Constraining Spatiotemporal Characteristics of Magma Migration at Piton De La Fournaise Volcano From Pre-eruptive Seismicity

Toward a near real-time magma ascent monitoring by combined fluid inclusion barometry and ongoing seismicity

Fluid inclusion microthermometry on olivines, clinopyroxenes, and amphiboles was used during a volcanic eruption, in combination with real-time seismic data and rapid petrographic observations, for petrological monitoring purposes. By applying this approach to the study of 18 volcanic samples collected during the eruption of Tajogaite volcano on La Palma Island (Canary Islands) in 2021, changes in the magma system were identified over time and space. Magma batches with distinct petrographic and geochemical characteristics emerged from source zones whose depth progressively increased from 27 to 31 kilometers. The rise of magma of deeper origin is attested by fluid inclusions made of N2 and CO, markers of mantle outgassing. Magma accumulation occurred over different durations at depths of 22 to 27 and 4 to 16 kilometers. Time-integrated magma ascent velocities (including ponding times) were estimated at between 0.01 and 0.1 meters per second. This method is cost-effective and quickly identifies changes in the magma system during an eruption, enhancing petrological monitoring procedures.

Unusually high SO2 emissions and plume height from Piton de la Fournaise volcano during the April 2020 eruption

Piton de la Fournaise volcano, La Réunion, France, erupted between the 2 and 6 April 2020, one of a series of eruptive phases which occur typically two or three times per year. Here, we use back trajectory analysis of satellite data from the TROPOMI instrument to determine that gas emissions during the June 2020 eruption were of unusually high intensity and altitude, producing 34.9 ± 17.4 kt of SO₂ and plume heights up to 5 km a.s.l. The early stages of the eruption (2-4 April 2020) were characterised by relatively low SO₂ emission rates despite strong low frequency tremor (LFT); the latter phase followed an increase in intensity and explosivity in the early hours of 5 April 2020. This period included lava fountaining, significantly increased SO₂ emission rates, increased high frequency tremor (HFT) and decreased LFT. Using the PlumeTraj back trajectory analysis toolkit, we found the peak SO₂ emission rate was 284 ± 130 kg/s on the 6 April. The plume altitude peaked at ~ 5 km a.s.l. on 5 April, in the hours following a sudden increase in explosivity, producing one of the tallest eruption columns recorded at Piton de la Fournaise. PlumeTraj allowed us to discriminate each day's SO₂, which otherwise would have led to a mass overestimate due to the plumes remaining visible for more than 24 h. The eruption exhibited a remarkable decoupling and anti-correlation between the intensity of the LFT signal and that of the magma and gas emission rates. LFT intensity peaked during the first phase with low magma and SO₂ emissions, but quickly decreased during the second phase, replaced by unusually strong HFT. We conclude that the observation of strong HFT is associated with higher intensity of eruption, degassing, and greater height of neutral buoyancy of the plume, which may provide an alert to the presence of greater hazards produced by higher intensity eruptive activity. This might be particularly useful when direct visual observation is prevented by meteorological conditions. This eruption shows the importance of combining multiple data sets when monitoring volcanoes. Combining gas and seismic data sets allowed for a much more accurate assessment of the eruption than either could have done alone.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00445-023-01628-1.

22 years of satellite imagery reveal a major destabilization structure at Piton de la Fournaise

Volcanic activity can induce flank failure, sometimes generating large earthquakes and tsunamis. However, the failure structures have never been fully characterized and the failure mechanism is still debated. Magmatic activity is a possible trigger, either through fault slip, which might be induced by dyke intrusions, or through sill intrusions, which might be undergoing coeval normal displacements and slip. At the Piton de la Fournaise volcano, satellite imagery combined with inverse modeling highlights the pathways of 57 magmatic intrusions that took place between 1998 and 2020. We show that a major arcuate dyke intrusion zone is connected at depth to a sill intrusion zone, which becomes a fault zone towards the sea, forming a spoon-shaped structure. Some sills are affected by coeval normal displacement and seaward slip. Overall, the structure is characterized by a continuum of displacement from no slip, to sheared sills and finally pure slip. Repeated intrusions into this spoon-shaped structure could trigger catastrophic collapses.

Seismic tremor reveals active trans-crustal magmatic system beneath Kamchatka volcanoes

The occurrence and the style of volcanic eruptions are largely controlled by the ways in which magma is stored and transported from the mantle to the surface through the crust. Nevertheless, our understanding of the deep roots of volcano-magmatic systems remains very limited. Here, we use the sources of seismovolcanic tremor to delineate the active part of the magmatic system beneath the Klyuchevskoy Volcanic Group in Kamchatka, Russia. The tremor sources are distributed in a wide spatial region over the whole range of crustal depths connecting different volcanoes of the group. The tremor activity is characterized by rapid vertical and lateral migrations explained by fast pressure transients and dynamic permeability. Our results support the conceptual model of extended and highly dynamic trans-crustal magmatic systems.

Time-window into the transcrustal plumbing system dynamics of Dominica (Lesser Antilles)

Dominica, one of the most magmatically active islands of the Lesser Antilles through its four active volcanoes, is likely host under its central part, below Morne Trois Pitons-Micotrin, to a well-established transcrustal mush system. Pre-eruptive spatiotemporal magma dynamics are examined for five, explosive, pumiceous eruptions of this volcano in the last 24 kyrs through a combined Crystal System Analysis and intracrystalline Fe-Mg interdiffusion timescales modelling approaches. Before all eruptions, two magmatic environments of close compositions have interacted. These interactions began ~ 10-30 years prior to the four smaller of these eruptions, with more sustained mixing in the last decade, accelerated in the last 2 years. This contrasts with the largest pumiceous eruption, involving deeper magmas, with magma interaction starting over roughly a century but with various patterns. This suggests a possibility that increasing reactivation signals could be registered at the surface some years before future eruptions, having significant implications for volcanic risk mitigation.

Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano

Volcanic tremor is key to our understanding of active magmatic systems, but due to its complexity, there is still a debate concerning its origins and how it can be used to characterize eruptive dynamics. In this study we leverage machine learning techniques using 6 years of continuous seismic data from the Piton de la Fournaise volcano (La Réunion island) to describe specific patterns of seismic signals recorded during eruptions. These results unveil what we interpret as signals associated with various eruptive dynamics of the volcano, including the effusion of a large volume of lava during the August-October 2015 eruption as well as the closing of the eruptive vent during the September-November 2018 eruption. The machine learning workflow we describe can easily be applied to other active volcanoes, potentially leading to an enhanced understanding of the temporal and spatial evolution of volcanic eruptions.

Combining InSAR and GNSS to Track Magma Transport at Basaltic Volcanoes

The added value of combining InSAR and GNSS data, characterized by good spatial coverage and high temporal resolution, respectively, is evaluated based on a specific event: the propagation of the magma intrusion leading to the 26 May 2016 eruption at Piton de la Fournaise volcano (Reunion Island, France). Surface displacement is a non linear function of the geometry and location of the pressurized source of unrest, so inversions use a random search, based on a neighborhood algorithm, combined with a boundary element modeling method. We first invert InSAR and GNSS data spanning the whole event (propagation phase and eruption) to determine the final geometry of the intrusion. Random search conducted in the inversion results in two best-fit model families with similar data fits. Adding the same time-period GNSS dataset to the inversions does not significantly modify the results. Even when weighting data to provide even contributions, the fit is systematically better for descending than ascending interferograms, which might indicate an eastward flank motion. Then, we invert the GNSS time series in order to derive information on the propagation dynamics, validating our approach using a SAR image acquired during the propagation phase. We show that the GNSS time series can only be used to correctly track the magma propagation when the final intrusion geometry derived from InSAR and GNSS measurements is used as an a priori. A new method to extract part of a mesh, based on the representation of meshes as graphs, better explains the data and better accounts for the opening of the eruptive fissure than a method based on the projection of a circular pressure sources. Finally, we demonstrate that the temporal inversion of GNSS data strongly favors one family of models over an other for the final intrusion, removing the ambiguity inherent in the inversion of InSAR data.