Magmatic Triggering of Earthquakes on Distal Faults as a Potential Medium‐Term Warning Signal From Ruapehu Volcano

Hurst, Arthur F.; Kilgour, Geoff; Hamling, I. J.

doi:10.1029/2018gl080677

Cited by 7 publications

(25 citation statements)

References 32 publications

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“…While most observations indicate changes in the very shallow portions of the subsurface (≤ 1 km of depth), the decorrelation may reflect the injection of fluids at greater depths. For example, stress changes due to the movement of magma have been hypothesized as early precursors 10-5 months prior to eruptions at Ruapehu volcano (Hurst et al 2018;Kilgour et al 2014) (Keats et al 2011), whereas progressive seal formation between 2006 and 2007 might have pressurized the gas column beneath the seal. This period of decorrelation at Whakaari/White Island interestingly coincides with a substantial and sustained CO 2 degassing event that commenced in early 2017.…”

Section: Post-2016 Phreatic Eruption Periodmentioning

confidence: 99%

A quest for unrest in multiparameter observations at Whakaari/White Island volcano, New Zealand 2007–2018

Caudron

Girona

Jolly

et al. 2021

Earth Planets Space

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The Whakaari/White Island volcano, located ~ 50 km off the east coast of the North Island in New Zealand, has experienced sequences of quiescence, unrest, magmatic and phreatic eruptions over the last decades. For the last 15 years, seismic data have been continuously archived providing potential insight into this frequently active volcano. Here we take advantage of this unusually long time series to retrospectively process the seismic data using ambient noise and tremor-based methodologies. We investigate the time (RSAM) and frequency (Power Spectral Density) evolution of the volcanic tremor, then estimate the changes in the shallow subsurface using the Displacement Seismic Amplitude Ratio (DSAR), relative seismic velocity (dv/v) and decorrelation, and the Luni-Seismic Correlation (LSC). By combining our new set of observations with the long-term evolution of earthquakes, deformation, visual observations and geochemistry, we review the activity of Whakaari/White Island between 2007 and the end of 2018. Our analysis reveals the existence of distinct patterns related to the volcano activity with periods of calm followed by cycles of pressurization and eruptions. We finally put these results in the wider context of forecasting phreatic eruptions using continuous seismic records.

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Section: Post-2016 Phreatic Eruption Periodmentioning

confidence: 99%

A quest for unrest in multiparameter observations at Whakaari/White Island volcano, New Zealand 2007–2018

Caudron

Girona

Jolly

et al. 2021

Earth Planets Space

Self Cite

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show abstract

“…Sealing also results in decreased gas flux, as observed in the lead up to the 2007 eruption, as well as a change in lake chemistry as cations that make up alunite/natroalunite seals (e.g., K and to a lesser extent Na) are depleted from the crater lake solution (Christenson et al, 2010). Magma intrusion can also create seismic swarms on the flanks, as well as at distant locations because of local stress changes caused by magma injection (Hurst and McGinty, 1999;Kilgour et al, 2014;Hurst et al, 2018). Girona et al (2018) also found that Ruapehu was sensitive to Sun-Moon gravitational forces during the 3 months prior to the 2007 eruption, suggesting the system was in a critically stressed state, with building overpressure behind a mineralogical seal.…”

Section: Ruapehu Conceptual Modelmentioning

confidence: 99%

Automated Eruption Forecasting at Frequently Active Volcanoes Using Bayesian Networks Learned From Monitoring Data and Expert Elicitation: Application to Mt Ruapehu, Aotearoa, New Zealand

Christophersen

Behr²,

Miller³

2022

Front. Earth Sci.

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Volcano observatory best practice recommends using probabilistic methods to forecast eruptions to account for the complex natural processes leading up to an eruption and communicating the inherent uncertainties in appropriate ways. Bayesian networks (BNs) are an artificial intelligence technology to model complex systems with uncertainties. BNs consist of a graphical presentation of the system that is being modelled and robust statistics to describe the joint probability distribution of all variables. They have been applied successfully in many domains including risk assessment to support decision-making and modelling multiple data streams for eruption forecasting and volcanic hazard and risk assessment. However, they are not routinely or widely employed in volcano observatories yet. BNs provide a flexible framework to incorporate conceptual understanding of a volcano, learn from data when available and incorporate expert elicitation in the absence of data. Here we describe a method to build a BN model to support decision-making. The method is built on the process flow of risk management by the International Organization for Standardization. We have applied the method to develop a BN model to forecast the probability of eruption for Mt Ruapehu, Aotearoa New Zealand in collaboration with the New Zealand volcano monitoring group (VMG). Since 2014, the VMG has regularly estimated the probability of volcanic eruptions at Mt Ruapehu that impact beyond the crater rim. The BN model structure was built with expert elicitation based on the conceptual understanding of Mt Ruapehu and with a focus on making use of the long eruption catalogue and the long-term monitoring data. The model parameterisation was partly done by data learning, complemented by expert elicitation. The retrospective BN model forecasts agree well with the VMG elicitations. The BN model is now implemented as a software tool to automatically calculate daily forecast updates.

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“…In several studies, including recent eruptions at Mt. Ruapehu (1969, 1971, 1977), Mount St. Helens (1980-1986 and Eyjafjallajökull (2010), rapidly increasing volcanic seismicity is often shown to correlate to shorter timescale data and shorter residence times (Saunders et al, 2012;Kilgour et al, 2014;Hurst et al, 2018;Pankhurst et al, 2018).…”

Section: Are the Timescales Related To Eruptive Styles?mentioning

confidence: 99%

Magmatic Processes at La Soufrière de Guadeloupe: Insights From Crystal Studies and Diffusion Timescales for Eruption Onset

et al. 2021

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Signals of volcanic unrest do not usually provide insights into the timing, size and style of future eruptions, but detailed analysis of past eruptions may uncover patterns that can be used to understand future eruptive behavior. Here, we examine basaltic-andesitic to andesitic eruption deposits from La Soufrière de Guadeloupe, covering a range of eruption styles, ages and magnitudes. Our work is timely given unrest at La Soufrière de Guadeloupe has increased over the last 25 years. We constrain the timescales of magmatic processes preceding four eruptions: 1657 Cal. CE (Vulcanian), 1010 Cal. CE (Plinian), ∼341 Cal. CE (Strombolian) and 5680 Cal. BCE (La Soufrière de Guadeloupe’s first known Plinian eruption). Using crystal-specific analyses of diffusion in orthopyroxenes, we calculate the timescale occurring between the last recharge/mixing event in the magma reservoir and the eruption. We use backscattered electron images, coupled with EMPA of the outermost crystal rim, to derive magmatic timescales. We model the timescale populations as random processes whose probability distributions provide expected (“mean”) timescales and the associated standard errors for each eruption. This provides a new statistical method for comparing magmatic timescales between disparate eruptions. From this, we obtain timescales of magma storage at La Soufrière de Guadeloupe ranging from 34.8 ± 0.4 days to 847 ± 0.4 days, with no clear distinction between eruption style/size and timescales observed. Based on these data, magmatic interaction timescales are a poor predictor of eruption style/size. This study shows that magmatic processes prior to eruption can occur on relatively short timescales at La Soufrière de Guadeloupe. Further to this basaltic-andesitic to andesitic volcanoes can rapidly produce large-scale eruptions on short timescales. These relatively short timescales calculated for volcanic processes at this system constitute a critical new data set and warrant an urgency in enhancing modeling and interpretation capabilities for near-real time monitoring data. These integrated efforts will improve early warning, eruption forecasting and crisis response management for different scenarios, as well as planning for long-term risk reduction.

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Magmatic Triggering of Earthquakes on Distal Faults as a Potential Medium‐Term Warning Signal From Ruapehu Volcano

Cited by 7 publications

References 32 publications

A quest for unrest in multiparameter observations at Whakaari/White Island volcano, New Zealand 2007–2018

A quest for unrest in multiparameter observations at Whakaari/White Island volcano, New Zealand 2007–2018

Automated Eruption Forecasting at Frequently Active Volcanoes Using Bayesian Networks Learned From Monitoring Data and Expert Elicitation: Application to Mt Ruapehu, Aotearoa, New Zealand

Magmatic Processes at La Soufrière de Guadeloupe: Insights From Crystal Studies and Diffusion Timescales for Eruption Onset

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