Empirical Ground Motion Prediction Equations Research Articles

Estimation of Seismic Loss for a Portfolio of Buildings under Bidirectional Horizontal Ground Motions due to a Scenario Cascadia Event

Earthquake ground motions induced by a scenario event are spatially (partially) correlated and (partially) coherent. Simulated ground motion records can be used to carry out nonlinear inelastic time history analysis for a portfolio of buildings to estimate the seismic loss, which is advantageous as there is no need to develop and apply empirical ground motion prediction equations and the ductility demand rules, or to search the scenario compatible recorded records at selected sites that may not exist. Further, if the structures being considered are sensitive to the orientation of the excitation, multiple-component ground motion records are needed. For the simulation of such ground motion records, previous studies have shown that correlation and coherency between any pair of ground motion components need to be incorporated. In this study, the seismic loss of a portfolio of hypothetical buildings in downtown Vancouver under bidirectional horizontal ground motions due to a scenario Cascadia event is estimated by using simulated bidirectional ground motion records that include realistic correlation and coherency characteristics. The hysteretic behaviours of the buildings are described by bidirectional Bouc-Wen model. The results show that the use of unidirectional ground motions and single-degree-of-freedom (SDOF) system structural model may underestimate the aggregated seismic loss.

FinDer v.2: Improved real-time ground-motion predictions for M2–M9 with seismic finite-source characterization

Recent studies suggest that small and large earthquakes nucleate similarly, and that they often have indistinguishable seismic waveform onsets. The characterization of earthquakes in real time, such as for earthquake early warning, therefore requires a flexible modeling approach that allows a small earthquake to become large as fault rupture evolves over time. Here, we present a modeling approach that generates a set of output parameters and uncertainty estimates that are consistent with both small/moderate (≤M6.5) and large earthquakes (>M6.5) as is required for a robust parameter interpretation and shaking forecast. Our approach treats earthquakes over the entire range of magnitudes (>M2) as finite line-source ruptures, with the dimensions of small earthquakes being very small (<100 m) and those of large earthquakes exceeding several tens to hundreds of kilometres in length. The extent of the assumed line source is estimated from the level and distribution of high-frequency peak acceleration amplitudes observed in a local seismic network. High-frequency motions are well suited for this approach, because they are mainly controlled by the distance to the rupturing fault. Observed ground-motion patterns are compared with theoretical templates modeled from empirical ground-motion prediction equations to determine the best line source and uncertainties. Our algorithm extends earlier work by Bose et al. for large finite-fault ruptures. This paper gives a detailed summary of the new algorithm and its offline performance for the 2016 M7.0 Kumamoto, Japan and 2014 M6.0 South Napa, California earthquakes, as well as its performance for about 100 real-time detected local earthquakes (2.2 ≤ M ≤ 5.1) in California. For most events, both the rupture length and the strike are well constrained within a few seconds (<10 s) of the event origin. In large earthquakes, this could allow for providing warnings of up to several tens of seconds. The algorithm could also be useful for resolving fault plane ambiguities of focal mechanisms and identification of rupturing faults for earthquakes as small as M2.5.

Peak ground accelerations from large (M\xa0\u2265\xa07.2) shallow crustal earthquakes: a comparison with predictions from eight recent ground-motion models

Strong-motion data from large (M ≥ 7.2) shallow crustal earthquakes invariably make up a small proportion of the records used to develop empirical ground motion prediction equations (GMPEs). Consequently GMPEs are more poorly constrained for large earthquakes than for small events. In this article peak ground accelerations (PGAs) observed in 38 earthquakes worldwide with M ≥ 7.2 are compared with those predicted by eight recent GMPEs. Well over half of the 38 earthquakes were not considered when deriving these GMPEs but the data were identified by a thorough literature review of strong-motion reports from the past 60 years. These data are provided in an electronic supplement for future investigations on ground motions from large earthquakes. The addition of these data provides better constraint of the between-event ground-motion variability in large earthquakes. It is found that the eight models generally provide good predictions for PGAs from these earthquakes, although there is evidence for slight under- or over-prediction of motions by some models (particularly for M > 7.6). The between-event variabilities predicted by most models match the observed variability, if data from two events (2001 Bhuj and 2005 Crescent City) that are likely atypical of earthquakes in active regions are excluded. For some GMPEs there is evidence that they are over-predicting PGAs in the near-source region of large earthquakes as well as over-predicting motions on hard rock. Overall, however, all the considered models, despite having been derived using limited data, provide reliable predictions of PGAs in the largest crustal earthquakes.

Toward an empirical ground motion prediction equation for France: accounting for regional differences in the source stress parameter

In low-to-moderate seismicity regions such as metropolitan France, characterized by limited strong-motion records in the magnitude-distance range of interest for seismic hazard assessment, the derivation of empirical ground motion prediction equations (GMPEs) is a major challenge. In this study, we take advantage of the RESORCE-2013 database ( http://resorce-portal.eu/ ) that contains uniformly processed records for the Pan-European region including relevant number of French records. After discussing the metadata for French events and stations, we first derive a base-case GMPE that is used to investigate the within-event and between-event residuals. The short-period between-event residuals for French (and Swiss) events show larger variability with respect to larger magnitude events in other regions. We show that the between-event residuals are clearly correlated with the stress parameter and that such larger variability can be explained by accounting for stress-parameter scaling. We derive an empirical scaling of ground motion with stress parameter that is consistent across regions and with the scaling predicted by stochastic GMPEs. This suggests that the scaling of ground motion with stress parameter for a given magnitude is largely region independent whereas the absolute stress parameter values may vary regionally. Based on these results we propose to adopt the scaling model as a function of stress parameter and magnitude by Yenier and Atkinson (Bull Seismol Soc Am 105(4):1989–2009, 2015) by adapting the reference stress parameter to our target regions. By accounting for stress parameter scaling in the GMPE we reduce the between-event variability for French and Swiss small-magnitude events. Finally, we investigate the aleatory variability (σ) of the GMPE and its components (τ, ϕ, ϕss). We propose a heteroscedastic σ model to be used when the stress-parameter scaling is not considered in the GMPEs due to lack of information. If enough information on the stress-parameter is available the adjusted GMPE can be applied using a homoscedastic σ. Despite using small events, the ϕss for French stations is found to be consistent with other studies and confirms the stability of ϕss across different regions and datasets.

Derivation of consistent hard rock (1000\xa0

A key component in seismic hazard assessment is the estimation of ground motion for hard rock sites, either for applications to installations built on this site category, or as an input motion for site response computation. Empirical ground motion prediction equations (GMPEs) are the traditional basis for estimating ground motion while VS30 is the basis to account for site conditions. As current GMPEs are poorly constrained for VS30 larger than 1000 m/s, the presently used approach for estimating hazard on hard rock sites consists of “host-to-target” adjustment techniques based on VS30 and κ0 values. The present study investigates alternative methods on the basis of a KiK-net dataset corresponding to stiff and rocky sites with 500 < VS30 < 1350 m/s. The existence of sensor pairs (one at the surface and one in depth) and the availability of P- and S-wave velocity profiles allow deriving two “virtual” datasets associated to outcropping hard rock sites with VS in the range [1000, 3000] m/s with two independent corrections: 1/down-hole recordings modified from within motion to outcropping motion with a depth correction factor, 2/surface recordings deconvolved from their specific site response derived through 1D simulation. GMPEs with simple functional forms are then developed, including a VS30 site term. They lead to consistent and robust hard-rock motion estimates, which prove to be significantly lower than host-to-target adjustment predictions. The difference can reach a factor up to 3–4 beyond 5 Hz for very hard-rock, but decreases for decreasing frequency until vanishing below 2 Hz.

Stress accumulation in the Marmara Sea estimated through ground‐motion simulations from dynamic rupture scenarios

AbstractWe compare ground motions simulated from dynamic rupture scenarios, for the seismic gap along the North Anatolian Fault under the Marmara Sea (Turkey), to estimates from empirical ground motion prediction equations (GMPEs). Ground motions are simulated using a finite difference method and a 3‐D model of the local crustal structure. They are analyzed at more than a thousand locations in terms of horizontal peak ground velocity. Characteristics of probable earthquake scenarios are strongly dependent on the hypothesized level of accumulated stress, in terms of a normalized stress parameter T. With respect to the GMPEs, it is found that simulations for many scenarios systematically overestimate the ground motions at all distances. Simulations for only some scenarios, corresponding to moderate stress accumulation, match the estimates from the GMPEs. The difference between the simulations and the GMPEs is used to quantify the relative probabilities of each scenario and, therefore, to revise the probability of the stress field. A magnitude Mw7+ operating at moderate prestress field (0.6 &lt; T ≤ 0.7) is statistically more probable, as previously assumed in the logic tree of probabilistic assessment of rupture scenarios. This approach of revising the mechanical hypothesis by means of comparison to an empirical statistical model (e.g., a GMPE) is useful not only for practical seismic hazard assessments but also to understand crustal dynamics.

Application and evaluation of a rapid response earthquake-triggered landslide model to the 25 April 2015 Mw 7.8 Gorkha earthquake, Nepal

The 25 April 2015 Mw 7.8 Gorkha earthquake produced strong ground motions across an approximately 250km by 100km swath in central Nepal. To assist disaster response activities, we modified an existing earthquake-triggered landslide model based on a Newmark sliding block analysis to estimate the extent and intensity of landsliding and landslide dam hazard. Landslide hazard maps were produced using Shuttle Radar Topography Mission (SRTM) digital topography, peak ground acceleration (PGA) information from the U.S. Geological Survey (USGS) ShakeMap program, and assumptions about the regional rock strength based on end-member values from previous studies. The instrumental record of seismicity in Nepal is poor, so PGA estimates were based on empirical Ground Motion Prediction Equations (GMPEs) constrained by teleseismic data and felt reports. We demonstrate a non-linear dependence of modeled landsliding on aggregate rock strength, where the number of landslides decreases exponentially with increasing rock strength. Model estimates are less sensitive to PGA at steep slopes (>60°) compared to moderate slopes (30–60°). We compare forward model results to an inventory of landslides triggered by the Gorkha earthquake. We show that moderate rock strength inputs over estimate landsliding in regions beyond the main slip patch, which may in part be related to poorly constrained PGA estimates for this event at far distances from the source area. Directly above the main slip patch, however, the moderate strength model accurately estimates the total number of landslides within the resolution of the model (landslides≥0.0162km2; observed n=2214, modeled n=2987), but the pattern of landsliding differs from observations. This discrepancy is likely due to the unaccounted for effects of variable material strength and local topographic amplification of strong ground motion, as well as other simplifying assumptions about source characteristics and their relationship to landsliding.

Empirical Correlation between Inelastic and Elastic Spectral Displacement Demands

Inelastic spectral displacement demand is arguably one of the most effective, simplified means of relating earthquake intensity to building damage. However, seismic hazard assessment is typically conducted using empirical ground-motion prediction equations (GMPEs) that only provide indications of elastic spectral response quantities, which an engineer subsequently relates to inelastic demands using empirical relationships such as the equal-displacement rule. An alternative approach is to utilize relationships for the inelastic spectral displacement demand directly within the seismic hazard assessment process. Such empirical relationships are developed in this work, as a function of magnitude, distance, building period, and yield strength coefficient, for four different hysteretic models that are representative of a wide range of possible structural typologies found in practice. The new relationships are likely to be particularly useful for performance-based seismic design and assessment.

Ground‐Motion Prediction Equations for Central and Eastern North America

A new ground‐motion prediction equation (GMPE) model for central and eastern North America (CENA) is presented. The Graizer 2016 (G‐16) model is based on the Next Generation Attenuation‐East (NGA‐East) database for this horizontal peak ground acceleration and 5% damped pseudospectral acceleration RotD50 component (Goulet et al. , 2014). The CENA database is not sufficient for creating purely empirical GMPE with recordings covering mostly a range of moment magnitudes M <6.0 and a limited number of near‐fault recordings. The functional forms of the G‐16 model are derived from filters representing a particular physical phenomenon affecting the seismic‐wave radiation from the source, following the approach developed by Graizer and Kalkan (2007, 2009, and 2011) for active tectonic environment. Main changes in the functional forms for CENA relative to the western United States model (Graizer and Kalkan, 2015) are a shift of maximum frequency of the acceleration response spectrum (RS) toward higher frequencies and an increase in RS amplitudes at high frequencies. The developed site correction is based on multiple runs of representative V S 30 profiles through SHAKE‐type equivalent‐linear codes. Site amplifications are calculated relative to the hard‐rock definition used in nuclear industry ( V S =2800 m/s). The number of model predictors is limited to a few measurable parameters such as moment magnitude M , closest distance to fault rupture plane R rup, V S 30, and anelastic attenuation factor Q . Incorporating Q as an input parameter allows adjustments based on the regional crustal properties. The model is applicable for the stable continental regions and covers the following range: 4.0≤ M ≤8.5, 0≤ R rup≤1000 km, 450≤ V S 30≤2800 m/s, and frequencies 0.1≤ f ≤100 Hz.

Copula‐based joint probability function for PGA and CAV: a case study from Taiwan

SummaryThis study aims to develop a joint probability function of peak ground acceleration (PGA) and cumulative absolute velocity (CAV) for the strong ground motion data from Taiwan. First, a total of 40,385 earthquake time histories are collected from the Taiwan Strong Motion Instrumentation Program. Then, the copula approach is introduced and applied to model the joint probability distribution of PGA and CAV. Finally, the correlation results using the PGA‐CAV empirical data and the normalized residuals are compared. The results indicate that there exists a strong positive correlation between PGA and CAV. For both the PGA and CAV empirical data and the normalized residuals, the multivariate lognormal distribution composed of two lognormal marginal distributions and the Gaussian copula provides adequate characterization of the PGA‐CAV joint distribution observed in Taiwan. This finding demonstrates the validity of the conventional two‐step approach for developing empirical ground motion prediction equations (GMPEs) of multiple ground motion parameters from the copula viewpoint. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Prediction of ground motion parameters for the volcanic area of Mount Etna

Ground motion prediction equations (GMPEs) have been derived for peak ground acceleration (PGA), velocity (PGV), and 5 % damped spectral acceleration (PSA) at frequencies between 0.1 and 10 Hz for the volcanic area of Mt. Etna. The dataset consists of 91 earthquakes with epicentral distances between 0.5 and 100 km. Given the specific characteristics of the area, we divided our data set into two groups: shallow events (SE, focal depth 5 km). The range of magnitude covered by the SE and the DE is 3.0 ≤ M L ≤ 4.3 and 3.0 ≤ M L ≤ 4.8, respectively. Signals of DE typically have more high frequencies than those of SE. These differences are clearly reflected in the empirical GMPEs of the two event groups. Empirical GMPEs were estimated considering several functional forms: Sabetta and Pugliese (Bull Seism Soc Am 77:1491–1513, 1987) (SP87), Ambraseys et al. (Earth Eng Struct Dyn 25:371–400, 1996) (AMB96), and Boore and Atkinson (Earth Spectra 24:99–138, 2008) (BA2008). From ANOVA, we learn that most of the errors in our GMPEs can be attributed to unmodeled site effects, whereas errors related to event parameters are limited. For DE, BA2008 outperforms the simpler models SP87 or AMB96. For SE, the simple SP87 is preferable considering the Bayesian Information Criterion since it proves more stable with respect to confidence and gives very similar or even lower prediction errors during cross-validation than the BA2008 model. We compared our results to relationships derived for Italy (ITA10, Bindi et al. Bull Earth Eng 99:2471–2488, 2011). For SE, the main differences are observed for distances greater than about 5 km for both horizontal and vertical PGAs. Conversely, for DE the ITA10 heavily overestimates the peak ground parameters for short distances.

Evaluation of the recorded ground motions for the unusual earthquake of 13 August 2006 (M w 5.3) in Michoacán México

The focal mechanism of the moderate earthquake of 13 August 2006 Mw = 5.3, which occurred in the border coastal area between Michoacan and Colima, Mexico, is unusual. As shown by the Global Centroid Moment Tensor (CMT) project and the Servicio Sismologico Nacional de Mexico (SSN), the thrust mechanism is striking almost perpendicularly to the majority of earthquakes occurring along the subduction zone of the Mexican Pacific continental margin which commonly strike nearly parallel to the trench. The purpose of this study is to analyze the observed ground motions of this particular event relative to those of the common events. First, we apply the H/V technique to verify that the stations involved in this study are nearly free of site effects. Then, we compare the observed ground motions with (i) three empirical ground motion prediction equations (GMPEs) appropriate for the region, (ii) ground motions of four real earthquakes with the common mechanism, and (iii) the Fourier spectrum of a selected common event.

Stochastic Simulation of Strong‐Motion Records from the 2012 Ahar–Varzaghan Dual Earthquakes, Northwest of Iran

Here, the generalized inversion of S ‐wave amplitude spectra is employed for deriving the site response and S ‐wave attenuation (quality factor) in the northwest region of Iran. A total of 279 strong‐motion accelerograms recorded at distances below 200 km from 41 earthquakes with moment magnitudes ranging from M w 3.8 to 6.5 are used to determine the region‐specific attenuation model. The site responses have been determined for all 54 stations individually. The bulk of strong‐motion data (i.e., 184 records) comes from the 2012 Ahar–Varzaghan dual earthquakes in northwest Iran and their aftershocks. Also, the modified finite‐fault method, which is able to model nonuniform stress distribution on the fault plane, is employed to investigate the coseismic stress parameter for the first and second Ahar–Varzaghan dual earthquakes by minimizing the difference between the synthesized and observed pseudospectral accelerations for 5% damping. Results denote a concentration of stress drops on the northwestern part of the first event’s fault and on the central and eastern part of the second fault. Stochastic simulations, using the calibrated stress distribution have been performed on a regular grid covering the study area for both rock‐ and soil‐site conditions (in total, 651 points). The results show that the maximum of peak ground accelerations (PGAs) during the Ahar–Varzaghan dual earthquakes for the rock‐site condition reached 557 cm/s/s, and the largest peak ground velocities (PGVs) were estimated around 76 cm/s. In general, comparisons between simulated data and empirical ground‐motion prediction equations (GMPEs) show that the stochastic predictions (PGAs and PGVs) are higher than those predicted by the empirical GMPEs for distances less than 30 km and are smaller for distances more than 30 km. The simulated data are also consistent with the modified Mercalli intensity observations and show reasonable agreement. This can be considered as another validation of the method.

Ground motion selection for simulation‐based seismic hazard and structural reliability assessment

SummaryThis paper examines four methods by which ground motions can be selected for dynamic seismic response analyses of engineered systems when the underlying seismic hazard is quantified via ground motion simulation rather than empirical ground motion prediction equations. Even with simulation‐based seismic hazard, a ground motion selection process is still required in order to extract a small number of time series from the much larger set developed as part of the hazard calculation. Four specific methods are presented for ground motion selection from simulation‐based seismic hazard analyses, and pros and cons of each are discussed via a simple and reproducible illustrative example. One of the four methods (method 1 ‘direct analysis’) provides a ‘benchmark’ result (i.e., using all simulated ground motions), enabling the consistency of the other three more efficient selection methods to be addressed. Method 2 (‘stratified sampling’) is a relatively simple way to achieve a significant reduction in the number of ground motions required through selecting subsets of ground motions binned based on an intensity measure, IM. Method 3 (‘simple multiple stripes’) has the benefit of being consistent with conventional seismic assessment practice using as‐recorded ground motions, but both methods 2 and 3 are strongly dependent on the efficiency of the conditioning IM to predict the seismic responses of interest. Method 4 (‘generalized conditional intensity measure‐based selection’) is consistent with ‘advanced’ selection methods used for as‐recorded ground motions and selects subsets of ground motions based on multiple IMs, thus overcoming this limitation in methods 2 and 3. Copyright © 2015 John Wiley &amp; Sons, Ltd.

A SSHAC Level 3 Probabilistic Seismic Hazard Analysis for a New-Build Nuclear Site in South Africa

A probabilistic seismic hazard analysis has been conducted for a potential nuclear power plant site on the coast of South Africa, a country of low-to-moderate seismicity. The hazard study was conducted as a SSHAC Level 3 process, the first application of this approach outside North America. Extensive geological investigations identified five fault sources with a non-zero probability of being seismogenic. Five area sources were defined for distributed seismicity, the least active being the host zone for which the low recurrence rates for earthquakes were substantiated through investigations of historical seismicity. Empirical ground-motion prediction equations were adjusted to a horizon within the bedrock at the site using kappa values inferred from weak-motion analyses. These adjusted models were then scaled to create new equations capturing the range of epistemic uncertainty in this region with no strong motion recordings. Surface motions were obtained by convolving the bedrock motions with site amplification functions calculated using measured shear-wave velocity profiles.

Referenced Empirical Ground-Motion Model for Eastern North America

ABSTRACT We update ground‐motion prediction equations (GMPEs) for eastern North America (ENA) using the referenced empirical approach of Atkinson (2008). The technique is based on the use of residual analysis that models differences between regional ground‐motion observations and a reference GMPE developed for a data‐rich region. The update is timely because the Next Generation Attenuation‐West 2 GMPEs for shallow crustal earthquakes in active tectonic regions enable a significant improvement in the implementation of this model, relative to previous work (e.g., Atkinson and Boore, 2011). The predicted ground‐motion amplitudes of the ENA referenced empirical model are very similar to the equivalent California values of Boore et al. (2014; hereafter BSSA14) at close distances ( R ≤50 km), at low‐to‐moderate frequencies ( f ≤5 Hz). At regional distances ( R >50 km) and at high frequencies ( f >5 Hz), the ENA data suggest higher ground‐motion amplitudes than the BSSA14 reference model, presumably due to lower attenuation and higher stress for ENA events relative to those in active tectonic regions. We also show that the referenced empirical approach predicts ground motions that are consistent with those that would be produced by the hybrid empirical approach (Campbell, 2003), considering recent equivalent point‐source models that match both ENA and California ground‐motion databases. Comparison between the referenced empirical GMPE of this study (HA14) and the stochastic GMPE of Atkinson and Boore (2006, 2011; denoted AB06′) shows that both models imply similar attenuation shape at all frequencies. For M 7 at R ≤50 km, the HA14 model predicts relatively smaller ground‐motion amplitudes than does the AB06′ model, likely because of the greater saturation effects in the empirical BSSA14 reference model.

Comparing the CENA GMPEs Using NGA-East Ground-Motion Database

Online Material: Tables and figures of GMPE parameters, NGA‐East database summary statistics, mean residuals, skewness and kurtosis, results from log‐likelihood analysis, and ranking. A number of ground‐motion prediction equations (GMPEs) have been introduced in recent years that are redefining the state of practice for probabilistic seismic‐hazard analysis (PSHA) in many earthquake‐prone regions worldwide. For example, the Next Generation Attenuation (NGA)‐East is developing a new ground‐motion characterization (GMC) model for the central and eastern North American (CENA) region. The GMC model will consist of a set of new GMPEs for median and standard deviation of ground motions and their associated weights in the logic trees for use in PSHA. An example is the empirical GMPE by Al Noman (2013). GMPEs are developed for specific tectonic environments using multivariate regression on ground‐motion databases, and the relationships are updated as more earthquake data are obtained (Kramer, 1996; Abrahamson and Shedlock, 1997). Because of the improvement of seismological networks, and increasing size and quality of ground‐motion databases, the number of proposed ground‐motion models has increased significantly in the last decade to reflect the seismological features of the seismic‐prone regions worldwide, that is, Douglas (2011) gives 289 empirical GMPEs for PGA and 188 models for the prediction of elastic response spectral ordinates. The NGA‐East project has developed an updated database of CENA ground motions (Cramer et al. , 2009, 2010, 2013) containing over 11,000 records and covering distance and magnitude ranges of 1–3500 km and M w 2.2–7.6, but mostly less than M w 6.0 (Fig. 1). The selection of candidate GMPEs, especially the assignment of logic‐tree weights, and selecting appropriate predictive models to calculate hazard in a site (or a region) of interest has become a popular topic in engineering seismology. The ground shaking in the target region must be well reflected …

CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning

Real-time applications such as earthquake early warning (EEW) typically use empirical ground-motion prediction equations (GMPEs) along with event magnitude and source-to-site distances to estimate expected shaking levels. In this simplified approach, effects due to finite-fault geometry, directivity and site and basin response are often generalized, which may lead to a significant under- or overestimation of shaking from large earthquakes (M > 6.5) in some locations. For enhanced site-specific ground-motion predictions considering 3-D wave-propagation effects, we develop support vector regression (SVR) models from the SCEC CyberShake low-frequency ( 415 000 finite-fault rupture scenarios (6.5 ≤ M ≤ 8.5) for southern California defined in UCERF 2.0. We use CyberShake to demonstrate the application of synthetic waveform data to EEW as a ‘proof of concept’, being aware that these simulations are not yet fully validated and might not appropriately sample the range of rupture uncertainty. Our regression models predict the maximum and the temporal evolution of instrumental intensity (MMI) at 71 selected test sites using only the hypocentre, magnitude and rupture ratio, which characterizes uni- and bilateral rupture propagation. Our regression approach is completely data-driven (where here the CyberShake simulations are considered data) and does not enforce pre-defined functional forms or dependencies among input parameters. The models were established from a subset (∼20 per cent) of CyberShake simulations, but can explain MMI values of all >400 k rupture scenarios with a standard deviation of about 0.4 intensity units. We apply our models to determine threshold magnitudes (and warning times) for various active faults in southern California that earthquakes need to exceed to cause at least ‘moderate’, ‘strong’ or ‘very strong’ shaking in the Los Angeles (LA) basin. These thresholds are used to construct a simple and robust EEW algorithm: to declare a warning, the algorithm only needs to locate the earthquake and to verify that the corresponding magnitude threshold is exceeded. The models predict that a relatively moderate M6.5–7 earthquake along the Palos Verdes, Newport-Inglewood/Rose Canyon, Elsinore or San Jacinto faults with a rupture propagating towards LA could cause ‘very strong’ to ‘severe’ shaking in the LA basin; however, warning times for these events could exceed 30 s.

Evaluating the Compatibility of Dynamic Rupture-Based Synthetic Ground Motion with Empirical Ground-Motion Prediction Equation

We performed an assessment of a database of synthetic ground motion generated by a suite of dynamic rupture simulations to verify compatibility of the peak ground amplitudes with respect to empirical ground‐motion prediction equations (GMPEs). The dynamic rupture model database, developed by Dalguer and Mai (2011), is composed of 360 earthquake scenarios with moment magnitudes in the range of 5.5–7, for three mechanisms of faulting (reverse, normal, and strike slip) and for both buried faults and surface rupturing faults, having depth‐ and non‐depth‐dependent normal stresses. Initial shear‐stress distribution follows a von Karman stochastic distribution. Overall, we show quantitatively that the upper frequency limit of the suite of simulations is 1.0 Hz. Up to this frequency, the synthetic data are compatible with the empirical model, which means that the residuals (defined as the differences between observed and predicted ground motions) fall in the range of ± σ of the empirical GMPE. Characteristics of the mean values along distance (10–45 km) and period T ≥1.0 s, including standard deviation of the synthetic response spectra and peak ground velocity, are comparable to their counterpart empirical GMPE. At very near source (<1–2 km), synthetics show supersaturation of the mean peak values, which is different from the saturation features predicted by the GMPEs. The effect of source parameters (such as stress drop, peak slip velocity, and rupture speed) and of surface and buried rupture, as well as hanging wall and footwall, are highly sensitive to ground motion, suggesting that these effects contribute to the variability of ground motion near the source and that inclusion of them in the source terms may contribute to reducing uncertainties in GMPEs.

Fourier spectral- and duration models for the generation of response spectra adjustable to different source-, propagation-, and site conditions

One of the major challenges related with the current practice in seismic hazard studies is the adjustment of empirical ground motion prediction equations (GMPEs) to different seismological environments. We believe that the key to accommodating differences in regional seismological attributes of a ground motion model lies in the Fourier spectrum. In the present study, we attempt to explore a new approach for the development of response spectral GMPEs, which is fully consistent with linear system theory when it comes to adjustment issues. This approach consists of developing empirical prediction equations for Fourier spectra and for a particular duration estimate of ground motion which is tuned to optimize the fit between response spectra obtained through the random vibration theory framework and the classical way. The presented analysis for the development of GMPEs is performed on the recently compiled reference database for seismic ground motion in Europe (RESORCE-2012). Although, the main motivation for the presented approach is the adjustability and the use of the corresponding model to generate data driven host-to-target conversions, even as a standalone response spectral model it compares reasonably well with the GMPEs of Ambraseys et al. (Bull Earthq Eng 3:1–53, 2005), Akkar and Bommer (Seismol Res Lett 81(2):195–206, 2010) and Akkar and Cagnan (Bull Seismol Soc Am 100(6):2978–2995, 2010).