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Author

S. Droznina

Other affiliations: Geophysical Survey
Bio: S. Droznina is an academic researcher from Russian Academy of Sciences. The author has contributed to research in topics: Lava & Seismic tomography. The author has an hindex of 6, co-authored 9 publications receiving 94 citations. Previous affiliations of S. Droznina include Geophysical Survey.

Papers
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Journal ArticleDOI
01 Nov 2014-Geology
TL;DR: In this paper, the authors used P-toS (compressional to shear) converted teleseismic waves to constrain the depth of the crust-mantle transition beneath Klyuchevskoy at ~25 km and to delineate a deeper seismic boundary at ~50 km.
Abstract: Klyuchevskoy volcano in Kamchatka (Russia) is unique in the island arc systems of Earth in having nearly continuous seismic activity beneath it at depths in excess of 20 km. Seismograms from these deep earthquakes carry an unmistakable signature of their tectonic nature. We use P-to-S (compressional to shear) converted teleseismic waves to constrain the depth of the crust-mantle transition beneath Klyuchevskoy at ~25 km, and to delineate a deeper seismic boundary at ~50 km. Earthquakes directly beneath Klyuchevskoy have hypocentral depths of 25–35 km. S-P delays in records of these earthquakes are always larger than delay times of P-toS converted waves originating at the crust-mantle transition and traversing nearly identical paths. Thus, deep seismic activity under Klyuchevskoy is definitely beneath the crust-mantle transition. Compositions of the Klyuchevskoy parental melts (inferred from melt inclusions and the most primitive lava) interpreted using a barometer based on Si activity in melts saturated with orthopyroxene + olivine show that Klyuchevskoy parental melts form at pressures within the range of 13.9 (±2) kbar (at depths of 46 ± 7 km). Together, the estimates of melting depths, the locations of seismic velocity features, and the occurrence of tectonic earthquakes all point to the existence of a subcrustal volume beneath Klyuchevskoy volcano where processes of magma accumulation are vigorous enough to promote brittle failure in mantle rock.

17 citations

Journal ArticleDOI
TL;DR: In this article, the authors compared seismic tomography results with remote sensing and petrology data to identify deep and subaerial manifestations of pre-eruptive processes at Bezymianny volcano in Kamchatka shortly before its violent explosion on December 20, 2017.
Abstract: Strong explosive eruptions of volcanoes throw out mixtures of gases and ash from high-pressure underground reservoirs. Investigating these subsurface reservoirs may help to forecast and characterize an eruption. In this study, we compare seismic tomography results with remote sensing and petrology data to identify deep and subaerial manifestations of pre-eruptive processes at Bezymianny volcano in Kamchatka shortly before its violent explosion on December 20, 2017. Based on camera networks we identify precursory rockfalls, and based on satellite radar data we find pre-eruptive summit inflation. Our seismic network recorded the P and S wave data from over 500 local earthquakes used to invert for a 3D seismic velocity distribution beneath Bezymianny illuminating its eruptive state days before the eruption. The derived tomography model, in conjunction with the presence of the high-temperature-stable SiO2 polymorph Tridymite in juvenile rock samples , allowed us to infer the coexistence of magma and gas reservoirs revealed as anomalies of low (1.5) and high (2.0) Vp/Vs ratios, respectively, located at depths of 2–3 km and only 2 km apart. The reservoirs both control the current eruptive activity: while the magma reservoir is responsible for episodic dome growth and lava flow emplacements, the spatially separated gas reservoir may control short but powerful explosive eruptions of Bezymianny.

14 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, the authors present observations of long-period earthquakes that occurred in 2011-2012 within the Klyuchevskoy volcano group in Kamchatka, Russia.
Abstract: Volcanic long-period earthquakes are attributed to pressure fluctuations that result from unsteady mass transport in the plumbing system of volcanoes Whereas most of the long-period seismicity is located close to the surface, the volcanic deep long-period earthquakes that occur in the lower crust and uppermost mantle reflect the activity in the deep parts of magmatic systems Here, we present observations of long-period earthquakes that occurred in 2011–2012 within the Klyuchevskoy volcano group in Kamchatka, Russia We show two distinct groups of long-period sources: events that occurred just below the active volcanoes, and deep long-period events at depths of ∼30 km in the vicinity of a deep magmatic reservoir We report systematic increases of the long-period seismicity levels prior to volcanic eruptions with the initial activation of the deep long-period sources that reflects pressurization of the deep reservoir and consequent transfer of the activity towards the surface The relatively fast migration of the long-period activity suggests that a hydraulic connection is maintained between deep and shallow magmatic reservoirs The reported observations provide evidence for the pre-eruptive reload of the shallow magmatic reservoirs from depth, and suggest that the deep long-period earthquakes could be used as a reliable early precursor of eruptions Shallow volcanic earthquakes can aid eruption forecasts Analysis of seismicity beneath the Klyuchevskoy volcano group in Russia reveals much deeper magma-induced earthquakes that may serve as an early eruption indicator

84 citations

01 Dec 2016
TL;DR: In this paper, high-precision electron microprobe analyses were obtained on olivine grains from Klyuchevskoy, Shiveluch and Gorely volcanoes in the Kamchatka Arc; Iraz u, Platanar and Barva volcanoes of the Central American Arc; and mid-ocean ridge basalt (MORB) from the Siqueiros Transform.
Abstract: High-precision electron microprobe analyses were obtained on olivine grains from Klyuchevskoy, Shiveluch and Gorely volcanoes in the Kamchatka Arc; Iraz u, Platanar and Barva volcanoes of the Central American Arc; and mid-ocean ridge basalt (MORB) from the Siqueiros Transform. Calcium contents of these subduction zone olivines are lower than those for olivines from modern MORB, Archean komatiite and Hawaii. A role for magmatic H2O is likely for subduction zone olivines, and we have explored the suggestion of earlier workers that it has affected the partitioning of CaO between olivine and silicate melt. We provide a provisional calibration of DCaO Ol/L as a function of magmatic MgO and H2O, based on nominally anhydrous experiments and minimally degassed H2O contents of olivine-hosted melt inclusions. Application of our geohygrometer typically yields 3–4 wt % magmatic H2O at the Kamchatka and Central American arcs for olivines having 1000 ppm Ca, which agrees with H2O maxima from melt inclusion studies; Cerro Negro and Shiveluch volcanoes are exceptions, with about 6% H2O. High-precision electron microprobe analyses with 10–20 lm spatial resolution on some olivine grains from Klyuchevskoy and Shiveluch show a decrease in Ca content from the core centers to the rim contacts, and a sharp increase in Ca in olivine rims. We suggest that the zoning of Ca in olivine from subduction zone lavas may provide the first petrological record of temporal changes that occur during hydration of the mantle wedge and dehydration during ascent, and we predict olivine H2O contents that can be tested by secondary ionization mass spectrometry analysis.

83 citations

Journal ArticleDOI
TL;DR: A new unsupervised machine learning framework that can detect and cluster seismic signals in continuous seismic records is developed and demonstrated the blind detection and recovery of the repeating precursory seismicity that was recorded before the main landslide rupture.
Abstract: The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert-intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed by seismologists. In response to both of these challenges, we develop a new unsupervised machine learning framework for detecting and clustering seismic signals in continuous seismic records. Our approach combines a deep scattering network and a Gaussian mixture model to cluster seismic signal segments and detect novel structures. To illustrate the power of the framework, we analyze seismic data acquired during the June 2017 Nuugaatsiaq, Greenland landslide. We demonstrate the blind detection and recovery of the repeating precursory seismicity that was recorded before the main landslide rupture, which suggests that our approach could lead to more informative forecasting of the seismic activity in seismogenic areas.

81 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe the onset and evolution of a large volcanic event thanks to the analysis of the seismicity from the initiation of the crisis through its first year, compared to the ground deformation observation (GNSS and InSAR) and modelling.
Abstract: On May 10th, 2018, an unprecedented long and intense seismic crisis started offshore, east of Mayotte, the easternmost of the Comoros volcanic islands. The population felt hundreds of events. Over the course of one year, 32 earthquakes with magnitude greater than 5 occurred, including the largest event ever recorded in the Comoros (Mw = 5.9 on May 15th, 2018). Earthquakes are clustered in space and time. Unusual intense long lasting monochromatic very long period events were also registered. From early July 2018, Global Navigation Satellite System stations and Interferometric Synthetic Aperture Radar registered a large drift, testimony of a large offshore deflation. We describe the onset and the evolution of a large magmatic event thanks to the analysis of the seismicity from the initiation of the crisis through its first year, compared to the ground deformation observation (GNSS and InSAR) and modelling. We discriminate and characterise the initial fracturing phase, the phase of magma intrusion and dike propagation from depth to the sub-surface, and the eruptive phase that starts on July 3rd, 2018, around fifty days after the first seismic events. The eruption is not terminated two years after its initiation, with the persistence of an unusual seismicity, whose pattern has been similar since summer 2018, including episodic very low frequency events presenting a harmonic oscillation with a period of ~16 s. From July 2018, the whole Mayotte Island drifted eastward and downward at a slightly increasing rate until reaching a peak in late 2018. At the apex, the mean deformation rate was 224 mm yr-1 eastward and 186 mm yr-1 downward. During 2019, the deformation smoothly decreased and in January 2020, it was less than 20% of its peak value. A deflation model of a magma reservoir buried in a homogenous half space fits well the data. The modelled reservoir is located 45 ± 5 km east of Mayotte, at a depth of 28 ± 3 km and the inferred magma extraction at the apex was ~94 m3 s-1. The introduction of a small secondary source located beneath Mayotte Island at the same depth as the main one improves the fit by 20%. While the rate of the main source drops by a factor of 5 during 2019, the rate of the secondary source remains stable. This might be a clue of the occurrence of relaxation at depth that may continue for some time after the end of the eruption. According to our model, the total volume extracted from the deep reservoir was ~2.65 km3 in January 2020. This is the largest offshore volcanic event ever quantitatively documented. This seismo-volcanic crisis is consistent with the trans-tensional regime along Comoros archipelago.

72 citations