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USGS2025

2023 Earthquake Ground-Motion Workshop for the Central and Eastern United States, with a focus on the Gulf and Atlantic Coastal Plains—Agenda and abstracts

The U.S. Geological Survey held a virtual workshop December 7–8, 2023, to share research and ideas about earthquake ground motions in the Central and Eastern United States, with a focus on the Atlantic and Gulf Coastal Plains. The workshop was organized to learn about potential regionalization of ground-motion characteristics (source, path, and site), consider new explanatory variables for site response, and hear and discuss updates on ground-motion research on the Atlantic and Gulf Coastal Plains. The workshop was organized into a series of contributed presentations and three panel discussions held during 2 days. This report documents the agenda, contributed abstracts, and panel summaries.

Scientific Investigations Report↗
USGS2026

A three-dimensional geologic framework model of the northern Great Plains region of Montana, North Dakota, South Dakota, and Wyoming, USA

This report presents a new three-dimensional geologic framework model (GFM) of the northern Great Plains region, encompassing parts of Montana, North Dakota, South Dakota, and Wyoming. The model provides a regionally consistent, geographic information system (GIS)-ready representation of Phanerozoic sedimentary strata, major fault systems, and Precambrian basement geometry across two sedimentary basins and adjacent uplifts. More than 300,000 geologic and geophysical data inputs were synthesized to model 41 stratigraphic horizons and 47 faults, yielding an internally coherent, sealed-volume interpretation of the subsurface. The modeling workflow developed for this study demonstrates an efficient and scalable approach for constructing basin-to regional-scale GFMs in geologically complex and data-variable settings. Although model fidelity varies with data density and quality, the resulting geometry is broadly consistent with 1:500,000-scale geologic mapping and highlights areas where additional geologic study is most needed. The three-dimensional GFM provides a foundational framework to support groundwater, energy, and mineral resource assessments, and offers a transferable methodology for potential future U.S. Geological Survey efforts to build large-area subsurface models in underexplored regions of the United States.

Montana, North Dakota, South Dakota, Wyoming↗
USGS2025

Identifying precursors and tracking pulses of magma ascent in multidisciplinary data during the 2018–2023 phreatomagmatic eruption at Semisopochnoi Island, Alaska

The 2018–2023 phreatomagmatic eruptions at Semisopochnoi Island, Alaska produced abundant long-period (LP) seismicity, harmonic and broadband tremor, and explosion signals over several well-monitored periods of eruption and quiescence. The corresponding dataset provides an excellent opportunity to investigate precursory and syn -eruptive geophysical signals of long-lived phreatomagmatic eruptions using multiparameter observations. We generated explosion and LP event catalogs through novel implementations of the REDPy ( Hotovec-Ellis, 2024 ) repeating event detector in mid-2021 following a network upgrade and the onset of a new phase of the eruption. The hundreds of detected explosions show a high degree of infrasound waveform similarity over more than a year, indicating a repeating source mechanism likely associated with explosive magma-water interaction. The seismic LP catalog shows that events began over a month prior to renewed explosive activity at the beginning of August 2021, and that lower frequency index (FI) LPs were generated in the week prior to the onset of explosions. We applied a recently developed machine learning tool (VOISS-Net, Tan et al., 2024 ) to catalog abundant broadband and harmonic seismic tremor recorded before and during the renewed explosive activity, along with LPs and explosions. The tremor catalogs complement the LP and explosion catalogs by filling out the seismic sequence with the dominant signal types. Together, these catalogs reveal a seismic sequence of renewed unrest that started with several weeks of LP events, followed by LPs with lower FI values and harmonic tremor in the days prior to explosive activity, and finally the onset of discrete explosions and broadband eruption tremor. We interpret this sequence as the ascent of a new pulse of magma that first interacted with the hydrothermal/groundwater system to produce LPs, followed by harmonic tremor, and that ultimately drove explosive magma-water interactions and periods of continuous ash emissions. The 2021 seismic sequence, in combination with long-term records of satellite SO 2 emissions, deformation from interferometric synthetic aperture radar (InSAR) analysis, ash sample analysis, infrasound, and volcano tectonic seismicity, allows us to interpret the entire 9-year period of unrest and eruption that began with an intrusion and earthquake swarm in 2014.

Alaska↗
USGS2024

The SCEC/USGS community stress drop validation study using the 2019 Ridgecrest earthquake sequence

We introduce a community stress drop validation study using the 2019 Ridgecrest, California, earthquake sequence, in which researchers are invited to use a common dataset to independently estimate comparable measurements using a variety of methods. Stress drop is the change in average shear stress on a fault during earthquake rupture, and as such is a key parameter in many ground motion, rupture simulation, and source physics problems in earthquake science. Spectral stress drop is commonly estimated by fitting the shape of the radiated energy spectrum, yet estimates for an individual earthquake made by different studies can vary hugely. In this community study, sponsored jointly by the U. S. Geological Survey and Southern/Statewide California Earthquake Center, we seek to understand the sources of variability and uncertainty in earthquake stress drop through quantitative comparison of submitted stress drops. The publicly available dataset consists of nearly 13,000 earthquakes of M1 to 7 from two weeks of the 2019 Ridgecrest sequence recorded on stations within 1-degree. As a community study, findings are shared through workshops and meetings and all are invited to join at any time, at any interest level.

Seismica↗
USGS2025

Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent

The increased demand for clean energy technology and a significant reliance on foreign supply chains have given impetus to understanding critical mineral systems and locating potential resources within the United States. At least thirteen critical mineral-bearing systems have been identified throughout the U.S. southern Midcontinent (Hofstra and Kreiner, 2020) but much of the region’s geologic framework is concealed by vegetation and sedimentary cover that hinder traditional geologic mapping efforts. Airborne geophysical data provide an effective way to overcome these obstacles and to provide additional insight into the deeper structures that underlie shallow mineralization. However, legacy airborne magnetic and radiometric data were collected using now-outdated instruments and methods, inconsistent survey parameters, and large flight-line spacings resulting in low-resolution data that present challenges to regional-scale study and interpretation. Over the last decade, the U.S. Geological Survey Earth Mapping Resources Initiative (EMRI) and National Cooperative Geologic Mapping Program have conducted a series of high-resolution airborne magnetic and radiometric surveys across the southern Midcontinent (Fig. 1) as part of an effort to improve understanding of the geophysical framework and natural resource potential in the region. These surveys are designed using modern survey methods and instruments with consistent parameters for flight-line spacing and flight height relative to magnetic sources. The EMRI airborne surveys are planned in collaboration with State geological surveys based on focus areas (Dicken et al., 2022) according to the presence of or potential for critical mineral deposits. High-resolution airborne magnetic and radiometric data cover focus areas such as the southeast Missouri iron metallogenic province and South-Central iron-oxide-apatite (IOA) – iron-oxide-copper-gold (IOCG) province, the Magnet Cove alkaline-carbonatite complex, the Midwest Permian ultramafic dike district, the Illinois-Kentucky fluorspar district, and several Mississippi Valley-type lead-zinc deposits and districts (Fig. 1). These focus areas represent known deposits or prospective host systems of critical minerals including rare earth elements (REEs), platinum-group elements (PGEs), cobalt, lithium, fluorspar, niobium, titanium, vanadium, lead, zinc, gallium, germanium, and many more. Other significant geologic and geophysical features covered include the Reelfoot rift, the New Madrid seismic zone, the Illinois basin, the Arkoma basin, the South-Central magnetic lineament, and the Kentucky-Tennessee magnetic anomaly (Fig. 1). This presentation focuses on new airborne magnetic and radiometric data with continuous coverage across parts of six states, preliminary interpretations, examples of geologic mapping applications, and discussion of newly discovered magnetic anomalies and follow-up investigations.

Conference Paper↗
USGS2024

Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020

Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow flood frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging. In response to a growing concern regarding nonstationarity in peak streamflows in the region, the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions. Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p -value cutoff point. A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected. A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State. Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.

South Dakota↗
USGS2026

Status and understanding of groundwater quality in the San Joaquin Valley Kern County subbasin domestic-supply aquifer study unit, 2022—California GAMA Priority Basin Project

The quality of water accessed by domestic wells (here referred to as domestic groundwater resources) in the San Joaquin Valley Kern County subbasin (basin number 5-022.14) was assessed as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project (GAMA-PBP), in cooperation with the California State Water Resources Control Board. Kern County is at the southern end of the San Joaquin Valley in California, and about 30,000 residents are estimated to use privately owned domestic wells for drinking water. Domestic wells typically draw from shallower parts of the aquifer system than public-supply wells and can be more vulnerable to effects from surface activities. Kern County is host to a highly productive agricultural industry, with Bakersfield as the main urban center. The Kern River runs through Bakersfield from the southern Sierra Nevada and intersects the Kern Water Bank, one of the largest groundwater banking operations in California, at the Kern River Intertie. The section of the Kern River running through the Kern Water Bank is dry most years. Kern County also encompasses some of the most productive oil and gas basins in California, with extensive underground and surface disposal of oil-field wastewater. This study was based on data collected from 33 sites sampled by the U.S. Geological Survey for the GAMA-PBP in 2022. To provide context for the water quality assessment, measured concentrations were compared to regulatory and non-regulatory health-based and aesthetic benchmarks. A grid-based method was used to estimate the proportions of the groundwater resources used for domestic-supply wells that have water-quality constituents below (low relative concentration), approaching (moderate relative concentration), or above (high relative concentration) benchmark concentrations. At least one measured constituent with a regulatory benchmark was categorized as having a high relative concentration in 72 percent of the aquifer area used for domestic groundwater resources. Inorganic constituents were detected at high concentrations in 45 percent of the domestic groundwater resources, and the constituents detected above regulatory benchmarks were arsenic, nitrate, and uranium. At least one organic constituent was detected at high concentrations in 41 percent of the domestic groundwater resources, and the constituents exceeding regulatory benchmarks were the fumigants 1,2,3-trichloropropane (1,2,3-TCP), 1,2-dibromo-3-chloropropane (dibromochloropropane [DBCP]), 1,2-dibromoethane (EDB), and the per-and polyfluoroalkyl substance (PFAS) perfluorooctanesulfonate. The disinfection by-product chloroform, the fumigant 1,2-dichloropropane, the herbicides atrazine and hexazinone, and the herbicide degradates 2-chloro-6-ethylamino-4-amino-s-triazine, 2-chloro-4,6-diamino-s-triazine, 4-hydroxychlorothalonil, and metolachlor sulfonic acid were detected in more than 10 percent of domestic groundwater resources, but concentrations did not exceed regulatory benchmarks. Land use, groundwater age (fraction of modern water and mean age), and geochemical environment (oxic or anoxic conditions, pH, alkalinity) were associated with the distribution of high relative concentrations of inorganic and organic constituents. Young, oxygenated water is recharged along the Kern River and adjacent recharge ponds, or as irrigation water in the agricultural areas. High concentrations of nitrate and volatile organic compounds occurred in the oxic water in urban and agricultural areas. The fumigants 1,2,3-TCP, DBCP, and EDB were reported throughout the agricultural areas, whereas chloroform, tetrachloroethene, and PFAS were associated with urban land use. High uranium concentrations were associated with young, modern groundwater in agricultural areas with low pH and high bicarbonate. Total dissolved solids increased with distance from the Kern River, as the contributions of fresh, oxic water decreased. High concentrations of arsenic were present in older anoxic or alkaline groundwater away from areas of recharge. Overall, groundwater age, redox conditions, and the source of recharge as a result of different land uses contribute to large aquifer-scale portions of domestic groundwater resources that exceed health-based benchmarks for nitrate, uranium, and fumigant concentrations.

California↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS1996

Analysis of nutrients in the surface waters of the Georgia–Florida Coastal Plain study unit, 1970–91

During the early phase of the Georgia-Florida National Water Quality Assessment study, existing information on nutrients was compiled and analyzed in order to evaluate the nutrient concentrations within the 61,545 square mile study unit. Evaluation of the nutrient concentrations collected at surface-water sites between October 1, 1970, and September 30, 1991, utilized the environmental characteristics of land resource provinces, land use, and nonpoint and point-source discharges within the study unit. Long-term trends were investigated to determine the temporal distribution of nutrient concentrations. In order to determine a level of concern for nutrient concentrations, the U.S. Environmental Protection Agency (USEPA) guidelines were used: (1) for nitrate concentrations, the maximum contaminant level in public-drinking water supplies (10 mg/L); (2) for ammonia concentrations, the chronic exposure of aquatic organisms to un-ionized ammonia (2.1 mg/L); (3) for total-phosphorus concentrations, the recommended concentration in flowing water to discourage excessive growth of aquatic plants (0.1 mg/L); and (4) for kjeldahl concentrations, however, no guidelines were available. For sites within the 10 major river basins, median nutrient concentrations were enerally below USEPA guidelines, except for total-phosphorus concentrations where 45 percent of the medians exceeded the guideline. The only median ammonia concentration that exceeded the guideline occurred at the Swift Creek site (3.4 mg/L), in the Suwannee River basin, perhaps due to wastewater discharges. For all sites within the Withlacoochee, Aucilla, and St. Marys River basins, median concentrations of nitrate, ammonia, and total phosphorus were below the USEPA guidelines. Nutrient data at each monitoring site within each major basin were aggregated for comparisons of median nutrient concentrations among major basins. The Ochlockonee and Hillsborough River basins had the highest median nutrient concentrations, the Aucilla River basin had the lowest. Median concentrations of nitrate and ammonia among all major basins were below USEPA guidelines. The median total-phosphorus concentrations for the following river basins exceeded the USEPA guideline: Hillsborough, St. Johns, Suwannee, Ochlockonee, Satilla, Altamaha, and Ogeechee. Although nutrient concentrations within the study unit were low, long-term increasing trends were found in all four nutrients. All 18 study-unit wide nitrate trends had increasing slopes ranging from less than 0.01 to 0.07 (mg/L)/yr. The range in slope for the 13 ammonia trends was -0.03 to 0.01 (mg/L)/yr with 6 increasing trends in the northern part of the study unit. Of the 17 total-phosphorus trends found in the study unit, 10 were found at sites where the median concentration exceeded the USEPA guideline. At these 10 sites, 4 sites had increasing trends with slopes ranging from less than 0.01 to 0.07 (mg/L)/yr, 5 sites had decreasing trends with slopes ranging from -0.01 to -0.24 (mg/L)/yr, and one site showed a seasonal concentration trend. Median nutrient concentrations were significantly different among the four land resource provinces: Southern Piedmont, Southern Coastal Plain, Coastal Flatwoods, and Central Florida Ridge. As a result, nutrient concentrations among basins with similar nutrient inputs but located within different land resource provinces are not expected to be the same due to differences in the combination of factors such as soil permeability, runoff rates, and stream channel slopes. This concept is an important consideration in designing a surface-water quality network within the study area. For the most part, the Coastal Flatwoods showed the lowest median nutrient concentrations and the Southern Coastal Plain had the highest median nutrient concentrations. Lower median nitrate concentrations in surface-water basins were associated with the forest/wetland land-use category and higher median concentrations of nitrate and ammonia with the urban category when land-use percentages were classified into four land-use categories (agriculture, forest/wetland, mixed, and urban). These results were reasonable based on expected high nutrient inputs from urban areas and low inputs from forested and wetland areas. However, the lack of association between high nutrient concentrations and the agricultural land-use category was not expected since high nutrient inputs are generally needed for agriculture production.

Florida, Georgia↗
USGS2026

Geophysical architecture and geochronology of the Neoarchean Mentor anorthosite intrusive complex, northwestern Minnesota: Largest anorthosite complex of the Superior Province?

The Neoarchean Mentor anorthosite intrusive complex (MAIC) lies within the Wawa subprovince in northwestern Minnesota, in a region where the Wawa, Quetico, and Wabigoon subprovinces are juxtaposed in close proximity. Archean rocks are entirely concealed, and interpretations are developed from aeromagnetic, gravity, and borehole samples. The MAIC includes both anorthosite (dense, weakly magnetized) and oxide-rich gabbro (strongly magnetized) lithologies. Anorthosite is coarse-grained to megacrystic, intensely altered, and locally brecciated. Pervasive epidote alteration enhanced the density of the anorthosite via introduction of higher-density mineral assemblages, explaining why the MAIC produces a significant gravity high. Oxide-rich gabbro forms a border phase of the MAIC and has potential for vanadium, chromium, and titanium mineralization, and produces a strong aeromagnetic high. The MAIC is interpreted to extend over an area of 640 km 2 , making it the largest known anorthosite complex of the Superior Province, as measured by preserved areal extent. Modeling indicates the MAIC extends more than 6 km into the subsurface. A new Pb–Pb zircon age of 2737.2 ± 4.5 Ma is interpretated as the crystallization age of anorthosite within the MAIC, showing that the MAIC formed well before the ca. 2690 Ma Shebandowanian orogeny, and raising new questions about correlations with other parts of the Wawa subprovince. A low-density batholith, here informally called the Fertile batholith, is interpreted to intrude the southern part of the MAIC. A new Pb–Pb zircon age of 2701.1 ± 6 Ma is interpreted as the magmatic age of the Fertile batholith.

Minnesota↗
USGS2026

Production of mineral commodities and geospatial map of the mineral industries and related infrastructure of China

As part of the U.S. Geological Survey’s (USGS) mission to distribute global mineral information and analyze supply chains, this study provides a comprehensive review of the global significance of China’s mineral production and capacity in 2023. Of 77 mineral commodities in the USGS dataset, China produced 74 and was the world’s first-ranked producer for 39 of the 74. Compared to the high share of global mineral production, including up to 98 percent of global gallium production, the country’s share of global mineral reserves was relatively small, ranging from 20 percent (zinc ore) to 52 percent (tungsten ore). China’s imports of metal ores, slag, and ash accounted for 64 percent of global imports of such commodities by value. The country’s exports of base metals and articles of base metal accounted for 17 percent of the global exports. To help nongeographic information system users assess the spatial distribution of mineral mines, processing facilities, and ports for trades in China, this study created a geospatial (also called “georeferenced”) portable document format (GeoPDF) map. In addition, the GeoPDF contains mineral resource tracts (such as antimony, copper, potash, coal, and oil and gas), exploration sites, and energy infrastructure based on the preexisting USGS data.

Open-File Report↗
USGS2025

Estimation of the accessible and useful resource base for electric-grade enhanced geothermal systems (EGS) resources of the Great Basin, USA

Scientists with the U.S. Geological Survey (USGS) recently completed a provisional assessment of the electric-grade geothermal resources associated with the low-permeability geologic formations of the Great Basin, USA, where resources are assumed to be accessible using enhanced geothermal systems (EGS) technologies (i.e., the engineering of sufficient permeability to facilitate efficient heat extraction). This assessment required estimation of the accessible resource base (electric-grade heat [>90ºC] at depths where drilling and stimulation are deemed achievable using current technology) and useful resource (heat that can be extracted from the accessible region). Electric-grade heat can be estimated from existing temperature models. The accessible resource base can be estimated as the electric-grade heat that exists at depths shallower than 6 km based on the limitations of current drilling and stimulation technologies, along with evidence for sustained natural fracture conductivity at depth. The useful part of the accessible heat can be estimated as the product of three efficiencies and factors: the heat extraction efficiency, the viable geology factor, and the reservoir spacing efficiency. The accessible and useful parts of the resource can be estimated in units of heat, or in units of electric power using an electrical conversion efficiency, which is a function of resource temperature. We also estimate the ranges for each of the efficiencies and describe the motivations behind the choice of best estimates used for the recent assessment. An analytic solution is provided for the useful resource above any depth (in units of electric power), where efficiency estimation assumes nearly steady heat extraction rates that cool reservoirs to 90ºC over 30 years of power generation.

Great Basin↗
USGS2026

Small-volume tephra deposits of the May 1924 explosions from Halemaʻumaʻu, Kīlauea volcano, and their origin

More than 50 explosive eruptions occurred from Halemaʻumaʻu at Kīlauea volcano over 17 days from May 11 to 27, 1924. Ballistics weighing as much as 14,000 kg were ejected and most landed within 2 km of the vent. Fine ash made up a major component of the tephra and was dispersed tens of kilometers downwind. Draining of the Halemaʻumaʻu lava lake occurred in late February 1924, with the crater floor eventually subsiding by a further ∼70 m (to ∼180 m below the crater rim) by the time the first explosions took place during the night of May 10–11. The largest explosions occurred on May 17–18 and smaller explosions continued until May 27, at which point Halemaʻumaʻu had more than doubled in width and depth. The explosions generated plumes reaching up to ∼10 km high with ballistics ejected up to 2 km from the crater. Almost 100 years later, we investigate and characterize the preserved tephra deposits within ∼3 km of the 1924 crater rim. Grain size and shape analyses were performed on 202 samples collected from 34 tephra profiles using dynamic image analysis, with a subset of layers from nine tephra profiles used for componentry (200 grains per layer in the 0.5–1 mm size fraction). Additionally, we characterize the average diameters (using the five largest clasts) at 216 locations and measure the average diameters of 2291 ballistics (largest per ∼100 m 2 area). Physical descriptions from fieldwork and grain size distributions were used to subdivide the tephra layers into five lithofacies: coarse homogeneous, fine homogenous, red ash, accretionary lapilli-bearing, and finely laminated. Grain size versus shape data show a range of values that demonstrate most grains are dense, smooth, and equant, in alignment with lithic clasts dominating the tephra componentry. The fine grained and accretionary lapilli-bearing nature of some of these lithofacies confirms that water influenced the style of the explosions. However, we also note juvenile clasts within many of the tephra layers, indicating that many of the layers were formed during phreatomagmatic explosions (sensu stricto), despite the eruptive mechanism being dominantly phreatic. Juvenile clasts are more abundant higher in the tephra profiles, suggesting that juvenile magma was more involved later in the explosive sequence. Thermal and hydrologic modeling indicate that groundwater inflow into a short-lived, small-diameter volcanic conduit (10-m to 120-m-diameter used for modeling) during the 78–85 days preceding the first explosion provides a physically plausible mechanism for this eruptive sequence.

Hawaii↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS2025

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska↗
USGS2026

Bascom Laser Diffraction Sedimentology Laboratory, Reston, Virginia

Introduction At the Bascom Laser Diffraction Sedimentology Laboratory, which is located in the Florence Bascom Geoscience Center at U.S. Geological Survey (USGS) headquarters in Reston, Virginia, scientists use physical sedimentology and particle characterization techniques to conduct detailed sediment characterization. Scientists address research problems in collaboration with other USGS science centers, State geological surveys, commercial industry, universities, and other partners. Laboratory capabilities include laser diffractometry for quantitative particle-size analysis, portable x-ray fluorescence (XRF) analysis for determining elemental abundances in rock or sediment samples, petrographic analysis of geologic media, and mechanical sieve analysis. These methods are used to analyze soil and sediment core material from terrestrial, marine, and lacustrine environments, surface sediments from coastal regions, and calcareous materials. Work done by the laboratory supports geologic mapping, resource assessments, land change studies, and geohazard analyses.

Fact Sheet↗
USGS1998

Design, revisions, and considerations for continued use of a ground-water-flow model of the coastal plain aquifer system in Virginia

A digital numerical model of the ground-water-flow system in the Virginia Coastal Plain was constructed as part of the Regional Aquifer System Analysis program of the U.S. Geological Survey and subsequently revised based on reinterpretations of the hydrogeologic framework. The revised model has been incorporated by the Virginia Department of Environmental Quality as a means to evaluate the effects of existing and proposed ground-water withdrawals. The revised model, which is documented here, includes many design features of the original model. Principal modifications are (1) reassignment of some model layers to represent different aquifers, (2) replacement of applied recharge and the uppermost surface-water layer by constant-head cells to represent the unconfined aquifer, and (3) revision of the lateral extents and transmissivity and vertical leakance values assigned to model layers. Ground-water levels simulated by the revised model under steady-state conditions, using withdrawal rates representing the period 1978-80, generally are similar to the water levels simulated by the original model under transient conditions using the same withdrawal rates. Differences probably result largely from changes in transmissivity and vertical leakance values. T he revised model enables the continued evaluation of development of the large and complex aquifer system. Improved information on parts of some aquifers has been incorporated. Only large, regional-scale trends in ground-water water levels, flow directions, and flow rates are simulated, however, and not local trends and (or) short-term changes in water level and flow. Changing hydraulic stresses, knowledge of hydrogeologic conditions, and resource-management needs require periodic revision of the model to maintain its usefulness for the management of ground-water resources in the Virginia Coastal Plain.

Virginia↗
USGS2024

Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional ( > 100 km 2 ) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.

Natural Hazards and Earth Systems Sciences (NHESS)↗