Rapid Estimating Epicentral Distance and Magnitude from a Single Seismic Record of Sarpol-e Zahab Earthquake

Document Type : Seismology and Engineering Seismology


International Institute of Earthquake Engineering and Seismology (IIEES)


Earthquake Early Warning System (EEWS) is issued by detection of P-wave,estimation of seismic parameters and decision to alarm. The EEWS provides advance warning of estimated seismic intensities and expected arrival time of S-waves. These estimates are based on prompt analysis of hypocenter location and earthquake magnitude using data observed by seismographs near the epicenter. In this study, the B-D method is examined to estimate an earthquake's magnitude and epicentral distance using only initial part of P-wave data (3 s) from a single station for application in EEWS. Fitting a simple function with the form of f(t)=Bt×exp(-At) to the first few seconds of the waveform envelope, coefficients A and B are determined through the least-squares method. B decreases with distance and shows independence from magnitude and logB is inversely proportional to logD, where D is the epicentral distance. B values are calculated on the basis of 65 vertical-component accelerograms of Sarpol-e Zahab earthquake (Mw 7.3) with epicentral distances less than 100 km. The magnitude and an amplitude parameter Pmax determined from the very beginning of P-wave, are important for EEWS, yet their dependence on source mechanism, focal depth and epicentral distance has not been fully studied. Using this method, we could estimate the epicentral distance by logD = -0.57logB + 2.4 ± 0.4 and earthquake magnitude by Mest= 1.99 log Pmax-1.76 log B + 5.62 ± 0.3.The greatest advantage of this method is its accuracy and rapidness. The EEW system issues several alarm messages during the course of one earthquake, improving the accuracy of the warning as the amount of available data increases. The EEW is transmitted to many kinds of devices and used for personal safety and automatic control. It is very important to observe strong motion in real-time using a dense network in order to improve the EEW system.


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