GMPV10.4
Advances in numerical modelling of volcanic hazards

GMPV10.4

EDI
Advances in numerical modelling of volcanic hazards
Co-organized by NH2
Convener: Gaetana Ganci | Co-conveners: Vito ZagoECSECS, Giuseppe Bilotta, Alexis Herault, Annalisa CappelloECSECS
Presentations
| Wed, 25 May, 15:10–16:35 (CEST)
 
Room -2.16

Presentations: Wed, 25 May | Room -2.16

15:10–15:15
15:15–15:25
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EGU22-7109
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ECS
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solicited
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Highlight
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Virtual presentation
Társilo Girona and Corentin Caudron

Linking geophysical and geochemical observables with subsurface processes is crucial to detect volcanic unrest and better anticipate eruptions. One of the most important observables to monitor pre-eruptive volcanic activity is tremor, a more or less persistent, highly periodic, ground vibration recorded near active vents. Tremor is commonly being monitored in near real-time by volcano observatories to anticipate unrest, as it may emerge, or change properties, when subsurface pressure varies. For example, it has been observed that the dominant frequency of tremor may glide towards higher or lower values before eruptions; overtones may appear or disappear; and seismic amplitude may increase or decrease. However, similar variations can be also observed during quiescence and when activity decreases. This leads to the following questions: How does tremor actually reflect the overpressure of the subsurface? Can we infer when and where the pressure beneath active vents increases or decreases by monitoring volcanic tremor? In this work, we present a new data assimilation technique that combines new physics-based models of volcanic tremor with a machine learning-based inversion algorithm to track pressure changes beneath volcanic craters in near-real time. In particular, our inversion algorithm is based on a supervised random forest classifier trained with synthetic data, whereas our physics-based model extends from Girona et al. (2019) and is based on a stop-and-go mechanism, i.e., tremor is assumed to emerge when: (i) gas is supplied randomly to shallow levels of the volcanic plumbing system; (ii) accumulates temporarily beneath permeable caps (e.g., beneath a dome or in a leaky fracture); and (iii) transfers via permeable flow to the surface. Using this machine learning-based data assimilation technique, we find that the recent 2013 unrest phase of Kawah-Ijen volcano (Indonesia) was driven by a pressure increase in the subsurface of a factor 2-to-5. This technique is currently also being applied to unveil the pressure history of the shallow vents of Pavlof and Veniaminof volcanoes (Alaska). 

Girona, T., C. Caudron, C. Huber (2019). Origin of shallow volcanic tremor: the dynamics of gas pockets trapped beneath thin permeable media. J. Geophys. Res., doi: 10.1029/2019JB017482.

How to cite: Girona, T. and Caudron, C.: A new machine learning-based data assimilation technique to detect volcanic unrest from tremor, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7109, https://doi.org/10.5194/egusphere-egu22-7109, 2022.

15:25–15:30
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EGU22-3045
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ECS
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On-site presentation
Séverine Furst, Virginie Pinel, and Francesco Maccaferri

The transport of magma through the crust may sometimes result in volcanic eruptions at the surface, feeding a central conduit, opening fissures on the volcano flank, or at new locations in a volcanic field. Magma travels in the brittle crust by opening its way through the surrounding rock. In addition to the fracturation of the medium, the process of diking is also controlled by the magma flow, fluid-gas phase transitions, and the heat exchange. Representing the propagation of magmatic intrusions using analog and numerical model is essential to understand the physical processes occurring in nature and to mitigate the volcanic hazard linked to the emplacement of magmatic intrusions.

In this context, we performed analog experiments of air and silicon oil injections in a solidified gelatin block. Using three cameras, we monitored the propagation of the oil-filled cracks from the front, side and top views of the tank. The processing of time lapsed pictures enables to access the crack shape (dimension and orientation), trajectory and velocity. This analog modeling technique is routinely used to simulate magmatic dike propagation in the crust. Then, taking advantage of these well constrained experiments, we could validate a novel 2D boundary element model for crack propagation coupling brittle-elastic and fluid-dynamic equations. To do so, we initiate the input and boundary conditions of our numerical simulations, using gelatin and oil parameters from the analog experiments. The outputs of the model include the crack shape, trajectory, and velocity, that is computed according to an energy conservation equation, under the assumption that fluid viscous forces are limiting the crack propagation velocity. Numerical simulations are faced with the observations from our air and oil-filled crack propagation experiments. Eventually, we applied the numerical model to the 1998 magmatic intrusion at Piton de la Fournaise volcano (La Réunion Island), confronting the timing of the of the propagation with the migration of volcano-tectonic events.

How to cite: Furst, S., Pinel, V., and Maccaferri, F.: The analog model, the numerical model and the Piton de la Fournaise : tale of a propagating dike, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3045, https://doi.org/10.5194/egusphere-egu22-3045, 2022.

15:30–15:35
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EGU22-484
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ECS
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Presentation form not yet defined
Francesco Zuccarello

Lava flows are recurring and widespread hazards that affect areas around active volcanoes, having the potential to cause significant social and economic loss. In the last decades, physics-based models of lava flows have been proven effective and powerful tools to forecast and assess the hazard posed by effusive events. These models require different input parameters, such as the physical properties of the fluid (e.g., melt compositions, water content, rheological law, thermal properties) and the topography of the terrain. A critical parameter in physical-mathematical modelling is the effusion rate, i.e. the rate at which lava is discharged. Lava effusion rate is variable in time, strongly controlling the emplacement and run-out distance of lava flows. Nevertheless, both for assessing long-term hazards and for monitoring efforts during on-going eruptions, effusion rate is assumed to be constant or to have a bell-shaped time-dependent behavior. Here we present an analysis of the time-averaged discharge rates (TADRs, i.e. the effusion rate averaged over given periods) estimated for recent flank eruptions at Mt. Etna volcano (Italy) in order to define a possible generalized effusion rate trend to be used for the physical modeling of lava flows. The temporal series of TADRs, derived from field measurements and satellite thermal imagery, were normalized in order to obtain homogeneous curves in duration and sampling times, reducing redundancies and improving data consistency. Our analysis indicates that most of the effusion rate curves for flank eruptions of Etna are characterized by a fast waxing phase with the peak occurring between the 0.5 and 29% of the total eruption time, followed by a progressive decrease in the waning phase. By using the median values associated to the occurrence of effusion peaks and to the slope variations of descending curves in the waning phase, we estimated an averaged curve that was used to run numerical tests by means of the physics-based GPUFLOW model. Different tests were performed considering how the “characteristic effusion rate curve” could impact single vent scenarios, as well as on short- and long-term hazard maps. Statistics on the final emplacements revealed variations up to 20%, confirming the key role of the effusion rate in controlling the development of lava flow fields.

How to cite: Zuccarello, F.: On the impact of the effusion rate trend for the assessment of lava flow hazards, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-484, https://doi.org/10.5194/egusphere-egu22-484, 2022.

15:35–15:40
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EGU22-9907
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Virtual presentation
Cristina Proietti, Massimo Cantarero, and Emanuela De Beni

Etna volcano has four summit craters that are characterized by periodic strombolian and lava fountaining episodes, often associated with lava flows. In the last years, the most active was the South East Crater that on 2021 produced more than fifty paroxysms that gave rise to lava flows rapidly propagating towards East, South, and South-West. Etna summit area is visited by thousands of tourists, especially in the summertime, thus it is important to evaluate the hazard related to lava flow emplacement. For this reason, we were urged to timely map the lava flows emplaced during each paroxysm whose frequency was as high as two events in 24 hours. This task has been accomplished through the integration of different remote sensing techniques, based on data availability and weather conditions. Several satellite images (Sentinel-2 MSI, Aster, Ecostress, Skysat, Landsat-8 OLI and TIRS) allowed us to map the lava flow field at spatial resolutions from 0.7 to 90 meters. Unoccupied Aerial System (UAS) surveys also allowed to acquire visible and thermal images, with high-spatial resolution, of the lava flows. Finally, thermal images acquired from the permanent network of cameras, managed by the Istituto Nazionale di Geofisica e Vulcanologia, were re-projected into the topography at 5-meter spatial resolution. The various remote sensing data enable the mapping of the lava flows and compiling a geodatabase that registers the main geometrical parameters (e.g. length, area, average thickness). The joint exploitation of remote-sensing data acquired through multi-sensors enabled, for the first time on Etna, to timely and accurately characterize frequently occurred effusive events.

How to cite: Proietti, C., Cantarero, M., and De Beni, E.: Timely mapping and quantification of the 2021 Etna lava flows through the exploitation of multi-sensors remote-sensing data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9907, https://doi.org/10.5194/egusphere-egu22-9907, 2022.

15:40–15:45
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EGU22-10168
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Presentation form not yet defined
Giuseppe Bilotta, Gaetana Ganci, and Annalisa Cappello

Modelling and simulation of geophysical flows are crucial to the forecasting of the propagation extent and the assessment of the related hazards. Here we introduce a new physics-based model called GPUFLOW, which was born from our twenty years of experience in Fluid Dynamics (CFD) modelling of geophysical flows. GPUFLOW features an improved physical model for the thermal and rheological evolution of lava flows, support for debris flows without thermal dependency and a parallel implementation on graphic processing units (GPUs). We estimate the influence that the GPUFLOW input parameters have on flow emplacement through different synthetic test cases and demonstrate its reliability through the 2014 pyroclastic flow and the 2018 eruption occurred at Etna volcano. This work was supported by the INGV project Pianeta Dinamico funded by MIUR (“Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese,” legge 145/2018), Tema 8 – PANACEA 2021.

 

How to cite: Bilotta, G., Ganci, G., and Cappello, A.: Modelling of geophysical flows through GPUFLOW, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10168, https://doi.org/10.5194/egusphere-egu22-10168, 2022.

15:45–15:50
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EGU22-9221
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ECS
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Virtual presentation
Luigi Mereu, Simona Scollo, Costanza Bonadonna, Franck Donnadieu, Valentin Freret Lorgeril, and Frank Silvio Marzano

Mt. Etna, in Italy, is one of the most active volcanoes in the world, whose explosive eruptions represent a serious threat to the nearby populations and producing various dangerous effects mainly on properties, crops and transports. During explosive eruptions, the real-time estimation of the mass eruption rate (MER) is challenging although crucial to mitigate the impact due to the erupted tephra. Microwave radar techniques at L- and/or X-bands, as well as thermal infrared imagery, can provide a reliable MER estimation in real-time. Using the Etna lava fountains of 3–5 December 2015 as test cases, we investigate the differences among different approaches to estimate the MER: i) the mass continuity approach (MCA); ii) the top plume approach (TPA); and iii) the surface flux approach (SFA). We also introduce a new approach, called the near source approach (NSA) that is based on the X-band radar data alone. Finally, we extend the volcanic advanced radar retrieval methodology to estimate for the first time the gas-tephra mixture density near the volcanic crater. The analysis allows us to identify the optimal real-time MER retrieval strategy, showing the potential and limitations of each method. We show that the MCA method, entirely based on the X-band radar data processing, is the best strategy with a percentage uncertainty in the MER estimation of 22.3%, whereas other approaches exhibit a higher uncertainty (26.4% for NSA, 30% for TPA, and 31.6% for SFA). We investigate and optimize the different strategies for the volume eruption rate (VER), total erupted mass and volume estimations (TEM and TEV, respectively) including their uncertainties. The MER retrieval methods, described and applied in this work, showed promising results that can be exploited to improve the tephra dispersal and fallout forecasts at Etna in near real-time. Further work might be devoted to explore new techniques, using low-cost sensors for the MER estimation and employing microwave radars as validation tools.

How to cite: Mereu, L., Scollo, S., Bonadonna, C., Donnadieu, F., Freret Lorgeril, V., and Marzano, F. S.: Ground-based remote sensing and uncertainty analysis of the mass eruption rate associated with the 3-5 December 2015 paroxysm of Mt.Etna, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9221, https://doi.org/10.5194/egusphere-egu22-9221, 2022.

15:50–15:55
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EGU22-3035
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ECS
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On-site presentation
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Frank Millward and Chris Johnson

Explosive volcanic eruptions release a rising plume of ash and gas into the atmosphere. Once such a plume reaches its altitude of neutral buoyancy, it spreads into an umbrella cloud, which is then distorted by the surrounding meteorological wind. At least four processes are important in governing the complex evolution of the umbrella cloud: buoyancy-driven spreading, turbulent skin drag, inertial drag at the advancing edge of the cloud, and the momentum of the cloud. Existing models have frequently assumed that just one of these drag forces is dominant. Here we present a model for the spread of an umbrella cloud in a crosswind, which is based on time-dependent partial differential equations that include all four key processes. The model confirms that spread far downstream is driven by a balance between turbulent drag and buoyancy. By including all four processes the transient behaviour of the cloud that occurs upwind of the drag-buoyancy regime can also be investigated. Our findings illustrate the fundamental differences between wind-blown umbrella clouds and those derived from an axisymmetric umbrella cloud approximation, and the consequent importance of accurate physical descriptions of the interaction between wind and umbrella clouds in volcanic ash dispersal models.

How to cite: Millward, F. and Johnson, C.: A unified model for wind-blown volcanic umbrella clouds, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3035, https://doi.org/10.5194/egusphere-egu22-3035, 2022.

15:55–16:00
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EGU22-4798
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ECS
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Virtual presentation
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Michel Bänsch and Jörn Behrens

Since the Eyjafjallajökull eruption in 2010, the volcanic modelling community has been focused on improving the prediction of ash dispersion and simulation of eruptive columns.
While many new and powerful numerical methods have been developed for Computational Fluid Dynamics (CFD) and Atmospheric Modelling, very few have been integrated into models for volcanic eruptions.
Conventional models usually lack high spatial resolution if the distance to the volcanic vent is large and (mostly) cannot represent shocks. Both of these problems need to be dealt with by using new CFD techniques.

In contrast to algorithms which are currently available in the volcanic modelling community,
this work focuses on implementing different spatial discretization methods - Discontinuous Galerkin Methods (DGM) instead of Finite Volume Methods or Finite Difference Methods - while also using Adaptive Mesh Refining (AMR) techniques.
This combination eliminates both resolution problems (due to AMR) and the lack of shock capturing (due to DGM).
Gas dynamics are described by either using the Euler or Navier-Stokes Equations while the AMR utilizes h-adaptivity with a suitable error estimation. 
Time-integration is performed with (explicit) Runge-Kutta (SSPRK or LSRK) methods.

We will present results that show the ability to model eruptions and present challenges that arise with both CFD and AMR approaches in volcanic modelling.

How to cite: Bänsch, M. and Behrens, J.: Adaptive volcanic modelling using Discontinuous Galerkin Methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4798, https://doi.org/10.5194/egusphere-egu22-4798, 2022.

16:00–16:05
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EGU22-11384
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ECS
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Presentation form not yet defined
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Laura Calabrò, Tomaso Esposti Ongaro, Mattia de' Michieli Vitturi, and Guido Giordano

Pyroclastic currents (PCs) are composed of hot mixtures of gas and pyroclastic particles, which travel at moderate to very high speed (tens to hundreds of m/s), under the effect of their density contrast with the surrounding atmosphere. They can be flowing over obstacles with ease but their pathway is often controlled by the topography they flow over. These characteristics make them one of the most dangerous and inaccessible to direct study, natural phenomena. For this reason, the use of numerical modeling could be one of the most useful tools to provide key quantitative information about their internal dynamics. In this study, we used the available data about Pozzolane Rosse ignimbrite (Colli Albani, Italy) caldera-forming, - 460 ka, 63 km3 DRE - to model source and flow dynamics with a depth-averaged model for inertial PCs. Numerical simulations allowed us to test the effects of 1) atmospheric air entrainment, by varying the Richardson number (), 2) the initial flow thickness, 3) initial flow velocity, 4) grain-size distribution, and 5) mixture density on PCs runout and thickness decay pattern. Model validation was performed by comparing i) model runout and field data; ii) the thickness of the deposit compared to the thickness of the model output with the distance; iii) the mass fractions of the different grain size classes for the actual deposit compared to the model output. Several simulations were carried out considering i) the influence of parameters h and v; ii) the density; iii) the temperature and iv) the topography. The results allowed us to understand and quantify the first-order variables that characterize flow propagation (runout) and thickness decay pattern, indicating that the depth-averaged model may be suitable to represent the dynamics of large PCs, such as those of the Pozzolane Rosse.

How to cite: Calabrò, L., Esposti Ongaro, T., de' Michieli Vitturi, M., and Giordano, G.: Reconstructing Pyroclastic Currents’ Source and Flow Parameters from Deposit Characteristics and Numerical Modelling: The Pozzolane Rosse Ignimbrite case study (Colli Albani, Italy), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11384, https://doi.org/10.5194/egusphere-egu22-11384, 2022.

16:05–16:10
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EGU22-9587
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ECS
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On-site presentation
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Shungo Tonoyama and Takashi Nakamura

Pyroclastic currents, which composed by ash particles and small pyroclasts, is one of destructive ejecta produced during volcanic eruptions. The behavior of this hazardous fluid is still not revealed yet. In particular, dilute fluids called pyroclastic surge can expand and diffuse by entrainment of ambient air and has a possibility of danger. Due to lack of understanding about pyroclastic surge, current disaster prevention measures are inadequate in estimating the run-out distance and range. In recent years, several experiments on the pyroclastic flows have been conducted; however, to reproduce both high temperature and high velocity is quite difficult. Therefore, the numerical calculation is considered as the powerful tool to analyze their flow structures. Here, we applied the numerical model of a pyroclastic surge to the experimental investigation at Smithsonian Institute in order to examine the air entrainment. Our model is based on solving Navier-Stokes equation by finite-difference scheme, CIP-CUP method, and Smagorinsky model applied to turbulent mixing. In this study, pyroclastic surge is treated as a dilute turbulent suspension, and gas and particles are assumed to be well-mixed or have certain settlement velocity. We applied the 2D and 3D model to experiments and investigated the effects of turbulence and settlement. As a result of a series of simulations, we can reproduce the generation of head and wake and it has a strong relationship with mesh size. The large mesh cannot capture the wake at rear of head. Furthermore, the temperature change process by turbulent mixing is confirmed. The experimental data at PELE (the pyroclastic flow Eruption Large-scale Experiment) is also compared and discussed about the change in flow height.

How to cite: Tonoyama, S. and Nakamura, T.: Numerical simulation of air entrainment by three dimensional pyroclastic surge flow model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9587, https://doi.org/10.5194/egusphere-egu22-9587, 2022.

16:10–16:15
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EGU22-9991
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Presentation form not yet defined
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Gaetana Ganci, Giuseppe Bilotta, Sonia Calvari, Annalisa Cappello, Luca D'Auria, Pedro Hernández, Nemesio M. Pérez, and Letizia Spampinato

On 19 September 2021, after about 50 years of quiescence, a new eruption started at Cumbre Vieja volcano (Canarias, Spain). The onset was preceded by a series of seismic swarms, the last one of which occurred on 11 September 2021. A system of eruptive fissures opened and multiple vents produced lava fountains, sustained ash columns, and lava flows that travelled over 5 km W to the sea, damaging hundreds of properties along their path. The eruption forced the evacuation of over 7,000 people and destroyed nearly 3,000 buildings, ending on 13 December, after 85 days.

We here detail the different phases of the eruption and describe and discuss the lava flow field structures and emplacement dynamics by using ground- and air-based thermal camera data as well as using multispectral satellite images. Indeed, the high temporal resolution of SEVIRI images - i.e. an image every 15 minutes - allowed tracking the lava flow development and provided an estimation of the effusion rate. Sentinel 2, Landsat 8 and PlanetScope images enabled mapping the active areas of the lava field and, thus to clearly depict the formation of lava tube systems promoting lava flow lengthening to the sea. Moreover, the satellite-derived data were used as input to the GPUFLOW model to produce near real time, short-term lava flow hazard maps.

How to cite: Ganci, G., Bilotta, G., Calvari, S., Cappello, A., D'Auria, L., Hernández, P., Pérez, N. M., and Spampinato, L.: Volcano hazard monitoring using remote sensing techniques during the Cumbre Vieja volcano 2021 eruptive crisis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9991, https://doi.org/10.5194/egusphere-egu22-9991, 2022.

16:15–16:20
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EGU22-12586
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ECS
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Presentation form not yet defined
Charles Balagizi, Gaetana Ganci, Elisa Trasatti, Cristiano Tolomei, and Lisa Beccaro

The 2021 Nyiragongo (DR Congo) eruption started on 22 May 2021, nineteen years after the last effusive eruption of 2002. The lava flows erupted from three vents, one East of the summit area and two along the southern slope, and produced two lava flows, the western of which inundated part of the Goma city, causing serious damages to population, buildings and infrastructures and stopped only at ~1 km from the Goma international Airport. Here we process a variety of satellite imagery, including visible, infrared and radar data, mapping the pre-eruptive phase, the evolution of the eruption and the post-eruptive phase. Most of the remote sensing data were acquired in the framework of Virunga Geohazards Supersite, which is part of the GEO-GSNL (Geohazard Supersite and National Laboratories) initiative. In particular we analysed: (i) Sentinel 1 (European Space Agency, ESA) and (ii) COSMOSkymed, CSK (Italian Space Agency, ASI) data providing displacement time-series and eruptive source model; (iii) Visible Infrared Imaging Radiometer Suite, VIIRS ( NASA/NOAA Suomi National Polar-orbiting Partnership) data at 375 m spatial resolution to provide thermal maps; (iv) different Pleiades (AIRBUS) triplets, at 0.5 m spatial resolution, to update the topography of the volcano.

Pre-eruptive 2020-2021 InSAR (Interferometric Synthetic Aperture Radar) analysis from Sentinel-1 and high resolution CSK data show a deflation of the summit area of Nyiragongo and Nyamuragira volcanoes amounting to few cm/yr Line of Sight (LOS). The syn-eruptive InSAR data evidence surface deformation of 70 cm LOS located South of Nyiragongo, in a wide area including the city of Goma and Lake Kivu. Modelling of the InSAR syn-eruptive data show a sub-vertical dike located from South Nyiragongo reaching Lake Kivu. The top depth is 1.5 km from the surface, and the volume variation is slightly less than 0.2 km3. Post-eruptive Sentinel-1 and CSK data showed deflation of the summit area of Nyiragongo, negative LOS surface deformation at Goma and lava cooling.

VIIRS data allowed us to see an increase in the size and temperature of the lava lake a few months before the eruption, and provided a first image of the erupted lava flow on 22 May 2021 at 22:47 GMT. Thanks to Pleiades imagery we could retrieve the lava flow area and by using a pre-eruptive topography we also provided an estimation of the erupted volumes.

Results highlight how the synergic use of multi-source, multi-temporal satellite imagery, along with innovative and automatic processing techniques, may be adopted for real-time hazard estimates in an operational environment especially in remote volcanoes with limited terrestrial networks.

This contribution is supported by the GEO-GSNL initiative and the H2020 Reliance project (grant agreement 101017501).

How to cite: Balagizi, C., Ganci, G., Trasatti, E., Tolomei, C., and Beccaro, L.: The 2021 Nyiragongo (DR Congo) eruptive crisis monitored by multi-sensor satellite remote sensing data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12586, https://doi.org/10.5194/egusphere-egu22-12586, 2022.

16:20–16:25
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EGU22-11576
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Virtual presentation
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Iole Serena Diliberto, Sophie Pailot Bonnètat, Andrew J.L. Harris, Philipson Bani, Victoria Rafflin, Guillame Boudoire, Alessandro Gattuso, Fausto Grassa, Benjamin Van Wyk de Vries, Giuseppe Bilotta, Annalisa Cappello, and Gaetana Ganci

By 2021, Vulcano, Aeolian Islands (Italy), experienced a dramatic increase in different monitoring parameters, including microseismicity, ground deformation, fumarole temperatures, and volatile emissions of steam, carbon, and sulfur dioxide. The volcanic unrest was noticeable in September 2021, causing the Civil Protection to raise the alert level from green to yellow on October 1st. Here we present a number of ground- and satellite-based thermal methodologies used to detect and characterize the change of state of the La Fossa hydrothermal system between January 2021 and January 2022. We analyzed: (i) the temperature and (ii) CO2 flux data acquired at 15 cm‐depth on a N-S profile N-S and grid in the geothermally heated area during three field surveys in June, September 2021 and January 2022; (iii) a time series acquired with a radiometer including temperatures and number of vents inside the fumarole field from 1994 to 2022; (v) thermal images acquired by a hand-held thermal camera during four field surveys in March, June and September 2021, plus January 2022; (v) nighttime multi-spectral satellite images acquired by ASTER, ECOSTRESS and VIIRS sensors from January 2021 to January 2022. Satellite images show a clear increase in the radiant heat flux/land surface temperature as well as in the number of thermally anomalous pixels, this thermal anomaly has been observed from mid-September. However, by combining ground and satellite techniques the starting point of this change can be tracked thermally from at least June 2021. Our experience suggests that the methods, essentially based on the thermal monitoring, could be used to herald upcoming crises. This method has been applied on a close conduit volcano and highlighted changes of trend in the solfataric release. Further tests, aiming to reduce (filter or define) the external effects on the land surface temperature, and to define the correlations with the long term monitoring data (either ground-based or by remote sensing) in this area, would assess a standardized methodology to monitoring the subtle, but diffuse fluid release. The assessed methodology could then be applied to other active hydrothermal systems, to herald thermal changes on the surface, related to the increasing energy released from a deep source.

How to cite: Diliberto, I. S., Pailot Bonnètat, S., Harris, A. J. L., Bani, P., Rafflin, V., Boudoire, G., Gattuso, A., Grassa, F., Van Wyk de Vries, B., Bilotta, G., Cappello, A., and Ganci, G.: The 2021 unrest at Vulcano: insights from ground-based and satellites observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11576, https://doi.org/10.5194/egusphere-egu22-11576, 2022.

16:25–16:30
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EGU22-13227
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ECS
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On-site presentation
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Eric Newland, Nicola Mingotti, and Andrew Woods
Deposits from explosive submarine eruptions have been found in several deep-sea locations, with both flow and fall deposits of small clasts, 1-3mm, extending 1000’s m over the seafloor. Here we propose that after mixing with seawater, the erupting fragmented material typically forms a negatively buoyant fountain. To explore their dynamics, we present a simple numerical model to describe the evolution of the eruption column and series of laboratory experiments of turbulent particle-laden fountains rising through a stratified water column.  Our experiments show that at the top of the fountain, some of the erupted material collapses to the seafloor to form a pyroclastic flow. However, some of the buoyant water in the fountain may separate from the top of the fountain, to form a buoyant plume which can carry particles higher into the water column. Eventually this mixture will be arrested by the ambient stratification and intrudes into the water column. Subsequently, the particles settle from this intrusion to form a fall-type deposit. Quantification of the controls on the concurrent fall and flow deposits, and comparison with field observations, including from the 2012 eruption of Havre Volcano in the South Pacific, open the way to new understanding of submarine eruptions.

How to cite: Newland, E., Mingotti, N., and Woods, A.: Dynamics of deep-submarine explosive eruptions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13227, https://doi.org/10.5194/egusphere-egu22-13227, 2022.

16:30–16:35
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EGU22-12630
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Highlight
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Virtual presentation
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Alexander Garcia, Laura Sandri, Jacopo Selva, Raffaele Azzaro, Giuseppe Bilotta, Stefano Branca, Mauro Coltelli, Salvatore D'Amico, Tomaso Esposti Ongaro, Gaetana Ganci, Luigi Mereu, Fabrizio Meroni, Vera Pessina, Cristina Proietti, Simona Scollo, and Annalisa Cappello

The effects of volcanic hazards can be quantified by applying new methods to provide support for rational decision-making. Mt Etna is one the most active volcanoes in the world, producing both effusive and explosive eruptions together with a very intense seismic activity, which significantly affect the territory and human society. We present the preliminary results obtained in the framework of the PANACEA project (INGV’s project “Pianeta Dinamico”, funded by the Italian Ministero dell’Università e la Ricerca, MUR) regarding the multi-hazard assessment around Mt Etna. These include: (i) the production of an updated spatio-temporal probability map of vent opening at Etna, using a procedure exploiting different Kernel functions (e.g. the exponential, Cauchy, and Gaussian functions), and testing volcanic deformation patterns to explore possible dynamic, structural conditioning on the vent opening process; (ii) the identification of a set of cascading effects scenarios that account for volcanic phenomena (i.e., volcanic unrest, seismicity, volcanic explosions, volcanic effusive events, lava flows, tephra/ballistic fall, and PDC), as well as other external hazards potentially linked in such chains (e.g., flooding, forest fires, etc.); and (iii) the identification of scenarios involving systemic impacts (e.g., impacts on the functionality or connectivity of networks).

How to cite: Garcia, A., Sandri, L., Selva, J., Azzaro, R., Bilotta, G., Branca, S., Coltelli, M., D'Amico, S., Esposti Ongaro, T., Ganci, G., Mereu, L., Meroni, F., Pessina, V., Proietti, C., Scollo, S., and Cappello, A.: Multi-hazard assessment at Mt. Etna volcano, Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12630, https://doi.org/10.5194/egusphere-egu22-12630, 2022.