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The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration

Water-quality appraisal of NASQAN stations below impoundments, eastern Tennessee

The National Stream Quality Accounting Network (NASQAN) is a network of stations at which systematic and continuing water-quality data are collected. Major objectives of this U.S. Geological Survey program are (1) to depict areal variability of streamflow and water-quality conditions nationwide on a year-by-year basis and (2) to detect long-term changes in streamflow and stream quality. Several NASQAN stations in East Tennessee are downstream from impoundments which have a significant effect on water quality. NASQAN data obtained from the Tennessee River below Watts Bar Dam and the Clinch River below Melton Hill Dam were compared to water-quality data from the basins upstream. The comparison indicates that NASQAN data obtained below impoundment may not be adequate to describe a composite picture of water quality in the accounting unit. Detention time of storage in the impoundments is believed to moderate the range of constituent values observed at the NASQAN stations. Data obtained upstream and downstream from Watts Bar Dam indicate that the water sampled at the NASQAN station comes from stratified layers of the impoundment and is not representative of an integrated sample of water from the impoundment. Values of total recoverable iron suggest that, because of adsorption to sediments in impoundments, some constituents are not accurately described by sampling below impoundments. Relations between water-quality constituents and flow at stations on the Clinch River and Tennessee River are not well defined due to regulation. Direct load computations for many constituents were therefore not possible, which diminished the utility of data from these NASQAN stations to account for quantity versus quality of the water. Load computations were only possible for ionic constituents through use of a continuous specific-conductance record as an intermediary. Compensation for the effects of discharge prior to application of the Seasonal Kendall test for trends could not be done and identification of trends in water-quality constituents caused by some process (source) change was not possible. Some water-quality trends indicated by data from the Clinch and Tennessee Rivers might reflect the decreasing trend in discharge during the 1972-82 water years. Thus the stations below Watts Bar Dam and below Melton Hill Dam do not adequately meet the NASQAN objective to detect and assess long-term changes in stream quality.

Tennessee

Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings

Fluvial erosion is increasingly responsible for infrastructure and building damages associated with floods as the intensity of extreme rainfalls hit rural and urban rivers in a variety of climate settings across the United States. Extreme floods in 2016 and 2018 caused widespread culvert blockages and road failures, including extensive damage along steep tributaries and ravines in the Marengo River, Wisconsin, watershed during 2016 and 2018. A study conducted by the U.S. Geological Survey (USGS), Wisconsin Wetlands Association (WWA), Ashland County, and the Northwest Wisconsin Regional Planning Commission (NWRPC) investigated the special concern of fluvial erosion hazards (FEHs) associated with gullying, streamside landslides, and the loss of wetland storage in headwaters. In 2019, a pilot study was begun to map and classify ephemeral and perennial streams and wetlands in terms of their sensitivity to FEHs. This study combined data from field-based rapid geomorphic assessments (RGAs) coupled with a stream network-wide geographic information system (GIS) approach for mapping stream segments, referred to as fluvial process zones (FPZ), sensitive to erosion, deposition, and channel change. The GIS approach used nationally available 10-meter (m) resolution topology and an extended stream network to map FPZs based on Strahler stream order, stream power, channel slope, presence of adjacent steep valley sides and headwater flats, and adjacent landform setting. Bankfull channel widths derived from RGA-based hydraulic geometry curves combined with drainage areas, an estimate of bankfull flow, and channel slope were used to calculate specific stream power for the FPZs. Lastly, the FPZs were characterized by their location within three major landform settings that affect erosion potential. The resulting vulnerability maps provided a screening framework to identify FPZs that are sensitive to incision, gullying and mass wasting along steep headwater ephemeral channels, as well as downstream perennial channels that have the potential for valley-side landslides, coarse sediment deposition, and channel change. Lastly, each FPZ was characterized in terms of hydrologic alteration associated with ditching. The vulnerability mapping products and rankings of sensitivity of FPZs will ultimately be used by Ashland County and their collaborators to prioritize natural flood management projects that mitigate FEHs, restore hydrology, and reconnect channels with adjacent wetlands and floodplains.

Wisconsin

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE

Investigation of land cover within wetland complexes at Dixie Meadows, Churchill County, Nevada, from October 2015 to January 2022

The U.S. Geological Survey investigated land cover at subannual time steps within six wetland areas in Dixie Valley, Churchill County, Nevada, from October 2015 to January 2022. As requested by the U.S. Fish and Wildlife Service, we used aerial photography and satellite remote sensing data to map surface water and other land cover types within the wetland complexes. We identified five land cover classes using the green normalized difference vegetation index (gNDVI) and its inverse relationship to the normalized difference water index (NDWI) within three U.S. Department of Agriculture National Agriculture Imagery Program aerial images (acquired in 2015, 2017, and 2019) and 110 European Space Agency Sentinel-2 satellite images (acquired 2015–2022). The relative wetness of soil conditions within each land cover class is estimated by comparison to previously published observations of relative conductivity measured by 79 field-based sensors within the wetlands from 2019 to 2021. We mapped the areal coverage of the five land cover classes for approximately 385 acres (1,559,000 square meters [m²]) comprising six individual wetland complexes as well as a larger 1,298- acre (5,254,000-m 2 ) area of interest inclusive of the wetland complexes and adjacent landscape. Land cover of open water (Class 5) primarily within ponds at one of the wetland complexes comprised 8,333 m 2 , on average, of the wetland complexes. Land cover of mixed shallow surface water, saturated soil, and vegetation (Class 4) comprised 111,723 m 2 on average of the wetland complexes. Land cover of dense green vegetation canopy cover (Class 3) that often (46 percent of observations) had underlying surface water or saturated soil conditions comprised 592,522 m 2 on average of the wetland complexes. The remaining areas of the wetland complexes not mapped as these three land cover types (Classes 2 and 1) had sparse vegetation or bare soil cover and commonly (greater than or equal to 67 percent of observations) had dry soil conditions. The investigation of land cover detailed in this report could inform future efforts to map land cover more precisely via higher resolution remote sensing or ground-based surveying or could be incorporated with other environmental monitoring data to characterize habitat and hydrology of the wetland complexes at Dixie Meadows.

Nevada

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire

Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

Ecosphere

Water-quality assessment of south-central Texas — Descriptions and comparisons of nutrients, pesticides, and volatile organic compounds at three intensive fixed sites, 1996-98

Water-quality samples were collected during April 1996-April 1998 at three intensive fixed sites in the San Antonio region of the South-Central Texas study unit as part of the U.S. Geological Survey National Water-Quality Assessment Program. The sampling strategy for the intensive fixed-site assessment is centered on obtaining information about the occurrence and seasonal patterns of selected constituents including nutrients, pesticides, and volatile organic compounds. The three sites selected to determine the effects of agriculture and urbanization on surface-water quality in the study unit are Medina River at LaCoste (agriculture indicator site), Salado Creek (lower station) at San Antonio (urban indicator site), and San Antonio River near Elmendorf (integrator site). Concentrations of two nutrients, dissolved nitrite plus nitrate nitrogen and total phosphorus, were largest at the integrator site, which is downstream of municipal wastewater treatment plants. Nitrite plus nitrate nitrogen concentrations at this site often exceeded the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for drinking water. All total phosphorus concentrations at the site exceeded the EPA recommended maximum concentration for streams not discharging directly into reservoirs. Nitrite plus nitrate nitrogen concentrations at the integrator site tended to be smaller, and total phosphorus concentrations at the urban site tended to be larger in samples collected during stormflow than during base flow. The most detections and largest concentrations of three pesticides (atrazine, diazinon, and prometon) were in samples collected at the urban site. Some pesticide concentrations at the agriculture site showed a seasonal pattern of increasing concentrations during spring, the peak application season. Four pesticides (atrazine, deethylatrazine, diazinon, and prometon) were detected in at least 38 percent of samples collected at all three sites. The concentrations of all detected pesticides that have an MCL were less than the MCL at the three sites. More volatile organic compounds (VOC) were detected at the urban indicator site than at the agriculture indicator site, mostly likely because more sources are located in urbanized areas. The most VOCs detected and the largest concentrations of two VOCs (chloroform and tetrahydrofuran) were in samples from the integrator site. More VOCs were detected in samples collected at the integrator site during stormflow than during base flow. The concentrations of all detected VOCs that have an MCL were less than the MCL at the three sites.

Texas

Nutrients and pesticides in ground water of the Ozark Plateaus in Arkansas, Kansas, Missouri, and Oklahoma

A total of 229 ground-water samples were collected from 215 sites as part of the Ozark Plateaus study unit of the National Water-Quality Assessment Program. These samples were collected from 1993 through 1995 using a network of springs and wells with three scale-dependent components. The first component, the study-unit survey, consisted of 99 randomly selected springs and domestic wells in the Springfield Plateau and Ozark aquifers. The second component, two land-use studies, consisted of 42 springs and domestic wells in a poultry-dominated agricultural area and 40 springs and domestic wells in a cattle-dominated agricultural area overlying the Springfield Plateau aquifer. The third component, the small-watershed study, consisted of 4 springs, 18 domestic wells, and 11 monitoring wells in a small basin within the poultry land-use study area. Samples were analyzed for major ions, nutrients, dissolved organic carbon, methylene blue active substances, tritium, and 88 pesticides and metabolites.The water-quality data from these samples were analyzed with descriptive and statistical methods. Nitrite plus nitrate, which was detected more often and in greater concentrations than any of the other nutrients, ranged from less than 0.05 to 25 milligrams per liter as nitrogen. Nitrite plus nitrate concentrations positively correlated to percent agricultural land use around each site. Median nitrite plus nitrate concentrations generally were greater in samples from springs than in samples from wells. Concentrations of nitrite, ammonia, and ammonia plus organic nitrogen were also affected by land use and also by concentrations of dissolved oxygen in the ground water. Concentrations of phosphorus and orthophosphate probably were affected by land use and also by phosphorus solubility. Pesticides were detected in 80 of 229 samples from 73 of 215 sites. A total of 20 pesticides were detected with a maximum of 5 pesticides detected in any 1 sample. The most commonly detected pesticides were tebuthiuron, atrazine, prometon, desethylatrazine, and simazine. Maximum concentrations ranged from 0.003 to 1.0 microgram per liter. The occurrence and distribution of pesticides were related to land use. Percent agricultural land use was greater for samples with pesticides detected than for samples with no pesticides detected. Pesticides were detected more often in samples from springs than in samples from wells. The occurrence of pesticides also was related to seasonality and chemical characteristics, such as solubility and persistence, of the compounds.

Arkansas, Kansas, Missouri, Oklahoma

Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent

The increased demand for clean energy technology and a significant reliance on foreign supply chains have given impetus to understanding critical mineral systems and locating potential resources within the United States. At least thirteen critical mineral-bearing systems have been identified throughout the U.S. southern Midcontinent (Hofstra and Kreiner, 2020) but much of the region’s geologic framework is concealed by vegetation and sedimentary cover that hinder traditional geologic mapping efforts. Airborne geophysical data provide an effective way to overcome these obstacles and to provide additional insight into the deeper structures that underlie shallow mineralization. However, legacy airborne magnetic and radiometric data were collected using now-outdated instruments and methods, inconsistent survey parameters, and large flight-line spacings resulting in low-resolution data that present challenges to regional-scale study and interpretation. Over the last decade, the U.S. Geological Survey Earth Mapping Resources Initiative (EMRI) and National Cooperative Geologic Mapping Program have conducted a series of high-resolution airborne magnetic and radiometric surveys across the southern Midcontinent (Fig. 1) as part of an effort to improve understanding of the geophysical framework and natural resource potential in the region. These surveys are designed using modern survey methods and instruments with consistent parameters for flight-line spacing and flight height relative to magnetic sources. The EMRI airborne surveys are planned in collaboration with State geological surveys based on focus areas (Dicken et al., 2022) according to the presence of or potential for critical mineral deposits. High-resolution airborne magnetic and radiometric data cover focus areas such as the southeast Missouri iron metallogenic province and South-Central iron-oxide-apatite (IOA) – iron-oxide-copper-gold (IOCG) province, the Magnet Cove alkaline-carbonatite complex, the Midwest Permian ultramafic dike district, the Illinois-Kentucky fluorspar district, and several Mississippi Valley-type lead-zinc deposits and districts (Fig. 1). These focus areas represent known deposits or prospective host systems of critical minerals including rare earth elements (REEs), platinum-group elements (PGEs), cobalt, lithium, fluorspar, niobium, titanium, vanadium, lead, zinc, gallium, germanium, and many more. Other significant geologic and geophysical features covered include the Reelfoot rift, the New Madrid seismic zone, the Illinois basin, the Arkoma basin, the South-Central magnetic lineament, and the Kentucky-Tennessee magnetic anomaly (Fig. 1). This presentation focuses on new airborne magnetic and radiometric data with continuous coverage across parts of six states, preliminary interpretations, examples of geologic mapping applications, and discussion of newly discovered magnetic anomalies and follow-up investigations.

Conference Paper

Component identification of solid biomass fuels using reflected light microscopy: Interlaboratory study 2

As nations transition toward sustainable energy systems , biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

International Journal of Coal Geology

Ungulate migrations of the Western United States, volume 4

Broadly distributed across the Western United States, ungulates (hooved mammals) play an important role in ecosystem function by affecting vegetation communities and forming the prey base for large carnivores. Additionally, ungulates provide economic benefits to regional communities through tourism and hunting and hold cultural significance for many Tribal communities. Many ungulates migrate seasonally between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. Increasingly, these migrations are threatened by the growing human footprint and associated subdivisions, energy development, and increased traffic volume. Efforts to study ungulate populations and conserve their migrations received support in recent years from the U.S. Department of the Interior Secretarial Order No. 3362, which provided Federal support for enhancing habitat quality for ungulates across the Western States. In response to Secretarial Order No. 3362, the U.S. Geological Survey (USGS) established the Corridor Mapping Team, a collaboration among USGS and participating State and Federal wildlife management agencies and numerous Tribal Nations. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States in the USGS “Ungulate Migrations of the Western United States” report series. This report (volume 4) details migrations and seasonal ranges from 31 new herds throughout nine Western States. Additionally, this report includes updates to two herds published in previous reports. Including this report, the report series has provided the mapped migrations and seasonal ranges of 182 unique herds and has provided a map-based inventory of the documented ungulate migrations across the Western United States for biologists, managers, policy makers, and conservation practitioners. This report also discusses how the mapping efforts associated with the Corridor Mapping Team can be used to guide management and policy regarding renewable energy development and ungulate disease, specifically chronic wasting disease, in the Western United States.

Arizona, California, Colorado, New Mexico, Nevada,

Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data

The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km 2 ) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m 2 ) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points ( n =870) during active mapping and accuracy assessment points ( n =216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones. The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m 2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.

Hawaii

Assessment of coastal and fluvial morphodynamic changes using Structure-for-Motion: A case study of the Sfȃntu Gheorghe Mouth (Danube Delta, Romania)

The ability to accurately map erosion, flooding, and habitat loss in coastal environments is crucial for formulating national strategies aimed at preventing and mitigating the impacts of natural disasters. A fundamental component of this process is the implementation of coastal morphodynamics monitoring through Structure-from-Motion (SfM) techniques, utilizing high-resolution 2D/3D data obtained from aerial photogrammetry. To assess morphodynamic changes over a three-year period (2022 – 2024), several SfM-based photogrammetric studies were conducted, each year, in the Romanian sector of the Danube-Black Sea coastal zone, specifically at the mouth of one of the Danube River distributaries (Sf Gheorghe branch) into the Black Sea, and along the left bank, near Sf Gheorghe locality, located within the Danube Delta Biosphere Reserve (DDBR). The essential equipment for aerial photogrammetry comprises Unmanned Aerial Vehicles (UAVs) and Global Navigation Satellite Systems (GNSS). In this study, the UAV used was a DJI Mavic 3T (Enterprise/Thermal) drone, complemented by two Trimble R12i and R4 GNSS systems, as well as approximately 10 Ground Control Points (GCPs). Data acquisition and processing were carried out using specialized photogrammetric software (Agisoft Metashape) along with various GIS tools (e.g., Blue Marble Geographics Global Mapper and ESRI ArcMap). The photogrammetric products generated for the study, as detailed in this paper, include Digital Elevation Models (DEMs), Digital Terrain Models (DTMs), orthomosaics (orthophotos), and others. At Sfântu Gheorghe beach, a comparison between 2023 and 2024 photogrammetric surveys revealed that the left bank of the Sf. Gheorghe Arm, at the river mouth into the Black Sea, suffered from a twist (erosion) of up to 64 metres. Additionally, on the selected perimetre (total area of 31,910 square meters ) from the beach and dune zone of Sf. Gheorghe, an area of up to 16,202 square meters was eroded between 2023 and 2024. This contrasts with the period between 2022 and 2023, during which deposition predominated. Erosion at the Danube mouths and the adjacent Black Sea coastline is driven by a complex interaction of natural and anthropogenic factors. Natural processes, including subsidence, sea-level rise, and episodic extreme storm events, contribute significantly to coastal dynamics. Meanwhile, human-induced factors, such as upstream hydrotechnical works that limits sediment transport, cutting of navigation canals, as well as the exacerbating effects of climate change, further accelerate erosion. The recent Structure-from-Motion (SfM) surveys provide essential quantitative data, enabling a detailed analysis of both short-term and long-term morphodynamic changes influenced by seasonal variations and extreme hydrometeorological events in this highly dynamic coastal system.

Sfȃntu Gheorghe Mouth (Danube Delta)

Federal lands greenhouse gas emissions and sequestration in the United States: Estimates for 2005–22

In 2016, the Secretary of the U.S. Department of the Interior requested that the U.S. Geological Survey (USGS) produce a publicly available and annually updated database of estimated greenhouse gas emissions associated with the extraction and use of fossil fuels from Federal lands. The first report in this series included emissions estimates from 2005 to 2014 and were reported for 29 States and two offshore areas. Native American and Tribal lands were not included in that analysis. This report recalculates those previous years (2005–14) with updated data and methods and extends the estimates to 2022. Nationwide emissions from fossil fuels produced on Federal lands in 2022 were 1,081.2 million metric tons of carbon dioxide equivalent (MMT CO 2 Eq.) for CO 2 , 33.4 MMT CO 2 Eq. for methane (CH 4 ), and 4.3 MMT CO 2 Eq. for nitrous oxide (N 2 O). Compared to 2005, the 2022 totals represent decreases in emissions for all three greenhouse gases (by 17 percent for CO 2 , 37 percent for CH 4 , and 30 percent for N 2 O). Emissions from fossil fuels produced on Federal lands represent, on average, 21.8 percent of U.S. emissions for CO 2 , 6.1 percent for CH 4 , and 1.3 percent for N 2 O over the 18 years included in this estimate. The trends and relative magnitudes of the greenhouse gas emissions estimated are roughly parallel to the Federal lands fossil fuel production volumes. In 2021, Federal lands of the conterminous United States stored 70,424 MMT CO 2 Eq. in terrestrial ecosystems. Soils stored most of the terrestrial ecosystem carbon (66 percent), followed by live vegetation (25 percent), deadwood (5 percent), and litter (4 percent). Carbon sequestration on Federal lands was highly variable over time, owing primarily to interannual variability in climate and weather, and variability in land use and land cover (LULC) change and disturbances, among these are wildfires and logging. Between 2005 and 2021, Federal lands sequestered an average of 83 MMT CO 2 Eq./yr. By subtracting the cumulative effects of LULC and disturbance-related CO 2 losses to the atmosphere from the total, we estimate that ecosystems at the national level sequestered CO 2 at an annual mean rate of 17 MMT CO 2 Eq./yr in a term called the net ecosystem exchange (NEE). This annual NEE sequestration value represents about 1.4 percent of average fossil fuel emissions over the same period. The USGS estimates presented in this report represent an accounting for the emissions resulting from fossil fuel extraction on Federal lands and the end-use combustion of those fuels, as well as for the sequestration of carbon in terrestrial ecosystems on Federal lands. A combined net CO 2 emissions estimate, which is the difference between the emitted and sequestered CO 2 from both the fossil fuel and ecosystems estimates, provides context for evaluating the greenhouse gas contributions of activities on these lands. The estimates included in this report can provide context for future energy decisions, as well as a basis to track change in the future.

Scientific Investigations Report

Diel temperature signals track seasonal shifts in localized groundwater contributions to headwater streamflow generation at network scale

Groundwater contributions to streamflow sustain aquatic ecosystem resilience; streams without significant groundwater inputs often have well-coupled air and water temperatures that degrade cold-water habitat during warm low flow periods. Widespread uncertainty in stream-groundwater connectivity across space and time has created disparate predictions of energy and nutrient fluxes across headwater networks, hindering predictions of cold-water habitat resilience under climate change scenarios. Recently, annual paired air and water temperature signals have been harnessed to indicate stream water thermal sensitivity and the dominance of deep versus shallow groundwater influence, although the utility of diel air–water temperature signal metrics for hydrologic inference has remained unexplored. Here we analyzed two consecutive years of locally paired, air–water temperature data from 47 headwater stream sites in the Catskill Mountains, New York, USA, and discovered characteristic seasonal patterns in diel temperature signal sinusoid metrics (amplitude ratio, phase lag, and mean ratio) driven by shifts in streamflow generation mechanisms and stream network position. Hydrologic interpretations of observed patterns were supported by stream heat budget model scenarios and additional analysis of paired air–water temperature data from two streams in Shenandoah National Park, Virginia, USA, with well characterized stream-groundwater connectivity. We found that within smaller tributaries, streamflow generation transitions from runoff to groundwater dominance were driven by hillslope drying during seasonal periods of lower precipitation. This was evidenced by significant correlations (p < 0.01) between daily water:air temperature signal amplitudes (non-linear decreases of ∼ 50 %) and derived base-flow index at 22 of the 28 sites, indicating enhanced local groundwater influence on streamflow promotes decoupling of diel air–water temperature signals. Additionally, ratios between daily water:air temperature signal means were lower in tributaries (∼0.68) when compared to main-stem (∼0.8) sites, increasing linearly throughout the observational period. In conceptual stream heat budget models, groundwater inflow had minimal effects on daily phase lags (∼0.2 hr), but increases in fractional groundwater discharge (0–50 %) depressed daily amplitude (∼20 % to 50 %) and mean ratios (∼15 %), supporting the sensitivity of daily metrics to interpreted changes in seasonal groundwater contributions to streamflow. During observational periods (i.e., April through October 2021 and 2022), significant differences (p < 0.01) between tributary and main-stem air–water metrics occurred when base-flow contributions were highest (∼0.93 vs. ∼ 0.68), as sites lower in the network had daily temperature metrics dominated by stream channel thermal inertia, rather than local groundwater connectivity, showing enhanced air–water diel signal coupling during warmer, drier periods. Divergent air temperature coupling across the network was interpreted as being driven by distance from local groundwater source zones, additional lateral groundwater inflows do not contribute a meaningful fraction to channel discharge lower in the network. Given the growing footprint of stream temperature observations, diel air–water temperature signals can provide distributed metrics sensitive to upstream groundwater discharge. Consequently, these metrics can support ongoing efforts by resource managers and researchers seeking to forecast the resilience of cold-water habitat to climate warming and changing precipitation regimes in mountain headwater streams.

New York, Virginia

Shallow hydrogeologic framework of the Tully Valley mudboil area, Onondaga County, New York

Mudboils have been documented in the Tully Valley in southern Onondaga County, New York, since the late 1890s. Sediment-laden water from the mudboils flows into Onondaga Creek, which empties into Onondaga Lake at Syracuse 15 miles to the north. Turbidity from the mudboils has degraded the water quality of Onondaga Creek despite a series of mitigation efforts that began in the early 1990s. Turbidity mitigation actions presently (2025) being considered include creek relocation and offline sediment settling. In support of these proposed actions during 2021–23, the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, U.S. Environmental Protection Agency, Onondaga Nation, Onondaga Environmental Institute, and Central New York Regional Planning and Development Board, collected and analyzed geologic, hydrologic, geophysical, and geotechnical data to characterize the shallow hydrogeology along four proposed creek-relocation paths and in the proposed offline settling basin area. The investigation indicated that the four proposed creek-relocation paths, two east of Onondaga Creek and two west of Onondaga Creek, are underlain by sediments including muck, alluvium, mudboil deposits, alluvial-fan sand and gravel, and lacustrine fines. The proposed excavations would penetrate partially to fully saturated conditions: generally, the water table is shallow near the creek and deep on the alluvial fans. The shallowest excavation, about 5 feet below land surface, would be near the creek and primarily in alluvium, and the deepest excavation, as much as 30 feet below land surface, would be in the alluvial-fan deposits. Brackish waters would be penetrated by proposed channel excavations on the eastern side of Onondaga Creek in an area downgradient from a potentially leaking historical salt-exploration borehole and near the main mudboil area. Excavation in these areas likely would provide a continuous source of brackish groundwater to the relocated creek. Proposed channel excavations of muck, soft to very soft lacustrine fines, and mudboil-type sediments in mudboil and suspected mudboil areas would pose an excavation and slope stability challenge and would have the greatest potential to create new mudboils. Proposed channel excavations below the water table on the Rattlesnake Gulf and Rainbow Creek alluvial fans would intercept groundwater and make the constructed streambank susceptible to seepage-induced slope instability. The substantial water-level fluctuation in the sediments of both alluvial fans would aggravate the stability condition. In addition, excavation on the Rattlesnake Gulf alluvial fan would have the potential to affect water-supply springs at the toe of the fan. The proposed offline settling basin area is in the northern part of the Rattlesnake Gulf alluvial fan. Natural and man-made diversions of Rattlesnake Gulf have resulted in saturated conditions in the general area of the proposed basin. The proposed offline settling basin would be excavated in, and berms would be constructed on, alluvial-fan deposits and lacustrine fines. In the proposed basin area, the alluvial deposits overlying the lacustrine fines are less than 10 feet thick. Excavation, berm construction, and loading of the saturated, soft to very soft lacustrine fines may be problematic and require soil strengthening.

New York

Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19

The Puget Sound basin encompasses the 13,700-square-mile area that drains to the Puget Sound and the adjacent marine waters of Washington State. Well more than 4 million people live within the basin, with numbers continuing to increase, who rely on the basin’s natural resources including groundwater. The Puget Sound Partnership was created by a Washington State statute to implement a science-based recovery of the Puget Sound to help address impacts to these resources. As part of the recovery, the partnership developed the Puget Sound Vital Signs as measures of ecosystem health that guide the assessment of progress toward Puget Sound recovery goals. The Puget Sound Partnership Leadership Council adopted a Drinking Water Vital Sign associated with human health and quality of life, recognizing certain indicators as integral to the sustainability of Puget Sound recovery efforts. One such Vital Sign indicator was the vulnerability of groundwater throughout the aquifers of the Puget Sound basin to elevated nitrate concentrations as defined by the probability of exceeding 2 milligrams/liter (mg/L) at a specific location and well depth. The U.S. Geological Survey (USGS) led the effort to characterize groundwater vulnerability. For this study, groundwater vulnerability refers to a probability with which a contaminant applied at or near the land surface can migrate to the aquifer of interest for a given set of land-use practices. Nitrate concentration data were selected for evaluation because elevated nitrate concentrations are typically caused by anthropogenic activities and have been associated with deleterious impacts on human health. To identify groundwater vulnerability to elevated nitrate concentrations, logistic regression was used to relate anthropogenic (human associated) and natural variables to the occurrence of elevated nitrate concentrations in untreated groundwater from large public water supply system wells found within the Washington State Department of Health Sentry database. Variables that were analyzed included well depth, soil hydraulic conductivity, precipitation, population density, fertilizer application amounts, and land-use types. Statistically significant models that predicted the probabilities of groundwater nitrate concentrations greater than 2 mg/L based on the predictor variables were created for the time periods 2000–04, 2005–09, 2010–14, and 2015–19. For all time periods, well depth and a measure of the abundance of urban and agricultural land over or near the well consistently helped explain the vulnerability of the well to elevated nitrate concentrations defined as a probability of exceeding 2 mg/L of nitrate. Precipitation and (or) soil hydraulic conductivity were also important predictor variables in the models. The models for each time period were used to create maps of groundwater vulnerability at 150- and 300-foot depths throughout the Puget Sound basin. As expected, the most vulnerable locations were associated with shallower well depths and increased agriculture and urban land cover. Across all four time periods, groundwater vulnerability throughout the Puget Sound was low, with probabilities of exceeding 2 mg/L concentrations of nitrate at depths at 150 and 300 feet typically less than 50 percent. Results also found a slight decrease in probabilities of elevated nitrate concentrations throughout the basin over time. More specifically, additional statistical tests found that groundwater with probabilities of less than about 60 percent declined from 2000 to 2019 and represented more than 75 percent of the modeled Puget Sound basin aquifer. Wells with greater than 60 percent probability increased over the same time period but represented only about 25 percent of the aquifer. The maps and statistical analysis presented in the study provide valuable and informative evaluation of the vulnerability of groundwater in the Puget Sound basin to elevated nitrate concentrations. The probability maps do not represent measured nitrate concentrations in groundwater, but rather they present the probability that nitrate concentrations exceed 2 mg/L. The models and predictions from this study are a viable indicator for the Puget Sound Partnership’s Healthy Human Population—Drinking Water Vital Sign. The logistic regression modeling approach presented here benefits water managers by allowing them to assess temporal trends in a range of probabilities, explore vulnerability changes as new regional land cover and anthropogenic data are generated, and distinguish vulnerabilities at different depths within the aquifer.

Washington