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Earthquake location and detection modeling for a future seafloor observatory along Mayotte's volcanic ridge

Abstract : The volcano-seismic crisis afflicting Mayotte since May 2018 has motivated France-based seismologists to consider the installment of a permanent seafloor observatory with one or more seismometers for monitoring surfacing magma and the associated seismicity. In general, deploying a seismometer offshore is known to improve earthquake location - particular in depth - and lower magnitude detection. However, how true are these claims for Mayotte when a land-based seismic network already exists? To address this, we investigate location and detection performance when deploying permanent seismometers offshore Mayotte. We modeled location and detection performance using both real and synthetic data in different network configurations. We found that, in the case of Mayotte, only longitude error is significantly reduced by adding seismometers offshore, perhaps due to the North-South configuration of the land network. Moreover, the size of the Mayotte volcano monitoring area, which spans depths and distances up to 50 km for both, prevents accurate location and detection performance with less than 2 permanent seismometers offshore. Therefore, we would need at least 2 cabled seismometers to monitor this volcanic system, i.e. locate and detect events in real-time. Overall, our modeling suggests that a one-side land network can perform relatively well by itself in location (errors <5 km) and detection (magnitude >1.3) so long as the seismicity occurs at epicentral distances and depths <20 km. However, beyond this distance, one or more seafloor seismometers would be needed to improve location and detection performance.
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Submitted on : Monday, February 28, 2022 - 4:46:33 PM
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Chastity Aiken, Jean-Marie Saurel, Océane Foix. Earthquake location and detection modeling for a future seafloor observatory along Mayotte's volcanic ridge. Journal of Volcanology and Geothermal Research, Elsevier, 2021, 418, 12 pp. ⟨10.1016/j.jvolgeores.2021.107322⟩. ⟨insu-03589889⟩



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