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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,662 records · Page 72Linked to original sources
USGS2026

Decadal shifts in groundwater age detected by environmental tracers across California, USA

Groundwater age offers important insight into recharge, storage, and contamination risk. Although models predict age changes can be driven by pumping and climate variability, direct observational evidence remains limited. Here, we analyzed paired environmental tracer suites (tritium, carbon-14, and tritiogenic helium-3) collected a decade apart from 268 wells across California to assess the prevalence of groundwater age transience. Travel-time distribution models and statistical tests indicated age transience at 29% of sites, occurring most often in agricultural regions, such as the San Joaquin Valley and Southern Coast Ranges, where large carbon-14 changes coincided with substantial nitrate and chloride shifts. Sites with tritiogenic helium-3 data showed more frequent age transience, underscoring the value of multi-tracer data sets. These results provide the first regional evidence of widespread groundwater age change and a method for detecting changing water balances with implications for groundwater sustainability and water quality.

California↗
USGS2025

Ungulate migrations of the Western United States, volume 5

Many ungulates migrate between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. In 2018, the U.S. Department of the Interior established Secretarial Order 3362, which provided Federal support to expand existing research efforts to study ungulate populations and conserve their migrations by enhancing habitat quality for ungulates across the Western United States. In response to the order, the U.S. Geological Survey (USGS) created the Corridor Mapping Team, which is a collaboration among 11 State agencies, regional and Federal partners, and an expanding number of Tribal wildlife agencies. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States and publishes them in the USGS “Ungulate Migrations of the Western United States” report series. This report details migrations and seasonal ranges from 36 additional herds and includes 2 herd updates detailed in previous reports. The Corridor Mapping Team has mapped the migrations and seasonal ranges of 218 unique herds for the report series, including this report. The report series serves as a map-based inventory of the ungulate migrations across the Western United States for biologists, managers, policymakers, and conservation practitioners. Building on the previous report volumes in the series, volume 5 additionally describes some of the local and national initiatives that are incorporating the products, tools, and information from this growing USGS report series.

Navajo Nation↗
USGS2025

ARCHI: A new R package for automated imputation of regionally correlated hydrologic records

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in “target” records by linear regression using more complete “reference” records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

California, New York↗
USGS2025

Evidence for offset of Cretaceous plutons by the Tintina fault in eastern Alaska: Implications for regional metallogeny

Cretaceous magmatism in eastern interior Alaska is voluminous, but temporally and spatially diverse – suggestive of varying sources and drivers. More than 150 new U-Pb zircon and more than 500 geochemical analyses of Cretaceous plutonic units allow for the grouping of distinct plutonic suites. Magmatism was continuous from 120-66 Ma but can be grouped into temporally distinct pulses from ca. 115-100 Ma, 100-90 Ma, and 75-66 Ma. Geochemical diversity occurs during each pulse, further distinguishing multiple suites. Diverse metallogenic epochs are strongly correlated to pluton chemistry. Mineralization is largely absent prior to 108 Ma. From 108-100 Ma, plutonism is coeval with sparse, but notable Au-quartz veins with variable Bi, As, W, and Mo. From 100-90 Ma, intrusion-related mineralization zones from Au-Cu(-Bi) and U-Th in the northwest to central Au- Bi-As-Te(-W), and Mo-W to the southeast. Porphyry style Cu-Mo(-Au) occurrences occur with the latest Cretaceous plutons emplaced from 75-66 Ma . Restoration of ~450 km of dextral movement on the Tintina fault and comparison of metallogenic and geochemical characteristics of Alaska plutons suggest 100-90 Ma plutons may be the continuation of the metallogenically significant Tombstone, Mayo, and Tungsten suites from the Yukon.

Alaska↗
USGS2026

A case study of maximum depositional ages from terrestrial sandstones near the Cretaceous—Paleogene transition, western Williston Basin, USA

We present a new Bayesian method for deriving maximum depositional ages from detrital K-feldspar using total-fusion 40 Ar/ 39 Ar data. Individual analyses weighted by K/Ca ratio, age uncertainty, and percent radiogenic argon prioritize a result to come from accurately measured volcanic sources. Results from this method applied to sandstones from the Hell Creek region of northeastern Montana show that detrital K-feldspar maximum depositional ages align closely with detrital U-Pb zircon ages as well as tephra based chronostratigraphic constraints from both 40 Ar/ 39 Ar and U-Pb data. An age model informed by maximum depositional ages and available tephra data provides an estimate of 1.74 ± 1.04 Ma for the duration of deposition for the Hell Creek Formation. Combined age model and maximum depositional age data suggest ≤ 1.84 Ma of missing time is represented by the Hell Creek and Fox Hills formational disconformity, coinciding with the final regression of the Western Interior seaway.

Montana↗
USGS2025

Grammar to graph—An approach for semantic transformation of annotations to triples

Data annotation is the process of labeling data to show the outcome that a related data model should predict. In this study, annotation data were transformed into semantic graph triples, mainly for use with the Resource Description Framework (RDF), a type of entity-relationship-attribute data model for graph databases. The transformation of annotation data to semantic graph triples provides complex linguistic meaning with data handling advantages such as reduced data storage needs, improved logical specification of relations between objects, and reusable classes and properties that support logic and inference. A grammar-based framework in graph form supports user questions and queries. The words defining approximately 334 topographic feature types compiled by the U.S. Geological Survey were tokenized as units of analysis and grouped by part of speech. Their dependency relations were identified for this study using natural language processing libraries. Dependency concepts are used as structured semantic relations among part-of-speech classes. Tokens, units equivalent to words, form instances of classes and were quantified within a tabular output format using PostgreSQL data storage software. Table data were logically aligned as triples following a mapping file and stored with an ontology file using Ontop virtual triplestore software. A grammar ontology schema for the data was synchronized to match queries whose results validated the graph’s structure. The text analysis produced 8 part-of-speech classes of content words for object representations and 4 classes of function words for operational applications. Dependency relations formed 27 ontology properties for topographic subgraph structures. Token occurrences shaped overall ontology salience and formed a lexicon of syntactic terms for subgraph objects and properties. The schema ontology of class and property population shapes formed the lexicon of English terms. SPARQL Protocol and RDF Query Language (SPARQL) was used with the lexicon to conform data to RDF guidelines. This study confirms the hypothesis that although linguistic logic varies from description logic, its approximation applies to ontology design. Property and query use case patterns extracted from the analysis support queries concerning complex topographic relations and patterns normally embedded within text definitions. The method used in this study could be applied to text forms in other domains, such as survey notes.

Scientific Investigations Report↗
USGS2025

A new groundwater energy transport model for the MODFLOW hydrologic simulator

Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.

Groundwater↗
USGS2025

The abandoned mine inventory of the United States—A brief summary

The Infrastructure Investment and Jobs Act of 2021 required the Secretary of the Interior to establish a program to inventory abandoned hard-rock mines in the United States. The Department of the Interior’s Office of Environmental Policy and Compliance asked the U.S. Geological Survey’s Mineral Deposit Database project (USMIN) to use existing data sources to build an inventory of all individual abandoned mine features in the United States. In addition to feature locations, this new database documents the surface land management agency, associated physical and environmental hazards, and any completed mitigation efforts. This information will improve risk assessment and support land management efforts, including hazard mitigation, ecosystem restoration planning, and reclamation. This fact sheet provides a brief overview of USMIN’s collaborative efforts with Federal, State, and Tribal agencies to build a comprehensive and authoritative national inventory of abandoned mine features.

Fact Sheet↗
USGS2026

Simulation of groundwater flow to evaluate hydrogeologic controls on a PFAS plume, Coakley Landfill Superfund site, Rockingham County, New Hampshire

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been detected at combined concentrations above 2,000 nanograms per liter (ng/L) at groundwater seep locations near the Coakley Landfill Superfund site, in North Hampton, New Hampshire. The landfill was active from 1972 to 1985. An impermeable cap was placed on the landfill in 1998. The adjacent area to the Coakley Landfill has many water supply wells, and transport of PFAS compounds to the wells is a concern. Fracture anisotropy in the underlying bedrock aquifer complicates the understanding of PFAS transport because groundwater preferentially travels along fractures that may not align with the prevailing groundwater flow direction. In 2018, the U.S. Environmental Protection Agency and the U.S. Geological Survey began an investigation of the groundwater flow from the Coakley Landfill site. This report describes the modification of a numerical groundwater-flow model for the local area around the Coakley Landfill and summarizes findings of the investigation. In addition, this report includes a brief description of PFOA and PFOS occurrence, a discussion of model construction, evaluation of model performance through calibration, and discussion of simulation results for two periods (before and after capping). Limitations are also discussed. Results show that simulated groundwater flow moves from the Coakley Landfill to the west and north. Advective transport modeling using particle tracking shows that groundwater from the landfill discharges primarily to streams to the west and north, and a small amount is transported to distal wells. Dilution of contaminants through advection and dispersion likely plays a role in whether PFAS compounds from the landfill will be detected above laboratory reporting levels at distal wells.

New Hampshire↗
USGS2024

Earthquake effects surveyed during the nineteenth century as ecological features of Chinookan tidelands

Lasting effects of a Cascadia earthquake in 1700 were documented during surveys of Chinookan tidelands near the mouth of the Columbia River between 1805 and 1868. The effects resemble estuarine consequences, near Anchorage, of the 1964 Alaska earthquake: fatal drowning of subsided meadows and forests by post-earthquake tides, rebirth of marshes and forests through post-earthquake sedimentation, and uplift. Chinookan remains of killed forests were recorded by James Graham Cooper, John J. Lowell, and Cleveland Rockwell. Cooper, attached to a railroad survey and the Smithsonian Institution, wrote of redcedar stumps and trunks standing dead in tidal marshes of Shoalwater (now Willapa) Bay. Two such snags served as bearing trees for Lowell as he platted a Shoalwater Bay township under contract with the General Land Office. Rockwell, of the US Coast Survey, flecked landward edges of tidal flats west of Astoria with symbols that evoke remains of a bygone spruce forest. The Lewis and Clark Expedition, while in that area in 1805–1806, mapped and puzzled over tideland vegetation that post-1700 succession helps explain.

Alaska, British Columbia, California, Oregon, Wash↗
USGS2025

Earthquake magnitude and source parameter estimation with a distributed acoustic sensing dataset in the Gorda subduction zone

Distributed acoustic sensing (DAS) systems offer a cost‐effective way to create large‐scale strainmeter arrays for seismological applications using fiber‐optic cables. DAS‐based strain measurements are known to be influenced by various factors, bringing into question their general reliability for accurate earthquake characterization. A 15‐km‐long DAS deployment in northern California was operational within 3 days of the 2022 M w 6.4 Ferndale earthquake and ran continuously throughout the aftershock sequence. We utilize these aftershock data to validate DAS‐based strain measurements in two ways. We first test the accuracy of DAS‐based magnitude estimates from peak dynamic strains by comparing them with magnitude and attenuation scaling relations derived independently from traditional borehole strainmeter (BSM) data. We demonstrate that DAS‐based magnitudes are comparable to BSM‐based magnitudes when corrections for variations in site response along the fiber‐optic cable are properly made. Magnitude errors are spatially correlated, potentially because of factors such as finite‐fault effects (e.g., stress drop) or more complex, unmodeled path attenuation or because of wave propagation effects in heterogeneous media. We then apply more advanced source characterization methodology to the DAS data using a time‐domain empirical Green’s function (EGF) deconvolution approach to measure details of the moment rate history. The EGF approach using DAS data depends on careful treatment of distorting factors such as anthropogenic sources of noise and optical phase wrapping but successfully isolates source spectra for moderate‐magnitude earthquakes: source spectral ratios obtained from DAS data, broadband seismometer data, and BSM data in the same region show consistent results, revealing differences in directivity and spectral shape among earthquakes. Although further research is needed to refine source‐time‐function estimation techniques for DAS data, particularly for larger magnitude events, these case studies demonstrate the clear potential of DAS for earthquake source characterization.

California↗
USGS2024

(Re)discovering the seismicity of Antarctica: A new seismic catalog for the southernmost continent

We apply a machine learning (ML) earthquake detection technique on over 21 yr of seismic data from on‐continent temporary and long‐term networks to obtain the most complete catalog of seismicity in Antarctica to date. The new catalog contains 60,006 seismic events within the Antarctic continent for 1 January 2000–1 January 2021, with estimated moment magnitudes (⁠Mw ⁠) between −1.0 and 4.5. Most detected seismicity occurs near Ross Island, large ice shelves, ice streams, ice‐covered volcanoes, or in distinct and isolated areas within the continental interior. The event locations and waveform characteristics indicate volcanic, tectonic, and cryospheric sources. The catalog shows that Antarctica is more seismically active than prior catalogs would indicate, examples include new tectonic events in East Antarctica, seismic events near and around the vicinity of David Glacier, and many thousands of events in the Mount Erebus region. This catalog provides a resource for more specific studies using other detection and analysis methods such as template matching or transfer learning to further discriminate source types and investigate diverse seismogenic processes across the continent.

Seismological Research Letters↗
USGS2025

Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning

As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.

Nankai subduction zone↗
USGS2025

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

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

Applied Computing and Geosciences↗
USGS2025

Sand provenance boundary in the Mu Us Sandy Land of northern China

Desert dunes are often assumed to have uniform mineral compositions due to extensive mixing during lateral transport, which complicates provenance studies. The Mu Us Sandy Land in north-central China, near the East Asian summer monsoon precipitation boundary, experiences a wetter climate than most deserts. Climate wetting as a result of a warming climate, and the ‘Sand Control Project’ implemented by the Chinese government to decrease the lateral movement of sand dunes in this area provide an opportunity to study surface processes of sand production and transport. Previous studies using zircon U Pb geochronology and heavy mineral composition indicate distinct sand sources for the Mu Us Sandy Land: local basement-derived middle Yellow River sediments and recycled dried-up lacustrine sediments for the eastern part, and northeastern Tibetan Plateau-derived upper Yellow River sediments for the western part. However, zircons and heavy minerals only represent trace amounts of the bulk mineralogy within a sand dune, so broader provenance analysis targeting common minerals is essential. We focus on the area near the proposed provenance difference boundary between the western and eastern Mu Us Sandy Land, using comprehensive sampling and provenance techniques to confirm distinct provenance characteristics and delineate the provenance boundary. Our findings reveal that sand from most of the Mu Us Sandy Land originated from the erosion of local basement by the middle Yellow River and recycled local dried-up lacustrine sediments, whereas the southwestern corner and the neighboring western-central Chinese Loess Plateau received sediments from the distal northeastern Tibetan Plateau.

Mu Us Sandy Land↗
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↗
USGS2026

Deep groundwater total dissolved solids mapping in the Dakota Group, Williston Basin, USA

Growing concern about the quantity of available freshwater around the world has led to interest in surveying groundwater total dissolved solids (TDS) below water well depths. Deep TDS has not been systematically mapped, and there is much to learn about the distribution and controls on deeper groundwater. In sedimentary basins across the United States, groundwater resources often overlie hydrocarbon resources, providing an opportunity to use borehole geophysical data collected for hydrocarbons to characterize groundwater and pore space resources. This study adapts a recently developed subsurface geostatistical and geophysical modeling approach to continuously map groundwater TDS, porosity, and temperature in the Dakota Group of the Williston Basin—an undercharacterized regional aquifer system overlying deeper hydrocarbon reservoirs. Groundwater TDS in the Dakota Group ranges from approximately 4800 to 26,900 mg/L. TDS patterns are stratified with higher TDS in the lower and upper Dakota Group, and relatively lower TDS in the middle Dakota Group. The lower TDS in the middle zone may represent a preferential regional flow path for lower-TDS meteoric recharge from the west. The alternating pattern of TDS may also be evidence of higher-TDS inflows into the Dakota Group from underlying and potentially from overlying aquifers. Porosity is lower near the center of the Williston Basin and tends to be higher to the east, which may be related to grain size distributions. The new regional TDS and porosity modeling serves as a quantitative reference for water users and provides supporting evidence for hypotheses on Dakota Group recharge.

Montana, North Dakota, South Dakota↗
USGS2026

Water table rise sustains carbon release from soils in wetland-dominated landscapes: An intact soil core study

Wetland-dominated landscapes influence carbon cycling through their potential to act as both carbon sinks and sources. Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces that change seasonally with variable surface water and groundwater levels. However, few studies have directly quantified dissolved organic matter (DOM) release and greenhouse gas (CO 2 , CH 4 ) fluxes from wetland soils along terrestrial-aquatic interfaces as they are seasonally re-saturated by groundwater. To estimate groundwater-mediated soil DOM and gas fluxes, we performed laboratory simulations of vertical groundwater rise on intact soil cores collected from four Delmarva bay wetlands located in the Mid-Atlantic United States. At each wetland, one core was collected from within the wetland basin and the other from the transitional zone at the basin edge. Cores were re-saturated with groundwater over 15 days and then kept fully saturated for an additional 25 days. Source groundwater, soil porewater, and exfiltrated surface water samples were collected and analyzed for pH, ORP, DOM concentration, and DOM optical indices. In both the wetland and transition zone cores, porewater DOM concentrations increased over the wet up and were sustained during prolonged saturation. Optical indices shifted from recently produced, microbial-like signatures towards aromatic, terrestrial-like signatures. Fluxes of CO 2 decreased as the duration of soil saturation increased and soil cores switched from CH 4 sinks to sources upon full soil core saturation. Results indicate that groundwater rise sustains carbon mobilization from soils in wetland-dominated landscapes, emphasizing the need to understand how climate-driven changes to groundwater dynamics may affect carbon fluxes along terrestrial-aquatic interfaces.

Delaware, Maryland↗