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 2020
Girina O.A., Gorbach N.V., Davydova V.O., Melnikov D.V., Manevich T.M, Manevich A.G., Demyanchuk Yu.V. The 15 March 2019 Bezymianny Volcano Explosive Eruption and Its Products // Journal of Volcanology and Seismology. 2020. Vol. 14. № 6. P. 394-409. https://doi.org/10.1134/S0742046320060032.
   Annotation
Bezymianny Volcano is one of the most active volcanoes in Kamchatka and in the world. This paper describes the preparation, behavior, products, dynamics, and the geological effect of the March 15, 2019 explosive eruption of the volcano, which was predicted 6.5 h before it began. The sequence of eruptive events was analyzed using data provided by video and satellite-based monitoring of the volcano; the quantitative characteristics for the distribution of pyroclastic deposits were obtained in the information system “Remote Monitoring of Activity of Volcanoes in Kamchatka and the Kurile Islands”. The explosions lifted ash to heights of 15 km above sea level (up to 12 km above the volcano), the eruptive cloud was moving northeastward and east from the volcano, the main ashfall area was 210 400 km2, including 15 000 km2 on land. Apart from tephra, the eruption produced pyroclastic flows and pyroclastic surges covering an area of 30 km2. The total volume of explosive products is estimated as 0.1–0.2 km3. The eruptive rocks are calc-alkaline moderate-K basaltic andesites (SiO2 = 54.84–56.29 wt %), they are the most mafic among all rocks of the current Bezymianny eruption cycle.
Girina O.A., Ladygin V.М. Monogenetic cones of Klyuchevskaya group of volcanoes (Kamchatka, Russia) // Abstract volume of the 8th International Maar Conference. Petropavlovsk-Kamchatsky: IVS FEB RAS. 2020. P. 56-57.
Girina O.A., Melnikov D.V., Manevich A.G., Nuzhdaev A.A., Petrova E.G. The 2019 Activity of Kamchatka and Kurile Islands Volcanoes and Danger to Aviation (oral report) // JpGU - AGU Joint Meeting 2020: Virtual. 12-16 July, 2020, Japan, Tokyo. 2020.
Girina O.A., Melnikov D.V., Manevich A.G., Nuzhdaev A.A., Petrova E.G. The 2019 Activity of Kamchatka and Kurile Islands Volcanoes and Danger to Aviation // Japan Geoscience Union Meeting 2020. Japan, Chiba: JpGU. 2020. № HDS10-P01.
Goltz A.E., Krawczynsky M.J., Gavrilenko M.G, Gorbach N.V., Ruprecht Ph. Evidence for Superhydrous Primitive Arc Magmas from Mafic Enclaves at Shiveluch Volcano, Kamchatka // Contribution to Mineralogy and Petrology. 2020. Vol. 175. P. 115 https://doi.org/10.1007/s00410-020-01746-5.
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Mafic enclaves preserve a record of deep differentiation of primitive magmas in arc settings. We analyze the petrology and geochemistry of mafic enclaves from Shiveluch volcano in the Kamchatka peninsula to determine the differentiation histories of primitive magmas and to estimate their pressures, temperatures, and water contents. Amphibole inclusions in high forsterite olivine suggest that the primitive melt was superhydrous (i.e. >8 wt% H2O) and was fractionating amphibole and olivine early on its liquid line of descent. We find that the hydrous primitive melt had liquidus temperatures of 1062±48°C and crystallized high Mg# amphibole at depths of 23.6-28.8 km and water contents of 10-14 wt% H2O. The major and trace element whole rock chemistry of enclaves and of published analyses of andesites suggest that they are related through fractionation of amphibole-bearing assemblages. Quantitative models fractionating olivine, clinopyroxene, and amphibole reproduce geochemical trends defined by enclaves and andesites in variation diagrams. These models estimate 0.2%-12.2% amphibole fractionated from the melt to reproduce the full range of enclave compositions, which overlaps with estimates of the amount of amphibole fractionated from parental melts based on whole rock dysprosium contents. This contribution extends the published model of shallow processes at Shiveluch to greater depths. It provides evidence that primitive magmas feeding arc volcanoes may be more hydrous than estimated from other methods, and that amphibole is an important early fractionating phase on the liquid line of descent of superhydrous, primitive mantle-derived melts.
Gorbach N.V., Philosofova T.M, Portnyagin M.V. Amphibole record of 1964 plinian and following dome-forming eruptions of Shiveluch volcano, Kamchatka // Journal of Volcanology and Geothermal Research. 2020. Vol. 407. № 107108. doi: 10.1016/j.jvolgeores.2020.107108.
   Annotation
Shiveluch is one of the most active explosive volcanoes worldwide. During the last рlinian eruption in 1964 and the following (1980-current time) dome-forming eruptions Shiveluch has produced andesites and dacites (SiO2~60-64 wt.%) containing variably zoned, compositionally and texturally diverse amphibole phenocrysts. In this work, we attempt to decode the complex zoning of the amphibole crystals in the 55-year series of pumice, dome rocks and mafic enclaves in order to reconstruct the most recent evolution of the volcano plumbing system.
The amphibole zoning in Shiveluch andesites reveals correlation with the style and date of eruption. High-Al cores mantled by low-Al rims in amphiboles from the 1964 plinian eruption record a drastic decrease of pressure and rapid magma ascent from the lower crust to the shallow magma chamber. Typically unzoned and often opacitized low-Al crystals from the early dome-building episodes in 1980-1981 and 1993-1995 reflect magma crystallization in the shallow magma chamber. Complexly zoned amphiboles from andesites erupted in 2000s indicate replenishment of the shallow magma chamber with mafic magma and syn-eruptive mixing processes. Amphibole-based barometric calculations obtained by different approaches indicate that the Shiveluch plumbing system is complex and comprises two, mafic and silicic magma storage zones at ~15-20 km and ~5-6 km depths. We suggest that both episodes of the plinian eruption in 1964 and the extensive dome growth in 2001-2016 were driven by influx of mafic magma in the shallow storage zone beneath Shiveluch. The mafic replenishment likely preceded the 1964 plinian eruption and repeatedly occurred during the period of extensive dome growth in 2001-2016. The variable styles of the recent Shiveluch eruptions may be controlled by the relative volume of the mafic recharges and their thermal and viscosity effects on the efficiency of magma mixing.
Gorbach N.V., Plechova A.A. The lava field in the center of Dzendzur-Zhupanovsky volcanic group, Eastern Kamchatka // Abstract volume of the 8th International Maar Conference, Petropavlovsk-Kamchatsky, Russia, August 24-30, 2020. Petropavlovsk-Kamchatsky: IVS FEB RAS. 2020. P. 58-59.
Khubaeva Olga, Bergal-Kuvikas Olga, Sidorov M.D. Identification of Ruptures and their Interaction with Hydrothermal–Magmatic Systems on Northern Paramushir Isl. (Kuril Islands, Russia): 3D Modeling of Tectonic Fragmentation // Geotecton. 2020. № 54. P. 785-796. doi: 10.1134/S0016852120060072.
Kopylova G.N., Boldina S.V. Groundwater Pressure Changes Due to Magmatic Activation: Case Study of The E-1 Well, Kamchatka Peninsula, Russia // Geothermal Volcanology Workshop 2020. September 03-09, 2020, Petropavlovsk-Kamchatsky, Institute of Volcanology and Seismology. 2020.
Korolev S.P., Urmanov I.P., Kamaev A., Girina O.A. Parametric Methods and Algorithms of Volcano Image Processing / Software Engineering Perspectives in Intelligent Systems. Advances in Intelligent Systems and Computing. Cham: Springer. 2020. Vol. 1295. P. 253-263. https://doi.org/10.1007/978-3-030-63319-6_22.
   Annotation
A key problem of any video volcano surveillance network is an inconsistent quality and information value of the images obtained. To timely analyze the incoming data, they should be pre-filtered. Additionally, due to the continuous network operation and low shooting intervals, an operative visual analysis of the shots stream is quite difficult and requires the application of various computer algorithms. The article considers the parametric algorithms of image analysis developed by the authors for processing the shots of the volcanoes of Kamchatka. They allow automatically filtering the image flow generated by the surveillance network, highlighting those significant shots that will be further analyzed by volcanologists. A retrospective processing of the full image archive with the methods suggested helps to get a data set, labeled with different classes, for future neural network training.