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USGS2025

Summary of selenium in the lower Gunnison River Basin, Colorado—Information and data gaps

The Cretaceous Mancos Shale is a geologic source of selenium in the lower Gunnison River Basin. Natural weathering processes and human activity mobilize selenium from the Mancos Shale and derived materials, and surface water, groundwater, and sediment all affect the transport of selenium from source areas to receiving streams and biota. Selenium accumulates through the aquatic food chain, and its toxic effects can result in invertebrate mortality and mortality, decreased reproduction, and deformities to fish and birds. The Bureau of Reclamation, in cooperation with the State of Colorado and Gunnison River Basin water users, is implementing a Selenium Management Program to reduce selenium concentrations in the lower Gunnison River Basin of Colorado. Goals of the Selenium Management Program are to (1) achieve compliance with the State of Colorado chronic aquatic-life standard for dissolved selenium (4.6 micrograms per liter) in the Gunnison River near Grand Junction, Colorado; (2) sufficiently improve water-quality conditions to assist in the recovery of endangered species in the Gunnison and Colorado Rivers by reducing selenium concentrations; and (3) support continued water uses in the basin. Many previous studies have contributed to the understanding of selenium in the environment; however, monitoring and research data gaps exist in the lower Gunnison River Basin. The purpose of this report is to summarize information regarding selenium in the lower Gunnison River Basin and describe strategies for scientific research and monitoring to potentially improve understanding of selenium sources; processes affecting the mobilization, transport, and fate of selenium; and the effects of selenium-mitigation projects in the lower Gunnison River Basin. Monitoring and research data gaps discussed in this report include geologic mapping and geochemical source characterization, long-term and ongoing monitoring of the surface-water and groundwater networks, developing and refining statistical models, characterizing selenium on suspended sediment, modeling selenium in the food web, evaluating best management practices, and more.

Colorado↗
USGS2026

Recent scientific contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary

Introduction The San Francisco Bay and Sacramento–San Joaquin Delta Estuary (hereafter, Bay-Delta) is the largest estuary on the West Coast of the United States. The Bay-Delta covers more than 1,600 square miles and drains a watershed of more than 75,000 square miles, which is greater than 40 percent of California. The region surrounding the Bay-Delta is home to about 10 million people, and its habitats (fig. 1) support more than 800 plant and animal species. The waterways of the Bay-Delta are the central hub of California’s extensive freshwater delivery system, supplying water to more than 27 million Californians and 4 million acres of farmland in the Central Valley. The U.S. Geological Survey (USGS) is the primary science agency of the U.S. Department of the Interior, providing a broad range of Earth, water, biological, and mapping data and expertise to inform natural resource management across the country. This fact sheet focuses on research conducted by the USGS in the Bay-Delta region, mostly within the past 5 years. The fact sheet is organized across five major themes: water flow and water quality, fish and wildlife, wetland restoration, invasive species, and hazards. In each of these areas, the USGS works closely with Federal, State, and local agencies; academia; and non-governmental organizations to provide objective, evidence-based science. The data and knowledge gained from USGS research and monitoring are publicly available and are routinely used by agencies, including the U.S. Bureau of Reclamation, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service, California Department of Water Resources, California Department of Fish and Wildlife, California State Water Resources Control Board, Delta Stewardship Council, and many additional organizations and stakeholders to inform management of the Bay-Delta region and its resources.

California↗
USGS2025

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

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

Wisconsin↗
USGS2026

The value of electronic tagging and tracking studies for understanding fish–hypoxia interactions

Objective Hypoxia (i.e., low dissolved oxygen availability) is a natural phenomenon but can also be induced by human activities (e.g., nutrient enrichment from runoff). Given that dissolved oxygen is essential for aquatic life, periods of hypoxia tend to have negative consequences (e.g., sublethal disturbances, mortality) for most fishes. Extensive laboratory research has documented hypoxia thresholds and physiological and behavioral outcomes for a variety of freshwater and marine fishes and there is also an extensive body of fieldwork assessing population-level responses (e.g., survival, distribution). Yet, studying how individual fish respond to hypoxia in the wild has proved challenging; electronic tagging and tracking tools (e.g., biotelemetry, biologging) have made it easier to study individual responses to hypoxia and complement other tools like hydroacoustics that tend to focus on population-level responses. Methods We review what has been learned from contemporary studies that employ electronic tagging and tracking tools to understand how fish respond to hypoxia in the wild. Topics explored include identifying and validating hypoxia thresholds, habitat compression, connectivity, mortality, physiological and bioenergetic consequences, and extreme weather conditions. We also consider what we have learned about evaluating various management plans for hypoxia and reflect on how electronic tags have also been used in aquaculture systems and in hybrid studies that combine laboratory and field research. We highlight fishes in Lake Erie as a research narrative to demonstrate how electronic tagging and tracking have markedly improved our understanding of a longstanding hypoxia issue. Results Our synthesis revealed that electronic tagging and tracking have provided critical information on how fish respond to hypoxia in the field, revealing complex trade-offs and compensatory mechanisms as well as cryptic hypoxia-induced mortality. Beyond just illuminating space use and mortality, tags equipped with various sensors are revealing how fish deal with hypoxia in real time in terms of physiology, bioenergetics, and behavior. Conclusions As electronic tagging and tracking methods experience further innovation and are increasingly applied to understand the effects of hypoxia on fish, we expect more unanticipated findings about the effects of hypoxia on fish in all aquatic ecosystems, which will strengthen our ability to manage and mitigate hypoxia. Combining tools and approaches (e.g., lab and field) is perhaps the best way to generate comprehensive understanding.

Transactions of the American Fisheries Society↗
USGS2026

Simulated ground motion dataset in the Azores Plateau, Portugal, on rock and soil sites

Building on a previously developed bedrock dataset, this study extends the Azores Plateau ground motion simulations to include soil-amplified records and introduces a comprehensive validation framework. Soil amplification is modeled using one-dimensional soil profiles. A stochastic source-based approach is employed to generate the dataset, incorporating randomization of input-model parameters to account for the aleatory uncertainty in seismic activity. The accuracy of the dataset is verified through a comprehensive validation framework, showing that the randomization effectively captures variance and inter-period correlation observed in records. This work provides a robust dataset for advancing seismic hazard and risk assessment in the Azores Plateau.

central and eastern Azores islands↗
USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗
USGS2025

Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States

Historically, Myotis septentrionalis (Northern Long eared Bat) was among the most common forest-interior species in North America. Largely due to high mortality from white-nose syndrome, this species has experienced severe population declines across its range. To create an updated species distribution map representing summer occupancy probabilities from 2017 to 2022, we integrated stationary acoustic data with live-capture data from the database of the North American Bat Monitoring Program into a multi-scale, multi-method occupancy modeling framework. Our results provide data-driven predictions with quantified uncertainty for summer occupancy probabilities for Northern Long-eared Bats at 2 spatial scales across the range of the species, while also accounting for inherent observation biases (e.g., imperfect detection).

Journal of North American Bat Research↗
USGS2026

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal↗
USGS2026

Statewide surficial geologic map of Nebraska underscores Quaternary landscape evolution from the High Plains to the Central Lowland

Surficial geologic mapping in Nebraska has been conducted primarily at the 1:24,000 scale since the mid-1990s, although there have also been limited efforts to map generalized Quaternary and surficial geology within the state and the region. We compiled and evaluated disparate maps (1:24,000–1:1,000,000) and datasets—including geologic, soil and soil parent material, and geomorphic maps as well as LiDAR derivatives—to produce a single 1:500,000 scale surficial geologic map of Nebraska that is the first of its kind. This new map provides a coarse-scale surficial geologic map that will be incorporated into a nationwide U.S. Geological Survey Quaternary geologic map. It also reflects the variation and uniqueness of physical landscapes in the state, where the Great Plains and Central Lowland physiographic provinces meet, further developing a richer interdisciplinary understanding of regional geomorphology in the heart of North America.

Nebraska↗
USGS2024

Case definitions for wildlife diseases

Welcome to the first manual of “Case Definitions for Wildlife Diseases,” a “living” electronic publication. The plan is to add and update this manual’s case definitions periodically as warranted; thus, this manual will never be completed, and readers should download the latest versions of specific chapters (that is, definitions) when available. Constructive suggestions from readers are welcome and will help guide adjustments as this project progresses. The purpose of this manual is to provide case definitions for selected diseases of importance to wildlife in Canada and the United States. Case definitions provide standard sets of criteria for classifying the degree of certainty of a particular diagnosis and help improve surveillance data quality and comparability. Better data and standardization allow for improved data sharing, which increases geographic and species surveillance coverage and permits more robust analyses. The definitions included in this manual have been developed by veterinary pathologists, epidemiologists, and wildlife biologists primarily from the U.S. Geological Survey National Wildlife Health Center (NWHC) and Canadian Wildlife Health Cooperative (CWHC). Pathologists from each organization reviewed and finalized the definitions. Each case definition has been peer reviewed by two scientific experts before publication. This manual begins with the case definition template. This generic template includes four sections: “Individual, Place, and Time Criteria for Diagnosis and Testing,” “Field Criteria for Diagnosis,” “Laboratory Criteria for Diagnosis,” and “Epidemiological Linkage Criteria for Diagnosis” and can be used to guide development of new case definitions. Information in each section is then combined to provide an overall case classification. Disease diagnoses are classified as “Confirmed,” “Presumptive,” or “Suspected;” and evidence of a pathogen or toxin is classified as “Exposed” or “Present/Detected.” Each subsequent chapter is then a case definition for a specific disease of wildlife, and infectious and non-infectious diseases are included.

Techniques and Methods↗
USGS2025

Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole

We use a high-resolution digital elevation model and a numerical thermal model to produce a variety of inputs for a water-ice prospectivity model for the Volatiles Investigating Polar Exploration Rover (VIPER) landing site. These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.

Planetary Science Journal↗
USGS2026

Synthesizing a twelve-year sediment trap time series of planktic foraminiferal flux in the Gulf of America (Mexico)

Sediment trap time series provide powerful frameworks for testing hypotheses about planktic foraminiferal assemblage composition, seasonality, and geochemical responses to environmental variability, all of which are central to improving paleoceanographic reconstructions. We present high resolution foraminiferal assemblage data from a long-running sediment trap (2008–2020) in the northern Gulf of America (Mexico). This study summarizes the species composition, seasonality, and size distribution of the fifteen most abundant species of planktic foraminifera, which account for 98% of total flux. Foraminiferal flux peaks in winter and reaches a minimum in summer, following the seasonal pattern of primary production in the northern Gulf. Winter assemblages are dominated by non-spinose taxa, whereas spinose taxa prevail during summer. Across nearly all species, average monthly test size covaries with temperature, independent of seasonal flux trends. Notably, Trilobatus sacculifer and Neogloboquadrina dutertrei show a significant decline in relative abundance and flux during 2017–2020, nearly disappearing from the assemblage.

Journal of Foraminiferal Research↗
USGS2025

National population exposure and evacuation potential in the United States to earthquake-generated tsunami threats

Previous efforts to characterize tsunami threats to people have focused primarily on individual scenarios in specific areas but have not recognized multiple scenarios across an entire country. This study addresses this gap by quantifying population exposure and evacuation potential in the United States to 102 earthquake-related, tsunami-hazard zones, including 92 local scenarios, 8 distant scenarios, and 2 probabilistic products. Geospatial path-distance modeling quantified evacuation potential and the influence of departure delays. We focused on residents to support other national, multi-hazard risk analyses. Millions of residents are in distant-tsunami zones, and hundreds of thousands of residents are in local-tsunami zones. In 41 scenarios, there is at least one resident that may have insufficient time to evacuate before wave arrival. Tens of thousands of residents may have insufficient time to evacuate from local tsunamis that impact the U.S. Pacific Northwest or Puerto Rican coastlines. The largest improvements in evacuation potential may come from reducing departure delays in some areas but may involve vertical-evacuation structures or changing land use in other areas.

International Journal of Disaster Risk Reduction↗
USGS2024

Self-guided decision support groundwater modelling with Python

The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.

Journal of Open Source Education↗
USGS2025

Using probability difference to compare streamflow information of alternatives for efficient operation of monitoring networks

Efficient operation of streamflow monitoring networks requires investments in technology and labor that provide the greatest benefits from available resources. Economic analyses comparing the costs and benefits from different types of alternatives for monitoring have not been practical to implement. Streamflow information provides a generic measure of benefits that can be incorporated into operational decisions as an objective for monitoring networks. A methodology for comparing how accuracy, monitoring period, and monitoring instead of modeling affects streamflow information is developed from information-theoretic approaches for network design but contributes three novel features: (1) a probability-difference model for conditional probability of monotonically paired variables, (2) explicit discounting of unverified information that may exceed the accuracy of streamflow records, and (3) run analysis to account for non-stationarity in streamflow probabilities. Application of the methodology to the U.S. Geological Survey streamflow monitoring network indicates the value of monitoring period to reduce the uncertainty of streamflow probabilities and, thus, increase streamflow information. The methodology has important limitations, particularly for sites with non-perennial streamflow, but demonstrates that probability difference could be used to evaluate operational alternatives to increase the efficiency of monitoring networks.

PLOS Water↗
USGS2021

Virginia and Landsat

From the shores of Jamestown and spreading north, south, and west, the lands that became the State of Virginia were some of the first in North America top experience rapid landscape change from European settlement. Imagery and data from the USGS Landsat series of satellites offer an unparalleled resource for the study, understanding, and preservation of Virginia’s land and water resources. From monitoring the health of water bodies to managing invasive species to planning for a range of climate change effects, the USGS National Land Imaging Program’s stewardship and public delivery of Landsat data have benefitted Virginians in myriad ways.

Virginia↗