI-provided telecommunications subsystem.

Element 2– Demonstration Lander: A JAXA-provided demonstration lander would piggyback on the main orbiter to provide ground-truthing capabilities with a potential complementary small instrument package.

Element 3 – Free-flying Smallsat: A NASA-provided, free-flying smallsat with a high-resolution imager would provide high-resolution imaging for context and continuity under a small low-cost mission profile and to meet the requirements for multiple scientific investigations and future mission site selection.

Mapping the unstudied near surface of Mars thanks to the synergic observations L-band SAR and the VHF Sounder, augmented by the High-resolution Imager, has the potential to fill a major data gap unmet by prior instruments sent to Mars and provide a broad evaluation of the abundance of water ice reservoirs at medium latitudes.

In order to characterize variability in the ionosphere both the SAR and the sub-millimeter sounder further addresses key questions about the connections in Mars’s dynamic climate regions and seasonal interactions of shallow subsurface volatiles with the atmospheric structure, of critical importance to both science and human-robotic mission planning.

In the International Moon to Mars objectives context, I-MIM would provide core information about the role of water ice and other volatiles in prior and active changes globally on Mars, identifying landed locations in ice-rich areas that represent potential habitable environments, for future robotic and human missions.

References: [1] I-MIM MDT Final Report (2022) 239 pp., online: https://science.nasa.gov/researchers/ice-mapper-measurement-definition-team

How to cite: Amoroso, M., Flamini, E., Ammanito, E., Viotti, M., Mugnuolo, R., Haltigin, T., Boulais, E., Usui, T., Hollibaugh Baker, D. M., Davis, R. M., Kelley, M. S., Collom, B., Lafrance, S., and Plourde, P.: International Mars Ice Mapper Mission: Detection, mapping and characterization of subsurface water ice and overburden on Mars with Synthetic Aperture Radar combined with VHF Sounding and High-Resolution Imaging, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10754, https://doi.org/10.5194/egusphere-egu24-10754, 2024.

EGU24-11581 | ECS | Orals | CR5.4

Evidence of Ice Flow Switching from Carlson Inlet to Rutford Ice Stream Based on Polarimetric Radar 

Álvaro Arenas-Pingarrón, Alex M. Brisbourne, Carlos Martín, Hugh F.J. Corr, Carl Robinson, and Tom A. Jordan

The flow of polar ice is controlled by its viscosity that is spatially variable and depends, among other factors, on the orientations of the anisotropic crystals of ice, often referred as crystal orientation fabric. Ice crystalizes in planes represented by the c-axis, a direction perpendicular to the main plane of the crystals, and it is highly anisotropic: the viscosity along the c-axis is two orders of magnitude greater than across, and hence it can be a key factor for ice flow modelling. Interestingly, the ice crystals rotate to accommodate ice flow, similarly to how dominoes tend to align under strain, and ice c-axis orientation evolves to be perpendicular to the direction of the maximum strain rate. Thus, ice flow and crystal orientation fabric are related. However, critically for our work, c-axis evolution is not instantaneous and, particularly in currently slow deforming ice, crystal orientation fabric contains traces or past ice flow conditions. Here, we use data from the British Antarctic Survey (BAS) airborne radar PASIN2 for deep ice sounding in Rutford Ice Stream, collected during the 2019-2020 season, to derive crystal orientation fabric. Because electromagnetic waves propagate at different speeds depending on the wave polarisation being parallel or perpendicular to the c-axis, an optical phenomenon called birefringence, we compare signals from different antenna orientations in our array to derive englacial crystal orientation fabric. We then compare our radar-derived crystal orientation fabric with strain rate derived from satellite ice flow observations. To aid the interpretation, we use a numerical model that bounds the prediction of ice fabric from ice flow under different assumptions. We find that Carlson Inlet, now stagnant, show traces of past fast flow on its crystal orientation fabric. This agrees with previous studies that suggest flow-switching and water-piracy between neighbouring Carlson Inlet and Rutford Ice Stream (Vaughan et al., 2008). Our method provides a framework to investigate the timing and the causes of the flow-switching event. More in general, we demonstrate the use of existing and future airborne polarimetric data to investigate recent changes in the cryosphere.

How to cite: Arenas-Pingarrón, Á., M. Brisbourne, A., Martín, C., F.J. Corr, H., Robinson, C., and A. Jordan, T.: Evidence of Ice Flow Switching from Carlson Inlet to Rutford Ice Stream Based on Polarimetric Radar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11581, https://doi.org/10.5194/egusphere-egu24-11581, 2024.

EGU24-11645 | ECS | Posters on site | CR5.4

A Seamless Ice Sheet Digital Elevation Model using CryoSat 

Carolyn Michael, Livia Jakob, Noel Gourmelen, Sophie Dubber, Karla Boxall, Andrea Incatasciato, Martin Ewart, Jerome Bouffard, and Alessandro Di Bella

The Greenland and Antarctic ice sheets are contributing to a quarter of current sea level change and have the potential to raise sea level by several metres in the future. The surface elevation of ice sheets, and its temporal evolution, is one of the essential climate variables, it forms the basis observation for mass balance monitoring and the projection of sea level contribution under future climate scenarios. This work explores the creation of a seamless and gapless annual digital elevation model (DEM) derived from CryoSat radar altimetry measurements to aid in the ongoing study of their ever-changing topography.

 

CryoSat-2 waveforms can be processed using two distinct techniques; (1) the conventional Point-Of-Closest-Approach (POCA), sampling a single elevation beneath the satellite, and (2) Swath processing which produces a swath of elevation measurements across the satellite ground track beyond the POCA, increasing spatial and temporal resolution. CryoSat operates in its Synthetic Aperture Radar Interferometric (SARIn) mode over the margins of the ice sheets allowing both processing techniques, however, within the ice sheet interior, CryoSat switches to its Low Resolution Mode (LRM), allowing solely the POCA technique for data processing. To achieve a comprehensive DEM encompassing the entirety of the ice sheet, whilst optimising data coverage, it is imperative to integrate and reconcile the outputs obtained from these distinct processing methodologies. This investigation uses two data sets provided by ESA’s CryoSat thematic product range: the CryoSat-2 ThEMatic PrOducts (CryoTEMPO) land ice data set that applies the POCA processing technique and covers the entirety of the ice sheets and the CryoTEMPO-EOLIS (Elevation Over Land Ice from Swath) data set that provides a comprehensive point cloud data set specific to the ice sheet margins.

 

In this investigation, the EOLIS and CryoTEMPO land ice datasets are aggregated into a spatial grid, utilising a Gaussian Radial Basis Function kernel to consider both, the spatial and temporal distribution of data points. To integrate EOLIS measurements from the margins of the ice sheet with CryoTEMPO land ice measurements from its interior, adjustments for variations in penetration are necessary to facilitate a seamless transition and mitigate the impact of anomalies. The combined and adjusted dataset is then post-processed to remove outliers while missing data is interpolated to generate a continuous DEM. Various spatio-temporal interpolation methods - such as External Drift Kriging, radial basis function, and DINCAE (Data Interpolating Convolutional Auto-Encoder) - have been explored and compared for their effectiveness.

 

This poster will provide and summarise an overview of the gridding, merging, and interpolation methodologies. Additionally, an assessment of the performance of different interpolation methods and their accuracies will be presented with comparisons to existing DEMs.

How to cite: Michael, C., Jakob, L., Gourmelen, N., Dubber, S., Boxall, K., Incatasciato, A., Ewart, M., Bouffard, J., and Di Bella, A.: A Seamless Ice Sheet Digital Elevation Model using CryoSat, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11645, https://doi.org/10.5194/egusphere-egu24-11645, 2024.

EGU24-11801 | Posters on site | CR5.4

Radar tomography of asteroid deep interior. JuRa / HERA to DIDYMOS and Ra proposed to APOPHIS  

Alain Herique, Dirk Plettemeier, and Wlodek Kofman

Our knowledge of the internal structure of asteroids relies entirely on inferences from remote sensing observations of the surface and theoretical modeling. Is the body a monolithic piece of rock or a rubble-pile, and how high is the porosity? What is the typical size distribution of the constituent blocks? Are these blocks homogeneous or heterogeneous? Direct measurements of an asteroid’s deep interior structure are needed to better understand asteroid accretion and their dynamic evolution. The characterization of the asteroids’ internal structure is crucial for science, planetary defense and exploration. In orbit Radar sounding is the most mature instruments capable of achieving the objective of characterizing the internal structure and heterogeneity, for the benefit of science as well as for planetary defense or exploration.

This is the goal of JuRa, the Juventas radar, onboard the ESA HERA mission. JuRa is a monostatic radar, BPSK coded at 60MHz carrier frequency and 20MHz bandwidth, inherited from CONSERT/Rosetta. The instrument design is under integration on Juventas cubesat for the ESA HERA mission. HERA will be launched this autumn to deeply investigate the Didymos binary system and especially its moonlet Dimorphos, five years after the DART/NASA impact. The main objective of JuRA is to characterize the asteroid interior, to identify internal geological structure such as layers, voids and sub-aggregates, to bring out the aggregate structure and to characterize its constituent blocks in terms of size distribution from submetric to global scale. The second objective is to estimate the average permittivity and to monitor its spatial variation in order to retrieve information on its composition and porosity.

This radar is also proposed to probe Asteroid 99942 Apophis in 2029, a potentially dangerous asteroid which will then approach Earth as close as 32000 kilometers on the DROID JPL/CNES and the RAMSES ESA proposed missions. This radar, which is a modified version of JuRa, will be able to operate in both monostatic and bistatic modes between orbiting or landed CubeSats. The knowledge of Apophis’ internal structure is crucial to improve our ability to study its stability conditions and to model its response to the gravitational constraints induced by Earth close approach. The Multipass processing will allow us to build a 3D tomographic image of the interior at different scales from submeter to global.

In this talk will present the instrument, its status, performances and goals as well as the science objectives in the context of the different targets.

How to cite: Herique, A., Plettemeier, D., and Kofman, W.: Radar tomography of asteroid deep interior. JuRa / HERA to DIDYMOS and Ra proposed to APOPHIS , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11801, https://doi.org/10.5194/egusphere-egu24-11801, 2024.

EGU24-12324 | ECS | Posters on site | CR5.4

Exploring Canyons Beneath Devon Ice Cap for Sub-Glacial Drainage Using Radar and Thermodynamic Modeling 

Chris Pierce, Mark Skidmore, Lucas Beem, Don Blankenship, Ed Adams, and Christopher Gerekos

Sub-glacial canyon features up to 580m deep between broad, flat mesas were identified beneath Devon Ice Cap, Devon Island, Nunavut, Canada during a recent Radar Echo Sounding (RES) survey. The largest canyon connects a hypothesized area of distributed sub-glacial water near the ice cap's summit with the marine-terminating Sverdrup outlet glacier. This canyon represents a probable drainage route for the hypothesized sub-glacial water system. Radar bed reflectivity is consistently 30 dB lower along the canyon floor than on the mesas, contradicting the signature expected in the presence of sub-glacial water. We compare these data with radar backscattering simulations to demonstrate that the reflectivity pattern may be topographically induced. Our simulated results indicated a 10m wide canal-like water feature is unlikely along the canyon floor averaging ~300m wide, however, smaller features may be difficult to detect via RES.

We calculated basal temperature profiles along the canyon using a 2-D finite difference method, and found basal conditions at the canyon floor may be significantly warmer than at the mesas. Despite elevated temperatures, there is limited evidence that the basal environment along the canyon floor could support a connected drainage system between the Devon Ice Cap summit and Sverdrup Glacier.

The complex terrain beneath Devon Ice Cap demonstrates some limitations for RES. Future studies should carefully consider attenuation correction methods near steep or complex terrain, and seek validation of RES analyses with multiple methods, as we have demonstrated here.  

How to cite: Pierce, C., Skidmore, M., Beem, L., Blankenship, D., Adams, E., and Gerekos, C.: Exploring Canyons Beneath Devon Ice Cap for Sub-Glacial Drainage Using Radar and Thermodynamic Modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12324, https://doi.org/10.5194/egusphere-egu24-12324, 2024.

EGU24-12330 | Orals | CR5.4

Retracker-dependent radar freeboard correction methods for satellite radar altimetry-based sea ice thickness estimation 

Hoyeon Shi, Gorm Dybkjær, Suman Singha, Sang-Moo Lee, Rasmus Tonboe, and Fabrizio Baordo

Sea ice thickness is derived from its freeboard measured by satellite radar altimeters. However, the radar freeboard, which is initially estimated freeboard by interpreting the observed waveform, needs correction before sea ice thickness estimation so that it coincides with the height of the snow-ice interface from the sea surface. The so-called radar freeboard correction is thus an essential procedure for sea ice thickness estimation from satellite radar altimeter data, such as those from the CryoSat-2 mission. Today, most studies do the correction taking into account a slower wave propagation speed in the snow layer on sea ice under the assumption that the main scattering horizon is the snow-ice interface. However, while several recent studies have raised questions on that assumption, there is also a possibility that a retracker, which is an algorithm that estimates radar freeboard from waveform, has systematic bias. Accordingly, this study revisits the conventional way of doing the radar freeboard correction. First, we directly compare the CryoSat-2-derived radar freeboards from different retrackers with reference airborne freeboard measurements to introduce alternative correction methods for each retracker. Then, those correction methods are combined with a recently developed methodology where snow depth, sea ice thickness, freeboard, and ice draft are retrieved simultaneously. In order to compare the performance of different correction methods, including the conventional light speed correction, retrievals are done using the updated methodology, and those results are assessed using various reference datasets. Those are snow depth and freeboard from airborne observation, ice draft from mooring observation, and freeboard from satellite laser altimeter observation. In addition, the correction methods are combined with another independent retrieval method that estimates snow depth and sea ice thickness by combining satellite laser and radar altimeter measurements. Lastly, the consistency between the results from the two retrieval methods is examined for each radar freeboard correction method.

How to cite: Shi, H., Dybkjær, G., Singha, S., Lee, S.-M., Tonboe, R., and Baordo, F.: Retracker-dependent radar freeboard correction methods for satellite radar altimetry-based sea ice thickness estimation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12330, https://doi.org/10.5194/egusphere-egu24-12330, 2024.

EGU24-12995 | Posters on site | CR5.4 | Highlight

Comprehensive multi frequency airborne mapping of the southern flank of Dome A: results of the COLDEX airborne program. 

Duncan Young, John Paden, Megan Kerr, Shivangini Singh, Shravan Kaundinya, Shuai Yan, Alejandra Vega González, Jamin Greenbaum, Dillon Buhl, Gregory Ng, Kristian Chan, Bradley Schroeder, Gonzalo Echeverry, Thomas Richter, Scott Kempf, Fernando Rodriguez-Morales, Richard Hale, Donald Blankenship, and Edward Brook

The Center for Oldest Ice Exploration (COLDEX) is a US initiative funded to search for climate records over the last 5 million years, including locating sites for an accessible continuous ice core going back 1.5 million years.  As part of this effort, COLDEX has mapped the southern flank of Dome A, East Antarctica using an instrumented Basler, including dual frequency radar observations of the ice sheet and ice bed, as well as potential fields measurements (see presentation by Kerr in EGU session G4.3) across two field seasons from Amundsen-Scott South Pole Station.  The aerogeophysical system included both the UTIG VHF MARFA radar system operating at 52.5-67.5 MHz, as well as a new large high resolution UHF array from CReSIS operating at 670-750 MHz operating simultanously.  A goal of this project was to obtain airborne repeat interferometry for segments of the survey, as well as directly feed ice sheet models using englacial isochrons (see Singh presentation in EGU session CR5.6).  These goals lead to a survey explicitly designed around ice sheet flow lines.  

While prior work had sampled the region at lithospheric scales, the COLDEX survey had two components - the first was to map the region at crustal scales (line spacing of 15 km), and the second was to map subareas at ice sheet scales (line spacing of 3 km).  Immediate observations include an extensive basal unit and strong discontinuity in englacial stratigraphy that runs across the survey area and appears correlated with changes in bed interface properties.  The airborne campaign will be used to inform follow up ground campaigns to understand processes relevant for old ice preservation.

How to cite: Young, D., Paden, J., Kerr, M., Singh, S., Kaundinya, S., Yan, S., Vega González, A., Greenbaum, J., Buhl, D., Ng, G., Chan, K., Schroeder, B., Echeverry, G., Richter, T., Kempf, S., Rodriguez-Morales, F., Hale, R., Blankenship, D., and Brook, E.: Comprehensive multi frequency airborne mapping of the southern flank of Dome A: results of the COLDEX airborne program., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12995, https://doi.org/10.5194/egusphere-egu24-12995, 2024.

EGU24-13404 | ECS | Orals | CR5.4

Characterizing the altitude dependence of radar reflectometry for the (near-)surface of icy worlds 

Kristian Chan, Cyril Grima, Christopher Gerekos, and Donald Blankenship

Knowledge of (near-)surface properties and their spatial heterogeneity can reveal much about the processes that dominate the evolution of the top few-to-tens of meters of icy worlds. Radar reflectometry has been demonstrated to be a valuable technique for characterizing near-surface ice on Earth and Mars with mature plans for it to be applied to future observations of the Jovian icy moons, collected by the Europa Clipper and Juice missions. Both missions host nadir-pointing ice-penetrating radar instruments: the Radar for Europa Assessment and Sounding: Ocean to Near-surface (REASON) on Europa Clipper operating at center frequencies of 60 MHz and 9 MHz, with bandwidths of 10 MHz and 1 MHz, respectively, and the Radar for Icy Moons Exploration (RIME) on Juice at a single 9 MHz center frequency but bandwidths of 1 and 2.8 MHz.

Previous applications of reflectometry rested on the assumptions implicit in the Radar Statistical Reconnaissance (RSR) technique, which has been regularly used to characterize bulk near-surface properties (e.g., porosity) and surface roughness, each predominantly dependent on the coherent and incoherent components of the total surface return, respectively. However, these previous applications of RSR utilized observations collected at near constant altitude. Europa Clipper and Juice will both perform flybys of their targets of interest with altitude that rapidly changes across the observation window. Thus, an understanding of how altitude (convolved with changes in the surface geology) can affect the balance between observed coherent and incoherent backscattered energy is necessary to confidently apply RSR on Europa and Ganymede.

Here, we simulate the radar surface echo from synthetic Europa-like terrains, using a version of the multilayer Stratton-Chu coherent simulator that computes the scattering contributions from every frequency component within the bandwidth of the emitted chirp. We then apply RSR to deconvolve the total simulated surface power into its coherent and incoherent components. We assess the coherent content of the total power to changes in altitude, by comparing the coherent power derived from simulated surface echoes at the REASON/RIME shared center frequency (9 MHz) but different bandwidths (1 vs. 2.8 MHz). Coherent and incoherent geometric power falls off at different rates with altitude. Thus, the coherent content of the total return at a particular altitude over the target of interest could affect our ability to invert for near-surface properties. Note in particular that different terrain types (e.g., chaos terrain versus ridged plains on Europa) may be better observed at different altitudes from the perspective of reflectometry. In addition, our results provide valuable insight into targets and altitudes suitable for cross calibrating RIME and REASON [9/1 MHz] for comparative radar studies across the Jovian icy moons.

How to cite: Chan, K., Grima, C., Gerekos, C., and Blankenship, D.: Characterizing the altitude dependence of radar reflectometry for the (near-)surface of icy worlds, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13404, https://doi.org/10.5194/egusphere-egu24-13404, 2024.

EGU24-14072 | Posters on site | CR5.4

The Potential Role of Anomalous Geothermal Flux for Enhanced Basal Melting and Suppressed Ice Velocity at Haynes Glacier, West Antarctica 

Jason Bott, Don Blankenship, Shuai Yan, Lucas Beem, and Duncan Young

In NASA’s MEaSUREs Ice Velocity Data, a distinctive 8.5km diameter patch of slow-moving to stationary ice (0-15m/year) can be observed near the grounding line of Haynes Glacier, amidst much faster-flowing ice (300-1300 m/year). Additionally, a number of anomalously drawn-down englacial radar reflections are observed in multiple aerogeophysical surveys with the McCORDs (Multichannel Coherent Radar Depth Sounder) Instrument upstream of this ice velocity anomaly. 

The potential source of this velocity anomaly is hypothesized to be either anomalous geothermal flux or high frictional heat upstream, coupled to a thinning of the ice column as it nears the grounding line. These factors, taken together, imply a scenario where the warmer ice at the base of the ice column melts away while colder ice enters from above at the accumulation rate along the flowline. Upstream, with the ice column's relatively high thickness (~1000m), the basal ice experiences sufficient pressure to induce significant down draw of layers from substantial melting that is consistent with basal friction and/or a source of anomalous geothermal flux; the result is significant thermal advection of the much colder surface accumulation deep into the ice column. Downstream, where the ice thins, the  reduced pressure results in freezing of the anomalously cold ice to the bed, leading to the observed velocity anomaly.The testing of this hypothesis requires reconciling of the vertical velocity profile necessary to produce the down draw with either expected frictional melt or anomalous geothermal flux along the flowline (given the accumulation gradient). We present here this coupled thermal and kinematic modeling of Haynes Glacier from the site of the down draw to the sticky spot near the grounding line. With our models of temperature variations and ice flow characteristics within the Haynes Glacier system, we can further refine our understanding of the importance of heterogeneous geothermal flux for cryosphere evolution  - which may prove to be vitally important to fully understand fast-flowing and vulnerable ice streams in the Amundsen Embayment of West Antarctica. This, in turn, may have further implications for the study of heterogeneous heat flux and volcanic activity within the broader context of West Antarctica.

How to cite: Bott, J., Blankenship, D., Yan, S., Beem, L., and Young, D.: The Potential Role of Anomalous Geothermal Flux for Enhanced Basal Melting and Suppressed Ice Velocity at Haynes Glacier, West Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14072, https://doi.org/10.5194/egusphere-egu24-14072, 2024.

EGU24-14822 | Posters on site | CR5.4

Big Data Analysis of Antarctic Ice Structures and Subglacial Lakes: Utilizing Moving IQR for Radar Intensity Processing 

Yong-Gil Park, Chol-Young Lee, Joo-Han Lee, and Dong-Chan Joo

The structure of Antarctic ice preserves the sequence of ice deposition, offering insights into ancient environmental conditions. Organisms discovered beneath the ice sheets, spanning from hundreds to thousands of meters in thickness, hold information on survival in extreme environments. Antarctic ice investigations are conducted using radar systems mounted on helicopters or vehicles, generating vast datasets covering hundreds of kilometers. Analyzing this large-scale data is essential to reduce time and cost for detecting ice structures and subglacial lakes. In this study, we developed algorithms for ice structure analysis and subglacial lake detection using big data analysis techniques, specifically outlier detection methods applied to radar signal values. Utilizing radar signal values represented in an 800x83,344 matrix, we employed the Spark platform with specifications of 400 cores and 1.6TB of memory for data analysis. To facilitate data processing in Spark, the data was transformed into a 3x66,675,200 dataframe after uploading to HDFS. Outlier detection, using the Moving Interquartile Range (IQR), identified abrupt changes in signal values based on columns, adjusting the IQR's range and scale to optimize the results. Detected outlier values were normalized within a 0-255 range and visualized based on intensity. Results revealed that using the Moving IQR for radar imagery processing effectively detected localized changes as the range increased; however, detection rates decreased with larger scales. Analyzing radar exploration results in a big data environment is anticipated to significantly reduce time and costs compared to traditional methods, contributing to Antarctic exploration and climate change response efforts.

 

How to cite: Park, Y.-G., Lee, C.-Y., Lee, J.-H., and Joo, D.-C.: Big Data Analysis of Antarctic Ice Structures and Subglacial Lakes: Utilizing Moving IQR for Radar Intensity Processing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14822, https://doi.org/10.5194/egusphere-egu24-14822, 2024.

EGU24-16685 | ECS | Posters on site | CR5.4

Mapping Glacier Hydrology in 3D: Novel GPR Acquisition and Processing Techniques 

Johanna Klahold, Benjamin Schwarz, Alexander Bauer, Gabriela Clara Racz, Bastien Ruols, and James Irving

Ground-penetrating radar (GPR) has become a well-established tool in the field of glaciology thanks to its capacity for high-resolution imaging and the excellent propagation characteristics of radar waves in snow and ice. In this context, 3D surveying and processing techniques hold significant promise for examining the internal structure and dynamics of glaciers, yet 3D studies are rarely done due to time and cost constraints. In particular, the field of glacier hydrology could immensely benefit from the acquisition and dedicated processing of high-density 3D GPR data sets, as observations of hydrological conditions inside the glacier and at its base are of critical importance for model calibration and validation.

In this contribution, we attempt to exploit the full potential of high-resolution 3D GPR data to study glacier hydrology. A novel drone-based GPR acquisition system enables us to collect high-density 3D data with unprecedented spatial coverage. Our corresponding processing scheme considers two complementary components: the prominent reflected arrivals, and the faint (often neglected) diffracted wavefield. Reflection amplitudes at the ice-bedrock interface are used to delineate subglacial channels, whereas diffraction imaging methods borrowed from exploration seismology facilitate the localization of englacial conduits.

We present results from two case studies in the Swiss Alps: the Haut Glacier d’Arolla and the Glacier d’Otemma. Our workflow provides complementary maps of the subglacial drainage system and of well-developed englacial channels. For the Glacier d’Otemma, we combine these results with supplementary methods (photogrammetry, dye tracing, time lapse cameras, steam drilling, and hydrological modeling) to obtain a more comprehensive characterization of the drainage system.

How to cite: Klahold, J., Schwarz, B., Bauer, A., Racz, G. C., Ruols, B., and Irving, J.: Mapping Glacier Hydrology in 3D: Novel GPR Acquisition and Processing Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16685, https://doi.org/10.5194/egusphere-egu24-16685, 2024.

EGU24-17445 | ECS | Posters on site | CR5.4

ApRES observations of ice fabric in Greenland: From a climatic transition in the North to a potential historical ice stream remnant in the South 

Anja Rutishauser, Reinhard Drews, Reza M. Ershadi, Falk M. Oraschewski, Kirk M. Scanlan, Nanna B. Karlsson, Carlos Martin, Anne M. Solgaard, Camilla S. Andresen, and Andreas P. Ahlstrøm

The crystal orientation fabric (COF) of ice sheets, characterized as the net alignment of ice crystals, can contain a record of past ice sheet dynamics and potentially climatic conditions. In turn, the COF significantly influences ice viscosity, thus impacting present-day ice deformation and flow velocities. Due to its dielectric properties, anisotropic COF can be detected with polarimetric radar measurements, including Autonomous phase-sensitive Radio-Echo Sounders (ApRES).

Here, we present findings from polarimetric ApRES measurements conducted at Camp Century North-West Greenland, and two sites in Southwest Greenland: Dye-2 and KAN-U. At Camp Century, the ApRES measurements indicate some COF anisotropy throughout the ice column, with a distinct boundary at the depth of the Holocene-Wisconsin ice transition, previously identified in a nearby ice core. We investigate the origin of this boundary in the ApRES data, and whether such signatures can be used to identify glacial-interglacial transitions from polarimetric radar data.

At both sites in Southwest Greenland, the signal is strongly attenuated and falls below the noise level beyond 500 m depth, likely due to significant scattering within a heterogeneous firn column. However, Dye-2 exhibits strong COF anisotropy in the uppermost 100-500 m of the ice column, despite the region’s slow ice flow. Conversely, KAN-U displays no evidence of  COF anisotropy. We investigate causes of the peculiar localized anisotropy at Dye-2, hypothesizing it as a residual imprint of a historic fast flowing, far inland-reaching ice stream.

How to cite: Rutishauser, A., Drews, R., Ershadi, R. M., Oraschewski, F. M., Scanlan, K. M., Karlsson, N. B., Martin, C., Solgaard, A. M., Andresen, C. S., and Ahlstrøm, A. P.: ApRES observations of ice fabric in Greenland: From a climatic transition in the North to a potential historical ice stream remnant in the South, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17445, https://doi.org/10.5194/egusphere-egu24-17445, 2024.

EGU24-18028 | Posters on site | CR5.4

Folded ice in the upper North East Greenland Ice Stream reveal timing of the onset of streaming 

Daniela Jansen, Steven Franke, Catherine Bauer, Tobias Binder, Dorthe Dahl-Jensen, Jan Eichler, Olaf Eisen, Yuanbang Hu, Johanna Kerch, Maria Gema Llorens, Heinrich Miller, Niklas Neckel, John Paden, Tamara de Riese, Till Sachau, Nicolas Stoll, Ilka Weikusat, Frank Wilhelms, Yu Zhang, and Paul Dirk Bons

Only a few localised ice streams drain most ice from the Greenland Ice Sheet. Thus, understanding ice stream behaviour and their temporal variability is crucially important to predict future sea-level change. The interior trunk of the 700 km-long North-East Greenland Ice Stream (NEGIS) is remarkable for the lack of any clear bedrock channel to explain its presence. Here we use isochronous radar reflections from an airborne radar survey as passive tracers of ice deformation. We present the first-ever 3-dimensional analysis of folding and advection of stratigraphic horizons within an ice stream, which shows that the localised flow and shear margins in the upstream part were fully developed only ca. 2000 years ago. This indicates that this type of streaming in the interior of an ice sheet can be triggered on short time scales.

How to cite: Jansen, D., Franke, S., Bauer, C., Binder, T., Dahl-Jensen, D., Eichler, J., Eisen, O., Hu, Y., Kerch, J., Llorens, M. G., Miller, H., Neckel, N., Paden, J., de Riese, T., Sachau, T., Stoll, N., Weikusat, I., Wilhelms, F., Zhang, Y., and Bons, P. D.: Folded ice in the upper North East Greenland Ice Stream reveal timing of the onset of streaming, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18028, https://doi.org/10.5194/egusphere-egu24-18028, 2024.

EGU24-18077 | ECS | Orals | CR5.4

Can polarimetric wide-angle radar surveys teach us more about ice fabric anisotropy? 

Falk M. Oraschewski, M. Reza Ershadi, Clara Henry, and Reinhard Drews

The fabric anisotropy of ice and its flow dynamics are co-dependent. Parameters used in models that solve the evolution of ice fabric are currently unconstrained, for which comparisons with observations are needed. In observations and models, the ice fabric can be represented by a crystal orientation tensor, describing the spatial distribution of ice crystal orientations. Because ice crystals are not only mechanically, but also dielectrically anisotropic, the fabric anisotropy causes birefringence and anisotropic scattering and can be inferred by polarimetric radar surveys. In recent years, the advancement of polarimetric radar methods has resulted in a surge of available observational data. However, all existing methods are performed with a nadir-looking radar geometry. As a consequence, these approaches are only sensitive to horizontal fabric anisotropy, making the assumption necessary that one eigenvector of the crystal orientation tensor is aligned in vertical (nadir) direction. We aim to develop an approach to measure the actual orientation of this eigenvector. 

Here, we present the results of a polarimetric wide-angle common midpoint (CMP) survey conducted on Ekström Ice Shelf, Dronning Maud Land, Antarctica, using the Autonomous phase-sensitive Radio Echo Sounder (ApRES). Our CMP survey had a maximum antenna offset of 200 m, with an ice shelf thickness of 250 m. For several englacial reflectors, we observe offset-dependent phase shifts between orthogonal antenna orientations. We explore these phase variations by modelling the off-nadir radio wave propagation in the birefringent ice. These wide-angle radar surveys have the potential to infer the full crystal orientation tensor, required for a constitutive paramerization of glacial flow.

How to cite: Oraschewski, F. M., Ershadi, M. R., Henry, C., and Drews, R.: Can polarimetric wide-angle radar surveys teach us more about ice fabric anisotropy?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18077, https://doi.org/10.5194/egusphere-egu24-18077, 2024.

EGU24-18237 | ECS | Posters on site | CR5.4

Mapping of deep internal reflection horizons, method modifications and applications. 

Hameed Moqadam, Claudius Zelenka, and Olaf Eisen

The task of mapping of deep internal reflection horizons (IRH) of ice sheets has been a crucial step for a variety of glaciological studies, for instance relating ice core age-depth relationships, tuning ice sheet models, and extend dated layers beyond ice core sites. However, mapping a sufficient number of IRHs is a time-consuming and error-proned task. Thus, there have been ongoing endeavors for automatized pipelines to perform this.

In this work, a complete pipeline for automatic mapping of deep IRH, which determine ice layer boundaries, is presented. This pipeline is tested on radargrams from Dronning Maud Land Antarctica and shows good performance in mapping a number of deep IRHs. The model shows great promise to be used on snow radargrams and obtaining recent accumulation rates as well.

We have applied convolutional neural networks (CNN) to achieve this. The training data is composed of a small set of complete hand-labeled radargrams as well as radargrams that are labeled using conventional feature extraction methods. This task requires dense pixel-level predictions, and ground-truth collection is time-consuming and prone to errors, therefore a group of modifications have been implemented on the model. The role of post-processing is discussed, since the output of the model is a raw image and much work is done on the model output. The potential of such a deep mapped stratigraphy is discussed and various applications are pointed out.

How to cite: Moqadam, H., Zelenka, C., and Eisen, O.: Mapping of deep internal reflection horizons, method modifications and applications., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18237, https://doi.org/10.5194/egusphere-egu24-18237, 2024.

Radar sounder (or Ice-penetrating radar) is one of the most suitable geophysical instruments to explore planets and moons given the very dry and/or cold conditions of their crusts, which favor the penetration of the radio waves at great depth. The first ever planetary subsurface radar was tested on the Moon, during the Apollo 17 mission: the ALSE (Apollo Lunar Sounder Experiment) multifrequency radar sounder operating onboard the Apollo Service Module (ASM) (Porcello et al., 1974). After this successful experiment more than twenty years passed before another radar sounder was included in the payload of a planetary mission. MARSIS was launched in 2003, on board Mars Express, and SHARAD in 2007 onboard Mars Reconnaissance Orbiter. Since the successful deployed on Mars, such radars collected data for more than 15 years, mapping the structures of the Martian poles and discovering the first extraterrestrial stable body of subglacial liquid water below the South pole cap. Six orbiting radar sounders have been employed so far to explore the Moon, Mars and the 67P/GC comet, and some of them are still in full operation today. The Jupiter icy moons will be the next destination of a new generations of radars: RIME, already on his way to Ganymede onboard JUICE and REASON that will be launch this year onboard Europa Clipper. These radars will explore the icy shells of Europa, Ganymede and Callisto to establish their habitability conditions and in search for evidence of liquid water. Finally, also Venus will be investigated in the next decade by a similar radar to help understand the geological and climatic evolution of the Earth twin.

In this talk I will discuss the new opportunities and challenges for the radar sounder community in the years to come.

How to cite: Pettinelli, E.: In search for liquid water using radio waves: from Earth to the icy moons of Jupiter, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18640, https://doi.org/10.5194/egusphere-egu24-18640, 2024.

EGU24-499 | Posters on site | HS8.2.10

Simulating the Hydro-Geo-Chemical Processes during Submarine Groundwater Discharge by TOUGHREACT 

Tao Wang, Chenming Zhang, Ling Li, and Yajuan Yin

More than 60% of the global population lives in coastal areas, especially within 100 km from the coastlines, relying mostly on shallow groundwater resources. Seawater intrusion and submarine groundwater discharge (SGD) occur in the coastal aquifer systems, threatening these critical freshwater resources. Salinity seawater and fresh groundwater complexly interact with each other via SGD and SI. The SGD drives the discharge of not only a large volume of freshwater, but also terrestrial geochemical substances into the ocean through a mixing zone between discharging freshwater and recirculating seawater. The flux of SGD may be even greater than that of surface water through rivers and estuaries. For example, the SGD was estimated to be ~40 % and 80 %~160 % of the river water discharging flux into the South Atlantic Bight and Atlantic Ocean, respectively, and as a major source of dissolved organic matter and nutrients to Arctic coastal waters and the Mediterranean Sea.

A few hydrological models, including MARUN, SEAWAT, SUTRA, and PHT3D, are commonly used for SGD studies. The recently developed TOUGHREACT is robust in simulating coupled hydrodynamic, thermodynamic, and geochemical processes. From TOUGH2 (Transport Of Unsaturated Groundwater and Heat, version 2), a multi-dimensional numerical model for simulating coupled transport of water, vapor, non- condensable gas, and heat in porous and fractured media. However, TOUGHREACT is rarely used for SGD analysis, despite it being a well-rounded model with wide applications. Additionally, relevant studies on the iron (Fe) precipitation during SGD have focused predominantly on its spatial distribution and the adsorption of dissolved species, and studies on the genesis and geochemical evolution are scarce.

Therefore, we developed a systematic method using TOUGHREACT to simulate the hydrological processes in STEs and benchmarked the estimations; and then we numerically explored the groundwater flow and salt transport dur SGD by considering the influencing factors of tidal amplitude, freshwater head, seawater diffusion coefficient, and beach slope ratio. Consequently, by employing TOUGHREACT simulation, we analyzed the formation and spatiotemporal distribution of the Fe precipitation in the shallow beach aquifer due to the mixing of freshwater and seawater, and identified the key influencing factors during SGD.

The results show that, freshwater-derived Fe2+ is oxidized by O2(aq) in seawater during SGD, then precipitates as Fe (hydr)oxides (Fe(OH)3) to form an Fe precipitation zone. Fe(OH)3 tends to accumulate in the freshwater side of the mixing zone, whereas Fe(OH)3 precipitation in the seaward side of the mixing zone is inhibited by locally high H+ concentrations. The Fe(OH)3 first precipitates in the shallow aquifer, then extends to deeper layers over time, which is attributed to the increase in the residence time with the depth of both freshwater and seawater. The spatial distribution, and particularly, the extent of the iron curtain are influenced by the water flux and the concentration ratio of O2(aq) to Fe2+. These results are beneficial for better understanding the formation and distribution of iron curtains, and shed light on enhancing the understanding of the hydrogeochemical processes in subterranean estuaries.

How to cite: Wang, T., Zhang, C., Li, L., and Yin, Y.: Simulating the Hydro-Geo-Chemical Processes during Submarine Groundwater Discharge by TOUGHREACT, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-499, https://doi.org/10.5194/egusphere-egu24-499, 2024.

EGU24-1319 | ECS | Orals | HS8.2.10

Identifying urban subsurface thermal and hydraulic processes from time-series groundwater temperature data 

Ashley Patton, Peter Cleall, and Mark Cuthbert

The subsurface Urban Heat Island effect has been proposed as a shallow geothermal energy resource, however, annual near-subsurface temperature variation may result in unexpected system performance. Understanding heat transport processes in the urban subsurface is key to managing and modelling city-scale thermal regimes for geothermal energy resource development. Existing studies have focussed on analysis of repeat temperature-depth profiles rather than long-term groundwater temperature time-series. We show here how time-series analysis can complement temperature-depth profiles and offer additional insights into the controls on subsurface thermal transport processes.

Annual variations in temperature time-series from 49 boreholes in the Cardiff Geo-observatory (UK), recorded between 2014-2018, fall into several distinct shape categories. We hypothesise these shapes are indicative of the dominance of particular flow and heat transport mechanisms such that sinusoidal profiles are associated with conduction-only settings, while ‘right-skewed’ profiles denote the influence of advection. Short-lived temperature events are observed on the cooling limbs of such profiles and are correlated with groundwater level rises, indicative of recharge events. These winter temperature drops have the effect of cooling groundwater faster in winter than it is warmed in summer. The short timescales of these events suggest recharge is localised and may be controlled by preferential flow paths within the superficial deposits overlying the aquifer. While these events do have an overall cooling effect on the seasonal temperature profile, groundwater temperatures following these events recover quickly to levels near what they were before the recharge event, suggestive of the presence of local thermal non-equilibrium with the gravel aquifer. More complex behaviours observed in boreholes located close to the city’s rivers indicate recharge responses coupled with the influence of stream-aquifer interactions. Thus, temperature time-series data have potential as a tool to identify subsurface hydraulic and thermal processes, with implications for geothermal exploration and the wider field of hydrogeology.

How to cite: Patton, A., Cleall, P., and Cuthbert, M.: Identifying urban subsurface thermal and hydraulic processes from time-series groundwater temperature data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1319, https://doi.org/10.5194/egusphere-egu24-1319, 2024.

EGU24-1879 | ECS | Orals | HS8.2.10

Does an anthropogenically induced subsurface temperature hotspot affect groundwater ecology? 

Maximilian Noethen, Julia Becher, Kathrin Menberg, Philipp Blum, Simon Schüppler, Erhard Metzler, and Peter Bayer

Worldwide shallow groundwater is increasingly exposed to anthropogenic impacts. The thermal state of this important resource is affected not only by global warming but also by various local structures that release heat into the subsurface. This additional heat can accumulate and lead to local hotspots or - mostly urban - areas of elevated groundwater temperatures. The consequences of this warming for groundwater quality and ecology are widely unknown. Groundwater ecosystems are embedded in a naturally relatively stable environment, where temperature changes can affect the highly specialized, cold-stenotherm invertebrate community and meso- to psychrophilic microorganisms. In this study, we examine whether and how a groundwater temperature hotspot impacts groundwater ecology. We identified such a thermal anomaly in Hockenheim, Germany, caused by a water park with heated swimming pools and basements. The thermal impact was monitored over the course of a year by temperature data loggers in nine wells – four upstream and downstream of the structure each and one inside the basement. The same wells were sampled for chemical and microbiological parameters, such as the microbial total cell count and the cellular ATP content, as well as groundwater fauna. We additionally tested three wells in a nearby forest to obtain reference values that are mostly unaffected by anthropogenic interference. The measurements were repeated every three months in order to account for seasonal variations. The preliminary results show a local heat plume and an increase in groundwater temperatures by up to 8 K. However, there is no significant deterioration in the ecological parameters. Regarding the fauna, which generally shows low abundance due to oxygen depletion in the study area, we observed only a minor decrease within the thermally affected zone. Finally, the outcome of this study will improve our understanding of the vulnerability of groundwater ecosystems in the context of subsurface warming.

How to cite: Noethen, M., Becher, J., Menberg, K., Blum, P., Schüppler, S., Metzler, E., and Bayer, P.: Does an anthropogenically induced subsurface temperature hotspot affect groundwater ecology?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1879, https://doi.org/10.5194/egusphere-egu24-1879, 2024.

Springs offer insight into the sources and mechanisms of groundwater recharge and can be used to characterize fluid migration during earthquakes. However, few reports provide sufficient annual hydrochemical and isotopic data to compare the variation characteristics and mechanisms with both atmospheric temperature and seismic effects. As such, it is critical to obtain time series observations of stable isptopes (δ2H, δ18O and δ13CDIC) to understand the complex interactions between hydrological processes, cycle, and relationship with earthquakes. In this study, we used continuous δ2H, δ18O, δ13CDIC, and major ion data from four springs over 1 year to understand the groundwater origin, recharge sources, circulation characteristics, and coupling relationships with atmospheric temperature and earthquakes. We found that (1) the four springs are likely recharged by deep circulation of meteoric water from Bogda Mountain in the east, as well as long-distance runoff recharge from the Turpan Basin to the south. (2) atmospheric temperatures above and below 0 °C can cause significant changes in ion concentrations and water circulation depth, resulting in the mixing of fresh and old water in the aquifer, it can cause changes in δ13CDIC but it doesn’t work in δ2H and δ18O. (3) Earthquakes of magnitude ≥ 4.8 within a 66 km epicentral distance can alter fault zone characteristics (e.g., permeability) and aggravate water–rock reactions, resulting in significant changes in δ2H, δ18O, and hydrochemical ion concentrations, accompanied by limited changes in δ13CDIC. (4) Hydrogen and oxygen isotopes are the most sensitive precursory seismic indicators. The results of this study offer a reference for the establishment of long-term hydrochemical and isotopic monitoring, with the potential for use in earthquake forecasting.

This work is financially supported by the Natural Science Foundation of China (Grant No. 42373067) and by the Science for Earthquake Resilience (grant number XH23048C).

How to cite: Zhou, Z., Ren, X., Zhong, J., and Feng, X.: Response Characteristics of Hydrogen, Oxygen, and Carbon Isotope Composition to Atmospheric Temperature and Seismic Activity in Spring Water Hydrogeochemistry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2499, https://doi.org/10.5194/egusphere-egu24-2499, 2024.

EGU24-4000 | Posters on site | HS8.2.10

The impact of our warming climate on global groundwater temperatures 

Susanne A. Benz, Dylan J. Irvine, Gabriel C. Rau, Peter Bayer, Kathrin Menberg, Philipp Blum, Rob C Jamieson, Christian Griebler, and Barret Kuryly

Groundwater, the largest reservoir of unfrozen freshwater on Earth, plays a crucial role in supporting life and ecosystems. Its thermal regimes influence various environmental processes, impacting groundwater-dependent ecosystems, geothermal potential, and groundwater quality. Despite its significance, little is known about how groundwater responds to surface warming across spatial and temporal scales. Here we present a comprehensive analysis of global groundwater temperature patterns, utilizing the latest CMIP6 scenarios.

In this study we developed the first global model of groundwater temperature patterns, combining analytical solutions to conductive heat transport with high-resolution maps of ground thermal diffusivity and geothermal gradient. This model, validated with over 8,000 groundwater temperature measurements, allows users to estimate present and future temperature depth profiles globally. Past trends show a median global groundwater temperature increase of 0.3 °C over the last two decades. When simulating projected groundwater temperatures globally, our model reveals an average warming of 2.2°C (SSP 245) to 3.8°C (SSP 585) between 2000 and 2100 at the depth of the water table. Regional variations are substantial due to climate change and water table depth variability, with mountainous regions exhibiting the lowest warming rates. These distinct regional variations emphasize important thermal controls and the need for localized analysis.

Our work sheds light on the importance of understanding groundwater warming patterns, identifying 'hot spots' that may pose risks to both ecosystems and human well-being. In this study we also offer a specific focus on Europe, providing averages to enhance regional relevance and address emerging challenges in groundwater quality and habitat preservation.

How to cite: Benz, S. A., Irvine, D. J., Rau, G. C., Bayer, P., Menberg, K., Blum, P., Jamieson, R. C., Griebler, C., and Kuryly, B.: The impact of our warming climate on global groundwater temperatures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4000, https://doi.org/10.5194/egusphere-egu24-4000, 2024.

EGU24-4575 | ECS | Orals | HS8.2.10

Offshore freshened groundwater identified in southern Sicily (Italy) by applying well logs petrophysical interpretation.  

Damiano Chiacchieri, Lorenzo Lipparini, Aaron Micallef, and Elizabeth Quiroga

The work focused on the Oligo-Miocene Ragusa Formation, a known regional shallow aquifer in the Hyblean Plateau in southern Sicily, made of medium to high porosity carbonates deposited in the ramp environment, also investigated in the adjacent offshore by deep well drilling.

The main objective was to investigate if and how this known shallow onshore aquifer extend in the coastal area and possibly offshore.

A detailed methodology was defined for the quantitative use of geophysical logs from about five deep Oil & Gas wells to characterize groundwater in the Ragusa Formation in terms of pressure, piezometry and salinity distribution, as it follows:

  • A first step was the digitization of the full suite of logs required for the application of petrophysical workflow for each well analysed, for a total of about 25 km of digitized logs, such as SP (Spontaneous Potential), GR (Gamma Ray), DT (Sonic log) and Resistivity logs.
  • At the same time a synthetic lithological log for each selected well was built, to support the understanding of lithological influence of electrical logs.
  • A customised petrophysical workflow to calculate porosity and salinity (concentration of salts in TDS) was applied, considering: lithotypes, BHT (borehole temperatures), porosity (derived to DT – sonic log), pore fluid resistivity.
  • A comparison of TDS results with salinity data from DST and composite logs was performed.
  • A detailed well correlation and comparison between onshore shallow water wells and deep Oil&Gas wells, both onshore and offshore, was carried out.

By applying this petrophysical approach, it was possible to identify and quantified key indications of the presence of fresh groundwater in the Ragusa Formation carbonates both onshore and offshore in southern Sicily (Italy). Indeed, has been demonstrated that the onshore outcropping aquifer appear likely connected with the deep offshore aquifer due to positive indications in the same geological formation 10 km offshore from the coastline.

How to cite: Chiacchieri, D., Lipparini, L., Micallef, A., and Quiroga, E.: Offshore freshened groundwater identified in southern Sicily (Italy) by applying well logs petrophysical interpretation. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4575, https://doi.org/10.5194/egusphere-egu24-4575, 2024.

EGU24-4855 | ECS | Orals | HS8.2.10

Hydrogeochemical Characteristics and Genetic Mechanisms of Geothermal Fields in the Xi'an Depression of the Weihe Basin 

Jian Liu, Zhanli Ren, Qiang Yu, Xinyun Yan, Kai Qi, Zhen Wang, Sasa Guo, Huaping Lan, Mingxing Jia, and Yanzhao Liu

The geothermal resources in sedimentary basins have high potential for development and utilization, and have become an important research topic worldwide(Olasolo et al.,2016; Pasvanoğlu and Çelik., 2019; Duan et al.,2022). This paper focuses on the genetic mechanism and evolution process of deep geothermal water were explored through the analysis of hydrogeochemical and isotope geochemical data, which can provide technical and theoretical support for the sustainable development of geothermal fields in the Weihe basin. The study indicates that: (1)the hydrochemical type of geothermal water of Dongda geothermal field are predominantly HCO3·SO4-Na type. Meanwhile, the hydrochemical type of geothermal water of the northern Xi'an Depression are mainly SO4·HCO3-Na and SO4·HCO3·Cl-Na types. The ionic fraction is primarily influenced by the dissolution of silicate and evaporite minerals, as well as alternating cation adsorption. (2) Geothermal water is primarily recharged by atmospheric precipitation originating from the Qinling Mountains. The recharge elevation ranges from 677.94 m to 1467.65 m. (3) The Dongda geothermal field has a thermal storage temperature ranging from 50.19℃ to 80.29℃, and a depth of thermal circulation ranging from 1126.32 m to 2129.62m. Meanwhile, the northern Xi'an depression has a thermal storage temperature ranging from 73.17℃ to 109.50℃, and a depth of thermal circulation ranging from 1892.41 m to 3103.22 m. (4) The δ18O of the geothermal water in the northern Xi'an depression is more significantly shifted to the right of the atmospheric precipitation line than that of the Dongda geothermal water, indicating a significant “oxygen drift”.(5) The Dongda geothermal reservoir in the southern Xi'an Depression mainly experiences heat transfer through convection, while the geothermal reservoir in the northern Xi'an depression experiences heat transfer through conduction.

References

[1]Duan, R., Li, P., Wang, L., He, X., & Zhang, L. (2022). Hydrochemical characteristics, hydrochemical processes and recharge sources of the geothermal systems in Lanzhou City, northwestern China. Urban Climate, 43, 101152.

[2]Olasolo, P., Juárez, M. C., Morales, M. P., & Liarte, I. A. (2016). Enhanced geothermal systems (EGS): A review. Renewable and Sustainable Energy Reviews, 56, 133-144.

[3]Pasvanoğlu, S., & Çelik, M. (2019). Hydrogeochemical characteristics and conceptual model of Çamlıdere low temperature geothermal prospect, northern Central Anatolia. Geothermics, 79, 82-104.

How to cite: Liu, J., Ren, Z., Yu, Q., Yan, X., Qi, K., Wang, Z., Guo, S., Lan, H., Jia, M., and Liu, Y.: Hydrogeochemical Characteristics and Genetic Mechanisms of Geothermal Fields in the Xi'an Depression of the Weihe Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4855, https://doi.org/10.5194/egusphere-egu24-4855, 2024.

EGU24-5269 | Orals | HS8.2.10

Exploring the Hidden Exchanges: Groundwater-Surface Water Interactions in a Critical Zone Observatory 

Julian Klaus, Günter Blöschl, Enrico Bonanno, Barbara Glaser, Laurent Gourdol, Christophe Hissler, Luisa Hopp, Laurent Pfister, and Keith Smettem

The exchange between groundwater (GW) and surface water (SW) plays a crucial role for streamflow generation and the biogeochemical cycles within landscapes. However, accurately observing and predicting this exchange remains challenging due to the spatial heterogeneity and temporally dynamic fluxes of groundwater within the stream corridor. This presentation offers new insights into the characteristics of GW-SW interactions and hydrological processes within the hillslope-riparian-stream continuum, employing a combined experimental and modeling approach. The research builds on a comprehensive, long-term dataset obtained through baseline monitoring in the Weierbach Experimental Catchment (WEC) in Luxembourg that is a 45-hectare forested catchment. In addition to baseline monitoring, our approach involved (i) a network of 43 wells and piezometers along a selected stream reach for continuous monitoring and tracer experiments, (ii) a network of 13 wells along the riparian-hillslope interface, and (iii) ground-based thermal infrared imagery to observe spatiotemporal dynamics of surface saturation along the stream corridor. An integrated surface-subsurface hydrologic model served as a hypothesis-testing tool to examine whether surface saturation is predominantly driven by groundwater inflow or precipitation and how the relevance of the processes – surface ponding from precipitation or subsurface exfiltration – change in space and time.

We coupled the hydrological model with a hydraulic mixing-cell approach that enabled deciphering the contributions from different water sources to SW. The well network and associated artificial tracer experiments provided valuable insights into the direction of GW-SW exchange, revealing directional variability at scales of a few meters. Additionally, wells at the riparian-hillslope interface demonstrated a strong non-linearity of GW contributions to SW, influenced by GW table fluctuations. The observed and simulated surface saturation aligned well, suggesting that GW exfiltration primarily controls surface saturation in the stream corridor. Furthermore, the mixing-cell simulations revealed that subsurface water exfiltration is the dominant source for riparian surface water and intermittent streamflow, with distinct differences between stream water and riparian surface saturation. Overall, the combination of experimental techniques, hydrologic modeling, and well networks clearly improved our understanding of GW-SW interactions and revealed previously hidden exchanges in the WEC.

How to cite: Klaus, J., Blöschl, G., Bonanno, E., Glaser, B., Gourdol, L., Hissler, C., Hopp, L., Pfister, L., and Smettem, K.: Exploring the Hidden Exchanges: Groundwater-Surface Water Interactions in a Critical Zone Observatory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5269, https://doi.org/10.5194/egusphere-egu24-5269, 2024.

The analysis of twenty geophysical well logs covering a shelf area of about 3,500 km2 in front of the Emilia-Romagna coast (Italy), has shown apparent resistivity (ρa) values consistent with important Offshore Freshened Groundwater (OFG) reserves stored in the first 450 m of the Middle-to-Upper Pleistocene succession, and extending seaward about 60 km from the modern shoreline. Four classes with different ρa intervals (i.e., different salinities) were identified. The first three (1, 2 and 3) classes are characterized by ρa ranges of 7-28 Ω m, 4-7 Ω m and 2-4 Ω m, respectively. These values are higher than seawater resistivity (< 2 Ω m - i.e., class 4) and, based on the OFG definition (i.e., “the water stored in the sub-seafloor with a total dissolved solid concentration below that of seawater”), they have been used for OFG identification. Class 1 ρa is coherent with fresh-to-brackish water content, whereas classes 2 and 3 have been interpreted as transitional to seawater.
The correlation of offshore wells (spontaneous potential and ρa profiles) with onshore data (stratigraphic and lithological) from water wells and additional geophysical well logs, led to the stratigraphic architecture reconstruction of the Plio-Pleistocene siliciclastic succession along onshore-offshore transects, up to 60 km-long, from the Apennine front to the Adriatic shelf. The uppermost (first 450 m) Middle to Upper Pleistocene interval displays a vertical alternation of high-permeability (amalgamated and laterally continuous gravel to sand bodies) and low-permeability (mud-dominated) strata made of fluvio-deltaic, coastal and shelfal deposits. The high-permeability bodies represent the offshore extension of the onshore aquifer systems, whereas the low-permeability units make the aquitards. Along the transects, different stratigraphic intervals characterized by the four ρa classes have been identified. The highest ρa values (class 1) have been documented in the first 300 m of the succession, despite its deposition mostly occurred in deltaic to marine (i.e., saline water) conditions. This interval wedges out seawards, with ρa progressively decreasing down to class 3 values at about 35 km from the coast. Similarly, ρa decreases vertically, between about 300 and 450 m depth. Such a vertical gradual decrease may suggest that locally aquitards do not completely prevent water exchange, and transitional classes 2 and 3 likely resulted from freshwater and seawater mixing through space and time. Below 450 m depth, ρa drops to < 2 Ω m (class 4), thus defining the lowermost limit of the OFG reserves.    
Onshore-offshore reconstructions additionally revealed how OFG aquifers are actively recharged in correspondence of the Apennine front, where the topographic gradient is higher and permeable units are subaerially exposed. Their extremely high degree of amalgamation even allows the topographically-driven recharge of the deeper (and marine) strata.
The relatively shallow depth (< 350 m) of the northern Adriatic aquifers and the presence of several and abandoned oil&gas platforms in the area, provide a good opportunity to further investigate these OFG reserves that are strategic for the densely populated Emilia-Romagna coastal plain.

How to cite: Campo, B. and Antonellini, M.: Offshore freshened groundwater reserves identification as revealed by geophysical and stratigraphic data: insights from the Northern Adriatic shelf (Italy) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5599, https://doi.org/10.5194/egusphere-egu24-5599, 2024.

EGU24-7016 | Posters on site | HS8.2.10

Characterization of near-shore fresh water and seawater interactions-the scale issues drawn from the experimental and numerical approaches 

Chuen-Fa Ni, Thanh Quynh Duong, Chia-Yu Hsu, Nguyen Thai Vinh-Truong, and Yu-Huan Chang

Understanding the dynamics of water and mass interactions in the coastal area is essential to quantify the influences of near-shore land use on the coastal aquifers and water environment. The study aims to integrate innovative experiments and modeling techniques to assess the heat and water exchanges in the coastal aquifer of the Taoyuan Tableland in northwestern Taiwan. The site-specific hydraulic and heat tracer tests are conducted to obtain flow and heat transfer properties for the specific aquifer layers at the site. We then used the SEAWAT numerical model to quantify the freshwater and seawater interactions. The model calibration relies on the groundwater levels and quality obtained from monitoring wells installed perpendicular to the shoreline. The experimental results show that the active heat tracer tests could significantly improve the identification of aquifer layers along a well and allow for the estimations of high-resolution natural groundwater flux toward the sea. The estimated flow rate based on the heat tracer test is approximately 0.2 m/day per unit depth. The numerical model shows good agreement with the observed water levels in wells. In the study area, the location of the seawater/groundwater mixing interface is estimated at approximately 350m seaward from the shoreline, which suggests the submarine groundwater discharge zone for the site. The vertical profile model shows that the flow rate for the 100m depth aquifer varies from 51 to 60 m3/day per unit width, depending on the tidal variations and upstream groundwater levels. The results show a large flow rate discrepancy between experimental and numerical approaches, which the resolution scales of the approaches might induce in the calculations. The water levels obtained from the fully opened screen wells might mix the flow responses in different aquifer layers.

How to cite: Ni, C.-F., Duong, T. Q., Hsu, C.-Y., Vinh-Truong, N. T., and Chang, Y.-H.: Characterization of near-shore fresh water and seawater interactions-the scale issues drawn from the experimental and numerical approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7016, https://doi.org/10.5194/egusphere-egu24-7016, 2024.

EGU24-7668 | ECS | Orals | HS8.2.10

Downhole passive fiber optics temperature monitoring for improved characterization of aquifer heterogeneities 

Davide Furlanetto, Matteo Camporese, Luca Schenato, Leonardo Costa, and Paolo Salandin

Unconfined shallow aquifers are particularly exposed to the risk of contamination. Especially when exploited for drinking water production, for which water quality is of particular concern, careful monitoring of the physical processes and detailed characterization of the subsurface properties are crucial. Furthermore, the possible presence of heterogeneities, such as intricate networks of hydraulically conductive paleo-channels that are often inherent in alluvial aquifers, can establish preferential pathways. Consequently, monitoring activities in these complex environments pose serious challenges and raise the demand for advanced techniques and innovative approaches. In this context, recent advances have been made possible by employing Fiber Optics Distributed Temperature Sensing (FO-DTS). This technology combines the use of heat as a natural tracer with a detailed spatiotemporal resolution and has proven informative in a wide variety of applications. In this study, we applied downhole passive FO-DTS to a cluster of piezometers in a highly heterogeneous phreatic gravelly aquifer. The aquifer is exploited for irrigation and drinking water supply, and exhibits both natural and pumping-induced groundwater temperature fluctuations. Vertical transient water temperature profiles were acquired over a 1-month experiment. Borehole-dependent and depth-related features of the temperature measurements were ascribed to possible spatial structures having different hydraulic conductivity. The collected data were used to invert the three-dimensional saturated hydraulic conductivity field of a physics-based numerical model that couples flow and heat transport. Even without active heating, FO-DTS has demonstrated its ability to provide valuable insights at an unprecedentedly high resolution.

How to cite: Furlanetto, D., Camporese, M., Schenato, L., Costa, L., and Salandin, P.: Downhole passive fiber optics temperature monitoring for improved characterization of aquifer heterogeneities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7668, https://doi.org/10.5194/egusphere-egu24-7668, 2024.

EGU24-9552 | ECS | Posters on site | HS8.2.10

Spatio-temporal distribution of subsurface urban heat islands – Insights from shallow groundwater temperature monitoring in Vienna 

Eva Kaminsky, Gregor Laaha, Cornelia Steiner, Eszter Nyéki, Constanze Englisch, Christian Griebler, and Christine Stumpp

In numerous cities worldwide, a rise in surface temperatures had been observed, contributing to the so-called "urban heat island effect". This effect leads to extended and hotter periods of warm weather within urban areas not only above but also below ground. The heat in the subsurface can be used for shallow geothermal energy, but it requires knowledge of spatial and temporal variations in groundwater temperature for efficient and environmentally friendly utilization of groundwater for heating and cooling. In the course of the 'Heat below the City' project, we have compiled spatial high-resolution data and developed groundwater temperature maps for the city of Vienna targeting the coldest and warmest annual conditions. Borehole temperature profiles were recorded in October 2021 and April 2022. This enabled the identification of distinct urban heat islands. Additionally, available long-term data (2001-2020) was used to conduct annual temperature trend analyses and extreme value assessments to evaluate temperature changes over time. In Vienna, an average annual temperature increase, considering all significant trends, of 0.9 ± 0.1 K/decade was observed for air, soil and shallow groundwater between 2001 and 2021. However, the increase is non-linear and, over the last decade, the change has accelerated with an increase of 1.4 ±0.2 K/decade (only significant trends taken into account). The current annual mean temperature is 14.1 °C (2021/ 2022) with individual warmer urban heat islands and locally heated locations of up to 30.6°C. Trends in extreme temperatures (represented by the lower/upper 10th percentile air, soil and groundwater temperature in quantile regression) generally show the strongest increase in the lower 10th percentile temperatures for all air and soil temperatures. But this varies site-specifically in shallow groundwater, where urban infrastructure and the interaction between surface and groundwater, in addition to climate change, influence groundwater warming. Potentially, those urban heat islands with increasing trends in groundwater temperatures have great potential for heat utilization, but should not be used for extraction of cold. These findings emphasize the importance of spatial and temporal high-resolution data and highlight the necessity for site-specific aquifer characterization for a sustainable use of shallow geothermal energy for heating and cooling.

How to cite: Kaminsky, E., Laaha, G., Steiner, C., Nyéki, E., Englisch, C., Griebler, C., and Stumpp, C.: Spatio-temporal distribution of subsurface urban heat islands – Insights from shallow groundwater temperature monitoring in Vienna, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9552, https://doi.org/10.5194/egusphere-egu24-9552, 2024.

EGU24-10761 | ECS | Orals | HS8.2.10

Conceptual 3D groundwater models of offshore freshened groundwater extraction and its economic viability assessment 

Daniel Zamrsky, Joep J.H. van Lith, and Rens van Beek

Offshore freshened groundwater reserves have been identified in numerous regions worldwide. These reserves were often deposited during past sea level lowstands and are therefore non-renewable and slowly salinized by infiltrating seawater. However, in some cases these offshore freshened groundwater reserves can be connected to inland groundwater systems and can be recharged by fresh groundwater inflow from the landward direction. It has recently been suggested that these offshore freshened groundwater reserves could provide an additional source of fresh (and brackish) water for coastal communities that often face increasing fresh water stress. The feasibility, both economic and physical, of offshore freshened groundwater extraction is investigated in this study. To assess this feasibility from a physical point of view we built a set of 3D semi-conceptual groundwater flow models using the imod-wq code which allows us to estimate the offshore groundwater salinity development over large time scales (i.e. one glacial-interglacial cycle). The result of these large time scale models can be interpreted as estimations of the current offshore groundwater salinity conditions and thus provide a better picture of the current presence and magnitude of the offshore freshened groundwater resources in the model domain. In the next modelling stress period we introduce a set of pumping wells into the offshore domain and simulate several offshore freshened groundwater extraction scenarios. In such way we can evaluate the time it takes for these offshore freshened groundwater reserves to be fully salinized and exhausted. Additionally, we can also assess any potential negative impacts on the groundwater system in the coastal hinterland such as decreasing groundwater levels and/or increased salinization.

In the second part of our study we evaluate the economic feasibility of the offshore freshened groundwater pumping and use as additional fresh water resource for coastal communities. Several coastal areas located in south and south-east Asia (e.g. Pearl River delta) were selected since this region is identified as a region with high possibility and magnitude of offshore freshened groundwater resources. The economic parameters that are taken into account as favourable for offshore freshened groundwater exploration are (i) the overall economic development (e.g. GDP, HDI), (ii) the presence of groundwater pumping and desalination plants inland meaning the technology is already present in the region and (iii) costs of fresh water and groundwater pumping and desalination infrastructure in the region. Our study is only the first step in assessing the feasibility of offshore freshened groundwater exploration and hopefully our approach will be improved and tested in other coastal regions around the world to evaluate the full potential of these still untapped fresh groundwater resources.

How to cite: Zamrsky, D., van Lith, J. J. H., and van Beek, R.: Conceptual 3D groundwater models of offshore freshened groundwater extraction and its economic viability assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10761, https://doi.org/10.5194/egusphere-egu24-10761, 2024.

The validation of hydrogeological distributed models in western african countries is limited by the quality and availability of point station data measured in-situ. Climate models, satellite and reanalysis data have been suggested to overcome this limit. Here, we assessed the quality of ERA5 reanalysis on water table depth (WTD), and soil water content (SWC) over the Benin basins at spatial scale and monthly time scale. The single-levels version with 0.25° x 0.25° resolution (ERA5) and the land surface version with 0.1° x 0.1° resolution (namely LAND) were compared with point station data using the correlation performance evaluators and the Mean Absolute Error (MAE). The results showed that ERA5 and LAND reanalysis present well the water planes of Benin (WTD =0m). Outside wetlands areas, both reanalyses slight overestimation the WTD (MAE of ERA5=4.73m vs. LAND=3.13m. The SWC between 0-7 cm; 7-28cm and 28-100cm presented on both reanalyses are well in line with observations for all stations and on a monthly scale (correlation sometimes > 0.85 for LAND and 0.83 for ERA5). We recommend the use of LAND for validation of hydrogeological distributed models in Benin. Correcting the variables of these reanalyses could improve their performance.

How to cite: Bodjrenou, R.: Assessment of water table depth and soil water content Estimates from ERA5 reanalysis in Benin (West Africa), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12160, https://doi.org/10.5194/egusphere-egu24-12160, 2024.

EGU24-12406 | ECS | Posters on site | HS8.2.10

Investigating Submarine Groundwater Transmissivity in Svalbard Fjord Sediments through the Analyses of Physical Properties and Chemical Composition 

Zaga Trisovic, Matthew O'Regan, Sophie ten Hietbrink, Beata Szymczycha, Arunima Sen, Aivo Lepland, Jochen Knies, and Wei-Li Hong

We investigate submarine groundwater transmissivity within Svalbard fjord sediments, where offshore freshened groundwater (OFG) was confirmed through analyses of dissolved chloride concentration and water isotope signatures (δ18O and δ2H). The analyses are comprised of physical, mechanical, and chemical attributes of three cores recovered from Tempelfjorden and Hornsund fjords. Multi-Sensor Core Logger (MSCL) analyses provide high-resolution physical characteristics of the sediment cores, including bulk density, p-wave velocity, magnetic susceptibility, and electrical resistivity. These are integrated with X-ray computed tomography (CT) images, acquired with a Geotek rotating X-ray CT system (RXCT), to identify sedimentary facies, which are used to investigate internal core structures. Discrete measurements of grain density and grain size are used to calculate sediment porosity and to estimate the permeability. Our results indicate a heterogeneous sediment matrix with frequent drop stones and ice-rafted debris interlayered with finer-grained materials. We hypothesize that the sediment matrix packaging and configuration is an important control for the sediment permeability and thus for freshened groundwater transmissivity in the sediments of these fjords. This work is not only relevant for characterizing groundwater transmissivity in Svalbard's fjords but also will contribute to ongoing geological modeling efforts. Our findings pave the way for hydrogeological simulations, enhancing our understanding of OFG occurrence, emplacement mechanisms, and OFG volumes over successive glacial cycles.

How to cite: Trisovic, Z., O'Regan, M., ten Hietbrink, S., Szymczycha, B., Sen, A., Lepland, A., Knies, J., and Hong, W.-L.: Investigating Submarine Groundwater Transmissivity in Svalbard Fjord Sediments through the Analyses of Physical Properties and Chemical Composition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12406, https://doi.org/10.5194/egusphere-egu24-12406, 2024.

EGU24-13147 | Posters on site | HS8.2.10

Assessing Surface Water and Groundwater Interactions Using Long-Term Hydrological and Time-Lapse Seismic Data in the Orgeval Critical Zone Observatory 

Agnès Rivière, Marine Dangeard, Ludovic Bodet, Ramon Sanchez Gonzalez, and Alexandrine Gesret

Quantifying the water and heat fluxes at the interface between surface water (SW) and groundwater (GW) is a key issue for hydrogeologists to consider for safe yield and good water quality. However, such quantification with field measurements is not straightforward because the SW-GW changes depend on the boundary conditions and the spatial description of the hydrofacies, which aren't well known and are usually guessed by calibrating models using standard data like hydraulic heads and river discharge. We provide a methodology to build stronger constraints to the numerical simulation and the hydrodynamic and thermal parameter calibration, both in space and time, by using a multi-method approach. Our method, applied to the Orgeval Critical Zone Observatory (France), estimates both water flow and heat fluxes through the SW-GW interface using long-term hydrological data, time-lapse seismic data, and modeling tools. We show how a thorough interpretation of high-resolution geophysical images, combined with geotechnical data, provides a detailed distribution of hydrofacies, valuable prior information about the associated hydrodynamic property distribution. The temporal dynamic of the WT table can be captured with high-resolution time-lapse seismic acquisitions. Each seismic snapshot is then thoroughly inverted to image spatial WT variations. The long-term hydrogeological data (such as hydraulic head and temperature) and this prior geophysical information are then used to set the parameters for the hydrogeological modeling domain. The use of the WT geometry and temperature data improves the estimation of transient stream-aquifer exchanges.

How to cite: Rivière, A., Dangeard, M., Bodet, L., Sanchez Gonzalez, R., and Gesret, A.: Assessing Surface Water and Groundwater Interactions Using Long-Term Hydrological and Time-Lapse Seismic Data in the Orgeval Critical Zone Observatory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13147, https://doi.org/10.5194/egusphere-egu24-13147, 2024.

EGU24-13973 | ECS | Orals | HS8.2.10

Turn up the heat to locate and quantify groundwater flow in fractured rock aquifers in coastal zones of the tropical island of Curaçao 

Titus Kruijssen, Mike Wit, Sandra Akkermans, Joshua Leusink, Boris van Breukelen, Martine van der Ploeg, and Victor Bense

Dual porosity flow is an important mechanism for groundwater transport in fractured rock aquifers. However, quantification and characterization of fracture flow systems remains challenging, as it often involves complex procedures such as the injection of tracers. In this study we conducted single-well pumping tests in 11 uncased wells in a coastal fractured rock aquifer while monitoring in-well salinity and temperature gradients through downhole casts using a Conductivity-Temperature-Depth (CTD) logger. In this way, we aimed to observe how naturally occurring salinity gradients in the well become disturbed by induced groundwater flow to the well, and if these gradients may serve as natural tracers for fracture flow. Since natural temperature gradients in the wells are minimal, we applied point electrical heating at the bottom of the well to create a plume of slightly warmer water to migrate up the wellbore during pumping from the top. During the pumping tests in this set-up, repeated CTD casts suggest that groundwater flow to these wells is strongly focused along narrow zones and is occurring at various rates over a range of salinities and temperatures. Hence, the observed patterns in both salinity and temperature presumably reflect the presence of fracture zones, which could indeed be confirmed by downhole camera observations for some wells. Further data analysis resulted in detailed hydrogeological characterization of the 11 wells, comprising an assessment of the fracture density and hydraulic conductivity of the aquifers, as well as the origin of the inflowing water being meteoric mostly fresh water or deeper saline groundwater.

How to cite: Kruijssen, T., Wit, M., Akkermans, S., Leusink, J., van Breukelen, B., van der Ploeg, M., and Bense, V.: Turn up the heat to locate and quantify groundwater flow in fractured rock aquifers in coastal zones of the tropical island of Curaçao, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13973, https://doi.org/10.5194/egusphere-egu24-13973, 2024.

Geothermal heat production and aquifer thermal energy storage have significant potential to contribute to the energy transition. However, due to higher temperature inside the wells used, it is known that this leads to heat loss through conduction to the surrounding cooler, shallower groundwater systems. Therefore it is important to be able to anticipates such impacts to allow effective monitoring and prevention or mitigation measures when needed. However the thermal impact on groundwater systems is expected to strongly depend on local conditions. Therefore, this study focused on the impact of operational conditions (e.g. effective well temperatures and intermittency) and aquifer conditions (e.g. permeabilities and heterogeneity) on the resulting heat transport processes into the aquifer by conduction and density driven flow. To evaluate the degree and variation of impact that may occur under field conditions, the heat loss to a shallow groundwater system was simulated using a 2D axisymmetric numerical MODFLOW 6 model for a wide range of conditions considering both the impact of conduction and density-driven flow. The results of this study indicate that the total thermal impact and its distribution (up to >10 m from the hot well in 10 years) in shallow groundwater systems is strongly impacted by the induced density driven flow in the relatively permeable layers of the groundwater system. Conduction is dominant in transfer of heat from the hot well in the low permeability confining layers and for mitigating temperature differences in the groundwater system induced by buoyancy flow. Overall, this study highlights the importance of considering local conditions in assessing thermal impact by heat losses from hot well casings, to allow distinguishing these thermal impacts from those induced by leakage and to allow efficient thermal groundwater impact monitoring.

How to cite: de Vries, E. and Hartog, N.: Thermal impact on shallow groundwater systems by heat loss from hot wells: the impact of operational conditions and subsurface heterogeneity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15116, https://doi.org/10.5194/egusphere-egu24-15116, 2024.

The presented study focuses on quantifying the impact of the anthropogenic heat input from residential buildings on the subsurface temperature regime, employing an innovative approach that combines building physics simulations with heat and groundwater flow modelling. To enhance the applicability of the approach, sensitivity analyses of various parameters that govern the heat transfer from the investigated buildings are performed. The investigated parameters took hydrogeological and meteorological conditions, building properties (including different insulation standards and building types) as well as petrophysical rock properties into account.

The findings contribute to a comprehensive understanding of the subsurface temperature regimes within densely settled areas, which is particular significant for the impact assessment of shallow geothermal applications. Results of the study show that neglecting anthropogenic heat input may lead to an underestimation of the effects of shallow geothermal applications on the underground temperatures.

How to cite: Hastreiter, N. and Vienken, T.: Anthropogenic heat input into the subsurface: Influencing factors and its importance during shallow geothermal impact assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16623, https://doi.org/10.5194/egusphere-egu24-16623, 2024.

EGU24-17299 | ECS | Orals | HS8.2.10

Groundwater Level Assessment using Data logger and Manual monitoring in developing Country, southwestern Ethiopia 

Adisu Befekadu Kebede, Fekadu Fufa Feyessa, Thomas Hermans, and Kristine Walraevens

Groundwater monitoring is fundamental, especially for areas where there is a high dependency on groundwater use. Groundwater level (GWL) monitoring is poorly known in Ethiopia. The study focused on evaluating groundwater levels and their relation to precipitation in Ethiopia's Gilgel Gibe and Dhidhessa catchment areas. Groundwater levels (GWL), spring discharges, and rainfall data were collected from various points over the 2022/2023 hydrological year.  Rainfall varied across the region, increasing from April to September and decreasing from plateaus to lowlands with a value between 1539 mm to 1973mm annually. Groundwater levels showed significant spatial and temporal variation, influenced by precipitation and local topography.  Maximum water level varies between 17.6 and 5.75 m in the northwest, 11.6 and 6.2 m in the central part, 11.5 and 3.2 m in the east, 13.1and 4.2 m in the south. Minimum water level varies between 13.2 and 3.8 m in the northwest, 5.8 and 2.7 m in the central, 3.5 and 1.1 m in the east and 7 and 3. 6 m in the south of the study area. Groundwater level fluctuation in the automatically monitored well was 1.55m in the deep well and 3.99m in the shallow well. The spatial drop of the water table in the northwest and south is due to a hydraulic gradient to lowlands and depressions, and evapotranspiration from dense forest coverage. In the central and eastern study area, GWL is shallow and intermediate based on the positions of monitoring wells. Some wells are fully saturated during the rainy season between August and September. Shallow wells reacted swiftly to rainfall, but their levels declined in the dry season. Some wells in high elevation areas experienced minimal fluctuations due to their perched aquifer positions. Groundwater drawdown from usage in dug wells quickly recovered, suggesting potential for small-scale agricultural use. Long-term monitoring and increased data logging are recommended for future studies.

How to cite: Kebede, A. B., Feyessa, F. F., Hermans, T., and Walraevens, K.: Groundwater Level Assessment using Data logger and Manual monitoring in developing Country, southwestern Ethiopia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17299, https://doi.org/10.5194/egusphere-egu24-17299, 2024.

EGU24-17913 | Posters on site | HS8.2.10

Exploring historical anthropogenic influences on groundwater in the alluvial plain of the Upper Seine River 

Anne Jost, Gurpreet Dass, Fanny Picourlat, Shuaitao Wang, Laurence Lestel, David Eschbach, Nicolas Flipo, and Agnès Ducharne

Human activities have significantly influenced the hydrological functioning of wetlands since they were first settled, often with the aim of reducing their perceived inconvenient wetness. Reconstructing these historical developments and understanding their impacts on hydrosystems is essential to inform strategies for the sustainable management and conservation of these vital resources. We take the example of the upper Seine valley upstream of Paris, within the vast Bassée floodplain, to illustrate and quantify how the many artificial changes it has undergone over the centuries may have had a reciprocal effect on groundwater resources. We have identified three main types of land development, ranging from hydraulic works to direct groundwater abstraction, including land use changes associated with the extraction of alluvial sands and gravels that give rise to the gravel pit lakes that are particularly prominent in the study area. Our approach is based on a detailed cartographic reconstruction of each of these influences, feeding into a hydrogeological model of the plain. We outline the main principles behind its conception and then quantify the relative impacts of anthropogenic pressures on the aquifer system budget and water table depth.

How to cite: Jost, A., Dass, G., Picourlat, F., Wang, S., Lestel, L., Eschbach, D., Flipo, N., and Ducharne, A.: Exploring historical anthropogenic influences on groundwater in the alluvial plain of the Upper Seine River, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17913, https://doi.org/10.5194/egusphere-egu24-17913, 2024.

EGU24-19115 | ECS | Orals | HS8.2.10

Passive characterization of aquifer permeability and shear modulus and their evolution following earthquakes using tidal signals 

Augustin Thomas, Jerome Fortin, Benoit Vittecoq, and Sophie Violette

Tidal analysis of borehole pressure has become in the recent years’ literature an essential method to follow the evolution of the hydraulic conductivity of an aquifer over time. Most traditional methods (mainly pumping or slug tests) only produce a small number of observations, and come at a greater cost. However, groundwater level tidal analysis only requires monitoring data at a sampling rate of 1 hour, data which is extensively available. These solutions are applicable provided aquifers respond to at least one tidal phenomenon among oceanic, earth or atmospheric tides.

Martinique Island, in the Lesser Antilles, is a very interesting field to study these techniques, since 16 years of piezometric level data have been recorded on this volcanic island in a monitoring network of 29 boreholes. Here we focus our study on a closely monitored study site in the Galion plain, with three boreholes, a seismometer and past conducted pumping tests and seismic surveys. We compute amplitude and phase response of aquifers to atmospheric and earth tides. Then, the response of the semi-confined aquifers to different loading sources at the tidal frequencies (between 1 and 2 cycles per day) is modelled. A careful inversion is done to obtain the characteristics of the aquifer, including aquifer transmissivity and shear modulus.

Finally, we analyse the evolutions of these inverted parameters and decipher their reversible and irreversible changes. Between earthquakes, we show the dominant effect of effective stress to control aquifer hydraulic conductivity. At the time of the earthquake, with the help of seismic stress numerical simulation, we show that seismic shear stresses are the most probable cause of aquifer properties changes both in permeability and shear modulus.

How to cite: Thomas, A., Fortin, J., Vittecoq, B., and Violette, S.: Passive characterization of aquifer permeability and shear modulus and their evolution following earthquakes using tidal signals, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19115, https://doi.org/10.5194/egusphere-egu24-19115, 2024.

Temperature-depth profiles in the central part of the Netherlands collected over the past 7 years in a large number of piezometers document a regional increase in groundwater temperatures to depths of upto ~100 meters. This rise is congruent to observed increases in air temperature, related to climatic change. For some locations the data collected recently can be compared to similar observations done in the 1970-80s. Our observations show that the magnitude and rate of increase in groundwater temperature strongly vary by location and across depth. In part these differences can be explained by contrasts in land-surface conditions, but our analysis demonstrates that varying groundwater flow conditions also play an important role in explaining the observed patterns. Moreover, we show that an analysis of the transience in the temperature-depth profile can yield quantitative estimate of groundwater flow rates and subsurface hydraulic properties when combined with observations of hydraulic head gradients. We conclude that the current rising trends in groundwater temperature should provide a significant opportunity for the hydrogeological community to quantitatively analyze groundwater flow systems worldwide.

How to cite: Bense, V. and Kurylyk, B.: Drifting groundwater temperatures in the Netherlands: opportunities for hydrogeological analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19219, https://doi.org/10.5194/egusphere-egu24-19219, 2024.

EGU24-19836 | ECS | Posters on site | HS8.2.10

Offshore freshened groundwater emplacement in an evolving siliciclastic margin (Canterbury Bight, New Zealand): A 3D modeling approach 

Ariel Thomas, Daniel Zamrsky, Kamaldeen Omosanya, Mark Person, Joshu Mountjoy, and Aaron Micallef

Offshore freshened groundwater (OFG) represents a globally distributed subsurface resource with potential applications in water management, oil recovery, and environmental studies. Despite growing interest, the understanding of OFG systems, including their geometry, distribution, and emplacement dynamics, remains limited. In this study, we address these gaps by employing a novel 3D geostatistical modeling approach, focusing on the Canterbury Bight, a passive siliciclastic margin with proven OFG resources. Our methodology integrates high-resolution 2D seismic lines and borehole data, allowing us to capture the geological heterogeneity of the passive margin. Unlike traditional static models, our 3D approach considers the evolving stratigraphic architecture over multiple sea-level cycles, offering a more comprehensive understanding of OFG systems. Key findings include the successful incorporation of isostatic shifts and decompaction into our model, resulting in OFG distributions closely resembling those observed in the Canterbury Bight. We emphasize the importance of infilled buried channels and paleo-topographic highs in promoting OFG emplacement, shedding light on distribution patterns not easily explained by current seafloor topography or hydraulic heads. Our study advances the field by demonstrating how a 3D consideration of continental margin evolution significantly influences numerical estimations and improves the characterization of OFG resources. These findings contribute to a better understanding of OFG systems and provide valuable insights for future research and resource management.

How to cite: Thomas, A., Zamrsky, D., Omosanya, K., Person, M., Mountjoy, J., and Micallef, A.: Offshore freshened groundwater emplacement in an evolving siliciclastic margin (Canterbury Bight, New Zealand): A 3D modeling approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19836, https://doi.org/10.5194/egusphere-egu24-19836, 2024.

The traditional territory of the Lù'àn Män Ku Dän (Kluane Lake People) is found along the Saint Elias Mountains in Yukon. It hosts the Burwash Landing community, home of the Kluane First Nation, which is one of eleven self-governing First Nations operating in tripartite with Yukon Government and Canada. Burwash Landing is primarily dependent on diesel for space heating and power generation. Cutting-edge technologies were deployed in the scope of geothermal resource assessment to evaluate the thermal state and properties of the subsurface. Active distributed temperature sensing was conducted with a composite heating and fiber-optic cable installed in the water column of two existing wells with the objective of quantifying the geothermal potential and groundwater flow along available wellbores. Heat injection tests were made in the 220 and 385 m deep wells located on the south and north side of the Denali fault, near a probable releasing bend that is favorable to permeability. Melting glacier water infiltrates in mountains and groundwater flows toward Kluane Lake, which is hypothesized to be a major groundwater discharge zone. The shallower well is at an altitude of 925 masl and intercepted 40 m of quaternary deposits before hitting fractured bedrock while the deeper well is at the valley bottom near the lake (altitude of 795 masl) and entirely drilled in quaternary deposits. Passive temperature monitoring was initially made and revealed a geothermal gradient of 34 ⁰C km-1 and 47 ⁰C km-1 in the shallow south side and deep north side wells. Heat was injected during active tests for 2 and 3 days and thermal recovery was monitored for 6 and 8 days, respectively. Temperature was measured every 25 cm at 4-minute intervals. The infinite line source equation and the superposition principle were used to analyze data and calculate a thermal conductivity profile. Nearly continuous ground thermal properties and temperature profiles were combined to assess the Earth natural heat flux, considering paleoclimate and topographic corrections. Analysis indicated a heat flux above 90 mW m‑2, thought to be favorable for geothermal resource development. Peclet number analysis was undertaken to infer horizontal groundwater flow in permeable horizons. Results are being used to develop a regional groundwater flow and heat transfer model to evaluate temperature at kilometer depth and assess the communities’ geothermal potential. This presentation will illustrate how active temperature sensing can be deployed to reduce geothermal exploration risks, acknowledging Kluane First Nation that allowed us to better understand groundwater flow in this magnificent territory.  

How to cite: Raymond, J., Chapman, F., Klepikova, M., Bour, O., and Soucy Laroche, R.: Active fiber-optic distributed temperature sensing to assess the geothermal potential and groundwater flow over the traditional territory of the Lù'àn Män Ku Dän, Yukon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20169, https://doi.org/10.5194/egusphere-egu24-20169, 2024.

EGU24-20229 | Posters on site | HS8.2.10

Characterization of deep infiltrations in subsurface drained agricultural system 

Hocine Henine, Julien Tournebize, Cedric Chaumont, Arnaud Blanchouin, Agnès Rivière, and Rémi Clément

Subsurface drainage practice is widely used in agriculture to eliminate temporary winter waterlogging of hydromorphic soils. Soil surface saturation is mainly due to the presence of an underlying layer (~1m deep) with a high clay content, considered as semi-impermeable. Generally, deep infiltration under this layer has been neglected in many hydrological studies. However, considering the variations in the ground water table levels, the recharge is mainly due to the deep infiltration. Understanding the dynamic of this infiltration is very important both for the quantitative management of groundwater resources and for the protection of its quality. Indeed, this infiltration can transfer spreading products (fertilizers and pesticides) used in agriculture, mainly the water-soluble molecules.

To understand the dynamic of the deep infiltration, hydrological and geophysical monitoring using ERT (Electrical Resistivity Tomography) method was set up on the drained experimental plot of Boissy le Châtel (Orgeval Observatory, in France). The water balance at the scale of the experimental plot highlighted the contribution of the deep infiltration to the groundwater table rise at the beginning of fall season.

Time-lapse geophysical survey coupled with water content monitoring on a 1.5m vertical profile showed the movement of a rewetting front from the soil surface towards deep layers during this very short transition period, which follows a precipitation event. After this period, during the intense drainage season, the deep infiltration below the drains continues (in the order of 0.12 mm/day compared to 2mm/day for subsurface drained flow) despite the rise of the water table to the surface layer. However, it is difficult to monitor its pathway using the passive ERT method, less sensitive to electrical resistivity variations in the range of soil water content close to saturation.

How to cite: Henine, H., Tournebize, J., Chaumont, C., Blanchouin, A., Rivière, A., and Clément, R.: Characterization of deep infiltrations in subsurface drained agricultural system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20229, https://doi.org/10.5194/egusphere-egu24-20229, 2024.

EGU24-21278 | ECS | Posters on site | HS8.2.10

 Using thermal tracer tests and numerical models to evaluate the layered flow characteristic in a coastal aquifer system  

An-Yi Hsu, Chuen-Fa Ni, Chia-Yu Hsu, and Yu-Huan Chang