Seismic‐Hazard Analysis of Long‐Period Ground Motion of Megathrust Earthquakes in the Nankai Trough Based on 3D Finite‐Difference Simulation

2016 ◽  
Vol 87 (6) ◽  
pp. 1265-1273 ◽  
Author(s):  
Takahiro Maeda ◽  
Asako Iwaki ◽  
Nobuyuki Morikawa ◽  
Shin Aoi ◽  
Hiroyuki Fujiwara
Keyword(s):  
Finite Difference ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Nankai Trough ◽  
Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Megathrust Earthquakes ◽  
Long Period ◽  
Long Period Ground Motion

Finite-Difference Simulation of Long-Period Ground Motion for the Sagami Trough Megathrust Earthquakes

2013 ◽  
Vol 8 (5) ◽  
pp. 926-940 ◽  
Author(s):  
Asako Iwaki ◽  
◽  
Nobuyuki Morikawa ◽  
Takahiro Maeda ◽  
Shin Aoi ◽  
...  
Keyword(s):  
Finite Difference ◽  
Ground Motion ◽  
Ground Motions ◽  
Source Area ◽  
Sagami Trough ◽  
Megathrust Earthquakes ◽  
Long Period ◽  
Fault Parameters ◽  
Source Models ◽  
Long Period Ground Motion

We perform long-period ground motion simulations for Sagami Trough earthquakes by a three dimensional finite-difference method. The Sagami Trough has been the site of two well-known megathrust earthquakes, the 1923 Taisho- and the 1703 Genroku-type Kanto earthquakes. However, a lack of accumulated historical earthquake records prevents us fromobtaining knowledge of the source model of the next anticipated event for long-period ground motion hazard evaluation. Therefore, it is important to consider numerous possibilities for the unknown source parameters. We compare ground motions for several scenarios with different source area, and with magnitudes ranging from Mw7.9 to 8.6. Peak ground velocity (PGV) within the Kanto basin, including the Tokyo metropolitan area, differs by several times depending on the choice of the source area. The effects of the variety in fault parameters, such as rupture starting points and asperity patterns, are also studied. They can greatly vary the ground motion within the Kanto area, especially in the direction of rupture propagation, suggesting the severe impact of directivity effects. Source models with different rupture starting points produce PGV and 5% damped velocity response (Sv) that vary from each other by as much as 10-20 times. PGV and Sv vary by up to five times depending on the asperity pattern. Our simulation results show that the predicted ground motion for the earthquake scenarios strongly depends on both the source size and other fault parameters of the source models. It is suggested that the seismic hazard assessment requires statistical evaluation of ground motions from as many source models as possible in order to overcome the uncertainties of the source.

scholarly journals A ground motion logic tree for seismic hazard analysis in the stable cratonic region of Europe: regionalisation, model selection and development of a scaled backbone approach

2020 ◽  
Vol 18 (14) ◽  
pp. 6119-6148
Author(s):  
Graeme Weatherill ◽  
Fabrice Cotton
Keyword(s):  
United States ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Eastern United States ◽  
Logic Tree ◽  
Short Period ◽  
Northeastern Europe

Abstract Regions of low seismicity present a particular challenge for probabilistic seismic hazard analysis when identifying suitable ground motion models (GMMs) and quantifying their epistemic uncertainty. The 2020 European Seismic Hazard Model adopts a scaled backbone approach to characterise this uncertainty for shallow seismicity in Europe, incorporating region-to-region source and attenuation variability based on European strong motion data. This approach, however, may not be suited to stable cratonic region of northeastern Europe (encompassing Finland, Sweden and the Baltic countries), where exploration of various global geophysical datasets reveals that its crustal properties are distinctly different from the rest of Europe, and are instead more closely represented by those of the Central and Eastern United States. Building upon the suite of models developed by the recent NGA East project, we construct a new scaled backbone ground motion model and calibrate its corresponding epistemic uncertainties. The resulting logic tree is shown to provide comparable hazard outcomes to the epistemic uncertainty modelling strategy adopted for the Eastern United States, despite the different approaches taken. Comparison with previous GMM selections for northeastern Europe, however, highlights key differences in short period accelerations resulting from new assumptions regarding the characteristics of the reference rock and its influence on site amplification.

Ranking of Ground-Motion Models (GMMs) for Use in Probabilistic Seismic Hazard Analysis for Iran Based on an Independent Data Set

2020 ◽  
Author(s):  
Zoya Farajpour ◽  
Milad Kowsari ◽  
Shahram Pezeshk ◽  
Benedikt Halldorsson
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Selection Process ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Data Set ◽  
Motion Models ◽  
Ground Motion Models

ABSTRACT We apply three data-driven selection methods, log-likelihood (LLH), Euclidean distance-based ranking (EDR), and deviance information criterion (DIC), to objectively evaluate the predictive capability of 10 ground-motion models (GMMs) developed from Iranian and worldwide data sets against a new and independent Iranian strong-motion data set. The data set includes, for example, the 12 November 2017 Mw 7.3 Ezgaleh earthquake and the 25 November 2018 Mw 6.3 Sarpol-e Zahab earthquake and includes a total of 201 records from 29 recent events with moment magnitudes 4.5≤Mw≤7.3 with distances up to 275 km. The results of this study show that the prior sigma of the GMMs acts as the key measure used by the LLH and EDR methods in the ranking against the data set. In some cases, this leads to the resulting model bias being ignored. In contrast, the DIC method is free from such ambiguity as it uses the posterior sigma as the basis for the ranking. Thus, the DIC method offers a clear advantage of partially removing the ergodic assumption from the GMM selection process and allows a more objective representation of the expected ground motion at a specific site when the ground-motion recordings are homogeneously distributed in terms of magnitudes and distances. The ranking results thus show that the local models that were exclusively developed from Iranian strong motions perform better than GMMs from other regions for use in probabilistic seismic hazard analysis in Iran. Among the Next Generation Attenuation-West2 models, the GMMs by Boore et al. (2014) and Abrahamson et al. (2014) perform better. The GMMs proposed by Darzi et al. (2019) and Farajpour et al. (2019) fit the recorded data well at short periods (peak ground acceleration and pseudoacceleration spectra at T=0.2  s). However, at long periods, the models developed by Zafarani et al. (2018), Sedaghati and Pezeshk (2017), and Kale et al. (2015) are preferable.

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