A Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Greece

Author(s):  
David M. Boore ◽  
Jonathan P. Stewart ◽  
Andreas A. Skarlatoudis ◽  
Emel Seyhan ◽  
Basil Margaris ◽  
...  

ABSTRACT Using a recently completed database of uniformly processed strong-motion data recorded in Greece, we derive a ground-motion prediction model (GMPM) for horizontal-component peak ground velocity, peak ground acceleration, and 5% damped pseudoacceleration response spectra, at 105 periods ranging from 0.01 to 10 s. The equations were developed by modifying a global GMPM, to account for more rapid attenuation and weaker magnitude scaling in the Greek ground motions than in the global GMPM. Our GMPM is calibrated using the Greek data for distances up to 300 km, magnitudes from 4.0 to 7.0, and time-averaged 30 m shear-wave velocities from 150 to 1200  m/s. The GMPM has important attributes for hazard applications including magnitude scaling that extends the range of applicability to M 8.0 and nonlinear site response. These features are possible because they are well constrained by data in the global GMPM from which our model is derived. An interesting feature of the Greek data, also observed previously in studies of mid-magnitude events (6.1–6.5) in Italy, is that they are substantially overpredicted by the global GMPM, which may be a repeatable regional feature, but may also be influenced by soil–structure interaction. This bias is an important source of epistemic uncertainty that should be considered in hazard analysis.

2021 ◽  
pp. 875529302110348
Author(s):  
Grace A Parker ◽  
Jonathan P Stewart ◽  
David M Boore ◽  
Gail M Atkinson ◽  
Behzad Hassani

We develop semi-empirical ground motion models (GMMs) for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 to 10 s, for the median orientation-independent horizontal component of subduction earthquake ground motion. The GMMs are applicable to interface and intraslab subduction earthquakes in Japan, Taiwan, Mexico, Central America, South America, Alaska, the Aleutian Islands, and Cascadia. The GMMs are developed using a combination of data inspection, data regression with respect to physics-informed functions, ground-motion simulations, and geometrical constraints for certain model components. The GMMs capture observed differences in source and path effects for interface and intraslab events, conditioned on moment magnitude, rupture distance, and hypocentral depth. Site effect and aleatory variability models are shared between event types. Regionalized GMM components include the model constant (that controls ground motion amplitude), anelastic attenuation, magnitude-scaling break point, linear site response, and sediment depth terms. We develop models for the aleatory between-event variability [Formula: see text], within-event variability [Formula: see text], single-station within-event variability [Formula: see text], and site-to-site variability [Formula: see text]. Ergodic analyses should use the median GMM and aleatory variability computed using the between-event and within-event variability models. An analysis incorporating non-ergodic site response should use the median GMM at the reference shear-wave velocity condition, a site-specific site response model, and aleatory variability computed using the between-event and single-station within-event variability models. Epistemic uncertainty in the median model is represented by standard deviations on the regional model constants, which facilitates scaled-backbone representations of model uncertainty in hazard analyses.


2019 ◽  
Vol 109 (4) ◽  
pp. 1358-1377
Author(s):  
Chih‐Hsuan Sung ◽  
Chyi‐Tyi Lee

Abstract The results of probabilistic seismic hazard analysis (PSHA) are sensitive to the standard deviation of the residuals of the ground‐motion prediction equations (GMPEs), especially for long‐return periods. Recent studies have proven that the epistemic uncertainty should be incorporated into PSHA using a logic‐tree method instead of mixing it with the aleatory variability. In this study, we propose using single‐station GMPEs with a novel approach (an epistemic‐residual diagram) to improve the quantification of epistemic uncertainty per station. The single‐station attenuation model is established from the observational recordings of a single station, hence, site‐to‐site variability (σS) can be ignored. We use 20,006 records of 497 crustal earthquakes with moment magnitudes (Mw) greater than 4.0, obtained from the Taiwan Strong Motion Instrumentation Program network, to build the single‐station GMPEs for 570 stations showing the peak ground acceleration (PGA) and spectral accelerations. A comparison is made between the total sigma of the regional GMPE (σT), the single‐station sigma of the regional GMPE as estimated by the variance decomposition method (σSS), and the sigma of single‐station GMPEs (σSS,S), for different periods. For most stations (70%), the σSS,S is about 20%–50% smaller than the σT. Furthermore, we adopt the epistemic‐residual diagram to separate the σSS,S into the epistemic uncertainty (σEP,S) and the remaining unexplained variability (σSP,S) for each station. The results show that in most areas, the σSP,S for the PGA is about 50%–80% smaller than the σT. Finally, the variations in the various sigma and model coefficients are mapped with the geographical locations of the stations for analysis of different regional characteristics.


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.


Author(s):  
John D. Thornley ◽  
Utpal Dutta ◽  
John Douglas ◽  
Zhaohui (Joey) Yang

ABSTRACT Anchorage, Alaska, is a natural laboratory for recording strong ground motions from a variety of earthquake sources. The city is situated in a tectonic region that includes the interface and intraslab earthquakes related to the subducting Pacific plate and crustal earthquakes from the upper North American plate. The generalized inversion technique was used with a local rock reference station to develop site response at >20 strong-motion stations in Anchorage. A database of 94 events recorded at these sites from 2005 to 2019 was also compiled and processed to compare their site response with those in the 2018 Mw 7.1 event (main event). The database is divided into three datasets, including 75 events prior to the main event, the main event, and 19 aftershocks. The stations were subdivided into the site classes defined in the National Earthquake Hazards Reduction Program based on estimated average shear-wave velocity in of the upper 30 m (VS30), and site-response results from the datasets were compared. Nonlinear site response was observed at class D and DE sites (VS30 of 215–300 and 150–215  m/s, respectively) but not at class CD and C sites (VS30 of 300–440 and 440–640  m/s, respectively). The relationship of peak ground acceleration versus peak ground velocity divided by VS30 (shear-strain proxy) was shown to further support the observation that sites with lower VS30 experienced nonlinear site response.


2018 ◽  
Vol 34 (3) ◽  
pp. 1177-1199 ◽  
Author(s):  
Pablo Heresi ◽  
Héctor Dávalos ◽  
Eduardo Miranda

This paper presents a ground motion prediction model (GMPM) for estimating medians and standard deviations of the random horizontal component of the peak inelastic displacement of 5% damped single-degree-of-freedom (SDOF) systems, with bilinear hysteretic behavior and 3% postelastic stiffness ratio, directly as a function of the earthquake magnitude and the distance to the source. The equations were developed using a mixed effects model, with 1,662 recorded ground motions from 63 seismic events. In the proposed model, the median is computed as a function of the vibration period and the normalized strength of the system, as well as the event magnitude and the Joyner-Boore distance to the source. The standard deviation of the model is computed as a function of the vibration period and the normalized strength of the system. The proposed model has the advantage of not requiring an auxiliary elastic GMPM to predict the median and dispersion of peak inelastic displacement.


2021 ◽  
pp. 875529302110560
Author(s):  
Yousef Bozorgnia ◽  
Norman A Abrahamson ◽  
Sean K Ahdi ◽  
Timothy D Ancheta ◽  
Linda Al Atik ◽  
...  

This article summarizes the Next Generation Attenuation (NGA) Subduction (NGA-Sub) project, a major research program to develop a database and ground motion models (GMMs) for subduction regions. A comprehensive database of subduction earthquakes recorded worldwide was developed. The database includes a total of 214,020 individual records from 1,880 subduction events, which is by far the largest database of all the NGA programs. As part of the NGA-Sub program, four GMMs were developed. Three of them are global subduction GMMs with adjustment factors for up to seven worldwide regions: Alaska, Cascadia, Central America and Mexico, Japan, New Zealand, South America, and Taiwan. The fourth GMM is a new Japan-specific model. The GMMs provide median predictions, and the associated aleatory variability, of RotD50 horizontal components of peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration (PSA) at oscillator periods ranging from 0.01 to 10 s. Three GMMs also quantified “within-model” epistemic uncertainty of the median prediction, which is important in regions with sparse ground motion data, such as Cascadia. In addition, a damping scaling model was developed to scale the predicted 5%-damped PSA of horizontal components to other damping ratios ranging from 0.5% to 30%. The NGA-Sub flatfile, which was used for the development of the NGA-Sub GMMs, and the NGA-Sub GMMs coded on various software platforms, have been posted for public use.


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