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Results for “Volcanica”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 19 recordsLinked to original sources
USGS1984

Climbing in the high volcanoes of central Mexico

A chain of volcanoes extends across central Mexico along the 19th parallel, a line just south of Mexico City. The westernmost of these peaks is Nevado de Colima at 4,636 feet above sea level. A subsidiary summit of Nevado de Colima is Volcan de Colima, locally called Fuego (fire) it still emits sulphurous fumes and an occasional plume of smoke since its disastrous eruption in 1941. Parictuin, now dormant, was born in the fall of 1943 when a cornfield suddenly erupted. Within 18 months, the cone grew more than 1,700 feet. Nevado de Toluca is a 15,433-foot volcanic peak south of the city of Toluca. Just southeast of Mexico City are two high volcanoes that are permanently covered by snow: Iztaccihuatl (17,342 fet) and Popocatepetl (17,887 feet) Further east is the third highest mountain in North America: 18,700-foot Citlateptl, or El Pico de Orizaba. North of these high peaks are two volcanoes, 14, 436-foot La Malinche and Cofre de Perote at 14,048 feet. This range of mountains is known variously as the Cordillera de Anahuac, the Sierra Volcanica Transversal, or the Cordillera Neovolcanica.

Central Mexico↗
USGS2020

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

Unoccupied aircraft systems (UAS) are developing into fundamental tools for tackling the grand challenges in volcanology; here, we review the systems used and their diverse applications. UAS can typically provide image and topographic data at two orders of magnitude better spatial resolution than space-based remote sensing, and close-range observations at temporal resolutions down to those of video frame rates. Responsive deployments facilitate dense time-series measurements, unique opportunities for geophysical surveys, sample collection from hostile environments such as volcanic plumes and crater lakes, and emergency deployment of ground-based sensors (and robots) into hazardous regions. UAS have already been used to support hazard management and decision-makers during eruptive crises. As technologies advance, increased system capabilities, autonomy and availability, supported by more diverse and lighter-weight sensors, will offer unparalleled potential for hazard monitoring. UAS are expected to provide opportunities for pivotal advances in our understanding of complex physical and chemical volcanic processes.

Volcanica↗
USGS2021

Tracking secondary lahar flow paths and characterizing pulses and surges using infrasound array networks at Volcán de Fuego, Guatemala

Lahars are one of the greatest hazards at many volcanoes, including Volcán de Fuego (Guatemala). On 1 December 2018 at 8:00pm local Guatemala time (2:00:00 UTC), an hour-long lahar event was detected at Volcán de Fuego by two permanent seismo-acoustic stations along the Las Lajas channel on the southeast side. To establish the timing, duration, and speed of the lahar, infrasound array records were examined to identify both the source direction(s) and the correlated energy fluctuations at the two stations. Co-located seismic and acoustic signals were also examined, which indicated at least 5 distinct energy pulses within the lahar record. We infer that varying sediment load and/or changes in flow velocity is shown by clear fluctuations in the acoustic and seismic power recorded at one of the stations. This particular event studied with infrasound provides insight into how lahars occur around Volcán de Fuego.

Volcán de Fuego↗
USGS2021

Simultaneous effusive and explosive cinder cone eruptions at Veniaminof Volcano, Alaska

Historical eruptions of Veniaminof Volcano, Alaska have all occurred at a 300-m-high cinder cone within the icefilled caldera that characterizes the volcano. At least six of nineteen historical eruptions involved simultaneous explosive and effusive activity from separate vents. Eruptions in 1944, 1983–1984, 1993–1994, 2013, 2018 and 2021 included periods of explosive ash-producing Strombolian activity from summit vents and simultaneous nonexplosive effusion of lava from flank vents on either the southern or northeast sides of the cone. A T-junction conduit network is proposed to explain the simultaneous eruptive styles and as a mechanism for gas-magma segregation that must occur to produce the observed activity. Historical eruptions with simultaneous summit and flank activity produced slightly higher rising ash clouds compared to historical eruptions where simultaneous activity did not occur. This could be a consequence of the partitioning of more gas-charged magma into the vertical conduit of a T-junction conduit system.

Alaska↗
USGS2022

Structured elicitation of expert judgement in real-time eruption scenarios: An exercise for Piton de la Fournaise volcano, La Réunion island

Formalised elicitation of expert judgements has been used to help tackle several problematic societal issues, including volcanic crises and pandemic threats. We present an expert elicitation exercise for Piton de la Fournaise volcano, La Réunion island, held remotely in April 2021. This involved 28 experts from nine countries who considered a hypothetical effusive eruption crisis involving a new vent opening in a high-risk area. The tele-elicitation presented several challenges, but is a promising and workable option for application to future volcanic crises. Our exercise considered an “uncommon” eruptive scenario with a vent outside the present caldera and within inhabited areas, and provided uncertainty ranges for several hazard-related questions for such a scenario (e.g. probability of eruption within a defined timeframe; elapsed time until lava flow reaches a critical location, and other hazard management issues). Our exercise indicated that such a scenario would probably present very different characteristics compared to recent eruptions, and that it is fundamental to include well-prepared expert elicitations in updated civil protection evacuation plans to improve disaster response procedures.

Volcanica↗
USGS2022

Spatial analysis of globally detected volcanic lightning from the June 2019 eruption of Raikoke volcano, Kuril Islands

The 21–22 June 2019 eruption of Raikoke volcano, Russia, provided an opportunity to explore how spatial trends in volcanic lightning locations provide insights into pulsatory eruption dynamics. Using satellite-derived plume heights, we examine the development of lightning detected by Vaisala’s Global Lightning Dataset (GLD360) from eleven, closely spaced eruptive pulses. Results from one-dimensional plume modeling show that the eruptive pulses with maximum heights 9–16.5 km above sea level were capable of producing ice in the upper troposphere, which contributed variably to electrification and volcanic lightning. A key finding is that lightning locations not only followed the main dispersal direction of these ash plumes, but also tracked a lower-level cloud derived from pyroclastic density currents. We show a positive relationship between umbrella cloud expansion and the area over which lightning occurs (the ‘lightning footprint’). These observations suggest useful metrics to characterize ongoing eruptive activity in near real-time.

Kuril Islands, Raikoke volcano↗
USGS2023

Hawai‘i residents’ perceptions of Kīlauea’s 2018 eruption information

The 2018 eruption of Kīlauea Volcano was notable for its variety of large and spatially distinct hazards, simultaneously affecting three geographically disparate, culturally diverse regions in Hawaiʻi. We conducted a pilot study, consisting of 18 semi-structured interviews, two survey responses, and several informal conversations with Hawaiʻi residents to learn which sources/messengers of eruption information were deemed most trusted and credible. Participants' perceptions of the U.S. Geological Survey Hawaiian Volcano Observatory (HVO), community-based messengers, and traditional news media can be examined across four themes: relevance, expertise, sincerity, and pace. Among our interview participants, Lower East Rift Zone (LERZ) residents placed the highest trust in their community messengers, summit residents deemed HVO most trustworthy, and Kaʻū residents trusted information from both HVO and local news media. Our findings suggest that future official eruption communications would benefit from 1) designating communications personnel to act as community liaisons and 2) increasing pace and relevance of information delivery.

Hawaii↗
USGS2023

Lessons learned from the 2022 CONVERSE Monogenetic Volcanism Response Scenario exercise

When volcanic unrest occurs, the scientific community can advance fundamental understanding of volcanic systems, but only with coordination before, during, and after the event across academic and governmental agencies. To develop a coordinated response plan, the Community Network for Volcanic Eruption Response (CONVERSE) orchestrated a scenario exercise centered around a hypothetical volcanic crisis in Arizona’s San Francisco Volcanic Field (SFVF). The exercise ran virtually from February 4 to March 4, 2022. Over 60 scientists from both academic and governmental spheres participated. The scenario exercise was assessed for its effectiveness in supporting collaborative production of knowledge, catalyzing transdisciplinary collaboration, supporting researcher confidence, and fostering a culture of inclusion within the volcanology community. This identified a need to support early career researchers through community and allyship. Overall, the 2022 CONVERSE exercise demonstrated how a fully remote, extended scenario can be authentically implemented and help broaden participation within the volcano science community.

Arizona↗
USGS2024

Craters of habit: Patterns of deformation in the western Galápagos

The western Galápagos islands of Fernandina and Isabela comprise six active volcanoes that have deformed since first observed by satellite radar in the early 1990s. We analyse new (2015–2022) displacement time series at Alcedo, Cerro Azul, Darwin, Fernandina, Sierra Negra, and Wolf volcanoes in the context of deformation and unrest since 1992. Previous discussions of volcano deformation have focused on eruptions, major intrusive episodes, and the structure of sub-volcanic systems. We discuss the full geodetic record of deformation and show that the style of eruptions, characteristics of unrest and deformation are distinctive at each volcano. These characteristic differences in deformation and unrest styles between the volcanoes have persisted for at least three decades, since the first satellite radar measurements. These consistent differences in shallow magma storage and eruptive dynamics reflect the influence of “top-down” factors and evolutionary stage, providing a basis to understand volcanic unrest here, and to inform monitoring strategies.

Volcanica↗
USGS2024

The utility of TerraSAR-X, TanDEM-X, and PAZ for studying global volcanic activity: Successes, challenges, and future prospects

TerraSAR-X (TSX), TanDEM-X (TDX), and PAZ Synthetic Aperture Radar data have been used at over 120 volcanoes to assess surface characteristics and change over time. We examine previous work, adding additional examples to understand where and when these data are most useful for volcanology. We focus on volcanoes as part of the Committee on Earth Observation Satellites (CEOS) Volcano Demonstrator Project. TSX/TDX/PAZ data provide a valuable means of detecting small surface changes from amplitude images and topographic changes from bistatic TSX/TDX data. For short temporal and perpendicular baselines, TDX/TSX/PAZ can also provide useful deformation data, even in presence of vegetation. No global background mission currently acquires TSX/TDX/PAZ data at volcanoes: 70 % high spatial resolution data, limiting their suitability for studying pre-eruptive unrest. Coordinated targeting by SAR constellations of priority volcanoes would provide data and insights valuable for forecasting eruptions and associated hazards.

Volcanica↗
USGS2025

Catastrophic lava flow levee failure: Precursors, processes, and implications

During an effusive eruption crisis the initial advance of a lava flow is typically the primary focus of model forecasts and hazard management efforts. Flow branching and lateral expansion of lava flows can pose significant dangers within evolving flow fields throughout the duration of an eruption and are an underappreciated hazard. We use field monitoring, infrasound, time lapse imagery, and lidar data collected during the 2018 lower East Rift Zone eruption of Kīlauea (Hawai‘i) to track the origins, progression, and implications of a flow branching event caused by catastrophic levee failure. Our analyses show that surges in effusion rate, rheologic transitions between pāhoehoe and ‘a‘ā flow regimes, slope-breaks, pre-existing topographic highs, and the structure of perched levee walls all played a role in the failure of the levee and subsequent re-routing of the lava flow. Failure of perched lava structures leads to an acutely hazardous situation because lava impounded by the structure can rapidly inundate the landscape. This is the first time a levee failure event has been observed in such detail with numerous monitoring techniques; this unprecedented level of observation provides quantifiable insights into levee failure processes that have important implications for hazard mitigation and an improved understanding of lava flow emplacement dynamics.

Hawaii↗
USGS2025

The morphological response to the 13 May 2022 major explosive event at Stromboli volcano, Italy, characterised by high-resolution UAS surveys

Since 2019, the frequency of major explosive eruptions at Stromboli volcano (Italy) has increased, heightening the exposure of population and scientists to the hazards posed by ejecta. Morphological changes can directly alter the hazard potential associated with these phenomena. Here, we present a quantitative morphological analysis of changes of the crater terrace area linked to the 13 May 2022 major explosive event. High resolution (2.5 cm pixel -1 ) aerial imagery was acquired by unoccupied aircraft systems 2 hours before and 19 hours after the event. The 13 May 2022 major explosive event consisted of a minimum of seven explosions from four vents located in the south-central crater area. The opportune timing of this campaign enabled the quantification of morphological changes at Stromboli related to a single major explosive event at high temporal and spatial resolution. A total of 12.7 × 10 3 m 3 was excavated and 5.5 × 10 3 m 3 deposited. Via the mapping and classification of bomb distributions we observe that angular blocks make up the largest fraction of ballistics >0.2 m, from which we infer a strong interaction with wall rock and/or fragmentation of solidified plugs in the shallow plumbing system. The morphological changes observed provide valuable constraints on how much material is displaced, and the shift in location and the number of active vents during major explosive events at Stromboli.

Stromboli volcano↗
USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗
USGS2026

Relating glassy rind thicknesses to ambient air temperatures at the Lost Jim flow field in the Imuruk Lake volcanic field, Alaska

The Lost Jim flow field, in the Imuruk Lake volcanic field, Alaska, extends west ~34 km from a single vent, crossing subarctic tundra and currently touches several lakes and streams. The weighted mean of five 36Cl cosmogenic exposure ages from the Lost Jim pāhoehoe flow is 7.73 ± 0.37 ka, indicating this eruption occurred substantially after the eruption of the underlying Camille flow, which was emplaced at 39.7 ± 1.3 ka. Paleoclimate records indicate the period when the Lost Jim flow field was emplaced was after deglaciation, and the climate was similar to today. We propose that the emplacement of lava in these cold subarctic conditions can lead to faster cooling of the lava surface compared to lava emplaced in warmer locations such as mid- latitude cold deserts. Glass abundance in the outermost rinds at the Lost Jim flow field was on average 74 % with 6.4 mm thick rims, compared to 60 % with 2.9 mm rims for cold mid-latitude desert samples. We interpret increased glass content as a proxy for rapid cooling likely occurring partly during winter. Glassiness values varied less across vent, margin, and mid-flow locations when compared to the mid-latitude flows suggesting the Lost Jim flow field was broadly impacted by the subarctic climate as opposed to responding to local microclimates. Our results indicate that lava glassiness may be a useful environmental indicator of cooler (in this case subarctic) conditions.

Alaska↗
USGS2026

A scanning electron microscope-energy dispersive spectrometry (SEM-EDS) method for the quantitative analysis of common volcanic phases

In situ microanalysis by X-ray spectrometry is a fundamental geochemical technique for volcanology and the geosciences generally and typically performed using an electron microprobe (EPMA) equipped with wavelength dispersive spectrometers (WDS). The related technique of energy dispersive spectrometry (EDS), implemented using either EPMA or a scanning electron microscope (SEM), offers advantages in throughput, simplicity, and cost, yet has historically been relegated to qualitative tasks. We present a quantitative EDS procedure implemented using a W-source SEM and a moderate size silicon drift EDS detector applied to common volcanic materials. Glass and mineral standard data demonstrate that the accuracy and precision of this method is comparable to EPMA–WDS. We show that electron beam damage can be mitigated in volcanic glass through sample-specific optimizations without the need for a time-dependent intensity correction. Our implementation using a relatively inexpensive instrument can potentially increase the accessibility of high-quality, quantitative X-ray microanalysis of major and minor elements.

Volcanica↗
USGS2026

Vulnerability of the petroleum sector to volcanic hazards: Application to multi-hazards at Taranaki Mounga volcano, Aotearoa New Zealand

Volcanic eruptions can cause substantial damage and disruption to infrastructure and communities. Contemporary societies typically depend on petroleum infrastructure. Volcanic unrest and eruptions can cause considerable operational and structural challenges for the petroleum sector. The vulnerability of this sector to volcanic hazards is understudied when compared to other potentially dangerous phenomena (e.g. earthquakes). In this paper, we present new volcanic physical vulnerability models for the four key asset classes of the petroleum sector: wells, pipelines, production facilities and storage tanks. The vulnerability models are developed based on a literature review and facilitated expert judgement in the form of workshops with petroleum engineers and volcanic risk experts. These models consider four hazard intensity metrics (burial thickness, static load, dynamic pressure and airborne ash concentration) and are thus applicable to multiple volcanic hazards. We apply these models to pre-existing multi-hazard eruption scenarios for Taranaki Mounga volcano in Aotearoa New Zealand, using an available impact assessment framework to demonstrate their usability in impact and risk modelling. Our impact assessment indicates that a future eruption of Taranaki Mounga volcano could cause widespread impacts to the petroleum sector, which would in turn create a prolonged national emergency due to energy supply shortages for major industries and consumers. These vulnerability models may be applied in other volcanic regions worldwide to inform risk reduction and readiness actions.

Taranaki Mounga volcano↗
USGS2025

Fast or slow: An evaluation of Ti-in-quartz diffusion coefficients through comparisons of quartz and plagioclase diffusion times

Diffusion geochronometry using Ti-in-quartz has become a valuable method in understanding the evolution of silicic magmas. However, four different options for Ti diffusivity ( D Ti ) currently exist, spanning three orders of magnitude, resulting in substantially different estimated times and interpretations. We present Ti-in-quartz diffusion times for the Cerro Galán Ignimbrite using the Cherniak et al. [2007] ( 10.1016/j.chemgeo.2006.09.001 ), Audétat et al. [2021] ( 10.1130/g48785.1 ), Audétat et al. [2023] ( 10.1038/s41467-023-39912-5 ), and Jollands et al. [2020] ( 10.1130/g47238.1 ) D Ti value and (1) compare these against plagioclase diffusion times derived from the same samples, (2) consider evidence for Ti diffusion in quartz under relevant magmatic timescales, and (3) compute derived quartz growth rates for crystals from the Cerro Galán Ignimbrite. On all accounts, we find that the Cherniak et al. [2007] diffusion coefficient yields diffusion times that agree much better with independent evidence than those derived using slower D Ti values [Jollands et al. 2020; Audétat et al. 2021; 2023].

Volcanica↗
USGS2025

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica↗