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Earthquake Seismic Moment, Rupture Radius and Stress-drop from P-wave Displacement Amplitude vs Time Curves
  • aldo zollo ,
  • sahar nazeri ,
  • Simona Colombelli
aldo zollo
Università di Napoli Federico II

Corresponding Author:[email protected]

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sahar nazeri
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Simona Colombelli
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The reliable determination of earthquake source parameters is a relevant task of seismological investigations which ground nowadays on high quality seismic waveforms collected by near-source dense arrays of ground motion sensors. Here we propose a parametric modelling technique which analyzes the time-domain P-wave signal recorded in the near-source range of small-to-large size earthquakes. Assuming a triangular moment-rate function and a uniform speed, circular rupture model, we develop the equations to estimate the seismic moment, rupture radius and stress-drop from the corner-time and plateau level of the average logarithm of the P-wave displacement vs time curves (LPDT). The constant-Q, anelastic attenuation effect is accounted by a post-processing procedure that evaluates the Q-unperturbed moment-rate triangular shape.
The methodology has been validated through the application to the acceleration records of the 2016-2017 Central Italy and 2007-2019 Japan earthquake sequences covering a wide moment magnitude range (Mw 2.5 - 6.5) and recording distance < 100 km. After correcting for the anelastic attenuation function, the estimated average stress-drop and the confidence interval (〈∆σ〉=0.60 (0.42-0.87) MPa and 〈∆σ〉=1.53 (1.01-2.31) for crustal and subcrustal events of Japan and 〈∆σ〉=0.36(0.30-0.44) MPa for Central Italy) show, for both regions, a self-similar, constant stress-drop scaling of the rupture duration/radius with seismic moment. The smaller sensitivity of the spatially averaged, time-varying peak displacement amplitude to the radiation from localized high slip patch on the fracture surface, could explain the retrieved smaller average stress-drops for sub-crustal earthquakes in Japan and M>5.5 events in Central Italy relative to previous estimates using spectral methods.