scholarly journals LONG-PERIOD AND LONG-DURATION GROUND MOTION PREDICTION EQUATIONS FOR EARTHQUAKES ALONG THE SAGAMI TROUGH BASED ON STRONG MOTION RECORDS

2019 ◽  
Vol 84 (758) ◽  
pp. 501-511
Author(s):  
Toshimi SATOH ◽  
Hiroto NAKAGAWA ◽  
Shin KOYAMA ◽  
Toshiaki SATO ◽  
Masanobu TOHDO
Keyword(s):  
Ground Motion ◽  
Strong Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Strong Motion Records ◽  
Sagami Trough ◽  
Long Period ◽  
Long Duration

scholarly journals Ground motion prediction equations derived from the Italian strong motion database

2011 ◽  
Vol 9 (6) ◽  
pp. 1899-1920 ◽  
Author(s):  
D. Bindi ◽  
F. Pacor ◽  
L. Luzi ◽  
R. Puglia ◽  
M. Massa ◽  
...  
Keyword(s):  
Ground Motion ◽  
Strong Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Strong Motion Database

Improvement of the Quantification of Epistemic Uncertainty Using Single‐Station Ground‐Motion Prediction Equations

2019 ◽  
Vol 109 (4) ◽  
pp. 1358-1377
Author(s):  
Chih‐Hsuan Sung ◽  
Chyi‐Tyi Lee
Keyword(s):  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Strong Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Ground Acceleration ◽  
Single Station

Abstract The results of probabilistic seismic hazard analysis (PSHA) are sensitive to the standard deviation of the residuals of the ground‐motion prediction equations (GMPEs), especially for long‐return periods. Recent studies have proven that the epistemic uncertainty should be incorporated into PSHA using a logic‐tree method instead of mixing it with the aleatory variability. In this study, we propose using single‐station GMPEs with a novel approach (an epistemic‐residual diagram) to improve the quantification of epistemic uncertainty per station. The single‐station attenuation model is established from the observational recordings of a single station, hence, site‐to‐site variability (σS) can be ignored. We use 20,006 records of 497 crustal earthquakes with moment magnitudes (Mw) greater than 4.0, obtained from the Taiwan Strong Motion Instrumentation Program network, to build the single‐station GMPEs for 570 stations showing the peak ground acceleration (PGA) and spectral accelerations. A comparison is made between the total sigma of the regional GMPE (σT), the single‐station sigma of the regional GMPE as estimated by the variance decomposition method (σSS), and the sigma of single‐station GMPEs (σSS,S), for different periods. For most stations (70%), the σSS,S is about 20%–50% smaller than the σT. Furthermore, we adopt the epistemic‐residual diagram to separate the σSS,S into the epistemic uncertainty (σEP,S) and the remaining unexplained variability (σSP,S) for each station. The results show that in most areas, the σSP,S for the PGA is about 50%–80% smaller than the σT. Finally, the variations in the various sigma and model coefficients are mapped with the geographical locations of the stations for analysis of different regional characteristics.

Moment Magnitude Estimation of Large Earthquakes Based on Long-Period Ground Motion Prediction Equations and Preassumed Fault Models

2016 ◽  
Vol 10 (02) ◽  
pp. 1640004
Author(s):  
Rami Ibrahim ◽  
Hongjun Si ◽  
Kazuki Koketsu ◽  
Hiroe Miyake
Keyword(s):  
Ground Motion ◽  
Magnitude Estimation ◽  
Moment Magnitude ◽  
Motion Prediction ◽  
Fault Models ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Long Period ◽  
Large Earthquakes

We proposed a simple method of moment magnitude estimation based on long-period (5–30[Formula: see text]s) ground motion prediction equations (GMPEs). We constructed empirical fault models for different trial magnitudes. The source-to-site distance from the preassumed fault models to seismic stations was estimated. The best magnitude estimate was determined with reference to the minimum residual between the magnitude estimated from the GMPEs and the trial magnitude used to define the fault model. Using this method, the moment magnitudes of six large interplate earthquakes that occurred around the Japan Islands were estimated. The estimated magnitudes obtained in this study are in good agreement with those calculated from the global centroid moment tensor project. The method has potential to be used for rapid moment magnitude estimation of large earthquakes.

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