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USGS2024

Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning

Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies, and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. High concentrations of lithium in brines have been observed in the Smackover Formation in southern Arkansas (>400 milligrams per liter). We used published and newly collected brine lithium concentration data to train a random forest machine-learning model using geologic, geochemical, and temperature explanatory variables and create a map of predicted lithium concentrations in Smackover Formation brines across southern Arkansas. Using these predicted lithium maps with reservoir parameters and geologic information, we calculated that there are 5.1 to 19 million tons of lithium in Smackover Formation brines in southern Arkansas, which represents 35 to 136% of the current US lithium resource estimate. Based on these calculations, in 2022, 5000 tons of dissolved lithium were brought to the surface within brines as waste streams of the oil, gas, and bromine industries.

Arkansas↗
USGS2024

From exploration to production: Understanding the development dynamics of lithium mining projects

Recently, there has been considerable recent controversy whether current and new lithium mines will be able to supply the rapidly growing needs of the electromobility transition. Mineral exploration projects are typically active for many years, and only some become operational mines. From exploration to production, the projects go through several stages of characterisation and evaluation. At each stage, decisions are made by companies and stakeholders to advance, continue or stop the project. This is a complex process, and even projects with very similar geological and technical characteristics may take very different trajectories, depending on external factors such as global market conditions and local regulatory environments. The present study investigates the dynamics of this process for lithium exploration projects. A global database of 397 lithium projects was compiled, covering their progression through major development stages between 2004 and 2022. Ordinal logistic regression was used for the statistical analysis of this data. Different explanatory variables were tested, including economic, geological, technical, and geographic factors, to identify the best predictors for project progress at each development stage. The results suggest an essential role for lithium carbonate prices, and a variable role for other factors at each stage. Critically, the already elapsed lead time and project economics, which are traditionally considered important for the prediction of the start-up of individual mines, do not appear to be relevant in all cases. The results provide important insights into the dynamics of lithium supply and may eventually allow more realistic forecasts to be made for future lithium market dynamics.

Resources Policy↗
USGS2026

A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries

The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modelling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed significant positive correlations for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.

New York↗
USGS2026

Evaluating groundwater quality influences from oil field operations and other anthropogenic activities in an urban setting, Santa Fe Springs, California

Groundwater quality is often affected by anthropogenic activities in urban settings. This study examines groundwater quality in and around the Santa Fe Springs Oil Field in Los Angeles County, California, where oil and gas production commonly intersects with high density industrial, commercial and residential land uses. Utilizing a combination of new and historical data, we evaluated potential pathways that would allow for oil field formation fluids to migrate into groundwater and whether mixing may have occurred based on the distribution of groundwater and oil field formation fluid tracers in samples. Samples were analyzed for a wide array of constituents including volatile organic compounds, light hydrocarbons, major ions, and various isotopic compositions. Despite evidence of oil field infrastructure providing potential pathways of migration via uncemented annular spaces, casing breaches and historical disposal of oil field formation water in surface ponds, the distribution and occurrence of stable isotopes of water, chloride, boron, and total dissolved solids do not indicate mixing of oil field formation water and groundwater. However, methane isotopic signatures and the presence of heavier alkanes suggest gas from oil-bearing formations have migrated from depth via oil field well infrastructure. Volatile organic compound detections were mainly from manufactured compounds unrelated to oil and gas production, with a relatively limited number of petroleum hydrocarbons also detected. Volatile organic compounds were generally found in wells tapping shallow, modern aged groundwater, indicating anthropogenic activities occurring at or near land surface as the source. Study results suggest that while oil field infrastructure provides migration pathways for oil field formation fluids to be introduced into groundwater, urban land uses not related to oil and gas production are the primary drivers of groundwater quality degradation.

California↗
USGS2025

Formation of the Mount Weld rare earth deposit, Western Australia: Geochronology constraints

Constraining the age of protracted chemical weathering in stable cratonic areas that may form thick regoliths and the potential enrichment of various elements is challenging. Economic deposits of aluminium, iron, copper, nickel, cobalt, niobium, and rare earth elements (REEs) form in this manner. Determining the age of formation can provide key information for exploration of similar deposits as well as to better constrain paleoclimatic conditions. This study describes our effort to constrain the age of formation of the Mount Weld deposit, a world-class carbonatite-derived REE laterite deposit. We utilize multiple geochronological techniques on different minerals. The oldest dates, ranging from ca. 100 to 50 Ma, were from laser ablation ICPMS, Lu-Hf dating of churchite, a heavy REE phosphate mineral formed by mineral saturation in groundwater. Growth bands on individual minerals show a younging outwards. 40 Ar/ 39 Ar geochronology of cryptomelane, a potassium-bearing manganese oxide mineral, yielded ages ranging from ca. 40 to 26 Ma. Similarly, (U–Th)/He geochronology of goethite yielded ages from ca. 45 to 19 Ma.

Mount Weld deposit↗
USGS2026

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

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

Alabama, Florida, Mississippi↗
USGS2026

Suitability of ground-motion models for seismic hazard assessment in Puerto Rico and the U.S. Virgin Islands

We perform linear mixed-effects analyses with a ground-motion dataset to evaluate how well ground-motion models (GMMs) fit active crustal, subduction interface, and subduction intraslab earthquakes in Puerto Rico and the US Virgin Islands. Most of the GMMs reproduce the spatial variation in peak ground motions with earthquake magnitude and rupture distance but predict ground motions 0.3–1.0 natural log units (35%–270%) greater than observations. Two GMMs developed for Puerto Rico that are based on ground-motion records from mostly magnitude 4–5 earthquakes do not perform as well. We attribute the period-dependent overprediction in observed ground motions to differences between the observed site response and the linear site response in the GMMs. Consequently, we developed region-specific GMMs by adjusting the period-dependent linear site response coefficients and period-dependent constant coefficients to remove most of the bias between predicted ground motions and observations. For the analysis, we compile ground-motion records and process waveforms to build a dataset with 10,127 records at 72 stations from 849 magnitude 4.0–6.4 earthquakes between 1 January 2006 and 31 March 2024. The earthquakes include active crustal, subduction interface, and subduction intraslab events. We evaluate the GMMs using the time-averaged shear wave speed in the top 30 m ( ), which we compile from site surveys and proxy values computed from horizontal to vertical spectral ratios. Site terms exhibit strong consistency across GMMs and crustal and subduction earthquakes, indicating that the linear mixed-effects analysis successfully isolates the effects of local site response. The event terms show little spatial correlation and more substantial variability than in other regions, which we attribute to uncertainties in the earthquake magnitudes. This analysis guides the selection of the GMMs for the 2025 update of the National Seismic Hazard Model for Puerto Rico and the US Virgin Islands.

Puerto Rico, U.S. Virgin Islands↗
USGS2025

Using public participatory geographic information systems (PPGIS) to explore uses and values for Mojave Trails National Monument, California

Many people ascribe a variety of values to public lands and waters, but some values are more difficult to assess and quantify than others. Public participatory geographic information systems (PPGIS) are tools that have been used to help quantify and map the public’s diverse values for a landscape. This work describes the first known Office of Management and Budget–approved use of PPGIS by a Department of the Interior bureau. The U.S. Geological Survey developed an internet-based application to aid in gathering PPGIS data, called Values Mapping for Planning in Regional Ecosystems (VaMPIRE). Further, this work describes the first pilot of the VaMPIRE application in coordination with the Bureau of Land Management to collect spatial data and other survey data regarding the public’s uses of and values for locations within Mojave Trails National Monument. We emailed the link to the VaMPIRE application to an interested party email list in 2024 with 207 valid emails and received 74 responses; we also received 47 responses from members of an off-roading social media group. Of the list of 16 value options, recreation was the most popular value for the monument, followed by wilderness and inspirational. Over 1,000 points were placed throughout the monument, indicating locations people use or value, with the locations spread throughout the entire monument. Additionally, most survey respondents stated their ability to receive benefits in locations they mapped would not change in response to a hypothetical scenario related to recreational facility development. This report describes exploratory results from the first use of the VaMPIRE tool in Mojave Trails National Monument and includes reflections on how the process went and considerations for future use of VaMPIRE.

California↗
USGS2026

Estimating the importance of floating surface material to the total phosphorus transport in Silver Creek, Wisconsin using Particle Image Velocimetry

Various techniques are used to estimate nutrient delivery in streams that combine flow and water-quality data. However, the transport of surface floating material is difficult to measure, and is therefore typically neglected when stream sampling and in the estimated nutrient delivery. Here, we describe an approach to estimate the amount of material (duckweed ( Lemna genus), filamentous algae, and other macrophyte fragments) and associated nutrients (in this case, phosphorus, P) transported on the surface of Silver Creek, Wisconsin, to determine if this material is an important transport mechanism and if historical P loads were underestimated. This approach includes estimating the transport of surface material using 10 s videos collected every 15 min from a downward-looking camera installed beneath a bridge. The average velocity of the surface material was first determined using Large-Scale Particle Image Velocimetry (LSPIV), which uses short videos to analyze surface particle movement. The amount of surface material in each video was then computed using computer-vision techniques. The P load associated with the transported surface material was then estimated by combining surface velocities, coverage of floating material, and laboratory-measured P content. Surface material transported ~9–11% of the total summer P load and ~4–7% of the annual load in Silver Creek.

Wisconsin↗
USGS2025

A review of abrupt permafrost thaw: Definitions, usage, and a proposed conceptual framework

Purpose of Review We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. Recent Findings We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Summary Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Current Climate Change Reports↗
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

Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh

Environmental gradients can affect organic matter decay within and across wetlands and contribute to spatial heterogeneity in soil carbon stocks. We tested the sensitivity of decay rates to tidal flooding and soil depth in a minerogenic salt marsh using the Tea Bag Index (TBI). Tea bags were buried at 10 and 50 cm depths across an elevation gradient in a subtropical Spartina alterniflora marsh in Georgia (USA). Plant and animal communities and soil properties were characterized once, while replicate tea bags and porewaters were collected several times over 1 year. TBI decay rates were faster than prior litterbag studies in the same marsh, largely due to rapid green tea loss. Rooibos tea decay rates were more comparable to natural marsh litter, potentially suggesting that is more useful as a standardized organic matter proxy than green tea. Decay was slowest at higher marsh elevations and not consistently related to other biotic (e.g., plants, crab burrows) or abiotic factors (e.g., porewater chemistry), indicating that local hydrology strongly affected organic matter loss rates. TBI rates were 32 %–118 % faster in the 10 cm horizon than at 50 cm. Rates were fastest in the first 3 months and slowed 54 %–60 % at both depths between 3 and 6 months. Rates slowed further between 6 and 12 months, but this was more muted at 10 cm (17 %) compared to 50 cm (50 %). Slower rates at depth and with time were unlikely due to the TBI stabilization factor, which was similar across depths and decreased from 6 to 12 months. Slower decay at 50 cm demonstrates that rates were constrained by environmental conditions in the deeper horizon rather than the composition of this highly standardized litter. Overall, these patterns suggest that hydrological setting, which affects oxidant introduction and reactant removal and is often overlooked in marsh decomposition studies, may be a particularly important control on organic matter loss in the short term (3–12 months).

Georgia↗
USGS2026

Opportunities for the U.S. Geological Survey’s National Seismic Hazard Model to improve seismic risk assessment of critical infrastructure.

As fragility and risk modeling techniques and computational capabilities evolve, complemented by moving toward more routine and systematic seismic risk assessment of all buildings and critical infrastructure, the authors pose a few critical questions to investigate how the U.S. Geological Survey (USGS) National Seismic Hazard Models (NSHMs) can be used and enhanced further to serve such issues. In this paper, we use three examples from multiple sectors to (1) identify the role of USGS NSHMs in evaluating seismic risks to critical infrastructure, (2) quantify potential impacts from NSHM enhancements (i.e., [i] hazard curves for the vertical component of ground motion, [ii] stochastic event sets, and [iii] maps of probabilistic ground failure hazards), and (3) clarify the feasibility of relevant NSHM improvements. We illuminate that NSHMs are commonly used in location-specific performance assessments, whereas earthquake effects on critical infrastructure can be widespread across large geospatial regions. Further, we found that without the NSHM extensions considered here, risk can be severely underestimated, e.g., neglecting ground failure hazards can underestimate regional loss by a factor of two or more. Although many challenges remain, we developed example prototypes to clarify the feasibility of the NSHM extensions, which can facilitate improved management of risks to critical infrastructure.

Earthquake Spectra Journal↗
USGS2024

Global geologic map of Europa

Discovered by Galileo Galilei more than 400 years ago and imaged in detail by the Voyager 2 Galileo spacecraft, Jupiter’s icy moon Europa has been a source of intrigue. A range of science investigations indicate that it contains the key ingredients for habitability, notably energy, chemistry, and liquid water. Europa’s surface is geologically complex and, based on the dearth of impact craters, interpreted to be as young as ~60 Ma. The array of geologic features that characterize the surface include extensive ridged plains, regions of broad disruption termed chaotic terrain, long, quasi-linear ridges that span thousands of kilometers, and bands as much as 60 kilometers wide and that extend 100s of kilometers. These features, along with other geophysical measurements, indicate the presence of a global briny liquid water ocean beneath the ice shell. It was not until the arrival of the Galileo spacecraft in 1995 that the true nature and level of complexity of the surface was revealed. Although image data returned by Galileo provided insight into the structure of a variety of regions, the entire satellite has yet to be observed at a regional scale (less than 250 meters per pixel) and the detailed geologic nature of much of its surface remains a mystery. Establishing the global context of the distribution and timing of Europan geologic units forms a basis to understand regional and local scale processes, serves as a tool for the planning of future missions, and most of all is essential to gaining insight into the potential habitability of this icy world.

Scientific Investigations Map↗
USGS2024

Hydrologic investigations and a preliminary conceptual model of the groundwater system at North Penn Area 1 Superfund Site, Souderton, Montgomery County, Pennsylvania

The U.S. Geological Survey (USGS) conducted hydrogeologic investigations, reviewed existing data, and developed a preliminary conceptual model of the groundwater system as part of technical support of the U.S. Environmental Protection Agency (EPA) at the North Penn Area 1 Superfund Site (hereafter, the NP1 Site) located within the Borough of Souderton in Montgomery County, Pennsylvania. Field work and monitoring took place during 2012–18. The area is underlain by sedimentary formations that form a fractured-rock aquifer used for drinking water and industrial supply. The EPA placed the Site on the National Priorities List in 1989, identifying tetrachloroethylene (PCE) and trichloroethylene (TCE) as contaminants of concern. During 2012–18, the USGS conducted field activities that included drilling an 82-foot (ft)-deep monitoring well (MG 2220) in 2016, reconstructing a 208-ft-deep former industrial production well (MG 668 [Granite Knitting Mill]), and collecting borehole geophysical and video logs and water levels from those and five additional wells, which ranged in depth from about 50 to 200 ft below land surface. Continuous water levels were collected during 2014–17, and a synoptic set of water levels were measured in April 2018 in the seven wells. The borehole geophysical logs (caliper, acoustic televiewer, natural gamma, single-point resistance, vertical flow, and fluid temperature and resistivity) and borehole video logs in the seven wells were evaluated to assess potential for lithologic correlation and to identify and describe water-bearing features, which included both low- and high-angle fractures and other openings oriented along dipping bedding planes, joints, or possible faults. Borehole geophysical logs collected by USGS in 1992 in a 300-ft-deep former production well near the Site were also evaluated. Few to no distinctive features were identified on geophysical logs (natural gamma and single-point resistance) that could be used for correlation, thus limiting this approach to determining local geologic structure. Extensive fracturing in the upper 62 ft of monitoring well MG 2220 indicates that the well was likely drilled through a zone of faulting, and other evidence of faulting is present in the area near the Site. Assessment of continuous water levels showed hydraulic connections among some wells as indicated by rising or falling water levels in response to changes in pumping rates at nearby wells. A map of water levels measured in April 2018 indicates potential for groundwater flow generally toward the stream to the south and southwest of the Site, but the limited water-level data are insufficient to describe vertical groundwater gradients or lateral gradients in any detail. Review of 1999–2022 volatile organic compound (VOC) monitoring data collected by the Pennsylvania Department of Environmental Protection for five monitoring wells indicates that the highest groundwater concentrations of PCE and TCE were found in samples from extraction well MG 2201 (S-1) downgradient from, and nearest to, the previously identified Site contaminant source area, and these concentrations fluctuated through time. PCE concentrations were higher than TCE concentrations in samples from all five monitoring wells and were much higher than TCE concentrations in samples from extraction well MG 2201 (S-1). Temporally variable recharge is a possible factor affecting observed fluctuations in PCE concentrations in groundwater samples from well extraction MG 2201 (S-1), as indicated by a general inverse relation between PCE concentrations and water levels in a nearby long-term observation well. The PCE concentration of 1,830 micrograms per liter (μg/L) in a May 2018 water sample from monitoring well MG 2220 was more than four times the PCE concentration of 444 μg/L in a December 2017 sample from the nearby extraction well MG 2201 (S-1), which is open to fewer fractures. Low concentrations of VOCs were measured in surface water at two stream sites downgradient from wells with the highest groundwater VOC concentrations at the Site, indicating that discharge of contaminated groundwater to the stream is likely. Development of a conceptual model of the groundwater system was constrained by limited data. In areas with no pumping, groundwater-flow directions generally are thought to be controlled by topography and geologic structure (bedding orientation) and likely to the south and southwest of the Site, with local flow directions affected by orientations of fractures, joints, and local faults. Additional investigations that could help improve the conceptual model of the groundwater system and help delineate the extent of groundwater contamination and its transport are discussed.

Pennsylvania↗
USGS2024

Colored shaded relief bathymetry and acoustic backscatter of Ozette Lake, Washington

Offshore of the Pacific Northwest of the United States is the Cascadia Subduction Zone, a 1,000-kilometer-long tectonic boundary defined by a large fault, called a megathrust, that extends from the Mendocino Junction off northern California to the Nootka Fracture Zone off Vancouver Island, Canada (U.S. Geological Survey, 2023). The Juan de Fuca and Gorda oceanic plates to the west of this boundary subduct under the North America continental plate to the east. Several other smaller faults that cut through the North America plate crust also affect the region. Although their effects upon Ozette Lake are uncertain, geological evidence for past earthquakes, such as underwater landslides, may be found in Pacific Northwest lakes. Underwater landslides caused by past earthquakes should be well preserved in these relatively undisturbed lake environments. The floor of Ozette Lake, Washington, located along the Pacific coast of the United States, west of the Puget Sound region and about 140 kilometers east of the megathrust was mapped by the U.S. Geological Survey in July of 2019 to search for evidence of past earthquakes. Mapping was completed using a SWATHplus-M 234-kHz interferometric side scan sonar system pole-mounted on the U.S. Geological Survey research vessel San Lorenzo. The system collected full-coverage bathymetric and acoustic backscatter data that were processed to 2-meter spatial resolution (Dartnell and others, 2024). This two-map series displays the results of this mapping. A colored shaded relief bathymetry map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities, respectively, that can be analyzed for evidence of past earthquakes.

Washington↗
USGS2025

Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution

A direct-injection liquid chromatography/tandem mass spectrometry method was developed to determine 34 per- and polyfluoroalkyl substances (PFAS), including selected branched isomers, in centrifuge supernatant of matrix-modified (amended with approximately 50 percent methanol) water samples. The method has been validated in reagent water, surface water, groundwater, and wastewater effluent. Other water types (for example, drinking water, untreated wastewater, and landfill leachate) have been analyzed by the method but not systematically validated. Recovery of isotope-dilution standards, added to each sample, may be used to assess method performance in nonvalidated matrices on a sample-by-sample basis. Using this method, PFAS concentrations were determined in the range of 2–2,000 nanograms per liter in water samples. This range can be extended by diluting concentrated samples. At circumneutral pH, most compounds are present in the environment in their ionized form, and data are reported as such (for example, perfluorooctanoic acid is referred to as “perfluorooctanoate” [PFOA], perfluorooctane sulfonic acid is referred to as “perfluorooctane sulfonate” [PFOS]). Sample preparation procedures were designed without the use of filtration and with minimum sample handling steps to mitigate procedural losses of target compounds due to sorption to surfaces. Further, isotope-dilution quantification allowed for the correction of bias that may result from procedural losses, matrix-induced signal suppression or enhancement, and other factors. Validation experiments to characterize bias and variability, method detection level, and holding time were done in four distinct water matrices—reagent water, surface water, treated wastewater effluent, and groundwater—at multiple concentration levels. Mean PFAS recoveries met data quality objectives of bias and variability studies in all four validation matrices except for two compounds with low and variable recovery in the reagent water matrix only. Isotope-dilution standards, treated as surrogate compounds, were analyzed in more than 1,500 customer-submitted environmental samples with aggregate recovery of 102.5±6.5 percent (mean±standard deviation). Maximum holding times for all target compounds in the four validation matrices were 28 days for refrigerated samples and 90 days for frozen samples.

Techniques and Methods↗
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↗