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Includes records with this source-supplied label or an explicit phrase match in their metadata. Matches indicate a mention, not proof that a paper uses a method or tests a material. Source versions are consolidated by DOI.

Sources: usgs. Collection updated 2026-09-15. Counts describe this index, not the complete source archives.

Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions

Study region: Headwaters of the upper Colorado River basin (UCOL), USA Study focus: Surface-water and groundwater numerical models incorporating water-use information were used to investigate changes in climate, water use, and simulated hydrologic responses of snow processes, evapotranspiration, groundwater, and streamflow during recent wet (1982–1999) and drought (2000–2022) periods in the headwater subregions of the upper Colorado River basin. New hydrologic insights for the region: Decreases in average streamflow between wet and drought periods ranged from 20 % in the Colorado River headwaters subregion to 23 % in the Gunnison River headwaters subregion. Like streamflow, average surface runoff was statistically less during the drought than the wet period, with decreases from 24–31 % in the headwaters. On a volume basis, runoff decreases were greater than streamflow decreases in both the Colorado River and Gunnison River headwaters. Although the amount of water-year groundwater discharge to streams remained nearly the same between the wet and drought periods, groundwater as a percentage of streamflow increased between the wet and drought periods, highlighting the importance of groundwater in sustaining streamflow during drought conditions. Multiple linear regression analyses revealed that snowmelt-only models were better than the best precipitation and temperature models at explaining streamflow variability from all headwater subregions for both the wet and drought periods.

Arizona, Colorado, New Mexico, Utah, Wyoming

The impact of burial diagenesis on soil-formed minerals in paleosols using stable isotopes of phyllosilicates and carbonate clumped isotopes

To understand the effects of burial diagenesis on the stable isotope geochemistry of soil-formed clay and carbonate minerals in paleosols, samples were collected from seven cores, spanning middle- to upper-Pennsylvanian strata of the Illinois Basin, with varied maximum burial depths of 1–3 km. Mixed-layer illite-smectite and kaolinite mixtures give δ 2 H and δ 18 O values of −83 ‰ to −36 ‰ and 11.9 ‰ to 21.1 ‰ (VSMOW), respectively. After carbonates were screened petrographically for diagenetic textures using transmitted light and cathodoluminescence, measured clumped isotope Δ 47 values range from 0.504 to 0.563 ‰ (I-CDES). Resulting mineral formation temperatures for phyllosilicate mineral mixtures are 28 to 66 °C (mean = 47 °C), whereas T(Δ 47 ) estimates for calcites are 36 to 61 °C (mean = 45 °C). Calculated δ 18 O water values from which phyllosilicate minerals and calcites precipitated under isotopic equilibrium ranges from −7.1 to −1.2 ‰ and − 1.4 to +4.9 ‰, respectively. Closed and open-system phyllosilicate-fluid exchange modeling indicates that phyllosilicate alteration occurred in the presence of a low temperature brine or meteoric water and is interpreted to occur in a layer-by-layer illitization transformation. Due to the lack of diagenetic textures and positively correlated T(Δ 47 ) and δ 18 O water , calcites are interpreted to have undergone solid-state bond reordering. Despite low to moderate temperatures (<125 °C) and varying depths of shallow burial (1–3 km), solid-state transformation of phyllosilicates and calcites indicates paleosols had prolonged exposure to burial conditions which has implications for the use of paleosol minerals for paleoenvironmental reconstructions.

Illinois, Indiana, Kentucky

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California

Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century

This study presents estimates of future years (2024–2051) United States Federal lease coal production and the resulting greenhouse gas (GHG) emissions from the combustion, transport, and mining of that fuel. Results from the coal production estimate indicate a decline in production from Federal leases; with known production of 240 million short tons (mtn) in 2023 and a projected decline to 34.0 mtn by 2051, which represents a reduction to 14.2% of the 2023 value. In parallel with this projection, total GHG emissions are estimated to decrease from 402.2 million metric tons of carbon dioxide equivalent (MMT CO 2 eq.) in 2024 to 55.0 MMT CO 2 eq. in 2051, a decline to 13.7% of 2024 emissions estimates. The reductions in coal production and emissions are mainly the result of planned coal combustion power plant closures, with major projected closures in 2037 and 2048. However, GHG emissions estimates for future years can be uncertain as they rely heavily on coal production estimates from operators' public business plans and other publicly available resources. Forward looking plans of this type are subject to significant changes if economic and political factors deviate from current information. Results suggest that average GHG emissions over the time series breakout to 95% end point combustion, 3.7% transportation combustion emissions, and 1.3% fugitive emissions, although there is uncertainty associated with these figures. Uncertainty stemming from production projections, sector distributions, and emissions factors on the future emissions estimates increases with time, ranging from −28% to +48% within the 2024–2051 timeframe.

Alabama, Colorado, Montana, North Dakota, Utah, Wy

Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA

The U.S. Geological Survey (USGS) is updating the 2008 assessment of conventional hydrothermal resources for the Great Basin in the western United States. As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty. For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.

California, Idaho, Nevada, Oregon, Utah

Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition

The U.S. Geological Survey (USGS), Defense Advanced Projects Research Agency (DARPA), NASA Jet Propulsion Laboratory (JPL), and MITRE ran a 12-week machine learning competition aimed at accelerating development of AI tools for critical mineral assessments. The Artificial Intelligence for Critical Mineral Assessment Competition solicited innovative solutions for two challenges: 1) automated georeferencing of historical maps, and 2) automated feature extraction from historical maps. Competitors used a new dataset of historical map images to train, validate, and evaluate their models. Automated georeferencing pipelines attained a median root-mean square error of 1.1 km. Prompt-based extraction (i.e., with user input) of polygons, polylines, and points from geologic maps yielded median F1-scores of 0.77, 0.56, 0.35, respectively. Geologic maps pose numerous challenges for AI workflows because they vary significantly. However, despite its short duration, the competition yielded promising results that have since spurred further innovation in this area and led to the development of new AI tools to semi-automate key, time-consuming parts of the assessment workflow.

Applied Computing and Geosciences

Comparison of creek and bay influences on salt marsh sediment budget and deposition patterns

The resilience of salt marshes with low organic production depends on their effective capture and retention of mineral sediment from adjacent waters. Little prior work has directly compared mechanisms of sediment import from wave-influenced marsh boundaries against those of tidal creeks. We used simultaneous deployment of net-deposition tiles and oceanographic sensors to identify the timing and magnitude of sediment import/export to, and redistribution within, a marsh in south San Francisco Bay. As the marsh has both an eroding bay-exposed scarp and a prominent tidal creek, we investigated the mechanisms and magnitudes of sediment import from the marsh-bay versus the marsh-creek interface. The strong daily sea breezes of the summer season produced most of the wave-driven erosion of the marsh scarp and controlled suspended sediment concentrations; the winter season had weaker winds punctuated by a few storms. A large seasonal difference in suspended sediment concentrations influenced both flood and ebb sediment fluxes to the marsh and led to much higher rates of import in the summer. Both bay-side and creek-side processes were important to total marsh sediment budget. Bay-side sediment contributions were more variable in time due to the bay-influenced environment, and creek-side contributions were overall larger, reflecting the large proportion of the marsh fed by creek water. Sediment was redistributed throughout the system, with erosion near the bay-edge, accretion near the creek-edge and slow import to the marsh interior. The marsh was net importing sediment in the summer and exporting in the winter from different rates of these processes; on an annual scale, the marsh was net importing despite rapid lateral marsh loss. These findings emphasize that a positive sediment budget does not imply a stable marsh and that both creek- and edge-side dynamics are important for marsh sedimentation and geomorphic trajectories. Further, we expand understandings of non-storm and seasonal controls on marsh sedimentation.

California

Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm

Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across >50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance – both across all reaches and by stream type (e.g., reservoir or groundwater influence) – as a baseline for future improvement. The model showed reach-level RMSE of <2 °C with 90 % prediction intervals that contain 90.7 % of observations. We also assessed how the model captured variability in ecologically relevant metrics (e.g., R 2 for annual 7-day maximum = 0.76; R 2 for days exceeding 25 °C = 0.75). This model does not outperform state-of-the-art machine learning efforts (e.g., RMSE ≤1.5 °C) due to a limited input set but does provide the most spatially complete modeling to date to support water availability assessments.

contiguous United States

Alteration mapping in granitic gneiss using handheld geophysical and geochemical instruments: Implications for iron oxide-apatite and rare earth elements exploration

The Adirondack Mountains of New York, U.S.A. contain iron oxide-apatite (IOA) mineral deposits with variable concentrations of rare earth elements (REE). The IOA mineral deposits are typically hosted in the Lyon Mountain Granite Gneiss and are spatially correlated with extensive Na metasomatism (albitization) of the surrounding country rocks, although some mineral deposits also occur in metagabbro, paragneiss, and anorthosite hosts. The location of albitization zones is key to finding new IOA mineral deposits and better understanding the mineralization processes associated with their genesis. However, the Na alteration zones are generally not visibly identifiable in outcrop or hand specimens because the color and textural changes are subtle and are thus difficult to map. Here, we discuss the results from testing two spectroscopic techniques (handheld, field gamma-ray spectroscopy, and portable X-ray fluorescence (pXRF)) to characterize albitization zones surrounding IOA mineral deposits. The gamma-ray and pXRF spectrometers successfully distinguished the relative intensity of alteration in the Lyon Mountain Granite Gneiss based on the K abundance. The measured K content decreases towards the IOA mineral deposits, and the magnitude and width of the gradient are similar along the strike of each mineral deposit. Elevated Th and U values are present in host rocks adjacent to REE-bearing IOA mineral deposits. The pXRF and gamma-ray spectrometer K values are remarkably consistent with laboratory-based, whole-rock XRF compositional data and, therefore, useful for semi-quantitative analysis. Notably, albitization aureoles are consistent around REE-rich and REE-poor mineral deposits, suggesting that saline fluids are essential for the petrogenesis of IOA mineral deposits but may not be critical to REE mineralization. Ultimately, this study demonstrates the utility of handheld gamma-ray and pXRF spectrometry for identifying otherwise cryptic albitization gradients associated with IOA mineral deposits in granitic gneiss.

New York

Uppermost Oligocene and Miocene diatom biostratigraphy of Ocean Drilling Program Sites 682 and 688 from the Peru Margin

The diatom biochronology of ODP (Ocean Drilling Program) Holes 682A and 688E provides a detailed framework for refiningMiocene diatom zonation in the East Pisco Basin of southern Peru, establishing both a nearly complete offshore reference section and a correlation tool for the fragmentary onshore vertebrate-bearing deposits. This new biostratigraphic record documents a complete succession of low latitude and/or northeastern Pacific Miocene diatom zones, with two notable exceptions: a dissolution and/or hiatus interval (*16.5–14 Ma) during the Middle Miocene Climatic Optimum and a likely earliest Miocene hiatus (*23.4–21.8 Ma). Although eastern equatorial Pacific diatom zones characterize the Upper Oligocene and Lower Miocene strata, an increased abundance of cool-water diatoms that lived during the Middle and Late Miocene allows better application of northeast Pacific diatom zones, except during the Messinian (7–6 Ma) when warm-water diatoms predominate. The effects of eustatic sea level and tectonics on depositional sequences in the EPB and in offshore cores off central Peru are discussed.

Stratigraphy

Cooling perspectives on the risk of pathogenic viruses from thawing permafrost

Climate change is inducing wide-scale permafrost thaw in the Arctic and subarctic, triggering concerns that long-dormant pathogens could reemerge from the thawing ground and initiate epidemics or pandemics. Viruses, as opposed to bacterial pathogens, garner particular interest because outbreaks cannot be controlled with antibiotics, though the effects can be mitigated by vaccines and newer antiviral drugs. To evaluate the potential hazards posed by viral pathogens emerging from thawing permafrost, we review information from a diverse range of disciplines. This includes efforts to recover infectious virus from human remains, studies on disease occurrence in polar animal populations, investigations into viral persistence and infectivity in permafrost, and assessments of human exposure to the enormous viral diversity present in the environment. Based on currently available knowledge, we conclude that the risk posed by viruses from thawing permafrost is no greater than viruses in other environments such as temperate soils and aquatic systems.

mSystems

Impact of gas/liquid phase change of CO2 during injection for sequestration

CO 2 sequestration in deep saline formations is an effective and important process to control the rapid rise in CO 2 emissions. The process of injecting CO 2 requires reliable predictions of the stress in the formation and the fluid pressure distributions – particularly since monitoring of the CO 2 migration is difficult – to mitigate leakage, prevent induced seismicity, and analyze wellbore stability. A key aspect of CO 2 is the gas–liquid phase transition at the temperatures and pressures of relevance to leakage and sequestration, which has been recognized as being critical for accurate predictions but has been challenging to model without ad hoc empiricisms. This paper presents a robust multiphase thermodynamics-based poromechanics model to capture the complex phase transition behavior of CO 2 and predict the stress and pressure distribution under super- and sub- critical conditions during the injection process. A finite element implementation of the model is applied to analyze the behavior of a multiphase porous system with CO 2 as it displaces the fluid brine phase. We find that if CO 2 undergoes a phase transition in the geologic reservoir, the spatial variation of the density is significantly affected, and the migration mobility of CO 2 decreases in the reservoir. A key feature of our approach is that we do not a priori assume the location of the CO 2 gas/liquid interface – or even if it occurs at all – but rather, this is a prediction of the model, along with the spatial variation of the phase of CO 2 and the change of the saturation profile due to the phase change.

Journal of the Mechanics and Physics of Solids

Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin

Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO 3 − ), magnesium (Mg 2+ ) and calcium (Ca 2+ ). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO 3 − , 0.65 for Ca 2+ , and 0.79 for Mg 2+ . Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.

Delaware, New Jersey, New York, Pennsylvania

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York

Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts

Study Region Cape Cod, Massachusetts, U.S.A. Study Focus Anthropogenic nitrogen (N) is a key factor in degrading groundwater and surface-water quality, particularly in coastal New England where onsite wastewater systems are prevalent. This study evaluated whether direct N-load measurements in streams on Cape Cod, Massachusetts, coupled with flow-path information from groundwater-flow models, can effectively identify potential land areas where nitrogen mitigation could substantially reduce loads to receiving waters. Nitrogen fluxes were measured along 63 stream reaches during winter and summer and paired with simulated groundwater recharge areas to identify and rank potential areas for reduction of nonpoint-source N inputs. New Hydrologic Insights for the Region Reach-scale nitrate-N loads ranged from −39.1–1182 kg-N/yr per 100 m of stream, indicating spatially variable groundwater inputs across seasons. “Reachsheds” — areas contributing groundwater recharge to specific stream reaches — were delineated using a regional groundwater-flow model. Strong correlations were found between observed N loads and land-use characteristics, especially the number of septic systems and total N inputs from the sum of considered sources. Observed N loads were moderately correlated with recharge area size and wastewater flow estimates. Correlating reach-specific groundwater N loads with land use and parcel-scale nitrogen-yield data identified reachsheds with the highest potential for N load reduction. This approach enables targeted implementation of restoration efforts to optimize nutrient management and support regional load reduction.

Massachusetts

Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California

The Sulphur Bank Mercury Mine (SBMM) hydrothermal system offers insights into active degassing processes in the Clear Lake volcanic field (CLVF), a high-threat region based on its record of Holocene eruptions and proximity to populated areas. Here we present chemical and isotopic analyses of gas samples collected between 2015 and 2023, along with the first comprehensive CO 2 flux survey of the SBMM area conducted in 2023. Sampled gases are CO 2 - and CH 4 -rich (≥84 and 6 mol% in dry gas, respectively) with high mantle-derived helium contributions ( 3 He/ 4 He = 6.54–7.86 R C /R A ). Carbon isotopic compositions of CO 2 (δ 13 C = −10.0 to −9.5 ‰) and CH 4 (δ 13 C = −35.8 ‰) indicate mixed sources, with significant contributions from metamorphism of organic-rich Franciscan Complex rocks hosting the hydrothermal system. Modeling of gas compositions shows that scrubbing by interaction with air-saturated groundwater strongly influences observed compositional variability. From our CO₂ flux measurements, we estimate the deeply derived CO 2 emission rate from the SBMM hydrothermal area (0.2 km 2 ) at 240 t d −1 , comparable to many quiescently degassing volcanoes worldwide. We also provide a first-order estimate of CH 4 emissions at approximately 0.5 t d −1 . Our findings establish crucial baseline data for future volcanic monitoring efforts, enhancing detection capabilities for potential changes in this active hydrothermal system. This work contributes to the broader understanding of volatile contributions from volcanic and metamorphic sources to the global carbon budget, while highlighting the strong influence of bedrock geology on gas compositions in the CLVF.

California

Estimated average annualized losses from potential building damage and fatalities due to earthquake-generated tsunamis in the United States

Earthquake-generated tsunamis represent substantial economic threats to states and territories in the United States (U.S.), but we are unaware of any effort to quantify potential impacts at the national level. This gap is partially due to the lack of nationally consistent data on tsunamigenic sources and associated return periods. This study addresses this issue and provides estimates of average annualized losses (AAL) for potential residential fatalities and capital stock losses associated with building damage (i.e., structural, non-structural, contents, and inventory damage) in the U.S. by curating tsunami-hazard information based on deterministic scenarios and probabilistic approaches, calculating potential losses, and estimating return periods where necessary. This assessment was done for the U.S. West Coast, Alaska, Hawaii, U.S. Pacific Territories, and U.S. Atlantic Territories. We estimate that earthquake-generated tsunamis that could affect these states and territories collectively represent $1 billion in potential AAL with 79 % of losses due to residential fatalities and 21 % of losses due to capital stock losses from building damage. We identify AAL variations based on county and county equivalents, states and territories, geographic regions, return periods, and departure-delay assumptions for evacuating residents. Results include high AAL values for potential fatalities in Puerto Rico and the U.S. Pacific Northwest region, high AAL values for potential building-related damage in Hawaii and California, and high building- and population-loss ratios for county equivalents in Alaska and U.S. territories.

International Journal of Disaster Risk Reduction

Petrogenesis and mineralization potential of spinifex komatiitic basalts in the Bradley Peak greenstone terrane, Wyoming Province

Komatiitic volcanic rocks are important hosts of Ni sulfide mineralization and record early Earth evolution; however, those in the well-studied Archean Wyoming Province have received little attention. Here, we elucidate the timing and petrogenesis of the Bradley Peak komatiitic volcanic rocks using field and textural observations, geochronology, and geochemistry. Detrital and igneous zircon U-Pb ages for two samples from previously undated units support published age determinations, placing the eruption age at 2.72 Ga. Stratigraphy of the volcanic flows was mapped and 36 samples including cumulates, greenschists, and spinifex-textured rocks were collected. Whole-rock geochemistry was used to classify the spinifex-textured samples as Al-undepleted komatiitic basalts (11–17 wt% MgO). Platinum-group element concentrations (n = 25) are like those in global Al-undepleted komatiitic basalts, and PGE/Ti ratios do not indicate the volcanic flows likely host sulfide mineralization. Initial ε Nd values of −0.5 to +4.7 (n = 16), indicate that these lavas were derived from a depleted mantle source and have negligible evolved crust contamination. The primary magma to the komatiitic basalt flows is estimated to have had 19 wt% MgO and be derived from ∼15 to 25 % mantle partial melting at 3–4 GPa. Trace element chemistry and thermodynamic modeling suggest the primary melt assimilated local banded iron formation. Although the Bradley Peak komatiitic basalts do not contain positive evidence of magmatic sulfide deposits, depleted Au in the flows suggests they could be source rocks for nearby orogenic gold deposits.

Wyoming
Compare source metadata on this page
WorkPublishedSource identifierSource
Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions202570268753usgs
The impact of burial diagenesis on soil-formed minerals in paleosols using stable isotopes of phyllosilicates and carbonate clumped isotopes202570268839usgs
Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model202570269899usgs
Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century202570270223usgs
Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA202570270953usgs
Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition202570271124usgs
Comparison of creek and bay influences on salt marsh sediment budget and deposition patterns202570271265usgs
Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm202570271353usgs
Alteration mapping in granitic gneiss using handheld geophysical and geochemical instruments: Implications for iron oxide-apatite and rare earth elements exploration202570271451usgs
Uppermost Oligocene and Miocene diatom biostratigraphy of Ocean Drilling Program Sites 682 and 688 from the Peru Margin202570271460usgs
Cooling perspectives on the risk of pathogenic viruses from thawing permafrost202570271497usgs
Impact of gas/liquid phase change of CO2 during injection for sequestration202570271508usgs
Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin202570271694usgs
A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed202570271905usgs
Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts202570271947usgs
Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California202570271972usgs
Estimated average annualized losses from potential building damage and fatalities due to earthquake-generated tsunamis in the United States202570271996usgs
Petrogenesis and mineralization potential of spinifex komatiitic basalts in the Bradley Peak greenstone terrane, Wyoming Province202570271998usgs

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