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.

Abstract. Here we propose a methodology for Earthquake Early Warning able issuing the alert based on the real-time estimation of the epicentral area where a ground Intensity measure is expected to exceed a user-set ground shaking level. The method provides in output a P-wave-based, time-evolutive “early” shake map. The P-wave displacement, velocity and acceleration amplitudes are jointly measured on a progressively expanded time window while the earthquake location and magnitude are evaluated using data at near source stations. A retrospective analysis of the 2016, Mw 6.5 Central Italy earthquake records shows that the method naturally accounts for effects related to the earthquake rupture directivity and spatial variability of strong ground motion related to source and path and site effects. Five seconds after the origin time the simulated performance of the system in predicting the event impact is very high: in the 40 km-radius area that suffered an Intensity MCS VIII-IX, 41 over 42 strong-motion instrumented sites would have been successfully alerted, with only one false alert. Even considering the 15-km-radius blind-zone, a 15-55 km wide annular area would have received the alert 2-14.5 sec before the occurrence of the strong ground shaking.The proposed EEW method evolves with time in a way that it minimizes the missed alarms while increasing successful alarms and to a lesser extent false alarms, so it is necessary for the end-user to accept these eventualities and account for them in a probabilistic decision scheme depending on the specific safety actuation measure to be undertaken in real-time

A primary task of a network-based, earthquake early warning system is the prompt event detection and location, needed to assess the magnitude of the event and its potential damage through the predicted peak ground shaking amplitude using empirical attenuation relationships. Most of real-time, automatic earthquake location methods ground on the progressive measurement of the first P-wave arrival time at stations located at increasing distances from the source but recent approaches showed the feasibility to improve the accuracy and rapidity of the earthquake location by using the additional information carried by the P-wave polarization or amplitude, especially unfavorable seismic network lay-outs. Here we propose an evolutionary, Bayesian method for the real-time earthquake location which combines the information derived from the differential P-wave arrival times, amplitude ratios and back-azimuths measured at a minimum of two stations. As more distant stations record the P-wave the posterior pdf is updated and new earthquake location parameters are determined along with their uncertainty. To validate the location method we performed a retrospective analysis of mainshocks (M>4.5) occurred during the 2016-2017 Central Italy earthquake sequence by simulating the typical acquisition layouts of in-land, coastal and linear array of stations. Results show that with the combined use of the three parameters, 2-4 sec after the first P-wave detection, the method converges to stable and accurate determinations of epicentral coordinates and depth even with a non-optimal coverage of stations. The proposed methodology can be generalized and adapted to the off-line analysis of seismic records collected by standard local networks.

In this work we propose and apply a straightforward methodology for the automatic characterization of the extended earthquake source, based on the progressive measurement of the P-wave displacement amplitude at the available stations deployed around the source. Specifically, we averaged the P-wave peak displacement measurements among all the available stations and corrected the observed amplitude for distance attenuation effect to build the logarithm of amplitude vs. time function, named LPDT curve. The curves have an exponential growth shape, with 31 an initial increase and a final plateau level. By analyzing and modelling the LPDT curves, the information about earthquake rupture process and earthquake magnitude can be obtained. We applied this method to the Chinese strong motion data from 2007-2015 with MS ranging between 4 and 8. We used a refined model to reproduce the shape of the curves and different source models based on magnitude to infer the source-related parameters for the study dataset. Our study shows that the plateau level of LPDT curves has a clear scaling with magnitude, with no saturation effect for large events. By assuming a rupture velocity of 0.9Vs, we found a consistent self-similar, constant stress drop scaling law for earthquakes in China with stress drop mainly distributed between a lower level (0.23Mpa) and a higher level (3.74Mpa). The derived relation between the magnitude and rupture length can be used for probabilistic hazard analyses and real-time applications of Earthquake Early Warning systems.