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Earthquake monitoring using hydro-acoustic datasets from oceanic gliders
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The seismic stations coverage is scarce in the oceans because it is expensive and logistically challenging, leading to a lack of global accurate earthquake data from oceanic locations.  At the seafloor-water boundary, seismic energy is converted into hydro-acoustic energy, known as Tertiary waves (or T-waves), characterized by low-frequencies ranging  up to 50 Hz and efficiently propagating, allowing them to be detected at great distances. To assess a novel oceanic seismological platform, we analyzed 5 years of data from Passive Acoustic Monitoring (PAM) sensors tethered in oceanic gliders to explore current and potential uses of these hydro-acoustic datasets for local and regional earthquake detection. The oceanic gliders are reasonably quiet, buoyancy-driven (no propellers), long-endurance (sampling rate dependent), and autonomous underwater profiling vehicles. This dataset is obtained from the Project of Underwater Soundscape Monitoring of Santos Basin (PMPAS-BS), with the primary goal of quantifying and evaluating anthropogenic hydroacoustic noise associated with the exploration and production (E&P) activities in the offshore region of southeastern Brazil. Analyzing the dataset, our findings characterized several signals related to cataloged earthquakes, both local and regional, exhibiting distinctive features, such as maximum energy in low frequencies (<10 Hz) and impulsive signals. For instance, on December 24, 2019, at 16:43:32 (UTC) a teleseismic event from Santiago del Estero Province, Argentina, with a magnitude of 6.1 was detected approximately 1800 km away from the epicenter, and the oceanic glider, positioned at a depth of about 750 m, registered the signal after approximately 3 minutes. On March 25, 2020, at 11:30:39 (UTC), we observed hydro-acoustic signals as an example of a local earthquake detection for a seismic event (4.2 mb) off the Southeast Coast of Brazil. At a depth of about 700 m and approximately 100 km away, the glider recorded two distinct arrivals: the first, impulsive one, ~22 s after the event time and the second, emergent one, arriving about 80 s later. Local earthquakes present clear emergent T waves distinguished by high amplitudes and defocused wavetrain with tapered envelope. Furthermore, by following these previous features, we were able to identify other uncataloged local earthquakes. These results suggest that ocean gliders serve as a potential platform for seismo-acoustics observations in oceanic areas on Earth, facilitating the monitoring of both natural and human-made seismic events. Our research also identifies some points to improve future passive acoustic monitoring with oceanic gliders: 1) Improvements of glider endurance; 2) Sampling rate adjustments for low-frequency signals; and 3) calibration of the passive acoustic monitoring system to minimize noise levels. This work is expected to expand seismological observations using oceanic gliders and motivate researchers in related fields to reprocessing their hydro-acoustics dataset.
Title: Earthquake monitoring using hydro-acoustic datasets from oceanic gliders
Description:
The seismic stations coverage is scarce in the oceans because it is expensive and logistically challenging, leading to a lack of global accurate earthquake data from oceanic locations.
  At the seafloor-water boundary, seismic energy is converted into hydro-acoustic energy, known as Tertiary waves (or T-waves), characterized by low-frequencies ranging  up to 50 Hz and efficiently propagating, allowing them to be detected at great distances.
To assess a novel oceanic seismological platform, we analyzed 5 years of data from Passive Acoustic Monitoring (PAM) sensors tethered in oceanic gliders to explore current and potential uses of these hydro-acoustic datasets for local and regional earthquake detection.
The oceanic gliders are reasonably quiet, buoyancy-driven (no propellers), long-endurance (sampling rate dependent), and autonomous underwater profiling vehicles.
This dataset is obtained from the Project of Underwater Soundscape Monitoring of Santos Basin (PMPAS-BS), with the primary goal of quantifying and evaluating anthropogenic hydroacoustic noise associated with the exploration and production (E&P) activities in the offshore region of southeastern Brazil.
Analyzing the dataset, our findings characterized several signals related to cataloged earthquakes, both local and regional, exhibiting distinctive features, such as maximum energy in low frequencies (<10 Hz) and impulsive signals.
For instance, on December 24, 2019, at 16:43:32 (UTC) a teleseismic event from Santiago del Estero Province, Argentina, with a magnitude of 6.
1 was detected approximately 1800 km away from the epicenter, and the oceanic glider, positioned at a depth of about 750 m, registered the signal after approximately 3 minutes.
On March 25, 2020, at 11:30:39 (UTC), we observed hydro-acoustic signals as an example of a local earthquake detection for a seismic event (4.
2 mb) off the Southeast Coast of Brazil.
At a depth of about 700 m and approximately 100 km away, the glider recorded two distinct arrivals: the first, impulsive one, ~22 s after the event time and the second, emergent one, arriving about 80 s later.
Local earthquakes present clear emergent T waves distinguished by high amplitudes and defocused wavetrain with tapered envelope.
Furthermore, by following these previous features, we were able to identify other uncataloged local earthquakes.
These results suggest that ocean gliders serve as a potential platform for seismo-acoustics observations in oceanic areas on Earth, facilitating the monitoring of both natural and human-made seismic events.
Our research also identifies some points to improve future passive acoustic monitoring with oceanic gliders: 1) Improvements of glider endurance; 2) Sampling rate adjustments for low-frequency signals; and 3) calibration of the passive acoustic monitoring system to minimize noise levels.
This work is expected to expand seismological observations using oceanic gliders and motivate researchers in related fields to reprocessing their hydro-acoustics dataset.
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