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1,661 records · Page 74Linked to original sources
USGS2025

Preferential groundwater discharges along stream corridors are disregarded sources of greenhouse gases

Groundwater delivery of greenhouse gases (GHGs) to stream banks and riparian areas, before mixing with surface waters, has not been well quantified. We measured preferential groundwater delivery of GHGs to stream banks within three stream reaches, and found that stream banks with discharging groundwater emitted more CO 2 and were sources of N 2 O compared to stream banks without actively discharging groundwater, which emitted less CO 2 and were N 2 O sinks. At one of our stream reaches, groundwater CO 2 and N 2 O concentrations were 1.4–19.2 and 1.1–40.6 times higher than those in surface water, respectively, and groundwater delivery rates of CO 2 and N 2 O were 1.5 and 1.6 times higher than surface water emissions per unit area. On average, 21% (range 0%–100%) of CO 2 and N 2 O were emitted at the stream bank before mixing with surface waters. Preferential groundwater GHG emissions may contribute substantially to stream corridor emissions and may be underestimated when using a channel-centric approach to estimate riverine GHG budgets.

JGR Biogeosciences↗
USGS2025

U.S. Geological Survey Integrated Water Availability Assessment—2010–20

This professional paper is a multichapter report that assesses water availability in the United States for water years 2010–20. This work was conducted as part of the fulfillment of the mandates of Subtitle F of the Omnibus Public Land Management Act of 2009 (Public Law 111-11), also known as the SECURE Water Act. As such, this work examines the spatial and temporal distribution of water quantity and quality in surface water and groundwater, as related to human and ecosystem needs and as affected by human and natural influences. Chapter A introduces the National Integrated Water Availability Assessment and provides important background and definitions for how the report characterizes water availability and its components. Chapter A also presents the key findings of Chapters B–F and thus acts as a summary of the entire report. Chapter B is a national assessment of water supply, which is the quantity of water supplied through climatic inputs. Chapter C is a national assessment of water quality, which is the chemical and physical characteristics of water. Chapter D assesses water use including withdrawals and consumptive use in the conterminous United States. Chapter E presents an analysis of factors affecting future water availability under changing climate conditions. The National Integrated Water Availability Assessment culminates with Chapter F, which is an integrated assessment of water availability that considers the amount and quality of water coupled with the suitability of that water for specific uses. Together, these six chapters constitute the National Integrated Water Availability Assessment for water years 2010–20.

Professional Paper↗
USGS2025

Widespread occurrence of former anhydrite phenocrysts in Laramide-age magmas related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, USA

Reports of magmatic anhydrite are relatively rare, with only ~30 occurrences documented worldwide so far. However, magmatic anhydrite saturation is difficult to recognize because anhydrite decomposes rapidly in near-surface environments. In most cases, only anhydrite inclusions shielded within other phenocryst phases were able to survive. Alternatively, since anhydrite phenocrysts preserved in fresh volcanic rocks are characteristically intergrown with apatite phenocrysts, the former presence of anhydrite phenocrysts can be recognized based on the occurrence of lath-shaped cavities that show a strong spatial association with apatite phenocrysts. These cavities can be either empty or filled with low-temperature, secondary minerals such as zeolites, carbonates, or microcrystalline silica. A systematic search for the occurrence of such cavities, combined with optical and Raman-spectroscopic identification of anhydrite inclusions preserved within apatite, hornblende and quartz phenocrysts, demonstrates that most of the Laramide-age magmas associated with the Santa Rita and Hanover-Fierro porphyry-skarn Cu (Zn, Mo, Au, Pb) deposits were saturated in magmatic anhydrite. The anhydrite typically coexisted with monosulfide solid solution (MSS), suggesting oxygen fugacities of ~2.0±0.5 log units above the fayalite-magnetite-quartz buffer. The magmas range from andesitic to rhyodacitic in composition, and from shortly pre-mineralization (~61 Ma) to shortly post-mineralization (~57 Ma) in age. In three samples with particularly well-recognizable former anhydrite phenocrysts, their modal abundance could be quantified based on high-resolution scans of polished hand specimens. The observed modal anhydrite abundances of 0.63–1.8 vol% translate into minimum magma sulfur contents of 0.20–0.56 wt% S. The highest sulfur content of 0.56 wt% S is difficult to reconcile with available anhydrite solubility models, but it could be reproduced in an anhydrite solubility experiment performed at 950 °C and 1.15 GPa on a natural latite containing 13.1 wt% dissolved H2O. The sample with the second-highest sulfur content of 0.26 wt% S requires ~10 wt% H2O in the silicate melt, and, consequently, a minimum pressure of ~0.5 GPa. Taken together, the results suggest that the magmas of the Central Mining District were extremely hydrous and thus originated from great depth. Indeed, their major element compositions and reconstructed H2O and S contents agree well with experimentally observed and numerically predicted compositions of residual silicate melts after 50–70 wt% crystallization of ordinary arc basalts at high pressure and high oxygen fugacities.

New Mexico↗
USGS2025

Evidence for fluid pressurization of fault zones and persistent sensitivity to injection rate beneath the Raton Basin

Subsurface wastewater injection has increased the seismicity rate within the Raton Basin over more than two decades, with the basin-wide injection rate peaked between 2009-2015. To understand the evolution of injection-induced earthquakes, we systematically analyzed 2016-2024 broadband recordings with a machine-learning-based phase picker and constructed a catalog with 95,993 earthquakes (-1≤ M L ≤4.3). We then inverted for full centroid moment tensors (CMT) for 90 M L ≥ 2 events, with a special interest in constraining the non-double-couple components via probabilistic metrics. Both relocations and CMT solutions support basement-rooted normal faults, including graben and half-graben structures. Furthermore, we observe the non-double-couple components that imply elevated pore pressure in the fault zones. An earthquake cluster emerged in the north-central basin in 2023, preceded by ~1-yr of increased injection volume from wells within 15km. Despite a basin-wide decrease in the injection volume, we highlights the persistence of seismicity that remains to sensitive to injection rates within the Raton Basin.

Colorado, New Mexico↗
USGS2025

Beyond optimality: Dryland ecosystems infrequently use water efficiently for carbon gain

Optimality theory assumes plants maximize carbon gain per unit water lost and is often implemented to scale leaf-level carbon gain and water use to regional and global scales. Optimality theory is often mathematically represented by assuming plant water-use efficiency (WUE) scales with VPD k , where k = ½ represents expected optimal behavior. It is unclear, however, if this relationship holds in arid and semi-arid ecosystems that are strongly impacted by soil and atmospheric moisture status. We used data from seven flux tower sites along an aridity gradient in New Mexico to answer: how does the relationship between WUE and VPD compare to expectations based on optimality theory? To address this question, we integrated the Dynamic Evapotranspiration Partitioning Approach for Rapid Timescales with a stochastic antecedent model to estimate ecosystem-level WUE (GPP/T) and the net sensitivity of WUE to VPD, or k Dynamic , which we compare to the theoretical optimal sensitivity of k = ½. Our results show that optimality theory is not always appropriate, and k Dynamic often deviates from ½, especially at some of the more arid sites or during periods of low soil moisture. At less arid, higher elevation sites, k Dynamic is most consistent with optimality theory at moderate VPD levels, but not at high VPD. In general, the sensitivity of WUE to VPD is highly variable such that k Dynamic exhibits notable daily and seasonal variability, suggesting highly dynamic stomatal behavior. These results emphasize that representing plant water-use strategies as dynamic in time and space is critical to improving large-scale estimates of plant water use.

New Mexico↗
USGS2025

Mine waste as a potential source of critical minerals and other commodities: Examples from the Four Corners states, USA

The growing demand for critical minerals and other mineral resources has raised concerns about possible supplies of these essential commodities. Mine waste is a potential source of these essential commodities. We compiled a geospatial database of publicly available data of the largest non-fuel mine waste features (>200,000 m 2 in areal extent) in the Four Corners states of the United States, where most of those features are from porphyry Cu deposits. The combined volume of those large porphyry Cu mine waste features is approximately 17 cubic kilometers, 60% of which is ore-related material such as tailings. Using publicly available data on density, grade, and previous recovery values, we estimate the contained endowments of Ag, As, Au, Bi, Cu, Mo, Re, S, Sb, Se, Te, and W. These estimates indicate endowments within ore-related mine wastes are collectively comparable to endowments of giant to supergiant deposits. If fully recovered, these commodities could meet current global demand from less than 1 year (Sb) to more than 200 years (Re), underscoring the enormous untapped resource potential of mine waste.

Arizona, Colorado, New Mexico, Utah↗
USGS2025

Introduction to the special section on improving measurements of earthquake source parameters

Earthquake source parameters such as magnitude, seismic moment, source dimension, stress drop, and radiated energy are fundamental to understanding earthquake physics, and are also key ingredients in earthquake ground‐motion modeling, rupture simulation, and statistical seismology. However, the uncertainties in these parameters estimated from the radiated seismic wavefield are large due to variability in approaches, including site and attenuation characterizations, and so estimates for an individual earthquake made by different studies can vary greatly. Estimating spectral source parameters remains a popular topic, due to a combination of their intrinsic importance and their apparent ease of measurement, but also a controversial one, due to many sources of variability and large uncertainty. The available methods coupled with necessary parameter choices and assumptions in the analysis make it challenging for researchers to apply methods or understand the reliability in results or reported source parameters. This Special Section on Improving Measurements of Earthquake Source Parameters showcasing comparisons between methods and studies seeks to alleviate some of these difficulties to help the community identify the important components and trade‐offs of decomposing recorded seismograms into their source, path, and site components.

Bulletin of the Seismological Society of America↗
USGS2000

Pesticides in surface waters of the Upper Colorado River Basin, Colorado, 1996-98

Forty-four river, stream, and drain sites in the Upper Colorado River Basin in Colorado were sampled during 1996-98 to determine the occurrence and distribution of pesticides in the basin. In a fixed-station study, 57 surface-water samples were collected from October 1996 through January 1998 at four sites. Each site was sampled approximately monthly for up to a year, with more frequent sampling during the spring and summer growing season. In a synoptic study, surface-water samples were collected at 43 sites in the agricultural areas of the Grand Valley and the Uncompahgre River Valley in May 1998. Each site was sampled once. Pesticide concentrations generally were low and varied seasonally and across land uses. Thirty-five pesticides were detected at least once in the two studies, and 11 pesticides accounted for almost 82 percent of the detections. Herbicides were more commonly detected than insecticides, and only the herbicides alachlor and atrazine were detected in more than 50 percent of the samples. Carbofuran was the most commonly detected insecticide and was detected in 19 percent of the samples. Pesticide detections increased and were measured at higher concentrations in the summer months and at the agriculture sites. All pesticide concentrations were less than drinking-water standards, and most complied with human-health advisories and criteria for the protection of freshwater aquatic life. Pesticides in the Upper Colorado River Basin in Colorado were detected slightly less frequently and generally at lower concentrations than in 20 National Water-Quality Assessment Program study-unit basins that collected water-quality data from 1992 through 1996. Results from surface-water sampling conducted during 1996?98 in the Upper Colorado River Basin in Colorado indicate that beneficial uses of water were not being impaired by the presence of pesticides in surface waters in the basin.

Colorado↗
USGS2024

Nitrogen deposition weakens soil carbon control of nitrogen dynamics across the contiguous United States

Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta-glucosidase (BG) and N -acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID-19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

contiguous United States↗
USGS1998

Stream habitat characteristics at selected sites in the Georgia-Florida coastal plain

Habitat characterization is part of a multidisciplinary approach to water-quality assessment implemented by the National Water-Quality Assessment Program. Habitat data were collected in the Georgia-Florida Coastal Plain study unit at 24 sites during 1993-95. Data were collected for habitat characteristics at three spatial scales: basin, segment, and reach. Basin data include physiography, land resource provinces, and land use, providing a description of the environmental setting at each site. Segment data include length, gradient, and sinuosity. A Kendall correlation analysis performed on segment characteristics and the log-of-basin area showed a correlation between segment gradient and the log-of-basin area and a correlation between sinuosity and segment length. Reach data consist of field-collected measurements of both instream and riparian habitats. Sand and detritus were the most common channel-bed substrates among the sampled sites. Measurements of channel width, water depth, and bank width and height were used to create cross-sectional profiles of each sampled area. Elevations of selected durations plotted on cross sections illustrated the percentage of time that the banks were inundated at each site. Sites were divided into two groups based on duration of bank inundation (less than or equal to 1 percent and greater than 1 percent). Bank woody vegetation was also sampled and a clustering algorithm known as Two-Way INdicator SPecies ANalysis (TWINSPAN) was used to analyze these data. TWINSPAN divided the sites into two groups based on their vegetation composition. A statistical comparison of the two types of site groups (duration of bank inundation and vegetation) was performed. The significant association between these groups was consistent with the hypothesis that inundation frequency affected riparian vegetation.

Florida, Georgia↗
USGS2024

Characterization of change in tree cover state and condition over the conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Forests↗
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

Background and geologic model for the 2024 U.S. Geological Survey assessment of undiscovered conventional petroleum resources in the Norphlet Formation, U.S. Gulf Coast

The Upper Jurassic Norphlet Formation is a stratigraphic unit located in the subsurface of the United States Gulf coastal plain and offshore Gulf of America (Gulf of Mexico). The Norphlet consists of clastic sediments derived from the southern Appalachian highlands, and was deposited in a continental dryland setting on the margins of the early Gulf of America rift basin. The formation contains a variety of sedimentary facies, including facies representing updip alluvial fans, wadis, red beds, and a widespread erg, or eolian sand sea. The erg facies form the primary reservoirs from which hydrocarbons sourced from the overlying Smackover Formation are produced. Development of the Norphlet began in earnest in the late 1960s, with new discoveries, including large fields at Flomaton, Hatters Pond, and Mobile Bay, continuing through the 2000s–2010s with the discovery of major oil fields in the offshore Desoto Canyon area. Onshore, Norphlet hydrocarbon traps typically are faulted salt anticlines, although many fields also have a stratigraphic trapping component because of the preservation of dune-scale bedforms. Thermal maturity across the Norphlet play varies significantly with depth, resulting in oil production transitioning downdip to natural gas liquids production, then dry gas production; production depths reach to greater than 21,000 feet. A 2024 U.S. Geological Survey assessment divided the Norphlet into four conventional assessment units defined by the type and frequency of trapping mechanisms, sedimentology, and thermal maturity of each area, with little potential for hydrocarbon development observed west of the Mississippi River. Although petroleum resources in the Norphlet were revised downward, it is probable that significant resources remain to be discovered.

Alabama, Florida, Mississippi↗
USGS2025

Water resources related to breccia pipe uranium mining in the Grand Canyon region

Introduction In the arid Grand Canyon region, water resources are limited to primarily the Colorado River and associated tributaries and to groundwater in the form of seeps and springs. Groundwater resources in the region supply water for human use and support diverse and rich ecosystems in the locations immediately surrounding the seeps and springs. Throughout the region, uranium resources occur and may interact with water resources in both mined and unmined uranium deposits. There is a need to better understand groundwater in the region and the effects from uranium mining in order to better manage the limited water resources in the area. This Fact Sheet summarizes results from U.S. Geological Survey studies that were conducted on this topic from 2012 to 2023.

Arizona↗
USGS2025

Near-fault amplification and ground motion variability during the 2019 Ridgecrest, California sequence

We estimate ground-motion variability near the 2019 M 7.1 Ridgecrest earthquake sequence. Accurate seismic hazard estimation requires understanding ground-motion spatial correlations, yet many studies lack the dense station coverage needed to resolve small-scale variability. The 2019 M 7.1 Ridgecrest earthquake sequence presents a unique opportunity to examine ground motions and their spatial correlations at a range of interstation distances. The permanent seismic network was augmented with hundreds of temporary stations including several fault-crossing nodal arrays. We compute the event ( δE i ) and within-event ( δW ij ) residuals from the observed peak ground velocity and peak ground acceleration data to isolate potential sources of ground-motion variability. We then compare δW ij between station pairs that record an event to understand the semivariance of the ground motion versus interstation distance. By fitting an exponential model to the semivariances, we determine a correlation range of 25 km for the Ridgecrest region. Although the exponential model fits the broad-scale increase of semivariance with interstation distance, we also observe smaller-scale trends. We find that ground motions are less correlated for station pairs that are near or across faults that ruptured during the 2019 Ridgecrest sequence. We also find large, positive median δW ij with relative values 2–3 times larger than nearby stations for individual stations’ near-fault traces. Near-fault amplification and greater ground-motion variability can delineate fault zones and may locally increase the seismic hazard.

California↗
USGS2022

U-Pb scheelite ages of tungsten and antimony mineralization in the Stibnite-Yellow Pine district, central Idaho

The Stibnite-Yellow Pine district contains the largest antimony resource in the United States, as well as significant gold, and is a historic producer of tungsten. Application of in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) direct dating of scheelite from two Au-Sb-W ore deposits, Yellow Pine and Hangar Flats, yielded an older group of U-Pb ages in the range of 60.0 ± 2.8 to 57.0 ± 1.1 Ma and a younger U-Pb age for scheelite intergrown with stibnite of 47.4 ± 1.1 Ma. These in situ analyses were calibrated by isotope dilution-thermal ionization mass spectrometry (ID-TIMS) U-Pb lower intercept ages of two coarsely crystalline scheelite samples that yielded ages of 57.52 ± 0.22 and 56.62 ± 0.16 Ma. Scheelite of the latter age is of sufficient quality to serve as a primary reference material for LA-ICP-MS scheelite U-Pb geochronology. The group of older U-Pb scheelite ages agrees with 40 Ar/ 39 Ar ages of 56.9 ± 1.2 to 56.38 ± 0.54 Ma on adularia from Yellow Pine and Hangar Flats, whereas the younger U-Pb scheelite age is similar to an 40 Ar/ 39 Ar age of 46.00 ± 0.40 Ma on adularia from an epithermal gold-silver deposit in the adjacent Thunder Mountain caldera. Our results indicate that the main stage of tungsten mineralization occurred at ca. 57 Ma, whereas the main stage of antimony mineralization occurred at ca. 47 Ma—thereby providing first-time age constraints for antimony and tungsten mineralization in the Stibnite-Yellow Pine district.

Idaho↗
USGS2026

Tephra from Kīlauea’s 2008–2018 lava lake eruption—Proximal deposits and dispersal characteristics

A network of ten buckets was established early in the 2008–2018 summit eruption at Kīlauea to collect proximal tephra ejected from the new, informally named the “Overlook crater”; the buckets were emptied on most days of the eruption thereafter. This report summarizes the results of more than 2,400 different sampling intervals (most 1–3 days long) during the eruption, focusing on the physical and dispersal characteristics of the tephra deposits. The network was within about 300 meters south of the vent to capture tephra dispersed by the dominant northeast trade wind. The juvenile tephra mainly reflected spattering at the southeast (SE) sink, a downwelling area in the southeastern part of the lava lake in the Overlook crater that remained in the same area throughout the eruption, with admixtures of solid rock and secondary minerals derived from the wall of the crater. The proportion of juvenile material to lithic material ranged widely early in the eruption but was generally greater than 90 percent for the last 6 years of the eruption as lake level rose and the crater walls decreased in height and became more stable. The accumulation rate of tephra at each bucket was strongly dependent on the location of the bucket and reflects the interplay between lava lake level and wind direction and speed. The mass per unit area (m/a) of collected tephra was a maximum of about 97 kilograms per square meter for the entire eruption, equivalent to a thickness of about 75 millimeters. Thirty-two explosive events with a volcanic explosivity index of −2 to −4 deposited much of the tephra in the network. Fifteen of these rock-fall-induced events occurred within 6 days of one another. Pele’s hair, a volcanic glass predominantly associated with quieter activity at the vent in the final half of the eruption, was dispersed more than 60 kilometers downwind from the lava lake and formed a nearly continuous deposit near the Overlook crater. This eruption was probably the most frequently sampled long-lasting eruption in history, but most of the deposits are ephemeral. The collected samples, although generally of small mass, are retained by the Hawaiian Volcano Observatory and are available for detailed study.

Hawaii↗
USGS2025

Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy

The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.

Open-File Report↗