Southern California Earthquake Center Research Articles

INFLUENCE OF HILLS AND VALLEYS ON FREE SURFACE SLIP AMPLIFICATION IN DYNAMIC RUPTURE ON A DIPPING FAULT

Dynamic rupture scenarios on various fault geometries are studied extensively in the literature for domains with the planar top surface. However, landscapes on the earth, particularly in tectonic regimes, can undulate upwards or downwards depending on faulting conditions. In this paper, we studied a dipping fault model with a dip fault angle of 60 degrees, inspired by the 2D version of dynamic rupture benchmark TPV10 from the Southern California Earthquake Center (SCEC). A topographic feature adjacent to the fault is introduced in the form of a hill or a valley. The shape of the undulation was varied from semi-circular form to Gaussian profile. This paper examines the impact of topographic features (valleys or hills) on slip amplitude on a fault. The distance at which the features exist also affects the amount of slip on fault, ruptured in that region. The results for a couple of different radii of semi-circular formation and equivalent standard deviation of Gaussian undulation are also summarized in this paper. The study depicts that the topography in the vicinity of the fault can affect the magnitude of slip propagation on fault surface.

A machine learning estimator trained on synthetic data for real-time earthquake ground-shaking predictions in Southern California

After large-magnitude earthquakes, a crucial task for impact assessment is to rapidly and accurately estimate the ground shaking in the affected region. To satisfy real-time constraints, intensity measures are traditionally evaluated with empirical Ground Motion Models that can drastically limit the accuracy of the estimated values. As an alternative, here we present Machine Learning strategies trained on physics-based simulations that require similar evaluation times. We trained and validated the proposed Machine Learning-based Estimator for ground shaking maps with one of the largest existing datasets (<100M simulated seismograms) from CyberShake developed by the Southern California Earthquake Center covering the Los Angeles basin. For a well-tailored synthetic database, our predictions outperform empirical Ground Motion Models provided that the events considered are compatible with the training data. Using the proposed strategy we show significant error reductions not only for synthetic, but also for five real historical earthquakes, relative to empirical Ground Motion Models.

Basin effects from 3D simulated ground motions in the Greater Los Angeles region for use in seismic hazard analyses

We develop basin-depth-scaling models (i.e. “basin terms”) from the long-period ([Formula: see text]) simulated ground motions of the Southern California Earthquake Center (SCEC) CyberShake project for use in seismic hazard analyses at sites within the sedimentary basins of southern California. Basin terms use the Next Generation Attenuation (NGA)-West-2 ground-motion models (GMMs) as reference models and use their functional forms with slight modifications. We investigate the use of two approaches to incorporate the time-averaged shear-wave velocity in the upper 30 m ([Formula: see text]) in these calculations and find that the use of site-specific and uniform [Formula: see text] has minor effects on the resulting basin terms for this data set. By centering the simulated ground motions on the basin terms, we separate the information from the simulations about absolute ground-motion level from information relating to the relative amplifications, such as the differences between shallow- and deep-basin sites. Recent observations from sedimentary basins of southern California indicate that additional amplification effect may persist at relatively shallow basin depths (i.e. the GMM basin terms should have positive values when differential depths, [Formula: see text], are near zero), and we present models for “centered” and “adjusted” basin-depth scaling models that reflect this potential. The simulation-modified GMMs are appropriate for crustal sources and for deep-basin sites ([Formula: see text]) within basins of the Greater Los Angeles region, for the magnitudes and distances defined by each of the reference NGA-West-2 GMMs.

Broadband Ground-Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation

ABSTRACT We present a data-driven framework for ground-motion synthesis that generates three-component acceleration time histories conditioned on moment magnitude (M), rupture distance (Rrup), time-average shear-wave velocity at the top 30 m (VS30), and style of faulting. We use a Generative Adversarial Neural Operator (GANO)—a resolution invariant architecture that guarantees model training independent of the data sampling frequency. We first present the conditional ground-motion synthesis algorithm (cGM-GANO) and discuss its advantages compared to the previous work. We next train cGM-GANO on simulated ground motions generated by the Southern California Earthquake Center Broadband Platform (BBP) and on recorded the Kiban–Kyoshin network (KiK-net) data, and show that the model can learn the overall magnitude, distance, and VS30 scaling of effective amplitude spectra (EAS) ordinates and pseudospectral accelerations (PSA). Results specifically show that cGM-GANO produces consistent median scaling with the training data for the corresponding tectonic environments over a wide range of frequencies for scenarios with sufficient data coverage. For the BBP dataset, cGM-GANO cannot learn the ground-motion scaling of the stochastic frequency components (f &amp;gt; 1 Hz); for the KiK-net dataset, the largest misfit is observed at short distances (Rrup&amp;lt;50 km) and for soft-soil conditions (VS30&amp;lt;200 m/s) due to the scarcity of such data. Except for these conditions, the aleatory variability of EAS and PSA are captured reasonably well. Finally, cGM-GANO produces similar median scaling to traditional ground-motion models (GMMs) for frequencies greater than 1 Hz for both PSA and EAS but underestimates the aleatory variability of EAS. Discrepancies in the comparisons between the synthetic ground motions and GMMs are attributed to inconsistencies between the training dataset and the datasets used in GMM development. Our pilot study demonstrates GANO’s potential for efficient synthesis of broadband ground motions.

Seismotectonics of the San Andreas Fault System in the San Gorgonio Pass region: A synthesis

In the San Gorgonio Pass region of Southern California, USA, the San Andreas fault exhibits greater geometric complexity than anywhere else along its length, with multiple nonparallel fault strands that branch and join both laterally and at depth (Fig. 1). These structures are associated with regional contraction within the San Gorgonio Pass region due to the nearby Big Bend of the San Andreas fault. The complexity of past and present faulting in this region has led Jon Matti, Doug Yule, and others to call this the “San Gorgonio knot.” Due to its complexity, this part of the San Andreas fault system may serve as both a barrier and an initiation point for devastating earthquakes. Research to understand and unravel the San Gorgonio knot has important implications for seismic hazard in southern California. The first author of this manuscript, Doug Yule, investigated slip rates and earthquake records in this enigmatic region from the mid-1990s until his death in 2022 (Fig. 2). During the 2010s, many researchers, including co-authors Cooke and Oglesby, were inspired by Doug Yule’s work in this area. Together, the three authors coordinated a five-year research effort to investigate active faulting within the San Gorgonio Pass, involving many researchers in the Southern California Earthquake Center (SCEC) community with support from SCEC, their various organizations, and institutions. Many of the results of this effort are compiled in this Geosphere thematic issue, with 11 papers that span earthquake geology, geomorphology, geodesy, potential field geophysics, crustal deformation models, and dynamic rupture models. Here, we highlight findings from these studies and honor the role that Doug played in bringing together earthquake scientists from a variety of disciplines to better understand the rupture potential through the complex faults of the San Gorgonio Pass. Much of this science can be organized around a few key questions.

Findings from a decade of ground motion simulation validation research and a path forward

Simulated ground motions have the potential to advance seismic hazard assessments and structural response analyses, particularly for conditions with limited recorded ground motions such as large magnitude earthquakes at short source-to-site distances. However, rigorous validation of simulated ground motions is needed for hazard analysts, practicing engineers, or regulatory bodies to be confident in their use. A decade ago, validation exercises were mainly limited to comparisons of simulated-to-observed waveforms and median values of spectral accelerations for selected earthquakes. The Southern California Earthquake Center (SCEC) Ground Motion Simulation Validation (GMSV) group was formed to increase coordination between simulation modelers and research engineers with the aim of devising and applying more effective methods for simulation validation. Here, we summarize what has been learned in over a decade of GMSV activities, principally reflecting the views of the SCEC research community but also extending our findings and suggestions for a path forward to broader United States and worldwide simulation validation efforts. We categorize different validation methods according to their approach and the metrics considered. Two general approaches are to compare validation metrics from simulations to those from historical records or to those from semi-empirical models. Validation metrics are categorized into ground motion characteristics and structural responses. We discuss example validation studies that have been impactful in the past decade and suggest future research directions. Key lessons learned are that validation is application-specific, our outreach and dissemination need improvement, and much validation-related research remains unexplored.

Spectral boundary integral equation method for simulation of 2D and 3D slip ruptures at bi‐material interfaces

AbstractThis paper presents a 3D spectral numerical scheme that can accurately model planarcracks of any shape residing on an interfacial plane between two elastic solids. The cracks propagate dynamically under the action of interfacial loads and interfacial constitutive laws. The scheme is a spectral form of the boundary integral equations (BIE) that relate the displacement discontinuity fields along the interfacial plane to the stress fields at the plane. In the BIE, the displacement discontinuities are expressed as a spatio‐temporal convolution of the traction components at the interface. This is in contrast with most previous studies which use a spatio‐temporal convolution of the displacement discontinuities or of the displacements at the interface. Due to the continuity of tractions across the interface, the present formulation is simpler, resulting in convolution kernels that can be written in closed‐form. Previous studies have relied on numerically obtained convolution kernels. The accuracy of the proposed scheme is validated with the known analytical solution of the 3D Lamb problem. Furthermore, new algorithms are developed for coupling the BIE with a slip‐weakening friction law, both for homogeneous materials as well as for bi‐material interfaces. This results in a widely applicable formulation for studying spontaneous rupture propagation. The algorithms are validated by comparing rupture simulation exercises to benchmark problems from Southern California Earthquake Center (SCEC). Finally, the methodology is used to simulate 3D frictional rupture propagation along a bi‐material interface.

Shear Wave Velocities in the San Gabriel and San Bernardino Basins, California

AbstractWe construct a new shear velocity model for the San Gabriel, Chino and San Bernardino basins located in the northern Los Angeles area using ambient noise correlation between dense linear nodal arrays, broadband stations, and accelerometers. We observe Rayleigh and Love waves in the correlation of vertical (Z) and transverse (T) components, respectively. By combining Hilbert and Wavelet transforms, we obtain the separated fundamental and first higher mode of the Rayleigh wave dispersion curves based on their distinct particle motion polarization. Basin depths constrained by receiver functions, gravity, and borehole data are incorporated into the prior model. Our 3D shear wave velocity model covers the upper 3–5 km of the crust in the San Gabriel, Chino and San Bernardino basin area. The Vs model is in agreement with the geological and geophysical cross‐sections from other studies, but discrepancies exist between our model and a Southern California Earthquake Center community velocity model. Our shear wave velocity model shows good consistency with the CVMS 4.26 in the San Gabriel basin, but predicts a deeper and slower sedimentary basin in the San Bernardino and Chino basins than the community model.

Fault Damage Zone Effects on Ground Motions during the 2019 Mw 7.1 Ridgecrest, California, Earthquake

ABSTRACT We have simulated 0–3 Hz deterministic wave propagation in the Southern California Earthquake Center Community Velocity Model (CVM) version CVM-S4.26-M01 for the 2019 Mw 7.1 Ridgecrest earthquake. A data-constrained high-resolution fault zone model (Zhou et al., 2022) is incorporated into the CVM to investigate the effects of the near-fault low-velocity zone (LVZ) on the resulting ground motions, constrained by strong-motion data recorded at 161 stations. The finite-fault source used for the simulation of the Ridgecrest event was obtained from the Liu et al. (2019) kinematic inversion, enriched by noise following a von Karman correlation function above ∼1 Hz with a f−2 high-frequency decay. Our results show that the heterogeneous near-fault LVZ inherent to the fault zone structure significantly perturbs the predicted wave field in the near-source region, in particular by more accurately generating Love waves at its boundaries. The fault zone decreases the 0.1–0.5 Hz mean absolute Fourier amplitude spectrum bias to seismic recordings for all sites in the model and in the Los Angeles basin area (∼200 km from the source) by 16% and 26%, respectively. The fault zone structure generally improves modeling of the long-period features in the data and lengthens the coda-wave trains, in better agreement with observations. The favorable fit to data was obtained with a model including high-resolution surface topography, a 700-m-thick geotechnical layer and frequency-dependent anelastic attenuation in the model domain, with QS=0.1VS and QS(f)=0.1VSf0.5 (VS in m/s) for frequencies lower and higher than 1 Hz, respectively. We recommend that a data-constrained fault zone velocity structure, where available, be included in ground-motion modeling to obtain the least-biased fit to observed seismic data.

Comparison of Nonergodic Ground-Motion Components from CyberShake and NGA-West2 Datasets in California

ABSTRACTIn this study, we compare the Southern California Earthquake Center CyberShake platform against the Next Generation Attenuation-West2 empirical datasets. Because the CyberShake and empirical datasets cover very different magnitude ranges and site conditions, we develop ground-motion models (GMMs) for CyberShake datasets to compare trends with empirical GMMs and decompose the residuals for further analysis. We apply mixed effects regression to four CyberShake datasets in southern, central, and northern California at 2, 3, 5, and 10 s periods, and compare the results with the empirical datasets using the same approach. CyberShake captures the total variability of ground motions in the empirical datasets but tends to predict larger median ground motions relative to the empirical GMMs. We then calculate and compare the repeatable source-specific location, site, and path effects between CyberShake and empirical datasets. We find that the correlations of site effects between the CyberShake and empirical datasets are generally satisfactory, but the variability of site effects is slightly smaller for CyberShake datasets. There is no apparent correlation of source-specific location effects between the CyberShake and empirical datasets. Comparison of path effects shows a wide range of correlation coefficients. Finally, we investigate the source of observed differences between the CyberShake and empirical datasets. We attribute the larger median ground-motion levels in CyberShake to a combination of the homogeneous slip patterns of the earthquake ruptures, the low resolution of near-surface materials in the velocity models, and strong reflections at high-contrast boundaries in the velocity models. These factors also impact the correlations of site and path effects between the CyberShake and empirical datasets. Moreover, the leakage from location effects into site and path terms further weakens the correlations. In summary, we find that CyberShake could be improved, but it is still very useful to supplement empirical datasets for ground-motion studies, especially to inform their nonergodic components.

Earth model-space exploration in Southern California: Influence of topography, geotechnical layer, and attenuation on wavefield accuracy

Accurately predicting the seismic wavefield is important for physics-based earthquake hazard studies and is dependent on an accurate source model, a good model of the subsurface geology, and the full physics of wave propagation. Here, we conduct numerical experiments to investigate the effect of different representations of the Southern California Earthquake Center and Harvard community velocity models on seismic waveform predictions in the vicinity of the San Andreas fault in Salton Trough. We test general preconceptions about the importance of topography, near-surface geotechnical layering, and anelastic attenuation up to a maximum frequency of 0.5 Hz. For the Southern California Earthquake Center model developed without topography, we implement 1D and linear model extensions that preserve the geologic structure and a pull-up approach that adapts the original model to topographic variations and distorts the subsurface. The Harvard model includes an elevation model, so we test the squashed topography representation, which flattens it. For both community models, we modify the top 350 m by partially applying the Ely geotechnical layer using a minimum shear wave velocity of 600 m/s and incorporate an Olsen attenuation model using a ratio of 0.05. We evaluate the resulting 24 model representations using the classical waveform misfit and five moderate-magnitude earthquakes. Only the inclusion of attenuation consistently improves the wavefield predictions. It becomes more impactful at higher frequencies, where it significantly improves the performance levels of the crude 1D and linear extension models close to that of the original version. The pull-up topography representation also enhances the waveform prediction ability of the original model. Squashing the topography of the elevation-referenced Harvard model produces better seismogram fits, suggesting that seismic imagers construct community tomographic models without topography to avoid issues related to missing model parameters near the free surface or discrepancies with a different elevation model. Although full implementation of the Ely geotechnical layer that would permit shear wave velocities as low as 90 m/s proves computationally expensive, our partial implementation provides slightly better results in some cases. Our results can serve as recommendations for implementing these community models for future validation or optimization studies.

“Ghost Transient” Corrections to the Southern California GPS Velocity Field from San Andreas Fault Seismic Cycle Models

Abstract Seismic cycle models of the northern and southern San Andreas fault (SAF) were developed to estimate corrections for viscoelastic transients embedded in the present-day Global Positioning System (GPS) velocity field. These models incorporate a viscous shear zone embedded in either a layered or a 3D viscoelastic structure. In the southern SAF model, the 3D effective viscosity structure is based on the Southern California Earthquake Center (SCEC) community rheology model (CRM) and the SCEC community thermal model. Viscoelastic materials are represented with Burgers or Maxwell viscoelastic rheologies, and ranges of rheological parameters and earthquake chronologies are explored. For the northern and southern SAF models, surface velocity perturbations or “ghost transients” (GTs) of up to 3.5–6 mm/yr are obtained for a wide range of conditions. In all cases, the GT velocities are consistent with left-lateral rather than right-lateral motion across the SAF, and subtracting them from the present-day GPS velocity field increases the apparent SAF offset rate. For the southern SAF model, GT velocities are fairly insensitive to the timing of large SAF earthquakes prior to 1857, but they are sensitive to rheology (i.e., temperatures and strain rates assumed for computing CRM effective viscosities). For the northern SAF model, GT velocities are sensitive to both rheology (mantle, lower crust and shear zone effective viscosities, and Burgers Body parameters Δb and RB) and mean earthquake recurrence interval. For the reference northern and southern SAF models provided to U.S. Geological Survey National Seismic Hazard Mapping Project deformation modelers, the maximum GT velocities are 3.73 and 4.84 mm/yr, respectively.

Ground-Motion Evaluation of Hybrid Seismic Velocity Models

Abstract Cost-effective strategies for enhancing seismic velocity models are an active research topic. The recently developed hybridization technique shows promise in improving models used for deterministic earthquake hazard evaluation. We augment the results of Ajala and Persaud (2021) by exploring other hybrid models generated using 13 sets of embedding parameters—taper widths and subvolumes—and summarize their effect on waveform predictions up to a minimum period of 2 s. Our results introduce the notion of compatibility as a consideration by showing that the same basin models embedded into two different regional models can produce notably different outcomes. In contrast to most of our hybrid Harvard models that produce better matching ground motions, only one of the hybrid models generated using the Southern California Earthquake Center model as a regional model gives a closer match to the waveforms. Similar results are obtained at higher frequencies; however, improvements due to hybridization are reduced. A potential explanation for these results may be the limited high spatial frequencies in the travel time tomography basin models and the &amp;gt;5–6 s wavefield-dominated adjoint regional models. Although the strongly tapered compatible hybrid models tend to produce better results, we find instances of improvements even with merging artifacts.

Calibration of the near-surface seismic structure in the SCEC community velocity model version 4

SUMMARYThe near-surface seismic structure (to a depth of about 1000 m), particularly the shear wave velocity (VS), can strongly affect the propagation of seismic waves and, therefore, must be accurately calibrated for ground motion simulations and seismic hazard assessment. The VS of the top (&amp;lt;300 m) crust is often well characterized from borehole studies, geotechnical measurements, and water and oil wells, while the velocities of the material deeper than about 1000 m are typically determined by tomography studies. However, in depth ranges lacking information on shallow lithological stratification, typically rock sites outside the sedimentary basins, the material parameters between these two regions are typically poorly characterized due to resolution limits of seismic tomography. When the alluded geological constraints are not available, models, such as the Southern California Earthquake Center (SCEC) Community Velocity Models (CVMs), default to regional tomographic estimates that do not resolve the uppermost VS values, and therefore deliver unrealistically high shallow VS estimates. The SCEC Unified Community Velocity Model (UCVM) software includes a method to incorporate the near-surface earth structure by applying a generic overlay based on measurements of time-averaged VS in top 30 m (VS30) to taper the upper part of the model to merge with tomography at a depth of 350 m, which can be applied to any of the velocity models accessible through UCVM. However, our 3-D simulations of the 2014 Mw 5.1 La Habra earthquake in the Los Angeles area using the CVM-S4.26.M01 model significantly underpredict low-frequency (&amp;lt;1 Hz) ground motions at sites where the material properties in the top 350 m are significantly modified by the generic overlay (‘taper’). On the other hand, extending the VS30-based taper of the shallow velocities down to a depth of about 1000 m improves the fit between our synthetics and seismic data at those sites, without compromising the fit at well-constrained sites. We explore various tapering depths, demonstrating increasing amplification as the tapering depth increases, and the model with 1000 m tapering depth yields overall favourable results. Effects of varying anelastic attenuation are small compared to effects of velocity tapering and do not significantly bias the estimated tapering depth. Although a uniform tapering depth is adopted in the models, we observe some spatial variabilities that may further improve our method.

0–5 Hz deterministic 3-D ground motion simulations for the 2014 La Habra, California, Earthquake

SUMMARYWe have simulated 0–5 Hz deterministic wave propagation for a suite of 17 models of the 2014 Mw 5.1 La Habra, CA, earthquake with the Southern California Earthquake Center Community Velocity Model Version S4.26-M01 using a finite-fault source. Strong motion data at 259 sites within a 148 km × 140 km area are used to validate our simulations. Our simulations quantify the effects of statistical distributions of small-scale crustal heterogeneities (SSHs), frequency-dependent attenuation Q(f), surface topography and near-surface low-velocity material (via a 1-D approximation) on the resulting ground motion synthetics. The shear wave quality factor QS(f) is parametrized as QS, 0 and QS, 0fγ for frequencies less than and higher than 1 Hz, respectively. We find the most favourable fit to data for models using ratios of QS, 0 to shear wave velocity VS of 0.075–1.0 and γ values less than 0.6, with the best-fitting amplitude drop-off for the higher frequencies obtained for γ values of 0.2–0.4. Models including topography and a realistic near-surface weathering layer tend to increase peak velocities at mountain peaks and ridges, with a corresponding decrease behind the peaks and ridges in the direction of wave propagation. We find a clear negative correlation between the effects on peak ground velocity amplification and duration lengthening, suggesting that topography redistributes seismic energy from the large-amplitude first arrivals to the adjacent coda waves. A weathering layer with realistic near-surface low velocities is found to enhance the amplification at mountain peaks and ridges, and may partly explain the underprediction of the effects of topography on ground motions found in models. Our models including topography tend to improve the fit to data, as compared to models with a flat free surface, while our distributions of SSHs with constraints from borehole data fail to significantly improve the fit. Accuracy of the velocity model, particularly the near-surface low velocities, as well as the source description, controls the resolution with which the anelastic attenuation can be determined. Our results demonstrate that it is feasible to use fully deterministic physics-based simulations to estimate ground motions for seismic hazard analysis up to 5 Hz. Here, the effects of, and trade-offs with, near-surface low-velocity material, topography, SSHs and Q(f) become increasingly important as frequencies increase towards 5 Hz, and should be included in the calculations. Future improvement in community velocity models, wider access to computational resources, more efficient numerical codes and guidance from this study are bound to further constrain the ground motion models, leading to more accurate seismic hazard analysis.

An Adaptable Random Forest Model for the Declustering of Earthquake Catalogs

AbstractEarthquake catalogs are essential to analyze the evolution of active fault systems. The background seismicity rate, or rate of earthquakes that are not directly triggered by other earthquakes, directly relates to the stressing rate, a crucial quantity for understanding the seismic hazards. Determining the background seismicity rate is challenging because aftershock sequences may dominate the seismicity rate. Classifying these events in earthquake catalogs—known as catalog declustering—is a common practice and most declustering solutions rely on spatiotemporal distances between events, such as the nearest‐neighbor‐distance algorithm, widely used in various contexts. This algorithm assumes that the nearest‐neighbor distance (NND) follows a bimodal distribution related to the background seismicity and to the aftershocks. Constraining these two distributions is crucial to distinguish the aftershocks from the background events accurately. Recent work often uses linear splitting based on the NND, ignoring the potential overlap between the two populations and resulting in a biased identification of background earthquakes and aftershock sequences. We revisit this problem with machine‐learning algorithms. After testing several popular algorithms, we show that a random forest trained with various synthetic catalogs generated by an Epidemic‐Type Aftershock Sequence model outperforms approaches such as k‐means, Gaussian‐mixture models, and support vector machine classification. We apply our model to two different earthquake catalogs: the relocated Southern California earthquake center catalog and the GeoNet catalog of New Zealand. Our model capably adapts to these two different tectonic contexts, highlighting the differences in aftershock productivity between crustal and intermediate‐depth seismicity.

Observation‐Constrained Multicycle Dynamic Models of the Southern San Andreas and the Northern San Jacinto Faults: Addressing Complexity in Paleoearthquake Extent and Recurrence With Realistic 2D Fault Geometry

AbstractUnderstanding mechanical conditions that lead to complexity in earthquakes is important to seismic hazard analysis. In this study, we simulate physics‐based multicycle dynamic models of the San Andreas fault (Carrizo through San Bernardino sections) and the San Jacinto fault (Claremont and Clark strands). We focus on a complex fault geometry based on the Southern California Earthquake Center Community Fault Model and its effect over multiple earthquake cycles. Using geodetically derived strain rates, we validate the models against geologic slip rates and recurrence intervals at various paleoseismic sites. We find that the interactions among fault geometry, dynamic rupture and interseismic stress accumulation produce stress heterogeneities, leading to rupture segmentation and variability in earthquake recurrence. Our models produce earthquakes with rupture extents similar to a recent comprehensive paleoseismic catalog. The “earthquake gates” of the Big Bend and the Cajon Pass occasionally impede dynamic ruptures. The angle of compression, which is the subtraction of the maximum shear strain rate direction from the local fault strike, can better determine the likelihood of the impedance of restraining bends to dynamic ruptures. Because the Big Bend has an angle of compression of ∼20°, ruptures that traverse the Big Bend, like the 1857 Fort Tejon earthquake, are more frequent than expected based on empirical relations which predict the ∼40° restraining bend to terminate most ruptures. Our models indicate that large ruptures tend to initiate north of the Big Bend and propagate southwards, similar to the 1857 earthquake, providing critical information for ground shaking assessment in the region.

Effect of Merging Multiscale Models on Seismic Wavefield Predictions Near the Southern San Andreas Fault

AbstractUpdating Earth models used by the scientific community in geologic studies and hazard assessment has a significant societal impact but is computationally prohibitive due to the large spatial scale. The advent of urban seismology allowed rapid development of local high‐resolution models using short‐term dense seismic arrays to become conventional. To incorporate the details in these local models in community models, we developed a technique for constructing window taper functions like the cosine taper in arbitrarily shaped spatial domains on regular grids. We apply our algorithm to the problem of low‐frequency ground shaking estimation near the southernmost San Andreas fault by creating two hybrid models. These models consist of basin‐scale (top 10 km or less) high‐resolution models developed using controlled source data embedded into two popular Southern California Earthquake Center community models. We evaluate the models by computing long period (6–30 s) wavefield energy misfits using 11 earthquakes with moment magnitudes between 3.5 and 5.5 not used in developing any of the models under consideration. One of the hybrid models produces an ∼24% decrease while the other has an ∼0.6% increase in the overall median misfit relative to their original community models. The overlapping misfit values between the models and variability in waveform fit for different events and stations emphasize the difficulties in model validation. Our approach can merge any type of gridded multiscale and multidimensional datasets, and represents a valuable tool for modeling in the computational sciences.

Ground motions in urban Los Angeles from the 2019 Ridgecrest earthquake sequence

We study ground-motion response in urban Los Angeles during the two largest events (M7.1 and M6.4) of the 2019 Ridgecrest earthquake sequence using recordings from multiple regional seismic networks as well as a subset of 350 stations from the much denser Community Seismic Network. In the first part of our study, we examine the observed response spectral (pseudo) accelerations for a selection of periods of engineering significance (1, 3, 6, and 8 s). Significant ground-motion amplification is present and reproducible between the two events. For the longer periods, coherent spectral acceleration patterns are visible throughout the Los Angeles Basin, while for the shorter periods, the motions are less spatially coherent. However, coherence is still observable at smaller length scales due to the high spatial density of the measurements. Examining possible correlations of the computed response spectral accelerations with basement depth and Vs30, we find the correlations to be stronger for the longer periods. In the second part of the study, we test the performance of two state-of-the-art methods for estimating ground motions for the largest event of the Ridgecrest earthquake sequence, namely three-dimensional (3D) finite-difference simulations and ground motion prediction equations. For the simulations, we are interested in the performance of the two Southern California Earthquake Center 3D community velocity models (CVM-S and CVM-H). For the ground motion prediction equations, we consider four of the 2014 Next Generation Attenuation-West2 Project equations. For some cases, the methods match the observations reasonably well; however, neither approach is able to reproduce the specific locations of the maximum response spectral accelerations or match the details of the observed amplification patterns.

Regional Calibration of Hybrid Ground-Motion Simulations in Moderate Seismicity Areas: Application to the Upper Rhine Graben

ABSTRACTThis study presents the coupling of the spectral decomposition results for anelastic attenuation, stress drop, and site effects with the Graves-Pitarka (GP) hybrid ground-motion simulation methodology, as implemented on the Southern California Earthquake Center (SCEC) broadband platform (BBP). It is targeted to applications in the Upper Rhine graben (URG), which is among the seismically active areas in western Europe, yet a moderate seismicity area. Our development consists of three main steps: (1) calibration of regional high-frequency (HF) attenuation properties; (2) modification of the hybrid approach to add compressional waves in the HF computation and examine various strategies to evaluate site amplification factors in the Fourier domain (e.g., VS30-based or site-specific factors); (3) testing of the simulations using earthquake records from the URG (3.7&amp;lt;Mw&amp;lt;5). The validation process of the simulated time histories is performed first on rock sites, and, then subsequently at all stations, whatever their site conditions. The performance of the simulations for rock sites is assessed through the standard validation technique in the BBP (comparison of the waveforms, intensity measures, and estimation of the response spectra model bias). We additionally compare the Fourier amplitude spectrum of the simulations and observations, and compute their corresponding bias. The results show that the simulated ground motions match the general characteristics of the recorded motions, and that the model bias generally fluctuates around zero across the broadband frequency range. Hence, the hybrid ground-motion methodology implemented in the SCEC BBP can be successfully applied outside high-seismicity areas and outside those areas for which it had been generally calibrated. Our results also show that HF modification and calibration were necessary to improve the fits with the observation, and demonstrate the potential benefits of using site-specific amplification factors compared to VS30-based amplification factors.