Ambient Noise Tomography of the Lipari Volcanic Island (Southern Italy) From a Dense Nodal Array

Calò, Marco; Luccio, F. Di; Persaud, Patricia; Ventura, Guido

doi:10.1029/2022gl101022

Cited by 9 publications

(8 citation statements)

References 56 publications

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Section: Discussionmentioning

confidence: 99%

“…Nonetheless, it is recognised that liquid-filled pores in rock matrix exhibit lower S-wave velocity than those without fluids 38,56 , while high-pressurized gas-saturated porous media could be associated with high S-wave velocity 42,57 . At Vulcano, the high anomalies are interpreted as: (1) cold, dry, and locally hardened intrusive magma bodies 34 ; or (2) high-pressurized hydrothermal fluids, mainly gas-saturated porous media 42 . On the other hand, the low anomalies are interpreted as: (1) variations in hydrothermal fluids, magmatic fluids and/or partial melts content 36,38,58,59 ; or (2) unconsolidated volcanoclastic materials emplaced during the successive caldera collapses 36,42,59 .…”

Section: Discussionmentioning

confidence: 99%

“…At Vulcano, the high anomalies are interpreted as: (1) cold, dry, and locally hardened intrusive magma bodies 34 ; or (2) high-pressurized hydrothermal fluids, mainly gas-saturated porous media 42 . On the other hand, the low anomalies are interpreted as: (1) variations in hydrothermal fluids, magmatic fluids and/or partial melts content 36,38,58,59 ; or (2) unconsolidated volcanoclastic materials emplaced during the successive caldera collapses 36,42,59 .…”

Section: Discussionmentioning

confidence: 99%

“…They may represent basaltic or andesitic bodies belonging to an ancient eruptive system 9 (Casa Grotta dell'Abate in Fig. 1C), and probably host highly pressurized hydrothermal CO 2 -rich fluids 42 that contribute to the strong activity visible at Baia di Levante. The sub-horizontal intrusion L1 at about 1.5 km depth, may fuel a vigorous convection with phase separation occurring where the H1 anomaly is located.…”

Section: Discussionmentioning

confidence: 99%

“…Ambient Noise Tomography studies have demonstrated their effectiveness in imaging structures across various scales, including continental 31 , regional 32 , and local scales 33 . This technique has been successfully applied in various volcanic and hydrothermal regions, ranging from hot-spots and rift volcanoes [34][35][36][37][38] , to more complex subduction-related stratovolcanoes [39][40][41][42] , and calderas 43 . The recent development of nodal technologies (e.g., 44,45 ), allows the investigation of highly scattering systems with a great resolution.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Imaging volcanoes during unrest: Ambient Noise Tomography of a transient plumbing system, Vulcano, Italy.

Stumpp,

Cabrera-Pérez,

Savard

et al. 2024

Preprint

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Volcanic hazards increase exponentially during periods of unrest. At present, it is difficult to discern whether magmatic intrusions or hydrothermal activity are the primary drivers of volcanic (re)awakening. This uncertainty complicates hazard mitigation and risk reduction strategies, ultimately influencing civil protection decisions and evacuation plans. In 2021, Vulcano, Italy, entered in unrest, featuring for the first time the occurrence of very long period (VLP) seismic events, which are frequently associated with magma motion at depth. The proposed causative VLPs models are non-unique and advocate either magmatic or hydrothermal activity. We deployed a dense nodal seismic network of 196 3C sensors during the unrest of Vulcano to image the source of deformation thanks to the inversion of seismic ambient noise data. We show that high-resolution Nodal Ambient Noise Tomography (NANT) can accurately identify regions of magma occurrence at depth and help discriminating between magmatic and hydrothermal drivers of unrest. We identify a sub-horizontal intrusion migrating northwards below the vertical projection of the VLP source location, which we suggest may be the causative source of deformation. The deployment of NANT during volcanic unrest, if rapidly processed, can map the distribution of S-wave anomalies and constrain the velocity structure of the regions undergoing major deformations. This approach has the potential to transform static evacuation plans into dynamic and source-dependent hazard mitigation schemes that may ultimately save lives.

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