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Results for “International Journal of Applied Earth Observations and Geoinformation”

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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↗
USGS2025

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica↗
USGS2024

Status and performance of the ShakeAlert® earthquake early warning system: 2019-2023

The U.S. Geological Survey (USGS)‐operated ShakeAlert® system is the United States West Coast earthquake early warning system ( Given et al. , 2018 ). In this study we detail ShakeAlert’s performance during some of the largest events seen by the system thus far. Statewide public alerting using ShakeAlert messages was authorized in California in October 2019. Over the next few years, public alerts were expanded into Oregon and then into Washington ( U.S. Geological Survey, 2024 ). ShakeAlert source results are routinely compared to the USGS Comprehensive Catalog (ComCat; Guy et al. , 2015 ; U.S. Geological Survey, Earthquake Hazards Program, 2017 ), which contains the earthquake location and magnitude determined using complete waveform data. M 4.5 and larger is the threshold used for public alerting and was deliberately set below the level where damage is likely to compensate for cases where the system underestimates the magnitude. Between 17 October 2019 and 1 September 2023, the ShakeAlert system created 95 events with maximum magnitude estimates of M ≥4.5, the public alerting threshold. 94 of the 95 events were due to real earthquakes. Seven were categorized “false” per ShakeAlert’s internal definition that there was no matching catalog event within 100 km and 30 s of origin time; however, all but one of these were real earthquakes that were poorly located, primarily because they were at the edges of the seismic network. Three detected events were labeled “missed” because they were very poorly located (>100 km location error). In addition, the system did not produce solutions for four ComCat events M ≥4.5 ( U.S. Geological Survey, Earthquake Hazards Program, 2017 ), which were all at the edge of the alerting and network boundaries. The ShakeAlert system has accurately detected the majority of earthquakes that have occurred within the operational region since completing the public rollout, and alerts from the system have been delivered to millions of cell phone users throughout the West Coast.

California, Oregon, Washington↗
USGS2026

Forecasting volcanic activity in Germany—A multi-criteria approach

Igneous activity, including shallow intrusions and volcanism, has the potential to disrupt underground critical infrastructure. Notably, future underground infrastructure projects like high-level radioactive waste repositories must be sited in areas of extremely low disruption probability by igneous activity. In Germany, according to the Repository Site Selection Act of 2017 (Standortauswahlgesetz, or StandAG), areas in which Quaternary volcanism is either present or future volcanic activity is expected within the next 1 million years (m.y.) must be excluded from the site selection process. Although the locations of regions with Quaternary volcanism are reasonably well known in Germany, forecasting potential igneous activity at intraplate volcanic fields is challenging, as many processes and their interactions control the spatial distribution of volcanic centers. Here, a semi-quantitative, multi-criteria approach is proposed for a regional evaluation of the relative potential of future igneous activity in Germany. A variety of geoscientific indicators are used, including seismic anomalies in Earth’s mantle, gravity data, tectonic activity, sutures, ground motion, earthquakes, mantle degassing centers, and geochronological data of volcanic rocks. The indicators describe the sequence of processes from potential melt generation in Earth’s mantle, through ascent and accumulation of melt within the lithosphere, to eruption at Earth’s surface. In total, 15 out of 30 proposed geoscientific indicators are selected and quantified using 20 total assigned parameters. Defined threshold values are used to spatially delimit relevant parameter properties to focus on areas with higher potential of future magmatic activity. To consider uncertainties of parameters and their underlying processes, which are usually more spatially extensive below ground, buffer zones are defined in which values of relevance decrease with increasing distance from the initial lateral shape of a parameter. Normalized parameters are combined into an index, whose spatial value distribution is used to differentiate the relative potential of future igneous activity (within the next 1 m.y.). The sensitivity of the results is shown by varying the weighting factors for the relevant parameters in country-wide index maps. Thereby, profiles illustrate the distribution of the resulting index values and respective index fractions of various parameters. Different index maps for the relative potential of future igneous activity are presented and can be used for hazard assessments.

Professional Paper↗
USGS2026

Archean to Mesozoic–Cenozoic seismic crustal structure: Implications for geological and biological evolution

We use >4500 measurements of crustal structure to investigate the seismic structure of continental crust, Archean to Mesozoic–Cenozoic. The mean crustal thickness of continents, including their margins, is 36.5 km. We find that Archean, Paleoproterozoic, and Mesoproterozoic crust have similar mean crustal thickness (41 km), seismic velocities, Vp/Vs ratio, and density. Crusts of these ages span 3 Ga, from 4.0 to 1.0 Ga, and their similarity of physical properties (thickness, density, and seismic velocities) suggests that the process of crustal formation may have been similar during this time period, which covers 66% of Earth's history. Neoproterozoic crustal properties differ significantly from Mesoproterozoic and older crusts. The mean thickness of Neoproterozoic crust is 32 km, some 9 km thinner than the mean thickness of Archean, Paleoproterozoic, and Mesoproterozoic crust. A lithospheric root with a thickness of 150–200 km underlies Archean, Paleoproterozoic, and Mesoproterozoic crusts, and this root resists lithospheric rifting and crustal extension and thinning. Based on these observations, particularly the lithospheric thickness, we conclude that Archean, Paleoproterozoic, and Mesoproterozoic lithosphere are unique and together form the stable cratonic nuclei, defined as the thick (150–250 km), long-lived cores of continents. Higher mantle temperatures during the Archean, Paleoproterozoic, and Mesoproterozoic may have played a key role in the formation of the thick lithospheric roots. The second key finding is that the similarities of mean seismic properties indicate that the process of crustal formation operating in the Archean continued during the Paleoproterozoic and Mesoproterozoic. The thin (mean value < 135 km) lithospheric root beneath Neoproterozoic and younger crust may be related to the steady decrease in mantle temperature through time. Neoproterozoic and Paleozoic crust have similar physical properties, and these eras are characterized by pronounced biodiversification, including the renowned Garden of Ediacara, the Cambrian Explosion, and the Great Ordovician Biodiversification. Mesozoic–Cenozoic crust is the most diverse and reflects the current tectonic and magmatic processes of crustal formation.

Book chapter↗
USGS2026

Ground-motion simulations for the 2024 Mw 4.8 Tewksbury, New Jersey, earthquake

Ground-motion simulations of notable earthquakes in the central and eastern United States are limited and typically assume one-dimensional (1D) Earth structure. In this study, we use a three-dimensional (3D) seismic velocity model to better constrain the depth and focal mechanism of the April 5th, 2024, moment magnitude 4.8 Tewksbury earthquake and investigate the spatial variability of earthquake ground motions and the effects of nearby sedimentary basins. We perform earthquake ground-motion simulations up to 0.5 Hz using the 3D spectral-element wave-propagation solver SPECFEM3D over a region 280-km wide by 260-km long by 77-km deep. Topography and subsurface geophysical structure are assigned using the U.S. Geological Survey National Crustal Model with a minimum shear-wave velocity of 200 m/s. We use earthquake time series from 13 broadband seismic stations in the region that have a uniform azimuthal distribution and epicentral distances ranging from 76 to 131 km to compare with synthetics and explore the effects of 1D versus 3D seismic structure on focal mechanism and depth solutions. Ground-motion intensity metrics are also presented relative to the NGA-East ground-motion models (GMMs) currently used in seismic hazard assessments for the region. We find that the 3D model, which reveals a wide spatial variability of period-dependent ground motions, yields better predictions of earthquake ground motions relative to the 1D model and the NGA-East ergodic ground-motion model, with 76 percent reduction of residual variance in observed ground motions averaged over 3-, 5-, 7-, and 10-second periods. Use of the 3D model to solve for a focal mechanism yields a shallower focal depth at 4 km and a shallower east-dipping focal plane relative to the U.S. Geological Survey regional moment tensor and Global Centroid Moment Tensor. Our study demonstrates that use of 3D seismic velocity models can improve estimates of earthquake focal mechanisms, ground motions, and seismic hazard.

New Jersey↗
USGS2000

Use of a ground-penetrating radar system to detect pre- and post-flood scour at selected bridge sites in New Hampshire, 1996-98

Ground-penetrating radar was used to measure the depth and extent of existing and infilled scour holes and previous scour surfaces at seven bridges in New Hampshire from April 1996 to November 1998. Ground-penetrating-radar survey techniques initially were used by the U.S. Geological Survey to study streambed scour at 30 bridges. Sixteen of the 30 bridges were re-surveyed where floods exceeded a 2-year recurrence interval. A 300-megahertz signal was used in the ground-penetrating radar system that penetrated through depths as great as 20 feet of water and as great as 32 feet of streambed materials. Existing scour-hole dimensions, infilled thickness, previous scour surfaces, and streambed materials were detected using ground-penetrating radar. Depths to riprap materials and pier footings were identified and verified with bridge plans. Post data-collection-processing techniques were applied to assist in the interpretation of the data, and the processed data were displayed and printed as line plots. Processing included distance normalization, migration, and filtering but processing was kept to a minimum and some interference from multiple reflections was left in the record. Of the 16 post-flood bridges, 22 ground-penetrating-radar cross sections at 7 bridges were compared and presented in this report. Existing scour holes were detected during 1996 (pre-flood) data collection in nine cross sections where scour depths ranged from 1 to 3 feet. New scour holes were detected during 1998 (post-flood) data collection in four cross sections where scour depths were as great as 4 feet deep. Infilled scour holes were detected in seven cross sections, where depths of infilling ranged from less than 1 to 4 feet. Depth of infilling by means of steel rod and hammer was difficult to verify in the field because of cobble and boulder streambeds or deep water. Previous scour surfaces in streambed materials were identified in 15 cross sections and the depths to these surfaces ranged from 1 to 10 feet below the streambed. Riprap materials or pier footings were identified in all cross sections. Calculated record depths generally agree with bridge plans. Pier footings were exposed at two bridges and steel pile was exposed at one bridge. Exposures were verified by field observations.

New Hampshire↗
USGS2025

Foundational uncertainties in terminal Ediacaran chronostratigraphy revealed by high-precision zircon U-Pb geochronology of the Nama Group, Namibia

The Nama Group of southern Namibia and northwestern South Africa hosts the best-dated mixed carbonate-siliciclastic foreland basin succession of the terminal Ediacaran [ca. 551 million years (Ma) ago to <538 Ma] and is key for resolving the chronology of early metazoan evolution. Numerous silicified volcanic tuff interbeds are present, but differing interpretations regarding the fidelity of their ages lead to different regional stratigraphic correlations, especially for the Urusis Formation of the Schwarzrand Subgroup. An expanded record of the Urusis Formation is found in the Swartpunt area of southern Namibia, which has yielded an important metazoan biota. But the succession in this area is preserved as a series of thrusts at the leading edge of the Gariep orogenic belt and zircon U-Pb data show systematic age repetition. We use regional stratigraphic and structural mapping, integrated with carbonate carbon isotope (δ 13 C carb ) chemostratigraphy and high-precision radioisotope U-Pb zircon geochronology from outcrop and recently acquired drill core to develop a temporally calibrated basin-wide depositional model. This integrated dataset either reflects complex zircon reworking, inheritance, or potential analytical biases (Scenario 1) or the presence of a Gariep-related cryptic décollement within the Spitskop Member that has resulted in stratigraphic repetition (Scenario 2). We investigate the evidence for and against both scenarios and consider their implications for stratigraphic and δ 13 C carb correlations between the Swartpunt area and coeval exposures along the Orange River border with South Africa. Given that these issues are in an area that hosts numerous silicified ash beds and extensive exposure, an inability to confidently discount either scenario highlights a level of compounding uncertainty in zircon U-Pb geochronology that must be considered when attempting to build global chronostratigraphic frameworks. Scenario 1 implies that some of the weighted mean ages and Bayesian eruption ages from the Swartpunt area may be >1 Myr older than the depositional age of their respective ash beds when assuming existing stratigraphic correlations. If this scenario is preferred, then a cautious approach would be to consider all weighted mean zircon U-Pb ages from ash beds to reflect maximum depositional ages. Both scenarios support deposition of the Huns Member >540 Ma in the Swartpunt area if the oldest weighted mean age reported here represents a near-depositional age, which has significant implications for the temporal calibration of important terminal Ediacaran ichnofossil assemblages and future cyclostratigraphic studies. Stratigraphic correlations common to both scenarios allow us to temporally calibrate a basin evolution model for the Nama Group. Temporal trends in initial hafnium isotope (εHf) compositions of zircon grains from ash beds throughout the succession may support progressive crustal thickening associated with underplating of the Damara orogenic belt along the northern periphery of the Kalahari craton from ca. 547 Ma to ca. 538 Ma. The compilation of new and published zircon U-Pb ages may also imply that the locus of carbonate platform development migrated from north to south (present co-ordinates), tracking the migration of foredeep subsidence.

Earth-Science Reviews↗
USGS2012

Development of vegetation based soil quality indices for mineralized terrane in arid and semi-arid regions

Soil quality indices (SQIs) are often management driven and attempt to describe key relationships between above- and below-ground parameters. In terrestrial systems, indices that were initially developed and modified for agroecosystems have been applied to non-agricultural systems in increasing number. We develop an SQI in arid and semi-arid ecosystems of the Western US impacted by different types of geologic mineralization using the relationship between vegetation community parameters and soil abiotic and biotic properties. We analyze these relations in soils associated with three different mineralization types: podiform chromite, Cu/Mo porphyry, and acid-sulfate gold vein systems at four different sites in California and Nevada. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized substrates as well as from waste rock and tailings. Aboveground net primary productivity (ANPP), canopy cover and shrub density were measured for the vegetative communities. Minimum data sets were developed based on correlations between the soil and vegetation parameters, refined using principal components analysis, scored using non-linear functions, and combined into an overall SQI. The indices are comprised of one or two microbial parameters and three to six abiotic parameters, the latter consisting of nutrients and metals. Given the preliminary development of this approach, the parameters and combinations to arrive at an SQI for a given site cannot at this time be correlated or compared with that of another site. This SQI approach provides a means of quantifying disturbed ecosystem recovery resulting from mining, and could be applied to other disturbances in a way that readily distills the information for potential use by land managers. However, severely disturbed areas with little to no aboveground biomass, such as unreclaimed tailings, have likely crossed an ecological threshold that precludes the use of this type of monitoring tool.

California↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the southern Appalachian orogen

The first quantitative mineral resource assessment for undiscovered lithium pegmatite deposits in the southern Appalachian region of the United States was conducted. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical and mineral occurrence data. Lithium pegmatite prospectivity of the tracts was ranked with simplified mappable criteria, including proximity to Paleozoic felsic intrusions and major lithotectonic structures, stream sediment geochemical anomalies, and pegmatite occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. These estimates were integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was applied to convert the probabilistic estimates of contained lithium into recoverable material. The identified lithium pegmatite resources for the Carolina Lithium and Kings Mountain deposits, North Carolina, contain 1589 thousand tons (kt) of Li 2 O. The median contained undiscovered resource for the southern Appalachian orogen was estimated to be 2240 kt Li 2 O. At 90% confidence, the region contains at least 130 kt Li 2 O, and 10,700 kt at 10% confidence. After applying economic filters, the median recoverable contained resource was 1430 kt Li 2 O, corresponding to approximately 201 years of current lithium imports for consumption in the United States. North and South Carolina are likely to contain most of these resources. Coarse data resolution and intra-state variations in the geological data contribute to uncertainty of undiscovered lithium pegmatite resources. Continued efforts to harmonize disparate geospatial datasets with updated or new information can improve the accuracy and precision of estimated undiscovered lithium pegmatite resources in the study area and at broader scales.

Alabama, Georgia, Maryland, North Carolina, South ↗
USGS2025

An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York

The U.S. Geological Survey, in cooperation with the New York State Department of Transportation, evaluated the effects of different deicing salt application rates on surface water, groundwater, and highway runoff quality near State highways in northern New York. Three reaches of State highways were tested with different deicing treatments between October 2019 and November 2022: a salt-sand mixture (Treatment A), a salt mixture applied at a lower rate (Treatment B), and a control mixture consistent with typical deicing salt amounts and application rates. Data on pavement conditions and the quality of surface water, highway runoff, and groundwater were collected. Surface electromagnetic data were also collected. Surface-water and groundwater quality downgradient from the State highways were compared with water quality at upgradient locations. The percentage of snow or ice coverage was used to evaluate the effectiveness of the salt applications. This report provides an overview of the transport of deicing salt. The Treatment B watershed had deicing mixture applied more frequently than other highway reaches, which caused it to have the highest annual total chloride application. Despite differences in chloride application, flow-weighted mean chloride concentrations in highway runoff were comparable across treatments. Chloride concentrations were elevated in surface water and groundwater downgradient from highways relative to chloride concentrations upgradient from highways. A chloride mass balance, calculated for one treatment watershed, indicated that groundwater affected by legacy deicing practices may be contributing additional chloride to surface water. Spatial patterns from electromagnetic surveys show a shallow saline plume alongside the highway in that area. Differences in winter severity and pavement-surface conditions drove deicing salt applications in the treatment areas. This study found that several factors affect chloride loads in the watersheds, including variable winter conditions, adaptive snow and ice management, legacy management practices, and area-specific aquifer and groundwater conditions.

New York↗
USGS2024

Insights on gas hydrate formation and growth within an interbedded sand reservoir from well logging at the Qiongdongnan Basin, South China Sea

Although variable well log resolution and its control on saturation estimation has been studied, it has not been directly applied to a specific location to explore the nature of gas hydrate within a sand reservoir. We applied in-situ measurements of resistivities, neutron porosity, and gamma ray at two sites in the Qiongdongnan Basin, South China Sea (QDN-W05–2021 and QDN-W08–2021) to investigate the reservoir parameters of a hydrate-bearing sand reservoir. Our results show that gas hydrate is distributed in 5 zones with a total thickness of 10.7 m and an average saturation of 69% at the QDN-W05–2021 site, while they are distributed in 2 zones with a total thickness of 4.3 m and an average saturation of 49% at the QDN-W08–2021 site. We found that variances in saturations estimated from lateral-extra deep button (RX), phase shift (P40H-P40L), and attenuation (A40H-A40L) resistivities within the laterally mapped continuous sand body were affected by the nature of gas hydrate occurrences. Results indicate gas hydrate forms and accumulates at the center of the sand layer and tends to be less or not present toward the top and base. Integrated with seismic data, the in-situ measurements provide insights in the evolution of a mushroom-shaped, hydrate-gas reservoir system. In the system, free gas is likely horizontally transported from the top-center of the gas chimney to the surrounding areas in the early stage dominated by a warm-gas environment, whereas hydrate forms in the opposite pathway starting from the surrounding areas in the following stage with temperature reducing. Our study suggests that high-resolution in-situ measurements not only are a tool to identify the physical properties, but also can be used to help explain the physical process of hydrate growth and accumulation.

Marine Geology↗
USGS2024

Methods to evaluate and improve the modeling of rupture directivity in assessment of seismic hazard

In recent years, there have been several advancements related to the modelling of near-source effects of earthquake rupture on strong ground shaking, leading to an improved characterization of ground motions and resulting seismic hazard. Some of these modifications have stemmed from physics-based numerical modelling of the earthquake rupture process, using physics-based dynamic rupture simulations. These contributions have led to a better understanding of how fault rupture characteristics, geometry, and the style of faulting can interact with the hypocenter-dependence on the path from source to site that may ultimately guide the development of seismic directivity models. Moving forward, the application of modern techniques can be used to incorporate these source characteristics and near-fault ground motion behavior that contribute to the azimuthally varying effects that result in rupture directivity. One example is the application of machine learning methods to support more automated integration of new predictor variables in model development and open more evaluation opportunities to access residuals. Here, we utilize several techniques to take advantage of the plethora of synthetic data and its ability to supplement preexisting trends observed in data. We showcase two examples of how models can be either developed, expanded upon, or constrained using artificial neural network model (ANNs). We evaluate the performance of the ANN with existing methods, comparing misfit, potential limitations, and ability to continue to improve upon these methods in the future. One approach uses a set of simulations with corresponding synthetic ground motions from the Southern California Earthquake Center (SCEC) CyberShake study to develop a ground motion model adapted to incorporate seismic directivity information using an ANN. This large database (TBs) enables us to train the model to capture magnitude, period, and distance variations and how these parameters relate to amplification from hypocenters located along finite-faults. In some cases, there is reduced misfit from better representing source features that aren’t included in base ground motion models that neglect hypocenter location (e.g. azimuthal variation, source-to-site terms). Another ANN method uses a shallow-layered neural network model to better fit a hypocenter-independent model. This method adjusts the median and aleatory variability to account for the averaged impact of various hypocenter distributions to fit the underlying directivity adjustment model. This method serves as a template to apply to other directivity models, improving computational efficiency and more readily enabling integration in hazard codes.

California↗
USGS2026

In-situ geochronology using LA-ICP-MS/MS: Application of the Lu-Hf system in carbonate, apatite and fluorite

Geochronology is a fundamental tool for reconstructing earth history and constraining the timing of ore deposit formation. Traditionally, U-rich minerals like zircon, titanite, monazite and apatite have been analysed to determine the timing of mineralization and alteration events. However, not all deposits or alteration assemblages contain these minerals, and the U-Pb system can be disturbed due to open system behaviour. We present a methodology for obtaining in-situ Lu-Hf dates from various minerals to demonstrate the potential for dating ore deposits that lack U-rich minerals. Carbonate, apatite and fluorite minerals from different tectonic settings and geological environments were analysed. We acquired Lu-Hf and REE (rare earth element) data from carbonate minerals from a carbonatite orebody and dike samples from the Mountain Pass REE carbonatite deposit in California, USA. We also tested a ‘double-dating’ method, where U-Th-Pb dates and Lu-Hf dates were obtained from the same analysis of apatite from rocks in the Michigan’s Great Lakes Tectonic Zone. Preliminary results for Lu-Hf dating of fluorite from carbonatite rocks in the Lemitar Mountains of New Mexico are also included. The analytical methodology shows promising results in each of these cases where there is sufficient parent Lu and U and measurable daughter Hf and Pb respectively.

Conference Paper↗
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↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
USGS2025

Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California

The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNd i = ‐2.2 ± 0.8) and zircon Lu-Hf (εHf i = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHf i in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.

California↗
USGS2026

Aspergillosis (Avian) case definition for wildlife

Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents. The intent of a case definition is to provide scientifically based criteria for determining: (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to aspergillosis and applies to all avian species.

Techniques and Methods↗