As magma temperature and composition drift and change, respectively, throughout an eruption, so does its rheology. These changes may span orders of magnitude in magma viscosity and result in orders of magnitude flow velocity changes, as well as transitions in eruptive style. In this study, we present a systematic high precision quantification of the rheological variations that occurred during the 2021 Fagradalsfjall Fires. In the field, we collected a suite of 22 representative samples emplaced between day 2 and 183 of the 2021 eruption. In the laboratory, we measured the melt viscosity of each sample in a concentric cylinder viscometer. Temperatures were initially raised to 1392 °C, and then lowered stepwise to eruptive temperatures as determined through syn-eruptive radiometric measurements. The resulting dataset is analyzed as a time series. An overall trend of viscosity decrease emerges. As the eruption progressed, melt viscosity decreased by 25%, from 40 Pa s to 30 Pa s at a constant temperature of 1200 °C. However, this trend is not monotonous. At least 3 positive spikes in viscosity can be identified, at day 80, 120, and 138 of the eruption. This trend tracks with geochemical variations.
Detailed knowledge of the pre-eruptive time scales associated with magma storage and transport is vital to improve volcanic hazard forecasting in active volcanic regions. However, quantification of the timescales of volcanic processes at mafic volcanic centres in continental intraplate settings is challenging, despite them being a source of significant hazards for human populations and infrastructure due to their limited predictability in space and time. We conducted a detailed petrological study to investigate the time scales of olivine storage and transfer throughout the eruption sequence of Waitomokia Volcanic Complex, a tuff ring and scoria cone complex in the Auckland Volcanic Field. Olivine crystal textures and compositions were determined from stratigraphically-constrained samples of the volcanic complex, from the initial phreatomagmatic phase to the final magmatic phase. Olivine crystals are typically <300 μm in length and characterised by skeletal morphologies, displaying chemical zoning in forsterite (Fo = 100*Mg/[Mg + Fe]; mol%), CaO, MnO and NiO wt% contents. We classified olivine into three major groups based on their Fo core compositions: (1) normally zoned crystals with high Fo content (Fo > 85), (2) crystals with intermediate Fo contents (84–81), and (3) reversely zoned crystals with lower Fo core content (<80). Olivine chemical zoning (diffusion) profiles were modelled in the context of a specific magmatic environment linked with changes in thermodynamic variables during storage (temperature, pressure, and oxygen fugacity). We propose that the normally zoned olivine crystals grew in one magmatic environment (ME1), which subsequently intruded into a more evolved (lower MgO) environment (ME2), where they interacted and were stored for up to 135 days before their eruption. During magma ascent to the surface, a second magma mixing event occurred between ME2 and magma within a third magmatic environment (ME3), forming reversely-zoned olivine crystals yielding notably shorter ascent times of approximately a few days. The rocks from the opening phreatomagmatic phase of the eruption show a larger range in olivine group types compared to the final magmatic phase, where those from the deeper ME1 are more abundant. The short time scales of magma transport obtained in our study, on the order of days to months, should be informative of the warning times that may be encountered between the onset of volcanic unrest and an eruption in the Auckland Volcanic Field.
Monogenetic volcanic fields are present in different geo-tectonic settings (subduction, divergence and intraplate settings) consisting of tens to hundreds of volcanic constructs (cones, maars, fissures, small shields) that are the physical expression of distributed volcanism.
Notably, the spatial distribution of the volcanic constructs in volcanic fields often shows a spatial clustering that is thought to be linked to shallow (i.e., crustal strain, structural inheritance) and deep processes (i.e., magma input, composition and rheology). Noteworthy, the spatial distribution of vents (cones, maars, fissures, small shields) is the final frame of the history of the volcanic field and does not provide information about its time-evolution.
Consequently, when a vent spatial clustering is assessed for a particular volcanic field two questions remain unanswered: i) have the vents always been clustered during the life of the volcanic field? ii) If not, when did the clustering of vents begin? To answer these questions, the spatial distributions of vents along with their morphologic classification have been applied to volcanic fields located in an active tectonic and volcanic area. The northern Main Ethiopian Rift, being its geo-tectonic setting and its geologic evolution well known, is the locale where the time evolution of vent spatial clustering can be investigated. Spatial distribution and morphometric analysis of vents have been applied to three well known monogenetic volcanic fields (Debre Zeyt, Wonji and Kone) in the northern Main Ethiopian Rift. Vent clustering initiated when about 60% of the vents formed within each of the above mentioned fields. The Kone volcanic field show vent clustering since the beginning suggesting that, within a specific tectonic setting, vent clustering is favoured by crustal strain partitioning and associated volcanic activity.
This study presents the development of a multiparametric system that utilizes artificial intelligence techniques to identify and analyze volcanic explosions in near real-time. The study analyzed 1343 explosions recorded between 2019 and 2021, along with seismic, meteorological, and visible image data from the Sabancaya volcano. Deep learning algorithms like the U-Net convolutional neural network were used to segment and measure volcanic plumes in images, while boosting-based machine learning ensembles were used to classify seismic events related to ash plumes. The findings demonstrate that these approaches effectively handle large amounts of data generated during seismic and eruptive crises. The U-Net network achieved precise segmentation of volcanic plumes with over 98% accuracy and the ability to generalize to new data. The CatBoost classifier achieved an average accuracy of 94.5% in classifying seismic events. These approaches enable the real-time estimation of eruptive parameters without human intervention, contributing to the development of early warning systems for volcanic hazards. In conclusion, this study highlights the feasibility of using seismic signals and images to detect and characterize volcanic explosions in near real-time, making a significant contribution to the field of volcanic monitoring.
The Nieve monogenetic volcanic cluster is located in the central–eastern region of the Michoacán–Guanajuato volcanic field, along the Huiramba fault zone, a relay ramp in the Morelia–Acambay fault system produced by oblique north-northwest transtension. This volcanic cluster includes at least 17 middle Pliocene to late Pleistocene lava domes, two small shield volcanoes, and two scoria cones. Between 4 and 3.8 Ma, two effusive eruptions built two small shield volcanoes overlying one another, with a magma volume of 3.93 km3. Between 2.9 Ma and 21.4 ka, 17 lava domes and two scoria cones were emplaced on the flanks of these volcanoes. The entire cluster resulted in a total erupted volume of 17 km3, covering an area of 326 km2 and reaching a thickness of emplaced volcanic material of 1200 m, resulting in a magma eruption rate equivalent to 0.004 km3/ka. All the rocks associated with this cluster are within a relatively restricted range in composition, between 53.9 and 64.2 wt% SiO₂, from andesite enriched in silica to basaltic andesite. The presence of intrusive-rock xenoliths and xenocrysts with dissolution textures reveals that assimilation processes modified the magmas. Based on the regional geological record, we suggest that the establishment of the Nieve volcanic cluster has been controlled by tectonic structures and the basement of the region, which has allowed the chemical evolution of these magma batches that probably had sources in at least two deep reservoirs as reflected by the Nb/Th versus Ta/U ratio.
Geysers are episodic features with variable eruption intervals that range from minutes to years. Although many previous studies on geysers have focused on subsurface properties and processes such as plumbing geometry and recharge process, it is known that erupting fluid column exhibits short-term behaviors such as individual water jets from the vent. In the present study, we conducted observations at Onikobe geyser, NE Japan, a relatively small geyser (geysering well) erupting water up to ∼6–8 m every ∼10 min and observed the erupting fluid column using a thermal infrared camera and an acoustic sensor. We succeed in tracking the water jets by analyzing spatio-temporal temperature map obtained from the thermal infrared observation, which clearly shows the eruptions at Onikobe geyser are not completely stationary but rather a series of intermittent jets with a short period interval of <1 s. We estimate the exit velocity by fitting a ballistic model under the air drag condition of inertial resistance to the jet trajectory. The exit velocity and the averaged gas volume fraction of the erupting fluid are estimated to be ∼4–79 m/s and ∼0.93–0.96, respectively. The exit velocity is ∼30 m/s during the first bursts, then it rapidly increases to ∼50–80 m/s for ∼15 s, and then decreases to ∼20–30 m/s until ∼10 s before the eruption ends. Time series analyses of the thermal infrared and acoustic signals during an eruption indicate harmonic spectra with integer multiple peaks. The fundamental frequency showing ∼4 Hz at the beginning gradually decreases to ∼2 Hz for ∼15 s, keeps almost constant in the following 30 s, and then slightly increases near the end of the eruption. These harmonic spectra may be caused by a resonance mechanism, non-linear fluid motion, and/or subsurface two-phase flow. We discuss the case of a closed organ-pipe resonance in a subsurface crack and attribute the frequency decrease to a decrease in the water level in the crack (an increase in the length of the resonating liquid-vapor column) and/or a decrease in the gas volume fraction of the liquid-vapor mixture in the crack. Since such harmonic characteristics are observed at other geysers, further simultaneous observation of the short-period oscillations on the erupting column proposed in this study with seismic observations of harmonic tremor may provide an improved understanding of geyser subsurface phenomena.
The longevity of lava lakes in open-vent volcanoes reflects a hydraulic connection between the lake and the deep part of the magma plumbing system. Constraining the size of the shallow magmatic system and resolving the rheology of magma filling in the system is essential to evaluate potential hazards like lava flow and other activities. As the lava lake is often perturbed by degassing bursts, rockfall, and even convection, seismic waves radiated from the oscillation of fluid and its mechanical coupling with the surrounding solid walls provide invaluable information on probing system geometry and magma rheology. In this report, I show the first observation of very long-period signals in Nyiragongo volcano, to uncover the sloshing of the world's largest known lava lake and its dynamic interaction with a deep reservoir during the relatively quiet period. The signal is manifested as the ground oscillations with two isolated spectral peaks at ∼15 s and ∼16 s sustaining up to half an hour and a spectral peak at a longer period of ∼76 s. The radiated seismic energy can be well recognized by the stations with distances of <50 km to the lava lake. The traveling time, particle-motion polarization, and deformation inversion suggest that the 15 s' and 16 s' modes are related to two orthogonal horizontal forces at a very shallow depth, likely pointing to the sloshing dynamics of the lava lake. The 76 s' mode is considered as the dynamic coupling between the lake bottom to a deep reservoir at a depth of 8–16 km through a conduit driven by the sloshing. The dynamic modeling of the 76 s' mode points to a deep reservoir storativity of ∼8 m3/Pa and a spherical reservoir with a radius of ∼7.5 km. High-frequency seismic waves before the onset of the 15 s' and 16 s' modes suggest that the signals may be excited by rigorous degassing or rockfall. Variations in the period and quality factor of the modes reflect the changes in the lake/reservoir geometry and magma rheology. This finding may improve our ability to understand the magmatic plumbing system, track magma evolution in Nyiragongo, and further probe the formation of lava lakes in active volcanoes.
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