| Title: |
Magma Pathways Beneath the Klyuchevskoy Volcanic Group, Kamchatka, Revealed by a Machine‐Learning‐Based Earthquake Catalog. |
| Authors: |
Lu, Weifan; Shapiro, Nikolai M.; Münchmeyer, Jannes |
| Source: |
Geophysical Research Letters; 7/16/2026, Vol. 53 Issue 13, p1-12, 12p |
| Abstract: |
Klyuchevskoy Volcanic Group (KVG) is one of the world's largest clusters of subduction‐zone volcanoes and hosts a complex trans‐crustal magmatic system. Using a machine‐learning–based detection workflow applied to data from the KISS seismic experiment in 2015–2016, we obtained an enhanced earthquake catalog for KVG volcano‐magmatic activity. Over 11,000 events were detected, approximately 14 times the number in the previous manual catalog, revealing seismicity strongly clustered in time and space and organized into localized bursts. Frequency index analysis and unsupervised clustering distinguish long‐period from volcano‐tectonic earthquakes. Long‐period events, associated with fluid and pressure changes, dominate the seismicity and span the crustal depth, forming deep‐to‐shallow conduits. Their frequency–magnitude patterns differ from typical tectonic earthquakes, highlighting volcanic source physics. Temporal changes in deep long‐period activity precede increases in shallow seismicity, consistent with magma or fluid pressure migration. Overall, our study reveals fine‐scale structure beneath KVG and provides insight into its multi‐volcano seismic processes. Plain Language Summary: Volcanic earthquakes provide a window into magma movement beneath active volcanoes, but conventional catalogs often miss small events and deep signals. We constructed an enhanced earthquake catalog of ∼11,000 events over 11 months for the Klyuchevskoy volcanic group using machine learning techniques. By separating volcano‐tectonic and long‐period events with a Frequency Index and clustering events by location, we identified distinct seismic populations beneath major volcanoes. Long‐period clusters span a broad depth range and show frequency‐magnitude distributions that depart from the Gutenberg‐Richter relation, with fewer large events and steeper decay. Deep and shallow long‐period events beneath different volcanoes exhibit distinct physical behaviors. Our results reveal fine‐scale magma plumbing structures and provide new indicators for pre‐eruptive activity, showing that traditional earthquake statistics may misrepresent volcanic long‐period sources. Key Points: We constructed an enhanced earthquake catalog of ∼11,000 events over 11 months for the Klyuchevskoy Volcanic Group using machine learningEnhanced catalog delineates distinct pathways linking the deep magma storage area with active volcanoes, dominated by long‐period eventsFrequency index analysis and clustering show long‐period earthquakes depart from the Gutenberg–Richter law, implying fluid‐pressure sources [ABSTRACT FROM AUTHOR] |
| : |
Copyright of Geophysical Research Letters is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |