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USGS2026

Groundwater quality near an oil field in a stream-dominated recharge setting, California, USA

Alluvial valley aquifers are important sources of water supply in many areas but effects of co-located oil and gas development on these resources have not been widely reported, especially in settings where recharge is dominated by stream infiltration. Interpreting the presence of geochemical indicators in the context of hydrology, geology, and other factors provides a more complete understanding of the relations between groundwater and sources of oil-field fluids and aids in identifying risks associated with oil and gas development. Groundwater and Salinas River water samples were collected in an alluvial valley near the San Ardo Oil Field in Monterey County, California and analyzed for a wide range of dissolved chemical, gas, and isotopic constituents to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with fresh groundwater used for supply. Hydraulic gradients, age-dating tracers, and other geochemical indicators show that recharge from the Salinas River has the potential to dilute oil-field fluids that might migrate or seep into the aquifer. Groundwater and Salinas River water collected downgradient of the San Ardo Oil Field showed little or no evidence of mixing with oil-field fluids. Some samples within the oil field contained trace amounts of hydrocarbons or elevated temperatures, indicating that any potential effects from oil-field activities are minor or have been diluted by recharge from the Salinas River. The two samples with the most geochemical evidence of potential mixing with oil-field fluids (SP-18 and GW-17) were collected west of or along the Los Lobos fault, where naturally occurring hydrocarbons are near the land surface. Those samples are also near active or inactive oil-field wells, and so anthropogenic activities and pathways cannot be ruled out as a cause of trace detections of hydrocarbons and elevated temperatures in the aquifer.

California↗
USGS1976

Availability of ground water in the area surrounding the Trident submarine construction facility, Kitsap County, Washington

This report provides general information on the water resources--with emphasis on ground-water occurrence and availability--in that part of Kitsap County (referred to as Trident Impact Area) that would be most affected by the development of the Trident submarine-construction facility at Bangor. Ground water occurs principally in a lower, confined aquifer near and below sea level and an upper, unconfined aquifer above sea level; both aquifers are extensive beneath the study area and are composed of sand and gravel layers separated by poorly permeable silt, clay, and till layers. Locally throughout the area efficiently constructed wells tapping each of the two aquifers are capable of yielding 100 to 1,300 or more gallons per minute. The estimated 1970 water use in the study area averaged about 13 million gal/day (gallons per day); of this amount about 9 million gal/day came from surface-water sources--from a large reservoir outside the study area--and about 4 million gal/day came from ground water pumped from the two aquifers. Anticipated water use soon will be about 18 to 21 million gal/day; virtually all the additional quantity required (about 5 to 8 million gal/day) above present use must come from ground-water sources. Preliminary evaluation of the aquifers suggests that an additional 1.5 million gal/day can be developed from the upper aquifer and 7 million gal/day from the lower aquifer. Existing wells tapping the lower aquifer might yield additional water and increase the total yield in the area by 3.5 million gal/day, and new wells drilled in selected areas could produce an additional 3.5 million gal/day from this aquifer. However, additional, large-scale ground-water withdrawal from the lower aquifer could induce saltwater intrusion into wells situated in coastal areas. Recommended future studies include additional data collection, monitoring of chloride concentrations in water from large-yield coastal wells, confirmation of well yields and capacities, and test-well drilling and analysis.

Washington↗
USGS2024

The 3D National Topography Model Call for Action—Part 1. The 3D Hydrography Program

The U.S. Geological Survey is initiating the 3D Hydrography Program (3DHP), the first systematic remapping of the Nation’s surface waters since the original 1:24,000-scale topographic mapping program was active from 1947 to 1992. Building on decades of experience maintaining the National Hydrography Dataset (NHD), the Watershed Boundary Dataset (WBD), and the NHDPlus High Resolution (NHDPlus HR), the 3DHP will completely refresh the Nation’s hydrography data and improve discovery and sharing of water-related data. The design of the 3DHP is based on the results of a study that estimated that the fully implemented program would have the potential to provide more than $1 billion in benefits to Federal, State, Tribal, Territorial, and local governments and to private and nonprofit organizations every year, in addition to myriad societal benefits. The 3DHP would directly support better decision making regarding water resources by providing more accurate, complete, and integrated information than is currently available. The 3DHP datasets will include a three-dimensional (3D) hydrography network generated from and integrated with elevation data from the 3D Elevation Program (3DEP) to better represent stream gradients and channel conditions, along with waterbodies, hydrologic units, hydrologically enhanced elevation and other surfaces, and more consistent and accurate attributes. The 3DHP datasets will inherit key attributes of the NHD, WBD, and NHDPlus HR, and they also will include new attributes and links to other data such as the U.S. Fish and Wildlife Service National Wetlands Inventory, groundwater data, and engineered hydrologic systems such as stormwater networks. The 3DHP will be designed to provide a set of open and interoperable web-based tools, maps, and data catalogs, creating a robust system for users to reference their information about water; the system elements are collectively referred to as the “infostructure.” The 3DHP and the infostructure can provide a foundational geospatial underpinning for the Internet of Water, a community-based effort to modernize tools and technologies to share water data. As proposed, the 3DHP would begin providing products and services to the public in 2024.

Circular↗
USGS2026

Determination of baseline water-quality conditions using continuous specific conductance and discrete measurements of total dissolved solids and selected major ions, Arkansas River Basin, Colorado

From 2022 through 2024, the U.S. Geological Survey (USGS) in cooperation with the Regional Resources Planning Group (Southeastern Colorado Water Conservancy District, Colorado Springs Utilities, Pueblo Water, Lower Arkansas Valley Water Conservancy District, Aurora Water, and Upper Arkansas Water Conservancy District) established a basinwide water-quality monitoring network in the Arkansas River Basin in Colorado. The study leveraged ongoing continuous measurements of streamflow and specific conductance (SC) at 13 sites along the main stem Arkansas River and Fountain Creek from the USGS 07108600 Arkansas River at Granite, Colo., (Ark Granite) site to the USGS 07137500 Arkansas River near Coolidge, Kansas, (Ark Coolidge) site. Baseline water-quality conditions were established using data from October 1989 through September 2022 to help identify changes in water quality that could result from changes in land and water use. Total dissolved solids (TDS) concentration was the main indicator of general water quality in this study because it can be accurately estimated from SC and is sensitive to changes in streamflow, water operations, and source contributions. Median TDS concentrations in Arkansas River samples (October 1989 through December 2023) ranged from 75 milligrams per liter (mg/L) at Ark Granite near the headwaters to 3,660 mg/L at Ark Coolidge near the Colorado–Kansas State line. Distinct seasonal differences in median streamflow and TDS were apparent during the winter and summer months. Seasonal Kendall tests showed no significant trends in monthly mean streamflow (October 1995 through September 2022) at Arkansas River sites upstream from Pueblo Reservoir. Upward trends in TDS concentrations and loads occurred only at Ark Granite. Downward trends in streamflow, TDS concentrations, and TDS loads occurred at Arkansas River sites from USGS 07109500 Arkansas River near Avondale, Colo., to Ark Coolidge. Downward trends in streamflow and SC (surrogate for TDS) were more prevalent during winter base flow months and may indicate changes in groundwater quantity, and possibly groundwater quality, potentially affecting the river water-quality condition.

Colorado↗
USGS2025

Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070

In 2019, the U.S. Geological Survey and Wake County Environmental Services began a collaborative study to evaluate groundwater resources and long-term groundwater availability in the county’s fractured-rock groundwater system. Wake County, in central North Carolina, is experiencing rapid population growth, associated land development, and changing water use. Hydrogeologic data including groundwater levels, aquifer testing, borehole fracture flow measurements, water-quality samples, and groundwater age-dating tracers were collected, along with findings from previous investigations, to help inform a conceptual model of the flow system used to develop a modular three-dimensional finite-difference groundwater-flow model (MODFLOW) for simulating historical and future groundwater conditions from 2000 to 2070. Hydraulic conductivity and transmissivity ranges were estimated from 17 slug tests and 21 borehole-flow measurements. Groundwater-quality analytical results from 19 sampling sites indicate that oxidation-reduction (redox) conditions varied within the regolith and bedrock and that minimal evaporation occurred before recharge entered the groundwater system. Age dating revealed mixtures of older and younger water, ranging from the 1940s to the 1990s—indicating variable flow pathways of recharge within permeable bedrock fracture zones. To simplify the complex fractured-rock groundwater system, two layers representing the regolith and the fractured bedrock were used in the MODFLOW model. Model calibration included parameter estimation and provided a reasonable fit to observed groundwater levels and estimated stream base flows. The model forecast scenarios incorporated future climate-model data for two emissions scenarios with land cover change projections to simulate potential impacts to future groundwater levels, recharge, and base flows. Recharge and base flow projections were largely within historical ranges, with no apparent long-term trends, but did indicate a slight downward shift in median values—likely, in part, because of differences in spatial resolution of input climate datasets. Seasonal patterns were consistent with historical data, with projections of possible increases in future winter recharge. Model limitations are discussed, and additional monitoring and model refinement needs are highlighted to support decision making for local groundwater management.

North Carolina↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
USGS2025

Groundwater-level elevations in the Denver Basin bedrock aquifers and Upper Black Squirrel Creek alluvial aquifer, El Paso County, Colorado, 2021–24

El Paso County is the second-most populous county in Colorado and is projected to grow another 15 percent by 2030. Within El Paso County is the Upper Black Squirrel Creek Designated Groundwater Basin (Black Squirrel Basin), an area where surface water is scarce and water users rely primarily on groundwater from five different aquifers (the Upper Black Squirrel Creek alluvial aquifer and four bedrock aquifers within the Denver Basin aquifer system: the lower Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers) to meet their needs. Currently (2024), land within the Upper Black Squirrel Creek Basin is primarily used for rural grazing and agriculture; however, municipal development is ongoing. In 2021, the U.S. Geological Survey, in cooperation with the Upper Black Squirrel Creek Ground Water Management District, began a study to establish a baseline dataset and assess the groundwater resources of the aquifers within the Black Squirrel Basin. A network of 39 wells was established in 2021; discrete groundwater-level measurements were made bimonthly. Nine of the 39 wells were equipped with pressure transducers to record hourly groundwater-level data. Seven wells had statistically significant seasonal trends, and trends at 3 wells were negative. For the discrete data, 16 wells had a significant trend for the study period, and 4 wells had negative trends. For the time-series data, 8 wells had significant trends, and 3 wells had negative trends. Potentiometric surface maps were created for this study using discrete, static groundwater levels measured in April 2023. These maps showed the estimated groundwater flow direction from the north-northwest to the south-southeast in the alluvial aquifer and from the northwest to the east-southeast for the lower Dawson and Denver aquifer wells. This study indicates the potential benefit of monitoring wells in the areas near municipal pumping. Additional monitoring could lead to a better understanding of connectivity between aquifers and be an important tool for assessing long-term sustainability of groundwater use.

Colorado↗
USGS2024

Geomorphic map of the Umatilla River corridor, Oregon

This map portrays the distribution of landforms along the Umatilla River in northeastern Oregon and covers a corridor 127 kilometers long from the confluence of the Umatilla River with the Columbia River upstream to Meacham Creek. The map encompasses the valley bottom and extends about 1 kilometer up the adjoining hillslopes. Map data are intended to support water quality and fisheries enhancement efforts pursuant to the First Foods, a resource-management approach that focuses on traditionally gathered foods including water, fish, big game, roots, and berries and calls attention to the reciprocity between people and the foods upon which humans depend. The Umatilla River drains about 6,300 square kilometers on the northwest slope of the Blue Mountains in northeast Oregon. Most of the drainage basin is underlain by Miocene basalt flows of the Columbia River Basalt Group. Younger, weakly lithified, late Miocene and early Pliocene gravel deposits of local origin (for example, McKay Formation) are mapped in a few places. Upland surfaces are mantled with windborne silt (loess) correlative with deposits elsewhere known as the Palouse Formation. Surfaces below an elevation of about 340 meters were inundated repeatedly by large Pleistocene glacial outburst floods, most emanating from glacial Lake Missoula in western Montana. In backflooded areas such as the lower Umatilla River valley, Missoula floods deposited extensive slack-water silt. Areas mapped as open water, active channel and tie channel, flood basin, valley bottom, and modified land constitute the geomorphic floodplain: the area subject to occasional inundation by the Umatilla River. Deposits and landforms within the floodplain are inset into Missoula flood deposits and hence postdate the 20–15-kilo-annum Missoula floods. Some floodplain deposits are no more than a few centuries old, as indicated by substantial erosion and deposition during the Umatilla River flood of February 2020, the largest since systematic measurements began in October 1903. Deposits and landforms of the floodplain are transient features within the longer-term incision of the Umatilla River into mid-Miocene flood basalts and younger gravel of the McKay Formation.

Oregon↗
USGS2025

Reservoir thermal energy storage pre-assessment for the United States

Storing thermal energy underground for later use in electricity production or direct-use heating/cooling is a promising, viable, and economical green energy option. Reservoir thermal energy storage (RTES) is one such option, which stores energy in underutilized permeable strata with low ambient groundwater flow rates and more geochemically evolved (e.g. brackish/saline) waters relative to overlying principal aquifer systems. The U.S. Geological Survey has begun assessing RTES potential nationally by focusing on five generalized geologic regions (Basin and Range, Coastal Plain, Illinois Basin, Michigan Basin, Pacific Northwest) across the United States. Hydrogeologic reservoir models are developed for the following eight metropolitan area cities within those regions to evaluate RTES performance across different climates and subsurface conditions: Albuquerque, New Mexico; Charleston, South Carolina; Chicago and Decatur, Illinois; Lansing, Michigan; Memphis, Tennessee; Phoenix, Arizona; and Portland, Oregon. Evaluated metrics include estimated required well spacing, thermal storage capacity, and thermal recovery efficiency through time. Also considered for each reservoir are potential complicating factors, including reservoir depth, thermally driven free convection, and groundwater salinity. This work focuses on direct-use cooling because the need for cooling modern office buildings greatly exceeds that for heating in most parts of the country (Falta and others, 2016); however, the evaluated metrics are also relevant to heating and electricity applications. Results indicate that favorable RTES conditions exist in each region, with the Coastal Plain and Basin and Range being especially favorable for thermal storage capacity, while the Pacific Northwest and Michigan Basin excel at energy recovery for the evaluated cooling application. The results underscore the utility of developing maps of thermal storage capacity, subsurface temperature models, and volumetric estimates of thermal storage capacity to serve as key RTES resource classification standards. Overall, this pre-assessment provides a basic understanding of RTES potential in several cities and geologic regions throughout the country and will aid ongoing thermal energy storage assessment efforts.

Arizona, Illinois, Michigan, New Mexico, Oregon, S↗
USGS2024

Methodology for inclusion of produced and stored carbon dioxide in the U.S. Geological Survey Federal lands greenhouse gas inventory

The U.S. Geological Survey (USGS) has developed two new carbon dioxide (CO2) emissions and sequestration accounting methods for use in future reports. The first method is a Federal lease-produced CO2 emissions calculation for an update of the report, “Federal Lands Greenhouse Gas Emissions and Sequestration in the United States.” The methodology to incorporate Federal lease CO2 production emissions into the updated report relies on CO2 sales royalty data from the Office of Natural Resources Revenue (ONRR). The end usage points for the gas include enhanced oil recovery with CO2 (CO2-EOR), food and beverage, and chemical production. CO2-EOR is the main end point for natural CO2 production in the United States; it accounted for 94% of usage in 2022 [1]. Federal lands emissions from this sector are estimated at 460 metric tons of CO2 in 2022, a very small amount relative to most other Federal lands emissions sector estimates. The second new method, planned for a separate report, is a calculation of the geologic storage of CO2 on Federal lands. The second method estimates the CO2 stored under Federal surface lands and documents Federal climate change mitigation efforts. Currently, there is no storage of CO2 at an industrial level on Federal lands, however multiple proposals and projects are planned. This method was developed on non-Federal lands datasets in an effort to prepare for when these activities on Federal lands will require accounting. National estimates for CO2 geologic storage using this method, but without a Federal lands filtering step, totaled 8.0 million metric tons (Mt) in 2022. The two methods described here are new benchmark methods in a collection of accounting procedures to document the current state of greenhouse gas emissions and their storage on Federal lands. These benchmarks can then be used to measure any subsequent changes in emissions from or carbon storage beneath Federal lands. While the magnitude of the values is currently non-existent to small, emissions mitigation goals established by decision makers indicate that these values will grow, and their documentation will take on greater value and use.

continental United States↗
USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗
USGS2024

Assessing potential effects of oil and gas development activities on groundwater quality near and overlying the Elk Hills and North Coles Levee Oil Fields, San Joaquin Valley, California

Groundwater resources are utilized near areas of intensive oil and gas development in California’s San Joaquin Valley. In this study, we examined chemical and isotopic data to assess if thermogenic gas or saline water from oil producing formations have mixed with groundwater near the Elk Hills and North Coles Levee Oil Fields in the southwestern San Joaquin Valley. Major ion concentrations and stable isotope compositions were largely consistent with natural processes, including mixing of different recharge sources and water-rock interactions. Trace methane concentrations likely resulted from microbial rather than thermogenic sources. Trace concentrations of benzene and other dissolved hydrocarbons in three wells had uncertain sources that could occur naturally or be derived from oil and gas development activities or other anthropogenic sources. In the mid-1990s, two industrial supply wells had increasing Cl and B concentrations likely explained by mixing with up to 15 percent saline oil-field water injected for disposal in nearby injection disposal wells. Shallow groundwater along the western margin of Buena Vista Lake Bed had elevated Cl, B, and SO 4 concentrations that could be explained by accumulation of salts during natural wetting and drying cycles or, alternatively, legacy surface disposal of saline oil-field water in upgradient ephemeral drainages. This study showed that groundwater had relatively little evidence of thermogenic gas or saline water from oil and gas sources in most parts of the study area. However, the evidence for groundwater mixing with injected disposal water, and possibly legacy surface disposal water, demonstrates produced water management practices as a potential risk factor for groundwater-quality degradation near oil and gas fields. Additional studies in the San Joaquin Valley and elsewhere could improve understanding of such risks by assessing the locations, volumes, and types of produced water disposal practices used during the life of oil fields.

California↗
USGS2025

The influence of pre-existing structures on geothermal springs: Inferences from potential field mapping in Surprise Valley, CA and other sites In the northwestern Great Basin

Surprise Valley, located in the northwestern Great Basin, is an asymmetric extensional basin that marks a major tectonic transition between the relatively un-extended volcanic Modoc Plateau to the west, and the Basin and Range to the east that has undergone 10-15% extension. In addition, it sits just north of the Walker Lane which accommodates up to 20% of dextral slip associated with Pacific-North American plate interactions. Thermal springs issue from eight areas within Surprise Valley. Most of these occur within the basin and are not situated on the main basin forming range-front faults. As a result, efforts to resolve the structural setting of the valley’s hydrothermal system have relied on geophysics to characterize basin structure and geology. Extensive efforts to map the basin with ground and airborne magnetics have revealed a >35 km-long linear, intra-basin magnetic high, interpreted as a buried dike swarm. Geothermal springs on the eastern side of the valley, including Seifert hot springs, Leonards hot springs, and Surprise Valley hot springs (SVHS), are all situated along the magnetic high and occur at local breaks and bends in the anomaly, suggesting that fracture permeability is enhanced along the feature and particularly at these discontinuities. Recent studies, including drilling over the anomaly near SVHS that likely intersected dike material, as well as subsequent mapping and sampling of dikes outcropping along the anomaly on the playa surface south of SVHS, confirm (as previously inferred) that mafic intrusives are the principal source of the anomaly. Similar interpretations made in two other valleys (in southern Oregon and northwestern Nevada), where inferred intra-basin dikes appear to be spatially correlated with hot springs or prospective geothermal resource areas, suggest that the impact of pre-existing basement structure on hydrothermal activity may pertain more generally to other hydrothermal settings throughout the Great Basin. If so, efforts to map basement may enhance understanding structural controls on some geothermal systems. Furthermore, similarities across these disparate sites suggest that magmatism may play a much larger role in accommodating extension and influencing basin evolution across the western Great Basin than previously recognized.

Conference Paper↗
USGS2024

Indications of preferential groundwater seepage feeding northern peatland pools

Groundwater seepage from underlying permeable glacial sedimentary structures, such as eskers, has been hypothesized to directly feed pools in northern peat bogs. These hypotheses directly contradict classical peat bog models for ombrogenous systems, wherein meteoric water is the sole water input to these systems. Variations in the underlying mineral sediment in contact with the peat imply that unrecognized hydrogeologic connectivity may exist with pools in northern peat bogs, particularly where high permeability materials are in contact with the peat. Seepage dynamics originating from these structural variations were investigated using a suite of thermal and hydrogeophysical methods deployed around pools in a peat bog of northeastern Maine, USA. Thermal characterization methods mapped anomalies that were confirmed as matrix seepage or preferential flow pathways (PFPs). Geochemical methods were employed at identified thermal anomalies to confirm upwelling of solute-rich groundwater. Conduits around pools were associated with surficial terminations of suspected peat pipes, based on the inference of pathways extending down into the peat, that focus flow through PFPs in the peat matrix. Discharge also occurred through the peat matrix adjacent to suspected pipe structures and matrix seepage rates were quantified using analysis of diurnal temperature signals recorded at multiple depths. Seepage rates, with a maximum of nearly 0.4 m/d, were measured at localized points around pools. Periods of synchronized temperatures paired with highly muted diurnal temperature signals, recorded in diurnal temperature with depth data, were interpreted qualitatively as activation of strong upward discharge rates through suspected peat pipes. These time periods correlated strongly with local precipitation events around the peatland. Ground-penetrating radar surveys revealed discontinuities in the low permeability glacio-marine clay at the mineral sediment-peat interface, interpreted to be regional glacial esker deposits, which were located beneath and around pools. Heat tracing, specific conductance contrasts, seepage rates, and trace metal concentrations all imply groundwater seepage originating from underlying permeable glacial esker deposits and directly sourcing pools. Preferential groundwater inputs into northern peat bogs may play a key role in developing and maintaining pool systems, with enhanced solute transport impacting peatland ecology, water resources, and carbon cycling.

Maine↗
USGS2025

Bathymetric contour maps, surface area and capacity tables, and bathymetric change maps for selected water-supply lakes in Missouri, 2022–23

Bathymetric data were collected at 13 water-supply lakes around the periphery of Missouri by the U.S. Geological Survey in cooperation with the Missouri Department of Natural Resources and various local agencies, as part of a multiyear effort to establish or update the surface area and capacity tables for the surveyed lakes. Surveys were carried out during the months of April and May in 2022 and 2023. All but two of the lakes had been surveyed previously by the U.S. Geological Survey, and the recent surveys were compared to the earlier surveys to document the changes in the bathymetric surface and capacity of the lake. Bathymetric data were collected using a high-resolution multibeam mapping system mounted on a boat. Supplemental depth data at three of the lakes were collected in shallow areas with an acoustic Doppler current profiler on a remote-controlled boat. Data points from the various sources were exported at a gridded data resolution appropriate to each lake, either 0.82 foot, 1.64 feet, or 3.28 feet. Data outside the multibeam survey extent and greater than the surveyed water-surface elevation were obtained from data collected using aerial light detection and ranging (lidar) point cloud data. A linear enforcement technique was used to add points to the dataset in areas of sparse data (the upper ends of coves where the water was shallow or aquatic vegetation precluded data acquisition) based on surrounding multibeam and upland data values. The various point datasets were used to produce a three-dimensional triangulated irregular network surface of the lake-bottom elevations for each lake. A surface area and capacity table was produced from the three-dimensional surface for each lake showing surface area and capacity at specified lake water-surface elevations. Various quality-assurance tests were conducted to ensure quality data were collected with the multibeam, including beam angle checks and patch tests. Additional quality-assurance tests were conducted on the gridded bathymetric data from the survey, the bathymetric surface created from the gridded data, and the contours created from the bathymetric survey.

Missouri↗
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↗
USGS2024

Geophysical modeling of a possible blind geothermal system near Battle Mountain, NV

The northeastern portion of the Reese River basin in north-central Nevada is the focus of detailed geophysical and geological studies as part of the INGENIOUS project, which aims to identify new, commercially viable hidden geothermal systems in the Great Basin region of the western U.S. This location, herein referred to as Argenta Rise, occupies a broad (~15km wide) left-step between major range-front fault systems along the northwestern edge of the Shoshone Range and Argenta Rim, with numerous ENE-striking intra-basin faults presumably accommodating sinistral-normal oblique slip across the step-over. Four discrete regions have been identified within the study area that have favorable structural settings for hosting a blind hydrothermal system. However, with no definitive or extensive surface manifestations of an active hydrothermal system (e.g., geysers, steam vents, sinter, etc.), detailed geophysical studies are necessary to resolve subsurface geology and structure, and identify zones of enhanced structural complexity that may promote hydrothermal fluid flow. Hence, we collected high-resolution gravity, MT, and rock property data (density, magnetic susceptibility), and analyzed the recently acquired GeoDAWN aeromagnetic data to characterize potential geothermal resources in this region. Using the new geophysical datasets, we jointly modeled gravity and magnetic data along a series of intersecting 2D profiles that integrated information from recent, local-scale fault mapping. Rock property measurements performed on outcrops and hand samples throughout the study area constrained the models. The MT data were used to construct a 3D resistivity model that highlights the location of inferred alteration and fluids in the subsurface. Combined MT and potential field results reveal which structures may be most important for controlling hydrothermal fluid migration, as well as which geologic units may host hydrothermal fluids. Our gravity derived depth to basement surface coincides well with the base of shallow conductive anomalies, suggesting hydrothermal fluids may be confined to basin fill sediments and volcanics. This work supports our development of 3D geophysical and geologic models that are focused along the western flank of the northern Shoshone Range and aids the process of selecting sites for temperature gradient drilling.

Nevada↗
USGS2026

Validating antler- and movement-based estimates of caribou reproduction using video camera collars

Wildlife agencies invest substantial resources in monitoring ungulate reproductive rates given ongoing concerns about population trends and their implications for management. For barren-ground caribou ( Rangifer tarandus ) in the North American Arctic, data on parturition and neonate survival have traditionally been collected using visual observations of antler retention and calf presence from small, fixed-wing aircraft. However, these surveys are weather-dependent, expensive, and dangerous, motivating the development of movement-based approaches that infer reproductive events from global positioning system (GPS) location data. We had the unique opportunity to use video camera collars to validate both antler- and movement-based methods for estimating reproduction in barren-ground caribou, using data from the Porcupine (2018–2023) and Western Arctic (2021, 2023) herds in Alaska, USA, and Yukon, Canada. For the movement-based approaches, we assessed individual-based and population-based methods, which both inferred parturition following a sharp decline in movement and inferred calf loss following a sharp increase in movement. We investigated these approaches using rarified 1-, 2-, 4-, and 8-hour fix intervals. Based on video collar observations, we found that antler retention at the onset of the calving period was highly accurate for predicting parturition (96% accuracy) but became unreliable as calving progressed, as approximately 80% of parturient females shed their antlers during the calving period. In contrast, both movement methods performed marginally for estimating caribou parturition (~70% accuracy), with estimates from the individual-based method exhibiting greater bias than those from the population-based method. The individual-based method also poorly predicted neonate survival (≤49% accuracy for detecting parturition and calf fate for the Porcupine Herd). Video data revealed that inaccuracies with the movement methods often occurred when caribou bedded during storms, rested after traversing mountainous terrain, lost a calf shortly after birth, or increased movement to evade insects. These results have important implications for management agencies using antler- and movement-based methods to estimate caribou reproduction, particularly when informing assessments of population decline or recovery. Our results demonstrate the utility of video collar data for validating reproductive monitoring approaches and provide insights into how these approaches can be improved.

Alaska, Yukon↗