Geology topics

Ninfa Lucia Bennington

Publications and source records attributed to Ninfa Lucia Bennington.

7 recordsLinked to original sources

USGS2026

Insights from more than a year of ongoing episodic lava fountaining at Kilauea

Episodic lava fountaining is rare globally, with only three occurrences from Kīlauea (Hawaii) since 1823. Beginning in December 2024, an eruption within the summit crater, Halemaʻumaʻu, has produced 52 fountaining episodes to date, each lasting typically for hours and separated by days to weeks. Although multiple mechanisms have been proposed, fundamental questions remain about how magma reservoir pressure, conduit permeability, and volatile exsolution control fountaining onset. We present a multi-parameter record of episodic fountaining at Kīlauea using modern geochemical, geophysical, and geologic monitoring. These observations revealed systematic correlations between fountaining and summit inflation, enabling unprecedented quantitative forecasts. This eruption will provide new constraints on the timing, evolution, and processes driving episodic fountaining globally, and highlights Kīlauea’s role as a natural laboratory for studying volcanic processes.

Hawaii↗

USGS2025

Nodal seismic deployment on Mauna Loa volcano, Hawaii: Dataset and preliminary insights

Mauna Loa is the largest active volcano on Earth, comprising ∼51% of the Island of Hawai‘i’s landmass and posing significant risks to the island’s communities, infrastructure, and natural environment. Historical eruptions have produced lava flows that have reached the ocean in as little as 3 hr. The timing and location of such lava flows in the past 200 yr underscore how critical determination of the location and geometry of magma storage and structure is for volcanic hazard assessment and eruption forecasting. Now, after nearly 38 yr of volcanic quiescence, Mauna Loa has erupted again. On 27 November 2022, fissures initiated within the summit caldera and then migrated to the northeast rift zone, where they generated a large lava flow that threatened a major highway. To improve our understanding of the geometry of this magma system, we deployed a temporary nodal array on Mauna Loa in the summer of 2024. This increased our seismic coverage sufficiently to image this magmatic system. This nodal array consists of 33 seismometers distributed on and around the volcano and was deployed for over three months to record seismic signals. The primary objective of this project is to resolve the high‐resolution seismic velocity structure and characterize seismic features associated with magma storage and ascent pathways. In this article, we present an overview of the deployment, evaluate the quality of the data, and show example recordings to evaluate the suitability of the data set for future seismic investigations, including earthquake relocation, seismic tomography, and receiver function analysis. Comparisons with nearby permanent broadband and short‐period seismic stations demonstrate that the nodal array recorded high‐quality waveforms, making it a valuable resource for constraining the magmatic system beneath Mauna Loa at multiple scales.

Hawaii↗

USGS2025

A decade of precursory seismicity at Mauna Loa: 2013–2022

The 2022 eruption of Mauna Loa was preceded by nearly 10 years of seismic unrest. Using the earthquake catalog of the Hawaiian Volcano Observatory, we describe and explore many aspects of unrest between January 1, 2013, and the start of the eruption on November 28, 2022 (UTC). Earthquakes associated with unrest occurred above an inflating dike at shallow depths under and to the south of Moku‘āweoweo and in the cluster of seismicity to the west of Moku‘āweoweo associated with a buried rift zone. Earthquakes also occurred in a broad region at the base of the crust, likely associated with a zone of magma accumulation. Unrest is broken down into four phases of increasing intensity with time and into individual geographic regions. While activity occurring at shallow depths under the caldera often alternated with activity on the west flank in the first two phases of unrest, the third phase of unrest featured increased rates of earthquake activity in both areas acting concurrently. We also document a slow shift in seismicity across multiple years from the south of Moku‘āweoweo to an area under the caldera that likely represents a change in the location of the intrusion through time. Broadly speaking, unrest observed in advance of the 2022 eruption occurred in the same areas as the unrest preceding eruptions in 1975 and 1984. Furthermore, precursory unrest prior to eruptions in 1975, 1984 and 2022 lasted years and culminated in an intense phase of seismic activity lasting on the order of hours that represented the final dike propagation to the surface. Concurrent earthquake activity under Moku‘āweoweo and the west flank of Mauna Loa, paired with a shift in earthquakes under Moku‘āweoweo were the two most notable long-term precursors to an eruption; however, neither provided an actionable timeline of an impending eruption. The decade of precursory seismicity prior to the 2022 eruption is similar to long precursory phases prior to eruptions in 1975 and 1984 and underscores the challenges of informing on eruption hazards in a timely manner. By combining seismic activity with other geophysical fields such as geodesy and gravity, we present a conceptual model to aid in the interpretation of future unrest at Mauna Loa.

Hawaii↗

USGS2025

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa↗

USGS2025

The progression of basaltic–rhyolitic melt storage at Yellowstone Caldera

Yellowstone Caldera is one of the largest volcanic systems on Earth, hosting three major caldera-forming eruptions in the past two million years, interspersed with periods of less explosive, smaller-volume eruptions 1 . Caldera-forming eruptions at Yellowstone are sourced by rhyolitic melts stored within the mid- to upper crust. Seismic tomography studies have suggested that a broad region of rhyolitic melt extends beneath Yellowstone Caldera, with an estimated melt volume that is one to four times greater than the eruptive volume of the largest past caldera-forming eruption, and an estimated melt fraction of 6–28 per cent 2 , 3 , 4 , 5 . Seismic velocity is strongly influenced by temperature, pressure and melt; however, magnetotelluric data are primarily sensitive to the presence of melt, making these data ideal for constraining volcanic systems. Here we utilize magnetotelluric data to model the resistivity structure of Yellowstone Caldera’s crustal magma reservoir and constrain the region’s potential for producing major volcanic eruptions. We find that rhyolitic melts are stored in segregated regions beneath the caldera with low melt fractions, indicating that the reservoirs are not eruptible. Typically, these regions have melt volumes equivalent to small-volume post-caldera Yellowstone eruptions. The largest region of rhyolitic melt storage, concentrated beneath northeast Yellowstone Caldera, has a storage volume similar to the eruptive volume of Yellowstone’s smallest caldera-forming eruption. We identify regions of basalt migrating from the lower crust, merging with and supplying heat to the northeast region of rhyolitic melt storage. On the basis of our analysis, we suggest that the locus of future rhyolitic volcanism has shifted to northeast Yellowstone Caldera.

Idaho, Montana, Wyoming↗

USGS2024

Triggering the 2022 eruption of Mauna Loa

Distinguishing periods of intermittent unrest from the run-up to eruption is a major challenge at volcanoes around the globe. Comparing multidisciplinary monitoring data with mineral chemistry that records the physical and spatio-temporal evolution of magmas fundamentally advances our ability to forecast eruptions. The recent eruption of Mauna Loa, Earth’s largest active volcano, provides a unique opportunity to differentiate unrest from run-up and improve forecasting of future eruptions. After decades of intermittent seismic and geodetic activity over 38 years of repose, Mauna Loa began erupting on 27 November 2022. Here we present a multidisciplinary synthesis that tracks the spatio-temporal evolution of precursory activity by integrating mineral and melt chemistry, fluid inclusion barometry, numerical modeling of mineral zoning, syn-eruptive gas plume measurements, the distribution and frequency of earthquake hypocenters, seismic velocity changes, and ground deformation. These diverse data indicate that the eruption occurred following a 2-month period of sustained magma intrusion from depths of 3–5 km up to 1–2 km beneath the summit caldera, providing a new model of the plumbing system at this very high threat volcano. Careful correlation of both the geochemistry and instrumental monitoring data improves our ability to distinguish unrest from the run-up to eruption by providing deeper understanding of the both the monitoring data and the magmatic system—an approach that could be applied at other volcanic systems worldwide.

Hawaii↗

USGS2024

A seismic nodal deployment to understand magmatic structure in the vicinity of the Pahala earthquake swarm

In summer-fall 2022, 80 three-component SmartSolo IGU-BD3C-5 nodal seismometers were deployed surrounding the Pāhala seismic swarm on the Island of Hawaiʻi, with the goal of improving seismicity catalogs, and seismic velocity images of the crust and upper mantle in this region. The Pāhala swarm, located south of Mauna Loa and Kīlauea, has been the site of a multiyear sustained swarm of seismicity at depths of ~ 25 – 40 km, with order of magnitude increases in rate in 2015, and then again in 2019. This seismicity is possibly related to the input of magma from the mantle plume below, which may then be subsequently transported to volcanic edifices. However, these processes remain enigmatic, in part due to a lack of precise earthquake locations and seismic velocity models in this region. Here we provide an overview of the deployment, an assessment of the quality of the collected data, and discuss the viability of the dataset for local earthquake relocation, tomography, and teleseismic receiver functions. Through comparisons with proximal permanent broadband and short period instruments, we find that the nodes produce high quality data, particularly at periods shorter than 5 s, although we find, document, and correct discrepancies with the gain and polarities of the instruments. We successfully record signals from teleseismic earthquakes, even at periods longer than 5 s (the corner of the flat response of the nodes). We also record local earthquakes, including details related to source characteristics. This indicates that the data is likely to prove useful for investigations using both local and teleseismic earthquake signals to better understand the connections between the deep and shallow magmatic systems of Hawaiʻi. While this deployment provides a snapshot in time, its success may provide a useful benchmark for future studies as the volcanic systems of Hawaiʻi continue to evolve in the future.

Hawaii↗