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Neural Network Nodal Ambient Noise Tomography of a transient plumbing system under unrest, Vulcano, Italy

Author

Listed:
  • Douglas Sami Stumpp

    (University of Geneva)

  • Iván Cabrera-Pérez

    (University of Geneva)

  • Geneviève Savard

    (University of Geneva)

  • Tullio Ricci

    (Istituto Nazionale di Geofisica e Vulcanologia)

  • Mimmo Palano

    (Università degli Studi di Palermo
    Osservatorio Etneo)

  • Salvatore Alparone

    (Osservatorio Etneo)

  • Andrea Ursino

    (Osservatorio Etneo)

  • Federica Sparacino

    (Osservatorio Etneo)

  • Anthony Finizola

    (Laboratoire GéoSciences Réunion
    CNRS)

  • Francisco Muñoz Burbano

    (University of Geneva)

  • María-Paz Reyes Hardy

    (University of Geneva)

  • Joël Ruch

    (University of Geneva)

  • Costanza Bonadonna

    (University of Geneva)

  • Matteo Lupi

    (University of Geneva)

Abstract

Volcanic risk escalates significantly during unrest. In late 2021, the Italian island of Vulcano entered into a phase of unrest featuring Very Long Period seismic events, which are considered to be markers of magma and gas flowing across the volcanic plumbing system. Here we show how Neural Network Nodal Ambient Noise Tomography generates a high-resolution shear-wave velocity model for investigating the causative drivers of Vulcano’s unrest. Using a deep learning model we harvest seismic dispersion data from a dense nodal seismic network deployed during the early unrest’s phase. The inverted 3-D model reveals a high-resolution tomography of the shallow part of a volcanic system in unrest. If deployed and rapidly processed in (near) real-time during periods of unrest, Neural Network Nodal Ambient Noise Tomography can lead to dynamic and adaptive evacuation plans. Such advances would contribute to more effective, source-dependent risk mitigation schemes in volcanic regions, potentially saving lives.

Suggested Citation

  • Douglas Sami Stumpp & Iván Cabrera-Pérez & Geneviève Savard & Tullio Ricci & Mimmo Palano & Salvatore Alparone & Andrea Ursino & Federica Sparacino & Anthony Finizola & Francisco Muñoz Burbano & María, 2025. "Neural Network Nodal Ambient Noise Tomography of a transient plumbing system under unrest, Vulcano, Italy," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-62846-z
    DOI: 10.1038/s41467-025-62846-z
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