Search USGSSearch

USGS · 70278984

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

Abstract

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.

Explore related subjects

Keep this discovery

BibTeXRIS

Xusong Yang, Guoqing Lin, Ninfa Lucia Bennington, Elizabeth Gallant. 2025-10-29. Nodal seismic deployment on Mauna Loa volcano, Hawaii: Dataset and preliminary insights. https://doi.org/10.1785/0220250232

Cite the original work for its findings. Save a collection to share your selection of sources.

Discover connections

Connections use source metadata and explicit phrase matches, not verified experimental comparisons.

KEEP EXPLORING

Related USGS reports

Distinguishing natural sources from anthropogenic events in seismic data

As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).

Seismological Research Letters

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters