New conditional, scenario-based, and traditional peak ground velocity models for interface and intraslab subduction zone earthquakes

An expanded Pacific Earthquake Engineering Research (PEER) Center Next Generation Attenuation Phase 2 (NGA-West2) ground motion database, compiled using shallow crustal earthquakes in active crustal regions (ACRs), was used to develop the closed-form GS24b backbone ground motion model (GMM) for the RotD50 horizontal components of peak ground acceleration (PGA), peak ground velocity (PGV), and 5% damped elastic pseudo-absolute response spectral accelerations (SA). The GS24b model is applicable to earthquakes with moment magnitudes of 4.0 ≤ M ≤ 8.5, at rupture distances of 0 ≤ Rrup ≤ 400 km, with time-averaged S-wave velocity in the upper 30 m of the profile at 150 ≤ VS30 ≤ 1500 m/s, and for periods of 0.01 ≤ T ≤ 10 s. The new backbone model includes VS30 site correction developed based on multiple representative S-wave velocity profiles. For crustal wave attenuation, we used the apparent anelastic attenuation of SA—QSA (f, M). In contrast to the GK17, the GS24b backbone is a generic ACR model designed specifically to be adjusted to any ACRs. The GS24bc is an example of a partially non-ergodic model created by adjusting the backbone GS24b model for magnitude M, S-wave velocity VS30, and fault rupture distance residuals.

The PEER NGA-Sub ground-motion intensity measure database is used to develop new conditional ground-motion models (CGMMs), a set of scenario-based models, and non-conditional models to estimate the cumulative absolute velocity ([Formula: see text]) of ground motions from subduction zone earthquakes. In the CGMMs, the median estimate of [Formula: see text] is conditioned on the estimated peak ground acceleration ([Formula: see text]), the time-averaged shear-wave velocity in the top 30 m of the soil ([Formula: see text]), the earthquake magnitude ([Formula: see text]), and the spectral acceleration at the period of 1 s ([Formula: see text]). Multiple scenario-based [Formula: see text] models are developed by combining the CGMMs with pseudo-spectral acceleration ([Formula: see text]) ground-motion models (GMMs) for [Formula: see text] and [Formula: see text] to directly estimate [Formula: see text] given an earthquake scenario and site conditions. Scenario-based [Formula: see text] models are capable of capturing the complex ground-motion effects (e.g. soil non-linearity and regionalization effects) included in their underlying [Formula: see text]/[Formula: see text] GMMs. This approach also ensures the consistency of the [Formula: see text] estimates with a [Formula: see text] design spectrum. In addition, two non-conditional [Formula: see text] GMMs are developed using Bayesian hierarchical regressions. Finally, we present comparisons between the developed models. The comparisons show that if non-conditional GMMs are properly constrained, they are consistent with scenario-based GMMs. The [Formula: see text] GMMs developed in this study advance the performance-based earthquake engineering practice in areas affected by subduction zone earthquakes.

The Pacific Earthquake Engineering Research Center Next Generation Attenuation-West2 database is used to derive a new conditional ground-motion model (CGMM) and a set of scenario-based models for estimating cumulative absolute velocity (CAV) for earthquakes in shallow crustal tectonic settings. Random-effects regressions were performed to develop the conditional model, with random effects across different earthquakes. The estimate of CAV is conditioned on the estimated peak ground acceleration (PGA), the time averaged shear-wave velocity in the top 30 m (VS30), the earthquake magnitude (Mw), and the rupture distance (Rrup). By combining the conditional CAV model with ground-motion models (GMM) in shallow crustal earthquake zones for PGA, new scenario-based models are developed for estimating the median CAV and its standard deviation, directly from an earthquake scenario and site conditions. A scenario-based CAV model captures inherently the complex ground-motion scaling effects included in the GMMs for spectral accelerations on which it is based on, such as, sediment-depth effects, soil nonlinearity effects, and regionalization effects. This approach also ensures consistency between the estimated CAV values and a design spectral acceleration response spectrum. The conditional and scenario-based models to estimate CAV are presented, and trends of the developed scenario-based models and previous traditional models for CAV are compared. Interestingly, we found a remarkable consistency between scenario-based and traditional nonconditional CAV models, when the underlain spectral GMM used in the implementation of the scenario-based model is properly constrained. Finally, we provide examples for the use of the conditional and scenario-based models in performance-based earthquake engineering.

One of the main objectives in engineering seismology or in seismic hazard studies is to estimate the possible ground motion for a given earthquake scenario. In the sparse data regions mostly the ground motion models (GMM) are developed using either seismological models or hybrid empirical approaches. However, if these GMMs do not accommodate the regional seismological attributes, a large uncertainty in ground motion estimates is possible. To overcome this concern, scaling 5% damped Pseudo Spectral Acceleration (PSA) from Fourier amplitude spectra (FAS) proves to be physically consistent as it can capture both spatial and temporal characteristics of the ground motion. Hence, the present study aims to develop a GMM for PSA using FAS and significant duration as the predictor variables. However, since there are few GMMs available for FAS, the current study also aims to develop a GMM for FAS using the earthquake parameters as the predictor variables for intraplate regions. This article employs an Artificial Neural Network (ANN) to develop both GMMs using the Next Generation Attenuation (NGA)‐East database for both horizontal (Effective Amplitude spectra for FAS and RotD50 component for PSA) and vertical components. To verify the performance of the developed models, the residuals analysis and parametric studies have been performed. The parametric study shows that the GMMs can capture the magnitude and distance scaling consistent with the observations. Further, the PSA GMM compared with the global GMMs and it is observed that the predictions lie well within the median of all the available models, proving the models’ effectiveness in estimating the ground motion predictions for future data. The developed model can be used only within the considered ranges of the predicted variables such as rupture distances between [19.05–1000] km, the Mw ranges from [3.12–5.74] with Vs30 in the range of [209–2000] m/s.

In this study, the hybrid empirical method (HEM) was used to develop a new ground-motion model (GMM) for the Gulf Coast of the United States. We used five new empirical GMMs developed by the Pacific Earthquake Engineering Research Center for the Next Generation Attenuation-West2 project to estimate ground-motion intensity measures (GMIMs) in the host region. The new GMM is derived for the horizontal peak ground acceleration and response-spectral ordinates at periods ranging from 0.01 to 10 s, moment magnitudes ranging from M 3.5 to 8.0, and rupture distance (RRUP) as far as 1000 km from the site, although the GMMs are the best constrained for RRUP<300–400 km. The predicted GMIMs are for a reference site defined as the Gulf Coast region hard rock with VS30=3000 m/s and κ0=0.006 s, in which VS30 is the time-averaged shear-wave velocity in the top 30 m of the site profile, and κ0 is the total attenuation of the ground motion as it propagates through the site profile. Seismological parameters used to derive the GMIM stochastic estimates in the Gulf Coast target region are adopted from the most recent research and published information for the region. The seismological parameters for the western North America host region are adopted from Zandieh et al. (2017). The proposed GMM is compared with the Pezeshk et al. (2018) model, which is also a HEM approach, and was developed for central North America and excluded the Gulf Coast region to show the differences between the regions.

Ground Motion Selection and Modification: An Overview of Recent Progress for Building Structures and the Implications for Lifeline Structures

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 , within‐event variability , single‐station within‐event variability , and site‐to‐site variability . 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.

ABSTRACTThe NGA-Sub (subduction zone earthquake) database developed by the Pacific Earthquake Engineering Research center is used to derive new correlation coefficients for a number of ground-motion intensity measure (IM) parameters from ground motions in subduction zone earthquakes, considering both interface and intraslab tectonic settings. The IMs include peak ground acceleration, pseudospectral accelerations with periods from 0.01 to 10 s, Arias intensity, cumulative absolute velocity, peak ground velocity, and significant duration. Comparisons of the estimated correlation coefficients for ground motions from the interface and intraslab tectonic settings generally show a good agreement. Our estimations are also in good agreement with correlation coefficients estimated in previous studies that used ground motions from shallow crustal earthquakes, supporting the concept that any variation in correlation coefficients comes from spectral shape (i.e., the distribution of peaks and troughs) rather than tectonic region. This study also explores the influence of parameters such as magnitude, distance, and site conditions on the estimated correlation coefficients. We did not find apparent trends of the correlation coefficients with respect to these parameters. Finally, we propose analytical models to estimate correlation coefficients between the IMs explored in this study, considering both subduction interface and intraslab tectonic settings.

In this study, we develop ground-motion models (GMMs) for the Island of Hawaii. This area has been the site of several significant earthquake events with a growing database of strong ground-motion observations. Ground-motion modeling on the Island of Hawaii is challenging due to different anelastic attenuation characteristics, the volcanic origin of some of the events, and event depth distribution. Only a few GMMs have been developed for the Island of Hawaii. In this study, we apply a hybrid empirical method (HEM) to develop two separate GMMs for shallow (hypocentral depth ≤ 20 km) and deep (hypocentral depth > 20 km) earthquakes on the Island of Hawaii. We utilize the ratio of the stochastic point-source model in the target and host regions as an appropriate adjustment factor. We apply these adjustment factors to convert the GMMs from the host (western North America) to the target (Island of Hawaii) region. We considered five GMMs proposed in the Next Generation Attenuation Phase 2 project by the Pacific Earthquake Engineering Research Center to model ground motions in the host region. We developed GMMs to predict peak ground acceleration and 5%-damped pseudospectral acceleration at periods T = 0.01–10 s, for moment magnitudes (M) in the range of 3–7.5, and for Joyner–Boore distances in the RJB≤200 km range. The applicability of HEM to develop GMMs for the Island of Hawaii and the growing strong ground-motion data result in further improvements in the capability of GMMs.

This article documents the earthquake ground motion database developed for the NGA‐East Project, initiated as part of the Next Generation Attenuation (NGA) research program and led by the Pacific Earthquake Engineering Research Center (PEER). The project was focused on developing a ground motion characterization model (GMC) model for horizontal ground motions for the large region referred to as Central and Eastern North America (CENA). The CENA region covers most of the U.S. and Canada, from the Rocky Mountains to the Atlantic Ocean and is characterized tectonically as a stable continental region (SCR). The ground‐motion database includes the two‐ and three‐component ground‐motion recordings from numerous selected events relevant to CENA ( M > 2.5, with distances up to 3500 km) that have been recorded since 1976. The final database contains over 27,000 time series from 82 earthquakes and 1271 recording stations. The ground motion database includes uniformly processed time series, 5% damped pseudo‐spectral acceleration (PSA) median‐component ordinates for 429 periods ranging from 0.01 to 10 s, duration and Arias intensity in 5% increments, and Fourier amplitude spectra for different time windows. Ground motions and metadata for source, path, and site conditions were subjected to quality checks by topical working groups and the ground‐motion model (GMM) developers. The NGA‐East database constitutes the largest database of processed recorded ground motions in SRCs and is publicly available from the PEER ground‐motion database website.

Ground-motion models (GMMs) are frequently used in engineering seismology to estimate ground motion intensities. The majority of GMMs predict the response spectral ordinates (such as spectral acceleration) of a single-degree-of-freedom oscillator because of their common application in engineering design practices. Response spectra show how an idealized structure reacts to applied ground motion; however, they do not necessarily represent the physics of ground motion. The functional forms of the response spectra GMMs are built around ideas taken from the Fourier spectral concept. Assuming the validity of Fourier spectral concepts in the response spectral domain could cause physically inexplainable effects. In this study, using a mixed-effects regression technique, we introduce four models capable of predicting the Fourier amplitude spectrum that investigates the impact of incorporating random-effect event and station terms and variations in using a mixed-effects regression technique in one or two steps using truncated dataset or all data (nontruncated dataset). All data consists of 2581 three-component strong ground motion data resulting from 424 events with magnitude ranging from 4.0 up to 7.4, from 1976 to 2020, and 706 stations. The truncated dataset’s records, events, and stations are reduced to 2071, 408, and 636, respectively. As part of this study, we develop GMMs to predict the Fourier amplitude spectrum for the Iranian plateau within the frequency range of 0.3–30 Hz. We adopted simple, functional forms for four models, and we included a limited number of predictors, namely Mw (moment magnitude), Rjb (Joyner–Boore distance), and VS30 (time-averaged shear-wave velocity in the top 30 m). Due to statistical analyses, the style-of-faulting term was excluded from the final functional forms. The robustness of the derived models is indicated by unbiased residual variation with predictor variables.

This study develops data-driven global and region-specific ground-motion models (GMMs) for subduction earthquakes using a weighted average ensemble model to combine four different nonparametric supervised machine-learning (ML) algorithms, including an artificial neural network, a kernel ridge regressor, a random forest regressor, and a support vector regressor. To achieve this goal, we train individual models using a subset of the Next Generation Attenuation-Subduction (NGA-Sub) data set, including 9559 recordings out of 153 interface and intraslab earthquakes recorded at 3202 different stations. A grid search is used to find each model’s best hyperparameters. Then, we use an equally weighted average ensemble approach to combine these four models. Ensemble modeling is a technique that combines the strengths of multiple ML algorithms to mitigate their weaknesses. The ensemble model considers moment magnitude (M), rupture distance (Rrup), time-averaged shear-wave velocity in the upper 30 m (VS30), and depth to the top of the rupture plane (Ztor), as well as tectonic and region as input parameters, and predicts various median orientation-independent horizontal component ground-motion intensity measures such as peak ground displacement, peak ground velocity, peak ground acceleration, and 5%-damped pseudospectral acceleration values at spectral periods of 0.01–10 s in log scale. Although no functional form is defined, the response spectra and the distance and magnitude scaling trends of the weighted average ensemble model are consistent and comparable with the NGA-Sub GMMs, with slightly lower standard deviations. A mixed effects regression analysis is used to partition the total aleatory variability into between-event, between-station, and event-site-corrected components. The derived global GMMs are applicable to interface earthquakes with M 4.9–9.12, 14≤Rrup≤1000 km, and Ztor≤47 km for sites having VS30values between 95 and 2230 m/s. For intraslab events, the derived global GMMs are applicable to M 4.0–8.0, 28≤Rrup≤1000 km, and 30≤Ztor≤200 km for sites having VS30 values between 95 and 2100 m/s.

This document is the final project report of the Next Generation Attenuation for Central and Eastern North America (CENA) project (NGA-East). The NGA-East objective was to develop a new ground-motion characterization (GMC) model for the CENA region. The GMC model consists of a set of new ground-motion models (GMMs) for median and standard deviation of ground motions and their associated weights to be used with logic-trees in probabilistic seismic hazard analyses (PSHA). NGA-East is a large multidisciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER), at the University of California. The project has two components: (1) a set of scientific research tasks, and (2) a model-building component following the framework of the “Seismic Senior Hazard Analysis Committee (SSHAC) Level 3” (Budnitz et al. 1997; NRC 2012). Component (2) is built on the scientific results of component (1) of the NGA-East project. This report documents the tasks under component (2) of the project. Under component (1) of NGA-East, several scientific issues were addressed, including: (a) development of a new database of ground motion data recorded in CENA; (b) development of a regionalized ground-motion map for CENA, (c) definition of the reference site condition; (d) simulations of ground motions based on different methodologies; and (e) development of numerous GMMs for CENA. The scientific tasks of NGA-East were all documented as a series of PEER reports. The scope of component (2) of NGA-East was to develop the complete GMC. This component was designed as a SSHAC Level 3 study with the goal of capturing the ground motions’ center, body, and range of the technically defensible interpretations in light of the available data and models. The SSHAC process involves four key tasks: evaluation, integration, formal review by the Participatory Peer Review Panel (PPRP), and documentation (this report). Key tasks documented in this report include review and evaluation of the empirical ground- motion database, the regionalization of ground motions, and screening sets of candidate GMMs. These are followed by the development of new median and standard deviation GMMs, the development of new analyses tools for quantifying the epistemic uncertainty in ground motions, and the documentation of implementation guidelines of the complete GMC for PSHA computations. Appendices include further documentation of the relevant SSHAC process and additional supporting technical documentation of numerous sensitivity analyses results. The PEER reports documenting component (1) of NGA-East are also considered “attachments” to the current report and are all available online on the PEER website (https://peer.berkeley.edu/). The final NGA-East GMC model includes a set of 17 GMMs defined for 24 ground-motion intensity measures, applicable to CENA in the moment magnitude range of 4.0 to 8.2 and covering distances up to 1500 km. Standard deviation models are also provided for site-specific analysis (single-station standard deviation) and for general PSHA applications (ergodic standard deviation). Adjustment factors are provided for consideration of source-depth effects and hanging-wall effects, as well as for hazard computations at sites in the Gulf Coast region.

Next Generation Attenuation Subduction (NGA-Sub) is a multi-year, multidisciplinary project with the goal of developing an earthquake ground-motion database of processed time series and ground-motion intensity measures (IMs), as well as a suite of ground-motion models (GMMs) for global subduction zone earthquakes. The project considers interface and intraslab earthquakes that have occurred in Japan, Taiwan, New Zealand, Mexico, Central America, South America, Alaska, and Cascadia. This report describes one of the resulting GMMs, one important feature of which is its ability to describe differences in ground motions for different event types and regions. We use a combination of data inspection, regression techniques, ground-motion simulations, and geometrical constraints to develop regionalized models for IMs for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration at 26 oscillator periods from 0.01 to 10 sec. We observe significant differences in ground-motion scaling for interface and intraslab events; therefore, the model terms for source and path effects are developed separately. There are complex distance-scaling effects in the data, including regional variations and forearc and backarc effects. No differences in site effects between the event types were observed; therefore, a combined site term is developed that is taken as the sum (in natural log units) of a linear term conditioned on the time-averaged shear-wave velocity in the upper 30 m (VS30), and an empirically constrained nonlinear term. Basin sediment depth terms are developed for Cascadia and Japan that are conditioned on the depth to the 2.5 km/sec shear-wave velocity horizon (Z2.5). Our approach to model development was to first constrain a path term capturing the observed effects, then to subsequently investigate magnitude scaling, source-depth scaling, and site effects. Regionalized components of the GMM include the model amplitude, anelastic attenuation, magnitude-scaling corner, VS30-scaling, and sediment depth terms. Aleatory variability models are developed that encompass both event types, with different coefficients for each IM. Models are provided for four components of ground-motion variability: (1) between-event variability, Φ ; (2) within-event variability, Φ ; (3) single-station within-event variability, ΦSS ; and (4) site-to-site variability,ΦS2S. The aleatory variability models are magnitude independent. The within-event variability increases with distances beyond 200 km due to complexities in path effects at larger distances. Within-event variability is VS30-dependent for distances less than 200 km, decreasing for softer soils with VS30 less than 500 m/sec. These reductions are attributed to soil nonlinearity. An ergodic analysis 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 (i.e., partially non-ergodic) should use the median GMM at the reference-rock shear-wave velocity (760 m/sec), a site-specific site amplification 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 deviation terms on region-dependent model constant terms, which facilitates scaled-backbone representations of model uncertainty in hazard analyses. Model coefficients are available in the electronic supplement to this report (Tables E1–E4), and coded versions of the model are available in Excel, MatLab, R, and Python from Mazzoni et al. [2020(b)].

Canada’s 2020 national seismic hazard model (CSHM 2020) provides hazard estimates for interface Cascadia Subduction Zone (CSZ) earthquakes in southwestern Canada using four ground motion models (GMMs) with equal weights. Two out of the four GMMs were derived using data primarily from subduction earthquakes in Japan so their use in CSHM 2020 includes a “Japan-to-Cascadia” factor to account for local site conditions. Despite this regional factor, the GMMs do not explicitly consider the amplification effects from the Georgia sedimentary basin below Metro Vancouver. This study benchmarks ground motion shaking from a suite of 30 physics-based simulations of M9 CSZ earthquakes, which explicitly account for basin effects for periods exceeding 1 s, to corresponding estimates from interface GMMs in CSHM 2020. Using this comparison, this study proposes site-specific and period-dependent basin amplification factors for a range of sites located within the Georgia sedimentary basin. The average basin amplification factors at the deepest basin location reach values as high as 2.24 and 6.29 at a 2 s period with respect to basin-edge and outside-basin reference locations, respectively. We evaluate the proposed factors by comparing them against long-period amplifications observed in empirical strong motion recordings from the 2001 M6.8 Nisqually earthquake. A framework to incorporate the proposed basin amplification factors in the calculation of CSHM 2020 uniform hazard spectra (UHS) is also proposed. The modified UHS ordinates at the deepest basin location reach values that are 58% to 271% higher, at a 2 s period, than non-basin UHS estimates when amplification factors are calculated with respect to basin-edge and outside-basin reference locations, respectively.