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Automated Identification and Characterization of Very Long-Period Seismic Events for Applications in Monitoring Volcanic Activities.

Description: 

Real-time applications in seismology play a crucial role in monitoring and surveilling active volcanoes, serving as invaluable tools for the early detection of volcanic unrest. Particularly at open-vent active volcanoes like Stromboli in Italy, the identification of Very Long Period (VLP) seismicity is essential. VLP seismicity, often associated with mild and persistent explosive activity, holds significance in volcano monitoring, with variations in occurrence rate and magnitude serving as potential precursors to an eruption.

In this study, we present a novel method for the automatic real-time detection and characterization of VLP seismicity at Stromboli. The detection algorithm relies on Three-Component Amplitude (TCA), derived from waveform polarization and spectral analysis of continuous recordings. This approach provides crucial information such as time of detection, azimuth, incidence, amplitude, and frequency of the identified VLP events.

Furthermore, VLP amplitudes obtained from all monitoring network stations, presented as peak-to-peak amplitudes and mean square amplitudes, are employed for an automated localization of the seismic VLP source. The results of our automatic detection algorithm are then compared with those obtained through manual and automatic inspections of seismic records, as well as with VLP time histories from existing published datasets.

The comparative analysis reveals that the VLP detection time series generated by our automatic algorithm effectively mirrors fluctuations in VLP activity observed manually by operators over an approximately 20-year period. This success allows for the integration of our approach into the real-time processing framework employed at Stromboli for ongoing volcano surveillance.

Session: Multidisciplinary Approaches for Volcanic Eruption Forecasting - II

Type: Oral

Date: 5/2/2024

Presentation Time: 05:00 PM (local time)

Presenting Author: Sergio

Student Presenter: No

Invited Presentation: 

Authors