Geology topics

Mario Angarita

Publications and source records attributed to Mario Angarita.

9 recordsLinked to original sources

USGS2026

Erupted volume during the 2014–2023 Semisopochnoi unrest and eruption constrained by multi-platform InSAR and volcanic gas observations

Volcano deformation data provide important constraints on magma dynamics during volcanic unrest and eruptions. From these observations, we can estimate subsurface pressure changes and relate them to volume change in the reservoir. However, because magma and rock are compressible, this volume change cannot be directly equated with eruptive volume. When we combine geodetic analyses with gas observations, petrologic constraints, volatile solubility modeling, and magma compressibility equations, however, we can estimate realistic lower and upper bounds of eruptive volume. Leveraging multi‐platform InSAR time series and satellite SO 2 data, we apply these methods to the 2014–2023 unrest and eruption of Semisopochnoi, Alaska. We find that this phreatomagmatic eruption sequence was fed by a spherical magma source at 6.5–7.5 km depth bsl, centered beneath the caldera, ∼5 km offset to the east from the vent. Volatile solubility modeling indicates that ∼50% of the initial dissolved CO 2 has exsolved at depths consistent with the geodetic source depth, increasing the magma compressibility. Combining geodetic model constraints with SO 2 observations, petrologic constraints, solubility models, and magma compressibility findings yields 12–32 Mm 3 as the most‐likely juvenile, dense‐rock equivalent eruptive volume, with a best estimate of 20 Mm 3 . Stress change modeling suggests that the local stress field encouraged conduit formation west of the pre‐eruptive inflation center, and that the 2014 M7.9 Rat Island earthquake, ∼65 km to the west of Semisopochnoi, reduced the compressive stress underneath the volcano, supporting prolonged eruptive activity.

Alaska↗

USGS2025

Identifying precursors and tracking pulses of magma ascent in multidisciplinary data during the 2018–2023 phreatomagmatic eruption at Semisopochnoi Island, Alaska

The 2018–2023 phreatomagmatic eruptions at Semisopochnoi Island, Alaska produced abundant long-period (LP) seismicity, harmonic and broadband tremor, and explosion signals over several well-monitored periods of eruption and quiescence. The corresponding dataset provides an excellent opportunity to investigate precursory and syn -eruptive geophysical signals of long-lived phreatomagmatic eruptions using multiparameter observations. We generated explosion and LP event catalogs through novel implementations of the REDPy ( Hotovec-Ellis, 2024 ) repeating event detector in mid-2021 following a network upgrade and the onset of a new phase of the eruption. The hundreds of detected explosions show a high degree of infrasound waveform similarity over more than a year, indicating a repeating source mechanism likely associated with explosive magma-water interaction. The seismic LP catalog shows that events began over a month prior to renewed explosive activity at the beginning of August 2021, and that lower frequency index (FI) LPs were generated in the week prior to the onset of explosions. We applied a recently developed machine learning tool (VOISS-Net, Tan et al., 2024 ) to catalog abundant broadband and harmonic seismic tremor recorded before and during the renewed explosive activity, along with LPs and explosions. The tremor catalogs complement the LP and explosion catalogs by filling out the seismic sequence with the dominant signal types. Together, these catalogs reveal a seismic sequence of renewed unrest that started with several weeks of LP events, followed by LPs with lower FI values and harmonic tremor in the days prior to explosive activity, and finally the onset of discrete explosions and broadband eruption tremor. We interpret this sequence as the ascent of a new pulse of magma that first interacted with the hydrothermal/groundwater system to produce LPs, followed by harmonic tremor, and that ultimately drove explosive magma-water interactions and periods of continuous ash emissions. The 2021 seismic sequence, in combination with long-term records of satellite SO 2 emissions, deformation from interferometric synthetic aperture radar (InSAR) analysis, ash sample analysis, infrasound, and volcano tectonic seismicity, allows us to interpret the entire 9-year period of unrest and eruption that began with an intrusion and earthquake swarm in 2014.

Alaska↗

USGS2025

Vent-specific unrest at Pavlof Volcano, Alaska: Insights from multidisciplinary data

Pavlof Volcano, a frequently active volcano in the Aleutian arc, has erupted six times between 2007 and 2022. Many Pavlof Volcano eruptions lack detectable precursory seismicity or ground deformation, making them challenging to forecast. Since 2007, these eruptions have ranged from Strombolian to Subplinian (VEI 2–3), with their characteristics seemingly related to their active vent location. Summit vent eruptions tend to be abrupt and explosive, while southeast flank vent eruptions tend to be more effusive and longer-lived. To better understand Pavlof Volcano’s plumbing system and improve eruption forecasts, we integrate geophysical, petrologic, and satellite-based thermal infrared and gas data to conduct a multidisciplinary data synthesis for eruptions between 2007 and 2022. Notably, a recently developed volcano seismicity detection model reveals unique pre- and syn-eruptive seismic tremor regimes associated with each vent system. The summit vent eruptions show greater tremor diversity and resurgent eruptive behavior, whereas the southeast flank vent eruptions show a steady tremor transition over a single eruptive phase. We use local infrasound data and air-to-ground coupled waves to build explosion catalogs, revealing gas-rich explosions during the 2021–2022 eruption from the summit vent, which was previously thought to be inactive during that eruption. Whole-rock composition and ash analyses indicate a near-uniform basaltic andesite composition spanning multiple eruptions, and a consistent anomalous presence of altered olivines in erupted material. We use these findings to propose a new conceptual model for Pavlof Volcano’s plumbing system: a shallow T-junction outlet controlling seismic tremor diversity and the partitioning of gas-charged magma; and an elongated, heated conduit transporting magma from depth and storing partly molten, residual magma between eruptions. We suggest that magma ascent rate and vent sealing modulate eruption style at Pavlof Volcano, where the T-junction directs rapidly ascending, gas-rich magma to the summit vent, and diverts slower rising, gas-poor magma towards the southeast flank vent.

Alaska↗

USGS2024

Versatile modeling of deformation (VMOD) inversion framework: Application to 20 years of observations at Westdahl Volcano and Fisher Caldera, Alaska, US

We developed an open source, extensible Python-based framework, that we call the Versatile Modeling of Deformation (VMOD), for forward and inverse modeling of crustal deformation sources. VMOD abstracts from specific source model implementations, data types and inversion methods. We implement the most common geodetic source models which can be combined to model and analyze multi-source deformation. VMOD supports Global Navigation Satellite System (GNSS), InSAR, electronic distance measurement, Leveling and tilt data. To infer source characteristics from observations, VMOD implements non-linear least squares and Markov Chain Monte-Carlo Bayesian inversions, including joint inversions using different sources of data. VMOD's structure allows for easy integration of new geodetic models, data types, and inversion strategies. We benchmark the forward models against other published results and the inversion approaches against other implementations. We apply VMOD to analyze deformation at Unimak Island, Alaska, observed with continuous and campaign GNSS, and ascending and descending InSAR time series generated from Sentinel-1 satellite radar acquisitions. These data show an inflation pattern at Westdahl volcano and subsidence at Fisher Caldera. We use VMOD to test a range of source models by jointly inverting the GNSS and InSAR data sets. Our final model simultaneously constrains the parameters of two sources. Our results reveal a depressurizing spheroid under Fisher Caldera ∼4–6 km deep, contracting at a rate of ∼2–3 Mm 3 /yr, and a pressurizing spherical source underneath Westdahl volcano ∼6–8 km deep, inflating at ∼5 Mm 3 /yr. This and past applications of VMOD to volcanic unrest benefit from an extensible framework which supports jointly inversions of data sets for parameters of easily composable multi-source models.

Alaska↗

USGS2023

Understanding the drivers of volcano deformation through geodetic model verification and validation

Volcano geodesy often involves the use of models to explain observed surface deformation. A variety of forward models are used, from analytical point sources to numerical simulations that consider complex magma system geometries, topography, and material properties. Various inversion methods can then be used to relate observed volcano data to models. Ideally, forward models should be verified through intercomparison, to check for implementation errors and quantify the error induced by any approximations used. Additionally, forward models and inversion methods should be validated through tests with synthetic and/or real data, to determine their ability to match data and estimate parameter values within uncertainty. However, to date, there have not been comprehensive verification and validation efforts in volcano geodesy. Here, we report on the first phase of the Drivers of Volcano Deformation (DVD) exercises, which were designed to build community involvement through web-based exercises involving calculations of static elastic displacement around pressurized magma reservoirs. The forward model exercises begin with a spherical reservoir in a homogeneous half space, then introduce topography, heterogeneous elastic properties, and spheroidal geometries. The inversion exercises provide synthetic noisy surface displacement data for a spherical reservoir in a homogeneous half space and assess consistency in estimates of reservoir location and volume/pressure change. There is variability in the results from both forward modeling and inversions, which highlights the strengths and limitations of different forward models, as well as the importance of inversion method choice and uncertainty quantification. This first phase of the DVD exercises serves as a community resource and will facilitate further efforts to develop standards of reproducibility.

Bulletin of Volcanology↗

USGS2022

Return from dormancy: Rapid inflation and seismic unrest driven by transcrustal magma transfer at Mt. Edgecumbe (L’´ux Shaa) Volcano, Alaska

In April 2022, a seismic swarm near Mt. Edgecumbe in southeast Alaska suggested renewed activity at this transform fault volcano, which was last active ≈800 years ago. Previously, thin rhyolitic tephras were deposited 5 and 4 ka. Satellite radar data from 2014 to 2022 resolves line-of-sight rapid inflation up to 7.1 cm/yr beginning in August 2018. Bayesian modeling suggests a transcrustal system of a deflating (−0.528 km 3 ) dipping sill at 20 km depth recharging a magma chamber at 10 km (0.222 km 3 ). A near-vertical conduit could capture the volume difference without noticeable surface deformation. Reanalyzed seismicity, recorded 25 km away, shows increases since July 2019. Magma ascent through ductile material and brittle strain release in a stressed overburden could explain the time delay. Cloud-native open data and workflows enabled discovery and analysis of this signal within days after going unnoticed for >3 years.

Alaska↗

USGS2022

Quantifying large-scale surface change using SAR amplitude images: Crater morphology changes during the 2019-2020 Shishaldin Volcano eruption

Morphological processes often induce meter-scale elevation changes. When a volcano erupts, tracking such processes provides insights into the style and evolution of eruptive activity and related hazards. Compared to optical remote-sensing products, synthetic aperture radar (SAR) observes surface change during inclement weather and at night. Differential SAR interferometry estimates phase change between SAR acquisitions and is commonly applied to quantify deformation. However, large deformation or other coherence loss can limit its use. We develop a new approach applicable when repeated digital elevation models (DEMs) cannot be otherwise retrieved. Assuming an isotropic radar cross-section, we estimate meter-scale vertical morphological change directly from SAR amplitude images via an optimization method that utilizes a high-quality DEM. We verify our implementation through simulation of a collapse feature that we modulate onto topography. We simulate radar effects and recover the simulated collapse. To validate our method, we estimate elevation changes from TerraSAR-X stripmap images for the 2011–2012 eruption of Mount Cleveland. Our results reproduce those from two previous studies; one that used the same dataset, and another based on thermal satellite data. By applying this method to the 2019–2020 eruption of Shishaldin Volcano, Alaska, we generate elevation change time series from dozens of co-registered TerraSAR-X high-resolution spotlight images. Our results quantify previously unresolved cone growth in November 2019, collapses associated with explosions in December–January, and further changes in crater elevations into spring 2020. This method can be used to track meter-scale morphology changes for ongoing eruptions with low latency as SAR imagery becomes available.

Alaska↗

USGS2021

Monitoring volcanic deformation

Deformation signals recorded at volcanoes have long been used to infer the processes behind subsurface magma intrusions. Monitoring strategies vary greatly depending on several factors such as the activity of the individual volcano, access, available personnel, and funding. Certain geodetic monitoring methods, such as Electronic Distance Measurements, are inexpensive but require that scientists be dangerously close to active areas. Other techniques, such as telemetered geodetic measurements (Electronic Tiltmeters and Global Navigation Satellite System), or deformation images from Interferometric Synthetic Aperture Radar, can be collected remotely and with less risk. Observed surface deformation can be fit to the predictions of mathematical source models to obtain quantitative estimates of their parameters (e.g., location, depth, volume change and more). Combined deformation and gravity change measurements can be used to infer the density of subsurface intrusions and better constrain the source of unrest. To be effective, geodetic monitoring must be done before, during, and after eruptions and must be integrated with other monitoring techniques (e.g., seismology, geochemistry, physical volcanology, remote sensing). It requires the long-term commitment of time and resources. Done effectively, geodetic monitoring not only can provide timely warnings of escalating volcano hazards but may also lead to improved understanding of how volcanoes work. Even when a volcano is not active, monitoring generates baseline information against which changes in volcano behavior can be compared. Preserving the integrity and accessibility of geodetic data archives is thus essential if future volcanologists are to benefit from the decades-long records of geodetic data gathered by volcano observatories.

Book chapter↗

USGS2019

Monitoring volcanic deformation

Whereas research in volcano geodesy seeks to push the boundaries of our knowledge of the physics of volcanoes, monitoring looks at changes in volcano behavior to predict when a volcanic crisis might develop. To be effective, geodetic monitoring must be done before, during, and after eruptions and must be integrated with other monitoring techniques . It requires the type of long-term commitment of time and resources that academic and industry scientists generally cannot make. A few, well-placed geodetic monitoring stations can make a huge difference to a country's ability to alert its people to an imminent volcanic eruption . Monitoring strategies vary greatly depending on several factors such as the activity of the individual volcano, access, and available personnel and funding. Rapid advances in technology allow for more precise geodetic monitoring today than was imaginable when many of the existing volcano observatories were established. Today, deformation measurements at active volcanoes are usually made with continuous Global Positioning System (CGPS) stations, supplemented by Interferometric Synthetic Aperture Radar (InSAR) images. Neither method requires a continuous presence of personnel in the field, except for the installation and maintenance of the GPS stations; however subsequent data analysis can be highly complex.

Book chapter↗