The 2001–2004 dome-forming eruption of Shiveluch volcano, Kamchatka: Observation, petrological investigation and numerical modelling

Dirksen, Oleg; Humphreys, Madeleine C. S.; Pletchov, P.; Melnik, Oleg; Demyanchuk, Yu. V.; Sparks, R. S. J.; Mahony, Susan H

doi:10.1016/j.jvolgeores.2006.03.029

Cited by 78 publications

(34 citation statements)

References 45 publications

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“…Data acquisition uncertainty considered as the absolute error. References: (1) Hill et al (1998), (2) INGV (2012), (3) Ripepe et al (2013), (4) Sahetapy-Engel et al (2008), (5) Iguchi (2013), (6) Druitt et al (2002), (7) Ruiz et al (2005), (8) Varley et al (2006), (9) Webb et al (2014), (10) Watt et al (2007), (11) Dirksen et al (2006), (12) Valade et al (2012), (13) Ripepe et al (2008 Unfortunately, this complexity is not encompassed by current classification schemes as they are mostly based on deposit properties, e.g. tephra dispersal, grainsize and/or erupted volume, with the assumption of steady-state conditions (e.g.…”

Section: Introductionmentioning

confidence: 99%

Quantifying unsteadiness and dynamics of pulsatory volcanic activity

Domínguez

Pioli

Bonadonna

et al. 2016

Earth and Planetary Science Letters

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Available online xxxx Editor: T.A. MatherKeywords: explosions pulsatory activity magma viscosity repose interval source dynamics eruptive style Pulsatory eruptions are marked by a sequence of explosions which can be separated by time intervals ranging from a few seconds to several hours. The quantification of the periodicities associated with these eruptions is essential not only for the comprehension of the mechanisms controlling explosivity, but also for classification purposes. We focus on the dynamics of pulsatory activity and quantify unsteadiness based on the distribution of the repose time intervals between single explosive events in relation to magma properties and eruptive styles. A broad range of pulsatory eruption styles are considered, including Strombolian, violent Strombolian and Vulcanian explosions. We find a general relationship between the median of the observed repose times in eruptive sequences and the viscosity of magma given by η ≈ 100 · t median . This relationship applies to the complete range of magma viscosities considered in our study (10 2 to 10 9 Pa s) regardless of the eruption length, eruptive style and associated plume heights, suggesting that viscosity is the main magma property controlling eruption periodicity. Furthermore, the analysis of the explosive sequences in terms of failure time through statistical survival analysis provides further information: dynamics of pulsatory activity can be successfully described in terms of frequency and regularity of the explosions, quantified based on the log-logistic distribution.A linear relationship is identified between the log-logistic parameters, μ and s. This relationship is useful for quantifying differences among eruptive styles from very frequent and regular mafic events (Strombolian activity) to more sporadic and irregular Vulcanian explosions in silicic systems. The time scale controlled by the parameter μ, as a function of the median of the distribution, can be therefore correlated with the viscosity of magmas; while the complexity of the erupting system, including magma rise rate, degassing and fragmentation efficiency, can be also described based on the log-logistic parameter s, which is found to increase from regular mafic systems to highly variable silicic systems. These results suggest that the periodicity of explosions, quantified in terms of the distribution of repose times, can give fundamental information about the system dynamics and change regularly across eruptive styles (i.e., Strombolian to Vulcanian), allowing for direct comparison and quantification of different types of pulsatory activity during these eruptions.

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Section: Introductionmentioning

confidence: 99%

Quantifying unsteadiness and dynamics of pulsatory volcanic activity

Domínguez

Pioli

Bonadonna

et al. 2016

Earth and Planetary Science Letters

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“…), whereas the summit of Young Shiveluch is approximately 2,800 m a.s.l. The activity at Young Shiveluch is composed of multiple extrusive andesite lava domes and thick (up to 100 m) lava flows [5]. Within the Holocene (last 10,000 years), at least 60 explosive eruptions have occurred at this location [6].…”

Section: Shiveluch Volcanomentioning

confidence: 96%

“…The 1964 eruption produced a Plinian eruption column and 0.8 cubic kilometres of juvenile material [7]. The first significant explosion occurred on 7 May 1964, following strong, spasmodic volcanic tremor [5]. The eruption column reached a height of 4.5 km a.s.l.…”

Section: Shiveluch Volcanomentioning

confidence: 99%

Long-Term Volcanic Activity at Shiveluch Volcano: Nine Years of ASTER Spaceborne Thermal Infrared Observations

Carter

Ramsey

2010

Remote Sensing

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Shiveluch (Kamchatka, Russia) is the most active andesitic volcano of the Kuril-Kamchatka arc, typically exhibiting near-continual high-temperature fumarolic activity and periods of exogenous lava dome emplacement punctuated by discrete large explosive eruptions. These eruptions can produce large pyroclastic flow (PF) deposits, which are common on the southern flank of the volcano. Since 2000, six explosive eruptions have occurred that generated ash fall and PF deposits. Over this same time period, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument has been acquiring image-based visible/near infrared (VNIR), short wave infrared (SWIR) and thermal infrared (TIR) data globally, with a particular emphasis on active volcanoes. Shiveluch was selected as an ASTER target of interest early in the mission because of its frequent activity and potential impact to northern Pacific air transportation. The north Pacific ASTER archive was queried for Shiveluch data and we present results from 2000 to 2009 that documents three large PF deposits emplaced on 19 May 2001, 9 May 2004, and 28 February 2005. The long-term archive of infrared data provides an excellent record on the changing activity and eruption state of the volcano.

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“…As additional conceptual adjustment, the loglogistic model (Connor et al, 2003(Connor et al, , 2006Dirksen, 2006) accommodates the inclusion of competing processes, where some factors increase the probability of an eruption with time, whereas others counteract them, decreasing the eruption probability:…”

Section: S Exp (T) = Exp (-T/t 0 )mentioning

confidence: 99%

On the likelihood of future eruptions in the Chilean Southern Volcanic Zone: interpreting the past century’s eruption record based on statistical analyses

Dzierma¹,

Wehrmann²

2012

andgeo

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ABSTRACT.A sequence of 150 explosive eruptions recorded during the past century at the Chilean Southern Volcanic Zone (SVZ) is subjected to statistical time series analysis. The exponential, Weibull, and log-logistic distribution functions are fit to the eruption record, separately for literature-assigned volcanic explosivity indices (VEI) ≥2 and VEI ≥3. Since statistical tests confirm the adequacy of all the fits to describe the data, all models are used to estimate the likelihood of future eruptions. Only small differences are observed between the different distribution functions with regard to the eruption forecast, whereby the log-logistic distribution predicts the lowest probabilities. There is a 50% probability for VEI ≥2 eruptions to occur in the SVZ within less than a year, and 90% probability to occur within the next 2-3 years. For the larger VEI ≥3 eruptions, the 50% probability is reached in 3-4 years, while the 90% level is reached in 9-11 years. RESUMEN. Probabilidades de futuras erupciones en la Zona Volcánica del Sur deChile: interpretación estadística de la serie temporal de erupciones del siglo pasado. Se presenta un análisis estadístico de la serie temporal de 150 erupciones volcánicas explosivas registradas durante el siglo pasado en la Zona Volcánica del Sur de Chile. Se modeló el conjunto de erupciones mediante la distribución exponencial, de Weibull y log-logística, restringiendo el análisis a erupciones de índice de explosividad volcánica (IEV) mayores a 2 y 3, respectivamente. Como los modelos pasan las pruebas estadísticas, los tres modelos se aplican para estimar la probabilidad de erupciones futuras. Se observan solo diferencias menores entre las predicciones mediante los distintos modelos, con la distribución log-logística dando las probabilidades más bajas. Para erupciones de IEV ≥2, la probabilidad de producirse una erupción dentro de un año es más del 50%, creciendo al 90% en 2-3 años. Para erupciones más grandes, de IEV ≥3, el 50% de probabilidad se alcanza dentro de 3-4 años, y el 90% dentro de 9-11 años.

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The 2001–2004 dome-forming eruption of Shiveluch volcano, Kamchatka: Observation, petrological investigation and numerical modelling

Cited by 78 publications

References 45 publications

Quantifying unsteadiness and dynamics of pulsatory volcanic activity

Quantifying unsteadiness and dynamics of pulsatory volcanic activity

Long-Term Volcanic Activity at Shiveluch Volcano: Nine Years of ASTER Spaceborne Thermal Infrared Observations

On the likelihood of future eruptions in the Chilean Southern Volcanic Zone: interpreting the past century’s eruption record based on statistical analyses

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