ORCID Profile
0000-0001-8499-0352
Current Organisations
GNS Science
,
GNS Science Ltd
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Publisher: American Geophysical Union (AGU)
Date: 12-2019
DOI: 10.1029/2019JB018681
Abstract: The Laguna del Maule volcanic field is a large rhyolitic magmatic system in the Chilean Andes, which has exhibited frequent eruptions during the past 20 ka. Rapid surface uplift ( cm/year) has been observed since 2007 accompanied by localized earthquake swarms and microgravity changes, indicating the inflating magma reservoir may interact with a preexisting weak zone (i.e., Troncoso fault). In this investigation, we model the magma reservoir by data assimilation with Interferometric Synthetic Aperture Radar data. The reservoir geometry is comparable to the magma body inferred by seismic tomography, magnetotelluric, and gravity studies. The models also suggest that a weak zone, which has little effect on surface displacement, is important as a fluid transport channel to promote earthquakes and microgravity changes. In particular, concentrated dilatancy within the weak zone facilitates the microfracture formation during reservoir inflation. High‐pressure fluid can inject into the weak zone from the magma reservoir to trigger earthquakes and further migrate upward to create positive gravity changes by occupying unsaturated storages. The pore pressure will then decrease, halting the seismicity swarm until the next cycle. This “hydrofracturing” process may release some accumulated stress along the magma reservoir delaying an eventual eruption in turn. Besides, the resultant models are propagated forward in time to evaluate potential stress trajectories for future unrest.
Publisher: Elsevier BV
Date: 06-2016
Publisher: American Geophysical Union (AGU)
Date: 04-2017
DOI: 10.1002/2017JB014048
Publisher: Elsevier BV
Date: 08-2020
Publisher: American Association for the Advancement of Science (AAAS)
Date: 18-06-2021
Abstract: Insights into the 9 December 2019 eruption of Whakaari/White Island from analysis of TROPOMI SO 2 imagery.
Publisher: Geological Society of London
Date: 1999
Publisher: American Geophysical Union (AGU)
Date: 02-2020
DOI: 10.1029/2019JB018247
Publisher: Informa UK Limited
Date: 22-02-2021
Publisher: Springer Science and Business Media LLC
Date: 08-11-2014
Publisher: Springer Science and Business Media LLC
Date: 04-2018
Publisher: Elsevier BV
Date: 11-2014
Publisher: Wiley
Date: 13-08-2020
Publisher: Geological Society of America
Date: 12-2014
DOI: 10.1130/GSATG216A.1
Publisher: Springer Science and Business Media LLC
Date: 20-03-2011
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 12-2022
Publisher: American Geophysical Union (AGU)
Date: 03-2019
DOI: 10.1029/2018JB016485
Publisher: Informa UK Limited
Date: 09-2001
DOI: 10.1071/EG01346
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 02-2017
Publisher: Frontiers Media SA
Date: 18-07-2022
DOI: 10.3389/FEART.2022.905965
Abstract: 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.
Publisher: American Geophysical Union (AGU)
Date: 08-2020
DOI: 10.1029/2019JB019329
Abstract: The Laguna del Maule volcanic field (LdMVF) in Chile, a rapidly inflating silicic volcanic system without historical eruption, is intersected by active regional faults. The LdMVF provides an opportunity to observe how faults influence, accommodate, or are driven by an actively deforming large silicic system. Here we use Compressed High Intensity Radar Pulse (CHIRP) acoustic reflection data to map the fault network in sediments captured within the eponymous lake at the LdMVF and combine our fault maps with the volcanic history, earthquake locations, focal mechanisms, and lacustrine magnetic data to interpret how faults and magmatism interact. Our seismic data image dominantly dip‐slip faults forming grabens within the lake, subparallel to regional faults. No indications exist in the seismic data to suggest that fault patterns were created by the volcanic system, either ring or radial faults. Fault strikes interpreted from seismic and magnetic data are consistent with mapped dike and fault orientations on land. We therefore interpret that active faults at the LdMVF are tectonic rather than volcanic in origin, forming a transtensional zone that hosts the magmatic system. However, vertical motion along a NS‐striking fault near the center of uplift suggests trapdoor‐style faulting above the volcanic center in which tectonic faults are reactivated to accommodate magmatic inflation and overlying deformation. Magnetic anomalies follow regional faults, suggesting that faults also provide migration pathways. Depositional patterns indicate a prior episode of uplift followed by quiescence, indicating that significant magmatically related uplift at the LdMVF can occur without an associated major eruption.
Publisher: Informa UK Limited
Date: 09-12-2020
Publisher: American Geophysical Union (AGU)
Date: 09-2020
DOI: 10.1029/2020GC009270
Publisher: American Geophysical Union (AGU)
Date: 08-2011
DOI: 10.1029/2011GL048136
Publisher: American Geophysical Union (AGU)
Date: 04-2021
DOI: 10.1029/2020JB020850
Abstract: The rhyolite‐producing Laguna del Maule volcanic field (LdMVF), Chile, has had numerous post‐glacial eruptions that produced large explosions and voluminous lava flows. During the Holocene ∼60 m of surface uplift is recorded by paleo‐shorelines of the fresh‐water Laguna del Maule, with an inflation source near the Barrancas volcanic complex. Rhyolites from the Barrancas complex erupted over ∼14 ka including some of the youngest (1.4 ± 0.6 ka) lava flows in the field. New gravity data collected on the Barrancas complex reveals a residual gravity low (−6 mGal, “Barrancas anomaly”) that is distinct from the pronounced gravity low (−19 mGal “Lake anomaly”) associated with present‐day ground uplift to the northwest. Three‐dimensional inversion of the Barrancas anomaly indicates the presence of a magma body with a maximum density contrast with the host rock of −250 kg/m 3 centered at a depth of ∼3 km below surface. Nearby Miocene high‐silica granites represent frozen remnants of highly evolved rhyolitic magma. Comparison of the densities measured from s les of these plutons with the geophysical model densities, and integration of thermodynamic modeling of silicic melt evolution, provide constraints on our interpretation. We propose a magma body, containing % melt phase and low volatile content, exists beneath Barrancas. The Barrancas and Lake gravity lows represent magma in different physical states, associated with past and present‐day storage beneath LdMVF. The gravity model mirrors geochemical observations which independently indicate that at least two distinct rhyolites were generated and stored as discrete magma bodies within the broader LdMVF.
Publisher: Wiley
Date: 26-06-2020
Publisher: Elsevier BV
Date: 08-2023
Publisher: Informa UK Limited
Date: 03-2007
Publisher: Elsevier BV
Date: 10-2014
Publisher: American Geophysical Union (AGU)
Date: 10-2023
DOI: 10.1029/2023JB026729
Publisher: American Geophysical Union (AGU)
Date: 21-08-2018
DOI: 10.1029/2018GL078780
Publisher: Informa UK Limited
Date: 02-05-2021
Start Date: 2022
End Date: 2025
Funder: Marsden Fund
View Funded ActivityStart Date: 2021
End Date: 2026
Funder: Ministry of Business, Innovation and Employment
View Funded Activity