Generation of a Stochastic Seismic Event Set Based on a New Seismicity Model in China’s Earthquake Catastrophe Model

2021 ◽  
Author(s):  
Weijin Xu ◽  
Mengtan Gao ◽  
Huiqiang Zuo
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Seismic Event ◽  
Hazard Analysis ◽  
Source Model ◽  
Seismic Events ◽  
Catastrophe Model ◽  
Potential Source ◽  
Potential Sources ◽  
Seismicity Model

Abstract Earthquakes are among the most devastating natural disasters in China, causing serious casualties and property losses. To effectively reduce catastrophic risk, it is important to establish an earthquake catastrophe insurance system based on the earthquake catastrophe model, of which seismic hazard analysis is a main module. Probabilistic seismic-hazard analysis uses the potential source model, seismicity model, and ground-motion attenuation model, as well as the probability method to obtain the seismic hazard value of a given point. However, because the influence of a single seismic event is required when the earthquake catastrophe model is used for risk analysis, a series of single events needs to be generated according to the potential source model so as to calculate the influence of each event on the given point. In this study, based on the seismicity model (potential sources and their seismicity parameters) used in compiling the fifth generation of Seismic Ground Motion Parameter Zoning Map of China, we use the Monte Carlo method to simulate seismic events conforming to temporal, spatial, and intensity distribution of China’s seismic activities. In the simulation process, we follow the Poisson distribution in occurrence time and the Gutenberg–Richter law in magnitude distribution, and we use potential sources and earthquake occurrence rates to describe spatial distribution. The simulated seismic events include the following parameters: date (year, month, and day), location (longitude and latitude), depth, magnitude, and attitude of seismogenic faults. The simulated seismic event set can support earthquake risk analysis in the earthquake catastrophe model and has been applied in the earthquake catastrophe model of China.

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.

scholarly journals Seismic Hazard Assessment for the Tianshui Urban Area, Gansu Province, China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenming Wang ◽  
David T. Butler ◽  
Edward W. Woolery ◽  
Lanmin Wang
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Seismic Design ◽  
Hazard Analysis ◽  
Seismic Hazard Assessment ◽  
Gansu Province ◽  
Mitigation Measures ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Acceleration Time Histories

A scenario seismic hazard analysis was performed for the city of Tianshui. The scenario hazard analysis utilized the best available geologic and seismological information as well as composite source model (i.e., ground motion simulation) to derive ground motion hazards in terms of acceleration time histories, peak values (e.g., peak ground acceleration and peak ground velocity), and response spectra. This study confirms that Tianshui is facing significant seismic hazard, and certain mitigation measures, such as better seismic design for buildings and other structures, should be developed and implemented. This study shows that PGA of 0.3 g (equivalent to Chinese intensity VIII) should be considered for seismic design of general building and PGA of 0.4 g (equivalent to Chinese intensity IX) for seismic design of critical facility in Tianshui.

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.

PSHA of the southern Pacific Islands

2020 ◽  
Author(s):  
K L Johnson ◽  
M Pagani ◽  
R H Styron
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Subduction Zones ◽  
Pacific Islands ◽  
Source Model ◽  
Occurrence Rate ◽  
Probabilistic Seismic Hazard ◽  
Maximum Magnitude ◽  
Probability Of Exceedance ◽  
Magnitude Scaling

Summary The southern Pacific Islands region is highly seismically active, and includes earthquakes from four major subduction systems, seafloor fracture zones and transform faults, and other sources of crustal seismicity. Since 1900, the area has experienced >350 earthquakes of M > 7.0, including 11 of M ≥ 8.0. Given the elevated threat of earthquakes, several probabilistic seismic hazard analyses have been published for this region or encompassed subregions; however, those that are publicly accessible do not provide complete coverage of the region using homogeneous methodologies. Here, we present a probabilistic seismic hazard model for the southern Pacific Islands that comprehensively covers the Solomon Islands in the northwest to the Tonga islands in the southeast. The seismic source model accounts for active shallow crustal seismicity with seafloor faults and gridded smoothed seismicity, subduction interfaces using faults with geometries defined based on geophysical datasets and models, and intraslab seismicity modelled by a set of ruptures that occupy the slab volume. Each source type is assigned occurrence rates based on sub-catalogues classified to each respective tectonic context. Subduction interface and crustal fault occurrence rates also incorporate a tectonic component based on their respective characteristic earthquakes. We demonstrate the use of non-standard magnitude-frequency distributions to reproduce the observed occurrence rates. For subduction interface sources, we use various versions of the source model to account for epistemic uncertainty in factors impacting the maximum magnitude earthquake permissible by each source, varying the interface lower depth and segmentation as well as the magnitude scaling relationship used to compute the maximum magnitude earthquake and subsequently its occurrence rate. The ground motion characterisation uses a logic tree that weights three ground motion prediction equations for each tectonic region. We compute hazard maps for 10% and 2% probability of exceedance in 50 years on rock sites, discussing the regional distribution of peak ground acceleration and spectral acceleration with a period of 1.0 s, honing in on the hazard curves and uniform hazard spectra of several capital or populous cities and drawing comparisons to other recent hazard models. The results reveal that the most hazardous landmasses are the island chains closest to subduction trenches, as well as localised areas with high rates of seismicity occurring in active shallow crust. We use seismic hazard disaggregation to demonstrate that at selected cities located above subduction zones, the PGA with 10% probability of exceedance in 50 years is controlled by Mw > 7.0 subduction interface and intraslab earthquakes, while at cities far from subduction zones, Mw < 6.5 crustal earthquakes contribute most. The model is used for southern Pacific Islands coverage in the Global Earthquake Model Global Hazard Mosaic.

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