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USGS2024

Revision of ModelMuse to support the use of PEST software with MODFLOW and SUTRA models

Executive Summary ModelMuse is a graphical user interface for several groundwater modeling programs. ModelMuse was updated to generate the input files for the parameter estimation software suite PEST. The software is used with MODFLOW or SUTRA models to run PEST-based parameter estimation and display the updated model inputs after parameter estimation. The PEST input files can also be used with the PEST++ version 5 software suite. Parameter estimation typically requires defining the parameters being adjusted during calibration and observations for assessing calibration quality. After a parameter is defined in ModelMuse, it can be applied to all or part of a model dataset. Pilot points—a parameterization device that facilitates higher levels of parameterization—can be used to assign spatially variable distributions of model inputs. Parameters can be applied to temporally varying features, such as boundary conditions, by either applying them to all the values in a series in one step or by applying separate parameters to individual members of a series. ModelMuse allows the definition of many observation types from various model output files. For MODFLOW 6 and SUTRA models, new options were added to ModelMuse to allow it to display the changed input after parameter estimation is complete. For MODFLOW–2005 and MODFLOW–NWT models, ModelMuse can import an entire model for visualization. An example illustrates the use of PEST with a MODFLOW 6 model in ModelMuse.

Techniques and Methods↗

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↗

USGS2024

Hypothetical CO2 leakage into, and hydrological plume management within, an underground source of drinking water at a proposed CO2 storage facility, Kemper County, Mississippi, USA

A large Geologic Carbon Sequestration (GCS) hub has been proposed in Kemper County, Mississippi. The target injection interval consists of numerous Cretaceous-aged deep saline aquifers overlain by a competent and extensive regional sealing layer. Above the seal, the deepest Underground Source of Drinking Water (USDW) at the site is the Eutaw aquifer of the Eutaw Group and McShan Formation, undifferentiated. To assess potential risks of leakage from the deep sequestration reservoir, a model of a portion of the Cretaceous Eutaw Group was constructed in this study. Simulations tested various permeabilities, hypothetical leakage rates, and plume mitigation strategies utilizing existing wells. Results suggest that, under the influence of regional groundwater flow fields, leaking CO 2 would effectively bypass the existing wells, and to influence this migration would require very large water extraction rates. Therefore, to ensure plume detection, monitoring for leakage at the injection wells themselves is very important.

Mississippi↗

USGS2025

Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm

Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across >50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance – both across all reaches and by stream type (e.g., reservoir or groundwater influence) – as a baseline for future improvement. The model showed reach-level RMSE of <2 °C with 90 % prediction intervals that contain 90.7 % of observations. We also assessed how the model captured variability in ecologically relevant metrics (e.g., R 2 for annual 7-day maximum = 0.76; R 2 for days exceeding 25 °C = 0.75). This model does not outperform state-of-the-art machine learning efforts (e.g., RMSE ≤1.5 °C) due to a limited input set but does provide the most spatially complete modeling to date to support water availability assessments.

contiguous United States↗

USGS2026

The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology↗

USGS2026

Multiple machine-learning estimation of groundwater levels and trends for the regional Mississippi River Valley alluvial aquifer

The Mississippi River Valley alluvial aquifer provides irrigation, public, and domestic water supplies across the south-central United States. Declining groundwater levels require improved characterization of changing conditions. Traditional potentiometric-surface mapping does not use all available water-level data or quantify uncertainty. To address these limitations, we developed a data-driven multiple machine-learning (MML) framework delivered through two open-source R packages. The covMRVAgen1 software assembles covariates to 155,960 monthly groundwater levels from 57,695 wells; the mmlMRVAgen1 software trains Cubist and Random Forest models, blends them, and makes 1-kilometer gridded predictions of monthly potentiometric surfaces for the period January 1980–December 2022. The MML approach provides a methodological foundation for region-scale spatiotemporal groundwater prediction and uncertainty quantification, generating 90-percent prediction limits with appropriate empirical coverage. Model performance is acceptable, with a root-mean-square error of about 4.2 feet, standard deviation of 24.82 feet, and a normalized Nash–Sutcliffe efficiency of 0.973.

Arkansas, Illinois, Louisiana, Mississippi, Missou↗

USGS2025

Climate-driven sulfate export in alpine watersheds may stimulate methylmercury production

Climate change is increasing sulfate export and changing wetland extent in mountain regions. These changes may increase microbially mediated production of the neurotoxic substance methylmercury due to enhanced sulfate metabolism in mountain environments. Here, we assess methylmercury concentrations and formation rates across high-elevation wetlands in the Colorado Rocky Mountains. We also investigate sulfate controls on methylmercury production within subalpine peatlands by amending soils with sulfate to mimic increased stream export of sulfate from the alpine zone and measuring methylmercury formation rates for different sulfate treatments. We found that subalpine peatlands have statistically significant higher methylmercury concentrations and formation rates compared to alpine, mineral-soil wetlands. Methylmercury production in subalpine peatlands also increased significantly ( p < 0.05) following sulfate additions; the highest rates occurred in sediments with intermediate extractable sulfate concentrations (∼0.60–1.4 mg sulfate g −1 dry soil). Our study is the first to identify soil sulfate-related thresholds for methylmercury production and sulfate-limitation of methylmercury production in subalpine peatlands. These findings highlight important linkages between climate-driven mineral weathering and mercury cycling in mountain regions globally.

Colorado↗

USGS2025

Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments

Correlations between grade and tonnage exist in mineral resource data compiled from published reports, but they are not always addressed during quantitative assessment of undiscovered mineral resources. Failure to account for correlated grade and tonnage distributions can result in geologically unrealistic assessment results. Current software tools simulate univariate ore tonnage and multivariate resource grades of undiscovered deposits independently. As a result, analysts are forced to rely on ad-hoc solutions to minimize the correlation issues by: 1) creating subsets of data with restricted criteria; 2) truncating grade and tonnage distributions; and 3) testing model robustness using exploratory data analysis. While these methods represent pragmatic solutions, the statistical solutions presented here provide additional options to address real correlations in grade and tonnage data used for mineral resource assessments. We present a modified version of the MapMark4 package in R that introduces two alternatives for modeling grade and tonnage distributions, consisting of a multivariate solution that accounts for correlations between ore tonnage and metal grades and an empirical solution that utilizes simple random sampling with replacement to reproduce coupled grades and tonnages from the input data. We present simulations for contained ore and metal for three case studies representing tungsten skarn, komatiite-hosted nickel, and sediment-hosted carbonate amagmatic zinc-lead (Mississippi Valley-type) deposits. Employing the methods presented here yields quantitative mineral resource assessment results that more closely reflect the empirical distributions of grades and tonnages observed in nature and expands the applicability of these tools for ongoing critical mineral resource assessments.

Applied Computing and Geosciences↗

USGS2026

PFAS mixture composition and internal exposure profiles shape biological responses under field-realistic exposure

Per- and polyfluoroalkyl substances (PFAS) occur as complex mixtures, yet mixture-dependent biological effects under environmentally realistic exposure conditions remain poorly understood. We conducted multiyear (2018, 2019, 2021) continuous-flow, field-based exposures of male fathead minnows ( Pimephales promelas ) using a low-PFAS reference well (REF; sum of measured PFAS (∑PFAS) 0.1–0.2 μg L –1 ) and PFAS-contaminated groundwater from a fire-training area (FTA) at Joint Base Cape Cod, Massachusetts. Dilution treatments enabled separation of concentration and mixture effects. Groundwater from well FTA1 was perfluorooctanesulfonate (PFOS) dominated (∑PFAS 10–31 μg L –1 ), whereas groundwater from well FTA2 had higher concentrations and was enriched in perfluorooctanoate (PFOA) and diverse precursors (∑PFAS ∼ 80 μg L –1 ). Despite comparable plasma ∑PFAS and PFOS in FTA1–100% and FTA2–50% on day-7, cumulative mortality reached approximately 35% in FTA2–50% and 17% in FTA2–100%, and secondary sex trait expression was reduced by approximately 65–80% relative to REF, whereas sperm motility effects were mixture- and time-dependent. Plasma PFAS profiles were dominated by perfluorohexanesulfonate (PFHxS), PFOS, and sulfonamide precursors. Liver transcriptomics from REF-acclimated fish revealed robust disruption of metabolic, mitochondrial, and endocrine pathways that link PFAS mixture chemistry and internal exposure profiles to organismal outcomes, and testis transcriptomics provided complementary insight into reproductive impairment. These results indicate that PFAS mixture composition and internal exposure profiles, including precursor-associated differences, are important determinants of ecotoxicological outcomes under field-realistic conditions.

Massachusetts↗

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↗

USGS2024

Agricultural tile drains increase the susceptibility of streams to longer and more intense streamflow droughts

Streamflow droughts are receiving increased attention worldwide due to their impact on the environment and economy. One region of concern is the Midwestern United States, whose agricultural productivity depends on subsurface pipes known as tile drains to improve trafficability and soil conditions for crop growth. Tile drains accomplish this by rapidly transporting surplus soil moisture and shallow groundwater from fields, resulting in reduced watershed storage. However, no work has previously examined the connection between tile drainage and streamflow drought. Here, we pose the question: does the extent of watershed-level tile drainage lead to an increased susceptibly and magnitude of streamflow droughts? To answer this, we use daily streamflow data for 122 watersheds throughout the Midwestern United States to quantify streamflow drought duration, frequency, and intensity. Using spatial multiple regression models, we find that agricultural tile drainage generates statistically significant ( p < 0.05) increases in streamflow drought duration and intensity while significantly reducing drought frequency. The magnitude of the effect of tile drainage on streamflow drought characteristics is similar to that of water table depth and precipitation seasonality, both of which are known to influence streamflow droughts. Furthermore, projected changes in regional precipitation characteristics will likely drive the installation of additional tile drainage. We find that for each 10% increase in tile-drained watershed area, streamflow drought duration and intensity increase by 0.03 d and 12%, respectively, while frequency decreases by 0.10 events/year. Such increases in tile drainage may lead to more severe streamflow droughts and have a detrimental effect on the socio-environmental usage of streams throughout the Midwest.

Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio↗

USGS2021

Critical review of mercury methylation and methylmercury demethylation rate constants in aquatic sediments for biogeochemical modeling

Mercury is a toxin that causes neurological impairments in adults, is particularly harmful for fetuses and children, and is deadly in severe cases, making it a worldwide health concern. Methylmercury (MeHg) is the environmentally relevant form of mercury (Hg) because it biomagnifies along the food chain. Methylmercury is mainly produced in aquatic sediments via methylation of inorganic Hg (Hg(II)) and transformed back via demethylation. Because transformation rates determine MeHg concentrations, quantification of methylation and demethylation rates is needed to inform management of MeHg. Published rate constants for Hg(II) methylation ( 𝑘 𝑚 ) and MeHg demethylation ( 𝑘 𝑑 ) vary greatly, stemming partly from differences in experimental methods. We conducted a comprehensive review of rate laws, evaluated published rate constants, and performed biogeochemical simulations to assess variability in reported 𝑘 𝑚 and 𝑘 𝑑 . Based on selected studies employing the same pseudo-first-order rate law and similar experimental methods, we found that 𝑘 𝑚 = 0.04 ± 0.03 d −1 is a reasonable range for wetland sediments. Over a number of environments, maximum 𝑘 𝑑 was smaller at sites without Hg source ( 𝑘 𝑑 = 0.5 d −1 ) than at sites with identified Hg source ( 𝑘 𝑑 = 1.8 d −1 ). Larger variability and higher uncertainty in 𝑘 𝑑 compared to 𝑘 𝑚 highlight the need for more research on MeHg demethylation rates. This critical review: (a) aids the design of future experimental studies of 𝑘 𝑚 and 𝑘 𝑑 ; (b) provides guidance for comparing rate constants from different studies; (c) presents a biogeochemical reaction model to assess rate constants; and (d) informs selection of 𝑘 𝑚 and 𝑘 𝑑 values from the literature for use in model simulations.

Critical Reviews in Environmental Science and Tech↗

USGS2025

“Leaky weirs” capture alluvial deposition and enhance seasonal mountain-front recharge in dryland streams

“Leaky weirs” are rock structures installed in dryland streams, which are anchored into exposed bedrock, loosely cemented, and designed to allow water to slowly pass through. They are being tested at a ranch in southeastern Arizona, USA, to restore and conserve the historic range and desert wetlands. Data are collected to assess how leaky weirs impact surface water, subsurface water, and groundwater recharge—including stream discharge, timing, and depth of infiltration, and groundwater elevations. Three adjacent watersheds, two with outlets just below leaky weirs and one with leaky weirs farther upstream, were instrumented with water-level loggers, wildlife cameras, and crest stage instruments with temperature sensors in the soil. As most groundwater recharge is assumed to be focused along the mountain fronts in this region, mountain-block recharge is also evaluated to differentiate between the two using isotope analyses. Finally, a single, late-season flood event is scrutinized to consider the leaky weir effect on all monitored components in the water budget. Results indicated groundwater flow is primarily from the mountains to the east via older, regional mountain-block recharge. However, the development of shallow alluvial aquifers is supported by the leaky weirs, that slow flows, capture permeable sediments, and allow infiltration, thus enhancing mountain-front recharge. In turn, these new pockets of water help support the restoration of historic wetlands. Sediment accumulates where leaky weirs are installed, reducing flashy peak flows, and resulting in a series of infiltration ponds along the channel that support vegetation during growing seasons and recharge the shallow aquifer during non-growing seasons.

Arizona↗

USGS2025

A glimpse into the future of tectonic tremor monitoring

Tectonic tremor is a weak, long-duration seismic signal often observed in subduction zones and on some other plate-bounding faults. Because of tremor's characteristically low amplitude (and low signal-to-noise) and lack of clear phase arrivals, detecting and locating tremor usually requires techniques distinct from those applied to typical earthquakes. Major advances in detection and understanding of tremor have derived in the past from a powerful combination of new data and new analysis techniques. In a recent study, Sagae et al. (2025, https://doi.org/10.1029/2025jb031348 ) exploit that combination again, developing a new machine-learning based workflow and applying it to the S-net cabled seismic network in the Japan trench offshore northern Honshu. Their approach, although complex, succeeds in detecting several times more tremor activity than earlier studies, resulting in new insights and providing a blueprint for similar approaches that could be applied elsewhere. As real-time earthquake monitoring adopts similar tools, it may present an opportunity to bring tremor monitoring into operational workflows. In turn, this could solidify tremor monitoring as a component of future operational earthquake forecasting.

JGR Solid Earth↗

USGS2025

Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets

Coastal marsh wetlands experience variations in vertical gains and losses through time, which have allowed them to infill relict topography and record variations in drivers. The stratigraphic unit associated with the development of the marsh also reflects the long-term importance of key ecosystem services supplied by the marsh environment, including carbon storage and storm mitigation. Mapping these coastal wetland sediments and the marsh unit thickness is challenging as traditional coastal geophysical tools are not easily deployable (acoustic methods) or are unreliable in saline-soil environments (e.g., ground-penetrating radar), leaving core-based methods the most viable mapping method. In the present study, we utilized prior information on the geologic architecture of the region to select spatial and physical metrics that likely persisted throughout evolution of the marsh during the late Holocene. We then assessed the individual and collective power of these metrics to predict marsh thickness observed from cores. Employing regressive predictive models powered by these data, we improve the quantification of marsh thickness for a coastal fringing marsh within the Grand Bay estuary in Mississippi and Alabama (USA). The information gained from this approach yields improved estimates of the carbon stocks in this environment. Additionally, the stored sediment masses reflect the past, and potential future, persistence of the Grand Bay marsh under historical and present marsh-estuarine sediment exchange fluxes. Such improvements to both the sediment budget of recent marsh stratigraphic units and the spatial extent provide new resources for comparison with large-scale landscape models, the latter of which may be used, when validated, to predict future change and ecosystem transformations.

Alabama. Mississippi↗

USGS2025

Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques

The effect of extraction methods on detecting hydrocarbon oxidation products (HOPs) in groundwater remains unclear. HOPs are polar, water-soluble byproducts of petroleum biodegradation. Our previous work showed that liquid–liquid extraction (LLE), a method commonly used in regulatory monitoring, has a significantly lower extraction efficiency for HOPs compared to solid-phase extraction (SPE). In this study, we evaluate the analytical limitations and compositional selectivity of LLE and SPE using groundwater samples from the Bemidji, MN, crude oil spill site. Optical properties were characterized using excitation–emission matrix spectroscopy (EEMs), and a three-component PARAFAC model was validated, showing consistent trends across both extracts and whole water samples. Ultrahigh-resolution mass spectrometry (UHR-MS) revealed that LLE selectively recovered aliphatic-like compounds but underrepresented more polar oxygenated HOPs. In contrast, SPE methods were more effective at isolating highly oxidized compound classes. These differences were consistent across a gradient of contamination. Overall, the LLE was less precise and less representative of polar HOPs, introducing bias in the characterization of HOPs. This study is the first to quantitatively demonstrate the compositional selectivity and analytical bias of LLE versus SPE for HOPs using combined EEM-PARAFAC and UHR-MS techniques, with implications for long-term monitoring and site assessment protocols.

Environmental Science and Technology↗

USGS2026

Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States

Worldwide, about 50% of the population is served by groundwater-sourced drinking water. Numerous groundwater quality assessments have found that geogenic constituents are among the most common contaminants in drinking-water aquifers. Documenting changing groundwater quality is a crucial aspect of water availability assessments. We assess trends and occurrence of geogenic constituent concentrations in groundwater across the continental United States using 3 decades of data from the U.S. Geological Survey’s National Water Quality Network. Thousands of groundwater wells were grouped into agricultural, urban, or domestic supply network types. Although most networks and constituents had no statistically significant change in concentration, many had increasing concentration trends, elevated concentrations, or both. Lithium, sodium, radium, sulfate, and uranium had increasing trends in more than 10% of the study networks. Urban and domestic well networks had increasing lithium and sodium trends more often than agricultural networks. Manganese most commonly increased in domestic well networks; uranium more commonly increased in agricultural and urban networks. Elevated concentration mixtures were widespread, and mixture complexities appeared to increase over time. Our results indicate that more than 2.3 million domestic-well users may be affected by elevated concentrations of one or more geogenic constituents.

continental United States↗

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↗