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USGS2025

Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)

Residual oil zones (ROZs) can offer significant oil resources via enhanced oil recovery (EOR) as well as subsurface carbon dioxide (CO 2 ) retention during injection. If injected CO 2 is anthropogenic, the ROZs can offer a substantial geologic storage potential. The ROZs below the oil/water contact (OWC) of main pay zones (MPZ) in conventional reservoirs or brownfields, are more commonly developed for CO 2 injection and oil production and reported in the literature. However, CO 2 -EOR in greenfield ROZs, reservoirs without a MPZ present, have rarely been developed for CO 2 -EOR operation. The Tall Cotton Field of West Texas, Permian Basin, which started production in 2015 (Phase 1) and expanded in 2017 (Phase 2) from the San Andres Limestone, is one of the first examples of greenfield ROZs developed for EOR by injecting CO 2 . This paper analyses EOR and CO 2 retention performance of Tall Cotton Field using allocated injection and production data from inverted 5-spot well patterns of Phase-1 and -2 developments. Production and injection data allocated to each of the 28 identified patterns (nine 20-acre patterns for Phase-1, three 20-acre and sixteen 10-acre patterns for Phase-2) were analyzed for historical and forecasted oil recovery using ratio-trend decline analysis, and for CO 2 retention performance of the patterns. The allocated data were further used to calculate injected reservoir pore volume and void replacement ratios (VRR) for the analysis period. Quantitative results indicated that oil recovery factors of the 5-spot patterns varied between 4–10 %, and 5–30 % between the end of injection and the forecast periods, respectively. Storage of CO 2 , on the other hand, increased to a mean value of ∼7130 MMscf per pattern in Phase-1 and to a mean storage of 3700 MMscf per pattern in Phase-2 until the end of injection, followed by a decline after the end of injection and into the forecast period. Resulting CO 2 utilization factors ∼6–50 Mscf/bbl were estimated at the end of injection. Overall, presented results suggested that developing greenfield ROZs for CO 2 -EOR can be as promising as brownfield ROZs and mature MPZs for EOR and underground storage of injected CO 2 . For Tall Cotton Field, results suggest that Phase-2 patterns generally outperformed Phase-1 for oil recovery factors, while Phase-1 performed better in CO 2 retention performance metrics. This is the first study in the literature that reports a detailed CO 2 -EOR performance analysis of a greenfield ROZ in the Permian Basin, which can potentially allow for comparison with MPZs and brownfield ROZs.

Texas↗
USGS2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

Comptes Rendus. Géoscience↗
USGS2026

Keeping pace: Migrating sea lampreys adjust swim speed in response to shifting water velocity to maintain a constant ground speed

Upstream migrating fish must balance energetic costs with environmental and ecological constraints. Theoretical models predict that fish can conserve energy by adjusting swim speed in response to changing water velocity, but detailed field tests of these predictions remain rare. We used fine-scale acoustic telemetry and hydrodynamic modeling to track adult sea lamprey (Petromyzon marinus) migrating through a river and evaluated how movement speeds varied with environmental conditions and individual traits. Swim speed increased with faster water velocities, while ground speed remained constant, supporting the hypothesis that lampreys regulate swim effort to maintain a fixed migration pace. The average ground speed aligned with a predicted optimum of ∼1 body length per second. Both swim and ground speeds declined slightly in deeper water, suggesting a trade-off between movement efficiency and predator avoidance. These findings provide field-based support for a theoretical model of energy optimization and underscore how migratory fish adaptively adjust behavior to local hydrodynamic conditions. Our results highlight the value of using high-resolution tracking and environmental modeling to reveal behavioral tactics that underlie efficient migration strategies.

Michigan↗
USGS2026

Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution

Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2026

Restoring dryland water cycles for precipitation feedback and climate stability; a review

Drylands across the globe are experiencing intensifying water scarcity, land degradation, and hydroclimatic extremes. This review integrates evidence from multidecadal field studies, hydrologic monitoring, geomorphic and ecological assessments, remote sensing, and land–atmosphere science to evaluate how restoration influences key components of the terrestrial water cycle. Low-tech natural infrastructure in dryland streams (NIDS)—including check dams, leaky weirs, one-rock dams, and gabions—has emerged as a promising but under-synthesized nature-based solution for restoring hydrologic function in these environments. We describe the mechanisms through which these interventions modify runoff detention, infiltration, sediment and alluvial storage, shallow-groundwater recharge, vegetation recovery, and surface-energy partitioning, and we summarize outcomes across diverse dryland settings. Findings consistently show increased water residence time, enhanced soil-moisture storage, expanded riparian vegetation, extended flow duration, and shifts toward greater latent-heat flux—producing localized cooling and strengthened ecohydrological feedbacks. Building on these localized effects, we articulate a hypothesis that links the spatial extent of restoration, the density of NIDS per unit drainage area, and the magnitude of the latent-to-sensible-heat contrast generated by wetter post-rainfall conditions. Specifically, we hypothesize that when NIDS are implemented at densities permitted by topography and across areas large enough to maintain elevated soil moisture after storm events, the resulting increases in latent heat flux, surface cooling, and boundary-layer moistening may enhance moisture convergence and boundary-layer development, potentially increasing the likelihood or stability of convective precipitation, analogous to how reductions in these processes have contributed to regional drought intensification. These land–atmosphere feedbacks remain untested at scale but represent an important research Frontier. By integrating hydrologic, geomorphic, ecological, and atmospheric perspectives, this review provides a comprehensive framework for considering how low-tech, landscape-scale interventions can strengthen watershed resilience and contribute to climate-relevant nature-based solutions.

Arizona↗
USGS2025

Emerging investigator series: Post-wildfire sediment geochemical characterization reveals manganese reactivity and a potential link to water quality impairment in the Gallinas Creek watershed, New Mexico

Water quality post-wildfire is often impaired by increased turbidity and elevated concentrations of elements such as manganese (Mn) and iron (Fe). Precipitation events exacerbate these issues, due in part to increased erosion and transport of sediment from hillslopes to surface water. Both Mn and Fe are major redox-active elements in sediments that drive a variety of biogeochemical cycles, precipitate adsorptive phases, and can themselves be drinking water contaminants. By investigating Mn and Fe sediment geochemistry in post-wildfire sediment deposits, related water quality hazards can be assessed. To establish and strengthen this connection, we analyzed the geochemistry of sediment deposits and surface water in the Gallinas Creek watershed, New Mexico over 1.5 years post-wildfire. Analyses included particle size analysis, water extractions, sequential extractions and aqua regia extractions to determine metal partitioning in sediment deposits. Data demonstrate Mn concentrations were distributed across labile and reactive fractions, such as the exchangeable and oxyhydroxide fractions, while Fe concentrations were mainly associated with the residual fraction. Manganese concentrations in aqua regia extractions and several fractions of sequential extractions were also strongly and significantly correlated with fine-grained sediment while the same pools of Fe concentrations were not. Dissolved Mn concentrations in surface water were elevated (>50 μg L −1 ) multiple times over the 1.5 years post-wildfire, highlighting a relationship between sediment geochemistry and water quality. This work shows Mn in sediments mobilized post-wildfire has an influence on water quality and highlights how further investigation into Mn sediment redox processes and mineralogy post-wildfire can inform risk assessments and resource management.

New Mexico↗
USGS2025

Wet meadow regeneration through restoration of biophysical feedbacks

Wet meadows are globally significant ecosystems that provide critical hydrological, ecological, and biogeochemical functions, yet their extent has declined dramatically due to land use changes and hydrologic alteration. These sedge-dominated wetlands exist at the drier end of the wetland gradient, maintained by shallow groundwater and periodic inundation. This paper is a global synthesis of the ecological, geomorphic, and hydrological dynamics of wet meadows, with an emphasis on alluvial systems, to inform effective restoration strategies. We compare wet meadows to other wetlands, classify them into palustrine, lacustrine, and alluvial types, then focus on alluvial wet meadows and discuss how their formation and persistence depend on ground and surface water interactions, sediment deposition and flow obstructions, all mediated by biological processes. In particular, we highlight the role of hydric graminoids in resisting erosion and maintaining soil cohesion, how beaver promote meadow persistence, and the significance of wet meadows as carbon sinks. We also present stratigraphic evidence demonstrating that incision, often triggered by anthropogenic activity or changing climate, is the primary mechanism of alluvial wet meadow degradation, resulting in water table decline and shifts in vegetation composition. Restoration requires reversing these incisional processes through techniques that elevate water tables, disperse flow and retain sediment—methods traditionally associated with either soil conservation or stream restoration. These include nature-based solutions that create obstructions such as beaver dams and their analogues, rock and wood-based obstructions and incision trench or gully filling and grading. Given their multifunctional value—including but not limited to flood attenuation, biodiversity support, and carbon sequestration—wet meadows warrant a focused restoration framework. This review advocates for a valley-floor scale restoration paradigm that integrates hydrological reconnection, sediment retention, and biological reinforcement to ensure long-term resilience of these systems in the face of changing climate and land use pressures.

Frontiers in Environmental Science↗
USGS2025

Potential for continental scientific drilling to inform fault mechanics and earthquake science

Our understanding of fault mechanics and earthquake processes remains limited, largely due to minimal direct observations near active faults at seismogenic depths. This lack of data restricts our ability to accurately assess and mitigate both natural and human-induced seismic hazards. However, recent advancements in drilling capabilities and downhole sensing technologies offer an opportunity: the ability to observe the physical conditions within a volume near active fault zones. In this contribution, we highlight how scientific drilling can provide access to the near-fault environment, enabling measurements of the stress, temperature, fluid pressure, and rock properties at depths where ruptures initiate, propagate, and arrest. These observations are essential to refine models of earthquake nucleation and dynamic rupture, bridging gaps between laboratory experiments, numerical simulations, and surface observations. These insights can advance fundamental understanding in earthquake science but also support the development of more effective seismic hazard assessments and risk mitigation strategies.

Seismica↗
USGS2025

Scoping decision-maker needs and science availability to support regional natural capital accounting in the U.S. Colorado River Basin

Natural capital accounting has the potential to yield important policy insights at multiple scales, but there remains a disconnect between regional-scale natural capital accounts and their use for informing policy. In this paper, we propose a roadmap that could lead to the creation of policy-relevant regional accounts, with steps split across an initial scoping phase and a subsequent development phase. We demonstrate the scoping steps in action with an application to the Colorado River Basin (“Basin”), a large watershed in the southwestern United States (U.S.) that has faced aridification and substantial high-profile tradeoffs around the use of its water and other natural resources. Drawing on prior U.S. Geological Survey science co-production efforts, we conducted a series of eight discussion sessions with 41 scientists and science representatives whose work is relevant to Basin water, riparian and riverine ecosystems, upland ecosystems and energy and minerals. We summarise participants' thoughts on key topics and economic linkages, their insights and questions of interest and their recommendations on existing scientific data sources and gaps. We evaluate the suitability of the available data for construction of System of Environmental-Economic Accounting (SEEA) Central Framework and SEEA Ecosystem Accounting accounts, including those for land, water, forests, energy and minerals and ecosystems (covering extent, condition and ecosystem services). We present a series of lessons learned during the scoping phase, as well as lessons that could be relevant for future practitioners engaging in the development phase. The information can help guide the development of timely and relevant regional-scale environmental-economic accounts in the U.S. and beyond.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2025

System characterization report on the Environmental Mapping and Analysis Program (EnMAP)

This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.

Open-File Report↗
USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗
USGS2025

Tapwater exposures, residential risk, and mitigation in a PFAS-impacted-groundwater community

Tapwater (TW) safety and sustainability are priorities in the United States. Per/polyfluoroalkyl substance(s) (PFAS) contamination is a growing public-health concern due to prolific use, widespread TW exposures, and mounting human-health concerns. Historically-rural, actively-urbanizing communities that rely on surficial-aquifer private wells incur elevated risks of unrecognized TW exposures, including PFAS, due to limited private-well monitoring and contaminant-source proliferation in urbanizing landscapes. Here, a broad-analytical-scope TW-assessment was conducted in a hydrologically-vulnerable, Mississippi River alluvial-island community, where PFAS contamination of the shallow-alluvial drinking-water aquifer has been documented, but more comprehensive contaminant characterization to inform decision-making is currently lacking. In 2021, we analyzed 510 organics, 34 inorganics, and 3 microbial groups in 11 residential and community locations to assess (1) TW risks beyond recognized PFAS issues, (2) day-to-day and year-to-year risk variability, and (3) suitability of the underlying sandstone aquifer as an alternative source to mitigate TW-PFAS exposures. Seventy-six organics and 25 inorganics were detected. Potential human-health risks of detected TW exposures were explored based on cumulative benchmark-based toxicity quotients ( ∑ TQ ). Elevated risks ( ∑ TQ ≥ 1) from organic and inorganic contaminants were observed in all alluvial-aquifer-sourced synoptic samples but not in sandstone-aquifer-sourced samples. Repeated sampling at 3 sites over 52–55 h indicated limited variability in risk over the short-term. Comparable PFAS-specific ∑ TQ for spatial-synoptic, short-term (3 days) temporal, and long-term (3 years quarterly) temporal samples indicated that synoptic results provided useful insight into the risks of TW-PFAS exposures at French Island over the long-term. No PFAS detections in sandstone-aquifer-sourced samples over a 3 year period indicated no PFAS-associated risk and supported the sandstone aquifer as an alternative drinking-water source to mitigate community TW-PFAS exposures. This study illustrated the importance of expanded contaminant monitoring of private-well TW, beyond known concerns (in this case, PFAS), to reduce the risks of a range of unrecognized contaminant exposures.

Wisconsin↗
USGS2026

Integrating habitat suitability and climate constraints to predict nonnative fish invasion risk for U.S. streams and inland lakes

Introduction: Nonnative fishes in streams and inland lakes can substantially alter aquatic ecosystems by degrading habitat conditions, competing with native species, and restructuring food webs. Identifying invasion hotspots can inform proactive management and prevention of nonnative species establishment. Methods: In this study, we identified streams and lakes across the conterminous United States that are vulnerable to invasion by 18 nonnative stream and 28 nonnative lake fish species. Habitat suitability models were developed separately for stream and lake species across nine ecoregions using natural and anthropogenic predictors, and species occurrences were predicted by integrating model results with climate match scores based on comparisons between environmental conditions in species’ native and potential nonnative ranges. We classified areas with both high habitat suitability and strong climate similarity as having high invasion potential and generated hotspot maps by stacking species-level predictions. Results: Florida exhibits the highest invasion risk for both habitat types. Stream hotspots were concentrated near major metropolitan areas, whereas lake hotspots were more widely distributed across the Great Lakes basin and the northeastern U.S. Twelve species were predicted to invade both habitat types, with goldfish ( Carassius auratus ) and pirapitinga ( Piaractus brachypomus ) showing particularly high invasion potential. Discussion: These findings provide a comprehensive assessment of nonnative freshwater fish invasion risk and support targeted monitoring and management strategies.

conterminous United States↗
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2024

Prioritizing US Geological Survey science on salinization and salinity in candidate and selected priority river basins

The US Geological Survey (USGS) is selecting and prioritizing basins, known as Integrated Water Science basins, for monitoring and intensive study. Previous efforts to aid in this selection process include a scientifically defensible and quantitative assessment of basins facing human-caused water resource challenges (Van Metre et al. in Environmental Monitoring and Assessment , 192(7), 458 2020). In the present work, we explore this ranking process based on water quality considerations, specifically salinity and salinization. We selected top candidate basins to study salinity and salinization issues in 18 hydrologic regions that include 163 candidate basins. Our prioritization is based on quantitative assessment of sources of salinity, drivers of change, and receptors that must respond to those sources and drivers. Source terms represented in the prioritization include geology, depth to brackish groundwater, stream conductivity, chloride in precipitation, urban and agricultural land use, application of road salt as a deicer, and irrigation. Drivers represented in prioritization include changes in chemical weathering as a result of changes in rainwater chemistry. Receptors include measures of water stress, measurements of stream ecological health, and socioeconomic factors. In addition, we present research activities for the USGS on salinity and salinization that can be pursued in these basins including assessment of sources, pathways, and loadings; predicting and understanding changes in sources, peaks, and trends; understanding the components of salinity and mobilization of contaminants; understanding the relationship between salinization and changing ecosystems; and developing knowledge on the causes and distribution of groundwater salinity, brackish water resources, and challenges related to desalination.

Enviornmental Monitoring and Assessment↗
USGS2025

Insights and strategic opportunities from the USGS 2024 Per- and Polyfluoroalkyl Substances (PFAS) Interagency Workshop

Introduction In 2021, the U.S. Geological Survey (USGS) published Circular 1490 titled, “Integrated Science for the Study of Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) in the Environment: A Strategic Science Vision for the U.S. Geological Survey” (Tokranov and others, 2021). Circular 1490 was created to be a resource for USGS scientists prioritizing and planning research related to per- and polyfluoroalkyl substances (PFAS) and to be a guide for developing partnerships with other scientists, State and Federal agencies, and stakeholders engaged in PFAS research and management and mitigation of the environmental and human-health effects of PFAS. This USGS PFAS Strategic Science Vision document was intended to be the foundation for a “living strategic vision,” periodically providing updates on the state of USGS PFAS research, emerging PFAS data gaps and needs, and progress on interagency and stakeholder PFAS partnerships and priorities. To meet this objective, the USGS planned to host an Interagency and Stakeholder PFAS Workshop every 2–3 years. During September 10–12, 2024, the USGS hosted the first Interagency and Stakeholder PFAS Workshop in Reston, Virginia. The Workshop brought together experts from other Federal agencies (U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, Food and Drug Administration, Department of Defense [Air Force, Army]), State agencies (Washington Fish and Wildlife, Virginia Department of Transportation), and academia (Harvard University, University of Maryland) to address key challenges relating to the measurement and modeling of PFAS and the implications for environmental health. Participants engaged in in-depth discussions centered around six pivotal topics related to PFAS: (1) sampling protocols, methods and interpretation; (2) environmental sources, source apportionment, and occurrence; (3) environmental fate and transport; (4) human and wildlife exposure routes and risk; (5) bioconcentration, bioaccumulation, and biomagnification; and (6) ecotoxicology and effects. Each topic had three breakout sessions. A recurrent theme of workshop discussions was how data on a nationwide scale for PFAS occurrence in various environmental matrices, including air, water, food crops, biota, soil, and streambed sediment could help to advance scientific understanding. Participants noted significant geospatial data gaps, particularly in the midwestern and southern United States and the Pacific Northwest. PFAS data collection tends to be more robust along the eastern seaboard and in California. Participants stressed how enhancing the integration of large and small datasets across various agencies could help to support national scale understanding of PFAS. To address these gaps, attendees suggested leveraging datasets from Federal entities like the USGS and the U.S. Department of Defense, State agencies, and municipal utility services to develop predictive contaminant detection and transport models. Improved coordination between water quality programs and USGS research could help to facilitate access to valuable data, leading to comprehensive databases that inform PFAS point (wastewater treatment plants and landfills) and nonpoint (runoff from land, atmospheric deposition, food packaging) sources, environmental transport mechanisms, environmental detection and concentrations, potential exposure routes, and health effects on different biota, including humans. A specific request was made to develop a map demarking the depth of modern (1953 or later) groundwater, which is susceptible to surface-derived anthropogenic (that is, human-made) contamination, based on tritium-age dating. Emphasis was placed on incorporation of hydrology, groundwater flow paths, groundwater–surface water interactions, and landscape factors in predictive statistical models as a step to improve contaminant source identification and tracking. Molecular fingerprinting approaches garnered attention as techniques to link specific PFAS mixtures detected in a sample to environmental sources and levels in biota (Dávila-Santiago and others, 2022). Integrating data from abiotic (that is, water, soil, and air) and biotic (that is, living organisms) systems identified as a research opportunity. For example, understanding the composition of soils and sediments, which include a mixture of mineral, plant, and animal components, could advance understanding of exposure pathways. The discussions highlighted opportunities to explore and understand the potential redistribution and biotic exposures of PFAS from biosolid and wastewater treatment plant effluent land application practices, in addition to atmospheric releases and discharges from landfill and wastewater treatment plants. Participants identified research gaps surrounding how these sources may contribute to contamination and may affect surrounding ecosystems, including a better definition of anthropogenic background concentrations. Moving forward, the collection of co-occurrence data was noted as a means to improve understanding of complex mixtures and to leverage companion modeling efforts focused on areas with high and low contamination levels to identify areas of concern and unaffected resources. Participants emphasized how centralized USGS databases and the establishment of sample-metadata archives can help to ensure that samples are preserved and accessible for future research. In conclusion, the workshop participants identified opportunities to bridge data gaps and improve measurement techniques, modeling frameworks, databases, and communication, to enhance the understanding of PFAS and their effects on environmental and human health. Upon completion of the workshop, participants indicated an interest in developing strategic data collection, modeling, and analytical approaches to address these challenges.

Open-File Report↗
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

Triple-oxygen isotopic evidence of prolonged direct bioleaching of pyrite with O2

Sulfate is often touted as containing atmospheric oxygen whose isotopic signature can constrain redox, environmental conditions, and biological activity. Yet, the amount and isotopic fractionation associated with air-O 2 incorporation during sulfate formation is still debated, making its verification difficult. In this study, we identify a distinct, microbially dominated environment with the potential to preserve maximum signals of air-O 2 in sulfate. We report triple-oxygen isotope data for sulfate produced from pyrite oxidation in microbial and abiotic experiments, and from natural dissolved sulfate from the Rio Tinto, Spain, an acid mine drainage site. The oxygen isotope systematics of sulfate in these environments define a unique kinetic isotope effect associated with initial stage pyrite oxidation by Acidithiobacillus ferrooxidans that preserves >80 % oxygen from air-O 2 in sulfate. Unlike experiments, which evolve toward water-oxygen dominated sulfate on short time scales, Rio Tinto, Spain hosts a microbe rich environment with distinct geochemistry that maintains high O 2 -oxygen in sulfate. Therefore, in addition to containing isotopic records from water and air, sulfates can also contain a biosignature that is promising for understanding conditions on Mars and early Earth.

Earth and Planetary Science Letters↗