Ground-motion models for Vrancea intermediate-depth earthquakes

2021 ◽  
pp. 875529302110329
Author(s):  
Elena Florinela Manea ◽  
Carmen Ortanza Cioflan ◽  
Laurentiu Danciu
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Seismic Station ◽  
Moment Magnitude ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Ground Shaking ◽  
Intermediate Depth ◽  
Motion Models ◽  
Ground Motion Models

A newly compiled high-quality ground-shaking dataset of 207 intermediate-depth earthquakes recorded in the Vrancea region of the south-eastern Carpathian mountains in Romania was used to develop region-specific empirical predictive equations for various intensity measures: peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration up to 10 s. Besides common predictor variables (e.g. moment magnitude, depth, hypocentral distance, and site conditions), additional distance scaling parameters were added to describe the specific attenuation pattern observed at the stations located not only on the back and fore but also along the Carpathian arc. In this model, we introduce a proxy measure for the site as the fundamental frequency of resonance to characterize the site response at each recording seismic station beside the soil classes. To additionally reduce the site-to-site variability, a non-ergodic methodology was considered, resulting in a lower standard deviation of about 25%. Statistical evaluation of the newly proposed ground-motion models indicates robust performance compared to regional observations. The model shows significant improvements in describing the spatial variability (at different spectral ordinates), particularly for the fore-arc area of the Carpathians where a deep sedimentary basin is located. Furthermore, the model presented herein improves estimates of ground shaking at longer spectral ordinates (>1 s) in agreement with the observations. The proposed ground-motion models are valid for hypocentral distances less than 500 km, depths over 70 km and within the moment magnitude range of 4.0–7.4.

NGA-subduction global ground motion models with regional adjustment factors

2021 ◽  
pp. 875529302110348
Author(s):  
Grace A Parker ◽  
Jonathan P Stewart ◽  
David M Boore ◽  
Gail M Atkinson ◽  
Behzad Hassani
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Epistemic Uncertainty ◽  
Peak Ground Velocity ◽  
Earthquake Ground Motion ◽  
Motion Models ◽  
Magnitude Scaling ◽  
Aleatory Variability ◽  
Single Station ◽  
Ground Motion Models

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.

Localizing Ground-Motion Models in Volcanic Terranes: Shallow Events at Mt. Etna, Italy, Revisited

2020 ◽  
Vol 110 (6) ◽  
pp. 2843-2861
Author(s):  
Giuseppina Tusa ◽  
Horst Langer ◽  
Raffaele Azzaro
Keyword(s):  
Ground Motion ◽  
Hazard Analysis ◽  
Total Error ◽  
Scaling Law ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Hypocentral Distance ◽  
Motion Models ◽  
Mt Etna ◽  
Ground Motion Models

ABSTRACT We present a set of revised ground-motion models (GMMs) for shallow events at Mt. Etna Volcano. The recent occurrence of damaging events, in particular two of the strongest earthquakes ever instrumentally recorded in the area, has required revising previous GMMs, as these failed to match the observations made for events with local magnitude ML>4.3, above all for sites situated close to the epicenter. The dataset now includes 49 seismic events, with a total of 1600 time histories recorded at distances of up to 100 km, and ML ranging from 3.0 to 4.8. The model gives estimates of peak ground acceleration (both horizontal and vertical), peak ground velocity (both horizontal and vertical), and 5% damped horizontal pseudoacceleration response spectral ordinates up to a period of 4 s. GMMs were developed using the functional form proposed by Boore and Atkinson (2008). Furthermore, with a slightly modified approach, we also considered a regression model using a pseudodepth (h) depending on magnitude according to the scaling law by Azzaro et al. (2017). Both models were applied to hypocentral distance ranges of up to 60 km and up to 100 km, respectively. From the statistical analysis, we found that reducing the maximum distance from the event up to 60 km and introducing a magnitude-dependent pseudodepth improved the model in terms of total error. We compared our results with those derived using the GMMs for shallow events at Mt. Etna found by Tusa and Langer (2016) and for volcanic areas by Lanzano and Luzi (2019). The main differences are observed at short epicentral distances and for higher magnitude events. The use of variable pseudodepth avoids sharp peaks of predicted ground-motion parameters around the epicenter, preventing instabilities when using a GMM in probabilistic seismic hazard analysis.

Ground-Motion Prediction Model Based on Neural Networks to Extract Site Properties from Observational Records

2021 ◽  
Author(s):  
Tomohisa Okazaki ◽  
Nobuyuki Morikawa ◽  
Asako Iwaki ◽  
Hiroyuki Fujiwara ◽  
Tomoharu Iwata ◽  
...  
Keyword(s):  
Ground Motion ◽  
Ground Acceleration ◽  
Site Specific ◽  
Motion Data ◽  
Motion Models ◽  
Proposed Model ◽  
Single Station ◽  
Input Variables ◽  
Ground Condition ◽  
Ground Motion Models

ABSTRACT Choosing the method for inputting site conditions is critical in reducing the uncertainty of empirical ground-motion models (GMMs). We apply a neural network (NN) to construct a GMM of peak ground acceleration that extracts site properties from ground-motion data instead of referring to ground condition variables given for each site. A key structure of the model is one-hot representations of the site ID, that is, specifying the collection site of each ground-motion record by preparing input variables corresponding to all observation sites. This representation makes the best use of the flexibility of NN to obtain site-specific properties while avoiding overfitting at sites where a small number of strong motions have been recorded. The proposed model exhibits accurate and robust estimations among several compared models in different aspects, including data-poor sites and strong motions from large earthquakes. This model is expected to derive a single-station sigma that evaluates the residual uncertainty under the specification of estimation sites. The proposed NN structure of one-hot representations would serve as a standard ingredient for constructing site-specific GMMs in general regions.

NGA-Subduction research program

2021 ◽  
pp. 875529302110560
Author(s):  
Yousef Bozorgnia ◽  
Norman A Abrahamson ◽  
Sean K Ahdi ◽  
Timothy D Ancheta ◽  
Linda Al Atik ◽  
...  
Keyword(s):  
Ground Motion ◽  
Research Program ◽  
Epistemic Uncertainty ◽  
Specific Model ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Motion Data ◽  
Motion Models ◽  
Aleatory Variability ◽  
Adjustment Factors

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.

Residual analysis of large strong-motion flatfiles as a tool for detecting data error and anomalies

2021 ◽  
Author(s):  
Claudia Mascandola ◽  
Giovanni Lanzano ◽  
Francesca Pacor
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Epistemic Uncertainty ◽  
Strong Motion ◽  
Consistency Check ◽  
Mixed Effect ◽  
Motion Models ◽  
Tree Classifier ◽  
The Common ◽  
Ground Motion Models

<p>The rapid increase of seismic waveforms, due to the increment of seismic stations and continuous real-time streaming to data centres, leads to the need for automatic procedures aimed at supporting data processing and data quality control. In this study, we propose a semi-automatic procedure for the consistency check of large strong-motion datasets, classifying the anomalies observed on the residuals analysis and identifying the possible causes.</p><p>The data collected in the strong-motion databases are usually arranged as parametric tables (called flatfiles), used to disseminate the Intensity Measures (IMs) and the associated metadata of the processed waveforms. This is the current practice for the ITalian ACcelerometric Archive (ITACA, D’Amico et al., 2020) and Engineering Strong Motion (ESM; Lanzano et al. 2019a) databases. The adopted criteria for flatfile compilation are designed to collect IMs and related metadata in a uniform, updated, and traceable way, with the aim of providing datasets useful to develop Ground Motion Models (GMMs) for Probabilistic Seismic Hazard Assessment (PSHA) and engineering applications. Therefore, the consistency check of the flatfiles is a crucial task to improve the quality of the products provided by the waveform services.</p><p>The proposed procedure is based on the residual distributions obtained from ad-hoc ground motion prediction equations for the ordinates of the 5% damped acceleration response spectra. In this study, we focus on the active shallow crust events in ITACA, considering the ITA18 ground motion model (Lanzano et al., 2019b) as a reference for Italy. The total residuals, computed as logarithm difference between observations and predictions, are decomposed in between-event, between-station and event-and-station corrected residuals by applying a mixed-effect regression (Bates et al., 2015). This is the common practice for the (partial) removal of the ergodic assumption in empirical GMMs (e.g., Stafford 2014), where the contribution of the systematic corrective effects of event and station on aleatory variability are identified and shifted to the epistemic uncertainty. Afterward, the proposed procedure is applied to raise a warning in case of anomalous residual values. Warnings are provided when the normalized residuals exceed a certain threshold, in three ranges of periods (i.e., 0.01-0.15 s, 0.15-1 s, 1-5 s). The causes of warnings may be several and may concern the event, the site, the waveform, or a combination of them. Among the possible sources of anomalous trends, the more common are: preliminary or inaccurate event localization or magnitude, wrong soil category assigned based on proxies, misleading tectonic regime assigned to the earthquake, and fault directivity that may cause strong-ground motion amplification in certain directions. Warnings may also raise for peculiarities in the site-response (e.g., large amplifications/de-amplifications at certain frequency-bands) and to the occurrence of near-source effects in the waveforms (see Pacor et al., 2018). Based on the raised warnings, a decision tree classifier is developed to identify the common anomaly sources and to support the consistency check of the semi-automatic procedure.</p><p>This study may help to enhance the waveform services and related products, besides reducing the variability of ground motion models and guiding decisions for site characterization studies and network maintenance.</p>

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

2020 ◽  
Author(s):  
David M. Boore ◽  
Jonathan P. Stewart ◽  
Andreas A. Skarlatoudis ◽  
Emel Seyhan ◽  
Basil Margaris ◽  
...  
Keyword(s):  
Prediction Model ◽  
Ground Motion ◽  
Site Response ◽  
Epistemic Uncertainty ◽  
Peak Ground Velocity ◽  
Motion Prediction ◽  
Ground Motion Prediction ◽  
Ground Acceleration ◽  
Magnitude Scaling ◽  
Nonlinear Site Response

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.

Ground Motion Prediction Equations for the Vertical Ground Motion Component Based on the NGA-W2 Database

2017 ◽  
Vol 33 (2) ◽  
pp. 499-528 ◽  
Author(s):  
Zeynep Gülerce ◽  
Ronnie Kamai ◽  
Norman A. Abrahamson ◽  
Walter J. Silva
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Vertical Component ◽  
Weighted Average ◽  
Motion Models ◽  
Nonlinear Site Response ◽  
Vertical Ground Motion ◽  
Vertical Ground ◽  
Standard Deviations ◽  
Ground Motion Models

Empirical ground motion models for the vertical component from shallow crustal earthquakes in active tectonic regions are derived using the PEER NGA-West2 database. The model is applicable to magnitudes 3.0–8.0, distances of 0–300 km, and spectral periods of 0–10 s. The model input parameters are the same as used by Abrahamson et al. (2014) except that the nonlinear site response and depth to bedrock effects are evaluated but found to be insignificant. Regional differences in large distance attenuation and site amplification scaling between California, Japan, China, Taiwan, Italy, and the Middle East are included. Scaling for the hanging-wall effect is incorporated using the constraints from numerical simulations by Donahue and Abrahamson (2014) . The standard deviation is magnitude dependent with smaller magnitudes leading to larger standard deviations at short periods but smaller standard deviations at long periods. The vertical ground motion model developed in this study can be paired with the horizontal component model proposed by Abrahamson et al. (2014) to produce a V/H ratio. For applications where the horizontal spectrum is derived from the weighted average of several horizontal ground motion models, a V/H model derived directly from the V/H data (such as Gülerce and Abrahamson 2011 ) should be preferred.

scholarly journals Characteristics of strong ground motion attenuation in the 2019 Mw 5.8 Changning earthquake, Sichuan, China

2021 ◽  
Author(s):  
J. J. Hu ◽  
H. Zhang ◽  
J. B. Zhu ◽  
G. H. Liu
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Response Spectra ◽  
Peak Ground Velocity ◽  
Arias Intensity ◽  
Ground Acceleration ◽  
Motion Models ◽  
Ground Motion Attenuation ◽  
Short Period ◽  
Strong Ground

AbstractA moderate magnitude earthquake with Mw 5.8 occurred on June 17, 2019, in Changning County, Sichuan Province, China, causing 13 deaths, 226 injuries, and serious engineering damage. This earthquake induced heavier damage than earthquakes of similar magnitude. To explain this phenomenon in terms of ground motion characteristics, based on 58 sets of strong ground motions in this earthquake, the peak ground acceleration (PGA), peak ground velocity (PGV), acceleration response spectra (Sa), duration, and Arias intensity are analyzed. The results show that the PGA, PGV, and Sa are larger than the predicted values from some global ground motion models. The between-event residuals reveal that the source effects on the intermediate-period and long-period ground motions are stronger than those on short-period ground motions. Comparison of Arias intensity attenuation with the global models indicates that the energy of ground motions of the Changning earthquake is larger than those of earthquakes with the same magnitude.

Arias Intensity Conditional Scaling Ground‐Motion Models for Subduction Zones

2019 ◽  
Vol 109 (4) ◽  
pp. 1343-1357 ◽  
Author(s):  
Jorge Macedo ◽  
Norman Abrahamson ◽  
Jonathan D. Bray
Keyword(s):  
Ground Motion ◽  
Subduction Zones ◽  
Spectral Acceleration ◽  
Scaling Effects ◽  
Arias Intensity ◽  
Ground Acceleration ◽  
Earthquake Scenario ◽  
Motion Models ◽  
Conditional Models ◽  
Ground Motion Models

Abstract Conditional ground‐motion models (CGMMs) for estimating Arias intensity (IA) for earthquakes in subduction zones are developed. The estimate of IA is conditioned in these models on the estimated peak ground acceleration (PGA), the spectral acceleration at T=1  s (SA1), time‐averaged shear‐wave velocity in the top 30 m (VS30), and magnitude (Mw). Random‐effects regressions are used to develop CGMMs for Japan, Taiwan, South America, and New Zealand. By combining the conditional models of IA with the ground‐motion models (GMMs) for PGA and SA1, the conditional models are converted to scenario‐based GMMs that can be used to estimate the median IA and its standard deviation directly for a given earthquake scenario and site conditions. The conditional scaling approach ensures the estimated IA values are consistent with a design spectrum that may correspond to above‐average spectral values for the controlling scenario. In addition, this approach captures the complex ground‐motion scaling effects found in GMMs for spectral acceleration, such as sediment‐depth effects, soil nonlinearity effects, and regionalization effects, in the developed scenario‐based models for IA. Estimates from the new scenario‐based IA models are compared to those from traditional GMMs for IA in subduction zones.

scholarly journals Regional broad-band ground-shaking modelling over extended and thick sedimentary basins: an example from the Lower Rhine Embayment (Germany)

2020 ◽  
Author(s):  
Marco Pilz ◽  
Fabrice Cotton ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Graeme Weatherill ◽  
Thomas Spies
Keyword(s):  
Ground Motion ◽  
Broad Band ◽  
Soft Rock ◽  
Sedimentary Basins ◽  
Response Spectra ◽  
Site Specific ◽  
Ground Shaking ◽  
Motion Models ◽  
Ground Motion Models ◽  
Lower Rhine Embayment

AbstractThe simulation of broad-band (0.1 to 10 + Hz) ground-shaking over deep and spatially extended sedimentary basins at regional scales is challenging. We evaluate the ground-shaking of a potential M 6.5 earthquake in the southern Lower Rhine Embayment, one of the most important areas of earthquake recurrence north of the Alps, close to the city of Cologne in Germany. In a first step, information from geological investigations, seismic experiments and boreholes is combined for deriving a harmonized 3D velocity and attenuation model of the sedimentary layers. Three alternative approaches are then applied and compared to evaluate the impact of the sedimentary cover on ground-motion amplification. The first approach builds on existing response spectra ground-motion models whose amplification factors empirically take into account the influence of the sedimentary layers through a standard parameterization. In the second approach, site-specific 1D amplification functions are computed from the 3D basin model. Using a random vibration theory approach, we adjust the empirical response spectra predicted for soft rock conditions by local site amplification factors: amplifications and associated ground-motions are predicted both in the Fourier and in the response spectra domain. In the third approach, hybrid physics-based ground-motion simulations are used to predict time histories for soft rock conditions which are subsequently modified using the 1D site-specific amplification functions computed in method 2. For large distances and at short periods, the differences between the three approaches become less notable due to the significant attenuation of the sedimentary layers. At intermediate and long periods, generic empirical ground-motion models provide lower levels of amplification from sedimentary soils compared to methods taking into account site-specific 1D amplification functions. In the near-source region, hybrid physics-based ground-motions models illustrate the potentially large variability of ground-motion due to finite source effects.

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