Long‐Period Ground‐Motion Prediction Equations for Moment Magnitude Estimation of Large Earthquakes in Japan

2016 ◽  
Vol 106 (1) ◽  
pp. 54-72 ◽  
Author(s):  
Rami Ibrahim ◽  
Hongjun Si ◽  
Kazuki Koketsu ◽  
Hiroe Miyake
Keyword(s):  
Ground Motion ◽  
Magnitude Estimation ◽  
Moment Magnitude ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Long Period ◽  
Long Period Ground Motion ◽  
Large Earthquakes

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.

scholarly journals Ground Motion Prediction Equations for Malaysia Due to Subduction Zone Earthquakes in Sumatran Region

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 23920-23937
Author(s):  
M. S. Liew ◽  
Kamaluddeen Usman Danyaro ◽  
Mazlina Mohamad ◽  
Lim Eu Shawn ◽  
Aziz Aulov
Keyword(s):  
Subduction Zone ◽  
Ground Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Subduction Zone Earthquakes

scholarly journals Ground motions in urban Los Angeles from the 2019 Ridgecrest earthquake sequence

2021 ◽  
pp. 875529302110039
Author(s):  
Filippos Filippitzis ◽  
Monica D Kohler ◽  
Thomas H Heaton ◽  
Robert W Graves ◽  
Robert W Clayton ◽  
...  
Keyword(s):  
Los Angeles ◽  
Ground Motion ◽  
Ground Motions ◽  
Earthquake Sequence ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Velocity Models ◽  
Spectral Accelerations

We study ground-motion response in urban Los Angeles during the two largest events (M7.1 and M6.4) of the 2019 Ridgecrest earthquake sequence using recordings from multiple regional seismic networks as well as a subset of 350 stations from the much denser Community Seismic Network. In the first part of our study, we examine the observed response spectral (pseudo) accelerations for a selection of periods of engineering significance (1, 3, 6, and 8 s). Significant ground-motion amplification is present and reproducible between the two events. For the longer periods, coherent spectral acceleration patterns are visible throughout the Los Angeles Basin, while for the shorter periods, the motions are less spatially coherent. However, coherence is still observable at smaller length scales due to the high spatial density of the measurements. Examining possible correlations of the computed response spectral accelerations with basement depth and Vs30, we find the correlations to be stronger for the longer periods. In the second part of the study, we test the performance of two state-of-the-art methods for estimating ground motions for the largest event of the Ridgecrest earthquake sequence, namely three-dimensional (3D) finite-difference simulations and ground motion prediction equations. For the simulations, we are interested in the performance of the two Southern California Earthquake Center 3D community velocity models (CVM-S and CVM-H). For the ground motion prediction equations, we consider four of the 2014 Next Generation Attenuation-West2 Project equations. For some cases, the methods match the observations reasonably well; however, neither approach is able to reproduce the specific locations of the maximum response spectral accelerations or match the details of the observed amplification patterns.

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