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San Francisco Bay Area: explore 6 source-linked works published from 2024 to 2026, with original documents and citations.

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Sources: usgs. Collection updated 2026-09-14. Counts describe this index, not the complete source archives.

USGS2026

Assessment of extreme subsurface hydrologic conditions captured during atmospheric river storms in the San Francisco Bay area (California, USA) with applications to shallow landslide early warning

An increase in soil pore water pressure is the typical trigger for the majority of landslides caused by rainfall. Atmospheric river storms, common to the west coast of North America during the winter season, can deliver landslide triggering rainfall resulting in severe impacts to coastal communities. Using a network of hydrologic monitoring stations situated within landslide-prone terrain in the San Francisco Bay area of California (USA), we assess the meteorologic conditions and resulting hydrologic and landslide response resulting from eight consecutive storm events that caused thousands of shallow landslides during the winter of 2022–2023. We find disparate hydrological responses and resultant degrees of observed landsliding ranging from < 1 landslide/km2 to 18 landslides/km2 at the monitoring sites that reflect the interplay and differences between rainfall delivery, subsurface hydrological characteristics, and geotechnical properties at each site. Antecedent soil moisture from both early season rainfall and the first storm in the sequence played a critical role in setting up some hillslopes for failure. Subsequent storms then generated elevated pore water pressures for several hours with associated landsliding. However, we find that the occurrence of widespread landsliding required not only sufficient pore water pressure magnitude in susceptible hillslopes, but also full and prolonged effective soil saturation throughout hillslope profiles. Landslides may still occur at lower values and durations of effective saturation but are likely to be less extensive regionally. We present these findings within the context of research directions and improvements to landslide early warning systems first suggested by researchers 40 years ago.

California↗
USGS2026

Earthquake ground-motion model adjustments for the San Francisco Bay area

We develop adjustments to ergodic ground‐motion models (GMMs) to improve their performance in the San Francisco Bay Area (SFBA). GMMs are widely used in hazard assessments to estimate characteristics of ground shaking based on known properties of the source, path, and site. Such models are often developed using datasets containing records from various regions, resulting in models that represent median ground‐motion behavior, which may not adequately represent ground motions within subregions. This is true for the SFBA, where ground motions attenuate more rapidly with distance than in many other parts of California that dominate GMM databases. To support improved seismic hazard estimates in the SFBA, we calculate regional constants and anelastic attenuation coefficient adjustments relative to two commonly used ergodic GMMs: BSSA14 ( Boore et al. , 2014 ) and ASK14 ( Abrahamson et al. , 2014 ). These adjustments are obtained for a suite of ground‐motion intensity measures (peak ground acceleration, peak ground velocity, and 5%‐damped pseudospectral acceleration at oscillator periods ranging from 0.075 to 10 s) using mixed‐effects regression. Use of the regionally adjusted models reduces the overall bias by up to 0.5 natural log units for BSSA14 and up to 0.6 natural log units for ASK14. We demonstrate one application of our attenuation adjustments and their implications in an earthquake early warning case study of the 2014 M 6.0 South Napa earthquake. The predicted extent of shaking using the adjusted models better matches observed shaking at large source‐to‐site distances, especially for lower shaking intensities, thus potentially reducing overalerting. We encourage the use of our model adjustments when ergodic models are considered for seismic hazard studies in the SFBA.

California↗
USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗
USGS2025

A newly identified creeping strand of the Concord fault, San Francisco Bay Area

The Concord fault constitutes a major branch of the Pacific–North America transform plate boundary in Northern California, bridging the strike‐slip Bartlett Springs ‐ Green Valley Fault system to the north with the Greenville and Calaveras Faults to the south. Like many faults in the San Francisco Bay Area its long‐term slip is partially accommodated by aseismic slip (creep). Although creep has been recognized and monitored on the northern half of the fault for decades, the precise location of the southern half of the fault and its slip rate—whether accommodated seismically or aseismically—has remained enigmatic. How slip transfers between the Concord and Greenville or Calaveras faults to the south remains an outstanding question. New field observations presented here indicate that the active trace of the fault south of downtown Concord is not where previously interpreted and is indeed actively creeping. We report observations of shallow creep continuing >7 km farther south along the Concord fault than previously reported, along a fault strand not previously recognized for most of its length. This is evident as right‐laterally deflected concrete curbs and sidewalk slabs on both sides of every street that crosses the fault at a high angle in southeast Concord and northeast Walnut Creek. We document the magnitude and location of these deflections to estimate accumulated right‐lateral aseismic slip expressed in engineered structures. Offsets of these piercing lines range from 8 to 18 cm, over widths varying from narrow breaks along centimeter‐scale concrete joints to 10‐m‐wide zones of deflection. Significantly, this active trace is ∼400 m west of where the Quaternary active trace has previously been inferred, placing it within—rather than bounding—the built area of suburban Concord. Slip along the fault has already caused infrastructure damage. These results revise our understanding of the southern Concord fault and help constrain its seismic potential.

California↗
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↗
USGS2024

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

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Compare source metadata on this page
WorkPublishedSource identifierSource
Assessment of extreme subsurface hydrologic conditions captured during atmospheric river storms in the San Francisco Bay area (California, USA) with applications to shallow landslide early warning2026-05-3070277694usgs
Earthquake ground-motion model adjustments for the San Francisco Bay area2026-04-0170276904usgs
Updating regional‐scale geospatial liquefaction models with locally available geotechnical data2025-09-1770275721usgs
A newly identified creeping strand of the Concord fault, San Francisco Bay Area2025-07-0270270648usgs
Relationship between peak and cumulative ground motions from 49 Mw 3-6 earthquakes in the San Francisco Bay Area2025-06-2470276847usgs
A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA202470256975usgs

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.