Uncertainty Analysis and Spatial Correlation of Ground Motion in the Kanto Basin, Japan

Author(s):  
Jinjun Hu ◽  
Lei Hu ◽  
Hui Zhang ◽  
Chaoyue Jin ◽  
Zhongwei Wang ◽  
...  
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.


2017 ◽  
Vol 17 (2) ◽  
pp. 2_74-2_87
Author(s):  
Yuta ABE ◽  
Haruki YAMAMOTO ◽  
Masaki NAKAMURA ◽  
Shinichi AKIYAMA ◽  
Tetsuya INOUE

2020 ◽  
Author(s):  
Shunsuke Takemura ◽  
Kazuo Yoshimoto ◽  
Katsuhiko Shiomi

Abstract We conducted centroid moment tensor (CMT) inversions of moderate (Mw 4.5–6.5) earthquakes in the Kanto region, Japan, using a local three-dimensional (3D) model. We then investigated the effects of our 3D CMT solutions on long-period ground motion simulations. Grid search CMT inversions were conducted using displacement seismograms for periods of 25–100 s. By comparing our 3D CMT solutions with those from the local one-dimensional (1D) catalog, we found that our 3D CMT inversion systematically provides magnitudes smaller than those in the 1D catalog. The Mw differences between 3D and 1D catalogs tend to be significant for earthquakes within the oceanic slab. By comparing ground motion simulations between 1D and 3D velocity models, we confirmed that observed Mw differences could be explained by differences in the rigidity structures around the source regions between 3D and 1D velocity models. The 3D velocity structures (especially oceanic crust and mantle) are important for estimating seismic moments in intraslab earthquakes. The seismic moments directly affect the amplitudes of ground motions. Thus, 3D CMT solutions are essential for the precise forward and inverse modeling of long-period ground motion. We also conducted long-period ground motion simulations using our 3D CMT solutions to evaluate reproducibility of long-period ground motions at stations within the Kanto Basin. The simulations of our 3D CMT inversion well-reproduced observed ground motions for periods longer than 10 s, even at stations within the Kanto Basin.


2019 ◽  
Vol 109 (2) ◽  
pp. 541-566 ◽  
Author(s):  
Deyu Ming ◽  
Chen Huang ◽  
Gareth W. Peters ◽  
Carmine Galasso

2005 ◽  
Vol 21 (4) ◽  
pp. 1137-1156 ◽  
Author(s):  
Min Wang ◽  
Tsuyoshi Takada

It is very important to estimate a macrospatial correlation of seismic ground motion intensities for earthquake damage predictions, building portfolio analyses etc., whereby damage in different locations has to be taken into account simultaneously. This study focuses on spatial correlation of the residual value between an observed and a predicted ground motion intensity, which is estimated by an empirical mean attenuation relationship. The residual value is modeled in such a way that the joint probability density function (PDF) of seismic ground-motion intensity can be characterized by the spatial correlation model as well as an empirical mean attenuation relationship, assuming that it constitutes a homogeneous two-dimensional stochastic field. Using the dense observation data of earthquakes that occurred in Japan and Taiwan in recent years, the macrospatial correlation model is proposed and the assumption of homogeneity is verified in this paper.


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