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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

Tracing mercury from land to river: Global sources, retention, and implications for sustainability

Mercury (Hg) pollution in river systems is a global sustainability challenge. Yet the transport, transformation, and retention of Hg within global rivers remain poorly quantified, particularly in regions with sparse observations such as Southeast Asia and Africa, hindering effective pollution mitigation and reinforcing geographic inequities in scientific knowledge and environmental governance. Here, we present the first global, high-resolution simulation of riverine Hg dynamics using a process-based model that traces Hg from land-based sources through river networks to the ocean. Under a realistic scenario, we estimate that ~1,900 megagrams per year (Mg/yr) of Hg enters global rivers, including 1,500 Mg/yr from human-induced sources and 400 Mg/yr from soil erosion. Nearly half of this flux (~1,000 Mg/yr) is retained in reservoirs and dams, which act as major sinks. While such retention limits downstream delivery to the oceans, it also heightens in-reservoir Hg methylation risks. By bridging the gap between Hg releases and observed riverine exports, our framework offers a scalable tool for data-limited regions, promotes data access, and supports global freshwater and pollution-management strategies.

EarthArXiv↗
USGS2026

Tracing mercury from land to river: Global sources, retention, and implications for sustainability

Mercury (Hg) pollution in river systems is a global sustainability challenge. Yet the transport, transformation, and retention of Hg within global rivers remain poorly quantified, particularly in regions with sparse observations such as Southeast Asia and Africa, hindering effective pollution mitigation and reinforcing geographic inequities in scientific knowledge and environmental governance. Here, we present the first global, high-resolution simulation of riverine Hg dynamics using a process-based model that traces Hg from land-based sources through river networks to the ocean. Under a realistic scenario, we estimate that ∼1900 megagrams per year (Mg/yr) of Hg enters global rivers, including 1500 Mg/yr from human-induced sources and 400 Mg/yr from soil erosion. Nearly half of this flux (∼1000 Mg/yr) is retained in reservoirs and dams, which act as major sinks. While such retention limits downstream delivery to the oceans, it also heightens in-reservoir Hg methylation risks. By bridging the gap between Hg releases and observed riverine exports, our framework offers a scalable tool for data-limited regions, promotes data access, and supports global freshwater and pollution-management strategies.

Environmental Science & Technology↗
USGS2026

Simulation-based scenario ShakeMaps for large magnitude (MW6.5+) crustal earthquakes on the Seattle, Tacoma, and southern Whidbey Island faults, Washington, USA

Scenario ground‐motion maps based on empirical ground‐motion models (GMMs) provide a rapid and generally reliable means of estimating the amplitude and distribution of earthquake shaking. However, because GMMs are designed for broad applicability, they often rely on simplified representations of Earth structure, which can limit their accuracy in regions with complex source, path, and site effects. This can substantially impact the accuracy of predicted shaking in areas like western Washington State, where deep, interconnected basin structure exerts a strong influence on seismic‐wave propagation. In this study, we present a new suite of simulation‐based scenario ShakeMaps that characterize ground shaking from large‐magnitude ( ⁠ M W 6.5–7.5) earthquakes on the Seattle, Tacoma, and southern Whidbey Island faults. These maps are developed using results from recent 3D wave propagation simulations ( Stone et al. , 2022 , 2023 , 2025 ) that incorporate realistic rupture geometries, variable slip distributions, and a regional 3D seismic velocity model with shallow soils. Broadband ground motions are estimated by combining the low‐frequency (<1 Hz) deterministic seismograms from these studies with high‐frequency (1–10 Hz) stochastic seismograms. Simulated ground motions are corrected to account for the enforced minimum shear‐wave velocity and nonlinear site response. The resulting ShakeMaps represent median ground‐shaking estimates derived from multiple rupture scenarios with varying slip distributions and hypocenter locations for each fault. To extend ShakeMap coverage beyond the simulation domain (i.e., into eastern Washington, northern Oregon, and southwestern British Columbia), we scale GMM‐based ground‐motion estimates using amplification patterns observed in the simulations. These new ShakeMaps reveal the substantial influence of deep basin structure on shaking intensity, underscoring the importance of considering crustal structure complexity in regional hazard assessments for the Pacific Northwest.

Washington↗
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↗
USGS2025

Dendroseismological investigation of redwood trees along the North Coast section of the San Andreas Fault

Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.

California↗
USGS2025

Characterization and validation of tidally calibrated strains from the Alto Tiberina Near Fault Observatory Strainmeter Array (TABOO-NFO-STAR)

Six horizontal borehole tensor strainmeters (TSM1-6) installed from Fall 2021 to Spring 2022 comprise the Alto Tiberina Near Fault Observatory Strainmeter Array (STAR), providing an unprecedented opportunity to investigate seismic and aseismic deformation from hazardous high- and low-angle normal faults in Italy. Prior to use in tectonic applications, they require in-situ calibration and correction for non-tectonic signals. We tidally calibrate the instruments, characterize the calibration uncertainty, and test the results against environmental and earthquake signals originating from local to teleseismic distances. The STAR sites demonstrably deviate from assumptions common to the standard manufacturer's calibrations, including negative areal coupling at TSM3-6. While the tidally calibrated strains have ~3-56% uncertainty, the calibrated dynamic strains show interstation precision and accuracy to nanostrain levels, and static coseismic offsets in the array footprint are within uncertainty. TSM3 records a complex series of strains that may arise from dynamically triggered near-borehole fracture slip and fluid flow that does not appear to affect its sensitivity to lower strain rate deformation. Future calibration improvement may be afforded with longer stable timeseries, particularly for TSM4. Overall, our analyses demonstrate expanded geodetic capability for detecting deformation in the Alto Tiberina Near Fault Observatory.

Alto Tiberina Near Fault Observatory↗
USGS2026

2025 USGS National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands: Overview of model and hazard results

The U.S. Geological Survey recently updated the National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The first version of the PRVI NSHM was released in 2003, and therefore this 2025 update includes over 20 years of new geologic, geophysical, and engineering data, methods, and models. Updates follow similar efforts performed in the recent 2023 50-state NSHM. However, this is the first NSHM in which we: (1) apply an inversion methodology to subduction interface fault sources in the earthquake rupture forecast (ERF) model; (2) develop scaled backbone median ground-motion models and independent aleatory variability models that are applied in the ground-motion characterization (GMC) model; and (3) calculate epistemic uncertainty related to alternative scenarios in the ERF and GMC models for all grid points in the study region. Long-term time-independent mean hazard calculations were performed for peak ground acceleration and 5%-damped pseudospectral acceleration at 21 spectral periods from 0.01- to 10.0-s, for eight National Earthquake Hazards Reduction Program site conditions ranging from V S30 = 150 to 1500 m/s, and for 2%, 5%, and 10% in 50-year probabilities of exceedance (return periods of 2475, 975, and 475 years, respectively). Epistemic uncertainty, in the form of selected percentiles, is also provided for a suite of test sites and all grid points in the study region for limited periods, site conditions, and probabilities of exceedance. Selected results, including comparisons with the 2003 PRVI NSHM, are shown and discussed for selected periods, site conditions, and probabilities of exceedance. When comparing the 2025 PRVI NSHM with the 2003 PRVI NSHM, hazard is generally higher at shorter periods and lower at longer periods, as a result of updates in both ERF and GMC models. The 2025 PRVI NSHM is applicable for return periods greater than ∼475 or less than ∼10,000 years.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

Recent advances in characterizing the crustal stress field and future applications of stress data: Perspectives from North America

The stress field controls patterns of crustal deformation, including which faults are likeliest to cause earthquakes or transmit fluids. Since the 1950s, maps of maximum horizontal stress ( S Hmax ) orientations have advanced dramatically, and the style of faulting (relative principal stress magnitudes) has recently been mapped in some regions as well. This perspectives paper summarizes developments in characterizing stress orientations and (relative) magnitudes, including new seismic and borehole methods, as well as progress in identifying the causes of stress variations. Despite these advances, adding far more spatiotemporal detail would allow geoscientists to address many of today's key challenges regarding natural hazards, energy development, and geodynamics. In particular, it is critically important to characterize stress heterogeneity at multiple scales while also recognizing the coherent variability of the stress field. The second part of the paper considers how more detailed stress datasets could prove essential to addressing some of the grand questions in geoscience, including deciphering the poorly understood feedbacks between crustal dynamics and surface processes, improving earthquake and eruption forecasts, and determining the origins and shared properties of plate boundaries.

Geological Society, London, Special Publications↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2024

Thermo-hydrologic processes governing supra-permafrost talik dynamics in discontinuous permafrost near Umiujaq (Québec, Canada)

Widespread supra-permafrost talik formation is currently recognized as a critical mechanism that could accelerate permafrost thaw in the Arctic (e.g., Connon et al. 2018; Farquharson et al. 2022). However, the trajectory of permafrost dynamics following talik formation may prove difficult to predict. Physically-based cryohydrogeologic models provide a powerful tool for understanding processes and factors controlling talik dynamics and, ultimately, how permafrost will respond to climate change. Such models are typically used to represent multiple non-linear processes relevant for groundwater systems in cold regions, such as coupled heat and groundwater movement, including freeze-thaw dynamics and the effects on the surface energy balance and the subsurface thermal and hydraulic properties (Lamontagne-Hallé et al. 2020). Though cryohydrogeologic modeling advances have been made in simulating talik dynamics, few applications have been tested against robust long-term hydrometeorological and subsurface observations.

Quebec↗
USGS2025

Implications of physics-based M9 ground motions on liquefaction-induced damage in the Cascadia Subduction Zone: Looking forward and backward

Given the likelihood of future M9 Cascadia Subduction Zone (CSZ) earthquakes, various estimates of the resulting, regional ground motions have been made, including a suite of 30 physics-based simulations that reflect key modeling uncertainties. However, because the last CSZ interface rupture occurred in 1700 CE, the shaking expected in such an event is especially uncertain, as are the impacts to the built and living environments. Like other coseismic impacts, soil liquefaction poses a significant threat and must be considered by any scenario study used to inform planning and response, or to focus mitigation resources. Liquefaction is also notable for its potential to “ground truth” ground-motion estimates, given that its presence or absence in the geologic record can provide constraint on the intensities of shaking in past events. It is thus an important phenomenon looking both forward and backward. Accordingly, using recent physics-based simulations, this study (1) predicts liquefaction in M9 CSZ ruptures at 400 locations in Oregon, Washington, and British Columbia (BC) using an array of cone-penetration-test based models and (2) uses paleoliquefaction evidence at ten sites spanning from Southern Oregon to Vancouver, BC to constrain possible ground-motion intensities experienced in the 1700 CE earthquake. The forward predictions indicate that liquefaction in M9 events could be pervasive in the region and affect numerous population hubs, with the potential for damage across hundreds of square kilometers. The backward analyses suggest that 1700 CE ground-motion intensities may have been less than expected from M9 simulations in some northern portions of the CSZ (e.g. Seattle), given the paucity of 1700 CE liquefaction evidence in these areas. Ultimately, further discovery and analysis of CSZ paleoliquefaction, or lack thereof, will confirm or modify this possibility and the conclusions drawn herein.

Oregon, Washington↗
USGS2026

Metallurgical coal—Deposits, production, resources, market dynamics, and supply chain risks

Plain Language Summary Metallurgical coal (met coal; consumed to produce coke for steelmaking) must meet specific chemical and physical specifications. In 2023, the conterminous United States produced 66 million short tons (mst) of met coal, consumed 15.85 mst domestically, exported 51.1 mst, and imported 0.7 mst. Most met coal was produced in the Appalachian Basin, but there are also resources that meet the specifications for met coal in the Western United States.

conterminous United States↗
USGS2025

Dynamic baseflow storage estimates and the role of topography, geology and evapotranspiration on streamflow recession characteristics in the Neversink Reservoir Watershed, New York

Estimates of dynamic groundwater volumes supplying baseflow to streams are important for water availability projections during extended periods of drought. The primary goals of this study were to provide dynamic storage volume estimates, inferred from streamflow recession analysis, for baseflow regimes within seven gaged catchments within the Neversink Reservoir Watershed (NRW), a critical municipal water source for New York City. Additionally, geomorphological properties, surficial geology and hydro-meteorological processes were quantified and described in relation to time and spatially variable recession behaviour and storage estimates across the NRW. To explore these relationships, we (1) evaluated seasonal trends in streamflow recession behaviour in relation to modelled potential evapotranspiration (PET) and catchment runoff rates, (2) derived empirical streamflow models for cool-season runoff using both linear and nonlinear reservoir assumptions for baseflow and (3) calculated metrics related to the geology and geomorphology of each catchment and compared these metrics to area normalised baseflow dynamic storage estimates. Results show that baseflow recession behaves as a nonlinear reservoir, and applying linear groundwater reservoir assumptions may underestimate the total dynamic storage volumes compared to what would be predicted for a nonlinear reservoir. Increases in PET caused decreases in storage conditions that resulted in increased recession rates and nonlinearity in streamflow recession during the growing season. Additionally, we found that while no single physical catchment characteristic solely predicted catchment storage dynamics, sediment volume and stream gradients were stronger predictors of normalised storage volumes than catchment surface area or surface topography alone. Within the NRW, catchments with the highest sediment volume exhibited the lowest recession rates and higher dynamic storage volumes, while the smallest catchment, mostly devoid of sediment, had the fastest recession rate and lowest dynamic storage volume.

New York↗
USGS2026

Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality

Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.

Maine, New Hampshire, Vermont↗
USGS2024

Spatial differences in soil nutrients along a hydrographic gradient on floodplains in Dongting Lake

The spatial heterogeneity of soil nutrients is crucial for the water bird and whole floodplain wetland ecosystem in large lakes, and it is influenced by the dramatic water level changes and sedimentation progress in West Dongting Lake (WDL). Soil samples were collected at various soil depths along the Yuan River and Li River that feed into WDL. The concentrations of soil total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), and soil grain size were tested. The stoichiometric ratios of C, N, P, and the mean value of soil grain size ( Mz ) were calculated. The differences of soil TOC, TN, TP and the stoichiometric ratio at different sites and soil depths were compared. Linear regression was used to explore the relationships of Mz and nutrient concentrations, and relationships between TOC, TN, and TP. Redundancy analysis was used to explore the relationship between soil nutrients, heavy metal concentrations, and plant community diversity. The results showed that the distributions of soil TOC, TN, and TP concentrations differed across regions in west Dongting Lake along the Yuan and Li Rivers. Total organic carbon concentration differed at different sedimentation depths. Soil grain size showed negative effect with soil TOC, TN, and TP concentrations in this region. Plant community diversity correlated positively with soil TOC and negatively with Hg. West Dongting Lake was N limited despite the high wet deposition of N. It could potentially be attributed to the insufficient presence of aerobic environments for microbes during intermittent flooding of the floodplain, coupled with feeble mineralization. This study can provide valuable insights for the conservation of water bird habitats and wetland ecosystems.

West Dongting Lake↗
USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗