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1,662 records · Page 82Linked to original sources
USGS2026

Indirect mineral import reliance and provenance

Mineral commodity supply chain analyses rely on international trade data reported by individual countries as quantities of a mineral commodity form imported from (or exported to) a partner. However, export quantities frequently exceed a country’s domestic production, or occur when no production data are reported, suggesting that the trade partner is merely an intermediary in a transshipment. These discrepancies can result in misleading conclusions regarding supply chain vulnerabilities and dependencies. We present a two-stage methodology to reconcile gaps between reported material sources and actual producers. First, we construct trade networks for specific mineral forms, treating production as a type of import to distinguish producing nations from entrepôts. By tracing flows through these networks, we attribute a target country’s imports to original producers via both direct (in a single trade link) and indirect (transferring through intermediaries) pathways. Second, these production-attributed flows are incorporated into multi-stage supply chains to determine the upstream provenance of feedstock for domestic refining and processing. This approach provides a more representative picture of trade reliance. For example, while the United States (U.S.) Geological Survey reports no imports of unwrought antimony metal from Russia in 2022 (U.S. Geological Survey (2025). Mineral Commodity Summaries 2025. 10.3133/mcs2025), our analysis reveals that over 16% of U.S. imports can be traced back to Russian mining through intermediate processing in countries such as China, India, and Vietnam. Additionally, our analysis of the aluminum supply chain shows that while the U.S. is reported as 52% net import reliant on aluminum materials in 2022, it is 100% reliant on foreign bauxite, 7% of which arrived indirectly. This unreported reliance, which is predominantly tied to bauxite mined in Brazil (43%) and Jamaica (28%), highlights our methods ability to capture the supply chain’s dependence on foreign feedstock that may be missing in single-stage trade data.

Mineral Economics↗
USGS2025

Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health

Produced water is a chemically complex waste stream generated during oil and gas development. Roughly four trillion liters were generated onshore in the United States in 2021 (ALL Consulting, 2022, https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf ). Efforts are underway to expand historic uses of produced water to offset freshwater needs in water-stressed regions, avoid induced seismic activity associated with its disposal, and extract commodities. Understanding the potential exposures from current and proposed produced water uses and management practices can help to inform health-protective practices. This review summarizes what is known about potential human exposure to produced water from onshore oil and gas development in the United States. We synthesize 236 publications to create a conceptual model of potential human exposure that illustrates the current state of scientific inquiry and knowledge. Exposure to produced water can occur following its release to the environment through spills or leaks during its handling and management. Exposure can also arise from authorized releases, including permitted discharges to surface water, crop irrigation, and road treatment. Knowledge gaps include understanding the variable composition and toxicity of produced water released to the environment, the performance of treatment methods, migration pathways through the environment that can result in human exposure, and the significance of the exposures for human and ecosystem health. Reducing these uncertainties may help in realizing the benefits of produced water use while simultaneously protecting human health.

Environmental Health Perspectives↗
USGS2025

Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California

The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.

California↗
USGS2024

The U.S. Geological Survey National Water Quality Network—Groundwater—2023

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, eight of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,114 wells in the network.

conterminous United States↗
USGS2026

Perspectives and insights gained from applying landscape ecological approaches to the Upper Mississippi riverscape

Advances in remote sensing, spatial data collection, hydraulic and geospatial models, and the maturation of landscape ecology during the early 2000s spurred the concept of rivers as landscapes or ‘riverscapes’. Since that time, the Upper Mississippi River Restoration (UMRR) Program - one of the world’s longest running large-river ecosystem restoration and monitoring programs - has applied landscape ecological principles to the Upper Mississippi River System (UMRS). I examine spatial patterns of aquatic nutrient concentrations, submersed aquatic vegetation, and fish and mussel communities, finding that within-river patterns are often patchy in nature, likely resulting from how nutrient processes and community traits interact with spatial variability in hydraulic exchange patterns. Local-scale patchy spatial patterns in the UMRS are embedded in system-scale longitudinal gradients and a hierarchical view of the river has provided a foundation for strategic river restoration planning. Key Words: Aquatic Habitat, hydraulic connectivity, patch, restoration, riverscape

BioScience↗
USGS2025

The Long Island Sound and Watershed Metadata map application

The Long Island Sound and its watershed encompass an area of about 17,000 square miles and include the Connecticut, Housatonic, and Thames Rivers, which all drain to the sound. Dozens of organizations from government agencies, nonprofits, and Tribal Nations have developed projects and monitoring programs to analyze and protect the water resources of the watershed and sound. The abundance of data and lack of an existing searchable index require a centralized metadata repository to allow users to find water resources data more efficiently. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and the Long Island Sound Study, has created an interactive map application to visualize and search for metadata information across organizations working to monitor and protect the Long Island Sound.

Connecticut, Massachusetts, New Hampshire, New Yor↗
USGS2025

Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments

Correlations between grade and tonnage exist in mineral resource data compiled from published reports, but they are not always addressed during quantitative assessment of undiscovered mineral resources. Failure to account for correlated grade and tonnage distributions can result in geologically unrealistic assessment results. Current software tools simulate univariate ore tonnage and multivariate resource grades of undiscovered deposits independently. As a result, analysts are forced to rely on ad-hoc solutions to minimize the correlation issues by: 1) creating subsets of data with restricted criteria; 2) truncating grade and tonnage distributions; and 3) testing model robustness using exploratory data analysis. While these methods represent pragmatic solutions, the statistical solutions presented here provide additional options to address real correlations in grade and tonnage data used for mineral resource assessments. We present a modified version of the MapMark4 package in R that introduces two alternatives for modeling grade and tonnage distributions, consisting of a multivariate solution that accounts for correlations between ore tonnage and metal grades and an empirical solution that utilizes simple random sampling with replacement to reproduce coupled grades and tonnages from the input data. We present simulations for contained ore and metal for three case studies representing tungsten skarn, komatiite-hosted nickel, and sediment-hosted carbonate amagmatic zinc-lead (Mississippi Valley-type) deposits. Employing the methods presented here yields quantitative mineral resource assessment results that more closely reflect the empirical distributions of grades and tonnages observed in nature and expands the applicability of these tools for ongoing critical mineral resource assessments.

Applied Computing and Geosciences↗
USGS2025

Airborne geophysical analysis to decipher salinization for coastal Louisiana

Coastal Louisiana is known for saltwater intrusion that threatens wetlands, aquifers, and rivers. However, the extent of saltwater intrusion is not well understood. This study develops an innovative framework with airborne electromagnetic (AEM) data to map chloride concentration distributions for wetlands in the Mississippi River deltaic plain and Chenier plain as well as for the Mississippi River Valley alluvial aquifer (MRVA) and Chicot aquifer. Moreover, the framework maps chloride concentrations along the Mississippi River and Atchafalaya River. Key components in the framework include the establishment of resistivity-to-chloride concentration transformation, 3D resistivity architecture building through geostatistics, and the employment of a lithologic model. The transformation functions correlate AEM resistivity data with porewater salinity measurements and groundwater and river chloride samples. The results show that AEM data reliably infers soil water chloride concentrations and correlates well with the distribution of various marsh types. AEM data reveals extensive saltwater presence at depth and near the coast, originating from salt domes and the Gulf of Mexico, respectively. The saltwater upconing pattern in the Chicot aquifer is likely due to excessive groundwater withdrawals. The AEM data also confirms a distinct tongue of saltwater intruding into the Atchafalaya Basin from the Gulf. The AEM data helps to identify faults that are obscured or eroded at the surface, which appear as leaky barriers in the subsurface where dramatic changes in chloride concentration are apparent. Finally, this study uses the AEM data to infer the presence of an extensive seawater wedge in the Mississippi River and Atchafalaya River.

Louisiana↗
USGS2024

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter↗
USGS2025

Groundwater structures fish growth and production across a riverscape

Landscapes are composed of habitat patches and conditions that vary across space and time. While habitat variability and complexity can support important ecological processes and ecosystem services, the dynamic nature of habitats can also constrain organismal growth and production as optimal conditions are fleeting. In riverine ecosystems, groundwater discharge to streams stabilises water temperature and flow regimes, thus mediating how habitat complexity is expressed. Yet, how stable habitats structure growth and production within the broader landscape matrix is not well understood. In this study, we explored the effects of groundwater on spatiotemporal variation in growth and production for juvenile Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) across the upper Snake River catchment, Wyoming, USA. We combined machine learning techniques and remotely sensed landscape data to estimate groundwater availability across the river network, which we linked to stream temperature regimes and conspecific density. We then used Bayesian hierarchical models to quantify the effects of temperature, density and groundwater on spatiotemporal variation in fish growth and production in 52 focal reaches. Finally, we predicted body size trajectories and trends in total production continuously over both space and time to understand the effect of groundwater at the riverscape scale. Groundwater discharged to streams where topography changes abruptly in valley-bottom areas underlain by coarse glacial deposits. Groundwater stabilised temperature regimes and was associated with high trout densities. Temperature and density, in turn, interacted to influence growth rates: growth increased strongly with temperature, but this effect was reduced when density was high. Accordingly, variation in groundwater availability among stream reaches diversified growth and production regimes. In reaches with low groundwater availability, growth and production declined over time from summer maxima. In contrast, in reaches with high groundwater availability, temporal trends in growth and production were hump-shaped—peaking in autumn—and mean production was greater. At the riverscape scale, temporal asynchrony in growth rates generated convergent spatial variation in growth capacity, but—when combined with density—led to the formation of distinct hotspots of production. Our results demonstrate how groundwater, an important driver of aquatic ecosystem heterogeneity, structures trout growth and production across space and time. Importantly, rare, but stable habitats may disproportionately affect ecological processes and serve as key sources of population diversity at larger spatial scales.

Wyoming↗
USGS2025

An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?

On October 19, 2020, the M w 7.6 Sand Point earthquake struck south of the Shumagin Islands in Alaska. Moment tensors indicate the earthquake was primarily strike-slip, yet the event produced an enigmatic tsunami that was larger and more widespread than expected for an earthquake of that magnitude and mechanism. Using a suite of hydrodynamic, seismic, and geodetic modeling techniques, we explore plausible causes of the tsunami. We find that strike-slip models consistent with the moment tensor orientation cannot produce the observed tsunami. Hydrodynamic inversion of sea surface deformation from deep ocean and tide gauge data suggest seafloor deformation more closely matches a megathrust, rather than a strike-slip, source. Static slip inversions, using sea level and Global Navigation Satellite System data, allow for a portion of co-seismic megathrust slip that can explain tsunamigenesis. Combining all available geophysical datasets to model the kinematic rupture, we show that considerable, relatively slow, megathrust slip is allowable in the Shumagin segment, concurrent with strike-slip faulting. We hypothesize that the slow megathrust rupture does not contribute much seismic radiation allowing it to previously go unnoticed with traditional seismic monitoring.

Alaska↗
USGS2025

Hydrogeology and groundwater quality in the Snake River alluvial aquifer at Jackson Hole Airport, Wyoming, 2011–20

The Snake River alluvial aquifer underlying the Jackson Hole Airport (JHA) in northwest Wyoming is an important source of water used for domestic, commercial, and irrigation purposes by the airport and nearby residents. The U.S. Geological Survey, in response to previously identified water-quality concerns in the area, monitored and evaluated changes in hydrogeologic characteristics and groundwater-quality conditions of the alluvial aquifer during 2011–20. During that period, the Jackson Hole Airport made several changes that potentially improved water quality at and downgradient from the airport. Well, water level, and hydrogeologic data were collected from the alluvial aquifer to identify hydrogeologic characteristic and groundwater quality changes. Additionally, results of statistical tests were applied to water-quality results to evaluate trends in selected physical properties and constituent concentrations with time. The trends of those data show that water quality did improve overall during the study period compared to previously collected data. Presumably, these trends are in response to the changes in the aircraft deicing/anti-icing fluid (ADAF) formulation used by the JHA, the many JHA infrastructure improvements made during 2011–20, the degradation of existing ADAFs in subsurface soils and groundwater, or some combination of these possibilities.

Wyoming↗
USGS2024

Using surficial geologic maps, vegetation, and monitoring to address erosion impacts from grazing in Channel Islands National Park, California

Employing a map-unit classification scheme based on geomorphic process and age, the U.S. Geological Survey (USGS) mapped Quaternary surficial deposits of the five islands comprising Channel Islands National Park (CHIS), California, as no such maps previously existed. Mapping was motivated through an agreement with the National Park Service (NPS) to aid natural resource assessments, including post-grazing disturbance recovery and identification of mass wasting and tectonic hazards. The resulting detailed (1:12,000 scale) maps portray areas of upland erosional transport processes and alluvial, fluvial, eolian, beach, marine terrace, mass wasting, and mixed depositional processes at a scale commensurate with the process signal on the landscape. Detailed, GPS-located observations of sedimentology, pedogenic development, landscape position, and geomorphology constrain map unit identification. In addition, map-unit boundary delineation was determined in a GIS using a variety of high-resolution (sub-meter) aerial imagery and lidar-based DEMs complemented by derivative raster products. The GIS geodatabase schema used is GeMS compliant. Resolvable map-unit widths are as small as 10-15 meter. Locational accuracy of unit boundaries is estimated to be as low as 10 m or better. Detailed mapping is at a scale allowing determination of geomorphic transport processes operating on the landscape and conveys geologic information to land managers at a resolution commensurate with park resources. Map unit ages are constrained by relative soil chronostratigraphy, vertebrate and invertebrate fossils, and materials collected for dating control using radiogenic, luminescence, and cosmogenic radionuclide techniques. Associated topical studies examined connections between geology, surface water, and vegetation distribution and restoration.

California↗
USGS2025

U.S. Geological Survey National Groundwater Climate Response Network

What is the U.S. Geological Survey National Groundwater Climate Response Network? The U.S. Geological Survey’s (USGS) National Water Monitoring Network is a network of networks that includes the Climate Response Network (CRN). The CRN is a network of wells selected to monitor the effects of climate variability, including droughts, on groundwater systems within the United States, Puerto Rico, and the U.S. Virgin Islands. The primary purpose of the CRN is to monitor these effects on groundwater levels in unconfined or near-surface confined aquifers that are minimally affected by pumping or other human-induced stresses.

Fact Sheet↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
USGS2024

Seismicity and anisotropic imaging reveal an active detachment beneath the northern Alaska Range foothills

North of the Denali Fault, the collision between the Yakutat block with North America is accommodated by a fold-thrust belt giving rise to the northern Alaska Range foothills. At the western end, the Kantishna Hills anticline hosts prominent microseismicity and surface deformation, interpreted as active folding of the Kantishna Hills anticline above a midcrustal detachment. We test for this detachment by using anisotropy-aware receiver functions to image fabric contrasts within the crust in context with seismicity. Seismic stations near the crest of the Kantishna Hills anticline and near its southern flank show a single strong contrast in dipping fabric at depths of 12–13 km near microseismicity clustering depths, consistent with a detachment plane beneath the fold. A minimum b -value at 10–13 km depth is consistent with seismicity on the detachment, compatible with the imaged anisotropic contrast, while off-fault seismicity is shallower and deeper with smaller magnitudes. South-dipping imbricate thrusts in schist characterize the northern Alaska Range foothills structure. This supports our interpretation of the observed anisotropy as reflecting SSW–SSE-dipping foliation above a detachment at ∼10–13 km depth that exploits existing crustal weaknesses along subtle fabric contrasts observed in the seismically quiescent region north of the actively deforming belt.

Alaska↗
USGS2024

Subducting plate structure and megathrust morphology from deep seismic imaging linked to earthquake rupture segmentation at Cascadia

The origin of rupture segmentation along subduction zone megathrusts and linkages to the structural evolution of the subduction zone are poorly understood. Here, regional-scale seismic imaging of the Cascadia margin is used to characterize the megathrust spanning ~900 km from Vancouver Island to the California border, across the seismogenic zone to a few tens of kilometers from the coast. Discrete domains in lower plate geometry and sediment underthrusting are identified, not evident in prior regional plate models, which align with changes in lithology and structure of the upper plate and interpreted paleo-rupture patches. Strike-slip faults in the lower plate associated with oblique subduction mark boundaries between regions of distinct lower plate geometry. Their formation may be linked to changes in upper plate structure across long-lived upper plate faults. The Juan de Fuca plate is fragmenting within the seismogenic zone at Cascadia as the young plate bends beneath the heterogeneous upper plate resulting in structural domains that coincide with paleo-rupture segmentation.

Oregon, Washington↗
USGS2025

Light absorbing particles deposited to snow cover across the Upper Colorado River Basin, Colorado Rocky Mountains, 2013-16: Interannual variations from multiple natural and anthropogenic sources

Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013–2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35–2.50 μm, varied by a factor of 1.9 (range, 0.2300–0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6–22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11–0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 μm) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

Colorado↗