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1,229 records · Page 2Linked to original sources
USGS2026

Widespread abyssal turbidites record megathrust earthquake-triggered landslides and coseismic deformation in the Cascadia subduction zone

Abyssal marine turbidites provide some of the longest and most spatially extensive records of subduction zone earthquake recurrence globally; however, correlation of these deposits over long distances and interpretation of synchronous emplacement requires both an understanding of the turbidite generating systems and precise dating. Here, we present an integrated suite of high-resolution bathymetry, subbottom profiles, and sediment cores from combined autonomous underwater vehicle, remotely operated vehicle, and ship-based studies at a key paleoseismic site in the southern Cascadia subduction zone. We demonstrate how widespread, earthquake-triggered landslides on the lower slope deposit discrete, proximal mass transport deposits (MTDs) that grade offshore into complex, interfingered abyssal turbidites, which correspond to records of megathrust earthquake history. We propose accretion and oversteepening of thrust folds on the lower slope both preconditions the slope to fail and provides a perpetual source of unstable material to fail during every earthquake cycle. Furthermore, we suggest the periodic and pervasive landsliding indicates coseismic deformation of the outer accretionary wedge during megathrust rupture.

California, Oregon↗
USGS2026

Constraining source and path effects of large magnitude earthquakes using ground motion simulations

The purpose of this study is to use ground‐motion simulations to investigate ways in which source and path effects for large‐magnitude earthquakes can be represented in nonergodic ground‐motion models (GMMs). To achieve this, we designed a ground‐motion study in the San Francisco Bay Area that includes earthquakes with a broad range of magnitudes distributed uniformly on a fault plane, and sites covering a large range of rupture distances and azimuths. After running a large suite of kinematic simulations (magnitude 4–7), we then develop a nonergodic GMM with the simulated data. We find that trends in the within‐site residuals are affected significantly by the earthquake radiation pattern, rupture directivity, and slip patterns. Next, we modify an existing rupture directivity model to fit and remove the observed radiation pattern and rupture directivity from the residuals. We also minimize the contributions of slip patterns by averaging the within‐site residuals among multiple source realizations. Finally, after removing the source effects from the within‐site residuals, we compare the path effects computed with different magnitude groups using two approaches. The first approach only considers the small events that have the same shortest path to a site as the large events, whereas the second approach considers all small events on the fault plane. The results indicate that it is difficult to satisfactorily approximate the path effects of large events with those of small events using either approach, at least in the case of simulations.

California↗
USGS2025

Revisiting an enigma on California's north coast: The Mw6.5 Fickle Hill earthquake of 21 December 1954

Many earthquakes occur along the North Coast of California in the vicinity of the Mendocino Triple Junction (MTJ), where the Pacific, Gorda, and North American (NA) plates meet, and on the adjacent plate boundaries. The MTJ marks the nexus of the Mendocino and San Andreas faults with the Cascadia subduction zone (CSZ). Historically, most large earthquakes around the MTJ have been within the offshore Gorda plate and its subducted portion beneath the NA plate. North of the MTJ, active faults mapped in the NA plate are part of the CSZ fold‐and‐thrust belt. Although some events have been detected in the NA plate, no large historic events have been associated with mapped surface faults. The 21 December 1954 M w 6.5 earthquake in Humboldt County is one possible exception. Using published data from catalogs and articles, unpublished data from Berkeley’s archives, and S ‐ P times interpreted from two U.S. Coast and Geodetic Survey (USCGS) accelerometers, we determine a probability cloud for the earthquake’s hypocenter using NonLinLoc. The highest probability location lies beneath Fickle Hill just east of the city of Arcata, California, at 40.87° N, 124.03° W, and ∼11 km depth. Using P ‐wave polarities from Berkeley stations and the digitized waveforms from the accelerometers, we find that the focal mechanism most consistent with the data indicates thrust movement with strike, dip, and rake of 350°, 10°, and 90°, respectively, at a depth of 14 km. Given the depth uncertainties of both this event and the megathrust, this implies that the earthquake most likely took place on the subduction interface rather than on the mapped faults in the Mad River fault zone that trend 322° and dip to the northeast. The revisited intensity in the epicentral region also supports a location beneath Fickle Hill to the east of the city of Arcata, California.

California, Idaho, Nevada, Oregon, Washington↗
USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗
USGS2024

Characterizing directivity in small (M 2.4-5) aftershocks of the Ridgecrest sequence

Directivity, or the focusing of energy along the direction of an earthquake rupture, is a common property of earthquakes of all sizes and can cause increased hazard due to azimuthally dependent ground‐motion amplification. For small earthquakes, the effects of directivity are generally less pronounced due to reduced rupture size, yet the directivity in small events can bias source property estimates and provide important insights into general regional faulting patterns. However, due to observational limitations, directivity is usually only measured and modeled for large events. As such, many studies of small earthquakes either ignore directivity altogether or assume a constant rupture direction for all events in a cluster. In our study, we apply a refined directivity fitting method constrained with two separate methods of source deconvolution to the dataset of aftershocks of the 2019 Ridgecrest earthquakes, which contain a large number of well‐recorded small‐to‐mid sized earthquakes occurring in close proximity to each other. The revealed directivity of 100+ small (M 2.4–5) earthquakes is highly heterogeneous and primarily oblique to and away from the main fault strike, suggesting a complex postseismic stress redistribution. In addition, the energy focusing effect of directivity appears to bias the selection of high‐quality data from stations in the direction of rupture, leading to average stress‐drop increases of 50% if directivity is not accounted for.

California↗
USGS2026

Unraveling protracted modification of Archean and Paleoproterozoic crust in central Laurentia, Penokean orogen, with garnet and accessory mineral geochronology and microstructural analysis

Proterozoic metamorphism and deformation of the southern margin of the Superior craton in the Lake Superior region is attributed to the Penokean orogeny (1890−1830 Ma). This model includes a period of crustal inversion in which Archean basement blocks were exhumed through overlying Paleoproterozoic strata, producing the corridor of gneiss domes that parallels the trend of the Penokean orogen across the northern Midcontinent, USA. However, recent geologic mapping and 40 Ar/ 39 Ar geochronology challenge this interpretation, suggesting instead that the gneiss dome structures reflect younger episodes of tectonic activity along the southern margin of Laurentia. In absence of integrated pressure-temperature-time-deformation constraints for these rocks, interpretations are largely limited to their final cooling history, making it difficult to both identify the tectonic forces that shaped the architecture of the Penokean orogenic belt and assess the extent to which later Proterozoic tectonism modified the southern Superior craton. We address this problem with an approach joining thermodynamic modeling, garnet and accessory mineral geochronology, and microstructural analysis for several metamorphic rocks across the gneiss dome corridor. The U-Pb ages of titanite reveal that the Proterozoic geometries of exhumed basement gneiss domes are governed by preexisting Archean structures. Garnet Lu-Hf geochronology constrains the timing of prograde-to-peak metamorphism in the Penokean orogenic belt. Granulite facies metamorphism is related to the final stages of the Penokean orogeny at 1837 Ma and localized in a belt of high-grade rocks near a major Penokean suture. Garnet Lu-Hf ages of samples adjacent to gneiss domes reflect regional metamorphism following the accretionary phase of the Penokean orogeny, between 1825 Ma and 1782 Ma, which we suggest reflects continued crustal thickening related to convergence farther south during this time interval. Combination of garnet microstructures and Sm-Nd ages reflects later exhumation of gneiss domes and buried metasedimentary rocks by ca. 1750 Ma, consistent with previously published 40 Ar/ 39 Ar cooling ages across the region. Reset Lu-Hf and Sm-Nd garnet ages and U-Pb ages of syn-kinematic titanite reflect reactivation of primary Penokean structures during this period of basement uplift. These data document significant modification of the Penokean orogen and the Archean crust of the southern Superior province between 1800 Ma and 1700 Ma. Tectonic activity during this interval coincides with collisional events recognized in western Laurentia, suggesting that the period immediately following the Penokean orogeny may be a broadly important time for crustal growth and modification in proto-North America.

Michigan, Wisconsin↗
USGS2025

Relationship between peak and cumulative ground motions from 49 Mw 3-6 earthquakes in the San Francisco Bay Area

We examine the relationship between peak ground velocity (PGV) and cumulative absolute displacement (CAD) for 49 M w 3 – 6 earthquakes in the San Francisco Bay Area (SFBA) and gain insight into the spatiotemporal partitioning of seismic energy in ground motion records with respect to source, path, and site effects. PGV and CAD are positively correlated, but there can be large deviations from the average trend. For example, ground motion records with either very long duration resonance or short pulse-like motions will have higher or lower CAD, respectively, but could have very similar PGV. We perform principal component analysis (PCA) on PGV-CAD for >7000 records in the SFBA with the goal of investigating what influences positive or negative anomalies in cumulative motions. PCA rotates the PGV-CAD datapoints into two principal components, where the one with the larger variance, which we call the “primary intensity” represents mostly the distance-dependence of ground motion amplitudes. The other principal component, which we call the “excess motion”, represents the deviation from cumulative motions that would be typical for a ground motion record with a given PGV. The excess motion will be positive in the case of records with long duration ringing and will be negative for short duration pulse-like ground motions. We find that excess motion is generally positive at sites in sedimentary basins and in soft sediments around the SF Bay. Excess motion is generally negative in the very near field, as well as at sites on hard bedrock. We discuss the findings here in terms of implications for seismic hazard applications and other wave propagation phenomena.

California↗
USGS2025

Earthquake magnitude and source parameter estimation with a distributed acoustic sensing dataset in the Gorda subduction zone

Distributed acoustic sensing (DAS) systems offer a cost‐effective way to create large‐scale strainmeter arrays for seismological applications using fiber‐optic cables. DAS‐based strain measurements are known to be influenced by various factors, bringing into question their general reliability for accurate earthquake characterization. A 15‐km‐long DAS deployment in northern California was operational within 3 days of the 2022 M w 6.4 Ferndale earthquake and ran continuously throughout the aftershock sequence. We utilize these aftershock data to validate DAS‐based strain measurements in two ways. We first test the accuracy of DAS‐based magnitude estimates from peak dynamic strains by comparing them with magnitude and attenuation scaling relations derived independently from traditional borehole strainmeter (BSM) data. We demonstrate that DAS‐based magnitudes are comparable to BSM‐based magnitudes when corrections for variations in site response along the fiber‐optic cable are properly made. Magnitude errors are spatially correlated, potentially because of factors such as finite‐fault effects (e.g., stress drop) or more complex, unmodeled path attenuation or because of wave propagation effects in heterogeneous media. We then apply more advanced source characterization methodology to the DAS data using a time‐domain empirical Green’s function (EGF) deconvolution approach to measure details of the moment rate history. The EGF approach using DAS data depends on careful treatment of distorting factors such as anthropogenic sources of noise and optical phase wrapping but successfully isolates source spectra for moderate‐magnitude earthquakes: source spectral ratios obtained from DAS data, broadband seismometer data, and BSM data in the same region show consistent results, revealing differences in directivity and spectral shape among earthquakes. Although further research is needed to refine source‐time‐function estimation techniques for DAS data, particularly for larger magnitude events, these case studies demonstrate the clear potential of DAS for earthquake source characterization.

California↗
USGS2025

Magnitude, depth and methodological variations of spectral stress drop within the SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Sequence

We present the first ensemble analysis of the 56 different sets of results submitted to the ongoing Community Stress Drop Validation Study using the 2019 Ridgecrest, California, earthquake sequence. Different assumptions and methods result in different estimation of the source contribution to recorded seismograms, and hence to the source parameters (principally corner frequency, f c ⁠ , spectral stress drop, Δσ, and seismic moment, M 0 ⁠ ) obtained from modeling calculated source spectra. For earthquakes smaller than magnitude (M) 2.5 there is negligible correlation between the f c values obtained by different studies, implying that no present method is reliable using available data. For larger magnitude events, correlation between f c measurements of different studies, within even a small M range is always higher than spectral ⁠Δσ , because the f c measurements simply reflect the underlying physical decrease in f c with increasing M. We model the observed trends of submitted f c with both magnitude and depth. Most methods report an increase in spectral Δσ with M, although a magnitude‐invariant spectral Δσ is within the confidence limits. The depth dependence is smaller and depends on whether a study allows attenuation to vary with source depth; a combination of depth‐dependent attenuation correction, and depth‐dependent shear‐wave velocity can compensate for reported depth trends. We model the submitted values to remove differing M and depth variation to investigate the relative interevent variability. We find consistent relative variation between individual events, and also lower relative spectral Δσ in the northwest of the aftershock sequence, and higher on the cross fault and in the region of main fault intersection. This large‐scale comparison implies that absolute spectral Δσ estimates are dependent on the methods used; studies of different regions or using different methods should not be directly compared and improved constraints on path and site corrections are needed to resolve these absolute spectral Δσ differences.

California↗
USGS2026

ShakeAlert Earthquake Early Warning System performance during the Mw 7.0 offshore Cape Mendocino earthquake

The 5 December 2024 M w 7.0 Offshore Cape Mendocino earthquake was a challenging test of the U.S. West Coast ShakeAlert earthquake early warning system due to its offshore epicenter and limited near‐source station coverage. We analyzed real‐time performance of all components of the ShakeAlert system, including the seismic algorithms (earthquake point‐source integrated code [EPIC] and Finite‐fault rupture Detector [FinDer]), the geodetic algorithm (Geodetic First Approximation of Size and Time–peak ground displacement [GFAST‐PGD]), and network telemetry during the event. EPIC created the first solution for this earthquake 15 s after origin time with an initial magnitude estimate of M 5.6 and location error of 10 km from the Advanced National Seismic System epicenter. An early spurious trigger from station CE.89101 fortuitously maintained location accuracy and, correspondingly, magnitude accuracy. FinDer contributed its first solution at 18 s with a location estimate closer to the seismic network and produced two distinct rupture geometries, leading to minor fluctuations in estimated intensity contours. GFAST‐PGD did not meet alerting thresholds but otherwise performed as expected. Network latencies were <2 s for most stations, supporting the rapid detection of this earthquake by the system. Roughly five million alerts were delivered to cell phone devices in California and Oregon during this event. This was also the first instance of a school district‐wide ShakeAlert‐powered system being activated. Comparisons to recorded seismograms demonstrate that the maximum warning times before potentially damaging shaking (intensity 6+) were in the range of 5–55 s. Although the ShakeAlert system provided accurate solutions and useful alert delivery, this earthquake raised awareness of potential issues within the system, including the need for improved offshore location estimates, a combination of solutions from ShakeAlert servers, and handling of spurious triggers.

California↗
USGS2024

SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters

Spectral source parameters used to estimate an earthquake’s stress drop (Δσ) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress-Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low-frequency displacement (Ω0) and corner frequency ( f c ) by fitting a smooth function to benchmark displacement spectra. Participants used linear- or log-sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate Ω0, f c , and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in Ω0 and f c can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade-off between Ω0 and f c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω0 and somewhat higher f c compared to those assuming a Brune model, although resulting Δσ estimates are similar. When compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ.

California↗
USGS2025

Combining multisite tsunami and deformation modeling to constrain slip distributions for the 1700 C.E. Cascadia earthquake

A major earthquake ruptured the Cascadia subduction zone (CSZ) on 26 January 1700. Key paleoseismic evidence associated with this event include tsunami deposits, stratigraphic evidence of coastal coseismic subsidence, written Japanese records of a tsunami unaccompanied by earthquake shaking, and margin‐wide turbidites found offshore and in lacustrine environments. Despite this wealth of independent clues, important details about this event remain unresolved. Dating uncertainties do not conclusively establish whether the proxies are from one earthquake or a sequence of them, and we have limited knowledge of the likely slip distributions of the event or events. Here, we use a catalog of 37,500 candidate synthetic ruptures between M w 7.8 and 9.2 and simulate their resulting coseismic deformation and tsunami inundation. Each model is then compared against estimated Japan tsunami arrivals, regional coastal subsidence records, and local paleotsunami deposits mapped at six different coastal marshes and one coastal lake along the CSZ. We find that seven full‐margin ruptures with a median magnitude of M w 9.1 satisfy all three constraints. We favor one M w 9.11 model that best matches all site paleoseismic observations and suggests that the Cascadia megathrust slipped up to ∼30 m and must have shallow geodetic coupling. We also find that some sequences composed of three or four ruptures can still satisfy the observations, yet no sequences of two ruptures can. Sequences are differentiated into three groups based on whether they contain a mainshock rupture located in the south (>44° N) or further north. All sequences contain unruptured portions of the megathrust and most contain mainshocks with peak slip above 40 m. The fit of the geologic evidence from sequences is poor in comparison to single‐event models. Therefore, sequences are generally less favored compared to full‐margin events.

British Columbia, California, Oregon, Washington↗
USGS2026

Testing characteristic magnitude distributions in modern PSHA models

The characteristic magnitude distribution hypothesis predicts a higher rate of large earthquakes than a Gutenberg–Richter extrapolation of the small‐earthquake rate would imply. Characteristic magnitude distributions have been commonly applied to faults in probabilistic seismic hazard analysis (PSHA), and in modern models they can emerge from the way short‐term seismicity constraints are combined with long‐term geologic and geodetic constraints. We test the characteristic magnitude distribution hypothesis by comparing the fault‐based magnitude distributions from the 2023 update to the National Seismic Hazard Model (NSHM23) in the Western United States with observed seismicity over the past 93 yr. We find that observed magnitude distributions fall outside the model‐predicted confidence bounds in regions where NSHM23 produces characteristic magnitude distributions: in these regions, the model predicts higher rates of large earthquakes than are observed. An analysis of the earlier California model (Uniform California Earthquake Rupture Forecast, version 3) also reveals discrepancies between the modeled and observed magnitude distributions. In addition, we find that observed magnitude distributions near modeled faults are not significantly different from those in background regions. These results challenge the prevalence of characteristic magnitude distributions in fault‐based seismic hazard models and call for a reassessment of how disparate data sets are integrated in PSHA.

western United States↗
USGS2025

An empirical Green’s function approach for isolating directivity effects in earthquake ground-motion amplitudes

In this study, we apply an empirical Green’s function (eGf) method within a ground‐motion modeling framework to mitigate trade‐offs between source, path, and site effects. Many physical processes contribute to spatial variations in observed ground motions, including earthquake radiation pattern, directivity, variable path attenuation, and site effects. Current nonergodic ground‐motion models use spatially varying coefficients for path and site effects, but they do not address trade‐offs with complex earthquake source effects. To quantify the influence of directivity on ground‐motion amplitudes, we use records from multiple smaller earthquakes with epicenters near that of a larger event. We use these small magnitude events as eGfs and estimate repeatable path and site effects at individual stations, assuming that the average adjustments are not controlled by directivity. We adjust residuals from the larger earthquake using the eGf terms, isolating effects related to the rupture. This method clearly enhances the observed broadband directivity observed in the 2022 M 5.1 and 2007 M 5.4 Alum Rock earthquake ground motions, reinforcing the conclusion that their ruptures were unilateral. For the 2004 M 6.0 Parkfield earthquake, we find a bilateral rupture model better fits the data because variations in rupture velocity, slip rate, and slip distribution seem to have a stronger effect on the ground motions than rupture direction alone. Applying eGf adjustments reduces the standard deviation of the rupture models over the three earthquakes by 32% on average and by up to 57% for the 2022 Alum Rock earthquake, confirming we have effectively removed repeatable effects related to the wave propagation path and site response. We propose a novel measure of the frequency‐dependent directivity amplification strength as the reduction in ground‐motion residual variability gained by fitting a directivity model; for the three earthquakes considered, this parameter varies between 25% and 75%, indicating that directivity can strongly influence ground motions and should be considered in ground‐motion modeling.

California↗
USGS2025

Geology and geochemistry of Ni-Co laterite occurrences of northern California and southern Oregon

Ni-Co laterite occurrences in the Klamath Mountains of southern Oregon and northern California contain Ni, Co, and Sc values comparable to global deposits. However, they are thin and limited in extent, often occurring as landslides and slumps. Olivine in the parent material contains Ni and Co and enstatite contains Sc. Through pervasive weathering, these elements where concentrated in Fe- and Mn-oxides. Unlike the mined Nickel Mountian deposit near Riddle, Oregon, these occurrences have no hydrous-Mg silicate minerals. Although the region experienced pervasive weathering in the Eocene, preservation of the laterite profiles was limited in the Klamath Mountains due to accelerated uplift and erosion compared to the Coast Range Provence.

Conference Paper↗
USGS2025

Bayesian ETAS modeling for the Pacific Northwest: Uncovering effects of tectonic regimes, regional differences, and swarms on aftershock parameters

The Pacific Northwest (PNW) of North America has high seismic hazard due to numerous earthquake sources under populated areas. It hosts several tectonic regimes and subregional seismic zones that are hypothesized to have different patterns of earthquake and aftershock occurrence. It is also predisposed to earthquake swarms, which can complicate the statistical modeling of these patterns. We present the first statistical seismicity model of the PNW catalog using the epidemic‐type aftershock sequence (ETAS) framework. We develop a Bayesian inference procedure that provides a stable estimation of both ETAS parameters and their uncertainties for different sets of PNW earthquakes, even those with very sparse catalogs. The Bayesian approach allows us to investigate how parameter estimates change between the intraslab and crustal tectonic regimes, the northern and southern PNW, and when swarms are included and excluded from the catalog. We also utilize our Bayesian framework to calculate parameter estimates under different prior beliefs about PNW seismicity, as well as to propagate catalog measurement errors into ETAS parameter estimates. We discuss the implications of parameter differences across the region for aftershock forecasting for the PNW.

Pacific Northwest↗
USGS2026

Site response models based on geometric parameters for southern California sedimentary basins

Site response in sedimentary basins is influenced by complex three-dimensional (3D) features, including trapping of seismic waves, focusing of seismic energy and basin resonance. Current ground motion models (GMMs) incorporate basin effects using one-dimensional parameters like V S30 and shear wave velocity isosurface depths, which are limited in capturing lateral and 3D effects. To address these limitations, we develop seismic site response models based on novel parameters that represent multi-dimensional properties of the Los Angeles Basin (LAB) geometry and shear wave velocity. We define a basin shape for the LAB using depth to subsurface geologic interfaces associated with the oldest sedimentary deposits (depth to a particular shear wave velocity horizon, i.e., 1.5 km/s - z 1.5 ) and the depth to the crystalline basement ( z cb ) which are determined using geologic cross sections and community seismic velocity model profiles. We explore a suite of geometric descriptors computed for the LAB and southern California, from which three parameters with the greatest predictive potential are selected and evaluated using empirical ground motion residual analyses in combination with the Boore et al. GMM. The results demonstrate that the zonal heterogeneity index ( ), standard deviation of the absolute difference between z 1.5 and z cb ( ) and standard deviation of z cb ( ) each provide a reduction in site-to-site variability ( ϕ S2S ) of empirical GMMs. The reduction in ϕ S2S is period-dependent, with average decreases of 3%, 26% and 6% for , , and , respectively. Although these reductions are modest from an engineering application perspective, they are statistically significant, underscoring the inherent difficulty in fully characterising complex basin effects. Collectively, these findings indicate that the inclusion of basin-specific geometric parameters yields measurable, albeit incremental, improvements in site response prediction and establishes a framework for the progressive refinement of seismic hazard characterisation within sedimentary basins.

California↗
USGS2026

Early Miocene volcanic rocks and associated tectonics, Lava Hills and southern Bristol Mountains, California

Volcanic rocks of latest Oligocene to early Miocene age form an east-west belt across part of the central eastern Mojave Desert from the Whipple Mountains on the east to the Rosamond Hills on the west. We term this the central belt because it is separated from northern and southern belts by swaths with no volcanic rocks. Limited geochronologic data indicate that much of the belt is latest Oligocene and early Miocene in age, about 24 to 19 Ma, a finding that is consistent with these rocks being overlain by the 18.8 Ma Peach Spring Tuff in many places. We describe Miocene geology in a central area of the belt, in the Lava Hills, southern Bristol Mountains, and southern Old Dad Mountains. Sedimentary basins formed coeval with early andesite to rhyolite volcanism, progressing from fluvial and lacustrine tuffaceous sandstone to volcanic lavas, tuffs, and breccias, indicating that early basins formed proximal to volcanic edifices. Higher strata are fluvial and lacustrine with lavas punctuating the sequence. Although basins may partly have been formed within topographic lows bounded by volcanic domes, plateaus, and stratovolcanoes, consistent stratigraphic sections over wide areas indicate that tectonic basin evolution affected broad areas. The volcanic section is capped by local basalt flows and the regional Peach Spring Tuff. Limited data on normal faults support interpretations of early extensional basin development caused by northeast-southwest oriented stretching. Later extension caused stratal rotations, tilting early deposits down to the southwest. This tilted and subsequently beveled basin architecture was overlain by the youngest volcanic deposits, primarily rhyolite and basalt. The Peach Spring Tuff, 18.8 Ma, lies within this upper unit. Similar stratigraphic and structural relations are exposed in the nearby Marble Mountains and Van Winkle Mountain sections, reinforcing that a broad area underwent similar volcanism and tectonism. In our study area the upper unit is only very gently tilted except near dextral strike-slip faults of the eastern California shear zone. These late Miocene to Recent faults are represented as four main fault zones spaced about 5 km apart, representing distributed shear north of the Bristol Lake basin.

California↗