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Results for “Water-Resources Investigations Report”

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1,206 records · Page 63Linked to original sources
USGS2024

Metal mobilization from thawing permafrost to aquatic ecosystems is driving rusting of Arctic streams

Climate change in the Arctic is altering watershed hydrologic processes and biogeochemistry. Here, we present an emergent threat to Arctic watersheds based on observations from 75 streams in Alaska’s Brooks Range that recently turned orange, reflecting increased loading of iron and toxic metals. Using remote sensing, we constrain the timing of stream discoloration to the last 10 years, a period of rapid warming and snowfall, suggesting impairment is likely due to permafrost thaw. Thawing permafrost can foster chemical weathering of minerals, microbial reduction of soil iron, and groundwater transport of metals to streams. Compared to clear reference streams, orange streams have lower pH, higher turbidity, and higher sulfate, iron, and trace metal concentrations, supporting sulfide mineral weathering as a primary mobilization process. Stream discoloration was associated with dramatic declines in macroinvertebrate diversity and fish abundance. These findings have considerable implications for drinking water supplies and subsistence fisheries in rural Alaska.

Alaska↗
USGS2025

2024 Surprise Inlet landslides: Insights from a prototype landslide‐triggered tsunami monitoring system in Prince William Sound, Alaska

Alaska's coastal communities face growing landslide hazards owing to glacier retreat and extreme weather intensified by the warming climate, yet hazard monitoring remains challenging. As part of ongoing experimental monitoring in Prince William Sound, we detected three large landslides (0.5–2.3 M m 3 ) at Surprise Inlet on 20 September 2024, within the span of an hour. These events were identified in near real-time through seismic data and later confirmed using satellite imagery, tidal records, and infrasound. The landslides generated a modest tsunami, and a 4 cm wave was recorded by a tide gauge 18 km away, marking the first recorded landslide to reach water since monitoring began in this region in 2021. Here, we examine the detection and interpretation of these landslides using multiple data sources and modeling. We demonstrate the effectiveness of this regional seismic monitoring system and show how complementary instrumentation, where available, can enhance detection capabilities.

Alaska↗
USGS2026

Emergent headwater types for watershed monitoring, research, and planning

Headwaters—that is headwater streams and the watersheds they drain—strongly influence water quality, ecosystem services, and hydrologic connectivity, yet remain poorly mapped, monitored, and understood at large spatial scales. Using available spatial data to classify headwater “types” could therefore enhance the utility of sparse monitoring data to advance research and watershed planning—and help update literature-based perceptual models of headwaters as steep, forested, and minimally disturbed watersheds. Here, we analyze headwaters across the contiguous United States to quantify how their attributes (climate, topography, land cover, soils) vary regionally and differ from their downstream watersheds. Our analysis (a) identified seven dominant headwater types with distinct combinations of biophysical and climatic attributes and (b) revealed systematic contrasts with downstream watersheds, with strongest differences in attributes representing potential flowpath depth. Our findings offer a transferable framework for classifying, modeling, and managing these critical yet understudied components of the hydrologic network.

conterminous United States↗
USGS2023

Explosive trachyte eruptions from the Al Efairia volcanic center in northern Harrat Rahat, Kingdom of Saudi Arabia

Harrat Rahat is an alkali basalt, continental, intraplate volcanic field located within the central-western part of the Kingdom of Saudi Arabia. The northern quarter of Harrat Rahat contains evolved volcanic products that achieve trachyte compositions (>60 weight percent SiO 2 ). Within the Al Efairia volcanic center, pyroclastic-flow and -surge deposits that reflect explosive trachyte volcanism (and minor exposed lava domes that reflect effusive trachyte eruptions) sit at the surface as the youngest expression of volcanic activity within this part of the Harrat Rahat volcanic field. Five trachyte deposits emplaced explosively have been identified within the Al Efairia volcanic center based on geologic mapping, petrography, geochemistry, and paleomagnetism. These units are the trachytes of Um Rgaibah, Gura 5, Gura 4, Al Efairia, and Al Qayf, in descending stratigraphic order. Here, we present 14 40 Ar/ 39 Ar analyses from four of these units, which yield eruption ages of 4.2±5.2 thousand years (ka) for the trachyte of Um Rgaibah, 79.7±1.6 ka for the trachyte of Gura 5, 84.3±1.6 ka for the trachyte of Gura 4, and 88.0±1.8 ka for the trachyte of Al Efairia. The eruption age of the trachyte of Al Qayf has been constrained to between 410.3±3.4 and 418.8±1.9 ka using paleomagnetic correlations and 40 Ar/ 39 Ar ages from overlying and underlying intermediate composition lava flows. Most of these trachytes have distinct geochemical compositions, petrographic characteristics, and directions of remanent magnetization. The exceptions are for the trachytes of Gura 4 and Gura 5, which overlap in their geochemical, petrographic, paleomagnetic, and geochronologic affinities. Based on these similarities, we interpret the trachytes of Gura 4 and Gura 5 to have erupted during a closely spaced (a few decades) time interval from the same magma batch but from craters that are >2 kilometers (km) apart. The eruption of the trachyte of Al Efairia at 88.0±1.8 ka is the result of a different magma batch that erupted a few thousand years prior to the trachytes of Gura 4 and Gura 5. The Al Efairia volcanic center is remarkably different from the Matan volcanic center located ~10 km to the north, which has also erupted young (<150 ka) trachytes. The Matan volcanic center has been shown to produce trachyte compositions only after eruption of basalt followed by intermediate lava flows, whereas only trachyte compositions have erupted within the Al Efairia volcanic center over this same time interval.

Al Efairia volcanic center, Harrat Rahat↗
USGS2026

Distributed volcanic fields—Patterns, products, processes, and plumbing

Distributed volcanic fields—also referred to as “monogenetic fields” or simply “volcanic fields”—are found on every continent, on the seafloors, and in every tectonic setting on Earth. Yet, our understanding of what constitutes a distributed volcanic field, and our knowledge of the common products, spatiotemporal patterns in activity, and plumbing systems of these fields, are commonly poor and (or) debated. Here we provide an overview of the current understanding of distributed volcanic fields (DVFs) through review and compilation of published data, with an emphasis on understanding the characteristics of fields that are essential to prepare for future hazardous volcanic activity. Distributed fields can erupt restricted to variable magma compositions. Activity in these fields produces nearly all types of volcanoes, including scoria and spatter cones, maars, low shields, lava fields, stratovolcanoes, and calderas, but monogenetic volcanoes are the defining characteristic of DVFs. The number of vents and lifespans of DVFs vary greatly; vent numbers range from 2 to greater than 1,000, and fields can remain active for 150,000 to 10 million years. Some characteristics of DVFs appear field dependent. Although the volumes of single monogenetic eruptions within DVFs globally are variable (from less than 0.1 to a few cubic kilometers), each field may have a characteristic range in eruption volumes. Eruptions within distributed volcanic fields can have a random distribution and timing, but spatial and (or) temporal vent clustering and alignment are common, and eruptions may be time or volume predictable. Average eruption recurrence intervals in DVFs span over an order of magnitude, from less than 3 to greater than 100 thousand years. Exposures of the shallow portions of older systems reveal that many magma batches end their ascent before reaching the surface, with some dikes stopping within only meters of the surface. Petrologic insights into the deeper plumbing systems of DVF volcanoes indicate variable depths of magma crystallization and (or) stalling, and that magma transport and storage systems may be unique to a particular DVF and its underlying crustal structure. Both seismic and petrologic data for mafic DVF eruptions corroborate intrusions of magma into storage systems in the months to years before eruption, as well as variable ascent rates through the crust (days to weeks). Few distributed fields are closely monitored, as they erupt infrequently, but these observations imply that the amount of time available to install monitoring instrumentation after the first felt seismicity may be short, as precursory activity is frequently on the order of days to months for modern DVF eruptions. Satellite-based geodesy may provide useful warning in such cases. This chapter concludes with outstanding questions and areas for future research that will aid in our understanding and preparedness for future DVF eruptions.

Professional Paper↗
USGS2024

Analyzing spatial distributions and alignments of pitted cone features in Utopia Planitia on Mars

Martian geomorphology and surface features provide links to understanding past geologic processes such as fluid movement, local and regional tectonics, and feature formation mechanisms. Pitted cones are common features in the northern plains basins of Mars. They have been proposed to have formed from upwelling volatile-rich fluids, such as magma or water-sediment slurries. In this study, we map the spatial distributions of pitted cone features across the Utopia Planitia (UP) basin. Using the Average Nearest Neighbor technique, we find that pitted cone features appear to be clustered across the basin, occurring in a narrow band around the circumferential rim of UP. Additionally, we find that pitted cone features also appear to be aligned in chains that are sub-parallel with the basin margin. Parallel bands of cones generally follow elevation contours of the UP basin, which suggests elevation or a correlated factor plays a major role in pitted cone and cone chain formation. We propose that pitted cones and cone chains may be related to vertical fractures formed around the UP basin rim from subsidence of infilling basin material.

Icarus↗
USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska↗
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↗
USGS2025

Dating a medieval tsunami with uranium-series techniques on Caribbean corals

Uranium-series dates from coral boulders constrain the timing of a medieval tsunami from the Puerto Rico Trench. Previously reported evidence for this tsunami includes hundreds of coral boulders that came to rest hundreds of meters inland on Anegada, British Virgin Islands. New U-series dates on these coral boulders provide limiting dates for the tsunami. The narrowest limits were by dating interior bands of a coral that retains the hemispherical form of a living coral colony, and which include adjustments for the number of annual density band couplets between the dated samples and the boulder exteriors. By those limits, the tsunami dates between 1381 and 1391 CE, and likely occurred during summer or fall. The tsunami is important as the only reported sign that the eastern Puerto Rico Trench has produced a great earthquake. The dating may aid in defining the earthquake source and in communicating tsunami hazards.

British Virgin Islands, Puerto Rico↗
USGS2026

Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python

Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.

Wisconsin↗
USGS2024

Neogene hydrothermal Fe- and Mn-oxide mineralization of Paleozoic continental rocks, Amerasia Basin, Arctic Ocean

Rocks dredged from water depths of 1,605, 2,500, 3,300, and 3,400 m in the Arctic Ocean included Paleozoic continental rocks pervasively mineralized during the Neogene by hydrothermal Fe and Mn oxides. Samples were recovered in three dredge hauls from the Chukchi Borderland and one from Mendeleev Ridge north of Alaska and eastern Siberia, respectively. Many of the rocks were so pervasively altered that the protolith could not be identified, while others had volcanic, plutonic, and metamorphic protoliths. The mineralized rocks were cemented and partly to wholly replaced by the hydrothermal oxides. The Amerasia Basin, where the Chukchi Borderland and Mendeleev Ridge occur, supports a series of faults and fractures that serve as major zones of crustal weakness. We propose that the stratabound hydrothermal deposits formed through the flux of hydrothermal fluids along Paleozoic and Mesozoic faults related to block faulting along a rifted margin during minor episodes of Neogene tectonism and were later exposed at the seafloor through slumping or other gravity processes. Tectonically driven hydrothermal circulation most likely facilitated the pervasive mineralization along fault surfaces via frictional heating, hydrofracturing brecciation, and low- to moderate temperature Fe- and Mn-rich hydrothermal fluids, which mineralized the crushed, altered, and brecciated rocks.

Geochemistry, Geophysics, Geosystems↗
USGS2025

Metaproteomics and metagenomics reveal microbial pathways of organic matter degradation and methanogenesis in a marginally producing natural gas well

The expansion of natural gas production and utilization worldwide has led to the decline of many once-productive wells, eventually resulting in costly well-plugging and unused infrastructure. However, in areas like the Michigan basin, MI, where the majority of natural gas is biogenically produced, microbial communities could potentially be stimulated to generate additional methane, increasing gas supply and reducing the need to drill new wells. In this study, we performed metaproteomic, metagenomic, and geochemical analyses of Antrim Shale formation water from a marginally producing natural gas well to evaluate resident microbial community functions in the context of potential bioenergy production. Functional proteins involved in methanogenesis, degradation/catabolism (including organic matter degradation), biosynthesis, energy utilization, transmembrane transport, and stress response were among the most commonly identified groups. Three metagenome-assembled genomes (MAGs) were characterized, including Methanomicrobiaceae, Methanothrix , and Smithella . For each, the identified proteins involved in methanogenesis and the degradation of diverse organic compounds, strongly suggest their role in utilizing shale-derived organic matter. These findings provide an increased understanding of the microorganisms and their metabolisms generating natural gas in the Antrim Shale and establish a foundation for future stimulation efforts aimed at enhancing biogenic methane production in marginal gas wells.

Michigan↗
USGS2026

Morphodynamics of snow barchans at Concordia Station, Antarctica

Barchans are crescent-shaped dunes that form and migrate under unimodal wind regimes in areas of low sediment availability. While sand barchan morphodynamics has been extensively studied, snow barchans remain poorly documented. Here, using hourly time-series images taken near Concordia Station, Antarctica, we measure the sizes (lengths 0.3 m to 13 m, widths 0.4 m to 7.5 m) and migration rates (0.13 m h −1 to 3.5 m h −1 ) of 44 populations of snow barchans during 2017–2022. We compare this dataset with established height–velocity and length-width relationships for sand barchans in both air and water. Our results show that snow barchans follow the same scaling as sand barchans, allowing us to estimate a characteristic sintering (bonding of snow particles) time of about one day. This sintering process limits the size of snow barchans when active, reduces their aspect ratios, and, once wind falls below the transport threshold, explains their preservation over a few years. During wind events, migrating barchans are too small to maintain their shape and orientation, making them highly responsive to fluctuations in wind direction. Thus, studying snow barchans improves understanding of an elementary bedform encountered in multiple environments and also of the surface properties of snow on different timescales, offering insights into snow accumulation and wind-blown snow in ice cores.

Geomorphica↗
USGS2025

Grand Canyon landslide-dam and paleolake triggered by the Meteor Crater impact at 56 ka

This paper hypothesizes that the Meteor Crater impact in Arizona, USA, 56,000 years ago triggered landslides in Grand Canyon that dammed the Colorado River and formed Nankoweap paleolake. This is compatible with shock and earthquake physics for the impact that infer a M5.4 seismic event, attenuated to an effective magnitude of M3.5 at Grand Canyon. Results that support the hypothesis include radiocarbon dating of driftwood and luminescence dating of associated slack-water lake sediments that are preserved in caves up to 60 m above the modern Colorado River. Radiocarbon ages from two locations, including Stanton’s Cave, date the driftwood as 55.25 ± 2.44 ka (n = 4). Sediments associated with the driftwood gave a luminescence age of 56.00 ± 6.39 ka (n = 2). These six Grand Canyon dates, and three published ages for the Meteor Crater impact, show statistically indistinguishable results that support the hypothesis for a geologically instantaneous series of events with a mean age of 55.60 ± 1.30 ka. This work highlights the value of radiocarbon dating near the limits of the technique, integration of multiple dating methods, and seismic and landslide hazards associated with meteorite impacts in regions of extreme topography like Grand Canyon.

Arizona↗
USGS2026

From model to action: Identifying the gaps in coastal marsh models for decision making

Coastal salt marsh modeling projects are designed to answer questions about where salt marshes may migrate, how they can migrate, and how they will be impacted by changing water levels. While this information is vital for climate-resilient marsh conservation, translating these findings into actionable results remains a challenge. The authors examined the actionability of marsh modeling efforts in the United States by analyzing data collected from semi-structured interviews of marsh model users ( n = 24) across two ongoing projects along the U.S. East Coast and the Gulf of America (Gulf of Mexico). By qualitatively analyzing the interview data, the authors found that the tasks of practitioners who use coastal marsh model outputs fall into three major themes: (1) marsh restoration, (2) planning with uncertainty, and (3) conserving habitat for marsh-reliant species. For each of these themes, the authors identify unmet needs, including high spatial resolution information for local planning, accessible descriptions of uncertainty to increase user confidence, and the incorporation of human dimensions data (e.g., human alterations to the landscape such as impoundments and culverts) for a comprehensive understanding of the coastal salt marsh. Marsh modeling projects should strategize how to fulfil these unmet user needs so that marsh modeling outputs can better support decisions related to marsh conservation and restoration.

Gulf of America, United States East Coast↗
USGS2026

Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality

Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.

Maine, New Hampshire, Vermont↗
USGS2025

Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes

Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.

Colorado↗
USGS2025

Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks

The estimated ultimate recovery (EUR) is an important parameter for forecasting oil and gas production and informing decisions regarding field development strategies. In this study, we combined site-specific geologic, completion, and operational parameters with the predictive capabilities of machine learning (ML) models to predict EURs of the wells for the Eagle Ford Marl Continuous Oil Assessment Unit. We developed an extensive dataset of wells that have produced from the lower and upper Eagle Ford Shale intervals and reduced the model complexity using principal component analysis. We tested the ML models and estimated the sensitivities of ML-predicted EURs to changes in the values of different input variables. The results of applying the optimized ML model to the Eagle Ford suggest that the approach developed in this study could be promising. The ML estimates of the EURs fit the DCA-based values with an R 2 ~ 0.9 and a mean absolute error of ~36 × 10 3 bbl. In the lower Eagle Ford Shale, the EUR estimates were found to be most sensitive to changes in porosity, net thickness of the interval, clay volume, and the API gravity of the oil; and that in the upper Eagle Ford Shale they were most sensitive to changes in the total organic carbon and water saturation, which suggests that it could be important to consider these parameters in assessing these intervals or close analogs.

Louisiana, Mississippi, Texas↗