Global volcanic unrest in the 21st century: An analysis of the first decade

Phillipson, Georgia G; Sobradelo, Rosa; Gottsmann, Joachim

doi:10.1016/j.jvolgeores.2013.08.004

Cited by 148 publications

(137 citation statements)

References 30 publications

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“…Most simply, volcanic unrest is defined as a deviation from background levels of activity towards a level which is a cause for concern over short time scales of hours to days. Volcanic unrest does not necessarily lead to eruption, although this is the most likely outcome, with 64% of 228 volcanoes that have experienced unrest since the year 2000 culminating in eruptive events (Phillipson et al 2013).…”

Section: Volcanic Unrestmentioning

confidence: 99%

Volcano Seismology: Detecting Unrest in Wiggly Lines

Salvage¹,

Karl

Neuberg

2017

Advances in Volcanology

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Seismology is a useful tool to gain a better understanding of volcanic unrest in real time as it unfolds. The generation of seismic signals in a volcanic environment has been linked to a number of different physical processes occurring at depth, including fracturing of the volcanic edifice (producing high frequency seismicity) and movement of magmatic fluids (producing low frequency seismicity). Further classification of seismic signals according to their waveform similarity, in addition to their frequency content, allows greater detail in temporal and spatial changes of seismicity to be detected. At Soufrière Hills volcano, Montserrat, one of the target volcanoes of the VUELCO project, families of similar waveforms provided valuable insight into evaluating the significance of ongoing unrest. In June 1997 over 6000 more events were able to be identified over a 5 day period of interest (22 to 25 June) by using families of seismic events, rather than a standard amplitude-based detection algorithm. In total, 11 families were identified, with the events clustering into a number of swarms, suggesting a repeating and non destructive cyclic source mechanism. Since each family is believed to represent a distinct source location and mechanism, identifying 11 coexisting families R.O. Salvage (&)

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Section: Volcanic Unrestmentioning

confidence: 99%

Volcano Seismology: Detecting Unrest in Wiggly Lines

Salvage¹,

Karl

Neuberg

2017

Advances in Volcanology

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“…In this framework, one of the main challenges of volcano monitoring is the identification and characterisation of the phase defined as "unrest", which consists of a relevant physical or chemical change in the volcanic system with respect to its background behaviour, leading to cause for concern. Unrest can be due to several factors and depends on the local characteristics of each volcanic system, making it very difficult to find general features or patterns (Phillipson et al 2013). Unrest may be followed by volcanic eruptions due to the movement of magma, but can also be associated with other dangerous phenomena: indeed, in addition to magma-related hazards (e.g., tephra fallout, lava flows, ballistics), hydrothermal and tectonic activities, without evidence for "magma-on-the-move", can also lead to dangerous outcomes (i.e., flank collapses, gas emissions, phreatic explosions, lahars).…”

Section: Resumen Extendidomentioning

confidence: 99%

The Need to Quantify Hazard Related to Non-magmatic Unrest: From BET_EF to BET_UNREST

Sandri

Tonini

Rouwet

et al. 2017

Advances in Volcanology

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Most volcanic hazard studies focus on magmatic eruptions and their accompanying phenomena. However, hazardous volcanic events can also occur during non-magmatic unrest, defined as a state of volcanic unrest in which no migration of magma is recognised. Examples include tectonic unrest, and hydrothermal unrest that may lead to phreatic eruptions. Recent events (e.g. Ontake eruption, September 2014) have demonstrated that the successful forecasting of phreatic eruptions is still very difficult. It is therefore of paramount importance to identify indicators that define the state of non-magmatic unrest. Often, this type of unrest is driven by fluids-on-the-move, requiring alternative monitoring setups, beyond the classical seismic-geodetic-geochemical architectures. Here we present a new version of the probabilistic model BET (Bayesian Event Tree), called BET_UNREST, specifically developed to include the forecasting of non-magmatic unrest and related hazards. The structure of BET_UNREST differs from the previous BET_EF (BET for Eruption Forecasting) by adding a dedicated branch to detail non-magmatic unrest outcomes. Probabilities are calculated at each node by merging prior models and past data with new incoming monitoring data, and the results can be updated any time new data has been collected. Monitoring data are weighted through pre-defined thresholds of anomaly, as in BET_EF. The BET_UNREST model is introduced here, together with its software implementation PyBetUnrest, with the aim of creating a user-friendly, open-access, and straightforward tool to support short-term volcanic forecasting (already available on the VHub platform). The BET_UNREST model and PyBetUnrest tool are tested through three case studies in the frame of the EU VUELCO project. Resumen extendidoLa mayoría de los estudios sobre amenazas volcánicas están enfocados en las erupciones magmáticas y fenómenos relacionados. Sin embargo, fenómenos volcánicos peligrosos pueden también ocurrir durante una fase de "unrest" no-magmático, definido por el estado de unrest volcánico en el cual no se reconoce la migración de un magma. Ejemplos de esto son unrest tectónico (capaz de causar preocupación independientemente del resultado posterior) y unrest hidrotermal, que pueden resultar en erupciones freáticas. Eventos recientes (e.g. la erupción de Ontake en septiembre 2014) han demostrado que las erupciones freáticas siguen siendo difícilmente previsibles. Por estas razones, es de extrema importancia identificar señales que permitan definir un estado de unrest no-magmático. Muchas veces, este tipo de unrest es provocado por fluidos en movimiento, y requiere la instalación de un sistema de monitoreo alternativo, más allá de la clásica arquitectura sismo-geodético-química. En este capítulo, presentamos la nueva versión del modelo probabilístico BET (Arbol de Eventos Bayesiano, por sus siglas en inglés), llamado BET_UNREST, específicamente desarrollado para incluir la previsión de unrest no-magmático y sus peligros relacionados. La estructura de BET_...

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“…A phase of precursory geophysical and geochemical signals is expected at least several days before the volcanic activity onset. The most reliable increased likelihood indications of eruption, based on precursors of historical eruptions, are (Sparks, 2003;Phillipson et al, 2013) The locations of precursors, and the measurements of the monitoring networks, will result in a first estimate of the location of any future active vents. The most likely location is on Nea Kameni, or in the shallow sea between Nea and Palea Kameni.…”

Section: Reactivation Scenarios -Plan Proposals For Nscmvcmentioning

confidence: 99%