ground motion prediction equation
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Author(s):  
Hao Xing ◽  
John X. Zhao

ABSTRACT A ground-motion prediction equation for the vertical ground motions from the western and the southwestern parts of China (referred to as SWC) is presented in this study. Based on the Xing and Zhao (2021) study, the Zhao et al. (2017) model (referred to as ZHAO2017) for the shallow crustal earthquakes in Japan was used as the reference model. We used a bilinear magnitude-scaling function hinged at a moment magnitude (Mw) of 7.1. The magnitude-scaling rate for events with Mw>7.1 was determined by records from the SWC dataset and the large events in the Pacific Earthquake Engineering Research Center Next Generation Attenuation-West2 dataset. Site classes (SCs) were used as the site response proxy. All other parameters were derived from the SWC dataset only. The magnitude-scaling rates for events with Mw≤7.1 in this study are larger than in the ZHAO2017 model at most periods. The absolute values of the geometric attenuation rates are larger, and the absolute values of the anelastic attenuation rates are smaller than in the ZHAO2017 model. The between-event standard deviations are smaller than in the ZHAO2017 model at short periods, and the within-event standard deviations are larger than in the ZHAO2017 model at all periods. The differences in the between-site standard deviations vary significantly from one SC to another. We also find that the between-event and within-event residuals are almost independent of magnitude and source distance. The response spectrum attenuates less rapidly than in the ZHAO2017 model at distances less than 30 km.


2021 ◽  
Vol 120 (6) ◽  
pp. 1074
Author(s):  
. Srinagesh ◽  
S. K. Singh ◽  
D. Arroyo ◽  
D. Srinivas ◽  
G. Suresh ◽  
...  

2021 ◽  
pp. 875529302098198
Author(s):  
John G Anderson ◽  
Fabrice Cotton ◽  
Dino Bindi

A method is proposed to identify within seismic catalogs those earthquakes that are most relevant to the seismic hazard. The approach contrasts with the classical approach to decluster the seismic catalog with the expectation that the remaining main shocks will be the relevant events for the seismic hazard analysis. We apply a time window like in the window declustering approach of Gardner and Knopoff, but the time window is motivated by relevance to engineering. A ground motion criterion replaces the spatial window. An event in the time window is included in the “Maximum Shaking Earthquake Catalog (MSEQ catalog)” if the median ground motion at its epicenter exceeds the predicted median ground motion there from the main shock, using a locally appropriate ground motion prediction equation. Ground motion can be measured by any parameter that is estimated by a ground motion prediction equation. We consider peak acceleration and spectral amplitude (SA) at periods of 0.2, 1.0, and 3.0 s. The longer period parameters systematically remove more small events. The purpose is not to produce a declustered catalog, in which each group of physically related earthquakes is represented by its largest event. Statistical properties of the MSEQ catalog somewhat resemble the corresponding declustered catalog in three tested regions, but the MSEQ catalogs all retain more large-magnitude earthquakes. The MSEQ catalog may better represent the potential hazard in a region, and thus might be considered as an alternative to a declustered catalog in developing the seismicity model for probabilistic seismic hazard analysis.


2020 ◽  
pp. 875529302095244
Author(s):  
Shu-Hsien Chao ◽  
Che-Min Lin ◽  
Chun-Hsiang Kuo ◽  
Jyun-Yan Huang ◽  
Kuo-Liang Wen ◽  
...  

We propose a methodology to implement horizontal-to-vertical Fourier spectral ratios (HVRs) evaluated from strong ground motion induced by earthquake (EHVRs) or ambient ground motion observed from microtremor (MHVRs) individually and simultaneously with the spatial correlation (SC) in a ground-motion prediction equation (GMPE) to improve the prediction accuracy of site effects. We illustrated the methodology by developing an EHVRs-SC-based model which supplements Vs30 and Z1.0 with the SC and EHVRs collected at strong motion stations, and a MHVRs-SC-based model that supplements Vs30 and Z1.0 with the SC and MHVRs observed from microtremors at sites which were collocated with strong motion stations. The standard deviation of the station-specific residuals can be reduced by up to 90% when the proposed models are used to predict site effects. In the proposed models, the spatial distribution of the predicted station terms for peak ground acceleration (PGA) from MHVRs at 3699 sites is consistent with that of the predicted station terms for PGA from EHVRs at 721 strong motion stations. Prediction accuracy for stations with inferred Vs30 is similar to that of stations with measured Vs30 with the proposed models. This study provides a methodology to simultaneously implement SC and EHVRs, or SC and MHVRs in a GMPE to improve the prediction accuracy of site effects for a target site with available EHVRs or MHVRs information.


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